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PHARMACOLOGICAL AND SENSORY STIMULATION OF
AUDITORY CORTEX PLASTICITY IN ADULT RATS
by
Vikram Jakkamsetti
APPROVED BY SUPERVISORY COMMITTEE:
___________________________________________
Dr. Michael P. Kilgard, Chair
___________________________________________
Dr. Lawrence J. Cauller
___________________________________________
Dr. Marco Atzori
____________________________________________
Dr. Christa K. McIntyre
Copyright 2008
Vikram Jakkamsetti
All Rights Reserved
Dedicated to Dad and Mom
PHARMACOLOGICAL AND SENSORY STIMULATION OF
AUDITORY CORTEX PLASTICITY IN ADULT RATS
by
VIKRAM JAKKAMSETTI, M.B.B.S., M.D., M.S.
DISSERTATION
Presented to the Faculty of
The University of Texas at Dallas
in Partial Fulfillment
of the Requirements
for the Degree of
DOCTOR OF PHILOSOPHY IN COGNITION AND NEUROSCIENCE
THE UNIVERSITY OF TEXAS AT DALLAS
December, 2008
2009
ACKNOWLEDGEMENTS
Working on a PhD has been like learning how to swim. I conquered my fear of drowning
only recently and the adrenaline surges during my first attempts at swimming last year have
definitely seared the experience deep into my memory. I vividly remember the burning lungs,
the panic, the flailing and thrashing of limbs as I groped for the edge of the pool. My first
few months in the PhD program were no less painful. I was overwhelmed, totally out of my
element, and often saw my sense of self-worth sinking toward dangerous lows. And just like
swimming, all I had to do was reach out and hold onto a firm support as I breathed sweet,
soothing fresh air each time. My support took many forms-mentor, colleague, mentee,
sibling, parent, friend, official, the memory of an inspiring grandparent. Without the buoyant
effect created collectively by all my supports, I would have definitely drowned.
The people who have supported me the most are my Dad and Mom. This awareness
surprised me a little, since Dad and I have rarely had detailed discussions regarding the rigors
of PhD. Yet, I hold him in the highest stead, probably because his example was good enough.
He grew up poor, the eldest son amongst fifteen brothers and sisters, with the responsibility
of being the primary provider for this family. His determination in continuing his PhD at a
highly respected and demanding institute in India, progress into working for respected
research institutes in Europe, eventual success in becoming an entrepreneur with his own
factory- a lot of this being done while being the primary provider and soul for his Mom,
siblings, wife and two children- inspires me tremendously. His example of using scientific
acumen and logical thought-and the successful consequences of the application of such
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acumen and thought in daily living- is a strong buoy holding me up as I traverse the choppy
waters of scientific research. My Mom instilled in me a love for literature and creative
writing and the beautiful art of generous diplomacy. As part of a struggling family with
relatively few resources to be shared amongst uncles, aunts and a sibling all under the same
roof, I learnt from her that sharing and negotiating gracefully helps everyone: an attribute
that helped my scientific research in a busy lab and collaborations with adjoining labs. In the
words of the respected late Randy Pausch PhD. : I believe I won the parents lottery.
I have no dearth of superlative words to describe my experience in having Dr.Kilgard
as my mentor-fantastic, super cool, awesome, very very very enriching, neuro guru- these are
some words that come to my mind. He coached me on learning how to think. “Experiments
will happen. You are here to learn to think”, he said in similar words. His example of picking
up a sub-field, mastering it, then moving onto another sub-field is an inspiration for two
useful attitudes: a) that one should master one thing at a time and b) having a good breadth of
knowledge across sub-fields helps instruct each sub-field. He approaches neuroscience with
fascinating enthusiasm that is extremely contagious. His style of management is my first
exposure to a fluid corporate style of complete delegation and complete accountability which
I aspire to emulate in the future. With his interaction with fresh PhD candidates I have begun
to appreciate a neat and subtle method adopted by him. He gauges a student’s growing
abilities and accordingly adjusts his level of expectations. This flexibility was extremely
helpful in my initial years as I floundered repeatedly in learning basic scientific writing
skills.
I have been lucky to have the opportunity to learn from my Dissertation Committee
members- Dr. Lawrence Cauller, Dr. Marco Atzori and Dr. Christa McIntyre. Specific
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incidents that come to my mind: a) Dr. Cauller suggesting that much of learning involves
forming our very own personal construct of a given phenomena, and seeing if new
information fits into that construct. If it does not, this leads to two possibilities-either the
construct is incomplete/wrong, or the new information is incongruent with a basic
neuroscientific principle-which in itself can be a fascinating issue to explore. b) Dr. Atzori’s
habit of committing to a deadline and respecting it regardless of circumstances. I’ve
promised myself that I shall one day succeed in inculcating this habit and practicing to do
that has been of immense benefit in managing small personal writing deadlines.
Kevin Chang has been my colleague and collaborator for most of my PhD education.
His assistance in my experiments was of immense help. As an undergraduate researcher, he
helped me train animals, troubleshoot broken equipment, record neuronal responses and
manage people. He was humble and methodical in something as simple as cleaning
enrichment cages, which allowed me to feel comfortable in delegating a modest proportion of
experiment work to him.
I am grateful for the multiple discussions and collaborations I have had with graduate
student colleagues Jai Shetake, Justin Nichols, Amanda Puckett, Crystal Engineer, Claudia
Perez, Rafael Carrasco, Roshini Jain, Mitali Bose, Ben Porter and Dave Pena, Helen. Jai
helped me tremendously in my experiments and patiently listened when I had an idea to
share and discuss. Justin and I collaborated on a paper and I learnt patience and staying calm
from him. I consider him a self-made engineer/scientist-the best kind-, a quality that I hope to
emulate. Amanda is a natural “smartie”. Having her insights was invaluable. I especially
cherish the holistic discussions we had of “how science is done”. Crystal is to me the epitome
of quiet elegant hard work. She is an inspiration and a trend setter. My standards have
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dramatically changed for the better after she published her Nature Neuroscience paper.
Working with Claudia was my first experience with being involved in a project where I did
not have all the answers. Her questions during inferior colliculus access surgery and mapping
stimulated me to be more aware of the details of experimental protocols. Rafael and
Roshini’s expertise and coaching in my first project helped keep me afloat during my tough
initial months. Mitali included me in her project and it gave me a lot of satisfaction being a
part of a project where I could be involved and enjoy the benefits of learning without having
to do the hard work required by the first author. Ben-bless his heart- has successfully taken
on the mantle of organizing regular lab activities like managing birthday cakes/organizing
lunches/setting up lab meeting times etc. Efficient organization saves a lot of time and I am
grateful for it. Dave stepped in to help me handle a molecular biology phase of an experiment
during “crunch” time and I am very thankful for that. Helen provided me with speech sounds
for my enrichment project.
Scores of undergraduates and four high school students helped me in my work and I
could not have completed my experiments without them. They include Juliann Record, Mona
Noorizadeh, Hamid Shah, Rachelen Samuel, Rachel Nance, Trishna Sharma, Jai Gandhi,
Caleb Dunham, Rolan Torres, Jamie Kalangara, Kamini Krishnan, Scott Nietfeld, Stuart
Michnick, Matt Ditzler , Joseanne Howard, Siby Spurgeon, Chris Heydrick, Sneha Idiculla,
Gabriel Mettlach , Theresa Lii, Linda Yang, Jessica Moore, Farwa Ali, Larry Nentwig,
Maulie Happawana, Blake Farha, Jennifer Grisiel, Kinsey Ram, Swati Chanini, Ann Nguyen,
Deepthi Vupalla, Laura Thibodeaux, Sana Khan and Miwa Murray. Rolan Torres, Kamini
Krishnan, Scott Nietfeld, Matt Ditzler, Kevin Jordan, Jamie Kalangara and Gabriel Mettlach
were especially helpful in recording neuronal responses. Rolan’s neat and methodically
viii
mapping skills, Kamini’s mapping expertise and Scott’s programming skills were of great
help when I had a deadline to meet.
I am grateful for Dr.Sandra Chapman’s time and effort during my first year in the
university. I was convinced at that time that I could do basic science research as well as
clinical research at the same time. Dr.Chapman arranged for me and attended a meeting with
a respected pediatrician. If it were not for her efforts (and Dr.Kilgard’s), I might have
followed up on my university applications to leave the University of Texas at Dallas for a
university with clinical facilities on a misconceived quest to do clinical and basic science
research at the same time.
I am thankful for the help provided by the staff in our department. Abbie Bailey
helped me tremendously in procuring equipment for the lab. Bonnie Dougherty, Mary Felipe,
Susie Milligan and Jo Valcik helped me breeze through any dealings with the department or
university. Nuvala Nguket helped in providing me with software when I needed it.
I have a special thank you for former graduates from the Kilgard Lab. Navzer
Engineer, Pritesh Pandya, Raluca Moucha and Cherie Percaccio laid the foundation for
students like me to build on. Their papers were immensely useful in giving me a ready
framework to build a paper on.
My loving non-university friends suffered through my prolonged absences in their
lives and I will never forget that. My sister Deepa Jakkamsetti and Molly Anderson have
been my closest and strongest of supports and I love them for that.
It is said that once you learn to swim, you can never forget that skill. I hope that is
true. I am only too aware that swimming in a pool while learning is far simpler than
swimming in the difficult waters of today’s research seas. I sincerely hope that I can
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successfully navigate through these seas and validate the trust, effort and time given by all
the people who supported me.
July 2008
x
PHARMACOLOGICAL AND SENSORY STIMULATION OF
AUDITORY CORTEX PLASTICITY IN ADULT RATS
Publication No. ___________________
Vikram Jakkamsetti, Ph.D.
The University of Texas at Dallas, 2008
Supervising Professor:
Dr. Michael Kilgard
The adult brain has an amazing capacity to change in response to environmental experience.
Understanding the principles of experience-dependent plasticity will help us design effective
treatments for neuronal processing disorders. Environmental enrichment has been
successfully used in treating multiple neuronal processing disorders. The underlying
physiological changes consequent to environmental enrichment has been studied in the
primary sensory cortex. However, non-primary sensory cortices occupy a greater proportion
of the cortex involved in sensory processing. In the first part of the dissertation I explored the
physiological consequences of environmental enrichment in the posterior auditory field
(PAF)-a distinct non-primary auditory field. It was seen that enrichment induced PAF
neurons to become selective, fire faster to stimuli, and respond better to rapidly successive
stimuli. In the second part of my dissertation I explored the induction of experiencedependent plasticity using modulation of developmental mechanisms. During development,
continuous sensory input prior to maturation of cortex increases the representation of the
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experienced sensory input in the cortex. Such experience-dependent plasticity depends on the
presence of high levels of cyclic adenosine monophosphate (cAMP) in the cortex prior to
maturation. In an adult rat, we paired acoustic input with injections of Rolipram-a drug that
increases cortical cAMP levels and observed that Rolipram increased the length of the cortex
activated by the paired tone and induced primary cortex neurons to become more selective to
the paired tone. In the third part of the dissertation I explored induction of experiencedependent plasticity using modulation of attentional mechanisms. It has been previously
demonstrated that paying attention to a tone for a tone discrimination task stimulates the
nucleus basalis to release cortical acetylcholine which activates muscarinic M1 receptors to
increase the representation of that tone in the primary auditory cortex. We paired acoustic
input with injections of M1 agonist Cevemiline and observed an increase in the length of the
cortex corresponding to the acoustic input. The experiments in this dissertation attempt to
understand experience dependent brain changes and use current understanding of the
mechanisms of experience dependent plasticity to research drugs that could help improve
neuronal processing for neuronal disorders.
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TABLE OF CONTENTS
Acknowledgments ...............................................................................................................v
Abstract .............................................................................................................................. xi
List of Illustrations ........................................................................................................... xiv
Chapter 1: Introduction ...................................................................................................... 1
Chapter 2: Plasticity of temporal and spectral information processing in the rat
posterior auditory field induced by environmental enrichment .......................................... 5
Appendix: Chapter 2 ..........................................................................................................22
Chapter 3: Rolipram induces frequency specific cortical plasticity in rat A1 .................. 38
Appendix: Chapter 3 ..........................................................................................................51
Chapter 4: M1 agonist Cevimeline (AF102B) induces input specific frequency
map plasticity in rat primary auditory cortex .................................................................... 6o
Appendix: Chapter 4 ..........................................................................................................73
Chapter 5: Summary and Conclusions ............................................................................. 87
Vita
xiii
LIST OF ILLUSTRATIONS
CHAPTER TWO
Figure 1. Schematic figure of standard and enriched environment. ................................. 22
Figure 2. Representative A1-PAF map from control (A) and enriched (B) group. .......... 23
Figure 3. Population PSTH of responses to pure ones recorded from enriched
(N=127) and control (N=127) rat PAF. ............................................................................ 24
Figure 4. Latency of response to pure tones in PAF. ....................................................... 25
Figure 5. Mean PSTHs for 9.6 Hz noise burst train in rat PAF neurons. ....................... 26
Figure 6. Normalized mean Repetition Rate Transfer Function (RRTF) in
PAF neuron. ...................................................................................................................... 27
Figure 7. Vector strength of PAF neurons in response to noise burst trains
in PAF. .............................................................................................................................. 28
Figure 8. Rayleigh Statistic of PAF neurons in response to noise burst trains. .............. 29
Figure 9. Nearest neighbor classifier performance in recognizing neural
responses to noise burst trains in PAF .............................................................................. 30
Figure 10. Examples of speech spectrograms. .................................................................. 31
Figure 11. Population PSTHs of response to /DAD/ & /TAD/ in PAF. ......................... 32
Figure 12.Population PSTHs of response to /RAD/ & /LAD/ in PAF. ............................ 33
Table 1. Response Properties of Posterior Auditory Neurons from rats housed
in enriched and standard environments............................................................................. 34
CHAPTER THREE
Figure 1.Illustration of experimental protocol. ................................................................. 51
xiv
Figure 2.Example of a tuning curve and frequency A1 map recorded from
a naïve rat. ......................................................................................................................... 52
Figure 3. Example of cortical length measurement for Rolipram injected group. .......... 53
Figure 4. Example of cortical length measurement for vehicle injected group. ............. 54
Figure 5. Cortical length comparisons. ............................................................................. 55
Figure 6. Bandwidth Plasticity. ......................................................................................... 56
CHAPTER FOUR
Figure 1. . Illustration of experimental protocol. .............................................................. 73
Figure 2 Example of a tuning curve and frequency A1 map recorded from
a naïve rat. ......................................................................................................................... 74
Figure 3. Example of cortical length measurement for low tone exposure group. .......... 75
Figure 4. Example of cortical length measurement for high tone exposure group. ......... 76
Figure 5. Cortical length comparisons (M1 agonist). ....................................................... 77
Figure 6.Cortical length comparisons (Amphetamine). .................................................... 78
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CHAPTER ONE
INTRODUCTION
Millions of adults suffer from mental health disorders. In the United States alone, 26.2 % of
adults have a diagnosable mental disorder for a given year . Based on the 2004 Census, this
results in 57.7 million people requiring help for mental health disorders. The magnitude of
the problem is huge and the cost to society in billions of dollars. Many of these disorders do
not have definitive treatments, and with a continuing addition of freshly diagnosed cases
being added to a pool of pre-existing ones, the issue is destined to become graver with time.
