Download Investigator/Program Director (Last, First, Middle): Nick, Teresa A.

Principal Investigator/Program Director (Last, First, Middle):
Nick, Teresa A.
1. The Candidate
A. CANDIDATE’S BACKGROUND
My research focuses on how neurons create behavior and how behavioral experience alters these
neurons and their interconnections. I prepared for this integrative approach to neural plasticity throughout
my career. Since there was no undergraduate neuroscience major at the University of Texas at Austin
when I attended, I created my own. I obtained a BA in Psychology and a BS in Zoology in three years,
graduating with high honors in 1989. As an undergraduate with Dr. Abram Amsel, I studied the role of the
hippocampus in single-patterned alternation, a simple operant task (Lobaugh et al., 1989). I realized that, to
understand it, the brain must be studied in an integrative manner with an array of tools that offer insights
from ion channel gating to circuit dynamics. I became intensely interested in the investigation of plasticity
at all levels from molecules to behavior in the powerful Aplysia model.
I pursued my interest in neural plasticity in Aplysia with Drs. Thomas Carew and Leonard Kaczmarek at
Yale University, graduating with a Ph.D. in 1996. I utilized multiple electrophysiological methods, including
extracellular, sharp micro-electrode intracellular, and whole-cell patch recording. I learned that the
excitability of a group of neuroendocrine neurons (bag cell neurons) that control reproduction in Aplysia is
tightly regulated during development, with the density of some ion currents up-regulated (e.g., potassium Acurrent and a calcium current induced by protein kinase C) and others down-regulated (e.g., delayedrectifier potassium current) (Nick et al., 1996a; White et al., 1998). The overall effect of the modulation of
ion currents was to decrease repetitive firing in neurons of juveniles, relative to adults. Since natural release
of the egg-laying hormone required repetitive firing, and since the juvenile neurons could release egg-laying
hormone when artificially stimulated to do so and the young animals could respond to the hormone with
appropriate behaviors, I concluded that the modulation of expression of defined ion channels controlled the
development of egg-laying behaviors in Aplysia (Nick et al., 1996b). In a side project, I found that a factor
found in haemolymph could modulate ion current expression in the bag cell neurons and that brain-derived
neurotrophic factor could mimic these effects. However, because Aplysia does not express vertebrate
neurotrophins, the project was difficult to pursue without extensive groundwork on Aplysia growth factors.
This led me to pursue extrinsic modulation of neuronal excitability in a vertebrate preparation, the Xenopus
neuromuscular junction (NMJ).
In the laboratory of Dr. Angeles Ribera at the University of Colorado Health Sciences Center, I utilized a
variety of molecular techniques, including gene cloning and sequencing, to study potassium channel
expression. To examine extrinsic modulation of excitability, I cultured embryonic Xenopus NMJs in defined
medium. Using whole-cell and outside-out macropatch recording, I found that myocytes exert an extrinsic
modulatory influence on the motor neurons that innervate them (Nick and Ribera, 2000). When synaptic
communication was blocked with an acetylcholine antagonist, α-bungarotoxin, the motor neurons developed
differently than if they were allowed to synaptically communicate with muscle. The Trk neurotrophin
receptor inhibitor K252a mimicked these effects and neurotrophin-3 ameliorated a subset of them. While I
found this line of research engaging, I wanted to study cells and synapses “in context”, in a functioning
circuit with a clear role in behavior. About this time, several groups published findings that suggested that
the birdsong system would be the perfect model for my research aspirations (Dave et al., 1998; Schmidt and
Perkel, 1998; Schmidt and Konishi, 1998; Mooney, 2000).
In Dr. Masakazu Konishi’s laboratory at the California Institute of Technology, I used chronic population
recordings to examine state-dependent and developmental modulation of activity in the song nucleus HVC
(this acronym is the proper name). I found that playback of the Bird’s Own Song (BOS) activates the adult
HVC more than any other auditory stimulus during slow-wave sleep (Nick and Konishi, 2001). Because the
adult response was state-dependent and because all previous investigations of HVC development had been
executed in anesthetized juveniles, I reasoned that the examination of juvenile responses across behavioral
states might reveal a neural signal that shapes behavior during song development. Konishi (1965) showed
that young birds in the process of song learning (1) compare auditory feedback and a memory of a learned
tutor song “template” and (2) use the result of this comparison to shape their behavior. I sought a neural
signal in the song control system that indicated matching between an auditory stimulus and the learned tutor
song. Indeed, Konishi and I found the instructive signal in the awake juvenile (Nick and Konishi, 2005a).
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Principal Investigator/Program Director (Last, First, Middle):
Nick, Teresa A.
I was attracted to the Department of Neuroscience and Center for Neurobehavioral Development at the
University of Minnesota due to the enormous research breadth that would facilitate my integrative approach.
During my short time here, I have already utilized the expert advice of numerous faculty, including Drs.
David Redish (multi-electrode recording) and Glenn Giesler (antidromic techniques). I am now routinely
recording from awake, behaving juvenile zebra finches using multi-electrode techniques. I have, for the first
time, combined antidromic identification techniques and multi-electrode recording such that single neurons
can be identified in an ensemble recording (see Preliminary Data). I have found that the temporal
relationships between brain activity and behavior change during vocal learning. I have set up three chronic
multi-electrode recording stations, a brain slice station, and an in vivo cellular recording station. An expert in
chronic recording in birds, Dr. Naoya Aoki, will arrive in April 2006 to begin a postdoctoral fellowship in my
laboratory that will focus on Aims 2 and 4 of this proposal. I will use my grant from The John Merck Fund for
Dr. Aoki’s salary and fringe benefits. I am well trained and well equipped to pursue the mechanisms
underlying vocal learning. I have laid the methodological foundation over the last two years to complete all
Aims. The faculty and institution are committed to my success. Achieving my goals will require that I am
able to commit a significant amount of time to this project, which is why I am applying for a K02 award.
B. CAREER GOALS AND OBJECTIVES: SCIENTIFIC BIOGRAPHY
The primary function of the nervous system is to enable adaptation to the environment. Behavioral
adaptation ultimately results from cellular plasticity. I have spent my career studying neural plasticity, from
proteins to behavior. Vocal learning, considered by many laypersons to be uniquely human, represents an
especially intriguing form of neural plasticity that involves the highest-order brain areas, which are least
understood. My career goal is to break the neural code that underlies vocal learning and to understand,
down to the ion channel, how vocal plasticity is orchestrated.
As an undergraduate, I realized that the brain is an integrative organ. Information acquired across time
through the organism’s interaction with the environment (behavior) is stored at the cellular or subcellular
level. Systems and local circuits intervene both during storage and retrieval. To understand the entire
process from behavior to molecules and back again, the entire process must be studied in a single system.
Much understanding has been achieved with simple systems, such as the Aplysia gill withdrawal reflex
and the crustacean stomatogastric ganglion. To learn the power and approach of simple systems, I worked
with Drs. Thomas Carew and Leonard Kaczmarek on Aplysia at Yale University. I found the development of
reproductive behaviors is ultimately controlled by the expression of ion channels in a population of
neuroendocrine cells. While I greatly appreciate the contribution of such systems to our understanding of
basic principles of neural function, I found that my own career path led towards the vertebrates, due to their
kinship to humans and their greater potential for revealing both higher cognitive processes and clinicallyrelevant results. My time working with Aplysia gave me a systematic and rational approach for taking apart
and understanding each piece of a behaving system.
The next stage of my training was to investigate the effects of extrinsic modulators on intrinsic
excitability. In Xenopus nerve-muscle co-cultures, I found that communication with the synaptic target was
critical for normal development of motor neuron excitability. This experience emphasized to me that the
developing nervous system is a dynamic interacting network that is constantly shaped by extrinsic
influences, as well as intrinsic genetic programs.
I further pursued extrinsic shaping of the nervous system by moving to the songbird vocal learning
model. I was able to record from the same animal and recording site for extremely long time periods using
chronic multi-unit recording methods. I monitored brain activity across the developmental period during
which a zebra finch shapes his vocalization to match a learned tutor song. Konishi and I reported several
major discoveries (Nick and Konishi, 2005a, b), including: (1) the song nucleus HVC (this acronym is the
proper name) receives a tutor song template-matching signal during waking within a restricted period of
development; (2) the nucleus HVC responds preferentially to the Bird’s Own Song during sleep throughout
development, even when the song is little more than repeated begging calls; and (3) ongoing HVC activity is
greater in juveniles than in adults. I was able to obtain these data because I recorded from awake,
behaving finches, instead of anesthetized finches, in which all other developmental studies had been done.
No one other than me has successfully executed longitudinal studies in the developing zebra finch song
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Principal Investigator/Program Director (Last, First, Middle):
Nick, Teresa A.
system because of the difficulty in maintaining recordings over several weeks. These findings laid the
foundation for my current work.
Although rigorously tested, my findings with Konishi remain controversial due to their conflicts with
established interpretations of a large body of data. Specifically, many in the birdsong field believe that the
tutor song template and all sites of neural plasticity lie downstream (efferent) of HVC, whereas our data
indicate that the template lies upstream (afferent) of HVC. The Anterior Forebrain Pathway (AFP;
downstream of HVC) clearly has a role in vocal plasticity (Bottjer et al., 1984; Brainard and Doupe, 2000). A
large number of birdsong physiologists have interpreted these data to mean that the AFP (1) stores the tutor
song memory (serves as the template store; see Troyer and Doupe, 2000b); (2) compares auditory
feedback to the tutor song memory (serves as the comparator); and (3) changes behavior by shaping
synapses between HVC and the premotor nucleus Robustus Arcopallialis (see Hahnloser et al, 2002).
However, how can the AFP be the template store and the comparator if HVC, which is upstream of the AFP,
receives a template-matching signal (Nick and Konishi, 2005a)? Although loops in the song system may
provide a route back to HVC from the AFP, the reigning hypothesis (i.e., the AFP contains the template) is
not the most parsimonious. Data from immediate early gene studies also suggest that the template store
and comparator are upstream of HVC (Mello et al., 1992; Mello and Clayton, 1994; Stripling et al., 2001).
Other data suggest that the AFP may induce variability in song behavior (Kao et al., 2005; Olveczky et al.,
2005). Because finches shape their songs through trial-and-error, behavioral variability is as critical for song
learning as a tutor song template. Thus, consistent with our data, the AFP has an important role in song
learning that has little to do with the template.
Although accumulating data support our finding that HVC receives a template-matching signal during
development, the birdsong field has not fully rejected the hypothesis that song system neural plasticity
occurs downstream of HVC. This skepticism, though reasonable, raises the bar for all work that will be
published on this subject. In response to constructive criticism, I have begun to record from single neurons
in the awake, behaving juvenile HVC. In addition, I have combined multi-electrode and antidromic
identification techniques for the first time in any system to obtain the identity of single neurons that carry the
instructive signal. The K02 award would allow me to continue these pivotal, but very difficult, studies.
Without it, I will be forced to focus on easier and lower profile experiments that I will be able to publish in a
shorter timeframe.
During my career, I have learned a wide variety of approaches to neural plasticity. I have brought this
breadth of experience to bear on the problem of vocal learning. Here I propose to extend the work
described in my R01 application and use chronic recording from awake, behaving finches during vocal
learning to (1) precisely characterize the instructive template-matching signal; (2) examine the effect of
perturbation of auditory feedback during singing (using two distinct perturbations); (3) resolve the destination
of the signal; and (4) systematically analyze brain activity-behavior relationships during vocal learning.
Relative to the R01, Aim 2 is expanded and Aim 4 is new. I am poised to execute these experiments
because I: (1) have the necessary expertise; (2) have developed the necessary methods; (3) have already
trained laboratory personnel in the technically difficult methods; and (4) have hired an electrophysiologist
with specific skills in chronic recording of awake, behaving birds, Dr. Naoya Aoki. This work will lead to a
better understanding of vocal learning, sensorimotor integration, and behavioral critical periods.
C. CAREER DEVELOPMENT/TRAINING ACTIVITIES DURING AWARD PERIOD
My research goal is to obtain an integrated understanding of vocal learning. I was awarded an R01
grant from the National Institute of Deafness and Other Communication Disorders to study the neural
mechanisms of song learning in the zebra finch songbird. Toward this end, I have already done most of the
necessary methodological groundwork, set up a productive finch breeding colony, trained my laboratory
personnel in very sophisticated and difficult methods, and hired a postdoctoral fellow skilled in chronic
electrophysiological recording of awake behaving birds. However, the R01 grant was cut both in terms of
modules (2) and years (from 5 to 3 years). To avoid a gap in funding, I will need to apply for renewal of the
grant in only 2 years. Renewal in this short timeframe will be difficult for four reasons: (1) I am recording (i)
from the song nucleus HVC in awake juveniles and (ii) over several weeks from developing juveniles,
neither of which has been achieved by anyone else in my field; (2) I am applying and optimizing multi-
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Principal Investigator/Program Director (Last, First, Middle):
Nick, Teresa A.
electrode and spike sorting methods to the song system for the first time; (3) I am combining multi-electrode
and antidromic identification methods for the first time in any system; and (4) Because of the novelty of my
approach, I have discovered that the reigning hypothesis of birdsong learning (i.e., the Anterior Forebrain
Pathway contains the template) is not the most parsimonious. Future experiments are likely to further
undermine this hypothesis, which, as should be expected, leads my colleagues in birdsong to hold my work
to a very high standard. Thus, I believe that my situation demonstrates the need for a period of intensive
research focus as a means of enhancing my research career. The Independent Scientist Award (K02)
would assist me in establishing my laboratory and reputation in the vocal learning field in several ways:
1. The K02 would allow more time to hone my new skills in multi-electrode recording and further optimize
the application of spike sorting analysis to the song nucleus HVC with assistance from my colleague, David
Redish, and to maximize the reliability of my method that combines multi-electrode, spike sorting and
antidromic techniques. These methods are very difficult and thus require significant time to develop,
implement, optimize, and train.
2. The K02 would enable me to apply the sophisticated methods that I have optimized for the song system
over the last two years to test specific hypotheses regarding the mechanisms of vocal learning. Although
most of the groundwork on the methodology has already been done, I will need a sustained period of
concentrated research time to execute the proposed studies and provide concrete results. My time for
active research in the laboratory would be protected by the K02. In my department, teaching and service
are expected to increase to ~30% time during the first four years as an assistant professor. Should I receive
this award, I could limit my teaching and service to 10% and conduct research for the other 90% of my time.
3. It would decrease the negative effects of a potential gap in funding. Without this award, my department
would require that I make up for lost salary dollars by increased teaching and service over and above the
30% expected without funding, which would decrease my chances of later renewal.
4. In addition to bench work, the protected time would enable enhancement of my career potential by
enabling increased collaboration with colleagues both at the University of Minnesota and elsewhere,
presentation of my work at more scientific meetings, and visits to colleagues and collaborators at other
institutions, such a Dr. Stephanie White, who will show me an anesthesia technique that may decrease my
juvenile mortality rate.
D. TRAINING IN THE RESPONSIBLE CONDUCT OF RESEARCH
The University of Minnesota has a Responsible Conduct of Research program that facilitates training in
scientific integrity, policies concerning the treatment of research subjects, and bioethics. As a new faculty, I
was required to attend two helpful workshops on the Responsible Conduct of Research. Throughout the
training period, I will attend at least one training session per year. My postdoctoral and graduate trainees
will be required to attend two workshops on Responsible Conduct of Research. In addition, all of my
trainees are aware that I have a zero-tolerance policy for mistreatment of animals and falsification of data.
In addition to research, I expect to participate in the following activities:
1. Teaching (5%) I expect to teach in the Developmental Neuroscience module of the summer Itasca
laboratory course for incoming graduate students. This allows me to form close relationships with other
developmental faculty, with whom I routinely discuss details of my studies and receive feedback, and also
provides an excellent opportunity for recruiting graduate students, who may be drawn to participate in the
proposed research. I will also teach five lectures in the Behavioral Neuroscience course, which allows close
interaction with behavioral neuroscientists and keeps me at the forefront of the literature of closely related
fields, such as bat echolocation, which informs the proposed research.
2. Service (2%) I will serve on the Colloquium Committee of the Graduate Program in Neuroscience. This
provides an excellent opportunity to stay abreast of the wide array of neuroscience research occurring at the
University of Minnesota.
3. Continuing Education (3%) I will attend at least two seminars per week, which will keep me informed of
cutting-edge research both at my home institution and elsewhere. I will also attend journal clubs on
Computational Neuroscience, Developmental Neuroscience, and Neural Plasticity. I will attend meetings of
the Society for Neuroscience and the International Society for Neuroethology when they occur. I will take
“mini-sabbaticals” to learn key techniques, such as a new anesthesia technique from Dr. Stephanie White.
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Principal Investigator/Program Director (Last, First, Middle):
2. Statement by Consultant
Letters from Drs. David Redish and Stephanie White.
