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Spontaneous and Stimulus-Evoked Intrinsic Optical Signals
in Primary Auditory Cortex of the Cat
MATTHEW W. SPITZER, MICHAEL B. CALFORD, JANINE C. CLAREY, JOHN D. PETTIGREW,
AND ANNA W. ROE
Vision, Touch and Hearing Research Centre, Department of Physiology and Pharmacology, The University of Queensland,
St. Lucia, Queensland 4072, Australia
Received 14 June 2000; accepted in final form 3 November 2000
Spitzer, Matthew W., Michael B. Calford, Janine C. Clarey, John
D. Pettigrew, and Anna W. Roe. Spontaneous and stimulus-evoked
intrinsic optical signals in primary auditory cortex of the cat. J
Neurophysiol 85: 1283–1298, 2001. Spontaneous and tone-evoked
changes in light reflectance were recorded from primary auditory
cortex (A1) of anesthetized cats (barbiturate induction, ketamine
maintenance). Spontaneous 0.1-Hz oscillations of reflectance of 540and 690-nm light were recorded in quiet. Stimulation with tone pips
evoked localized reflectance decreases at 540 nm in 3/10 cats. The
distribution of patches “activated” by tones of different frequencies
reflected the known tonotopic organization of auditory cortex. Stimulus-evoked reflectance changes at 690 nm were observed in 9/10 cats
but lacked stimulus-dependent topography. In two experiments, stimulus-evoked optical signals at 540 nm were compared with multiunit
responses to the same stimuli recorded at multiple sites. A significant
correlation (P ⬍ 0.05) between magnitude of reflectance decrease and
multiunit response strength was evident in only one of five stimulus
conditions in each experiment. There was no significant correlation
when data were pooled across all stimulus conditions in either experiment. In one experiment, the spatial distribution of activated patches,
evident in records of spontaneous activity at 540 nm, was similar to
that of patches activated by tonal stimuli. These results suggest that
local cerebral blood volume changes reflect the gross tonotopic organization of A1 but are not restricted to the sites of spiking neurons.
Aside from the systematic representation of frequency (Merzenich and Brugge 1973; Reale and Imig 1980), details of the
functional organization of auditory cortex remain controversial. Several studies have provided evidence of compartmental
organization within the tonotopic representation of primary
auditory cortex (A1) in the cat based on clustered or banded
distributions of neurons with different response properties
(e.g., Imig and Adrian 1977; Mendelson et al. 1993; Middlebrooks and Pettigrew 1981; Phillips et al. 1994; Schreiner and
Mendelson 1990). Due to limitations of conventional microelectrode mapping techniques, however, a comprehensive view
of the functional organization of A1 has yet to emerge. In a
single mapping experiment, it is only possible to characterize
effects of a few stimulus parameters from a large number of
recording sites. Consequently, it is not yet clear how the
various topographies of response properties described by dif-
ferent studies relate to one another. A second limiting factor is
the lack of anatomical markers. The discovery of histological
markers for functionally distinct neuronal subpopulations,
most notably cytochrome oxidase, was a considerable aid to
elucidating the functional organization of visual cortex (Horton
and Hubel 1981; Humphrey and Hendrikson 1983; WongRiley 1979). In auditory cortex, by contrast, the same markers
provide little compelling evidence for compartmentalization
(Tootell et al. 1985; Wallace et al. 1991). Resolution of this
issue in auditory cortex may have implications for our understanding of cortical organization in general.
Optical imaging (OI) of intrinsic signals (Grinvald et al.
1986; Ts’o et al. 1990) offers both vastly increased spatial
sampling density and the potential to sample cortical responses
to a larger stimulus repertoire in a single experiment than is
possible with microelectrode mapping, making it a promising
alternative approach for studying the physiological organization of A1. This technique uses changes in light reflectance,
associated with physiological activity, to visualize the location
of cortical tissue activated by a given stimulus. The light
reflectance signals derive from multiple sources, including
changes in local blood volume, which dominate the signal at
wavelengths below 600 nm, and changes in the oxygenation
state of hemoglobin and light scattering, which provide a major
source of signals at longer wavelengths (Frostig et al. 1990;
Malonek and Grinvald 1996; Malonek et al. 1997). Because
neuronal responses are measured indirectly, it is essential to
verify results obtained by this method with electrophysiological recording. Although most studies of visual cortex have
shown a high degree of correspondence between stimulusevoked optical and neurophysiological responses (Crair et al.
1997; Ghose and Ts’o 1997; Grinvald et al. 1986; Roe and
Ts’o 1995; Shmuel and Grinvald 1996; Shoham et al. 1997),
under certain conditions, the areal extent of over which evoked
optical signals are recorded can be several times greater than
that of the neuronal spiking response (Das and Gilbert 1995).
Recently, several groups have used OI of intrinsic signals to
study the topography of stimulus evoked activity in auditory
cortex of rodents (Bakin et al. 1996; Harrison et al. 1998; Hess
and Scheich 1996). Results of these studies differ from those of
single-unit mapping studies of cat A1 (Heil et al. 1994; Phillips
Present address and address for reprint requests: M. W. Spitzer, Institute of
Neuroscience, University of Oregon, Eugene, OR 97403 (E-mail: spitzer@
uoneuro.uoregon.edu).
The costs of publication of this article were defrayed in part by the payment
of page charges. The article must therefore be hereby marked ‘‘advertisement’’
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
INTRODUCTION
www.jn.physiology.org
0022-3077/01 $5.00 Copyright © 2001 The American Physiological Society
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SPITZER, CALFORD, CLAREY, PETTIGREW, AND ROE
et al. 1994) in several respects, including threshold and time
course of evoked activity, spatial distribution of tone-evoked
activity, and effects of changing sound pressure level (SPL). It
is not clear, however, to what extent these apparent differences
are due to species differences or recording methodology because in only one case (Bakin et al. 1996) were optical images
verified with electrophysiological recording.
For a number of reasons, including the large exposed surface
area of auditory cortex and the elaborate auditory cortical
specializations, most mapping studies of A1 have been performed on the domestic cat (Reale and Imig 1980). As a result,
it is possible to formulate relatively high-order questions about
physiological organization in this species. On the other hand,
all published intrinsic signal-based OI studies of A1 have been
conducted on rodents, about which much less is known. The
present study was therefore undertaken to characterize stimulus-evoked intrinsic optical signals at different wavelengths in
cat A1 and to compare optical responses to neuronal spiking
responses elicited by the same stimuli. Preliminary accounts of
the results were published in abstract form (Spitzer and Clarey
1998).
METHODS
Anesthesia and surgical procedures
All surgical and experimental procedures were approved by the
Animal Experimentation Ethics Committee of the University of
Queensland and conformed to the guidelines for use of animals of the
National Health and Medical Research Council of Australia. Experiments were performed on cats between 8 wk and 10 mo of age.
Stimulus-evoked optical signals at 540 nm, presented in the following
text, were obtained from three cats, aged 18, 20, and 27 wk. Young
animals were used because it has been reported that the signal-tonoise ratio of optical signals is higher than in older animals (Hubener
et al. 1997). Moreover, because response properties of auditory cortical neurons such as latency and threshold mature to adult-like levels
within the first three to four postnatal weeks (Brugge et al. 1988), it is
unlikely that the present results are compromised by any physical
immaturity of auditory cortex.