A lack of treatment for mental disorders could be attributed to a major extent to a lack of
definitive knowledge regarding the underlying disorder and its potential therapy. Instances
where a working knowledge of the nature of the pathology and mechanisms of potential
therapies have been discerned, have led to breakthrough treatments for brain disorders (Tallal
et al., 1998). This optimism, that understanding neuronal mechanisms will make a
contribution-however small-to finding treatments, was a strong motivation behind the
research in this dissertation.
An effective therapeutic intervention that spans across many neuronal disorders is
that of exposure to an enriched environment (Will et al., 1977; Kolb and Gibb, 1991;
Hannigan et al., 1993; Hockly et al., 2002; Morley-Fletcher et al., 2003). Along with genetic
influences, an organism’s survival is hugely influenced by cues from the environment. For
example, a deer seeking to escape from a leopard is genetically endowed with an ability to
outrun the leopard over long distances. However, learning to detect miniscule variations in
1
2
acoustic input is essential for survival, since this will allow the deer to discern the movement
of a leopard through the grass and avoid being ambushed. The ability of the deer’s brain to
learn to detect behaviorally relevant acoustic input allows its survival. Such brain plasticity in
response to environmental cues has been studied in the laboratory. Enriching animals with
behaviorally environmental cues leads to significant changes in gene expression (Staiger et
al., 2002) morphology(Volkmar and Greenough, 1972), physiology (Engineer et al., 2004)
and behavior (Churs et al., 1996). Such an ability to induce brain plasticity has been used in
treating multiple neuronal processing disorders. Understanding the physiological
underpinnings of environmental enrichment in the cortex will be helpful in furthering our
knowledge of neuronal mechanisms involved in effective treatments.
The first chapter involves understanding the physiological response of a non-primary
auditory cortex to environmental enrichment. Multiple studies have explored experience
dependent plasticity in primary sensory cortices. However non-primary cortices comprise a
bigger portion of the cortex devoted to sensory processing, and to the best of our knowledge,
physiological changes induced by enrichment in non-primary cortices have yet to be
investigated. We exposed rats to an environment that was rich in behaviorally relevant
acoustic cues and then investigated physiological responses of a distinct non-primary
auditory field – the posterior auditory field(PAF). Previous experiments exploring
environmental enrichment induced plasticity in primary sensory cortices demonstrated that
receptive fields get sharper, onset latencies get faster and the strength of neuronal responses
get stronger. An increase in response strength to a single tone lead to a decreased ability to
recover quickly and fire again to a successive tone. This is a quandary, since clinical
literature suggests that experiential plasticity induced by training leads to a better ability to
3
respond to rapidly successive auditory stimuli (Hayes et al., 2003a). However, clinically seen
evoked potentials are a summation of action potentials seen across different auditory fields.
Investigating non-primary auditory cortex for temporal processing plasticity induced by
enrichment could help resolve this quandary.
The impressive changes in physiological processing of sounds after enrichment seen in
our lab (Engineer et al., 2004; Percaccio et al., 2005; Percaccio et al., 2007) induced a keen
curiosity to understand the synaptic mechanisms involved. This resulted in my collaboration
with Dr.Marco Atzori’s lab members, wherein it was revealed that glutamate release at
synapses increases significantly after environmental enrichment (Nichols et al., 2007). The
involvement of neurotransmitter modulation in plasticity is exciting, since it offers the
possibility of clinical manipulation. While systemic administration of agents that directly
increase glutamate release may not be clinically viable due to adverse effects, the seed of the
possibility of inducing plasticity through neuromodulation had taken root.
The second chapter deals with induction of experience dependent plasticity through
neuromodulation of critical period mechanisms. The period between establishment of
connections from peripheral sensory organs to sensory cortex and final maturation of the
sensory cortex is referred to as a critical period. During the critical period, passive exposure
to sensory stimuli can drive stimuli specific changes in the cortex. Experiments have proved
that such activity dependent cortical reorganization is mediated by an increase in basal cAMP
(cyclic adenosine mono phosphate) levels in the cortex. We hypothesized that raising cAMP
levels in adult rat cortex will mimic experience dependent plasticity seen during the critical
period. Rolipram increases cortical cAMP levels by inhibiting its breakdown. This would
suggest that rolipram can induce experience dependent plasticity by harnessing mechanisms
4
involved in critical period plasticity. Training to increase cortical representation of an
environmental cue is suggested to be of benefit in cortical disorders (Xerri et al., 1998).
Providing evidence that Rolipram increases cortical representations of cues that are paired
with rolipram injections could be of great use in inducing cortical plasticity to correct cortical
processing disorders.
The third chapter provides evidence for cholinergic neuromodulation of cortical
plasticity. Multiple studies demonstrate the involvement of acetylcholine in generating
cortical plasticity (Kilgard and Merzenich, 1998b; Penschuck et al., 2002; Zhang et al.,
2006). Experience dependent plasticity is mediated by cholinergic activation of muscarinic
receptors (Kilgard and Merzenich, 1998a) , specifically M1 receptors (Zhang et al., 2006).
We hypothesized that systemic administration of an M1-agonist (Cevemiline Hydrocholride)
immediately before exposure to multiple repetitions of a single tone would induce tone
specific plasticity in the primary auditory cortex.
Researching neuronal mechanisms that could lead to treatments for cortical
processing disorders might seem daunting at first glance. After all, the brain is a complex
system, and research involves examination of a relatively narrow region. However, each
study adds a significant piece to the brain puzzle, taking us one step closer to helping the
millions of our fellow human beings who suffer from cortical disorders. I hope you enjoy
reading the following chapters as much as I did in conducting the research for them.
CHAPTER TWO
PLASTICITY OF TEMPORAL AND SPECTRAL INFORMATION PROCESSING IN
THE RAT POSTERIOR AUDITORY FIELD INDUCED BY
ENVIRONMENTAL ENRICHMENT
Vikram Jakkamsetti, Kevin Q. Chang, and Michael P. Kilgard
School of Behavioral and Brain Sciences, GR41
The University of Texas at Dallas
800 W. Campbell Road
Richardson, Texas 75080-3021
Running Title: Plasticity of Temporal and Spectral Information Processing in the rat
Posterior Auditory Field induced by Environmental Enrichment
Key words: : non-primary auditory cortex, paired-pulse facilitation, repetition rate transfer
function, spike synchronization, speech coding
Corresponding author: Vikram Jakkamsetti
Email: [email protected]
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ABSTRACT
Sensory non-primary cortex constitutes an important component of the cortex involved in
sensory information processing. Little is known regarding their representation of neuronal
plasticity. In our previous studies in primary auditory cortex (A1) we observed that
environmental enrichment is a powerful tool that induced significant changes in neuronal
onset latencies, receptive field bandwidths, increased response strength and increased paired
pulse depression to successive stimuli. Here we examine neurophysiological plasticity in the
posterior auditory field (PAF) of rats after environmental enrichment. Enrichment caused a
significant decrease in onset latencies and response durations to pure tones by more than
30%. Short response durations increased the ability to respond to rapidly successive stimuli,
leading to paired pulse facilitation and increased phase locking of PAF responses to noise
burst trains. Finally, enriched enhanced the response to speech sounds with rapid onsets. Our
results support earlier observations that non-primary fields are more plastic than primary
fields.
INTRODUCTION
Environmental enrichment significantly improves recovery from stroke and traumatic brain
injury (Will et al., 1977; Kolb and Gibb, 1991; Hannigan et al., 1993; Rampon et al., 2000;
Hockly et al., 2002; Morley-Fletcher et al., 2003; Jankowsky et al., 2005) and has been
proposed as a treatment for neuronal disorders like Alzheimer’s disease, dyslexia and autism
(Hayes et al., 2003a; Percaccio et al., 2005). However, its mechanism of action is far from
clear. Molecular and morphological analyses of the cerebral cortex in enriched animals
reveal that enrichment increases glutamate release (Nichols et al., 2007), gene expression
7
(Staiger et al., 2002), dendritic spines (Globus et al., 1973) , dendritic branching (Volkmar
and Greenough, 1972; Greenough et al., 1973) and synapses per neuron (Sirevaag and
Greenough, 1987). Neurophysiological studies document that enrichment causes primary
cortical neurons to respond more strongly and more selectively to sensory stimuli (Beaulieu
and Cynader, 1990; Coq and Xerri, 1998; Engineer et al., 2004). Enrichment also modulates
temporal response properties in these neurons, inducing neurons to fire earlier (Engineer et
al., 2004) and increasing paired pulse depression (Percaccio et al., 2005). While these studies
have advanced our knowledge of primary cortex physiology after enrichment, primary
regions occupy but a small proportion of cortex, and little is known regarding enrichment
induced plasticity in non-primary sensory cortex. Having a more comprehensive idea of
cortical changes as a consequence of sensory enrichment would be helpful.
Previous plasticity studies have suggested that non-primary sensory cortex is more
susceptible to experience-dependent changes. For example, discriminating orientations of
bars induces greater plasticity in V4 than V1 neurons (Raiguel et al., 2006). Fear
conditioning generates greater receptive field plasticity in non-primary auditory cortex
compared to primary auditory cortex (A1) (Diamond and Weinberger, 1984). Nucleus
basalis stimulation paired with a tone causes changes in receptive fields and neuronal firing
rates in posterior auditory field (PAF) that is not observed in A1 (Puckett et al., 2007). These
studies led us to hypothesize that enrichment would induce changes in non-primary auditory
cortex that were greater in magnitude than A1.
We chose to conduct our study in the well characterized posterior auditory field (PAF).
Compared to A1, PAF neurons have broader frequency bandwidths, slower onset responses
and a lesser ability to fire to each stimuli in a train of rapidly successive stimuli (Doron et al.,
8
2002; Pandya et al., 2007). PAF has been implicated in processing of slow varying complex
spectro-temporal stimuli(Phillips et al., 1995; Heil and Irvine, 1998; Tian and Rauschecker,
1998; Loftus and Sutter, 2001; Pandya et al., 2007) and plays a critical role in sound
localization (Malhotra et al., 2004).
In this study, we tested the hypotheses that enrichment would 1) increase PAF’s selectivity
and strength of response for tones 2) increase the cortical following rate of PAF for noise
burst trains, and 3) increase the onset response to speech.
METHODS
Thirteen female Sprague-Dawley rats aged 25 days post partum were placed in either
enriched or standard environments for 8 weeks. The enriched and standard housing
conditions were identical to earlier reports published from our lab (Engineer et al., 2004;
Percaccio et al., 2005). Rats in both environments received food and water ad libitum and
were on a reverse 12-h light/dark cycle.
Environmental Exposure
Enriched Environment: Six rats were housed in a large cage (45 X 76 X 90 cm) located in a
room separate from the main rat colony. The cage had four levels linked by ramps and rats
entering a level elicited a unique sound due to hanging chains and wind chimes hung over the
entrance of each level. Stepping on two of the three ramps triggered delivery of two different
tones (2.1 or 4 kHz). Motion near the water source set off a motion detector that emitted an
electronic chime. Rats on an exercise wheel evoked a tone (3 kHz Piezo speaker) and
activated a small green light emitting diode with each rotation. Each movement-activated
9
sound had unique spectral and temporal features that provided behaviorally meaningful
information about the location and activity of other rats in the cage.
The rats were exposed to 74 randomly selected sounds every 2-60 s from a CD player, seven
of which triggered a pellet dispenser (Med Associates, St. Albans, VT, USA) to release a
sugar pellet to encourage attention to the sounds. The sounds included simple tones,
amplitude-modulated and frequency-modulated tones, noise burst, and other complex sounds
(rat vocalizations, classical music, rustling leaves, etc.). The rewarded tracks included
interleaved tones of different carrier frequencies (25-ms long, 4-,5-,9-,12-,14-, and 19-kHz
tones with interstimulus intervals ranging from 50 ms to 2 s) and frequency modulated
sweeps (1 octave up or down in a 140- or 300-ms sweep with interstimulus intervals ranging
from 80 to 800 ms). The rats in the enriched environment were exposed to these sounds
spanning their entire hearing range (1-45 kHz), 24h/day. After four weeks in the enriched
environment, rats reached sexual maturity and a vasectomized male rat was added to the cage
to encourage natural social interactions appropriate for the age.