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Nick, Teresa A.
Principal Investigator/Program Director (Last, First, Middle):
Nick, Teresa A.
3. Environment and Institutional Commitment to Candidate
A. DESCRIPTION OF INSTITUTIONAL ENVIRONMENT
Dr. Teresa Nick proposes to unravel the mechanisms of vocal learning by taking an integrative
electrophysiological approach. The University of Minnesota has strengths at every stage of analysis that
she will pursue. We have a large Department with 33 faculty members and a substantial number share
Teresa’s research interests. She has already established a collaborative relationship with Dr. David Redish
who has developed several methods that are necessary for triode recording including the most widely used
software package for data analysis. David’s lab has a weekly Computational Journal Club that focuses on
neural coding, which is quite relevant to Teresa’s work. Teresa has already begun to identify neurons within
the song nucleus HVC using antidromic methods. Dr. Glenn Giesler has served as a consultant on these
studies. He has more than 30 years of experience using antidromic activation methods. The developmental
group within the Neuroscience Department, which includes Paul Letourneau, Steve McLoon, Lorene Lanier,
Yasushi Nakagawa, and Naoko Koyano, was actively involved in recruiting Teresa and has already provided
a great deal of feedback on her research and ideas. The developmental group is active and highly
engaged. They frequently come together, for example in their weekly journal club, to discuss ideas and
approaches to understanding the developing nervous system. Each of these investigators is available to
help Teresa with her research. The Center for Neurobehavioral Development, which includes Michael
Georgieff and Kathleen Thomas, is also greatly interested in Teresa’s continuing success and, reflecting this
interest, has given her full-member status in the Center. This group is actively involved in translational
research and provides a great pre-clinical resource.
Birdsong is a sensorimotor behavior, and we have strengths in both sensory perception and motor
control. There is a strong auditory neuroscience group that includes Mark Bee, Neal Viemeister, Bert
Schlauch, Peggy Nelson, Andrew Oxenham, and Lance Zirpel. Mark Bee has been meeting with Teresa
regarding her exploration of auditory feedback in the song system. Members of our large and renowned
motor group include: James Ashe, Martha Flanders, Apostolos Georgopoulos, John Soechting, and myself.
As Teresa begins to take aspects of her work to the cellular level, we have faculty to assist her there as
well, including Paul Mermelstein, Bob Miller, Eric Newman, Mark Thomas, and LiLian Yuan. Many of our
faculty our interested in neural plasticity and actively discuss new work in the Neural Plasticity Journal Club.
The Graduate Program in Neuroscience is an excellent resource. There is a weekly Neuroscience
Colloquium that showcases the work of faculty and students here at the University of Minnesota and a
Neuroscience Seminar Series that hosts neuroscientists from around the world. The President of the
University of Minnesota, Robert Bruinicks, has recently shown his enthusiasm for neuroscience at the
University by providing support for a Presidential Symposium on Neuroscience, which will occur in the Fall
of 2006 and feature twelve eminent neuroscientists. In recognition of the breadth of her understanding of
neuroscience, I appointed Teresa to chair the organizing committee for the Symposium. She has done an
outstanding job.
For her research, Teresa requires an aviary facility for an active breeding program. I arranged for a large
facility to set aside for the aviary prior to her arrival. As she has expanded her program, a second room has
been set up as a colonial breeding facility. The Research Animal Resources at the University has worked
closely with Teresa to ensure that she has an aviary producing healthy subjects at top capacity.
Teresa requires a large amount of computational resources for her work. She has recently received an
award from the Super Computing Institute at the University, which allows her to utilize a super computer to
process her multi-electrode data. Dr. Shuxia Zhang from the Institute has worked with Teresa to parallelize
her computer code such that it runs up to 8 times faster on the super computer. In recognition of the
required office space for her computers, I recently moved her to a larger office that is closer to the
colleagues with which that she actively collaborates, including the developmental group, David Redish, and
Glenn Giesler. We will continue to offer Teresa an environment that will facilitate and enhance her
research.
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Principal Investigator/Program Director (Last, First, Middle):
Nick, Teresa A.
B. INSTITUTIONAL COMMITMENT TO CANDIDATE’S RESEARCH CAREER DEVELOPMENT
The Department of Neuroscience at the University of Minnesota is delighted to enthusiastically support
the application of Dr. Teresa Nick for a KO2 award. We believe that she is a perfect candidate. She is
remarkably intelligent, dedicated and creative. She has had ideal training with several of the most prominent
leaders in the field (Drs. Thomas Carew, Leonard Kaczmarek, Angeles Ribera, and Masakazu Konishi) at
Yale, University of Colorado, and Cal Tech. She has been consistently productive, publishing exclusively in
top-flight journals. Teresa works in the important area of development of song in birds, the most powerful
animal model of development of speech in humans. We believe that Teresa will become a star in the field.
The Department has already invested substantially in Teresa’s career and will continue to do so. Teresa
arrived here in January of 2004 and was given a substantial start-up package and excellent lab space. She
has already been productive in her new laboratory and is about to submit her first manuscript. She received
support from the John Merck Scholars Foundation in 2005, which she will use for a postdoc salary, and
recently she was awarded an RO1.
As an Assistant Professor in the Department of Neuroscience, Teresa’s primary responsibility is to
establish an internationally respected research reputation and laboratory. She has already made several
major breakthroughs in her chosen field, which have initiated a reconsideration of established hypotheses
regarding the development of birdsong behavior and reinterpretation of a large amount of previously
acquired data. Because of the groundbreaking nature of her research, it has been consistently held to a
very high standard. Moreover, the techniques that she uses are cutting edge. She is the first to apply an
assortment of techniques to the birdsong system. This has greatly extended the publication time of her
work. While this is to be expected, it occurs at a critical juncture in her career. A K02 Independent Scientist
Award would enable continuation of her research during this vulnerable period.
In recognition of the K02 award, I would be able to reduce Teresa’s total teaching and administrative load
to 10%, allowing 90% time for research. The proposed limited teaching and administrative responsibilities
that I approve complement her research goals, creating potential for graduate student recruitment and
increasing interactions with key faculty. The K02 would also protect Teresa’s time for research in the
unlikely event that her R01 is not renewed. The Department will certainly help her financially if she is unable
to immediately renew her R01. Funds will be provided so that she can continue her work during any unfunded period. The Neuroscience Department, Medical School, and Graduate School each have programs
for bridge funding.
To further assist in Teresa’s career development, we are happy to support her attendance of at least two
scientific meetings per year and her efforts to take “mini-sabbaticals” to learn new, important techniques in
her field. We encourage our junior faculty to invite at least one speaker per year to our seminar series to
enhance their interaction with colleagues in their field.
In summary, I am committed to the continued career development of Teresa Nick as an independent
neuroscientist. She is an outstanding young faculty at a critical point in her career. She needs a period of
sustained and concentrated effort to execute her pivotal studies in vocal learning. The K02 would enhance
her potential and facilitate her ability to make significant contributions to our understanding of a key model of
speech.
________________________________________________ DATE:________________________________
Timothy Ebner, M.D., Ph.D.
Professor and Head
Department of Neuroscience
Visscher Chair of Physiology
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Principal Investigator/Program Director (Last, First, Middle):
Nick, Teresa A.
4. Research Plan
A. SPECIFIC AIMS
Songbirds and humans are rare among animals in that they possess specialized sensorimotor brain
areas dedicated to vocal learning and production (Doupe & Kuhl, 1999). The zebra finch songbird
acquires its song by first memorizing a model song from a tutor and then matching its own vocalizations
through auditory feedback to the memory trace of the tutor song, called the template (Konishi, 1965).
The Template Theory, based on behavioral data, requires that the auditory feedback/template
comparison sculpt the brain circuitry that drives singing. Yet, after 40 years, the key physiological
evidence is missing, namely that a neural representation of the tutor song affects singing behavior. In
recordings from waking juvenile finches, we recently showed that the premotor song nucleus HVC (this
acronym is the proper name) is selectively tuned to the tutor song in juveniles (Nick and Konishi,
2005a), which suggests that the template is located afferent to HVC. Yet, the most popular model
(Troyer and Doupe, 2000b) proposes that the template is located efferent to HVC. The proposed
research will clarify the relative location of the template, test the hypothesis that the neural tuning
observed in the HVC of young finches is an instructive template-matching signal, and begin to
illuminate the role of this neural tuning in song development. The long-term goals of this project are to
track and manipulate the putative matching signal through time and brain space, ultimately revealing
fundamental principles of brain processing, such as how sensation and memory shape motor activity
and behavior. Specific aims are:
1. Examine the precision of neural tuning of all HVC neurons in awake, unrestrained finches
during song development. Previous reports of HVC neural tuning to the tutor song relied on neural
population data (Nick and Konishi, 2005a). Recording single neurons will (1) reveal if all HVC neurons
or only a subset respond to tutor song and (2) enable a fine-grained analysis of stimulus selectivity in all
HVC neurons. Thus, this aim specifically assesses the auditory stimulus selectivity of single HVC
neurons during the template-matching phase of song development. Auditory tuning of individual HVC
neurons of awake unrestrained juvenile finches will be investigated with the techniques of song
playback, multi-electrode recording and song analysis. My hypothesis predicts that the magnitude of
the response of individual HVC neurons will be directly proportional to the degree of similarity between
the stimulus and the tutor song.
2. Determine the activity of tutor song selective neurons during singing. The Template Theory
predicts that a template-matching signal occurs during singing. This aim will focus on identifying the
putative matching signal during singing in developing finches with multi-electrode techniques.
Experiments consisting of a single recording session will: (1) use playback of auditory stimuli to identify
the tutor song selective neurons; (2) examine the activity of these specific neurons during singing; and
(3) perturb auditory feedback using two independent methods to test the hypothesis that the activity of
these neurons during singing depends on auditory signals. These experiments will test if auditory
feedback occurs during singing in HVC neurons that respond selectively to tutor song.
3. Resolve the destination of the putative matching signal. HVC contains three major subtypes of
neurons that can be identified by their projections: those that project to the basal ganglia, those that project
to the motor cortex analog, and interneurons. A corticothalamic-basal ganglia loop (the Anterior Forebrain
Pathway) has roles in song learning (Bottjer et al., 1984), suggesting that HVC neurons afferent to the basal
ganglia may be especially important in learning. This aim will identify which HVC subtype(s) carries the
putative matching signal and thus show where the signal is transmitted. Multi-electrode recording in awake
unrestrained juveniles, combined with antidromic techniques, will identify the neurons that respond
selectively to tutor song and the destination of the putative matching signal. My hypothesis predicts that
only neurons that project to the basal ganglia respond selectively to tutor song.
4. Test a specific mechanism through which the template-matching signal may shape behavior.
The problem of synaptic delays between motor command and sensory feedback poses severe constraints
on any sensorimotor system. Known cellular mechanisms of activity-dependent plasticity require close
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Principal Investigator/Program Director (Last, First, Middle):
Nick, Teresa A.
temporal association of action potentials in neurons that exhibit activity-dependent strengthening (i.e.,
neurons that fire together, wire together). Therefore, I propose a hypothesis that would enable temporal
overlap of motor command and sensory feedback: Higher order motor circuits (in HVC) that drive
vocalization are active longer relative to the vocalization in juveniles than adults, allowing sensory feedback
to shape synaptic connectivity via activity-dependent mechanisms. I will test this hypothesis by comparing
HVC neuronal population activity during song behavior across development. My hypothesis predicts that
HVC activity will outlast the vocalization in actively learning finches, but not in adults.
B. BACKGROUND AND SIGNIFICANCE
While the majority of children develop complex speech abilities by the age of four years with no formal
instruction, there are a large number of cases where speech is delayed or never acquired. Even when
conditions such as hearing loss were excluded, more than one million of the students in U.S. public school
special education classes were diagnosed with speech or language impairments (US Dept. Education,
(2002). Many of these children had communication disabilities such as autism. In fact, an estimated ten
percent of all Americans exhibit speech and language delay (Law et al., 2000). Unfortunately, these
problems persist in those with a history of language and speech impairment, as language performance
exhibits considerable stability over many years (Johnston et al., 1999). Appreciable movement towards
treatment and cure of these disorders will require an understanding of the fundamental biological principles
of vocal learning.
Potential animal models for the investigation of speech and language development are rare. No primate
other than Homo sapiens learns its vocalizations (Doupe and Kuhl, 1999). The other groups of mammals
that are vocal learners, cetaceans (whales and dolphins), elephants, and bats, are difficult to study
physiologically during vocal learning. Three types of birds are vocal learners: hummingbirds, parrots, and
songbirds (Nottebohm, 1972; Baptista and Schuchmann, 1990). Of these, the songbirds have been studied
in the most detail, both behaviorally and physiologically (Konishi, 1985; Nottebohm et al., 1990).
Development of song behavior
The development of song behavior dramatically resembles the development of human speech (Doupe
and Kuhl, 1999). Notably, both humans and songbirds have two critical periods of development: (1) a
perceptual or sensory phase during which species-typical vocalizations are learned and (2) a sensorimotor
phase during which the juvenile’s vocalization is shaped through auditory feedback (Konishi, 1965). The
Template Theory provided a seminal contribution to our understanding of vocal learning in songbirds
(Konishi, 1965). Briefly, during the sensory phase, a memory or template of the song of a tutor is formed.
Although the neural mechanisms of memory formation and storage are unknown, they may involve selective
neural tuning to specific stimuli or the fine-tuning of an innate perceptual filter (Marler and Peters, 1977;
Konishi, 1985). During singing in the sensorimotor phase, the Bird’s Own Song (BOS) is shaped by
comparison of the template and auditory feedback or, if you will, by the passage of auditory feedback
through the template perceptual filter (Fig. 1). In the model below, the hypothetical neural signal resulting
from the passage of auditory feedback through the template filter will be referred to as the “templatematching signal” or “matching signal”. In summary, behavioral experiments indicate that (1) a memory
(template) of the tutor song exists and (2) auditory feedback is compared to the memory during singing to
produce a matching or error signal that shapes song behavior during the sensorimotor phase (Konishi,
1965).
Figure 1. A simple schematic of the sensorimotor phase of vocal learning in songbirds.
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A forebrain pathway with clear roles in song learning
Each brain hemisphere has one set of specialized nuclei that control song, collectively called the song
system (Nottebohm et al., 1976). Although the nucleus HVC projects directly to the nucleus Robustus
Arcopallialis (RA), which drives the brainstem nuclei that produce singing, another pathway from HVC to RA
exists, the Anterior Forebrain Pathway (AFP; gray nuclei in Fig. 2). The importance of the AFP in song
development was clearly shown by lesioning a song nucleus in the AFP during different stages of vocal
learning (Bottjer et al., 1984). Briefly, in zebra finches, the magnocellular nucleus of the anterior nidopallium
(MAN, which includes the lateral MAN, LMAN) received bilateral electrolytic lesions. Finches lesioned 35 –
50 days post-hatching sang abnormal songs for the rest of their lives. Interestingly, finches aged 55 – 65
days sang songs that were disrupted according to the status of their song before lesioning: Those with no
recognizable song pattern resembled the 35 – 50 day finches, singing abnormal songs thereafter. In
contrast, those finches with a recognizable song exhibited no immediate song disruption. The song of adult
birds was stable for as long as 5 weeks after lesioning, indicating that, in terms of several weeks, MAN has
no role in song production or in song maintenance in the adult. (Subsequent experiments have shown that
LMAN enables adult song plasticity over a period of many weeks in the deafened adult (Brainard and
Doupe, 2000).) Collectively, these data indicate that MAN has a critical role in the shaping of song during
development (Bottjer et al., 1984). These authors keenly observed that the time course of the efficacy of
MAN lesioning (~35 days to the date of emergence of a recognizable song pattern) did not match the time
course of dependence on auditory feedback (~35 – 90 days; the sensorimotor phase)(Bottjer et al., 1984).
This suggests that (1) the early sensorimotor phase selectively involves the AFP and (2) the behaviorally
defined ‘sensorimotor phase’ may actually be divided into more than one neural processing phase.
Figure 2. A simplified schematic of the neural
song system of the zebra finch. A subset of
nuclei and connections are shown. The Anterior
Forebrain Pathway is shown in gray.