Animals were initially sedated with ketamine hydrochloride and
inspected to ensure there were no signs of external ear blockage or
middle ear infection. Surgical anesthesia was then induced with a
single dose of pentobarbital sodium (25 mg/kg ip). Atropine sulfate
(10 mg/kg sc) was administered to minimize bronchial mucous secretion. Anesthesia was maintained with supplemental doses of ketamine
hydrochloride (0.5–5 mg 䡠 kg⫺1 䡠 h⫺1 iv, typically starting 2 h after
barbiturate injection) throughout the subsequent surgery and recording session. The subject’s heart rate was monitored throughout the
recording session. During the optical and electrophysiological recording sessions, anesthetic and supplementary fluids (lactated Ringer
solution) were administered by intravenous injection and/or continuous intravenous infusion; anesthetic dose rate was adjusted to maintain a constant heart rate and no signs of skeletal muscle activity
(indicated by high-frequency contamination of the electrocardiogram). Anesthetic level was sufficient to attenuate the eye-blink
reflex. Throughout all procedures, the animal’s temperature was maintained with a homeothermic heating blanket (Harvard Instruments).
Following induction of surgical anesthesia, the trachea was cannulated and an intravenous line was established. A craniotomy was
performed to expose the temporal cortical surface with the dura intact.
A recording chamber was mounted over the skull opening with acrylic
cement. The dura was then reflected to expose the cortical surface, and
the recording chamber was filled with low-viscosity silicone oil
(Corning) and sealed with a glass cover. Following the optical recording session, the top of the recording chamber was removed to permit
introduction of microelectrodes. Dexamethosone was administered (1
mg/kg iv) prior to reflection of the dura and opening of the recording
chamber to prevent cerebral edema. During the recording sessions,
subjects were situated on a vibration isolation table (Newport Instruments) housed in an anechoic chamber. The cat’s head was stabilized
by attachment of the skull to a stereotaxic frame. Following experiments, animals were euthanized by overdose of pentobarbitone sodium (120 mg/kg iv).
Optical data acquisition and acoustic stimulation
Intrinsic optical signals were recorded using the Imager 2001
video acquisition system (Optical Imaging, Germantown, NY), the
details of which have been described previously (Bonhoeffer and
Grinvald 1996; Grinvald et al. 1986, 1988; Ts’o et al. 1990). The
cortical surface was illuminated with narrowband light, generated
by band-pass filtering (band centers, 540, 630, or 690 ⫾ 10 nm;
interference filters from Edmund Scientific, Barrington, NJ) the
output of a tungsten light source, and conveyed by two fiber-optic
light guides. Video images of the illuminated cortex were acquired
at 30 frames per second with a CCD camera (Bischke, Japan). The
camera was positioned orthogonal to the exposed surface of putative primary auditory cortex (gyral surface between the tops of the
anterior ectosylvian and posterior ectosylvian sulci). Data were
collected with the camera focused between 350 and 500 ␮m below
the cortical surface to minimize artifacts due to the presence of
surface blood vessels. A typical imaging session began at least 4 h
after induction of anesthesia and continued for 12 h. While 12-bit
cameras permit the encoding of absolute reflectance value, the
Imager 2001 system employs differential imaging methodology to
allow the use of standard 8-bit video technology. In this method, a
reference image (average of 64 video frames) is obtained prior to
each block of recording trials. This reference image is subtracted
from each subsequent recorded image within a block of trials. The
reference-subtracted images constitute the stored data files on
which further analyses are performed. Such initial reference subtraction allows the encoding of the differential signal within the
8-bit limit and has comparable signal-to-noise resolution as that
obtained by storing the absolute reflectance values. Absolute reflectance values can be reconstructed from the reference images. In
this study, intrinsic optical signals were acquired by summing
video frames captured over 0.5 s for stimulus-evoked signals, or 1 s
for spontaneous signals, followed by reference subtraction. The
resulting differential image was then amplified, digitized (8 bits),
and stored on computer disk. The stored image produced by this
process will be referred to hereafter as a data frame.
Acoustic stimuli were generated digitally (MALab, Kaiser Instruments, Irvine, CA) and presented via a calibrated piezo-electric transducer (Motorola KSN 1141) positioned 25 cm from the ear contralateral to the imaged cortex and approximately 50° in azimuth from the
cat’s midline. Individual acoustic stimuli consisted of trains of five to
seven identical tone pips (10-ms cosine rise and fall, 70-ms duration,
730-ms inter-pip interval), as illustrated in Fig. 5. Detailed stimulus
parameters are included in figure legends. Stimuli were presented in
sets consisting of five or six combinations of frequency and sound
pressure level (SPL) and a no-stimulus condition, presented in random
order.
Acoustically evoked optical signals were recorded by acquiring
a sequence of data frames during presentation of each acoustic
stimulus. Acquisition of optical data was synchronized to acoustic
stimulus presentation, starting one frame (500 ms) prior to stimulus
onset and continuing for up to 6.5 s after stimulus offset (see Figs.
3 and 5). Following this data acquisition period, there was a silent
interval of 12 s. To remove periodic spontaneous variation of the
OPTICAL IMAGING IN AUDITORY CORTEX
optical signal (see RESULTS), it was necessary to sum optical data
recorded during multiple repeated trials of each stimulus set.
Typically, data were collected and stored on-line in blocks of four
or five repeated stimulus sets.
Acoustically evoked and spontaneous optical signals were visualized by off-line analysis (SumAnal program) (Ghose and Ts’o 1997).
For acoustically evoked images, corresponding data frames (i.e., same
stimulus and time after stimulation) from multiple blocks of stored
data were first summed. Each successive summed frame collected
after stimulus onset was then divided by the frame collected prior to
stimulus onset within the trial. (n.b. This differential analysis procedure should not be confused with the initial reference image subtraction performed prior to saving data, on-line.) The resulting values
indicate the change in light reflectance (⌬R) at each measured pixel
following stimulus onset. Further analyses are described in RESULTS.
To display ⌬R data as images, images were clipped (top and bottom
19% of the pixel value distribution removed) to eliminate large signals
due to blood vessel artifact and fit to a common linear 33 color scale
(shown in each figure). Spontaneous optical signals were visualized
using a similar procedure of frame-by-frame, temporal analysis of
signal development. However, data from individual trials (20-s data
acquisition period, no stimulus) were analyzed separately without
summation across blocks.
The present data were obtained in 10 experiments performed on
cats maintained under ketamine anesthesia. An earlier series of experiments was performed on 15 cats maintained under barbiturate
anesthesia (pentothal sodium). In general, results obtained using barbiturate anesthesia were inconclusive due to excessive variability.
However, a few references are made to results from these experiments, where appropriate.
Electrophysiological recording
Electrophysiological mapping was performed in four of the experiments. Following the imaging session, a dose of dexamethosone (1
mg/kg iv) was administered, and the lid of the recording chamber was
removed. A reference image of the cortical surface collected under
illumination with green light (590 nm) was used to guide electrode
placement and for later alignment of optical and electrophysiological
data. Glass-coated, tungsten microelectrodes (0.5–2.5 M⍀ impedance
at 1 kHz) were introduced perpendicular to the cortical surface using
a stepping motor microdrive (Herb Adams, Caltech) controlled from
outside the anechoic chamber. The electrode signal was amplified
(⫻1,000 gain) and filtered 0.3–5 kHz. Recordings of multi- and
single-unit activity were obtained by level triggering (MALab).
Multiunit recordings were only obtained at sites where action potentials of the constituent units could be clearly distinguished visually
using an oscilloscope. Single-unit recordings were also distinguished
by visual criteria. In each electrode penetration, an attempt was made
to record from the closest site to the cortical surface exhibiting
acoustically driven unit activity. In practice, the majority of recordings were obtained at depths between 400 and 800 ␮m.