Standard Environment: Six age matched control rats were housed 2 per cage (26 X 18 X 18
cm). These rats heard sounds related to typical room traffic and vocalizations from 30-40
other similarly housed rats.
All methods and procedures were in accordance with guidelines set by NIH for
Ethical Treatment of Animals and received the approval of the University Committee on
Animal research at the University of Texas at Dallas.
Acute Surgery
Physiological experiments were conducted after eight weeks of differential housing.
Anesthesia for surgery was induced by pentobarbital sodium (50 mg/kg ip) to achieve a state
10
of areflexia and maintained with supplemental dilute pentobarbital (8 mg/kg ip). The rat’s
level of anesthesia was monitored by heart rate, breath rate, and toe pinch and cardiovascular
status monitored by the presence of urine during regular bladder voiding. A heating pad and
rectal probe was used to hold the core body temperature at 37oC. Fluid balance was
maintained with a 1:1 mixture of 5% dextrose and Ringer lactate (~0.5 ml/h). The trachea
was cannulated to administer humidified air and ensure adequate ventilation and to minimize
breathing sounds. The cisterna magna was drained to prevent cerebral edema. The right
auditory cortex was then exposed, the dura resected and viscous silicon oil added to the brain
surface to prevent desiccation. Electrode penetration points were referenced using vascular
landmarks and marked on a digitized photograph of the auditory cortex surface. Care was
taken to avoid penetration of visible vasculature.
Experimenters were blind to the housing condition of the rat during surgery and
recordings, though in some cases unkempt fur made it clear that the rats were housed in the
enriched environment.
Stimulus Presentation
Acoustic stimuli were presented in a double-walled sound attenuating chamber from a
speaker (Motorola model No. 40-1221) at 90 degrees azimuth and 0 degrees elevation from
the base of the contralateral ear. Frequency and intensity calibrations were done using
Tucker-Davis (Alachua, FL) SigCal software and an ACO Pacific (Belmont, CA)
microphone (PS9200-7016).
Tones: 1296 randomly interleaved pure tones (25 ms duration, 3 ms ramps, every 500 ms)
were generated using Brainware (Tucker-Davis Technologies). The tones included 81
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logarithmically spaced frequencies from 1-32 kHz, each at 16 different intensities spaced 5
dB SPL apart from 0-75 dB SPL.
Noise burst Trains: 12 repetitions of 14 noise burst trains (3-20 Hz interstimulus intervals)
with each noise burst 25ms in duration, having ramps of 3ms and a bandwidth of 1-32 kHz.
Each train was presented 2 s after the termination of the last train.
Speech: Four natural speech sounds, /dad/, /tad/, /rad/ and /lad/, were recorded from a single
native English speaker in a sound booth with a sampling rate of 44,100 Hz. As in our earlier
study, the sounds were frequency shifted one octave higher with a vocoder without altering
the amplitude envelope to better match the rat hearing range (Engineer et al., 2007). The
intensity of each speech sound was adjusted so that the loudest 100 ms was 65 dB SPL.
Speech sounds was presented in random order, each speech sound repeated 20 times, with a
sampling rate of 100 kHz and a silent interval of 2 sec separating each stimuli presentation.
Recording
Two pairs of Parylene-coated tungsten microelectrodes (FHC, Bowdoin, ME) with 250 μm
separation, 1.5 ± 0.5 MΩ) were lowered 600-680 μm below the pial surface (layer IV/V) of
the auditory cortex to record multi-unit activity from 35 – 60 penetration sites. The neural
signals were filtered using a high pass filter and amplified (10,000 times). Action potentials
waveforms were recorded whenever a set threshold (600 mv) was surpassed. A1 was defined
based on tonotopy and latency. The abrupt lack of tonotopicity at A1’s posterior most border
was taken as the A1-PAF border. A site was considered non responsive if the action
potentials at that site were less than two standard deviations above the mean of spontaneous
firing rate. Criteria for identifying PAF sites were applied by a well-trained observer blind to
the housing status of each rat.
12
Data Analysis
Tuning Curve Analysis: All data analysis was done offline to avoid a potential bias in site
selection and by an observer blind to the housing condition of the rat for the data being
analyzed. Tuning curve parameters were defined by a program written in MATLAB. The
spontaneous firing rate was calculated as the spike rate in the first 8 ms recorded after
presentation of tone and before onset of a neural response in the cortex. Onset latency was
the time from the onset of the stimulus to the earliest reliable neural response reaching two
standard deviations above spontaneous firing rate. End latency was defined as the time when
the PSTH (post stimulus time histogram-created by summing responses to all the tones
within a site’s tuning curve) returned back to baseline. The characteristic frequency (CF) was
defined as the frequency that evoked a reliable response at the lowest intensity (response
threshold). Frequency bandwidth (BW) was the range of frequencies that a site responded to
at 10, 20, 30 and 40 dB above threshold. Voronoii tessellation using MATLAB was done to
determine polygons corresponding to each penetration site (Figure 1). In essence, each point
within a polygon is closest to the recording point enclosed within that polygon.
Noise Burst Train Analysis: Noise burst repetition rate transfer functions (RRTF) were
calculated for each site by quantifying action potentials per stimulus. A normalized RRTF
was calculated for comparison across recording sites since the number of neurons involved in
a multi-unit cluster could vary. Normalized RRTFs were estimated by finding the mean
evoked response of neurons to each of the last 5 noise bursts in a train and dividing that by
the evoked response to the first noise burst. Hence, values greater than 1 indicate facilitation
and values less than 1 indicate adaptation. Neuronal responses during the first 5 ms after
noise burst train presentation were considered as spontaneous firing rate. Action potentials
13
within a time window of 14-85 ms after the onset of a noise burst in a noise burst train were
considered as having occurred in response to the noise burst. For noise burst trains presented
at rates greater than 10 Hz, the time windows associated with each noise burst in a train
would overlap. Hence for rates >10Hz the time window began with 14ms after the onset of
the second noise burst and ended 85 ms after the onset of the fifth noise burst. To examine
the synchronization between neuronal firing and repeated noise bursts, we estimated vector
strength using the following formula:
where n= total number of action potentials, ti is the time of occurrence of the ith action
potential and T is the interstimulus interval. A value of 1 depicts perfect synchronization
while a value of 0 indicates none. The Rayleigh Statistic (2n x Vector Strength2, where n is
the total number of action potentials) is a circular statistic that combines vector strength and
number of action potentials to indicate the statistical significance of vector strength. A value
greater than 13.8 is considered statistically significant.
Speech Analysis: The average spike rate for each speech sound was estimated in 1 ms bins
from the Post Stimulus Time Histogram (PSTH). The average spike rate in the first 14 ms
after presentation of the speech sound was taken as the spontaneous discharge rate and
subtracted from the mean firing rate in all analysis. Driven spike rates for speech onsets were
estimated from 14 to 140 ms after presentation of speech sound. Neuronal responses from a
site were considered in the analysis if that site had a driven response (i.e. greater than thrice
the standard deviation above the mean of spontaneous discharge) to speech onset.
14
RESULTS
General Observations
A total of 792 extracellular multi-unit cortical sites (control=432 , enriched=360)
from 13 rats (control=7, enriched=6) were recorded in the auditory cortex across A1
(control=110 sites, enriched=69sites), PAF (control=156 sites, enriched=127 sites) and
ventral auditory field (control= 45 sites, enriched=34 sites) . A1 low frequency neurons were
recognized by their antero-posterior frequency gradient, short onset latencies and narrow
receptive fields. Consistent with a previous study from our lab (Engineer et al., 2004) this
subset of A1 neurons demonstrated a trend towards enrichment induced decrease in onset
latency (control=12.7 ±.45ms, enriched = 12.04 ± 0.29ms, p= 0.28) and significantly
sharpened receptive fields (Bandwith 10dB above threshold: control=1.66± 0.16 octaves,
enriched=1.19±0.22 octaves, p<.05) . A1 neurons progressively decrease in CF with
posterior extent and a sharp interruption of this frequency gradient at A1’s posterior border
signifies the A1-PAF border (Doron et al., 2002; Pandya et al., 2007). 283 recording sites
posterior to the A1-PAF border were classified as being in PAF (control=156,
enriched=127). As seen in earlier studies greater onset latencies and wider bandwidths of
PAF neurons contrasted sharply with A1 recording sites at the A1-PAF border (figure 2). The
antero-posterior (AP) length and total area of PAF were indistinguishable in enriched and
control rats (AP length: control 1.07±0.15, enriched 1.35±0.18 mm, p>0.05; Area : control
0.71± 0.15 mm2, enriched 1.07±0.18 mm2, p>0.05).
15
Plasticity in processing temporal information
Enrichment decreases latency of neuronal responses
As auditory information from the cochlea progresses through each neuronal
processing station, the time of onset of neuronal response and the total duration of driven
response progressively increases . PAF is classified as non-primary cortex and is
characterized by neurons that are slow to respond and have a long duration of driven
response. Consistent with previous reports , control PAF neurons had a rise in firing rate that
was more gradual, with a slower return to baseline and a longer duration of driven response
when compared to A1 (figure 3). Exposing rats to an enriched environment caused their PAF
neurons to respond faster. In enriched rats, PAF neurons responded significantly quickerresponses beginning in almost half the time, and reaching peak firing rate 42% earlier than
control PAF neurons. The return of neuronal firing rate to spontaneous levels took 37% less
time than taken by control rats (figure 4) (see Table 1). The rapid rise to peak firing rate and
quick return to baseline lead to 30% shorter response durations when compared to control
rats (control 46.07± 3.29 ms, enriched 32.2 ± 1.91 ms, p<0.01).
Enrichment enhances synchronization to rapidly successive stimuli
PAF contains neurons with varying onset latencies and varying response durations (Doron et
al., 2002). As a population, different PAF neurons respond at different times to the same
acoustic input. This results in poor synchronization between acoustic stimuli and neuronal
response when compared to A1 (Pandya et al., 2007), especially for rapidly incoming input.
On using vector strength (VS) as a measure of synchronization, we observed that our control
rats had values similar to an earlier published study from our lab (figure 7) (Pandya et al.,
16
2007)- vector strength decreased with increased speed of stimuli occurrence. Enrichment
induced neurons to fire more in phase with each iteration of a noise burst in a rapidly
modulated noise burst train. The average maximum vector strength (VS) for control rats was
0.52 ± 0.02 and for enriched rats was 0.69 ± 0.02 (p< 10-7). As a population, control PAF
neurons had their highest vector strength at 5.12 Hz while enrichment increased this measure
to 7.6 Hz. The Rayleigh statistic, a measure of the statistical significance of vector strength
was significantly higher for the enriched group (figure 8) (average maximum Rayleigh
Statistic : control rats 128 ± 16.9 ,enriched rats 182.9 ± 17.9 , p< 0.05).
Enrichment induces paired pulse facilitation
PAF behaves as a low pass filter for temporally modulated sounds. For repeated acoustic
stimuli with long interstimulus intervals, PAF neurons respond almost as well to successive
stimuli as they do to the first stimulus. However, for more rapidly incoming acoustic input,
neurons respond more weakly to successive stimuli, evidencing paired pulse depression at
rapid rates of stimuli iterations (Pandya et al., 2007). In agreement with these prior studies,
for modulation rates upto 7.6 Hz , our control PAF response to a following noise burst was
almost as strong as the first noise burst. With more rapid modulation rates, the neuronal
response to repeated stimuli progressively decreased, depicting paired-pulse depression
(figure 5 & 6).
Latencies are correlated with better cortical following rates (Kilgard and Merzenich,
1999). Enrichment induced shorter latencies should likely lead to better cortical following
rates in the enriched neurons. In sharp contrast to control neurons, enrichment induced
paired-pulse facilitation at slow modulation rates and decreased paired pulse depression at
17
rapid modulation rates (figure 6). For example, at a modulation rate of 8.4 Hz, control rats
had a normalized response significantly less than 1, indicating paired pulse depression
(numbers p<.05), whereas enriched rats responded to the second noise burst with almost
twice the number of spikes evoked for the first noise burst (numbers, p<.05). The average
best modulation rate for enriched rats was significantly higher than that for control rats
(control=4.13 ± 0.27 Hz , enriched=5.29 ± 0. 37 Hz, p<0.05). After responding to the first
noise burst in a train, enriched neurons recovered faster to fire at 50% of the first response for
the second noise burst. The average limiting repetition rate (the fastest modulation rate that
evoked a response at least 50% of the best modulation rate) was significantly greater after
enrichment (control= 8.49 ± 0.44 Hz, enriched=10.93 ± 0.42 Hz ,p<10-3).
An ability to respond quickly and for a briefer period to successive temporal cues suggests
that enriched PAF neurons respond differentially to noise burst trains that have minor
differences in their inter noise burst intervals. In other words, enriched PAF neurons might
find it easier than control rat neurons to differentiate a rapid noise burst train from noise burst
trains with almost similar speeds of presentation. To test this, we used a near-neighbor
classifier- this classifier compares the PSTH of the presented noise burst train with the
average PSTHs of each of the 14 noise burst train groups (see Methods) and finds the best
match. The presence of neuronal activation to noise burst trains enabled control PAF neurons
to correctly predict the rate of the noise burst train amongst the 14 choices (correct prediction
= 24.24 %, chance= 7.2 %, p<.01). Enrichment significantly increased the prediction above
control rats to 33% (control = .2424 ± .024 enriched= .3372 ± .024, p<.01), more than 4
times greater than a chance prediction.
18
Enrichment enhances sensitivity to temporal cues in cortical processing of speech
A speech sound is encoded in A1 in the precise timing of action potentials generated in
response to that speech sound (Engineer et al., 2007). Only a millisecond-by-millisecond
observation of the temporal sequence of neuronal activation after presentation of a speech
sound correlates best with behavioral recognition of that speech sound. Current literature
suggests that PAF neurons respond best to temporal cues that change slowly over time, over
tens of milliseconds. This suggests that PAF neurons would respond to speech with poor
temporal resolution. However, enrichment quickens response latencies in PAF. This lead us
to hypothesize that enrichment would increase the sensitivity to temporal cues in speech. To
test this hypothesis we examined the response of enriched PAF neurons to speech sounds.