Little evidence of a template-matching signal within the song system and the problem with
anesthesia
Extracellular and intracellular recordings from anesthetized adult songbirds have consistently shown that
song nuclei respond selectively to the Bird’s Own Song (BOS)(Margoliash, 1983; Mooney, 2000). No widely
accepted argument explains why BOS is the best song system stimulus during sleep and anesthesia,
although the authors of one study speculated that song preference for BOS is related to rehearsal of song
during sleep (Dave and Margoliash, 2000). BOS is also the most effective activating stimulus during
anesthesia in developing songbirds (Volman, 1993; Doupe, 1997; Solis and Doupe, 1997, 1999, 2000). The
overall picture painted by these studies suggests that song nuclei are not selective for any song in very
young anesthetized birds (30 days in finches), but these nuclei become selective for BOS through
development. By 60 days, the majority of neurons in nuclei of the Anterior Forebrain Pathway are activated
most by BOS under anesthesia, while others respond more to tutor song or equally well to both tutor song
and BOS (Solis and Doupe, 1999). If the recorded activity is a template-matching signal, it should be most
activated by tutor song, not BOS. However, tutor song was not the overall most effective stimulus in any
developmental study in anesthetized birds. What is the impetus for change? Where is the matching or error
signal that indicates whether the auditory input matches or mismatches the template? This apparent
paradox may be explained by the fact that the anesthetized song system behaves differently than the
waking song system. Indeed, in adult finches, the song system exhibits strikingly different activity patterns
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depending on anesthesia and sleep/wake state (Dave et al., 1998; Schmidt and Konishi, 1998; Nick and
Konishi, 2001). Recent studies indicate that the song selectivity measured in juvenile finches is also
different during waking compared to anesthesia (Nick and Konishi, 2005a). Thus, song preference should
be examined in waking juveniles.
Learning studies in adults versus juveniles
Previous research has examined song learning in adult zebra finches (Dave and Margoliash, 2000). In
addition, studies in adults have suggested that the mechanisms of song learning are called into play during
adult plasticity (Brainard and Doupe, 2000). Indeed, perturbation of auditory feedback clearly illustrates the
plasticity of adult song behavior (Nordeen and Nordeen, 1992; Leonardo and Konishi, 1998), but plasticity is
not equivalent to learning. Learning, by definition, involves the ACQUISITION of skills or knowledge. Zebra
finches provide an extreme example of overtraining: they sing the same series of sounds hundreds to
thousands of times every day throughout their adult lives. There is little evidence that adult zebra finches
can learn new song material, especially at the dramatic rates evinced by juveniles (Zevin et al., 2004). All
adult “learning” data are also consistent with a more parsimonious model of song MAINTENANCE. Thus, to
understand song learning, song acquisition in juveniles must be examined.
Single neuron recordings
Examination of the activity of single neurons in the song system has relied on single wire recordings that
were subjected to a simple amplitude threshold (Dave and Margoliash, 2000; Hahnloser et al., 2002).
Signal-to-noise ratio traditionally has been used as a measure of single-unit quality, although it is rarely
reported and subject to error. Since the cells of HVC occur in clusters, the likelihood of recording multiple
units is high. Ultimately, with simple thresholding of extracellular data, the distinction between multi-unit and
single-unit data is in the eye of the beholder.
High impedance sharp wire electrodes required to monitor single-unit activity are impractical for
recordings more than a few minutes in freely moving animals because movements of the electrode may
damage the cell or cause the electrode to move away from the cell (Harris et al., 2000). Song researchers
have been able to achieve some success in recording from freely moving animals with single wire
electrodes under the control of miniaturized motorized microdrives (Fee and Leonardo, 2001). However, the
use of the ~1.5 g microdrive in juvenile finches < 60 days old, which possess thin, flexible skulls and weak
neck musculature, may not be feasible. In addition, NO evidence indicates that neurons can be recorded for
longer than a few seconds with single-wire electrodes in singing finches. There are two major reasons that
electrophysiologists desire stable recordings: (1) to have time to do the appropriate controls, and (2) to be
sure that the observed activity is not an aberration caused by the destabilization of the neuronal
plasmalemma by the mechanical pressure of the electrode. Neurons will die within a few seconds if they
are firing robustly due to mechanical pressure. However, if the neuron is held only for a few seconds,
distinguishing aberrant from normal activity is impossible. Multi-electrode arrays are routinely placed under
the control of lighter weight manual microdrives and produce data of exceptional quality (Wilson and
McNaughton, 1993; Harris et al., 2000; Redish et al., 2001; Buzsaki, 2004). The manual microdrive that will
be used in the proposed experiments weighs ~400 mg (< 1/3 the weight of the Fee microdrive). Another
drawback of the single wire recording technique is that only one cell can be reliably recorded at a time,
which is not the case with triode recordings. Triodes enable the use of larger wires, which improve
mechanical stability, and provide greatly improved methods for the sorting of spikes from the same cell,
based on the temporal coherence of activity across all channels (Harris et al., 2000). Moreover, even the
best single wire records exhibit error rates that are almost twice those of a three-wire multi-electrode (Harris
et al., 2000). Collectively, these benefits of multi-electrodes over single wire electrodes argue for the use of
multi-electrodes in developing zebra finches.
State-dependence of song preference in the juvenile HVC
Initial efforts to find the matching signal in waking finches focused on the premotor nucleus HVC (Nick
and Konishi, 2005a). HVC is the ideal nucleus to receive template-matching information, since it (1)
receives and transmits auditory signals to both RA and the AFP and (2) drives singing (e.g., stimulation of
HVC during singing ‘resets’ the song (Vu et al., 1994)). Strikingly, neural population data reveal that the
HVC of young finches (35 – 69 days) exhibits state-dependence of song preference: playback of BOS
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activates HVC most during sleep, as in adults, whereas the tutor song activates HVC most during waking
(Nick and Konishi, 2005a). HVC exhibits neural tuning to the tutor song only during waking and only during
the specific period of development (early sensorimotor phase) during which the finch matches his own song
to the song of the tutor. The observed neural tuning thus appears to be a template-matching signal.
Linking the template-matching signal to changes in behavior
The nervous system exists to enable adaptation to the environment through changes in behavior. In the
case of simple reflexes, sensory input induces a motor action. For more sophisticated behaviors, such as
walking and talking, sensory feedback is used to precisely guide the motor action. The on-line perceptual
guidance of actions requires that sensory inputs and motor commands interact continuously within the
nervous system through sensorimotor integration. Many current hypotheses of neural modulation rely on
the mechanisms of activity-dependent synaptic plasticity (electrical activity-induced change in the strength of
connections between neurons). Activity-dependent plasticity requires simultaneous electrical activity in the
two neurons that are connected (i.e., neurons that fire together, wire together). This poses a problem for the
processing of sensorimotor signals in the central nervous system, because there are temporal delays
between the transmission of the motor command and the occurrence of sensory feedback due to the
relatively large number of processing stages (Fig. 3A). By the time the sensory feedback reaches the brain
area that transmitted the motor command, the motor activity has already ceased.
Figure 3. Schematic of neural sensorimotor activity and the issue of temporal delays. (A) In the
adult zebra finch song system, motor command activity and sensory feedback do not appear to
coincide. (B) Coincidence of motor and sensory firing may occur during song learning through
increased excitability in the motor command (pre-vocal) neurons. In B, the motor command may
not continue to induce behavior due to the failure of transmission in the pathway that intervenes
between the command and the muscle. Consistent with this hypothesis, pre-vocal activity
outlasts the vocalization during song learning (see Preliminary Data).
The development of birdsong, which parallels human speech, provides an ideal model in which to
investigate activity-dependent mechanisms of sensorimotor learning. It is estimated that there is a lag of at
least 60 ms between the firing of pre-vocal (motor command) neurons and the sensory response in these
same neurons. One model of birdsong learning that addresses the problems of sensorimotor learning
suggests that motor to sensory mapping is learned via activity-dependent synaptic strengthening across this
60-ms delay (Troyer and Doupe, 2000a). Yet, other studies indicate that synaptic strengthening requires a
delay of 20 ms or less (Bi and Poo, 2001). Thus, during the initial construction of the song system, a
significant time gap must be closed to enable proposed activity-dependent associations to occur.
Long duration action potential bursts in pre-vocal motor neurons would bridge the time gap between
motor command and sensory feedback (Fig. 3B). Mark Konishi and I recently discovered that the levels of
spontaneous activity in a key pre-vocal song nucleus are significantly greater during the sensorimotor phase
of song development (Nick and Konishi, 2005a), during which song behavior is shaped by auditory feedback
(Konishi, 1965). These data suggest the hypothesis that increased song system excitability during the
sensorimotor phase allows coincident activation of both motor command and sensory feedback pathways,
which enables activity-dependent modulation of the brain substrates of song behavior. Aim 4 will test a key
prediction of this hypothesis.
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Tracking the engram: The matching signal in song development
The electrophysiological studies of the song system over the last 20 years have focused almost
exclusively on anesthetized finches (e.g., Gentner and Margoliash, 2003; Rosen and Mooney, 2003), while
very few have examined waking finches (McCasland and Konishi, 1981; Hahnloser et al., 2002). Recent
studies conclusively show that the activity during anesthesia and sleep by no means reflects activity during
waking (Dave et al., 1998; Schmidt and Konishi, 1998; Nick and Konishi, 2001). These findings compel the
birdsong field to rethink our understanding of neurophysiology in this system. We have already identified a
putative matching signal expressed during waking in the developing HVC (Nick and Konishi, 2005a). The
aims described in this proposal will (1) examine the information contained in the putative matching signal
(Does it convey a graded signal of similarity to tutor song at the level of single neurons?); (2) test the
function of the putative matching signal in template-matching (Does it occur during singing?); (3) elucidate
its underlying mechanisms in shaping the developing song system (Is it sent to the Anterior Forebrain
Pathway?); and (4) test a mechanism through which the template matching signal may shape behavior
using well-known mechanisms of activity-dependent plasticity (Do temporal aspects of brain-behavior
relationships change during vocal learning?).
C. PRELIMINARY STUDIES
Section 1. Quantification of spike cluster quality
The primary advantage of multi-electrode over single electrode recording is the reliability of the results.
In single electrode recordings, spikes of a single unit are usually identified using a single parameter
(amplitude threshold) arbitrarily selected by the experimenter. Multi-electrode data relies on multiple
parameters that describe the spike amplitude as well as spike shape across more than one electrode. This
decreases the likelihood of errors, such as obtaining only a subset of the activity of a unit or concluding that
the activity of multiple units is only that of a single unit. Sophisticated computer algorithms such as
KlustaKwik (by K. Harris) cluster multiple events in a multi-dimensional space, with each dimension
reflecting a different spike parameter. However, there is no widely used method of quantifying how well a
cluster of events (presumably reflecting the activity of a single neuron) is separated from other events.
Quantification of spike cluster quality (i.e., how reliably the data represent all of the spiking activity of one
neuron and only one neuron) will be achieved using methods established by my collaborator David Redish
(Schmitzer-Torbert et al., 2005). Using measures of energy (L2-Norm; related to amplitude, see below) and
the first principal component coefficient from all three electrodes, I will calculate the L-ratio, a measure of
the amount of noise around a multi-dimensional cluster, and the Isolation Distance (I.D.), a measure of
how distant a given cluster is from the overall noise distribution. I will use the following thresholds for
inclusion in further analyses: L-ratio must be less that 0.05; Isolation Distance must be more than 16. In
addition, I will ensure that there are no changes in the firing pattern of the cell (under similar conditions) over
the duration of the experiment (~ 4 hrs), which would suggest that more than one cell or that only part of the
activity of one cell has been clustered. I will also inspect the interspike interval for each clustered neuron.
Interspike intervals of less than 200 μsec will suggest that more than one cell has been clustered, since all
neurons have a refractory period during which another spike cannot be generated. An example of a spike
cluster from HVC that I analyzed with spike sorting techniques is shown in the Figure 4. These data show
that the activity of single neurons in awake, behaving juvenile zebra finches can be stably recorded and
quantitatively analyzed using multi-electrode recording and spike sorting techniques.
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Figure 4. Voltage spikes in HVC from three electrodes were clustered in 15 dimensions. The two
dimensions shown in this figure are L2-Norm (a measure of energy of the trace) on electrodes 1 and 3.
The LEFT panel shows a contour plot of the densities of all of the spiking events that occurred during
the recording session. The RIGHT panel shows the scatter plot of points in the same dimensions. The
red cluster is well-separated (indicating a single unit), given the L-ratio and Isolation Distance (ID),
whereas the green cluster is not acceptable for further analysis. A sample of the raw data that were
analyzed for these plots is shown in Fig. 5.
Section 2. Analysis of auditory responses in single neurons during singing
Aim 2 examines the activity of HVC neurons during singing. A critical first step in these experiments
involves production of song in the presence of masking noise. Comparable numbers of songs are produced
by a juvenile finch under masking noise and silent conditions (Fig. 5; masking noise, N = 7; silence, N = 11).
I now provide preliminary evidence of auditory feedback in the zebra finch during sensorimotor learning.
Recordings were made from a single HVC neuron for over 4 hours. This neuron produced action potentials
that were similar in amplitude and spiking pattern to tutor song selective neurons that Konishi and I have
previously observed (large signal-to-noise for an extracellular recording with relatively large diameter wire;
Nick and Konishi, 2005b).
Spike-sorting techniques were used to evaluate the activity of a single neuron in the HVC of a juvenile
finch (data from the same neuron shown in Figs. 4 - 6) during singing (3 exemplar songs are shown in Fig.
5) and during non-vocal periods. Ongoing activity of the single neuron did not change with presentation of
masking noise (Fig. 6A). This is an important control to assess nonspecific auditory effects that are not
related to auditory feedback. In contrast, during singing, activity of this neuron significantly decreased with
masking noise compared to singing without masking noise (Fig. 6B). Since the total auditory stimulation
actually increased during masking noise, these data suggest that the subset of HVC activity during singing
that was decreased by masking noise was selective for the sound produced.
The activity during singing of the single HVC neuron described above may have been auditory, motor, or
a combination of both. My data suggest that at least part of the activity depended on auditory feedback. To
thoroughly investigate the issue of whether the changes in the HVC neuron’s activity were auditory or
motor-related, several controls were employed: control and masking noise songs were interleaved
(changes induced during a masking noise period would be measured during the next song produced during
a control period and vice-versa, taking all but the most instantaneous changes out of the equation) and the
songs produced under noise and no noise conditions were compared with regard to amplitude and
similarity. I measured the root mean square of the song amplitude between 5.5 – 6.5 kHz, over which
masking noise was not played. If there were a simple, direct relationship between HVC activity and relative
song amplitude, the activity and amplitude should change in the same direction, since increased HVC
premotor activity may be required for increased song amplitude and increased song amplitude may further
activate HVC through auditory feedback. To the contrary, there was no significant difference between song
amplitude during noise and no noise conditions (RMS μV: Noise: 702.7 ± 10; Control: 653.6 ± 7, p = 0.34),
with a trend in the opposite direction of what would have been predicted based on a simple relationship
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between song amplitude and HVC activity.
These data suggest that the decrease in HVC activity with
masking noise reveals HVC activation by SELECTIVE auditory feedback.
Figure 5. Juvenile finches sing during masking
noise as well as during silence. Increased
neural activity in the brain area HVC
accompanies song production, as in adults.
TOP: Spectrogram of sound in the acoustic
chamber temporally aligned with neural
recordings below (high sound intensity
indicated by red color). Masking noise (15 sec,
80 dB) was preceded and followed by silent
periods (a window was left in the noise at 5-7
kHz to enable song identification). The juvenile
finch sang both during masking noise and
silence. The gray bars indicate the timing of the
vocalization for comparison to the BOTTOM
three panels: Recordings from HVC using a
three-wire multi-electrode.
Raw voltage
recordings from each electrode are shown
separately.
Figure 6. Masking noise has differential
effects depending on whether the finch is
singing.
(A) Activity of a single HVC
neuron is not affected by noise if the finch
is not singing (mean ± sem; p = 0.38, N(15
sec intervals) = 7,7). (B) Activity of the
same neuron during singing is significantly
decreased during masking noise compared
to no noise (*t-test, p = 0.05; N(songs) =
11,7).
Song similarity was compared using the Sound Analysis Pro software developed by Tchernichovski and
colleagues (2000). The band of frequencies between 5.5 – 6.5 kHz was compared between noise and
control songs. Noise – control comparisons yielded percent similarities that were not different from control –
control comparisons (% Similarity: Noise-control, 86.4 ±0.3 Control-control: 80.0 ± 1.3; p = 0.25, t-test).
Collectively, these data indicate that the song produced does not change during noise playback. This
finding suggests that the changes in activity observed in HVC are AUDITORY and not motor-related.
If masking noise induced changes in motor activity and performance (i.e., influenced learning), then the
control songs and corresponding motor activity should have changed from the beginning to the end of the
session. To the contrary, during the session there was no significant change in HVC activity during song
production in control periods (Spike Rate (Hz), First 5 control songs: 69.5 ± 1.3; Last 5 control songs: 75.8 ±
1.1, N.S.).
In summary, my controls for motor-dependent versus auditory-evoked activity include: (1) interleaving
masking noise and silence to obtain songs under control and experimental conditions during the same time
periods; (2) comparison of noise/no-noise activity during non-vocal periods as well as singing; (3)
comparison of song similarity and amplitude; and (4) comparison of activity during singing under control
conditions from the beginning and end of the recording session. I have also increased control in these
experiments by not using a female to elicit song. Although singing rate in the absence of a female is
relatively low, I will be able to collect enough data from a single neuron to rigorously analyze due to the
stability of the multi-electrode recording technique.