Neuronal responses to the stimulus set used for optical imaging
were collected at each recording site. In addition, an attempt was
always made to determine the frequency/level combination that
gave an optimal response. The response to the “optimal” stimulus
was also recorded if it was considerably greater than responses to
any of the stimuli used for optical imaging. Slight modifications to
the stimulation protocol were made for electrophysiological recording: stimuli were presented as 70-ms-duration tone pips
(10-ms cosine rise/fall), 730-ms interstimulus interval, 20 repetitions. The time of occurrence of triggered action potentials and
stimulus events were logged (more than 1-␮s resolution) and
stored in a FIFO buffer, from which they were retrieved by the host
computer and stored on disk.
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RESULTS
Spontaneous optical signals
Spontaneous changes of light reflectance in auditory cortex
were observed in the absence of acoustic stimulation in 9/10
cats. In most cases, the spontaneous signals were manifest as
irregular variations of reflectance in the no-stimulus condition
but were obscured by averaging signals from multiple trials. To
visualize the spontaneous signal directly, optical signals were
recorded without averaging from one cat. An example of the
spontaneous optical signal recorded under illumination with
540-nm light is shown in Figs. 1 and 2. The change in cortical
light reflectance (⌬R) during a 20-s sampling period was measured by recording 21 consecutive 1-s data frames and dividing
frame 2 through 21 by frame 1. During the sampling period, the
reflectance of 540-nm light increased and decreased relative to
the initial frame in an oscillatory manner at a frequency of 0.1
Hz (Fig. 1). The optical signal thus recorded has two components. The first component is a coherent oscillation of reflectance at all points on the cortical surface (Fig. 1C). A second
component consists of systematic variation of the amplitude of
signals recorded at different sites. The local variations of signal
amplitude can be dissociated from the global variations by
dividing the reflectance change at each site by the mean reflectance change measured over the entire image. Such analysis
(Fig. 1D) reveals that the amplitude of reflectance change at
each site oscillates relative to the image mean at a frequency of
0.1 Hz and that the phase of oscillation shifts with changes
of position across the cortical surface. The local variation of
optical signals can also be visualized by displaying the reflectance change at each measured pixel as an image (individual
frames in Fig. 2; see METHODS for details). In this case, the
global reflectance changes are removed by fitting the histogram
of pixel values of each frame to a common color map, a similar
transformation to division by the image mean. When viewed as
an image, it becomes apparent that in each frame areas of
similar relative reflectance change form distinct patches, several millimeters across. A similar 0.1-Hz oscillation of cortical
light reflectance was also recorded using 690-nm light (not
shown).
Stimulus-evoked optical signals
Stimulus-evoked intrinsic optical signals were clearly evident in only 3/10 cats imaged with 540-nm light. A similar
success rate has been reported for imaging at 540 nm in
chinchilla auditory cortex (Harrison et al. 1998). In two of the
unsuccessful cases, normal multiunit responses were recorded
after the imaging sessions, indicating that our failure to record
optical signals was not a result of a physiologically unresponsive auditory cortex. In successful cases, it was necessary to
average responses to large numbers of stimulus presentations
to obtain acceptable image quality and to negate the spontaneous signals. An example of the optical signal recorded at 540
nm by averaging responses to 50 presentations of a tone pip
train is illustrated in Figs. 3 and 4. Stimulus-evoked optical
signals were measured by recording optical data for 10.5 s,
starting just prior to stimulation, and dividing data frames
collected after stimulus onset by the frame collected before
stimulus onset (Fig. 3C). Within 3 s of stimulus onset, reflectance begins to decrease at nearly all points on the cortical
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SPITZER, CALFORD, CLAREY, PETTIGREW, AND ROE
FIG. 1. Oscillatory spontaneous optical signals recorded with 540-nm light. A: schematic illustrates the location of the imaged
area with respect to the major cortical sulci. AES, anterior ectosylvian sulcus; PES, posterior ectosylvian sulcus; SSS, suprasylvian
sulcus; M, medial; A, anterior. B: macroscopic view of the exposed cortical surface. Scale bar ⫽ 5 mm. C: reflectance change was
measured in a 162 ⫻ 129 pixel region (box in A and B) by recording video data during a 21-s period as a series of 21 data frames
and dividing pixel values in frames 1–20 by the corresponding pixel values in frame 0. Mean reflectance change (⌬R) measured
in 5 ⫻ 5 pixel regions (crosses in B) underwent coherent oscillatory change throughout the 20-s sampling period. D: dividing ⌬R
values measured at each site by the mean ⌬R value of all pixels of each frame (mean ⌬R) revealed incoherent local oscillations
of ⌬R amplitude.
surface (Fig. 3D). Reflectance continues to decrease throughout the duration of the 4.8-s stimulus sequence and then returns
to prestimulation levels following stimulus offset. The magnitude of the stimulus evoked reflectance changes at most sites is
much greater than that of any fluctuations evident in the no
stimulus condition (- - -). The absence of large reflectance
changes in the no-stimulus condition indicates that signal averaging was sufficient to negate the contribution of spontaneous signals. Local variations of the amplitude of stimulusevoked reflectance changes are clearly evident in Fig. 3D.
Division by the image mean reveals a restricted region exhibiting relative decrease of reflectance near the center of presumptive A1 (Fig. 3E). The image representation (Fig. 4A)
shows development of an “activated” area (red and orange),
corresponding to the location of maximum reflectance decrease, and, presumably, maximum blood volume increase,
within 1 s of stimulus onset. The activated area remains relatively stable from 2-s postonset until stimulus offset and then
quickly dissipates. Note, also, the late “activation” of posteromedial and anterolateral regions that showed relative increases
of reflectance during stimulation. In comparison to the stimulated condition, the unstimulated condition shows only minor
and unsystematic fluctuations of reflectance (Fig. 4B).
The position of the activated region revealed by optical
signals at 540 nm is dependent on stimulus frequency. Optical
signals recorded from the same cortex in response to six
different frequency-level combinations are shown in Fig. 5.
Responses to stimuli presented at 65 dB SPL show a clear
progressive shift of the activated region from caudal to rostral
as stimulus frequency is incremented from 5 to 20 kHz, in
agreement with the known tonotopic organization of cat A1
(Reale and Imig 1980). In contrast to the pattern of neuronal
activation, described previously (Heil et al. 1994; Phillips et al.
1994; Schreiner et al. 1992), the position of optical activation
evoked by 15-kHz tones remains constant across a 30-dB range
of stimulus level. The decaying phase of the activation sequence follows a curious course in responses to the 15-kHz,
80-dB and 20-kHz, 65-dB stimuli. In both cases, following
stimulus offset the region of decreased reflectance shifts in a
caudal direction. Similar shifts of the activated region after
stimulus offset or during the later stages of the stimulation
period were observed in all three successful 540-nm imaging
experiments. In this particular case, as a result of the shift, the
images obtained for over 2 s following offset of the 20-kHz
stimulus are very similar to the stimulus-evoked images recorded in response to the 5-kHz stimulus. Thus in this and the
other two cases, a topographic relationship of reflectance
changes was apparent only for the period during stimulus
presentation.
Weak stimulus-evoked intrinsic optical signals were also
evident in 9/10 cats imaged using 690-nm light and ketamine
anesthesia, including those exhibiting stimulus-evoked signals
at 540 nm. The magnitude of evoked reflectance changes at
690 nm was approximately one-tenth that observed at 540 nm.