/DAD/ and /TAD/ have a quick onset of spectral energy while /RAD/ and /LAD/ has a
slower onset of spectral energy (figure 10). Enrichment caused PAF neurons in enriched rats
to respond to speech stimuli in a more phasic manner. Speech stimuli with rapid onset power
spectrograms like /DAD/ elicited stronger instantaneous peak firing rates (see figure for
values with significant changes between groups), while those with slower onset power
spectrograms like /LAD/ induced a weaker PAF response after enrichment.
Plasticity in processing spectral information
The enriched environment contains multiple spectral cues experienced by rats as behaviorally
relevant. An enriched experience induced a sharpening of receptive fields (bandwidths) in A1
(Engineer et al., 2004). This finding was confirmed in our subset of control A1 neurons
(Bandwith 10dB above threshold: control=1.66± 0.16 octaves, enriched=1.19±0.22 octaves,
p<.05). PAF receives input from multiple frequency areas in A1 and is characterized by
19
wider bandwidths . In agreement with earlier studies, our control rats had bandwidths in
PAF that were wider than in A1 (see Table 1 for control data). Enrichment significantly
increased the selectivity of frequency tuning in PAF. Enriched rats had 25% narrower
bandwidths than control rats 10 dB above threshold (Table 1). The 1st and 3rd quartiles for 10
dB above threshold for enriched rats were 0.13 and 1.75 octaves respectively whereas for
control rats the 10th and 90th percentiles were 0.75 and 2.43 octaves respectively.
Greater response strength in enriched rats
Pure Tone Stimuli: Since earlier studies demonstrate an increase in action potentials induced
by the presentation of a tone after environmental enrichment in the primary auditory cortex,
we predicted that PAF in enriched rats would respond to tones with more spikes. enriched
rats had a 53% greater response in instantaneous firing rate at the time of population PSTH
peak when compared to control rats (control 24.80 ± 3.79 spikes/sec, enriched 37.97 ± 3.91
spikes/ sec p<0.05). (mention findings reflected in single units) . Similarly, enrichment
caused a significant increase in the instantaneous peak firing rate in response to a single noise
burst (Table 1) without a change in the total number of spikes/noise burst. Spontaneous firing
rate and total number of spikes/tone did not change after enrichment (see Table1).
DISCUSSION
Synopsis of findings
We provide evidence that enriched induces PAF neurons to fire more selectively, fire faster
to acoustic stimuli and return faster to baseline. This makes it possible for the cortex to keep
up with rapidly incoming stimuli.
20
Narrowing of Bandwidths
The brain responds to behaviorally relevant stimuli by reorganizing its neurons to respond
more selectively to it. Neurons that responded to a wider range of sensory stimuli get
reorganized to respond to a selective subset of stimuli. Such a narrowing of receptive fields is
seen in primary cortices across sensory systems. Our finding of sharper receptive fields in
secondary cortex confirms previous such findings of plasticity in studies of non-primary
cortex (Diamond and Weinberger, 1986; Bao et al., 2001; Puckett et al., 2007)). While
Diamond and Weinberger (1984) pointed out that a greater proportion of secondary cortex
neurons undergo bandwidth narrowing when compared to primary cortex, our study is the
first to show the magnitude of narrowing.
Greater magnitude of changes in PAF compared to A1
Our current results indicate that environmental enrichment causes more plasticity in
PAF compared to our previous study in A1 (Engineer et al., 2004). Engineer et al showed
that enrichment decreases frequency bandwidth and peak latency in A1 by 8% and 5%,
respectively. Our new results reveal a 42% and 25% reduction in PAF bandwidth and peak
latency, respectively, which is a 3-fold greater reduction in bandwidth and an 8-fold greater
decrease in latency compared to A1. This finding is in agreement with earlier observations
that non primary auditory cortex evidences greater plasticity compared to A1 (Diamond and
Weinberger, 1984; Puckett et al., 2007)
Along with receiving auditory input from ventral region of thalamus via A1, PAF
receives direct auditory connections from medio-dorsal thalamus as part of the non-classical
pathway (winer Current Opin Neurobio). Similar to PAF, medial and dorsal divisions of the
thalamus have longer latencies and response durations (refs). They evidence frequency
21
specific changes in firing rate after classical conditioning (Edeline behav neruosc,
1991,1992) . Stronger non-classical pathway connections would lead to faster neural
transmission which would shorten PAF response latencies. Since shorter latencies are
associated with better phase-locking and a better cortical following rate (Kilgard Hearing
research and Brosch and Schreiner Table 1), the changes in response latency may be
responsible for the observed changes in PAF processing of temporally complex sounds.
Clinical Relevance
Sensory enrichment has been useful as a therapeutic intervention for neuronal disorders .
Sensory enrichment through training improves behavioral measures and neural phase-locking
to stimuli for dyslexia (Tremblay et al., 2001; Hayes et al., 2003). Without treatment,
dyslexics have difficulty using temporal information in speech (Tallal and Piercy, 1973;
Tallal et al., 1985; Reed, 1989; Hari and Kiesilä, 1996; Wright et al., 1997) paralleled
physiologically by a weaker response to the second tone in a pair (Nagarajan et al., 1999) and
a response less in phase with acoustic stimuli (McAnally and Stein, 1996). While our
previous observation that enrichment impaired A1 responses to rapidly presented stimuli
seemed to be at odds with clinical observations our new observation that environmental
enrichment enhances PAF responses to rapidly presented stimuli suggests the possibility that
plasticity in non-primary auditory cortex could contribute to clinically observed
neurophysiological and behavioral improvements after training.
APPENDIX
CHAPTER TWO
Figure 1. Schematic figure of standard and enriched environments. A) The standard
environment consisted of 1-2 rats housed in a hanging cage in the animal colony. B) The
enriched environment contained meaningful acoustic cues: a rat’s movement near the water
source, on a ramp, on the running wheel or through the chimes hanging at a level’s entrance
triggered different sounds. Seven of the 74 sounds randomly played by the CD player were
accompanied by the dispensation of a sugary reward.
22
23
CONTROL
A
B
ENRICHED
64
2.5
64
2
32
32
2
A1
1.5
16
1.5
A1
1
2
4
16
14
8
0.5
5
8
4
2
6 7
810
2
3
2
9
16
8
o
12
7
7
8
2 6
2 2
2
5
8
5
o
8 26 o
9
1
10
3
1
4
7
68
5
2
2
2
2
2
13
16
5
0.5
24
o
8
2
1
1
8
6
o
2
o
o
49
o
o o
13
2
13 o
23
8
23
3 2
7
17
11
o
o
o
7
35 7
9
8
0
1
1
1
PAF
PAF
2
13
18
8
1112 1
19
2020 17
12 9
1117 10 12
10
13
10 13
10 o
o
28
2
0
0.5
1
1.5
2
8
o
o
9
4
2
2
o
0
1
-0.5
16
21
o
17
21
o 20
21
21
2.5Best Freq (kHz)
1
-0.5
0
0.5
1
1.5
2 Best Freq (kHz)
Figure 2. Representative A1-PAF map from control (A) and enriched (B) group. Each
polygon represents one recording site . Values within each polygon reflect the parameter
being mapped. The dark line indicates the A1-PAF border. The empty circles denote sites
unresponsive to tones.
24
Figure 3
PSTH of PAF Response to Tones
Standard
Enriched
Response Strength (Spikes/sec)
40
30
20
10
0
-10
0
50
100
150
200
250
300
Time after tone onset (ms)
350
Figure 3. Population PSTH of responses to pure ones recorded from enriched (N=127) and
control (N=127) rat PAF. Gray shading indicates standard error of mean. Note the increase in
instantaneous firing rate and shorter response duration following enrichment.
25
A
Latency Measures
110
Standard
Enriched
100
*
90
80
Latency(ms)
70
*
60
*
50
40
30
20
10
0
Onset
Peak
B
End of Peak
C
Control
Enriched Rat
70
2.5
70
2
60
60
2
50
1.5
A1
PAF
40
28
42
10 11 10
20
33
11
0 0
11 1329
10
4175 0
10
11 10 11 1213
31
0
0 0
10
65
10
72 23 95 0 0
10 11 11 10 13 1731 58 75
0
9 11 12 11
1456 30
8
11
10
30
11
17 66 19
161
3
20
74
9
12
62
0
12
10 0 0
16
9
0
1
0
13
1
12
12
0.5
A1
1.5
30
0.5
1
PAF
50
11
1313
15
14 0
15
14 14
12
19 14 14 0 19 234
13
13
18
12 13 13
18
14
11
16 261114 19
15
15
151612
0
16 12 1516 13 17
19 0
15 14
18 14
15
29
17 21
1650
0
14
23
14
0
20
40
30
20
0
0
10
-0.5
0
0.5
1
1.5
2
2.5
Latency
10
-0.5
0
0.5
1
1.5
2
Latency
Figure 4. Latency of response to pure tones in PAF A) Bars plot the mean latency to onset,
peak and end of neuronal response. Enriched rat neurons (N=127) initiate, reach peak and
terminate their responses faster than control rat neurons (N=156). B) Control rat A1-PAF
map illustrating varied onset latencies in PAF which are greater than that in A1. C) Enriched
rat A1-PAF map depicting a quicker onset latency in PAF neurons compared to control rats
26
PSTH response to noise burst
90
80
Enriched
Control
70
Spikes/sec
60
50
40
30
20
10
0
100
200
300
400
500
600
Time(ms)
700
800
900
Figure 5. Mean PSTHs for 9.6 Hz noise burst train in rat PAF neurons. For the second noise
burst, note facilitation of response in neurons after enrichment (N=115) and depression of
response in the control neurons (N=132). The black dots above the PSTHs indicate
significant differences (p<.05) in instantaneous firing rate at that millisecond for the two
housing conditions .
27
Repetition Rate Transfer Function
* ** **
*
Standard
Enriched
Normalized spikes/stimulus
Action Potentials/Stimulus
2
1.5
1
0.5
0
0
2
4
6
8
10
12
14
16
18
20
Repetition Rate(Hz)
Figure 6. Normalized mean Repetition Rate Transfer Function (RRTF) in PAF neurons. The
mean RRTF at each repetition rate is plotted with standard error of mean. Enriched neurons
(N=115) demonstrate a greater ability than control neurons (N=132) in keeping up with fast
incoming acoustic input. Asterisks (*) denote p<.05.
28
Vector Strength
0.65
Standard
Enriched
0.6
0.55
Vector Strength
0.5
0.45
0.4
0.35
0.3
0.25
0.2
2
4
6
8
10
12
Rates(Hz)
14
16
18
20
Figure 7. Vector strength of PAF neurons in response to noise burst trains in PAF. Vector
strength, an indication of phase-locking of stimuli is plotted for each rate of noise burst train
presentation with standard error of mean. Enriched neurons (N=115) had a greater
synchronization than control neurons (N=132) between acoustic stimulus and action
potentials for faster rates of noise burst trains. Asterisks (*) denote p<.05.
29
Rayleigh Statistic
300
Enriched
Standard
Raleigh Statistic value
250
200
150
100
50
0
2
4
6
8
10
12
Rates(Hz)
14
16
18
20
Figure 8. Rayleigh Statistic of PAF neurons in response to noise burst trains. Rayleigh
Statistic combines the degree of synchronization with action potentials evoked and is a
measure of the statistical significance of vector strength. Asterisks (*) denote p<.05.
30
NOISE BURST CLASSIFIER
0.4
PERCENT CORRECT
0.35
0.3
0.25
0.2
0.15
0.1
chance
0.05
0
CONTROL(n=156)
ENRICHED(n=127)
Figure 9. Nearest neighbor classifier performance in recognizing neural responses to noise
burst trains in PAF. The classifier is presented with a single sweep of neural activity to a
noise burst train and predicts the rate of the noise burst train. Enriched neurons had more
distinct responses to each of the 14 noise burst trains and a higher performance on the
classifier.. Asterisk (*) denotes p<.0001.
31
/tad/
4
x 10
4
x 10
Frequency (kHz)
4
3
2
200
Time (ms)
4
Liquid Consonants
0
0
400
/dad/
x 10
4
Frequency (kHz)
Stop Consonants
1
3
2
1
0
0
100
200
300
Time (ms)
400
3
2
1
0
0
200
400
Time (ms)
4
x 10
/rad/
4
Frequency (kHz)
Frequency (kHz)
4
/lad/
3
2
1
0
0
200
400
Time (ms)
Figure 10. Examples of speech spectrograms. Spectrograms of 4 speech sounds used to
determine PAF neuron responses. Note the slow onset of spectral energy in liquid consonant
sounds /lad/ and /rad/ (right panel) as compared to stop consonants /tad/ and /dad/ (left
panel).
32
B
A
PSTH response to /DAD/ in PAF
100
Control
Enriched
Control
Enriched
80
80
60
60
Spikes/sec
Spikes/sec
100
PSTH response to /TAD/ in PAF
40
20
40
20
0
0
50
100
150
200
250
Time(ms)
300
350
400
450
50
100
150
200
250
Time(ms)
300
350
400
450
Figure 11. Population PSTHs of response to /DAD/ & /TAD/ in PAF. The black dots above
the PSTHs indicate significant differences (p<.05) in instantaneous firing rate at that
millisecond for the two housing conditions . Note an increase in instantaneous firing rate for
the onset response to /DAD/ & /TAD/ in enriched neurons (N=124) compared to control
neurons (N=135).