My study is different from previous studies in several key areas. (1) I study much younger finches (50-65
days post-hatching). Previous studies focused on older finches (>70 days) that had passed the period of
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greatest plasticity. (2) I analyze undirected song (no female present). Previous studies used a female to
elicit song (directed song) or did not record whether or not a female was present. Data indicate differential
brain activity during directed and undirected singing (Jarvis et al., 1998; Hessler and Doupe, 1999). In
addition, both directed and undirected songs are produced in the presence of a female, which increases
variability and decreases control. (3) Although fewer songs are emitted in the absence of a female, my
recording technique (multi-electrode recording) is stable enough to allow many songs to be recorded (see
below). Previous studies used single-electrode recording, which is much less mechanically stable than the
multi-electrode bundle (Harris et al., 2000) and, thus, enables only short-term recordings.
Playback of tutor song tended to induce more activity in this neuron than conspecific song, although the
difference was not significant (Fig. 7). For Aim 2, I will play back a minimum of 50 songs to clarify this issue.
Figure 7. The single HVC neuron shown above
may be more active during playback of tutor song
(A) than conspecific song (B)(Spike rate during N
playback trials (Hz); Tutor: 4.2 ± 0.3, N = 29;
Conspecific: 2.0 ± 0.2, N = 30; t-test, p = 0.22).
Sonograms are shown temporally aligned above
the recordings from the three-wire multi-electrode
in HVC.
Scale bar: 200 μV, 300 msec.
Section 3. Identification of single neurons in an ensemble recording
Initial experiments in the zebra finch song system revealed that the very power of the multi-electrode
technique, namely the recording of groups of neurons, interfered with the identification of antidromicallyactivated spikes. I antidromically stimulated song nucleus Area X (basal ganglia) and recorded from its
afferent, nucleus HVC. HVC has three main subtypes of neurons: those that project to Area X, those that
project to robustus arcopallialis (a premotor song area), and interneurons. The Area X-projecting HVC
neurons are of particular interest because Area X and the other nuclei of the Anterior Forebrain Pathway are
known to have roles in song plasticity (Bottjer et al., 1984; Brainard and Doupe, 2000). Often, antidromic
stimulation of the target nucleus resulted in a burst of activity or a large stimulus artifact in the recorded
nucleus, such that the antidromically-stimulated spike amplitude and waveform was obscured. Since spike
sorting of multi-electrode data relies on relatively constant spike parameters, the problem was significant.
However, a defining test of antidromicity provided the solution: orthodromic-antidromic spike collision (Fig.
8). Collision of a spontaneous orthodromic spike with the antidromic spike shows that the neuron that
produces the orthodromic spike projects to the stimulated area. Thus, instead of using the obscured
antidromic spike for my analysis, I used the spontaneous orthodromic spike. In the pre-stimulus time frame,
the orthodromic spike is not obscured by antidromically triggered bursts or stimulus artifacts. It has as a
high signal-to-noise ratio as any other recorded spikes and can thus be co-clustered with behaviorallyrelevant spikes.
Figure 8. Two key properties of antidromicity.
The HVC voltage recordings in A-C are all
aligned relative to the antidromic stimulus.
Scale bar: 600 μV, 10 msec.
(A) 15
antidromically-evoked spikes have a relatively
constant latency.
Inset: Higher temporal
resolution of the 15 antidromic spikes reveals
low latency variability. Scale bar: 600 μV, 0.5
msec.
(B) A single antidromic spike for
comparison with C. (C) A collision event. The
orthodromic spike begins at the soma and
collides with the evoked spike such that the
antidromic spike does not reach the soma and is
therefore not recorded.
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For this example, all data during a 9-hour recording period were clustered. Four high-quality (L-Ratio <
0.05; Isolation Distance > 16) clusters were obtained. Spikes that occurred within the collision time window
prior to stimulation were identified from each cluster (Fig. 9). Orthodromic spikes in clusters 1,2, and 4 did
not collide with the spike evoked by Area X stimulation (arrows, Fig. 9 C,D,F). In contrast, orthodromic
spikes in cluster 3 routinely resulted in collisions (asterisks, Fig. 9 E), indicating that the unit in cluster 3
projected to Area X.
Figure 9. Identification of an Area X-projecting
HVC neuron in the waking juvenile using combined
multi-electrode and antidromic techniques. Four of
six clustering parameters are shown. Energy (A)
and Principle Component 1 (B) are shown for
electrodes 1 and 2. In C-F, electrodes 1 and 2 are
shown temporally aligned. Three instances during
which spontaneous orthodromic spikes occurred
during the collision time window preceding the
stimulus are shown for each cluster.
The
spontaneous orthodromic spike is indicated by a
gray box outlined by the color of the cluster shown
in A and B. The stimulus artifact is indicated by a
dotted line in the middle of each trace. In C, D,
and F, antidromic spikes occurred (arrows). In E,
collisions occurred (asterisks), which indicate that
cluster 3 contained the activity of an Area-X
projecting neuron. Scale bar: 600 μV, 10 msec.
Section 4. Developmental modulation of brain-behavior relationships in the song system
I used multi-unit recording to monitor the activity of a population of HVC neurons for prolonged time
periods during development. I found that vocal-associated activity is developmentally modulated. Figure 10
shows recordings from a birds that was recorded in my laboratory as a juvenile in the process of song
learning and as an adult after song learning (crystallization). The adult HVC shows typical premotor activity,
with activity beginning ~20 msec prior to vocalization and ending ~20 msec prior to the end of vocalization.
In contrast, juvenile HVC activity is not well-correlated with vocalization, beginning well before or after the
typical adult activity start time and lasting tens to hundreds of milliseconds beyond the vocalization. These
data are consistent with the hypothesis that increased song system excitability during the sensorimotor
phase allows coincident activation of both motor command and sensory feedback pathways, which enables
activity-dependent modulation of the brain substrates of song behavior.
PHS 398/2590 (Rev. 09/04)
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Figure 10. Repeated recordings across development reveal modulation of brain activity-behavior
relationships. Population recordings were obtained from the same bird and the same electrode (Orange
298) during the late sensorimotor phase (LEFT; 65 days) and during adulthood (RIGHT; 104 days). Five
simple calls from each age are shown with HVC activity overlaid to show temporal relationships. HVC activity
outlasts the vocalization in the juvenile, but not the adult. Scale bar: 100 μV; 100 msec.
D. RESEARCH DESIGN AND METHODS
The songbird presents the ideal model for examining both vocal learning and fundamental mechanisms
of forebrain control of behavior in vertebrates. To learn its song, the zebra finch must first memorize the
song of a tutor and then match its own vocalizations to the memory trace, or template, through auditory
feedback (Konishi, 1965). Shaping of the behavior requires that the results of the comparison of memory
and auditory input (the template-matching signal) ultimately impact the forebrain premotor song circuitry, the
nuclei HVC (this acronym is the proper name) and RA (Robustus Arcopallialis). With Mark Konishi, I
recently reported the first evidence of a template-matching signal in the song control nucleus HVC (Nick and
Konishi, 2005a). Specifically, the tutor song activates HVC more than any other auditory stimulus during
waking in juveniles (Nick and Konishi, 2005a). The response to the Bird’s Own Song (BOS) appears to
reflect the degree to which BOS resembles the tutor song (Nick, 2004), further strengthening the hypothesis
that the HVC response during waking reveals a template-matching signal. The proposed experiments will
use the putative matching signal to begin to unravel the brain mechanisms of vocal learning in songbirds
(Table II). The studies described below will test the hypothesis that the observed selective activity functions
as a matching signal during song development, as well as determine key mechanistic bases of the signal.
These experiments have been designed to avoid many of the complicating factors associated with previous
studies. Specifically, the proposed studies will utilize: (1) awake finches, in preference to sleeping or
anesthetized finches, to study the neural bases of a behavioral process (template-matching) that occurs
during waking; (2) juvenile finches, in preference to adults, to study song learning; and (3) multi-electrode
(triode) and multi-unit recording, in preference to single wire single-unit recording, to stably assess the
activity of single neurons or populations over extended periods. Toward accomplishing the stated goals, I
have already obtained preliminary data using the powerful techniques of multi-electrode recording (Recce
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and O'Keefe, 1989; Wilson and McNaughton, 1993) and antidromic stimulation (Ranck, 1975). In addition,
an expert on multi-electrode recording, A. David Redish, will assist with these experiments.
Table II. A brief summary of the research plan.
Aim
Questions
1
2
3
4
Do single HVC neurons indicate the
degree of stimulus similarity to tutor
song?
Does the putative matching
signal occur during singing?
What HVC neurons carry the signal?
Where is the signal transmitted?
Do temporal aspects of brain-behavior
relationships change during vocal
learning?
Techniques
Preliminary
data?
multi-electrode recording
auditory playback
Yes
Informative
regardless of
outcome?
Yes
multi-electrode recording
auditory playback
song recording
multi-electrode recording
spike collision
multi-unit recording
song recording
Yes
Yes
Yes
Yes
Yes
Yes
These experiments are technically challenging due to the age of the animals (their skulls are soft and
they often fail to recover after surgery) and the fact that the animals are awake and unrestrained. To my
knowledge, only one group other than ours has successfully recorded chronically from the brain of
the juvenile zebra finch (34 – 60 days), and they met with limited success (Adret et al., 2005). All other
studies have utilized anesthetized finches and/or finches >63 days. My success rate for recording from
HVC during surgery in juveniles is ~100%. However, ~40% of juveniles die within 2-3 days after surgery. In
general, those that survive the first 3 post-operative days survive to adulthood. Of the juvenile finches that
survive, my own preliminary data indicate that a third exhibit high-quality recordings from HVC (recordings
that yield single units as defined by my strict criteria). Aim 3 requires that, in addition to these successes,
the deep nuclei Area X and RA must be stimulated. In adults, the volume of Area X is approximately 1.8
cubic millimeters, whereas the volume of RA is approximately 200 cubic microns (Both values were
calculated from E. Akutagawa’s zebra finch brain atlas). These nuclei are smaller in juveniles. Thus, the
experiments described below are very labor intensive with regard to data acquisition. In addition, spikesorting data analysis is time and labor intensive. Although these experiments are very difficult, I am
confident in my ability to execute all four aims, due to my extensive experience with
electrophysiological techniques both in the developing song system (Nick and Konishi, 2004, 2005b)
and in other developing neural systems (Nick et al., 1996a; Nick and Ribera, 2000).
Aim 1. Examine the precision of neural tuning of single HVC neurons in awake, behaving
finches during song development.
Hypothesis: During waking in the early sensorimotor phase, individual HVC neurons are selectively
activated by stimuli that resemble the tutor song.
Predictions: The magnitude of the response of individual HVC neurons will be directly proportional
to the degree of similarity of the given stimulus to the tutor song.
It is well-accepted that the singing finch uses the comparison of auditory feedback and a tutor song
memory to shape its song during development (Konishi, 1965), but neural evidence to corroborate this
behavioral hypothesis has not been found. During the early sensorimotor phase, passive listening to
playback of the tutor song selectively activates neurons within the song nucleus HVC (Nick and Konishi,
2005a). HVC neurons respond more to tutor song than to any other auditory stimulus, including the Bird’s
Own Song (BOS) and songs of other adult male zebra finches. Moreover, the selective response to tutor
song occurs only during the developmental phase when the song is sculpted to match the tutor song
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(template-matching period/early sensorimotor phase/35 – 69 days post-hatching). The fundamental
hypothesis of these studies proposes that this selective activity is a “matching signal” resulting from the
comparison of incoming auditory signals and the tutor song memory or template. Measuring the putative
matching signal at the level of single neurons is a critical step towards understanding the development of
the song system.
The putative matching signal may be either all-or-none or graded. The most parsimonious hypothesis
proposes that the matching signal is graded, since this would allow the bird to sing a series of successive
approximations toward the tutor song before arriving at the final version of his own song. In general,
behavioral experiments support the idea of gradual shaping of the song during development (Immelmann,
1969; Tchernichovski et al., 2001), although one study suggests that fast transitions of the spectral
properties of single syllables can occur (Tchernichovski et al., 2001). Knowing if the putative matching
signal is graded or all-or-none will reveal a key aspect of the neural mechanisms of song learning.
EXPERIMENTAL PLAN
Individual HVC neurons of juvenile zebra finches in the early sensorimotor phase will be recorded with
chronically implanted triodes under the control of a manual microdrive (Figs. 11 – 12). Various auditory
stimuli, including multiple copies of the tutor song and the Bird’s Own Song (BOS), will be played back to the
finch. Due to the requirement of several presentations of each stimulus and the large number of stimuli,
these experiments will extend over several hours and, thus, would not be feasible using single-wire
extracellular recording techniques. Spike sorting techniques (based on the temporal coherence of spiking
events across the three electrodes of the triode) will allow analysis of the activity of individual HVC neurons.
HVC neurons that respond selectively to the tutor song in preference to all other stimuli will be identified.
The activity of these neurons will then be further examined for information content. Specifically, the
magnitude of the response (number of action potentials) of the tutor song selective HVC neurons will be
compared to the similarity between the given auditory stimulus and the tutor song. These experiments will
reveal if the waking HVC response indicates similarity between the stimulus and the tutor song.
Figure 12. Schematic of the chronic electrode and
microdrive implant.
Figure 11. Schematic of the chronic recording apparatus.
CONTROLS (Where relevant, these controls also apply to Aims 2 and 3.)
Quantification of spike cluster quality. Quantification of spike cluster quality (i.e., how reliably the data
represent all of the spiking activity of one neuron and only one neuron) will be achieved using methods
established by my collaborator David Redish (Schmitzer-Torbert et al., 2005). For all clusters, the L-ratio, a
measure of the amount of noise around a multi-dimensional cluster, and the Isolation Distance, a measure
of how distant a given cluster is from the overall noise distribution, will be calculated from measurements of
energy and the first principal component from all three electrodes. The following thresholds will be used for
inclusion in further analyses: L-ratio must be less that 0.05; Isolation Distance must be more than 16. In
addition, I will ensure that there are no changes in the firing pattern of the cell (under similar conditions) over
the duration of the experiment (~ 4 hrs), which would suggest that more than one cell or that only part of the
activity of one cell has been clustered. I will also inspect the interspike interval for each clustered neuron.
Interspike intervals of less than 200 μsec will suggest that more than one cell has been clustered, since all
neurons have a refractory period during which another spike cannot be generated.
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Playback of a consistent song type. The general category of song that is played back to the finch is an
important parameter to consider when studying behavior and neurophysiology. Data indicate that (1) songs
directed to a female and undirected songs differ with regard to several parameters and (2) directed and
undirected song are associated with differential activation of the brain (Jarvis et al., 1998; Hessler and
Doupe, 1999). This proposal will utilize undirected song produced in the absence of a female for playback.
Confirmation of stimulating and recording electrode location. All recorded finches will be anesthetized
with pentobarbital and perfused with saline and 2% paraformaldehyde. Brains will be sunk in sucrose and
sliced on a cryostat (10 μm slices). Tissue slices will be stained using cresyl violet and examined and
photographed with a Axioskop microscope (Zeiss, Germany) to confirm electrode localization in HVC
(recording electrode), near HVC (reference electrode), in Area X (stimulating electrode), and in RA
(stimulating electrode).
EXPERIMENTAL METHODS
Animals and surgery. The same set of chronically implanted finches will be used for aims 1-3. 200 zebra
finches will be reared on a 12/12 light cycle in the aviary. To ensure that the male parent serves as the sole
song tutor, finches will be reared in acoustic attenuation chambers (Eckel Acoustic, Cambridge, MA). At the
age of 44 - 46 days post-hatching, finches will be chronically implanted with an electrode assembly and
microdrive. Finches will be weighed and anesthetized with 5 μL/g body weight of the following: ketamine
hydrochloride (3 mg/mL) and xylazine hydrochloride (1.5 mg/g).
Multi-electrodes, microdrive, and video monitoring. Finches will be recorded 50 – 65 days posthatching. The implant will consist of the following: 2 stimulating tetrodes, a reference triode, a recording
triode, and a ground electrically connected to a 10-pin nanoconnector. For recording, triodes will be used
instead of tetrodes because (1) they provide almost as much confidence as a tetrode (that a putative single
unit is actually a single neuron)(Harris et al., 2000); and (2) several major pieces of equipment in the
laboratory are designed to process 4 recordings simultaneously, which allows for recording of the 3 wires of
the triode and a reference electrode. For recording, triodes and a reference electrode will be made of 12 μm
nichrome-formvar wire (Kanthal Palm Coast, FL). All three wires of the triode and the reference electrode
will be referenced to an animal ground (100 μm bare silver wire). Differential electrode recordings will be
obtained by referencing the triodes within HVC to a reference electrode that will be placed in a less active
brain area outside of HVC.