In contrast to the optical signals recorded at 540 nm, at 690 nm,
reflectance changes were uniformly distributed across the cortical surface, and their topography was uninfluenced by stimulus frequency. Multiunit mapping was performed in four cats
OPTICAL IMAGING IN AUDITORY CORTEX
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FIG. 2. Temporal progression of spontaneous optical signals recorded at 540 nm from the boxed region in Fig. 1. Numbered
images correspond to data frames averaged over successive 1-s sampling periods. Crosses indicate positions sampled in Fig. 1.
Regions showing minimum ⌬R values, corresponding to maximum reflectance decrease and, presumably, maximum increase in
local blood volume, are shown in red, and maximum ⌬R values are shown in black. ⌬R values were mapped, linearly, onto the
indicated color table. ⌬R values less than or greater than the clipped range are shown in red and black, respectively. Scale bar ⫽
2 mm.
exhibiting stimulus evoked signals at 690 nm, and in all cases,
revealed normal multiunit responses with stimulus-dependent
topography. Cross-condition analyses of the evoked optical
signals (e.g., dividing responses to different frequencies and
levels, subtracting responses to a single condition from the sum
of all conditions, dividing across binaural conditions in barbiturate anesthetized animals), such as those performed in studies
of visual cortex (Bonhoeffer and Grinvald 1993; Frostig et al.
1990; Ts’o et al. 1990), did not reveal any stimulus-dependent
topography at 690 nm. Finally, similarly uniform and stimulusfeature-independent topography of intrinsic optical signals was
observed in barbiturate anesthetized cats using light band-pass
filtered at 690 or at 636 nm or long-pass filtered with 650-nm
cutoff.
Comparison of optical and multiunit responses
Multiunit mapping was performed in 2/3 animals that exhibited stimulus-evoked optical signals at 540 nm. Results of
one experiment in which optical signals and multiunit electrophysiological data were recorded from the same cortex are
shown in Fig. 6. The optical images form a tonotopic sequence
with the region of activation shifting progressively from caudal
to rostral as stimulus frequency is incremented from 5 to 20
kHz. Multiunit responses were classified as either clear responses, no response, or near-threshold responses (details in
legend). In each image, there are a number of multiunit recording sites at which the optical and electrophysiological responses are in apparent agreement (e.g., 5 kHz: 1, 6, 9; 10 kHz:
3, 5, 8, 9; 15 kHz: 4, 5, 6; 20 kHz: 1, 3, 4, 5, 6, 8) and a number
at which they clearly disagree (e.g., all stimuli at sites 10 and
11; 10 kHz: 1, 2, 4; 15 kHz: 3; 20 kHz: 7). Multiunit records
and optical signals recorded at each site in response to the 20
kHz stimulus are shown in Fig. 7 to permit detailed comparisons. This case was chosen for illustration because it represents
the best agreement between optical and multiunit responses.
While there appears to be good agreement between optical and
multiunit responses at the majority of sites (e.g., 1– 6, and 8),
there are also sites where the two measures clearly disagree (10
and 11), and others where the relationship is questionable (7
and 9).
Examination of cases where the optical and multiunit re-
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SPITZER, CALFORD, CLAREY, PETTIGREW, AND ROE
FIG. 3. Stimulus-evoked optical signals recorded at 540 nm. A: schematic illustrates location of imaged region. Abbreviations
and conventions same as Fig. 1. B: macroscopic view of the exposed cortex. Scale bar ⫽ 5 mm. C: stimulus consisted of a train
of 7 tone pips (pip duration, 70 ms; rise/fall time, 10 ms; interpip interval, 730 ms) of 10 kHz at 65 dB SPL. Data frames were
summed from 50 trials per stimulus. After summation, frames 1–20 were individually divided by frame 0 to calculate ⌬R. D: ⌬R
decreased at all sites during the period of stimulus presentation (䡲 above time axis) and returned to prestimulus levels thereafter.
Stimulus evoked optical signals (—) were much larger than reflectance changes measured in the unstimulated condition (- - -). E:
division by the image mean revealed systematic local variations of amplitude of stimulus evoked signals.
sponses disagreed revealed several examples of both false
positive (decrease of reflectance relative to image mean, but no
multiunit response; e.g., Fig. 6, site 3 at 15 kHz, sites 1 and 4
at 10 kHz) and false negative (clear multiunit response but no
reflectance decrease relative to image mean; e.g., Figs. 6 and 7,
sites 10 and 11 for all stimuli) optical signals. In experiment
98s11, 55 comparisons of optical and multiunit responses
(responses to 5 stimulus conditions compared at 11 sites)
revealed 22 clear mismatches of which 9 were false positives
and 13 false negatives. Cases where the multiunit response was
classified in the threshold category were not counted in this
analysis. In experiment 98s5, 95 comparisons (5 stimulus conditions, 19 sites) revealed 30 mismatches of which 8 were false
positives and 22 were false negatives. Thus in both experiments in which multiunit data are available, the majority of
errors were false negatives.
It is not obvious from the preceding qualitative comparisons
whether the level of agreement of optical signals and multiunit
responses is higher than that expected by chance. To address
this issue, quantitatively, the magnitude of optical and multiunit responses was compared at each electrophysiological recording site in two cats. A strong association would be expected to result in a significant negative correlation between
these two response measures. Scatter plots relating the magnitudes of optical signals and multiunit responses, recorded at the
same sites, in response to all stimuli that elicited clear, stimulus-evoked optical signals, are shown in Fig. 8 (see legend for
details). To enable comparison of multiunit responses across
recording sites, response magnitude at each site is expressed as
a percentage of the response to the optimal stimulus at that site.
Sites at which an optimal stimulus could not be determined
were excluded from analysis. The level of correlation between
magnitudes of optical signals and multiunit responses was
assessed separately for each stimulus condition and also for all
responses pooled across stimuli within each experiment, by
calculating Spearman’s rank order correlation coefficient (Rs; a
nonparametric measure was used because the multiunit response data were not normally distributed due to a strong
ceiling effect). Correlation values for individual stimulus conditions are shown in Table 1. In only 3 of the 10 cases was a
significant (P ⬍ 0.05) correlation detected between optical and
multiunit response magnitudes. Furthermore, in one of the
three cases showing significant correlation, the direction of
relationship was reversed. Due to the small sample sizes, it
remains possible that a weak association existed in the remaining cases but was not detected. However, analysis of data
pooled across conditions in each experiment (Fig. 8) provided
no evidence of a significant correlation. Thus the present data
provide little evidence of an association between the magnitude
of stimulus-evoked optical and multiunit responses.