33
B
A
PSTH response to /LAD/ in PAF
PSTH response to /RAD/ in PAF
100
Control
Enriched
Control
Enriched
80
80
60
60
Spikes/sec
Spikes/sec
100
40
40
20
20
0
0
50
100
150
200
250
Time(ms)
300
350
400
450
50
100
150
200
250
Time(ms)
300
350
400
450
Figure 12.Population PSTHs of response to /RAD/ & /LAD/ in PAF. The black dots above
the PSTHs indicate significant differences (p<.05) in instantaneous firing rate at that
millisecond for the two housing conditions . Note a lack of an increase in instantaneous firing
rate for the onset response to /RAD/ & /LAD/ in enriched neurons (N=124) compared to
control neurons (N=135) when contrasted with responses to /DAD/ & /TAD/ (figure 10).
Table 1. Response Properties of Posterior Auditory Neurons from rats housed in enriched and standard environments
Parameter
Standard
Enriched
(N=153 PAF sites)
(N=126 PAF sites)
Significant change
after EE
P value
Receptive Field - BW10 (octaves)
1.83 + 0.12
1.37 + 0.15
25%
<0.05
Onset Latency (ms)
43.83+ 5.8
24.23+ 3.72
45%
<0.05
Peak Latency (ms)
57.48+ 5.64
33.33+ 3.64
42%
<0.01
End Latency (ms)
89.53 + 5.67
56.43+ 3.9
37%
<0.0001
Neural response threshold (dB)
25.16 + 1.46
22.47 +1.29
NA
0.19
Tonal peak firing rate(spikes/sec)
24.8 + 3.79
37.97 + 3.91
53%
<0.05
Tonal response strength(spikes/tone)
1.44 + 0.1
1.12 + 0.07
22%
<.05
Noise burst peak firing rate(spikes/sec)
43.88 + 1.12
56.08 + 1.63
28%
<10-5
Noise burst response strength(spikes/noise)
1.14 + 0.11
1.17 + 0.11
NA
0.71
Spontaneous firing (spikes/20ms)
11.68 + 0.77
13.27 + 1.09
NA
0.22
Values indicate mean + standard error. Statistical significance was assessed using Student’s t-tests.
increase in value
or
indicates a decrease or
34
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CHAPTER THREE
ROLIPRAM INDUCES FREQUENCY SPECIFIC CORTICAL PLASTICITY
IN RAT A1
Vikram Jakkamsetti, Kevin Q. Chang, Jai A. Shetake and Michael P. Kilgard
School of Behavioral and Brain Sciences, GR41
The University of Texas at Dallas
800 W. Campbell Road
Richardson, Texas 75080-3021
Running Title: Rolipram Induces Frequency Specific Cortical Plasticity in rat A1
Key words: : phosphodiesterase IV, critical period, experience dependent plasticity,
neuromodulation
Corresponding author: Vikram Jakkamsetti
Email: [email protected]
38
39
ABSTRACT
The period between establishment of connections from peripheral sensory organs to
sensory cortex and final maturation of the sensory cortex is referred to as a critical period.
During the critical period, passive exposure to sensory stimuli can drive stimuli specific
changes in the cortex. Experiments have proved that such activity dependent cortical
reorganization is mediated by an increase in basal cAMP (cyclic adenosine mono phosphate)
levels in the cortex. We hypothesized that raising cAMP levels in adult rat cortex will mimic
experience dependent plasticity seen during the critical period. To test this we injected rats
with 0.5mg rolipram, a phosphodiesterase IV inhibitor, and immediately exposed them to
tones ~every 1 sec for 2 hours every day for 20 days. We observed that the length of the
cortex corresponding to half an octave above and below input frequency had increased by
30%. Rolipram significantly narrowed the receptive fields for tones in an input specific
manner. Reactivation of input specific critical period plasticity in adults could contribute to
researching tools for effecting targeted plasticity in neurorehabilitation.
INTRODUCTION
The cerebral cortex is highly plastic during development. Passive exposure to sensory stimuli
in a developing animal causes stimuli specific reorganization of the sensory cortex. Examples
of such experience dependent plasticity can be seen across sensory systems. Suturing the
eyelid shut during development increases the proportion of the primary visual cortex
responding to the contralateral eye (Hubel et al., 1977). Plucking all but one row of whiskers
in a mouse induces an increase in barrel cortex column size for that row (Schlaggar et al.,
1993). In the auditory cortex, passive exposure to a tone during development increases the
40
brain extent responding to that tone (Zhang et al., 2001a; de Villers-Sidani et al., 2007).
However, after a critical period, such passive sensory exposure fails to cause experience
dependent plasticity in the sensory cortex (Recanzone et al., 1993; de Villers-Sidani et al.,
2007). Reactivation of activity dependent plasticity in the adult cortex could be of immense
value in providing a tool to research treatments for cortical processing disorders in adults.
Experience dependent plasticity in the developing sensory cortex requires synaptic
reorganization and related protein synthesis (Antonini and Stryker, 1993; Lendvai et al.,
2000; Trachtenberg et al., 2002). An event implicated in such synaptic reorganization is the
activation of cortical Cyclic Adenosine Monophosphate (cAMP) Response Element Binding
(CREB) protein (Mower et al., 2002). An increase in cortical cAMP levels during the critical
period activates PKA to stimulate CREB mediated activity dependent plasticity (Reid et al.,
1996) (Fischer et al., 2004) (Muller, 2000).. In fact, local infusion of cAMP analogues in
adult animals resulted in reactivation of ocular dominance plasticity in adult visual
cortex(Imamura et al., 1999). We hypothesized that elevation of cortical cAMP levels with a
systemically administered agent would induce experience dependent plasticity too.
Systemically administered Rolipram inhibits phosphodiesterase-IV to elevate cAMP
in brain structures, including the dorsal cochlear nucleus, medial geniculate body and all six
layers of the auditory cortex (Perez-Torres et al., 2000). The presence of evidence
suggesting that rolipram can cause input specific cortical plasticity could be of immense
benefit in stimulating the research of clinically applicable tools for inducing input specific
cortical plasticity.
41
To test our hypothesis, we administered rolipram to rats daily, followed immediately
by exposure to multiple iterations of a pure tone. After twenty days we evaluated
electrophysiological properties in A1 for cortical plasticity.
METHODS
To test rolipram’s ability to cause frequency specific map expansion, we involved 34
Sprague-Dawley rats (Charles Rivers Laboratories, Wilmington, MA). Of these fourteen
were injected with rolipram and exposed to either 4 or 19 kHz tones. Twelve more underwent
the same sound exposure preceded by injections with a vehicle instead of rolipram. Eight rats
underwent electrophysiological protocols without exposure to either tone or drug (figure 1).
Drug treatments and acoustic stimuli administration during chronic sound exposure::
Rolipram (Sigma,St.Louis,MO) dissolved in 1% DMSO and 0.9% saline at a dilution of
0.5mg/ml and was injected subcutaneously at a dose of 0.5mg/kg immediately before
exposing animals to pure tones in a double walled sound shielded chamber over a period of
two hours, once every day for 20 days. The period of exposure was based on the fact that
rolipram reached peak serum levels at 30mins after systemic administration and had a half
life of 1-3 hours for rats (Krause and Kuhne, 1988). DMSO control animals received 1ml/kg
of 1% DMSO dissolved in saline with the same acoustic exposure as the experimental
animals. Naïve control animals did not receive drug or acoustic exposure. A lack of weight
loss and untoward behavior of rats on daily observation indicated that the experiment
protocol was not stressful.
42
Acoustic stimuli-Tones: Pure tones, 4 or 19 kHz, 250ms duration, 25 ms onset and offset
ramps, at ~ 1 sec inter stimulus intervals with randomly varying amplitudes (20-60 dB). The
tones were generated by a MATLAB (Mathworks Inc., Natick, MA) program using Real
Time Processors (RP2) manufactured by TDT Technologies Inc. (Alachua, FL) and played
by a speaker calibrated for using an ACO Pacific (Belmont, CA) microphone (PS9200-7016)
and programs written in MATLAB for calibration of tone and intensity.
Surgery and Electrophysiological recording:
Acute Surgery
24 hours after the last day of drug and tone exposure, the rats underwent acute surgery for
electrophysiology. Anesthesia for surgery was induced by pentobarbital sodium (50 mg/kg
ip) and maintained to achieve a state of areflexia with supplemental dilute pentobarbital (8
mg/kg ip). The rat’s level of anesthesia was monitored by heart rate, breath rate, and toe
pinch. The animal’s cardiovascular status was further monitored by presence of urine during
hourly bladder voiding. Body temperature which was kept at 37oC by a heating pad each time
the anal temperature fell below 37 oC. Fluid balance was maintained with a 1:1 mixture of
5% dextrose and Ringer lactate (~0.5 ml/h). The trachea was cannulated to administer
humidified air and minimize oropharyngeal breath sounds. The cisterna magna was drained
to prevent cerebral edema. The right auditory cortex was then exposed, the dura resected and
viscous silicon oil added to the brain surface to prevent desiccation. Electrode penetration
points were referenced using vascular landmarks and marked on a digitized photograph of
the auditory cortex surface. Care was taken to avoid penetration of visible vasculature.
43
Stimulus Presentation and data collection:
Acoustic stimuli-Tones: were presented in a double-walled sound attenuating chamber from
a speaker (Motorola model No. 40-1221) 10 cm away from the contralateral ear. Frequency
and intensity calibrations were done using Tucker-Davis SigCal software and an ACO
Pacific (Belmont, CA) microphone (PS9200-7016). 1296 randomly interleaved pure tones
(25 ms duration, 3 ms ramps, every 500 ms) were generated using Brainware (Tucker-Davis
Technologies). The tones included 81 logarithmically spaced frequencies from 1-32 kHz,
each at 16 different intensities spaced 5 dB SPL apart from 0-75 dB SPL. Parylene-Tungsten
electrodes, 50μm in diameter, were used to collect multi-unit data from cortical layer IV-V
(600-650 μm intracortical depth).
Data Analysis
Tuning Curve Analysis: All data analysis was done offline. Tuning curve parameters were
defined by a program written in MATLAB. The spontaneous firing rate was calculated as the
spike rate in the first 9 ms recorded after presentation of tone and before onset of a neural
response in the cortex. Onset latency was the time from the onset of the stimulus to the
earliest reliable neural response reaching two standard deviations above spontaneous firing
rate. End latency was defined as the time when the PSTH (post stimulus time histogram)
returned to spontaneous levels. The neuronal responses between onset latency and end
latency were plotted with frequency of tone presentation as abscissa and intensity of tone
presentation as ordinate to derive tuning curves (figure 2). The characteristic frequency (CF)
was defined as the frequency that evoked a reliable response at the lowest intensity (response
threshold). Frequency bandwidth (BW) was the range of frequencies that a site responded to
44
at 10, 20, 30 and 40 dB above threshold. Voronoii tessellation using MATLAB was done to
determine frequency polygons corresponding to each penetration site (Figure 1). In essence,
each point within a polygon is closest to the recording point enclosed within that polygon.
Classification of the primary cortical field:The auditory cortex in rats consists of at least 4
distinct fields-primary auditory cortex(A1), posterior auditory field(PAF), anterior auditory
field(AAF) and ventral auditory field(VAF). We recognized A1 sites by their anteroposterior gradient, shorter latencies and narrower bandwidths (figure 2). The border of A1
with neighboring auditory fields was decided in the following manner: a) the A1-Posterior
auditory field(PAF) border was demarcated by an abrupt termination of A1’s frequency
gradient and confirmed by PAF sites having wider bandwidths and slower onset times
(Kalatsky et al., 2005; Pandya et al., 2007; Polley et al., 2007). b) the A1-Anterior auditory
field(AAF) border was demarcated by the reversal of the tonotopic gradient between the two
fields (Kalatsky et al., 2005; Polley et al., 2007) c) the A1-Ventral auditory field (VAF) was
decided by the presence of VAF sites having longer onset latencies, wider bandwidths and an
increased incidence of non-monotonic sites (Kalatsky et al., 2005).
Calculation of normalized antero-posterior extent: There is a significant correlation between
CFs in A1 and anteroposterior distance. Since the slope of this frequency gradient varied
with each rat (give standard deviations for both groups), for analysis of antero-posterior
extents of A1 across rats, we rotated the recording points along the frequency gradient axis
until the best correlation between CFs and antero-posterior distance was attained. The anteroposterior total length of A1 was calculated from the anterior most point in A1 to the posterior
most point in A1 and assigned the value of 1. All intra A1 lengths were compared in relation
to the total length and assigned the proportional value. We compared normalized antero-
45
posterior extents across groups to see for an effect in map expansion since % area could be
affected by a variability in A1 recording site distribution.
RESULTS
Exposing rats to a repeated tone after injecting them with rolipram increased the cortical A1
representation of the tones in a frequency specific manner. A1 neurons activated by the
presented tone became more selective with rolipram.
The auditory cortex in rats consists of at least 4 distinct fields-primary auditory
cortex(A1), posterior auditory field(PAF), anterior auditory field(AAF) and ventral auditory
field(VAF). A total of 2117 extracellular multi-unit cortical sites from 34 rats were recorded
in the auditory cortex across different fields including A1, PAF, AAF, and VAF. We
recognized A1 sites by their antero-posterior gradient, shorter latencies and narrower
bandwidths. Recordings from non-A1 sites were used to ascertain the borders of A1 (see
methods).