Triode and reference recordings will be unity-gain amplified with a quad op-amp (Texas Instruments,
Dallas, TX) connected directly to the 10-pin connector (Omnetics) on the bird’s head (Schmidt and Konishi,
1998; Nick and Konishi, 2001). An 11-channel mercury commutator (Herb Adams Engineering, Pasadena,
CA) will enable reliable recording while the bird moves freely about a small Plexiglas cage. A headstage
controller (Caltech Biology Electronics Shop, Pasadena, CA) will power the headstage amplifier and
facilitate differential recording. Each of the electrode signals from the triode and the reference electrode will
be passed to a 4-channel AC amplifier (A-M Systems) for amplification (1000x) and filtering (300 – 10,000
Hz). These signals will then be passed, along with recorded sound, to a National Instruments (Austin, TX)
PCI card via a BNC interface. Sounds will be recorded with a high quality omnidirectional microphone
(Earthworks SRO, Milford, NH). Data collection software for song and electrode data was custom-written in
LabView (National Instruments) per my specifications (Datafleet, Minneapolis).
Playback experiments will begin approximately 1 hour after the sound attenuation chamber lights are
turned on, during the bird’s normal lights-on cycle. All birds will be presented with sets of 50 - 100 trials
consisting of multiple stimuli, in random order: silence, the tutor song (3-4 copies), conspecific song (3-4
copies with varying similarity to the tutor song), heterospecific song (from a Bengalese finch), white noise (3
sec), and BOS (3-4 copies). To test if the putative matching signal is graded, multiple versions of the
current BOS, as well as older versions of BOS, will be played back. The intertrial recovery period will last
15-s.
Song recording and playback. For song recording, male zebra finches will be isolated in acoustic
attenuation chambers. Songs will be recorded, digitized, and played back at 44,100 Hz. Songs will be
edited with MATLAB (Mathworks, Natick, MA). Undirected (song not directed at a female) and directed
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(song directed at a female) songs differ in terms of consistency and speed of delivery (Sossinka and
Bohner, 1980; Bischof et al., 1981). When a female is present, songs may be undirected as well as
directed. Thus, all songs for playback will be recorded with no female present (undirected) to control for this
variation.
Analysis of Song Playback Data. Song similarity will be scored with Sound Analysis (Tchernichovski et
al., 2000). Electrophysiological data will be analyzed with MATLAB functions included with the MATLAB
software or written by a member of the Nick laboratory or A. David Redish (MClust; see below). A MATLAB
function will automatically discard trials with movement artifacts (revealed by thresholding of large
deflections of the reference electrode record) and trials during which the bird vocalizes. Vocalizations will
be identified by subtraction of a filtered amplitude envelope of an exemplar trial from a filtered amplitude
envelope of the trial under consideration. Any increases in sound amplitude at any point in the trial, from 1sec preceding the trial to 20-msec after the playback stimulus ends, will lead to rejection of the trial. As in
prior finch studies (Dave et al., 1998; Dave and Margoliash, 2000; Rauske et al., 2003), I will use behavioral
criteria to determine wake state. To be classed as ‘awake’, the birds will have to have open eyes and
feathers that lay close to the body and are not ruffled.
Multi-electrode (triode) recording is superior to single electrode recording, which has traditionally been
used in birdsong research. Triodes provide more mechanical stability, an ~50% lower error rate, and the
ability to record from more than one neuron simultaneously (Harris et al., 2000). Individual neurons can be
identified in a set of adjacent multi-unit records with the techniques of spike sorting or ‘clustering’. Spike
sorting relies on the fact that each action potential waveform can be described by a set of parameters (e.g.,
spike height, first principal component). In addition, these parameters will be different depending on the
spatial location of each electrode relative to the neuron, which enables an even larger parameter set for
each spike event. The parameter vector for each spike can be plotted in a multi-dimensional space. The
points describing the spikes of a given neuron tend to cluster in multi-dimensional space (McNaughton et
al., 1983). For all experiments, the activity of individual neurons (the number and timing of action potentials
during song playback) will be determined using the MClust suite of spike sorting/clustering functions written
in MATLAB (MClust written by A.D. Redish). The chief author of this software, A. David Redish, has agreed
to assist me with this analysis (Schmitzer-Torbert et al., 2005).
Selectivity will be determined by comparing the number of action potentials during tutor song playback to
the number of action potentials during playback of other stimuli. A one-way ANOVA (with a post-hoc TukeyKramer) will compare the number of action potentials during each stimulus across stimuli. Cells with
significantly more action potentials during tutor song playback will be considered ‘selective’. These cells
carry the putative matching signal.
To examine the graded or all-or-none nature of responses, the number of action potentials in response to
a given stimulus will be plotted against the similarity of that stimulus to tutor song. Scatter plots thus
constructed for each neuron, as defined by spike sorting, will be fit with a linear regression. Goodness of fit
will assess the graded nature of the response.
Aim 2. Identify and manipulate the activity of tutor song selective neurons during singing.
Hypothesis: The putative matching signal occurs during singing.
Predictions: HVC recording during singing will reveal activity in the same neurons that respond
passively to tutor song. Further, the singing-associated activity of these neurons will be eliminated
by perturbation of auditory feedback.
The Template Theory proposes that a matching signal during singing sculpts the developing song
(Konishi, 1965). If the observed HVC neural tuning to the tutor song is a template-matching signal, then (1)
the neurons that selectively respond to tutor song should fire during singing, and (2) perturbation of auditory
feedback should decrease their activity (the putative matching signal) during singing. Reversible auditory
feedback will be perturbed with two distinct methods: masking noise and paralysis of the middle ear muscles
with lidocaine injections. Masking noise can be used as an immediate and reversible means of perturbing
auditory feedback. By virtue of its random frequency and time relationship, masking noise obscures
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concomitant sounds. Behavioral data already indicate that masking noise interferes with auditory feedback
during singing (Iyengar and Bottjer, 2002; Zevin et al., 2004). The proposed experiments will test the
hypothesis that auditory feedback occurs during singing in the developing zebra finch with particular focus
on the HVC neurons that respond to playback of the tutor song. Moreover, this aim will show whether the
putative matching signal for sensory and template information occurs within the premotor nucleus HVC
during song behavior.
Previous studies concluded that perturbation of auditory feedback with masking noise does not affect
HVC activity in adult zebra finches (Kozhevnikov and Fee, 2003, 2004). The proposed experiment would be
executed in juvenile zebra finches, that (1) are clearly more plastic in terms of both normal behavior
(Immelmann, 1969; Tchernichovski et al., 2001) and behavior following perturbations such as deafening
(Konishi, 1965) and lesioning (Bottjer et al., 1984); and (2) exhibit the putative matching signal (Nick and
Konishi, 2005a). The proposed study specifically focuses on the neurons that respond passively to tutor
song playback in the wake state. The study will be informative irrespective of the outcome.
EXPERIMENTAL PLAN
The goal of this study is to assess the presence of a matching signal in the sensorimotor nucleus HVC
during singing. To accomplish this goal, I propose to identify neurons (single units identified by spike
sorting) that respond to passive playback of the tutor song and then compare, within the same individual
neurons, activity during singing with and without perturbation of auditory feedback. I will compare HVC
activity during normal singing (with normal auditory feedback) and HVC activity during singing with auditory
feedback signals obscured (with masking noise or middle ear paralysis)(Fig. 13). If the aim were to assess
auditory signals, per se, then this experiment would not make sense, since auditory signals will still impact
the cochlea. In fact, there will be more auditory information than without masking noise. However, the
underlying hypothesis proposes that the only signals that make it through a “template filter” are those that
are similar to the tutor song. Obscuring the auditory signal prevents it from passing through the filter. Thus,
there will be no matching signal if the obscured auditory signal does not match the memorized tutor song.
The proposed matching signal only occurs in a narrow developmental window: the template-matching
period (during early sensorimotor phase; ~50 – 65 days post-hatching). Thus, this experiment will only be
performed on these young animals. Juvenile finches have thin, flexible skulls and weaker neck
musculature, compared to adults. Thus, I will not attempt to employ single-unit recording with motorized
microdrives, as several other birdsong groups are currently applying in adult finches (Fee and Leonardo,
2001). Instead, I will use triode recording, which will allow the use of lighter, manual microdrives. Triodes
provide a means for recording the same group of neurons for longer periods of time than is possible with
single-unit techniques because triodes (1) are more mechanically stable than a single wire and (2) enable
the tracking of a cluster of characteristics of a given unit over time, even as the electrode makes slight
movements (Harris et al., 2000).
Figure 13. Simple schematic of the experiment described in Aim 2, executed during the early sensorimotor
phase. Masking noise will obscure auditory feedback and, according to the hypothesis, prevent the template filter
from generating a matching signal. HVC, a premotor song nucleus, will be recorded using multi-electrode
techniques. The hypothesis predicts that less HVC activity will be recorded during perturbation than during
normal singing.
CONTROLS
Nonspecific effects of masking noise. Activity of each single neuron will be compared between noise
and no noise for both singing and non-singing conditions to evaluate nonspecific auditory effects of noise.
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Changes in song during the recording session. Perturbation of auditory feedback may influence the
song produced in two ways: (1) instantaneous feedback plasticity, such that the finch sings differently
because he cannot hear himself; and (2) maintained plasticity, such that the finch retains a “memory” of the
previous song that was subjected to auditory feedback at least long enough for the memory to affect
production of the next song. Instantaneous feedback plasticity will be monitored by comparing the song
similarity and amplitude of song produced during silence and during masking noise. A window will be made
in the masking noise between 5 – 7 kHz such that song similarity and amplitude can be monitored.
Maintained plasticity will be monitored through comparison of the songs produced and corresponding
activity during silence throughout the 4-hour recording session. Preliminary Data indicate that neither of
these forms of plasticity in song production occur during the time course of the experiment.
Changes in song between recording sessions. Changes in song production may require a period of
sleep or quiet waking for consolidation of plasticity induced during the recording session. Thus, data will
NOT be compared across days. We have already shown that there is a sensitive period in development for
expression of the tutor song response in HVC (Nick and Konishi, 2005a). The current study focuses
exclusively on the tutor song response during time periods of several hours. Each recording session will be
treated as a separate experiment, with all three aims executed within each day.
Saline injections. For the middle ear paralysis experiment, a set of control saline injections will
complement the lidocaine injections. Saline injections will control for nonspecific isoflurane, stress, or fluid
effects that are not due to middle ear paralysis.
EXPERIMENTAL METHODS
Animals and surgery. The same set of chronically implanted finches will be used for aims 1-3. Please see
Aim 1 for details.
Triodes, microdrive, video monitoring, and lidocaine/saline injections. For this section, see Aim 1
except for details of perturbation of auditory feedback:
For the masking noise experiment, all birds will be presented with sets of 50 - 100 trials consisting of
multiple stimuli, in random order: silence, the tutor song (1 copy), conspecific song (1 copy), a recent copy
of BOS (<72 hrs old; 1 copy), and 4 copies of masking noise (15 sec duration with a 5 –7 kHz window). The
intertrial interval will be 20-s. Thus, masking noise will be played for 60 out of every 160 seconds. For the
middle ear paralysis experiment, playback stimuli will be identical except the 4 copies of masking noise will
be replaced with silence trials. Birds will be temporarily anesthetized with isoflurane and injected in the
middle ear with either 0.9% saline or 2% lidocaine hydrochloride. A small hole in the skull dorsoventral to
the ear canal opens directly to the middle ear (E. Rubel, personal communication; personal observations).
Song recording and masking noise playback. For song recording, male zebra finches will be isolated in
acoustic attenuation chambers. Songs and masking noise will be recorded, digitized, and played back at
44,100 Hz. Songs will be edited with MATLAB (Mathworks, Natick, MA). All songs for playback will be
recorded with no female present (undirected).
Masking noise for playback (created with MATLAB) will be band-pass filtered such that the noise
contains no energy at frequencies between 5 – 7 kHz and above 10 kHz. Power in frequencies between 5 –
7 kHz will be used to determine the onset and offset of singing and the amplitude and sequence of syllables
that are produced.
Analysis of Singing/Masking noise Playback Data. All data will be analyzed with Matlab functions. A
MATLAB function will be used to find songs. For both perturbed and normal singing data sets, a trained
blind human observer will check the sound segments identified by MATLAB as songs. Neuronal activity
patterns during the motif will be assessed for the tutor song selective neurons (identified in the Song
Playback Studies that precede the Feedback Perturbation experiment). The amount of each neuron’s
activity during perturbed and normal singing will be compared using an unpaired, two-tailed Student’s t-test.
I predict that perturbation of auditory feedback will specifically decrease the activity of tutor song selective
HVC neurons.
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Aim 3. Identify the destination of the matching signal.
Hypothesis: The matching signal is conveyed to the Anterior Forebrain Pathway (AFP), known to
have roles in song learning.
Prediction: Antidromic identification of HVC neurons that carry the matching signal will reveal that
they project to Area X (basal ganglia) of the AFP.
HVC contains three major subtypes of neurons defined by where they project: (1) basal ganglia (Area X;
HVC-X), (2) the motor cortex analog (Robustus Arocopallialis; HVC-RA), and (3) within HVC (interneurons).
Only a subset of these may carry the matching signal. There are two well-established methods that could
be used to determine the identity of the tutor song selective neurons: antidromic techniques and filling the
cells with vital dye. Dye fills require restraint of the finch, which may affect neuronal activity. In contrast,
antidromic techniques do not require restraint. To decrease the potential plasticity induced by repeated
antidromic stimulation, I will execute the antidromic identification tests between and not during recording
sessions. I will cautiously interpret data that suggest that interneurons are responsive to tutor song (see
Controls and Potential Results below).
We hypothesize that the HVC neurons that respond selectively to tutor song project to Area X, which is
part of the corticothalamic-basal ganglia loop known as the Anterior Forebrain Pathway (AFP). The AFP
clearly has a role in song development, since lesioning a nucleus in this pathway in juveniles abruptly
disrupts song learning (Bottjer et al., 1984).
EXPERIMENTAL PLAN
To test the hypothesis that HVC-X projection neurons carry the matching signal, I will examine tutor song
selectivity in HVC neurons in awake juveniles and identify their projection targets using antidromic
techniques (Fig. 14). Awake juveniles in the early sensorimotor phase (50 – 65 days) will be chronically
implanted with recording and stimulating electrodes. After each recording session that addresses Aim 1 or
Aim 2, neurons will be tested using antidromic techniques (Preliminary Data, Figs. 8 - 9). Spikes recorded
during the Aim 1/2 recording session and during antidromic testing will be sorted (clustered) together,
without regard or knowledge of spike timing or the context of each action potential.
CONTROLS
Tests for antidromicity. Two tests will be used to distinguish between antidromic activation and synaptic
excitation, which is a concern since HVC contains interneurons that can be activated through antidromic
activation of either Area X or RA. Rheobase (minimum current necessary to stimulate a spike) will be
established at the beginning of each experiment. Stimulation current will be equal to rheobase, with the
established standard duration of 200 μsec (Ranck, 1975). After the experiment, location of the stimulating
electrodes to Area X and RA will be confirmed with cresyl violet histology (see Aim 1 Controls).
A short and invariant latency. The time between the beginning of the stimulus and the peak of the
extracellular spike will be compared for 10 stimuli that were not preceded by a spontaneous spike within a
time period equaling T. T is the absolute refractory period plus 2 times the antidromic latency (Lipski, 1981).
The absolute refractory period will be conservatively estimated at 300 μsec. The antidromic latency will be
experimentally determined as maximal delay between the beginning of the stimulus and the peak of the
antidromic spike. Fixed latency will be defined as spike latency variance ≤ 200 μsec. Variances of ≥ 200
μsec will indicate that the cell is activated through synaptic mechanisms and not through antidromic
stimulation.
Collision of antidromic response with orthodromic spontaneous spikes. Spike collision is the best test for
antidromicity and will be applied to every cell recorded. Area X and RA will be stimulated during and after
the time period T, relative to the spontaneous spike. Antidromic stimulation will be revealed by a consistent
ability to stimulate the neuron after, but not during, T.
Synaptic activation of interneurons. Stimulation of Area X and RA causes synaptic activation of neurons
within HVC (Hahnloser et al., 2002; M. Fee, personal communication). Interneurons can be activated within
the same latencies as projection neurons. Cells that are not antidromically stimulated by electrodes that are
within Area X and RA will tentatively be categorized as ‘interneurons’ (see Potential Results).
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Figure 14. Schematic representation of the experiment proposed in Aim 3, executed during the early
sensorimotor phase. This aim will delve into the motor circuitry (see brain below). Five of the brain song nuclei
are shown. Anterior is right; dorsal is up. The nucleus HVC, also recorded in the other 2 aims, will be recorded
with a triode. All recorded neurons HVC will be tested with antidromic stimulation of Area X and RA. The Anterior
Forebrain Pathway is indicated by the gray nuclei.