Relation of stimulus-evoked and spontaneous optical signal
Finally, an intriguing similarity between spatial patterns of
spontaneous and stimulus-evoked optical signals was observed
OPTICAL IMAGING IN AUDITORY CORTEX
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FIG. 4. Optical images illustrate the relatively focal topography of stimulus-evoked
optical signals recorded at 540 nm. Crosses
indicate locations sampled in Fig. 3. Scale
bar ⫽ 3 mm. A: in the stimulated condition,
a focal region of maximum reflectance decrease develops and is maintained for the
duration of stimulus presentation. ⌬R values
for each image frame were mapped onto the
color table shown such that numerically
smallest values, corresponding to maximum
reflectance decrease, are red and numerically
largest values are black. B: only minor reflectance changes are evident in the unstimulated condition.
in the single case for which both forms of data are available. A
comparison of spontaneous and stimulus-evoked images obtained at 540 nm from the same cortex, is shown in Fig. 9. The
top row of images are single frames (frame 5, 2,000- to
2,500-ms poststimulus onset) taken from sequences of stimulus-evoked activity, which form a tonotopic sequence as shown
in Fig. 6. The images in the middle row are single frames,
arbitrarily selected, from sequences of spontaneous optical
activity recorded from the same cortex. The apparent similarity
of patterns of stimulus-evoked and spontaneous optical signals
was confirmed by subtracting each image in the middle row
from the image above it (results shown on bottom row). The
resulting difference images show little overall variation from
the mean value, with most of the remaining peaks and troughs
corresponding to major blood vessels. The similarity of topography of stimulus-evoked and spontaneous images might appear to suggest that all of the images resulted from spontaneous
activity. This suggestion is, however, untenable because it
1290
SPITZER, CALFORD, CLAREY, PETTIGREW, AND ROE
FIG. 5. Optical images recorded at 540 nm show tonotopic organization of stimulus-evoked reflectance changes. Images were
collected in response to 6 frequency ⫻ sound pressure level combinations (left) and a no-stimulus condition from the same cortex
as in Figs. 3 and 4. The region of peak activation during the stimulation period shifts from posterior to anterior as stimulus
frequency is incremented from 5 to 20 kHz. Schematic, at bottom, illustrates timing of stimulus sequence relative to image frames.
cannot account for synchronization of reflectance changes to
onset of acoustic stimulation, persistence of stimulus-evoked
signals despite averaging images from multiple presentations,
dependence of the topography of evoked images on stimulus
frequency, nor for absence of major reflectance changes in the
no-stimulus condition after extensive averaging. An alternative, albeit speculative explanation is that the neuronal or
vascular functional units that are activated by acoustic stimulation are also spontaneously active in the absence of stimulation.
DISCUSSION
The major findings of the present study are that both spontaneously occurring and stimulus-evoked optical signals were
observed in auditory cortex of anesthetized cats; the spatial
distribution of stimulus-evoked optical signals recorded at 540
nm was consistent with the known tonotopic organization of
A1; and despite the stimulus-dependent topography of optical
signals, the distribution of maximum reflectance changes was
apparently not related to the distribution of extracellularly
recorded neuronal activity.
The mismatch between the spatial distribution of optical
signals and multiunit responses suggests that the optical signal
at 540 nm corresponds to local blood volume changes within
vascular functional units, recruited in response to physiological
activation, whose fine structure is imprecisely matched to that
of the multiunit response. The following sections discuss the
rationale for these conclusions as well as alternative explanations of our results.
Differences in recording depth of optical and multiunit
responses
Due to constraints imposed by light penetration and scattering, intrinsic optical signals are recorded from the superficial
cortical layers (Bonhoeffer and Grinvald 1996). In these experiments, optical signals were recorded at a depth of 500 ␮m
below the cortical surface. Because the superficial cortical
layers contained few electrically responsive units, multiunit
responses were recorded at depths ranging from 320 to 1,200
␮m, with mean recording depths of 821 and 580 ␮m for
experiments 98s5 and 98s11, respectively. The difference in
depths at which optical and multiunit responses were recorded
raises two issues pertinent to interpretation of the present
results and may help to explain the low success rate of the
imaging experiments. First, do neuronal response properties
vary with depth in A1? In agreement with the general concept
of columnar organization, several studies have shown that
response properties, including type of response to contralateral
ear stimulation and frequency tuning, remain consistent
throughout the depth of A1 (Abeles and Goldstein 1970; Imig
OPTICAL IMAGING IN AUDITORY CORTEX
1291
FIG. 6. Comparison of multiunit responses and optical images recorded at 540 nm in 1 animal. Multiunit responses were
recorded at numbered sites and classified qualitatively as either clear responses, threshold responses, or no response. The threshold
category included responses of less than 7 spikes per 20 stimulus presentations and in a few cases where it was difficult to
differentiate a putative response from spontaneous activity. Optical images of responses to tone pips at 65 dB SPL were collected
as shown in Fig. 4, using identical stimulus parameters. Image frames 4 –7 were summed, and results were median filtered to reduce
noise.
and Adrian 1977), including the superficial layers (Reser et al.
2000). A major exception is that, under binaural conditions, the
influence of ipsilateral ear stimulation may vary with cortical
depth (Phillips and Irvine 1979; Reser et al. 2000). Despite the
variation of ipsilateral ear influences, however, Clarey et al.
(1994) found that preferred azimuth remained homogenous
throughout cortical depth in 72% of electrode penetrations.
Thus although it is possible that the response to the contralaterally located speaker, used in the present study, would change
with depth at some recording sites, such effects would be
limited to a minority of sites.
Furthermore it is difficult to evaluate the extent to which
such depth effects might confound the comparison of multiunit
and optical responses because it is unknown whether the optical signals are generated in response to subthreshold neuronal
activity in the superficial cortical layers or suprathreshold
activity in the middle layers. The depth disparity is only
relevant in the latter case. A second issue is whether the
540-nm optical signals could be displaced laterally from their
site of origin due to blood flow with an orientation parallel to
the cortical surface. This would appear unlikely because the
arterioles and venules that supply the cortical parenchyma are
oriented orthogonal to the cortical surface (Edvinsson et al.
1993). Reflecting this anatomical arrangement, numerous studies have demonstrated that local blood flow within the cerebral
cortex follows a course parallel to that of neuronal columns
(e.g., Bryan and Duckrow 1995). Thus optical signals with a
hemodynamic basis should remain aligned with their column
of origin regardless of recording depth. Finally, the paucity of
neuronal responses in the superficial layers of A1, where
optical signals are recorded, is an obvious potential cause of
the low success rate of the imaging experiments. Future attempts at intrinsic signal based imaging of A1 might benefit
from use of anesthetics, such as isofluorane, which are less
disruptive to cortical activity patterns, or an awake preparation.
Spontaneous optical signals
In the present study we observed spontaneous oscillatory
changes of reflectance of both red and green light at frequencies close to 0.1 Hz. Spontaneous optical signals with similar
properties have been reported previously (Mayhew et al. 1996).
Using similar optical recording methods, Mayhew and coworkers observed 0.1-Hz oscillations of reflected dichromatic light
(570 and 660 nm) from the surfaces of diverse brain structures
in anesthetized rats and unanesthetized cats. Furthermore they
demonstrated that the change of intensity of reflected light was
highly correlated with changes of local blood flow measured in
the same tissue by laser-Doppler flowmetry. Thus it is highly
likely that the spontaneous optical signal recorded by Mayhew
et al., and in the present study results from vasomotion, a
0.1-Hz oscillation of local cerebral and somatic blood flow that
has been widely reported (Dirnagl et al. 1989; Fagrell et al.
1980; Golanov et al. 1994; Meyer et al. 1988; Morita-Tsuzuki
et al. 1992).
Spontaneous optical signals are a major source of noise
that must be overcome to record stimulus-evoked signals.
The spontaneous signals measured by Mayhew et al. could
be as large as 1–2% of the total reflected light signal;
whereas, the “mapping signals” used to define functional
architecture by intrinsic signal based optical imaging are
typically an order of magnitude smaller (Frostig et al. 1990;
Grinvald et al. 1988). At least one other optical imaging
study of auditory cortex has reported “spontaneous waves of
cortical activity” with a cycle of 5–10 s that acted as a major
source of interference (Harrison et al. 1998). In the present
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SPITZER, CALFORD, CLAREY, PETTIGREW, AND ROE
FIG. 7. Comparison of optical (540 nm) and multiunit responses to 20 kHz, 65 dB stimulus recorded at numbered sites in Fig.