Rolipram induces frequency specific plasticity in A1
During development, the cortical plasticity seen is dependent on the sensory input
experienced. Exposure to a low frequency tone causes a low frequency A1 map expansion
and exposure to a high tone causes a high frequency A1 map expansion (Zhang et al.,
2001b). To test our hypothesis that rolipram would induce experience dependent plasticity
similar to that seen during development, we compared rats injected with rolipram that
received either a low frequency (4 kHz) or a high frequency (19 kHz) tone. Figure 3 depicts
data from an example A1 map from each group. Rats injected with rolipram and exposed to
46
a low frequency tone evidenced a higher proportion of A1 responding to low frequency
tones. For the rat exposed to 4kHz, 32 % area of A1 had CFs ranging from 2.8 to 5.6 kHz
(half an octave below and above 4 kHz respectively). In stark contrast, rats exposed to 19
kHz had a contraction in representation of low frequencies. Only 19 % area of A1 had CFs
ranging from 2.8-5.6 kHz. However, the rat exposed to 19 kHz had an expansion in A1 area
(A1 area= 39 %) that had CFs ranging from 13.4 kHz to 26.9 kHz (half an octave below and
above 19 kHz respectively) while the rat exposed to 4 kHz had a contraction in A1 area (A1
area= 20 %) representing higher frequencies. Correspondingly, the antero-posterior extent of
the frequency region being activated by chronic tone exposure increased, while the nonactivated cortical region showed a contraction in length. Rolipram significantly increased the
cortical extent corresponding to 4kHz to 29% above vehicle controls (mean normalized
length of A1 for 4kHz : vehicle = 0.17 ± 0.03, rolipram=0.22 ± 0.02 , p<.05) (figure 5). A
similar rolipram induced increase was seen for rats exposed to 19 kHz after rolipram
injections (mean normalized length of A1 for 19kHz : vehicle = 0.28 ± 0.03, rolipram=0.36
± 0.04 , p<.05). As has been demonstrated in previous reports, an experience dependent map
expansion was accompanied by a significant decrease in the proportion of cortex not
activated by the tone paired with rolipram (Kilgard and Merzenich, 1998a).
Rolipram causes an input specific change in receptive fields
Neurons in the primary sensory cortex respond to a specific range of sensory stimuli in the
somatosensory, visual or auditory space. For example, an A1 neuron might fire action
potentials for any tone in a 2 to 8 kHz range, which is referred to as the receptive field for
that neuron. Experience dependent plasticity can modify receptive fields. Training to
47
discriminate a low frequency tone for example, narrows receptive fields (Recanzone et al.,
1993). To examine if rolipram modifies bandwidths (receptive fields) of activated neurons,
we compared the bandwidths of low and high frequency neurons (figure 6). Being exposed to
a high frequency tone while under the effect of rolipram significantly sharpened the receptive
fields of high frequency neurons (5.6 – 32 kHz) (BW @ 40 dB for 19kHz exposed groups :
vehicle = 2.15 ± 0.06, rolipram=1.7 ± 0.05 , p<.05). The same low frequency neurons had
wider receptive fields if the rat was exposed to a 19 kHz tone. Similarly, a 19 kHz tone
caused a narrowing of bandwidths in high frequency neurons and a widening of bandwidths
for low frequency neurons. In effect, rolipram induced neurons to become more selective to
the tone that activated them.
Changes associated with passive tone exposure
Passive sensory input exposure has shown mixed results in previous studies. While
habituation is seen to occur to response strength in A1 (Condon and Weinberger, 1991) and
hyper stimulation of a whisker decreases cortical area in somatosensory cortex (Feldman and
Brecht, 2005), studies in the auditory cortex have noted a lack of similar map contraction to
non behaviorally relevant stimuli. Exposure to ~300 repetitions of a tone daily that did not
have behavioral relevance or that which was not paired with nucleus basalis stimulation did
not change the representation of that tone in the cortex (Recanzone et al., 1993; Kilgard and
Merzenich, 1998a). Possibly due to a 20 fold greater daily sound exposure (exposure to
~6400 tone repetitions daily) in our study, we observed a trend towards a decreased
representation of a tone after passive exposure. It appears that rolipram prevents this
contraction and further increases cortical representation of tone above naïve control rats by
48
9% (see figure). Passive exposure showed a trend towards affecting receptive fields too.
Neurons activated by a repeated tone became less selective for that tone, which was
significant for high frequency neurons (figure 6).
We failed to see a tone specific change in response strength, latencies or spontaneous firing
rates.
DISCUSSION
We provide evidence of inducing frequency specific plasticity in adult rats by
modulation of critical period mechanisms. A previous study has provided evidence for
pharmacological reactivation of critical period plasticity by modulating cortical inhibitory
systems in adult animals receiving continuous drug and sensory stimulation for multiple
weeks (Vetencourt et al., 2008).We suggest that our study is unique in contributing to the
issue since : a) We propose and modulate a different system -cAMP modulation for
reactivation of critical period rather than modulation of inhibitory systems. b) The precision
of input specific plasticity is greater in our study c) Our study simulates a therapy session in a
rehabilitative clinic- short drug and tone exposure times decreasing the possibility that post
therapy environment would affect map plasticity.
Concerns arise regarding the ubiquitous presence of cAMP and hence a wide region
of action of rolipram in the body. Studies indicate sub-cortical sites for rolipram action
(Perez-Torres et al., 2000) , suggesting the plausibility that our study’s A1 findings could be
attributed to a primarily sub-cortical re-organization. In fact, studies of cortical map
reorganizations also noticed massive sub-cortical receptive field re-mapping (Pons et al.,
49
1991; Jones, 2000). It remains to be shown if such sub-cortical plasticity cause or are caused
by cortical reorganization.
The anesthesia used in this study, sodium pentobarbital, activates GABAA (γ-amino
butyric acid) receptors at multiple sites involved in auditory signal processing (Richter and
Holtman Jr, 1982), potentially influencing our plasticity study. However, the following
points suggest the validity of using sodium pentobarbital in our study : a) a lack of effect of
sodium pentobarbital on CFs (Gaese and Ostwald, 2001), b) the fact that both the
experimental and the control rats received the same anesthesia and any change in neuronal
response would be due to a factor that is not common to both groups, c) the lack of an
opportunity for rolipram to interact with anesthesia since all anesthetic recordings took place
at least 24 hours after the last rolipram injection.
Rolipram could be useful in a clinical context. Rolipram can penetrate the blood brain
barrier and improve memory for hippocampal tasks (Barad et al., 1998; Zhang and
O'Donnell, 2000), achieve beneficial effects in models of Alzheimer’s disease (Gong et al.,
2004), depression (Wachtel, 1983), psychosis (Siuciak et al., 2007) and inflammatory
disorders in the Central Nervous System (CNS) (Sommer et al., 1995) . Rolipram is
prescribed as an oral anti-depressant in Europe and Japan and has shown proof of beneficial
CNS effects (Smith, 1996). Our presence of evidence suggesting that rolipram can cause
input specific cortical plasticity could be of immense benefit in a) stimulating the research of
clinically applicable tools for inducing input specific cortical plasticity and b) appropriate
usage of the drug when used as an anti-depressant.
Administration of other agents did succeed in achieving sensory input specific
receptive field plasticity in adults (Manunta and Edeline, 1997; Imamura et al., 1999;
50
Penschuck et al., 2002). However, their route of drug administration was either local or short
lasting (lasting only minutes) or both. Our preliminary results are the first to show
development of input specific cortical plasticity as a consequence of systemic administration
of an agent. Besides, since our cortical recordings are done at least 24 hours after the last
rolipram injection, our results are the first to show long lasting input specific cortical
plasticity induced by systemically administered agents. Developing systemically applicable
agents that cause long term targeted cortical reorganization could be of great value in guiding
neuronal rehabilitation research.
APPENDIX
CHAPTER THREE
Habituation
Injection + Tone Exposure
Period after
last
injection
Neurophysiological
recording
Rolipram + 4 kHz (N=8)
Rolipram + 19kHz (N=6)
Vehicle + 4 kHz(N=6)
Vehicle +19 kHz(N=6)
1-2 days
20 days
1 day
Figure 1. . Illustration of experimental protocol. Habituation involved making a rat
comfortable with the immobilization technique used for subcutaneous injections. A waiting
period of 24 hours after the last injection was undertaken to avoid high serum levels of
injected agent during physiology.
51
52
B
A
Naïve Control
60
1.8
Naïve Control
1.6
9x
o
6x
1.4
1.2
1
0.8
0.6
o
0.4
0.2
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40
5x 16
x
x
26
x
32
0
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-0.5
50
2
2
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2
1x
6
2
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2
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x
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8 4
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16
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6
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32
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2x
7x
3x
1
1
25
30
20
10
x
10
1.5
2
2.5
3
3.5
Best Freq
Figure 2.A) Example of a tuning curve recorded from a naïve rat. CF=Characteristic
Frequency. BW=Bandwidth. B) Example of a cortical primary auditory cortex (A1) map
from a naïve rat. Note the frequency gradient from high to low frequencies progressing from
anterior to posterior. “x” indicates sites in non-primary auditory cortex and “o” indicates
sites non-responsive to tones.
53
A
B
r3final
1
60
16
8
1.7
5
21 22
25
25
31
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24
15
20 23 15 17
26
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6 6
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Normalized antero-posterior distance
2
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Characteristic Frequency
16
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1
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1
D
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26 17
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C
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1.8
3
2
6
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1.8
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32
32
16
8
4
2
1
0
Figure 3. Example of cortical length measurement for Rolipram injected group . A) &B)
Example A1 map and illustration of frequency gradient of a rat injected with Rolipram and
exposed to 4 kHz tones. The vertical dark blue solid and dotted vertical lines bracket the
regions half an octave above and below 4 kHz and 19 kHz. C) & D) Similar example plot of
rat injected with Rolipram and exposed to 19 kHz tones. Note the increase in antero-posterior
length around 4 kHz for the rat exposed to 4 kHz and around 19 kHz for the rat exposed to
19 kHz. Note also the A1 map contraction around the unexposed frequency.
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A
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Figure 4. Example of cortical length measurement for vehicle injected group . A) &B)
Example A1 map and illustration of frequency gradient of a rat injected with vehicle and
exposed to 4 kHz tones. C) & D) Similar example plot of rat injected with vehicle and
exposed to 19 kHz tones. Note the decrease in antero-posterior length around 4 kHz for the
rat exposed to 4 kHz and around 19 kHz for the rat exposed to 19 kHz.
55
A
B
CORTICAL LENGTH OF HIGH FREQ. NEURONS
0.45
0.4
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NORMALIZED CORTICAL LENGTH
CORTICAL LENGTH OF LOW FREQ. NEURONS
0.45
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0
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Veh+4k Veh+19k
Roli+4k Roli+19k
Figure 5. Cortical length comparisons. A) Cortical length corresponding to half an octave
above and below 4 kHz. B) Cortical length corresponding to half an octave above and
below19 kHz. (*) = significant changes between the two rolipram injected groups. (***)=
significant changes between the rolipram group and the vehicle group exposed to the same
tone. (.) = significant changes between the two vehicle injected groups All significant
comparisons characterized by p< .05..
56
A
B
BANDWIDTH PLASTICITY
BANDWIDTH PLASTICITY
2.5
2.5
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Veh+19k
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BANDWIDTH @ 40 dB(OCTAVES)
BANDWIDTH @ 40 dB(OCTAVES)
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LOW CF NEURONS
HGH CF NEURONS
LOW CF NEURONS
HGH CF NEURONS
Figure 6. Bandwidth Plasticity. A) Average bandwidths 40 dB above threshold for the two
Rolipram injected groups along with standard error of means. The solid line between the low
and high frequency neuron groups illustrates a double dissociation effect induced by
rolipram. Low frequency neurons underwent narrowing of receptive fields if activated by low
frequency tone and broadened receptive fields if not activated ( by a 19 kHz tone). A
corresponding effect is seen for high frequency neurons. B) Average bandwidths 40 dB
above threshold for the two Rolipram injected groups along with standard error of means.
Note that repeated passive exposure to a tone causes changes opposite to that seen with tones
+ Rolipram.
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CHAPTER FOUR
M1 AGONIST CEVIMELINE (AF102B) INDUCES INPUT SPECIFIC FREQUENCY
MAP PLASTICITY IN RAT PRIMARY AUDITORY CORTEX
Vikram Jakkamsetti, Jai A. Shetake, Kevin Q. Chang, Rolan O. Torres, Kamini Krishnan,
and Michael P. Kilgard
School of Behavioral and Brain Sciences GR41
The University of Texas at Dallas
800 W. Campbell Road
Richardson, Texas 75080-3021
Running Title: M1 agonist Cevimeline (AF102B) induces input specific
frequency map plasticity in rat primary auditory cortex
Key words: : nucleus basalis stimulation, critical period, amphetamine, neuromodulation
Corresponding author: Vikram Jakkamsetti
Email: [email protected]
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ABSTRACT
Nucleus Basalis stimulation paired with sensory input releases cortical acetylcholine in adult
mammals to induce input specific cortical plasticity. Acetylcholine mediates this effect
through muscarinic M1 receptors. We hypothesized that M1 agonist administration paired
with sensory stimuli would induce stimuli specific cortical plasticity. To test this hypothesis,
rats were given subcutaneous injections of an M1 agonist Cevimeline (AF102B) and exposed
to a 250ms pure tone ~1/ sec for two hours every day for 20 days. One day after the last
injection, multi-unit recordings were conducted under anesthesia to construct primary
auditory cortex frequency maps. For rats exposed to a 4 kHz tone, the proportion of cortex
containing characteristic frequencies 4 kHz ± 0.25 octaves was significantly increased by
30%. Similarly, pairing a 19 kHz tone with M1 agonist injections increased the extent of
cortex containing characteristic frequencies 19 kHz ± 0.25 by 25%. Having a
pharmacological tool to reopen the critical period and induce input specific cortical plasticity
could be useful in better understanding and treating cortical disorders.
INTRODUCTION
The adult brain has a remarkable potential to rewire itself. Significant cortical reorganization
is induced in response to behaviorally relevant sensory cues in the environment. Training to
detect a sensory stimulus leads to an enhanced representation of that stimulus in the cortex .