Stimulation of fibers of passage. The nucleus HVC has only two efferent targets: Area X (basal ganglia) and
the nucleus RA (motor cortex analog). Stimulating fibers of passage is generally not a concern, since these
nuclei are located near the most anterior (Area X) and posterior (RA) extents of the finch cerebrum. However,
if very high amplitude currents are used, it may be possible to stimulate both sets of fibers. Therefore, stimuli
will be the lowest current amplitude up to 500 μA that reliably evokes a spike. If 500 μA fails to evoke a spike,
the neuron will be considered “not projecting” to the stimulated nucleus. A stimulus of amplitude 500 μA and
duration 200 μsec will travel a spherical radius of approximately 2 mm (Ranck, 1975), which is enough to
stimulate the nucleus in which the electrode is placed without stimulating the other target nucleus or HVC.
EXPERIMENTAL METHODS
Animals and surgery. The same set of chronically implanted finches will be used for aims 1-3. Please see
Aim 1 for details. The cathode of the bipolar stimulating electrode will be placed in the nucleus to be
stimulated.
Multi-electrodes, microdrive, and video monitoring. For this section, see Aim 1 except for details of the
stimulating electrode implantation:
Stimulating electrodes will be tetrodes made of 25-μm nichrome-formvar. One lead of each tetrode will be
wired to the 10-pin connector that connects the electrodes from the bird’s head to the headstage. Tetrodes
instead of a single wire will be used for rigidity, which will facilitate placement of the stimulating electrode in the
appropriate deep brain area (Area X or RA). Stereotaxic coordinates, combined with electrophysiological
monitoring during surgery, will ensure implantation of the stimulating electrodes in the correct brain area. Both
Area X and RA have unique electrophysiological activity profiles under ketamine-xylazine anesthesia.
Antidromic techniques. Stimulation of Area X and RA will be achieved with a Master-8 stimulator and an
IsoFlex Stimulus Isolation Unit (A.M.P.I., Israel). Orthodromic-antidromic spike collision will be achieved by
triggering the Master-8 off the spontaneous orthodromic spikes using an APM window discriminator (FHC,
Bowdoinham, ME). There is an inherent delay of 1-msec in the electronics from trigger to antidromic stimulus.
The least amount of current that can routinely elicit an antidromic spike (rheobase) will be used.
Finding other action potentials of the antidromically-stimulated neuron. Identification of the synaptic
target of a single unit must be done in the larger context of identifying that neuron’s activity patterns during
playback of auditory stimuli (Aim 1) and during singing (Aim 2). To link activity patterns to an identifiable HVC
neuronal subtype, I will cluster all action potentials from the preceding Aim 1 or Aim 2 recording session with
the action potentials that are obtained from the antidromic tests that follow. Each clustered neuron will be
examined for spike collision. If the clustered unit collides with the antidromically-stimulated spike, it will be
identified as a projection neuron. Spike timing information will be extracted from the clustered data and
examined relative to auditory stimuli and song behavior. Neurons that do not pass the spike collision test will
be classed as putative interneurons.
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4. Test a specific mechanism through which the template-matching signal may shape
behavior.
Hypothesis: The temporal relationships between HVC brain activity and song behavior change during
song learning, revealing a potential mechanism for activity-dependent shaping of vocal behavior.
Predictions: During the sensorimotor phase, HVC activity will (1) correlate less with behavior than in
adults and (2) outlast the vocalization.
The problem of delays between motor command and sensory feedback poses severe constraints on any
sensorimotor system. Known cellular mechanisms of activity-dependent plasticity require close temporal
association of action potentials in neurons that exhibit activity-dependent strengthening (e.g., neurons that fire
together, wire together). The song system of juvenile finches that are actively learning song is more electrically
active than that of adults (Nick and Konishi, 2005a). Therefore, I propose a hypothesis that would enable
temporal overlap of motor command and sensory feedback: Higher order motor circuits (in HVC) that drive
vocalization are active longer than those in adults, allowing sensory feedback to shape synaptic connectivity
via activity-dependent mechanisms. I will test this hypothesis by comparing HVC neuronal population activity
during song behavior across development. My hypothesis predicts that HVC activity will outlast the
vocalization in actively learning finches, but not in adults.
EXPERIMENTAL PLAN
This experiment aims to compare activity in the same neuronal population across developmental stages.
The best method for achieving this goal is multi-unit recording. Previously, I have successfully obtained
recordings for many weeks in developing finches (Nick and Konishi, 2005a, b). Ten juveniles in the early
sensorimotor phase (50 – 65 days) will be chronically implanted with multi-unit recording electrodes. After 3
days recovery, their vocalizations and corresponding brain activity will be recorded. These finches will not
experience auditory playback, as described above, since sound playback affects brain activity in vocal areas in
awake juveniles and may confound my results (Nick and Konishi, 2005a, b).
CONTROLS
Circadian effects. Because circadian effects on vocal activity in the song system are completely unknown,
birds will be kept on a strict 12:12 light cycle with vocal recordings for this experiment occurring only during the
first five hours of waking.
Directed versus Undirected Singing. The presence of a female finch affects song system activity during
singing. Thus, to decrease variability and increase control, only undirected singing (in the absence of a
female) will be studied. If time permits, I will also examine activity during directed singing across development.
EXPERIMENTAL METHODS
Animals and surgery. Please see Aim 1 for details of surgical implantation. Ten juvenile zebra finches age
50-65 will be implanted with two 25 μm multi-unit recording electrodes within HVC and a 25 μm reference just
outside of HVC.
Multi-unit electrodes and video monitoring. For this section, see Aim 1, since recording parameters will the
same. Only calls less than 300 msec in duration and with 500 msec of silence before and after will be
analyzed.
Analysis of multi-unit data. Multi-unit data will be analyzed relative to the vocalization. The root mean
square will be obtained for the voltage trace in 20-msec bins, beginning 300 msec prior to vocalization and
ending 60 msec after vocalization onset and beginning 60 msec prior to vocalization offset and ending 300
msec after the vocalization. The mean data for each bin will normalized to the maximum bin for each recording
day. The combined data for each bin, relative to the vocalization, will be compared between juveniles and
adults using two-way ANOVA.
SUMMARY
Both humans and songbirds are vocal learners that share behavioral and biological characteristics (Doupe
and Kuhl, 1999). Notably, both humans and songbirds exhibit a vocal learning phase during which
vocalizations are matched to learned species-typical sounds. The proposed experiments will test the
hypothesis that a template-matching signal occurs within a premotor song nucleus (HVC) during song learning
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and extend knowledge of the neural events that occur during vocal learning. The proposed study is specifically
designed to avoid pitfalls that have confounded previous studies, such as the use of anesthesia. Key aspects
of the putative matching signal will be investigated: (1) What information does the matching signal convey? (2)
Does it occur during singing? (3) What brain area receives the matching signal? (4) Do brain-behavior
relationships change during development and facilitate effects of the matching signal? I am particularly well
qualified to execute these experiments because of my extensive experience with electrophysiological
techniques in developing neurons and neural systems (Nick et al., 1996a; Nick and Ribera, 2000) and my
familiarity with the physiology of the developing HVC (Nick and Konishi, 2005a, b).
Future experiments will build on these findings by tracking and manipulating the putative matching signal
through the song system. Key questions for future study include: (1) How is the tutor song memory (template)
stored? (2) What brain space compares the template to auditory input? (3) How are changes in motor circuits
and behavior induced? Understanding the brain mechanisms of vocal learning may enable extension or
reinstantiation of vocal plasticity in humans and treatment of manifold communication disorders that affect our
society.
TIME-LINE
I propose to utilize the same juvenile finches for the first three aims, when possible. These aims will run
concurrently (Fig. 15), but I expect to move more quickly toward the primary goals of Aims 1 and 2, due to the
difficulty of the experiments described in Aim 3. I will begin to work on Aim 4 during the third year of funding.
Should my R01 not be renewed upon the first submission, I will support the laboratory with my remaining start
up funds and a grant from the John Merck Fund.
Due to the time delays inherent in working with breeding pairs and the extremely labor intensive techniques
involved, it would be impossible to complete these aims in less than 5 years. At the end of 5 years, several
key aspects of vocal learning in songbirds will be revealed: (1) the information encoded by a putative templatematching signal; (2) whether the putative matching signal occurs during singing; (3) the identity and targets of
the neurons that carry the putative matching signal; and (4) a potential mechanism for transforming the
template-matching signal into changes in behavior. Further progress in understanding vocal learning will be
difficult without this information.
Figure 15. Timeline of the proposed experiments. Darkness indicates
projected output. Expected publications are shown below.
E. Human Subjects
None.
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F. Vertebrate Animals
1. Description of the proposed use of animals. 200 male zebra finches, aged 45 – 65 days will be
utilized in the proposed work. The same finches will be used for all aims.
2. Justification. The neurophysiological mechanisms of vocal learning, a complex behavior, are
completely unknown. Therefore, computational modeling or cell culture experiments are not possible.
Due to the invasive nature of the experiments, use of humans to examine these questions would be
unethical. Therefore, the use of animals is warranted.
There are only six groups of vocal learners in the animal kingdom: humans, whales and dolphins, a
genus of bats, parrots, hummingbirds, and songbirds. Of these the best characterized and most
tractable for study is the songbird. Zebra finches are the favorite model for birdsong physiology, due
to their hardy physique, rapid breeding in captivity, and well-characterized behavioral development
and brain architecture. 200 finches will be used for the experiments, because a minimum of 10
finches is required for rigorous statistics and I expect a minimum success rate of 5%.
3. Veterinary care. Veterinary care will be provided by the University of Minnesota’s Research
Animal Resources Department. Finches will be observed daily. Any signs of ill health will be
reported immediately to the veterinarian in charge.
4. Minimization of discomfort. Finch discomfort will be minimized in a number of ways. Prior to
chronic implant surgery, finches will be anesthetized with a general anesthetic (ketamine/xylazine,
see Methods). Post-operative analgesia will be provided by injection with meloxicam.
5. Euthanasia. Finches will be euthanized with a systemic injection of sodium pentobarbital (300
μg/g). This method of euthanasia is widely used in the birdsong community. Sodium pentobarbital
results in a rather quick, painless death and yet enables perfusion of the brain with fixative, which is
required for histological analyses.
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excitability and secretory ability in Aplysia bag cell neurons. J Neurophysiol 76:3351-3359.
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SUMMARY STATEMENT
( Privileged Communication )
PROGRAM CONTACT:
Dan Sklare
(301) 496-1804
[email protected]
Release Date:
08/01/2006
Application Number: 1 K02 DC008521-01
Principal Investigator
NICK, TERESA A PHD, UNIVERSITY OF MINNESOTA TWIN CITIES
Review Group: CDRC
Communication Disorders Review Committee
Meeting Date: 06/21/2006
Council: OCT 2006
Requested Start: 12/01/2006
RFA/PA: PA00-020
PCC: VS20
Project Title: Mechanisms of vocal learning in the zebra finch
SRG Action: Priority Score: 184
Human Subjects: 10-No human subjects involved
Animal Subjects: 30-Vertebrate animals involved - no SRG concerns noted
Project
Year
1
2
3
4
5
___________
TOTAL
Direct Costs
Requested
98,373
98,373
98,373
98,373
98,373
_______________
491,865
Estimated
Total Cost
106,242
106,242
106,242
106,242
106,242
_______________
531,210
ADMINISTRATIVE BUDGET NOTE: The budget shown is the requested budget and has not been
adjusted to reflect any recommendations made by reviewers. If an award is planned, the costs will be
calculated by Institute grants management staff based on the recommendations outlined below in the
COMMITTEE BUDGET RECOMMENDATIONS section.
NEW INVESTIGATOR
1 K02 DC008521-01
NICK, T
2
CDRC
1 K02 DC008521-01 NICK, TERESA
SCIENTIFIC REVIEW ADMINISTRATOR’S NOTES
RESUME AND SUMMARY OF DISCUSSION: This Independent Scientist Award application requests
five years of support to study how auditory-selective neurons in a vocal-control nucleus (HVC) of the
zebra finch brain that are tuned to the learned song contribute to the matching signal and song
production. The study of learning and song production in birds is relevant to the development of
speech in humans. The Candidate has expertise in bird song, excellent training in electrophysiology
and will develop a recording technique (multi-electrode) allowing characterization of unit activity and
antidromic activation to identify projection neurons in awake behaving birds. Overall, this is a well
presented research application from a strong Candidate. There are a few concerns: some
experiments, particularly those addressing aim one, are not described in adequate detail. More detail
for the linear regression analysis is needed. The rationale might have been presented more clearly,
and more discussion of alternative approaches and interpretations should be included. Some of the
aims are not sufficiently focused to advance our understanding of the mechanisms that underlie vocal
learning, or the functional role of the auditory-selective neurons in the process. The research is
anticipated to generate interesting results. The request for support of the Investigator is appropriate
because developing the recording technique and carrying out the proposed studies will be difficult and
time consuming. The Candidate has the support of her department Chair, and will be free to commit up
to 90% effort to the research. The scientific environment includes good collaborators.
DESCRIPTION (provided by applicant): Communication disorders affect millions of people.
Understanding the neural bases of vocal learning will enable early diagnosis and effective treatment of
these diseases. There are a few nonhuman vocal learners, of which the songbirds offer the bestcharacterized model in terms of physiology and behavior. As with humans, the zebra finch songbird
learns its song in two phases: a sensory phase during which the song of an adult tutor is memorized
and a sensorimotor phase during which the birds own vocalizations are shaped through auditory
feedback to match the tutor song. The shaping of the vocalization requires that the comparison
between auditory feedback and the memory of the tutor song sculpt the song motor control circuitry.
We recently found that the tutor song selectively activates a key nucleus of the song premotor pathway
(Nick & Konishi, 2005a). This selective activation occurs only during waking and only during the period
of development when the tutor song memory is used to shape vocalizations. This suggests that the
comparison of auditory feedback with the tutor song memory generates an instructive matching signal
that is relayed to the premotor nucleus. There are 4 specific hypotheses: (1) responses of individual
neurons convey the degree of similarity between stimuli and the tutor song memory; (2) the matching
signal occurs during singing; (3) the matching signal is relayed to the basal ganglia; and (4) the
mechanism that transforms the matching signal into behavioral change involves sustained neural
activity in the song system that enables temporal overlap of motor command and sensory feedback and
subsequent activity-dependent plasticity. The study will utilize three powerful techniques in awake
juveniles: multi-electrode recording, which enables the stable assessment of the activity of many single
neurons, antidromic stimulation, which enables the identification of individual neurons, and long-term
population recordings. The ultimate goal is to use the matching signal to illuminate the role of memory
and sensation in shaping vocal behavior. The candidate, Dr. Teresa A. Nick, is uniquely qualified to
execute these experiments. She has received training on (1) the development of neurons and circuits
from Drs. Thomas Carew and Leonard Kaczmarek (Yale); (2) extrinsic modulation of neuronal
development from Dr. Angeles Ribera (Univ. Colorado); and (3) the development, state-dependent
modulation, and learning of birdsong from Dr. Masakazu Konishi (Caltech). She has published
extensively on neural development and has discovered the first evidence for a template-matching
signal. She has already applied several novel techniques to the song system and developed a new
method combining multi-electrode and antidromic techniques. The University of Minnesota provides the
ideal environment in which to pursue these experiments, due to strengths in auditory processing, multielectrode techniques, and antidromic methods.
CRITIQUE 1
1 K02 DC008521-01
NICK, T
3
CDRC
Candidate: Teresa Nick is qualified to carry out the proposed experiments, as she has extensive
training in electrophysiological methods and has generated novel and interesting data in the area of
vocal learning in songbirds. Thus, she has the expertise and initial data, upon which to build. The
proposed approach may advance our knowledge of the mechanisms of vocal learning during sensitive
periods. The Investigator has the potential to become a leader in her field, and the potential for the
proposed experiments to result in significant contributions is high. The number of publications from the
Investigator has not been particularly high (9 peer-reviewed publications over the course of 18 years,
starting as an undergraduate), but the publications have been of high quality and published in excellent
journals. Her proposal is thoughtful and well-organized, and her background and experience combine
to make this a strong proposal. If supported this work will provide Dr. Nick with the opportunity to learn
new techniques (triode/tetrode recording in awake behaving songbirds) and develop new hypotheses
for the mechanisms of developmentally-regulated vocal learning.
Career Development Plan: The likelihood that the proposed training plan will contribute substantially
to the development of the Candidate is high. Although the research plan is ambitious, developing
reliable triode/tetrode recordings in songbird brain would be a substantial advance. As described, the
plan would enable the Candidate to focus her efforts (90%) on research, which is an essential prerequisite for developing the new and challenging techniques proposed.
Research Plan: In general, the research plan is very strong. One general comment is that the
individual experiments should be described in greater depth in terms of methodological details, possible
outcomes and conclusions, and alternate outcomes and potential pitfalls.