6. Optical signals recorded in a 5 ⫻ 5 pixel region centered on each multiunit site in the stimulated and unstimulated conditions
are shown as — and - - -, respectively. Multiunit responses are shown as poststimulus time histograms and dot rasters below each
optical signal. Ordinate axes of histograms are scaled relative to the maximum response recorded at each site. Pip duration (
)
is shown on the horizontal axis of each histogram.
study, averaging data from multiple stimulus presentations
(more than 16) proved sufficient to remove major contributions of the spontaneous signals.
Comparison with previous studies of auditory cortex
Results of recent optical imaging studies of auditory
cortex in ketamine-anesthetized chinchillas (Harrison et al.
1998) and barbiturate-anesthetized cats (Dinse et al. 1996)
are similar to those obtained with 540-nm light in the
present study. Harrison et al. (1998) recorded tone-evoked
optical signals at 540 nm with similar time course and
topography to those reported here. Threshold levels for
reliably eliciting optical signals were between 40 and 50 dB
SPL. Both previous imaging studies reported monotonic
growth of activated regions as stimulus SPL was increased
and tonotopic organization of activated regions at suprathreshold SPL.
Results obtained with optical imaging at 540 nm differ in
several respects from the previously described maps of singleunit (Phillips et al. 1994), and multiunit (Heil et al. 1994;
OPTICAL IMAGING IN AUDITORY CORTEX
1293
FIG. 8. Peak amplitude of optical signals recorded at 540
nm is plotted against multiunit response magnitude at each
recording site for all stimuli that evoked clear optical responses
in experiments 98s11 and 98s5. Stimuli are listed in Table 1.
Only stimuli that evoked a clear decrease in reflectance (⌬R) at
multiple recording sites, initiated within the first 3 s after
stimulus onset, were included in this analysis. Spearman’s rank
order correlation coefficient (Rs) are shown atop each plot. In
neither case was the correlation significant (P ⬍ 0.05). Optical
signals were measured by calculating the reflectance change
(⌬R) in a 5 ⫻ 5 pixel window centered at each multiunit
recording site and determining the maximum absolute value
occurring within 3 s of stimulus onset. Multiunit response
magnitude is expressed as percentage of response to the optimum stimulus at each recording site. Stimulus parameters and
optical recording procedures are identical to those in Fig. 4.
Schreiner et al. 1992), responses to tones in A1. First, singleunit thresholds were often lower than 10 dB SPL, and patches
of neighboring sites containing units responding to a given
frequency were evident at 20 dB SPL, at least 20 dB below
threshold for optical signals. Second, as SPL was increased, the
location of patches of active neurons changed such that the
location of neurons responding maximally at the highest SPL
was usually very different from the location of neurons active
near threshold SPL. All maps contained at least some patches
of recording sites where neuronal activity decreased as a function of increasing SPL. By contrast, the area of activated cortex
indicated by optical recording grows monotonically with increasing SPL, remaining centered on the site showing activation at threshold (Dinse et al. 1996; Harrison et al. 1998).
Finally, at high SPL (e.g., at least 60 dB), the distribution of
single-unit activity consisted of multiple, discrete, patches of
active neurons separated by intervening areas of unresponsive
neurons. The largest continuous patches of active neurons were
not more than 3 mm across. Optical imaging, on the other
hand, typically reveals a single, large region of activation
(Dinse et al. 1996; Harrison et al. 1998; present results). In our
hands the activated region could span more than 5 mm (Figs.
4 and 5). Finally, the lack of correspondence between multiunit
responses and optical signals at 540 nm reported here is unsurprising, given the major discrepancies between the previously reported optical and single-unit maps.
It might be argued that the maps of unit activity obtained
using contralateral ear stimulation, are not directly comparable
to the images obtained in the present study, using free-field
stimulation. Certainly, the single-unit maps obtained with different procedures are likely to differ, primarily as a result of
differences in the contribution of ipsilateral ear stimulation.
However, the effects of SPL on the distribution of active
1. Correlations of ⌬R and multiunit response magnitude
for individual stimuli
TABLE
Experiment
n
98s11
11
98s5
19
Stimulus
5
10
10
15
20
5
10
10
10
15
kHz,
kHz,
kHz,
kHz,
kHz,
kHz,
kHz,
kHz,
kHz,
kHz,
65
50
65
65
65
65
50
65
80
65
dB
dB
dB
dB
dB
dB
dB
dB
dB
dB
Rs
Significance
0.03
⫺0.43
⫺0.29
⫺0.13
⫺0.63
0.58
⫺0.35
⫺0.32
⫺0.52
0.19
NS
NS
NS
NS
P ⬍ 0.05
P ⬍ 0.01
NS
NS
P ⬍ 0.05
NS
neurons primarily reflect the patchy organization of neurons
with different forms of sensitivity to SPL (Clarey et al. 1994;
Heil et al. 1994; Phillips et al. 1994; Sutter and Schreiner
1995), as opposed to binaural interaction, and are therefore
unlikely to be dramatically altered by the difference in stimulation procedures.
Two studies, thus far, have reported tone-evoked optical
signals at wavelengths greater than 600 nm in auditory cortex.
Hess and Sheich (1996) recorded at 610 nm in auditory cortex
of unanesthetized gerbils, and Bakin et al. (1994) recorded at
630 nm in barbiturate-anesthetized rats and guinea pigs. In
agreement with the present findings, in both studies optical
imaging indicated activation of very large, continuous regions
of A1. The contiguous and broad distribution of activated
regions revealed by optical imaging at 630 nm in rats (Bakin et
al. 1996) differs from the patchy distribution of single-unit
activity reported by Phillips et al. (1994) in cats. Subsequent
multiunit mapping, however, revealed much better agreement
between optical and neuronal responses in rats than was evident in the present study. The mapping data presented by Bakin
et al. (1994) permit 214 comparisons of optical and multiunit
responses (2 stimulus conditions at 107 sites) of which only 33
showed clear disagreement between the two measures. Thus
the difference between imaging results in rats and single-unit
mapping results in cats may indicate a fundamental difference
in the topographic representation of suprathreshold tones in
auditory cortex of the two species. In the gerbil, the location of
the activated region revealed by optical imaging shifted at later
stages of the stimulation period and continued to shift after
cessation of stimulation (Hess and Scheich 1996). Similar
shifts were observed in all three cats successfully imaged at
540 nm in the present study. Hess and Sheich suggested that
shift of the activated area is indicative of a corresponding shift
of subthreshold electrophysiological activity. However, in the
absence of corroborating electrophysiological data, and in light
of the lack of correspondence between optical signals and
neuronal responses demonstrated here, it is equally likely that
the phenomenon reflects the spatiotemporal properties of the
hemodynamic response rather than those of the neuronal response.