For example, in the auditory cortex, training to discriminate a tone leads to an increased
representation of that tone in the auditory cortex (Recanzone et al., 1993). Fear conditioning
to a tone induces identical receptive field plasticity in the cortical map (Bakin and
Weinberger, 1990). The nucleus basalis has been implicated in this experience dependent
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plasticity. On presentation of a behaviorally relevant cue, connections from the forebrain and
the amygdala to the nucleus basalis stimulate the nucleus basalis to release acetylcholine in
the cortex (Mesulam and Geula, 1988). The released acetylcholine plays a crucial role in
nucleus basalis mediated plasticity. Cortical acetylcholine modifies cortical receptive field
properties to increase the representation of the cue (Kilgard and Merzenich, 1998a). In fact,
lesions of the cholinergic neurons in the nucleus basalis prevent the development of cortical
plasticity (Kilgard and Merzenich, 1998a; Miasnikov et al., 2001) and blocking the effect of
acetylcholine on muscarinic receptors causes a lack of cortical reorganization (Miasnikov et
al., 2001). Acetylcholine’s induction of activity dependent plasticity is mediated by M1
receptors . In M1-knockout mice, there is about 70% reduction of nucleus basalis mediated
tone-specific changes in receptive fields, suggesting that nucleus basalis mediated plasticity
requires M1 receptor activation (Zhang et al., 2006).
We hypothesized that activation of the
M1 receptor by an M1-agonist along with presentation of a tone will induce activity
dependent reorganization of the auditory cortex. To test this hypothesis, we evaluated the
cortical responses of rats after 20 days of daily exposure to tones after subcutaneous
injections of M1-agonist Cevemiline.
Since about 30% of the cortical plasticity achieved by nucleus basalis stimulation
occurs through non-M1 muscarinic receptors it seems likely that administration of an agent
that induces cortical acetylcholine release by directly stimulating NB would induce cortical
plasticity that is greater in magnitude than administration of an M1-agonist. Systemic
Amphetamine has been demonstrated to stimulate the nucleus basalis to release cortical
acetylcholine (Casamenti et al., 1986; Arnold et al., 2001). We hypothesized that
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administration of amphetamine along with tones would lead to activity dependent plasticity
that is greater than that seen by M1-agonist alone.
METHODS
Forty five Sprague-Dawley rats (Charles Rivers Laboratories, Wilmington, MA) underwent
neurophysiological analysis in this study. Of these twelve were injected with Cevemiline and
exposed to either 4 or 19 kHz tones. Twelve more rats underwent the same sound exposure
preceded by injections with saline instead of Cevemiline. Nine were injected with
amphetamine and exposed to either 7 or 24 kHz tones. Three rats were injected with saline
and exposed to 7 kHz. Eight rats underwent electrophysiological protocols without exposure
to either tone or drug (figure 1).
Drug treatments and acoustic stimuli administration during chronic sound exposure::
Cevimiline (Evoxac®, Daiichi Sanyo Inc., Parsippany, NJ, USA) or D-amphetamine (SigmaAldrich Corp , St.Louis, MO, USA) dissolved 0.5mg/ml in 0.9% saline was injected
subcutaneously at a dose of 0.5mg/kg immediately before exposing animals to pure tones in a
double walled sound shielded chamber over a period of two hours, once every day for 20
days. The period of exposure was based on the fact that Cevimeline reached peak serum
levels at one and a half hours after systemic administration (product brochure from Evoxac)
and that D-amphetamine induced acetylcholine release in the cortex almost reached baseline
levels 110 minutes after i.p. injection (Casamenti et al., 1986). Saline vehicle control animals
received 1ml/kg of 0.9% saline with the same acoustic exposure as the experimental animals.
Naïve control animals did not receive drug or acoustic exposure. A lack of weight loss and
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excessive salivation on daily observation indicated that the experiment protocol did not result
in observable adverse effects.
Acoustic stimuli-Tones: Pure tones, 4 or 19 kHz, 250ms duration, 25 ms onset and offset
ramps, at ~ 1 sec inter stimulus intervals with randomly varying amplitudes (20-60 dB). The
tones were generated by a MATLAB (Mathworks Inc., Natick, MA) program using Real
Time Processors (RP2) manufactured by TDT Technologies Inc. (Alachua, FL) and played
by a speaker calibrated for using an ACO Pacific (Belmont, CA) microphone (PS9200-7016)
and programs written in MATLAB for calibration of tone and intensity.
Surgery and Electrophysiological recording:
Acute Surgery
24 hours after the last day of drug and tone exposure, the rats underwent acute surgery for
electrophysiology. Anesthesia for surgery was induced by pentobarbital sodium (50 mg/kg
ip) and maintained to achieve a state of areflexia with supplemental dilute pentobarbital (8
mg/kg ip). The rat’s level of anesthesia was monitored by heart rate, breath rate, and toe
pinch. The animal’s cardiovascular status was further monitored by presence of urine during
hourly bladder voiding. Body temperature which was kept at 37oC by a heating pad each time
the anal temperature fell below 37 oC. Fluid balance was maintained with a 1:1 mixture of
5% dextrose and Ringer lactate (~0.5 ml/h). The trachea was cannulated to administer
humidified air and minimize oropharyngeal breath sounds. The cisterna magna was drained
to prevent cerebral edema. The right auditory cortex was then exposed, the dura resected and
viscous silicon oil added to the brain surface to prevent desiccation. Electrode penetration
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points were referenced using vascular landmarks and marked on a digitized photograph of
the auditory cortex surface. Care was taken to avoid penetration of visible vasculature.
Stimulus Presentation and data collection:
Acoustic stimuli-Tones: were presented in a double-walled sound attenuating chamber from
a speaker (Motorola model No. 40-1221) 10 cm away from the contralateral ear. Frequency
and intensity calibrations were done using Tucker-Davis SigCal software and an ACO
Pacific (Belmont, CA) microphone (PS9200-7016). 1296 randomly interleaved pure tones
(25 ms duration, 3 ms ramps, every 500 ms) were generated using Brainware (Tucker-Davis
Technologies). The tones included 81 logarithmically spaced frequencies from 1-32 kHz,
each at 16 different intensities spaced 5 dB SPL apart from 0-75 dB SPL. Parylene-Tungsten
electrodes, 50μm in diameter, were used to collect multi-unit data from cortical layer IV-V
(600-650 μm intracortical depth).
Data Analysis
Tuning Curve Analysis: All data analysis was done offline. Tuning curve parameters were
defined by a program written in MATLAB. The spontaneous firing rate was calculated as the
spike rate in the first 9 ms recorded after presentation of tone and before onset of a neural
response in the cortex. Onset latency was the time from the onset of the stimulus to the
earliest reliable neural response reaching two standard deviations above spontaneous firing
rate. End latency was defined as the time when the PSTH (post stimulus time histogram)
returned to spontaneous levels. The neuronal responses between onset latency and end
latency were plotted with frequency of tone presentation as abscissa and intensity of tone
presentation as ordinate to derive tuning curves (figure 2). The characteristic frequency (CF)
66
was defined as the frequency that evoked a reliable response at the lowest intensity (response
threshold). Frequency bandwidth (BW) was the range of frequencies that a site responded to
at 10, 20, 30 and 40 dB above threshold. Voronoii tessellation using MATLAB was done to
determine frequency polygons corresponding to each penetration site . In essence, each point
within a polygon is closest to the recording point enclosed within that polygon.
Classification of the primary cortical field:The auditory cortex in rats consists of at least 4
distinct fields-primary auditory cortex(A1), posterior auditory field(PAF), anterior auditory
field(AAF) and ventral auditory field(VAF). We recognized A1 sites by their anteroposterior gradient, shorter latencies and narrower bandwidths (figure). The border of A1 with
neighboring auditory fields was decided in the following manner: a) the A1-Posterior
auditory field(PAF) border was demarcated by an abrupt termination of A1’s frequency
gradient and confirmed by PAF sites having wider bandwidths and slower onset times
(pandya, doron,polley). b) the A1-Anterior auditory field(AAF) border was demarcated by
the reversal of the tonotopic gradient between the two fields (polley,kalatsky) c) the A1Ventral auditory field (VAF) was decided by the presence of VAF sites having longer onset
latencies, wider bandwidths and an increased incidence of non-monotonic sites (kalatsky).
Calculation of normalized antero-posterior extent: There is a significant correlation between
CFs in A1 and anteroposterior distance. Since the slope of this frequency gradient varied
with each rat (give standard deviations for both groups), for analysis of antero-posterior
extents of A1 across rats, we rotated the recording points along the frequency gradient axis
until the best correlation between CFs and antero-posterior distance was attained. The anteroposterior total length of A1 was calculated from the anterior most point in A1 to the posterior
most point in A1 and assigned the value of 1. All intra A1 lengths were compared in relation
67
to the total length and assigned the proportional value. We compared normalized anteroposterior extents across groups to see for an effect in map expansion since % area could be
affected by a variability in A1 recording site distribution.
RESULTS
General Observations
A total of 3441 extracellular multi-unit cortical sites from 45 rats were recorded in the
auditory cortex from different fields including A1 , PAF, and ventral auditory field (VAF)
.CFs and classification of sites as belonging to A1 were done as in chapter 3. Briefly, A1
sites were identified by their tonotopcity, narrow bandwidths and shorter latencies and nonA1 sites were used to determine the border of A1 (see methods).
Cevimeline + 4 kHz increases low frequency cortical extent
. Exposure of a rat to a tone during nucleus basalis stimulation increases the proportion of the
cortex that represents that tone. To test our hypothesis that Cevimeline would induce
plasticity similar to that seen during nucleus basalis stimulation we estimated the area of the
cortex that corresponded to CFs half an octave above and below 4kHz . Consistent with
nucleus basalis stimulation studies, Cevimeline demonstrated a 33% increase in the
percentage of A1 area with CFs associated with the input frequency. Inspite of an impressive
difference in means between the rat groups, a variability in the narrow region of area being
compared likely prevented this result from being statistically significant (%area of A1 for
4kHz : vehicle = 27± 4.8 , Cevimeline= 33 ± 5.3 , p>.05). The anteroposterior extent of a
frequency region is a one dimensional measure and less variable in A1. This measure is less
68
likely to show a change without an actual shift in the border of a frequency region along the
tonotopic axis. We quantified the cortical extent corresponding to a given tone by
determining the antero-posterior distance covered by CFs that ranged half an octave below
and above the given tone (figure 3). Cevimeline significantly increased the cortical extent
corresponding to 4kHz to almost 30% above controls (normalized length of A1 for 4kHz :
0.17± 0.03 vehicle = , Cevimeline=0.22 ± 0.01 , p<.05) (figure 5 A).
Cevimeline + 19 kHz increases high frequency cortical extent
To observe if Cevimeline causes effects that are input specific, we examined cortical extents
of rats injected with Cevimeline and exposed to 19 kHz. Compared to vehicle rats ,
Cevimeline injected rats had a 30 % increase in the cortical length corresponding to half an
octave above and below 19 kHz controls (normalized length of A1 for 4kHz : 0.27± 0.03
vehicle = , Cevimeline=0.33 ± 0.04 , p<.05) (figure 5 B). Expansion to the input frequency
was accompanied by a contraction of cortical extent corresponding to non input frequencies.
For example, the frequency region corresponding to 4kHz in a rat injected with Cevimeline
and exposed to 19 kHz was significantly smaller than for a rat injected with Cevimeline and
exposed to 4 kHz.
Amphetamine + tone fails to induce input specific plasticity
Animals injected with amphetamine and exposed to 7 kHz had the same frequency gradients
as the saline control and the naïve control group. A clear difference in tonotopicity between
the different groups was not obvious. In order to objectively check for changes in
tonotopicity, we examined the antero-posterior distance covered by CFs that ranged from 0.5
69
octaves below to 0.5 octaves above 7 kHz. Administration of amphetamine at 7 kHz did not
significantly increase the relevant cortical length when compared to both the naïve control
and the saline control animals (figure 6A) . Administration of 24 kHz along with
Amphetamine did not cause an input specific change in the cortical map either (figure 6B).
DISCUSSION
We provide evidence that activation of M1-receptors in adults with 0.5mg of Cevemiline
induces frequency specific plasticity in the cortex. Amphetamine, which causes a nonspecific activation of multiple cholinergic receptors, does not induce input specific plasticity.
Many studies, both clinical and animal based, (Feeney and Hovda, 1985; Walker-Batson et
al., 1995; Buetefisch et al., 2002; Dinse et al., 2003; Tobey et al., 2005) suggest a strong role
of amphetamine in facilitating activity dependent . However, pairing amphetamine with
exposure to pure tones failed to cause input specific changes in the tonotopicity of A1. There
are two possibilities: A) Amphetamine did elicit input specific plasticity but the results were
not discernable or B) Amphetamine did not produce input specific frequency map plasticity
A)Amphetamine generated input specific plasticity in non-primary auditory cortex: Tobey et
al, 2005 used functional brain imaging techniques and found an enhancement of the signal in
regions of the auditory cortex responsible for processing the stimuli. Functional brain
imaging has a relatively lower spatial resolution (over millimeters) as compared to multiunit
electrode recording (fractions of a millimeter). The changes seen in functional brain imaging
could be the result of plasticity in a local network that extends over the primary auditory
cortex, possibly even including some secondary auditory cortical areas. Our study evaluated
70
changes in the primary auditory cortex and could have missed any plasticity occurring
outside this field.