As a first aim, the Candidate proposes to make triode recordings in HVC in awake behaving juvenile
birds during song playback, with the idea that this technique will confer much greater stability for
extended recordings, allow multiple neurons to be recorded, and enable better identification of
individual units. The various auditory stimuli and methods for presentation are not described in
adequate detail. The only stimuli mentioned are tutor song and the bird’s own song (BOS) – but not
other conspecific songs, which would seem to be an important control. This study will measure the
“number of action potentials” in neurons that are responsive to tutor songs relative to “other” songs
(presumably this means spike rates, post-stimulus time histograms [PSTHs], and/or other). It will also
be important to measure the exact proportion of HVC neurons that are or are not selective for tutor
song, and if not, whether they exhibit alternate preferences.
Aim 2 is to identify HVC neurons that respond to tutor song playback in juvenile birds using triode
recordings, and examine the activity of such neurons during song production with or without
perturbations of auditory feedback. The rationale is to test whether the activity of HVC neurons that
respond to hearing tutor song also receive auditory feedback during singing. Pilot data indicates that
playback of masking noise does not alter the amplitude or form of song production, and one neuron
showed a small but significant decline in spike rate when masking noise was presented during singing.
This is an important, but difficult, experiment. Dr. Nick will also use middle ear inactivation as an
alternate means of perturbing auditory feedback; this is a good idea, and might show larger effects.
One reason that only small-magnitude effects might be observed is that individual HVC neurons might
exhibit both pre-motor and auditory activity. Presumably this could be resolved in this study, and would
be very interesting. This is another example of something that needs to be discussed in more detail. It
will also be important to determine whether neurons that do NOT respond selectively to tutor song
playback show a change in activity during perturbation of auditory feedback during singing. There is no
a priori reason to think that the neurons that respond to passive playback of tutor song are the same
ones that may respond to auditory feedback. If these experiments go smoothly, the Investigator might
consider inactivating the higher-order auditory areas NCM and CMM. Recent evidence suggests that
one or both of these areas may be the repository of the template (these studies are not cited in this
proposal, which is an unfortunate oversight . . .). If a template signal in NCM and/or CMM is conveyed
to HVC, then inactivation of these areas would be expected to alter activity in one or more subsets of
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HVC neurons. In any case, this proposed study will generate important results, but may not resolve
whether the response to tutor song or to auditory feedback in HVC serves as “the matching signal”.
Aim 3 is to use antidromic identification techniques to determine if the HVC neurons that respond to
tutor song project to Area X in juvenile birds. The Investigator presents preliminary data showing the
feasibility of this technique, and the experiment seems straightforward. Although the emphasis as
described is on Area X, it is known that HVC neurons that project to RA also have auditory sensitivity.
Thus, if tutor-selective neurons are projecting to Area X, does another class of auditory neurons in HVC
project to RA? This is not discussed. The Investigator needs to state clearly if different auditory stimuli
will be presented, combined with antidromic stimulation in both Area X and RA.
Aim 4 is to pursue an interesting aspect of the preliminary data that suggests that multi-unit activity in
HVC is greater in juveniles and then decreases during the course of song learning. This study will test
the degree of correlation between activity in HVC and song production, as well as measure the overall
amplitude and duration of activity. The results will provide an initial documentation of patterns of neural
activity in HVC during song production at different stages of vocal development, which are important
normative data.
The Candidate should avoid overstating conclusions based on previous findings. She has made an
important discovery, which is that neurons in the cortical song-control nucleus HVC are tuned to the
tutor song that serves as the model for learning during a restricted period of development. This finding
raises the possibility that HVC neurons tuned to the tutor song may participate in the process by which
birds are able to gradually match their vocal output to that of the tutor song. However, it does not mean
that the she has “found the instructive signal” (p. 19) or that HVC “receives a tutor song templatematching signal during waking within a restricted period of development”. There is no evidence that the
auditory tuning of HVC neurons is used for template matching. Indeed, this is the fundamental question
that the current proposal addresses. Further, the idea that there is a prevalent view in which the AFP
stores the tutor song memory in order to serve as the template is over stated. In fact, one of the aims is
to test the idea that a “template-matching” signal will be projected to the AFP (Area X) from HVC; such
a signal might look like the auditory tuning discovered in HVC. Also the implicit idea that the template
will be localized to only one brain region is potentially an over-simplification; template storage and
template matching may be carried out in multiple locations.
Simply put, the importance of Dr. Nick’s previous work is considerable: the search for any auditory
tuning that might constitute physiological evidence for a “template” has not yet been successful. Her
discovery that the tutor song serves as the most effective stimulus for HVC neurons in awake juvenile
birds is therefore a key discovery that may lead to studies of how such auditory tuning is used in the
process of song refinement.
A postdoctoral trainee who will have a major involvement in this proposal (Dr. Aoki, see p. 20) was not
listed under Other Significant Contributors (no Biographical Sketch was included). Despite the fact that
Dr. Aoki’s salary is from another source, she should be listed given that she will be contributing to two
of the four aims.
Environment and Institutional Commitment: The environment is excellent, and includes excellent
colleagues, one of whom has expertise in triode recordings and will serve as a consultant. In addition,
the Investigator has strong support from her department chair. Dr. Nick has established at least initial
facility with all of the techniques used in the proposal, and has sought out collaborations with other
investigators to enhance the research.
Vertebrate Animals: No concerns.
CRITIQUE 2
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Candidate: This is a strong Candidate with broad education and training in Psychology, Zoology, and
Neuroscience, whose area of expertise is electrophysiological approaches to neural plasticity and
learning. The Candidate is clearly an independent researcher who has developed a novel multi-unit
recording approach for identifying the neural representation of auditory memories in the songbird brain.
The results will either strengthen established interpretations of prior results, or lead the way to a new
understanding of the coding of auditory memories.
The Candidate’s research productivity is strong, although the number of publications is not high.
However, the breadth of the research areas in which she has published is impressive. In addition, her
recent songbird work, reporting chronic recordings from the brains of developing birds, is labor
intensive. She is a recently established faculty member (her position at UM started in 04), who recently
obtained an NIH funded R01 and two smaller grants from private foundations for her work.
Her current research is an extension of work that she began as a post-doctoral fellow in the lab of
Masakazu Konishi at CalTech. She addresses a long-standing issue in neuroscience: how the brain
stores a memory of a past event (in this case, an auditory memory), and how this memory can then be
referenced to shape present behavior (in this case, a song pattern). It seems highly likely that her
research findings in songbirds will provide important insight into the nature and treatment of human
vocal disorders.
Given her extensive education and training in electrophysiological techniques, current approach to a
difficult important issue in neuroscience, and demonstrated ability to generate important new findings,
Dr. Teresa Nick is a strong Candidate for a K02 award.
Career Development Plan: The Candidate states that her motivation in applying for this award is to
focus intensively on the development of her research program. Because her laboratory is still at an
early stage of development, and her R01 was funded for only three years, she indicates that a funding
gap is likely if she is not able to dedicate the majority of her time to the laboratory. Gaps in funding will
likely lead to such things as an increased teaching load, which the Candidate feels would further
jeopardize chances for successful renewal of her R01. Thus, K02 funding presents a means by which
she can focus 90% of her time on the development of her laboratory and research program and limit
her institutional commitments to 10%.
Overall, the research development plan outlined by the Candidate could place her laboratory among an
elite group of songbird electrophysiology labs around the country. However, her career development
plan would be strengthened by greater collaboration with other active researchers. While the
collaborations listed may provide limited opportunity for growth in new directions, it is worth noting that
the Candidate’s primary motivation in applying for a K02, is to dedicate most of her time to her
research.
Research Plan: Before a songbird can learn to sing, it must first hear an example of adult song and
store a long-term memory of that adult song (this memory is often referred to as the ‘template’). Song
learning then appears to involve a trial-and-error process that requires auditory feedback – in other
words, the memory of the adult song must be referenced to correct errors in vocal production. In 2005,
the Candidate reported that she had identified a putative matching (or template) signal in the brain of
juvenile birds that are learning song; this signal was located in HVC, a brain region positioned at the top
of a hierarchical forebrain network that controls song. These findings stand in contrast to the most
widely held view, which is that the template must lie somewhere downstream from HVC. (Although the
evidence for this has never been overwhelming, especially since most of the data came from adult birds
that had already learned their songs.) The research plan is to extend her original 2005 finding of tutorselective neurons in HVC. Overall enthusiasm for the proposed program of research is high, although
the 3rd and 4th aims are weaker than the first two.
Aim 1: Examine the precision of neural tuning of single HVC neurons during song development. This
experiment is a modification of the Candidate’s original study showing that HVC of juvenile birds shows
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a selective response to the tutor song. However, the objective is to compare the responses of individual
HVC neurons as birds hear their own partially-learned song, various other auditory stimuli, and the tutor
song. The number of action potentials generated during playback of the tutor song will be compared to
the number of action potentials generated during other auditory events. The objective is to determine
whether the tutor-selective neurons in HVC generate an ‘all-or-none’ signal (only respond to the tutor
song) or a graded signal (respond best to tutor song, but respond to other sounds based on similarity to
the tutor song). This experiment is interesting regardless of the outcome.
Aim 2: Identify and manipulate the activity of tutor-selective neurons during singing. This aim is to
determine whether HVC neurons that respond to playback of the tutor song are active during singing. If
so, the plan is to determine if perturbed auditory feedback alters the singing-driven activity of these
neurons (masking noise and middle ear paralysis will be used to perturb auditory feedback). The
Candidate hypothesizes that singing-driven activity in these neurons is dependent on auditory input that
approximates the tutor song. Thus, these neurons could serve as a real-time matching system,
responding only (or best) when the bird produced a vocal pattern that resembled or matched the tutor
song. This experiment will generate interesting results.
Aim 3: Identify destination of the ‘matching signal’. This aim is to determine which of HVC’s three
neuron types carries the putative matching signal. The Candidate hypothesizes that the matching signal
will be carried by HVC neurons that project into a basal ganglia circuit that is necessary for vocal
learning. Antidromic electrophysiological techniques will be used to identify the efferent targets of tutorselective neurons. A potential weakness of this approach is that recordings are made with a multielectrode array, and it will not be possible to anatomically label (dye fill) the tutor-selective neurons.
Moreover, the Candidate does not discuss how the results will be interpreted if the tutor-selective
neurons project to RA (HVC’s other efferent target), or are HVC interneurons.
Aim 4: In juveniles, test whether HVC activity correlates less with behavior in adults, and whether HVC
activity in juveniles outlasts vocalization. The Candidate predicts that when HVC activity is measured
across the period of vocal development, she will find that HVC activity in juveniles will exhibit a lower
correlation with behavior that will gradually improve as birds learn their songs, and that HVC activity in
juvenile birds will ‘outlast’ the vocalization, allowing sensory feedback to shape HVC circuits towards
the learning goal. Both predictions are interesting, but there is no consideration of how negative results
will be interpreted.
Training in the Responsible Conduct of Research: There are no concerns related to the proposed
course of training.
Environment and Institutional Commitment: Institutional commitment to the development of the
Candidate’s research career is strong. The Department will reduce her teaching and institutional
commitments to 10% upon funding of this proposal, leaving her with a 90% commitment to research..
Budget: There are no concerns.
CRITIQUE 3
Candidate: Teresa Nick is an excellent Candidate for a K02 fellowship at the Univ. of Minnesota.
Although she has only recently joined the faculty and has not fully established her research program,
she has great potential. She is addressing difficult experimental questions that are central to the
advancement of the field of birdsong research, and may make outstanding contributions to the field.
She has generated high quality data and publications in the labs of her previous Mentors. Her previous
research covered a wide range of models, from cellular to circuits and complex systems, resulting in
significant contributions. She has not published a large number of papers, but the difficulty related to
the experimental approaches is a reasonable justification. Her research proposal demonstrates her
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ability to formulate long-term research plans and career goals. She has excellent training and the
expertise to carry out the proposed experiments.
Career Development Plan: The award would allow the Candidate to dedicate her efforts towards
research and be relived from substantial teaching and institutional responsibilities. This is especially
important, because of the nature of the proposed experiments that require full-time involvement. Her
goal is to not have research productivity reduced, which could adversely impact her ability to retain
funding. The proposed plan relates directly to the Candidate’s stated career goals. Although
collaborations are not a major strength of the application, the Candidate will likely gain further expertise
in specific electrophysiology techniques and surgical methods through interactions with other scientists
(David Redish, at Univ. Minnesota, and Stephanie White, at UCLA). The Candidate states that she will
attend an annual training session on the Responsible Conduct of Research, but there is no mention of
specific content and duration of training.
Research Plan: The Candidate proposes an exciting approach to address fundamental questions in
the field of vocal learning. The proposal is generally well-written and the hypotheses are clearly stated.
The proposed experiments are supported by substantial preliminary data and should advance the field
considerably regardless of the results obtained.
Specifically, the Candidate has evidence that neuronal cells within HVC, a major song nucleus in the
zebra finch brain, respond selectively to the sound of the tutor’s song. This finding is exciting and
potentially highly relevant to the field, as it may represent the first evidence for an acquired memory of
the tutor’s song (the so-called acquired template) that will guide the bird’s own vocal development. The
key to this discovery was the recordings in awake birds, since the responses in the song system are
highly sensitive to behavioral state. The recordings in juveniles during the early sensorimotor phase of
vocal learning demonstrate the persistence and dedication of the researcher to the project.
The Candidate proposes to extend these findings. In the first Aim, she will determine if the song
responses of HVC neurons in juveniles are proportional to the degree of similarity between the stimulus
and tutor songs. For this purpose she will use multi-electrode (triode) recordings and spike sorting and
clustering algorithms developed by her collaborator A. Redish. She will use a series of the bird’s own
song (BOS) with varying degrees of similarity to the tutor song for the primary comparison, as well as
various other auditory stimuli as controls. This is a well thought out experiment and the results should
be informative. A relatively minor issue is that it is not clear that the BOS recorded at earlier ages will
provide a broad enough range of songs with different degrees of similarity to the tutor song for a
regression analysis, especially for recordings performed at the earlier ages, when BOS may still be very
dissimilar from the tutor’s song. Thus, it may be necessary to generate also a set of artificial stimuli that
differ from the tutor’s song by defined amounts of specific song parameters for a clear correlation
analysis. In addition to examining the overall response to song, it would be interesting to examine
whether tutor song selective HVC neurons respond preferentially to specific components of the tutor’s
song, and whether different units pay attention to different components. The Candidate did not discuss
the expected frequency of HVC units that show selective responses to tutor’s song, to give a clearer
indication of the amount of effort required to achieve the proposed goal. Also, she did not propose to
examine tutor song selectivity in naïve juveniles. If the phenomenon observed reflects an internalized
template, it should be absent or less obvious in birds that have not yet been exposed to the sound of
conspecific song. A comparison between the responses before vs. after such exposure would provide
the most direct evidence that the responses to tutor song were acquired through experience.
In the second Aim, the Candidate will examine the effect of disruptions in auditory feedback on the
recorded activity of HVC neurons during singing. This is a central tenet that has been untested in the
field, namely that auditory information reaches the nuclei that encode the vocal motor program during
singing, in order to potentially modify vocal motor representations. The major difficulty lies in the fact
that vocal motor neurons are activated during singing, which makes it difficult to identify concomitant
sensory responses triggered by auditory feedback. The Candidate has produced some very tantalizing
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preliminary data suggesting that she has identified a component of the activity of vocal motor neurons
in HVC that corresponds to auditory feedback activity. Namely, a significant decrease in the activity
(spike rate) is observed when comparing singing with or without a masking noise. The rationale is that
the mask disrupts auditory feedback from singing, resulting in the observed drop in activity. She now
intends to systematically test this effect in identified HVC neurons that respond to tutor song
stimulation. For auditory feedback disruption she will use masking noise or the temporary paralysis of
the middle ear with a local anesthetic. For the latter procedure, it is not clear that the birds would
recover from anesthesia and sing while the local anesthetic is still effective. Are there any data to
support this technique? In general, this is an exciting aim the experiments are likely to be informative.
The third Aim is to identify the neurons that respond selectively to the tutor’s song between the two
types of projection neurons in HVC, X- and RA-projecting cells. This may identify the target of the
processed auditory responses in HVC (towards the motor pathway or the anterior pathway involved in
vocal plasticity). This is a difficult experiment, as it involves methods to test for antidromic activation in
conjunction with the recording of auditory responses. The implantation of stimulating tetrodes to the
desired targets will be required in addition to the recording triodes. If successful, this is another very
strong and important component of the proposal that will raise further intriguing questions. For example,
if tutor song-selective cells turn out to be X-projecting, what is the functional relevance of activating the
anterior forebrain pathway when these cells are activated by a matching stimulus? Or perhaps the
activation of these cells might have an inhibitory effect on the final output of that pathway and on vocal
plasticity.