Comparison with previous studies of visual and
somatosensory cortex
The findings of the present study differ from those of intrinsic signal-based optical imaging studies of visual and somatosensory cortices in two regards. First, in the present study
1294
SPITZER, CALFORD, CLAREY, PETTIGREW, AND ROE
FIG. 9. Similarity of stimulus-evoked and spontaneous optical images recorded at 540 nm. Top: optical images in response to
stimuli of 5 kHz (A), 10 kHz (B), and 20 kHz (C) at 65 dB SPL. Data are the same as in Fig. 6. Middle: individual 1-s frames
selected from 3 20-s epochs of spontaneous activity recorded as in Fig. 1. Bottom: results of subtracting images in the middle row
from images in the top row (G ⫽ A–D; H ⫽ B–E; I ⫽ C–F).
optical signals with stimulus-dependent topography were recorded at 540 nm but not at longer wavelengths. By contrast,
in visual cortex, similar functional maps of ocular dominance
and orientation preference can be obtained at wavelengths
ranging from 480 to 940 nm (Frostig et al. 1990). In rodent
somatosensory cortex, stimulation of a single facial vibrissa
also evokes optical images with similar spatial location and
extent at 550, 610, and 850 nm (Narayan et al. 1994). The
wavelength dependence of optical signals in cat auditory cortex
suggests that stimulus-evoked changes in local blood volume,
oxygen saturation of hemoglobin, and light scattering, which
provide the major sources of optical signals recorded at 540,
630, and 690 nm, respectively (Frostig et al. 1990; Malonek
and Grinvald 1996; Malonek et al. 1997), are not as well
coupled in this cortex as they are other sensory cortices and,
presumably, in auditory cortex in other species (Bakin et al.
1996; Harrison et al. 1998; Hess and Scheich 1996). The
reason for this apparent difference is not readily apparent. A
second difference is that, in the present study, the topographies
of optical signals and neuronal spiking responses evoked by the
same stimulus were unrelated. By contrast, several studies have
demonstrated a tight correspondence between the spatial distribution of optical and spiking responses in visual cortex
(Crair et al. 1997; Ghose and Ts’o 1997; Grinvald et al. 1986;
Roe and Ts’o 1995; Shmuel and Grinvald 1996; Shoham et al.
1997) and rodent somatosensory cortex (Masino et al. 1993;
Peterson et al. 1998). In the following text, we consider three
possible explanations for the latter difference.
Visualization of subthreshold and interneuron activity
Two studies of visual cortex, using spatially restricted stimuli, provide evidence that intrinsic optical signals reflect both
sub- and suprathreshold neuronal activity. In contrast to previous imaging studies that used full-field visual stimulation,
these studies demonstrated that partial field stimulation evokes
optical signals distributed over a much larger cortical area than
the corresponding neuronal spiking responses. Using stimuli
OPTICAL IMAGING IN AUDITORY CORTEX
designed to simulate the receptive field size of a single cortical
neuron, Das and Gilbert (1995) reported that the areal extent of
evoked optical signals was approximately 20 times greater than
that of evoked spiking activity. In a second study, using partial
field stimulation, single-unit data provided evidence of subthreshold physiological activity within regions containing
evoked optical signals but no spiking neurons (Toth et al.
1996). Thus in visual cortex, stimuli that elicit spatially restricted patterns of spiking activity, as do tones in auditory
cortex, reveal large discrepancies between the spatial distribution of optical and unit responses, most likely due to visualization of subthreshold physiological activity. It is therefore
possible that visualization of subthreshold activity could be a
primary cause of the mismatch between patterns of optical
activation and spiking activity observed in the present study.
Another potential source of the mismatch between optical
and unit activity is the difficulty of recording spiking activity
from inhibitory interneurons with extracellular electrodes.
Mountcastle et al. (1969) reported that the majority of extracellular recordings obtained with metal electrodes in somatosensory cortex exhibited a type of waveform referred to as
“regular spikes.” Only occasionally were recordings obtained
from neurons with “thin spikes,” characterized by a comparatively shorter initial negative phase, smaller amplitude, and
spatially restricted electrical field. A slightly higher proportion
of “thin,” or “fast spiking,” neurons have been recorded in
studies using glass micropipette electrodes (e.g., Simons 1978).
More recently, intracellular experiments have confirmed
Mountcastle’s proposal that regular spiking neurons have pyramidal morphology and thin spiking neurons have aspiny
stellate morphology, typical of GABAergic inhibitory interneurons (McCormick et al. 1985). These findings provide
strong circumstantial evidence that metal extracellular electrodes record preferentially from pyramidal neurons. The temporal properties of stimulus-evoked spike bursts recorded extracellularly in auditory cortex are consistent with this view
(Bowman et al. 1995; Phillips et al. 1996). Consequently a
mismatch between multiunit and optical responses could potentially arise in areas where spiking activity of interneurons
generates a strong optical signal, while simultaneously inhibiting nearby pyramidal neurons.
There is certainly considerable evidence that stimulation
with tones at high SPL elicits subthreshold electrophysiological activity throughout a substantial proportion of auditory
cortex, including a major component due to inhibitory processes and, presumably, spiking activity in inhibitory interneurons. First, because many A1 neurons have frequency-domain
inhibitory side bands (Calford and Semple 1995; Calford et al.
1993; Phillips 1988; Phillips and Cynader 1985; Schreiner and
Mendelson 1990; Shamma and Symmes 1985; Shamma et al.
1993), a tonal stimulus of a given frequency will induce
widespread inhibition of neurons with higher and lower best
frequencies. Second, many A1 neurons exhibit level-dependent
suppression (Phillips and Irvine 1981), referred to as “nonmonotonicity,” a substantial proportion of which is likely generated by intracortical inhibitory mechanisms (Barone et al.
1996; Prieto et al. 1994). Because nonmonotonic neurons are
distributed in patches (Clarey et al. 1994; Phillips et al. 1994),
the spatial pattern of cortical activity induced by tones at high
SPL should be expected to include patches of spiking inhibitory interneurons, together with inhibited pyramdial neurons.
1295
Consistent with this contention, a recent voltage-sensitive dyebased imaging study of guinea pig auditory cortex demonstrated that tonal stimulation produces regions of activation,
flanked by regions of inhibition, and that the area of excitatory
activation could be dramatically expanded by local application
of GABA antagonists (Horikawa et al. 1996). Finally, although
binaural inhibitory mechanisms would not be expected to have
a major influence on the distribution of unit responses to
contralaterally presented tonal stimuli, such stimuli might induce subthreshold activation of “predominantly binaural” cortical neurons (Kitzes et al. 1980).
In addition to the difference between optical and multiunit
responses within A1, failure to distinguish between supra- and
subthreshold activity might also account for the difference in
the degree of correspondence of optical and unit responses
between A1 and visual cortex. In visual cortex, columns of
neurons with similar orientation preference are interconnected
by a lattice-like array of axonal projections (Gilbert and Wiesel
1983, 1989; Rockland and Lund 1983). As a result, stimulation
of a single orientation column gives rise to subthreshold excitatory and inhibitory synaptic inputs preferentially directed to
surrounding columns with similar orientation preference (Grinvald et al. 1994; Weliky et al. 1995). Consequently, the spatial
pattern of subthreshold electrophysiological activation induced
by partial visual field stimulation corresponds very closely to
the pattern of suprathreshold activation induced by full-field
stimulation. Thus for full-field stimulation, the failure to distinguish between sub- and suprathreshold activation has little
effect on the correspondence of optical and unit responses. In
auditory cortex, by contrast, it is likely that the patches of
activated and actively inhibited pyramidal neurons are spatially
separated. Thus visualization of subthreshold physiological
activity could have a far greater effect on results in auditory
cortex than in visual cortex.
The hypothesis that the discrepancy between optical and unit
responses in cat auditory cortex results entirely from visualization of subthreshold activity, and/or inability to record spiking activity of interneurons, is inconsistent, however, with the
fact that the majority of mismatches that we observed were
false-negative errors. In either case, one expects the majority of
errors to be false positives. Although our data do not allow us
to rule out a contribution of visualized subthreshold activity or
interneuronal spiking activity, it is unlikely that either is the
major cause of discrepancies between optical and multiunit
responses observed here.