II) Amphetamine failed to produce input specific frequency map expansion:
A failure to see significant findings could be due to the following factors: a) action on
multiple neurotransmitters: Along with increasing cortical acetylcholine, amphetamine also
increases nor-epinephrine, dopamine and serotonin levels in the cortex. With the resultant
non-specific activation of multiple cortical sites with multiple neurotransmitters, experience
dependent activation of specific cortical neurons could have had less of an effect in driving
plasticity. b) Chronic administration of drug instead of acute: Neurorehabilitation studies
that show activity or use-dependent enhancement of function achieved by amphetamine were
done using acute administration of amphetamine (Buetefisch et al., 2002; Dinse et al.,
2003)Those studies employing long term amphetamine administration did so with intervals
of 3-4 days between sessions (Feeney and Hovda, 1985; Walker-Batson et al., 1995). Acute
or interrupted administration of amphetamine could potentially prevent phenomena like
down-regulation of receptors associated with long-term continuous application of
amphetamine. Daily administration of drugs that prevent re-uptake of norepinephrine or
serotonin – the same neurotransmitters that amphetamine elevates – prevents development of
cortical plasticity (Gerdelat-Mas et al., 2005; Lange et al., 2007) . We used daily
amphetamine doses in our current study, and this protocol of administration could have
contributed to a lack of significant findings.
Recordings in this study were done under the effect of anesthesia. The current study
is based on the hypothesis that M1 receptors activated by acetylcholine contribute to cortical
plasticity. A number of plasticity studies examining the function of nucleus basalis mediated
71
acetylcholine release in the auditory cortex suggest that the use of general anesthesia does not
obscure significant findings. These studies include the use of a different anesthetic agent
urethane (Edeline et al., 1994b; Bakin and Weinberger, 1996; Bjordahl et al., 1998), under
anesthesia during training and recording(Bakin and Weinberger, 1996) , awake during
training but recording under anesthesia(Bjordahl et al., 1998) and unanesthetized during
training and recording (Edeline et al., 1994a) . Significant changes are noticed in acute
(Edeline et al., 1994a; Edeline et al., 1994b; Bakin and Weinberger, 1996; Bjordahl et al.,
1998) as well as chronic training protocols (Kilgard and Merzenich, 1998a) and have
reliably shown plasticity findings whether investigated immediately(Edeline et al., 1994b;
Bakin and Weinberger, 1996; Dimyan and Weinberger, 1999) or a day after cessation of
training (Bjordahl et al., 1998; Kilgard and Merzenich, 1998a) . The above given evidence
suggests that recording under anesthesia would not have obscured findings of cortical
plasticity in our study.
Systemic administration of Cevemiline (AF102B) and similar M1 agonists have been
used successfully to enhance memory in adult rats (ref), Alzheimer models (ref), and to
induce an increase in tone evoked responses in the auditory cortex (O’Neill). Cevemiline is
currently being used in the United States for Sjogren’s syndrome (refs). The presence of
evidence suggesting that Cevemiline can cause sensory input specific brain changes could be
of immense benefit in a) stimulating the research of clinically applicable tools for inducing
input specific cortical plasticity and b) appropriate usage of the drug today when used for
Sjogren’s syndrome.
Millions of people suffer from deficits in cortical neuronal processing as a
consequence of stroke, trauma, developmental anomalies and tumors. Recovery from and
72
rehabilitation of cortical neuronal processing disorders has been largely unsuccessful.
Expansion of primary cortical maps has been associated with improvements in behavioral
outcomes after cortical lesions in animal models (Xerri et al., 1998). Basic science
experiments have demonstrated that the frequency map of A1 is capable of massive
frequency specific map expansion as a consequence of long term operant training in a tone
discrimination task (Recanzone et al., 1993), fear conditioning (Bakin and Weinberger, 1990)
and nucleus basalis stimulation (Kilgard and Merzenich, 1998a). However, translation of
these map expansion methods into clinical practice as a therapy for cortical disorders has
proved to be very challenging. We suggest that researching M1 agonists to stimulate input
specific map plasticity in a clinical setting may aid the development of more effective
therapies for cortical processing disorders.
APPENDIX
CHAPTER FOUR
Habituation
Injection + Tone Exposure
Period after
last injection
Neurophysiological
recording
Cevimeline + low(N=6)
Cevimeline+ high (N=7)
Amphetamine + low (N=5)
Amphetamine + high (N=4)
Vehicle + low (N=9)
Vehicle + high (N=6)
1-2 days
1 day
20 days
Figure 1. Illustration of experimental protocol. Habituation involved making a rat
comfortable with the immobilization technique used for subcutaneous injections. A waiting
period of 24 hours after the last injection was undertaken to avoid high serum levels of
injected agent during physiology. The vehicle + low group included vehicle + 4 kHz (N=6)
and vehicle + 7 kHz (N=3).
73
74
A
Naïve Control
60
1.8
Naïve Control
1.6
9x
o
6x
1.4
1.2
1
0.8
0.6
o
0.4
0.2
0
0.5
3x
40
5x 16
x
x
26
x
32
0
-0.2
-0.5
50
2
2
5x
2
1x
6
2
2x
2
1 1
x
14
4
4 2
11
1
8 4
2
19
2
23
10
11
2
17
15
27
2
o
13 10
16
o
5
5
24 13 15 13
6
24 1215
32
2x
111512 8
24 24 23
12
12
13
31
x
14
6
26
25
x
23
11
3x
x
10
o
x
16
o
6x 2x
2x
2x
2x
7x
3x
1
1
25
30
20
10
x
10
1.5
2
2.5
3
3.5
Best Freq
Figure 2.A) Example of a tuning curve recorded from a naïve rat. CF=Characteristic
Frequency. BW=Bandwidth. B) Example of a cortical primary auditory cortex (A1) map
from a naïve rat. Note the frequency gradient from high to low frequencies progressing from
anterior to posterior. “x” indicates sites in non-primary auditory cortex and “o” indicates
sites non-responsive to tones.
75
A
B
rolipa4kdms09final
32
32
16
4
2
1.8
2
34
4 1.8 2
4
5
2
9
4
1.7
1.9
11
4
15
13
15
15
13
15 14
8
15
27
11
23 22
16
25
28
7
22
29
13
16
16
24
24
26 17
15
25
16
8
4
2
Characteristic Frequency
60
1
Normalized antero-posterior distance
C
6
14
13
19
11
16
27
26
13 16
20 19
13
14
26
16
26
15 14
26
6
13
13
11
5
14
13
11
6
4
7
11
32
1.9
2
2
16
2
5
8
4
35
43
1.8
1.9
5
6
4
6
2
0
0.2
0.4
0.6
0.8
Normalized antero-posterior distance
1
0.2
0.4
0.6
0.8
Normalized antero-posterior distance
1
32
1.8
6
12
Normalized antero-posterior distance
2
1
Best Freq (kHz)
Characteristic Frequency
1.7
13
7
2
D
8
11
4
1
60
12
8
Best Freq (kHz)
m1agonist4k06modfinal
14
16
16
8
4
2
1
0
Figure 3. Example of cortical length measurement for low tone exposure group . A) &B)
Example A1 map and illustration of frequency gradient of a control rat injected with vehicle
and exposed to 4 kHz tones. The vertical dark blue solid and dotted vertical lines bracket the
regions half an octave above and below 4 kHz and 19 kHz. C) & D) Similar example plot of
rat injected with M1 agonist Cevemiline and exposed to 4 kHz tones. Note the increase in
antero-posterior length around 4 kHz for the Cevemiline injected rat .
76
A
B
rolipa19kdm21final
32
32
7
24
30
9
24
26
19 15
22
18
8
20
15
15
8
13
7
1.5
3
7
7
18
5
9
1.8
2
6
2 6
14
16
4
3
7 6
2
2
7
8
12
1.7
8
1.9
1.9
4
6
13
2
28 23
Characteristic Frequency
60
16
8
4
2
25
1
Normalized antero-posterior distance
C
1
Best Freq (kHz)
16
8
10
28
25
27
24
19
10
14
11
13
5
5
713
13
15
15
5
8
6
7
3
4
3
2 1.8
5 1.8
2
4
1.8
5
5
5
4
2
Characteristic Frequency
32
26
1
0.2
0.4
0.6
0.8
Normalized antero-posterior distance
1
32
60
8
0.2
0.4
0.6
0.8
Normalized antero-posterior distance
D
m1agonist19k1final
25
0
16
8
4
2
5
Normalized antero-posterior distance
1
Best Freq (kHz)
1
0
Figure 4. Example of cortical length measurement for high tone exposure group . Example
A1 map and illustration of frequency gradient of a control rat injected with vehicle (A & B)
and Cevemiline (C&D) and exposed to 19 kHz tones. Note the increase in antero-posterior
length around 19 kHz for the Cevemiline injected rat .
77
A
B
CORTICAL LENGTH OF HIGH FREQ. NEURONS
0.45
0.45
0.4
0.4
NORMALIZED CORTICAL LENGTH
NORMALIZED CORTICAL LENGTH
CORTICAL LENGTH OF LOW FREQ. NEURONS
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0.35
0.3
0.25
0.2
0.15
0.1
0.05
Nav
Veh+4k Veh+19k
M1+4k M1+19k
0
Nav
Veh+4k Veh+19k
M1+4k M1+19k
Figure 5. Cortical length comparisons. A) Cortical length corresponding to half an octave
above and below 4 kHz. B) Cortical length corresponding to half an octave above and
below19 kHz. (***)= significant changes between the rolipram group and the vehicle group
exposed to the same tone. (.) = significant changes between the two vehicle injected groups.
All significant comparisons characterized by p< .05.
78
A
B
CORTICAL LENGTH OF LOW FREQ. NEURONS
CORTICAL LENGTH OF HIGH FREQ. NEURONS
0.25
NORMALIZED CORTICAL LENGTH
NORMALIZED CORTICAL LENGTH
0.25
0.2
0.15
0.1
0.05
0
0.2
0.15
0.1
0.05
Nav
Veh+7k
Amph+7k Amph+24
0
Nav
Veh+7k
Amph+7k Amph+24
Figure 6.Cortical length comparisons. A) Cortical length corresponding to half an octave
above and below 7 kHz. B) Cortical length corresponding to half an octave above and below
24 kHz. Note lack of significant changes in cortical length induced by amphetamine
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CHAPTER FIVE
SUMMARY AND CONCLUSIONS
The adult brain samples the environment through the sensory system and undergoes
dramatic changes for behaviorally relevant environmental features. This ability to adapt helps
an organism benefit from experience to increase its chances for survival. Understand the
mechanisms of experience dependent plasticity will help us harness this amazing ability of
the brain to change to relevant sensory input, which could help us clinically drive brain
changes that counteract those seen in brain disorders. This brings us to two main questions
that the dissertation aims to address: First, how does the sensory representation of the
environment in the brain change with meaningful experience? Second, how could we induce
experience dependent changes that could be explored in a clinical context?
The first chapter attempts to answer the first question by examining experience
dependent changes induced by environmental enrichment in a non-primary cortical auditory
field. Environmental enrichment has long been used for treating cortical processing disorders
and this chapter aims in understanding the cortical substrate of auditory enrichment. We
observed that enrichment induces PAF neurons to fire faster, more in phase with acoustic
input and with a better ability to keep up with rapid incoming input. An ability to respond
quickly allows neurons to more easily detect small changes in speed of incoming input.
Speech sounds that have a fast onset of sound energy induce stronger responses after
enrichment. An ability to fire more easily to rapidly incoming input by PAF neurons is
congruent with clinical findings of a betterment in cortical processing speed of dyslexics
87
88
after auditory training (Hayes et al., 2003b). Since enrichment induces paired pulse
depression to rapid inputs in A1 (Percaccio et al., 2005), we suggest that the clinically seen
findings might be attributable to non-primary cortical processing.
The second and third chapter attempt to bridge the gap between powerful basic
science insights and clinically applicable treatments for brain disorders. Multiple studies have
induced experience dependent plasticity in an adult lab animal. These studies predict the
immense clinical possibilities based on their research. For example, nucleus basalis
stimulation or local cortical application of cholera toxin (a cAMP elevating agent) paired
with a sensory stimuli induce input specific cortical reorganization (Kilgard and Merzenich,
1998a; Imamura et al., 1999). However the expense of deep brain stimulation and potential
adverse effects of deep brain electrode implantation or systemic administration of cholera
toxin decrease the feasibility of directly using these insights in a clinical context. We aimed
to bypass this bottleneck in translational research by using pharmacological agents that
induce plasticity through systemic administration. We observed that exposing rats to multiple
repetitions of a single tone after an increase of cAMP via injections of rolipram significantly
increased the extent of the cortex that responded to that tone. Rolipram also induced an input
specific narrowing of receptive fields within 20 days, a finding normally only seen after
auditory training for multiple months (Recanzone et al., 1993). M1-agonist, Cevemiline
increased the length of the cortex responding to the exposed tone. In contrast, an agent that
caused a non specific activation of all cholinergic receptors (amphetamine) failed to cause
tone specific cortical plasticity.
While we understand that much work has to be done to take our understanding of
experiential plasticity to clinically applicable treatments, we hope that the studies offered in
89
this dissertation will make a contribution-albeit small- to building a bridge from basic science
to clinical therapy.
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VITA
Vikram Jakkamsetti was born in Baroda, India in 1973. After completing his high school
education in Rosary High School, Baroda in 1992, he entered the medical school program at
Government Medical College, Surat, India. He was awarded his M.B.B.S. degree in 1998 and
subsequently went on to receive an M.D. in Internal Medicine from the same institute in
2002. His residency dissertation demonstrated correlative patterns between adenosine
deaminase levels in the cerebrospinal fluid (CSF) and CSF total protein, CSF white blood
corpuscle counts and mortality in tuberculosis meningitis patients. He elected to pursue a
fourth year as senior resident to complete and publish a study of cardiovascular
manifestations of leptospirosis in the Journal of Association of Physicians in India. He
subsequently entered the University of Texas at Dallas to begin his doctoral studies under the
guidance of Dr.Michael Kilgard. His long-term objective is to work to translate basic science
research into clinically viable therapeutic interventions for brain disorders.