In the fourth aim, the Candidate will examine the duration of the activity of HVC neurons during singing
to test the prediction that such activity extends further (beyond the end of vocalizations) in juveniles
than in adults. Although this experiment is also likely to be informative, based on the preliminary data, it
will not necessarily demonstrate that auditory feedback may shape motor programs in juveniles. Even if
the recorded activity in juveniles extends beyond the end of the vocalizations, it is unclear whether this
extension reflects auditory feedback, an extended motor-related activity that is not tightly correlated
with the vocalization emitted, or both. Thus, this experiment seems to be the weakest in terms of testing
the proposed hypothesis.
Environment and Institutional Commitment: There are clear signs of institutional commitment and
support for the Candidate as an independent scientist and integral part of the research program. The
Univ. on Minnesota has a high commitment to scientific research and provides an excellent
environment for the Candidate’s further growth in the neurosciences, including interactions with several
other well established colleagues, opportunities for collaborations, and exposure to other researchers
through seminars and visits.
Budget: The period and amount of support appear to be appropriate for the Candidate’s goals and the
proposed aims. This support will be important if the Candidate encounters difficulties in renewing her
current R01.
Vertebrate Animals: The animal care provided is adequate. There are also adequate measures to
avoid unnecessary pain and discomfort to the animals, and the number of animals to be used is well
justified.
THE FOLLOWING RESUME SECTIONS WERE PREPARED BY THE SCIENTIFIC REVIEW
ADMINISTRATOR TO SUMMARIZE THE OUTCOME OF DISCUSSIONS OF THE REVIEW
COMMITTEE ON THE FOLLOWING ISSUES:
VERTEBRATE ANIMALS: The committee has no concerns regarding the number of animals
proposed for use. All procedures within this application, including husbandry, surgical, anesthetic,
analgesic and euthanasia, are appropriate and have been approved by the Investigator’s Institutional
Animal Care and Use Committee.
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SCIENTIFIC REVIEW ADMINISTRATOR’S NOTES: Responsible Conduct of Research – A course on
the responsible conduct of research is mentioned but the course contents are not adequately
described, so it is not possible to determine if the course fulfills the requirements. Clarification on this
must be provided to the NIDCD training program director before any potential award can be made.
COMMITTEE BUDGET RECOMMENDATIONS: If approved for funding, the budget is recommended
as requested.
NOTICE: The NIH has modified its policy regarding the receipt of amended applications.
Detailed information can be found by accessing the following URL address:
http://grants.nih.gov/grants/policy/amendedapps.htm
NIH announced implementation of Modular Research Grants in the December 18, 1998 issue
of the NIH Guide to Grants and Contracts. The main feature of this concept is that grant
applications (R01, R03, R21, R15) will request direct costs in $25,000 modules, without
budget detail for individual categories. Further information can be obtained from the Modular
Grants Web site at http://grants.nih.gov/grants/funding/modular/modular.htm
MEETING ROSTER
Communication Disorders Review Committee
NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS
CDRC
June 21, 2006 - June 22, 2006
CHAIRPERSON
GILLAM, RONALD B., PHD
PROFESSOR
COMMUNICATION SCIENCES AND DISORDERS
JESSE H. JONES COMMUNICATION CENTER
UNIVERSITY OF TEXAS AT AUSTIN
AUSTIN, TX 78705
MEMBERS
BEESON, PELAGIE M PHD, PHD *
ASSOCIATE PROFESSOR
DEPARTMENT OF SPEECH AND HEARING SCIENCES
UNIVERSITY OF ARIZONA
TUCSON, AZ 85721
BIRK, DAVID E, PHD *
PROFESSOR
DEPARTMENT OF PATHOLOGY, ANATOMY
AND CELL BIOLOGY
JEFFERSON MEDICAL COLLEGE
PHILADELPHIA, PA 19107
BOATMAN, DANA F., PHD
ASSOCIATE PROFESSOR
DEPARTMENT OF NEUROLOGY
JOHNS HOPKINS UNIVERSITY
SCHOOL OF MEDICINE
BALTIMORE, MD 212877222
BOPPANA, SURESH B, MD
ASSOCIATE PROFESSOR
DEPARTMENT OF PEDIATRICS & MICROBIOLOGY
UNIVERSITY OF ALABAMA AT BIRMINGHAM
BIRMINGHAM, AL 352331711
BOTTJER, SARAH W., PHD *
PROFESSOR
DEPARTMENT OF BIOLOGICAL SCIENCES
UNIVERSITY OF SOUTHERN CALIFORNIA
LOS ANGELES, CA 900892520
CAMPAGNARI, ANTHONY A, PHD *
PROFESSOR
DEPARTMENT OF MICROBIOLOGY AND IMMUNOLOGY
SCHOOL OF MEDICINE AND BIOMEDICAL SCIENCE
STATE UNIVERSITY OF NEW YORK AT BUFFALO
BUFFALO, NY 14214
CARNEY, LAUREL H., PHD
PROFESSOR
DEPT. OF BIOMEDICAL & CHEMICAL ENGINEERING,
& ELECTRICAL ENGINEERING & COMPUTER SCIENCE
SYRACUSE UNIVERSITY
SYRACUSE, NY 132445290
CATTS, HUGH W , PHD *
PROFESSOR AND CHAIR
UNIVERSITY OF KANSAS
SPEECH-LANGUAGE-HEARING
LAWRENCE, KS 66045
CHAN, ROGER W, PHD *
ASSISTANT PROFESSOR
DEPARTMENT OF OTOLARYNGOLOGY - HNS
UNIVERSITY OF TEXAS
SOUTHWESTERN MEDICAL CENTER
DALLAS, TX 753909035
CHEATHAM, MARY ANN, PHD
RESEARCH PROFESSOR
DEPARTMENT OF COMMUNICATION SCIENCES &
DISORDERS
NORTHWESTERN UNIVERSITY
EVANSTON, IL 60208
CLELAND, THOMAS A, PHD *
PROFESSOR
NEUROBIOLOGY AND BEHAVIOR
CORNELL UNIVERSITY
ITHACA, NY 14853
COLLINS, LESLIE M., PHD *
ASSISTANT PROFESSOR
DEPT OF ELECTRICAL & COMPUTER ENGINEERING
DUKE UNIVERSITY
DURHAM, NC 27708
DEMARIA, THOMAS F, PHD *
PROFESSOR
DEPARTMENT OF OTOLARYNGOLOGY
COLLEGE OF MEDICINE
OHIO STATE UNIVERSITY
COLUMBUS, OH 43210
DI LORENZO, PATRICIA M, PHD *
PROFESSOR
DEPT OF PSYCHOLOGY
BINGHAMTON UNIVERSITY
BINGHAMTON, NY 139026000
DRONKERS, NINA F., PHD
DIRECTOR
CENTER FOR APHASIA & RELATED DISORDERS
VA NORTHERN CALIFORNIA HEALTH CARE SYSTEM
MARTINEZ, CA 94553
EISENBERG, LAURIE S, PHD
SCIENTIST II
CHILDREN'S AUDITORY RESEARCH
AND EVALUATION CENTER
HOUSE EAR INSTITUTE
LOS ANGELES, CA 90057
FADOOL, DEBRA A., PHD
ASSOCIATE PROFESSOR
PROGRAM IN NEUROSCIENCE & MOLECULAR
BIOPHYSICS
FLORIDA STATE UNIVERSITY
TALLAHASSEE, FL 32306
JOHNSON, JAMES F, PHD *
ASSOCIATE PROFESSOR
DEPARTMENT OF PSYCHOLOGY
FLORIDA STATE UNIVERSITY
TALLAHASSEE, FL 32306
FOWLER, CAROL A, PHD *
PRESIDENT AND DIRECTOR OF RESEARCH
HASKINS LABORATORIES
NEW HAVEN, CT 06511
KANDLER, KARL , PHD *
ASSOCIATE PROFESSOR
DEPARTMENT OF NEURIOBIOLOGY
UNIVERSITY OF PITTSBURGH
PITTSBURGH, PA 15261
FRITZ, ANDREAS , PHD *
ASSOCIATE PROFESSOR
DEPARTMENT OF BIOLOGY
EMORY UNIVERSITY
ATLANTA, GA 30322
KANWAL, JAGMEET S., PHD
ASSOCIATE PROFESSOR
DEPARTMENT OF PHYSIOLOGY & BIOPHYSICS
GEORGETOWN UNIVERSITY MEDICAL CENTER
WASHINGTON, DC 20007
FRITZSCH, BERND , PHD *
PROFESSOR
DEPARTMENT OF BIOMEDICAL SCIENCES
CREIGHTON UNIVERSITY
OMAHA, NE 68178
KIDD, KENNETH K., MD, PHD *
PROFESSOR OF GENETICS, PSYCHIATRY AND BIOLOGY
DEPARTMENT OF GENETICS
YALE UNIVERSITY
NEW HAVEN, CT 06520
GENTER, MARY BETH , PHD *
ASSOCIATE PROFESSOR
UNIVERSITY OF CINCINNATI
ENVIRONMENTAL HEALTH
144 KETTERING LABORATORY
3223 EDEN AVE.
CINCINNATI, OH 45267-005
LOCKWOOD, ALAN H, MD *
PROFESSOR OF NEUROLOGY AND NUCLEAR MEDICINE
VA. WESTERN NY HEALTHCARE SYSTEM
CENTER FOR PET (115P)
3495 BAILEY AVENUE
BUFFALO, NY 14215
GRIGORENKO, ELENA L, PHD *
ASSOCIATE PROFESSOR
CHILD STUDY CENTER
AND DEPARTMENT OF PSYCHOLOGY
YALE UNIVERSITY
NEW HAVEN, CT 065113720
HELLER, STEFAN , PHD *
ASSOCIATE PROFESSOR
DEPARTMENT OF OTOLARYNGOLOGY
STANFORD UNIVERSITY
SCHOOL OF MEDICINE
STANFORD, CA 940358739
HERNESS, M. SCOTT, PHD
PROFESSOR
DEPARTMENT OF ORAL BIOLOGY
COLLEGE OF DENTISTRY
OHIO STATE UNIVERSITY
COLUMBUS, OH 43210
HULLAR, TIMOTHY E, MD *
ASSOCIATE PROFESSOR
DEPT OF OTOLARYNGOLOGY
WASHINGTON UNIVERSITY
ST LOUIS, MO 63110
JIANG, JACK J, MD, PHD *
ASSOCIATE PROFESSOR
DIVISON OF OTOLARYNGOLOGY
DEPARTMENT OF SURGERY
UNIVERSITY OF WISCONSIN MEDICAL SCHOOL
MADISON, WI 53706
MELLO, CLAUDIO V, MD, PHD *
ASSISTANT SCIENTIST
NEUROLOGICAL SCIENCES INSTITUTES
OREGON HEALTH AND SCIENCES UNIVERSITY
BEAVERTON, OR 97006
MERCHANT, SAUMIL N., MD *
ASSOCIATE PROFESSOR OF OTOLOGY &
LARYNGOLOGY
DEPARTMENT OF OTOLARYNGOLOGY
MASSACHUSETTS EYE & EAR INFIRMARY
BOSTON, MA 02114
MICHEL, WILLIAM C, PHD *
PROFESSOR
DEPARTMENT OF PHYSIOLOGY
UNIVERSITY OF UTAH
SALT LAKE CITY, UT 84108
MIDDLEBROOKS, JOHN C., PHD *
PROFESSOR
KRESGE HEARING RESEARCH INSTITUTE
MEDICAL SCHOOL
UNIVERSITY OF MICHIGAN
ANN ARBOR, MI 481090506
MOELLER, MARY PAT , PHD *
DIRECTOR
CENTER FOR CHILDHOOD DEAFNESS
BOYS TOWN NATIONAL RESEARCH HOSPITAL
OMAHA, NE 68131
NEWLANDS, SHAWN D., MD, PHD *
CHAIRMAN
DEPARTMENT OF OTOLARYNGOLOGY
UNIVERSITY OF TEXAS
GALVESTON, TX 775550521
NIGHORN, ALAN J, PHD *
ASSOCIATE PROFESSOR
UNIVERSITY OF ARIZONA
ARIZONA RESEARCH LABS
TUCSON, AZ 85721
RICE, MABEL L., PHD
DISTINGUISHED PROFESSOR
CHILD LANGUAGE DOCTORAL PROGRAM
THE UNIVERSITY OF KANSAS
LAWRENCE, KS 66045
RYUGO, DAVID K., PHD
PROFESSOR
DEPARTMENT OF OTOLARYNGOLOGY
& NEUROSCIENCE
JOHNS HOPKINS UNIVERSITY
SCHOOL OF MEDICINE
BALTIMORE, MD 21205
SCHICK, BRENDA S., PHD *
ASSOCIATE PROFESSOR
DEPARTMENT OF SPEECH, LANGUAGE,
AND HEARING SCIENCES
UNIVERSITY OF COLORADO
BOULDER, CO 803040409
SHAKER, REZA , MD *
PROFESSOR AND CHIEF
DIVISION OF GASTROENTEROLOGY AND HEPATOLOGY
MEDICAL COLLEGE OF WISCONSIN
MILWAUKEE, WI 53226
STEINSCHNEIDER, MITCHELL , MD, PHD
PROFESSOR OF NEUROLOGY & NEUROSCIENCE
DEPARTMENT OF NEUROLOGY
ALBERT EINSTEIN COLLEGE OF MEDICINE
BRONX, NY 10461
STONE, JENNIFER S., PHD
RESEARCH ASSISTANT PROFESSOR
DEPARTMENT OF OTOLARYNGOLOGY
HEAD AND NECK SURGERY
UNIVERSITY OF WASHINGTON
SEATTLE, WA 98105
THIBEAULT, SUSAN L, PHD *
ASSISTANT PROFESSOR
DEPARTMENT OF SURGERY/OTOLARYNOLOGY
HEAD AND NECK SURGERY
UNIVERSITY OF UTAH
SALT LAKE CITY, UT 841322301
TURNER, CHRISTOPHER W., PHD
PROFESSOR
DEPARTMENT OF PATHOLOGY & AUDIOLOGY
UNIVERSITY OF IOWA
IOWA CITY, IA 52242
TYLER, RICHARD S, MSC, PHD *
PROFESSOR AND DIRECTOR OF AUDIOLOGY
DEPARTMENT OF OTOLARYNGOLOGY
HEAD AND NECK SURGERY
UNIVERSITY OF IOWA
IOWA CITY, IA 52242
WARCHOL, MARK E., PHD *
RESERACH ASSOCIATE PROFESSOR
CENTRAL INSTITUTE FOR THE DEAF
DEPARTMENTS OF OTOLARYNGOLOGY AND ANATOMY
AND NEUROBIOLOGY
SCHOOL OF MEDICINE
WASHINGTON UNIVERSITY
ST. LOUIS, MO 63110
WILBUR, RONNIE B, PHD *
PROFESSOR & DIRECTOR
LINGUISTICS PROGRAM
PURDUE UNIVERSITY
WEST LAFAYETTE, IN 47907
WONG, PATRICK C, PHD *
ASSISTANT PROFESSOR
DEPARTMENT OF COMMUNICATION SCIENCES AND
DISORDERS
NORTHWESTERN UNIVERSITY
EVANSTON, IL 60208
ZUO, JIAN , PHD *
ASSOCIATE MEMBER
ST. JUDE CHILDRENS HOSPITAL
DEVELOPMENTAL NEUROBIOLOGY
MEMPHIS, TN 380152794
ZWIEBEL, LAURENCE J, PHD *
PROFESSOR
DEPARTMENT OF BIOLOGICAL SCIENCES
VANDERBILT UNIVERSITY
NASHVILLE, TN 37235
SCIENTIFIC REVIEW ADMINISTRATOR
OAKS, STANLEY C. JR.
SCIENTIFIC REVIEW ADMINISTRATOR
DIVISION OF EXTRAMURAL ACTIVITIES
NATIONAL INSTITUTE ON DEAFNESS AND
OTHER COMMUNICATION DISORDERS
BETHESDA, MD 20892
STICK, MELISSA J., MPH, PHD
CHIEF, SCIENTIFIC REVIEW BRANCH
DIVISION OF EXTRAMURAL ACTIVITIES
NATIONAL INSTITUTE OF DEAFNESS AND
OTHER COMMUNICATION DISORDERS
BETHESDA, MD 20892
GRANTS TECHNICAL ASSISTANT
JOHNSON, NICHELLE
GRANTS TECHNICAL ASSISTANT
SCIENTIFIC REVIEW BRANCH
DIVISION OF EXTRAMURAL ACTIVITIES
NIDCD, NIH
BETHESDA, MD 20892
* Temporary Member. For grant applications, temporary
members may participate in the entire meeting or may review
only selected applications as needed.
Consultants are required to absent themselves from the room
during the review of any application if their presence would
constitute or appear to constitute a conflict of interest.