Timing of auditory cortical neuronal responses
The characteristic temporal response properties of neurons
in auditory cortex of anesthetized cats might account for the
difference in results of optical imaging in auditory and other
cortical areas. Most neurons in A1 respond to best-frequency
tonal stimulation with one or two spikes synchronized to stimulus onset, followed by suppression of spiking activity for the
duration of the stimulus (Fig. 7). In addition, because repeated
stimulation at short interstimulus intervals results in decreased
responsiveness, it is necessary to use a stimulation duty cycle
with a low ratio (⬃1:10) of stimulus-on time to stimulus-off
time to obtain maximum responsiveness to individual stimuli
(Hocherman and Gilat 1981; Phillips et al. 1989). As a consequence, using optimal stimulus parameters, suprathreshold
1296
SPITZER, CALFORD, CLAREY, PETTIGREW, AND ROE
neuronal responses are only elicited during a very small fraction of the duration of a repetitive tone-pip sequence. By
contrast, sustained neuronal responses lasting several seconds
are elicited by optimal stimuli in visual cortex of barbiturate
anesthetized animals (Hubel and Wiesel 1959). Because of this
difference in response properties, discharge rates of optimally
stimulated neurons in visual cortex, recorded throughout a 5-s
stimulus presentation, may exceed those of auditory cortical
neurons by more than a factor of 15 (Roe and Ts’o 1995;
Sengpiel and Blakemore 1994). In barrel cortex, periodic
vibrissal stimulation elicits sustained spike discharges, with
two spike bursts per stimulus period (Peterson et al. 1998). The
4- to 5-Hz stimulation frequencies, typically used in optical
imaging studies, would thus elicit discharge rates several times
those typically observed in auditory cortex.
The gross differences in amount of suprathreshold neuronal
responses throughout the period of stimulation in different
cortical areas may be reflected in the corresponding optical
signals. Specifically, the paucity of neuronal spiking responses
may be insufficient to generate a reliable and robust optical
signal at 540 nm in auditory cortex. This explanation is consistent with the unreliability of the optical signal, which was
only detectable in 3/10 cats tested, and then only after extensive averaging. This hypothesis may, at first, appear inconsistent with the fact that optical imaging has been shown to reveal
both suprathreshold and subthreshold activity (Das and Gilbert
1995; Toth et al. 1996), as the paucity of spike discharges in
A1 is at least partly due to an abundance of stimulus-evoked
inhibitory processes some of which may last beyond the stimulus duration (Volkov and Galazjuk 1991, 1992). It should be
noted, however, that optical signals accompanying suprathreshold activity are larger than those accompanying subthreshold activity and can be distinguished on this basis using appropriate analysis (Toth et al. 1996). Furthermore it is not clear
how inhibitory activity is reflected by intrinsic optical signals.
Thus it remains entirely plausible that the failure of optical
signals recorded at 540 nm to reveal physiologically relevant
functional topographies in cat auditory cortex is due in large
part to the sparseness of neuronal spiking responses. If this is
the case, one potential approach to improving the quality of
optical signals recorded from auditory cortex would be the use
of an awake, behaving preparation. Previous studies have indicated that tones evoke a wider range of response types in A1
of unanesthetized animals, including a greater prevalence of
sustained responses (Abeles and Goldstein 1972; Brugge and
Merzenich 1973; Pfingst et al. 1977). One previous optical
imaging study of auditory cortex used an awake preparation
(Hess and Scheich 1996), but in the absence of corroborating
physiological data, there is no reason to suppose that the results
were any different to those of the present study.
Vascular organization
Finally, we consider the possibility that the success of optical imaging in visual and barrel cortex depends on specializations of the vascular supply that may be absent in cat auditory
cortex. The primary and secondary visual cortices of primates
are distinguished by a finely structured modular organization
that is demarcated by the pattern of cytochrome oxidase staining (Horton and Hubel 1981; Livingstone and Hubel 1984a;
Murphy et al. 1995; Wong-Riley 1979). Neurons within the
different cytochrome oxidase defined modules have different
response properties (Hubel and Livingstone 1987; Livingstone
and Hubel 1984a; Silverman et al. 1989; Ts’o and Gilbert
1988). Furthermore the modularity of functional organization
is reflected in the distribution of metabolic activity (Humphrey
and Hendrikson 1983; Tootell et al. 1983) as well as the
patterns of intrinsic and interareal cortico-cortical connections
(Hubel and Livingstone 1987; Levitt et al. 1994; Livingstone
and Hubel 1984b, 1987; Rockland and Lund 1983; Yoshioka et
al. 1996), and in the distribution of a number of neurochemical
markers including CAT-301 (Hendry et al. 1984) and parvalbumin (Blumcke et al. 1990). At least in macaque monkeys,
the modular neuronal organization within visual cortex is also
reflected by the distribution of small diameter blood vessels
(Zheng et al. 1991). The density of capillaries and radial
penetrating vessels is greater in cytochrome oxidase-rich blobs
and stripes than in the intervening cortical tissue. Similarly, in
barrel cortex each histologically defined barrel is delimited by
a dense capillary plexus within the barrel core (Patel 1983).
There is not, however, a one-to-one relationship between individual barrels and vascular supply, as individual penetrating
arterioles give rise to capillaries in several adjacent barrels
(Woolsey et al. 1996). Nevertheless, in both visual and barrel
cortex, there is evidence that the microvasculature is organized
into functional units that bear a close spatial relationship to the
anatomically and physiologically defined neuronal functional
modules.
Because optical imaging relies primarily on blood-borne
signals, it is possible that the organization of vascular elements
sets constraints on the spatial pattern of activation that can be
visualized with this technique. Consistent with this view, the
areal extent of activation in barrel cortex produced by nearthreshold deflection of a single vibrissa (Peterson et al. 1998)
corresponds very well with the areal extent of the minimal
vascular functional unit, consisting of the capillaries supplied
by a single penetrating arteriole (Woolsey et al. 1996). If an
equivalent complementarity of neuronal and vascular functional units does not exist in auditory cortex, the local blood
volume changes, presumably the major source of optical signals recorded at 540 nm, might be spatially decoupled from the
pattern of electrophysiological activity. It is difficult to further
evaluate this conjecture at present, however, because it is not
known whether A1 exhibits modular neuronal organization,
comparable to that in visual cortex, and because the microscopic organization of blood supply to A1 has not been described.
We thank S. Kaiser, M. Ward, and the staff of Optical Imaging, without
whose technical expertise these experiments would not have been possible. We
also thank D. Vaney for contributing the vibration isolation table, D. Ts’O for
use of the SumAnal program, and K. Keller for help with image analysis.
This work was supported by National Health and Medical Research Council
of Australia Project Grants 971147 and 96/NHMRC9002G to M. W. Spitzer
and J. D. Pettigrew, respectively, and by NHMRC Project Fellowship Grant
961226 to M. B. Calford.
Present addresses: M. B. Calford, Faculty of Medicine and Health Sciences,
The University of Newcastle, Callaghan, NSW 2308, Australia; J. C. Clarey,
Dept. of Otolaryngology, The University of Melbourne, Melbourne, VIC 3010,
Australia; A. W. Roe, Dept. of Neurobiology, Yale University School of
Medicine, New Haven, CT 06520.
OPTICAL IMAGING IN AUDITORY CORTEX
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