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The Journal of Neuroscience, 1999, 19:RC3:1-7
RAPID COMMUNICATION
Modal Behavior of Cortical Neural Networks during Visual
Processing
David M.
Senseman1 and
Kay A.
Robbins2
Cajal Neuroscience Research Center, Divisions of 1 Life
Sciences and 2 Computer Science, The University of Texas
at San Antonio, San Antonio, Texas 78249
 |
ABSTRACT |
The network behavior of cortical cells during the processing of a
light flash was characterized in an isolated, but functionally intact,
turtle visual system. Rapid changes in intracellular membrane potential
were monitored optically using a voltage-sensitive dye (VSD). Spatially
coherent changes in membrane potential were determined by subjecting
high-speed movies of the VSD signals to Karhunen-Loéve decomposition. In all experimental trials analyzed
(n > 50), coherent activity was restricted to a
small number of similar spatial patterns or modes. At least four modes
(M1,1, M1,2,
M2,1, and M2,2) have an
organizational structure similar to the normal modes of a vibrating
membrane (drum). This empirical observation of modal activity provides
a useful framework for analyzing the macroscopic behavior of cortical networks.
Key words:
cerebral cortex; visual cortex; pyramidal cell; neural
network; voltage-sensitive dye; turtle
 |
INTRODUCTION |
Relatively little is known about the
basic principles governing the global behavior of cortical neural
networks during the processing of sensory information. Much of our
current insight has come from analyses of neurocomputational models
(Suarez et al., 1995
; Xing and Gerstein, 1996
; Ulinski, 1998
). This
report describes the results of an empirical analysis of global
activity evoked in the turtle cerebral cortex by brief light flashes.
The turtle was selected for study because an usually complete and detailed record of global membrane potential changes can be obtained in
this experimental preparation using high-speed optical imaging of
voltage-sensitive dye (VSD) signals (Senseman, 1996
, 1999
; Prechtl et
al., 1997
). Senseman (1996)
has also shown that the waveforms of
cortical VSD signals correspond closely to the complex waveforms of
compound postsynaptic potentials recorded currently in cortical
pyramidal cells with conventional intracellular microelectrodes.
 |
MATERIALS AND METHODS |
Experimental preparation and optical imaging.
Experiments were performed on adult (shell length, 10-21 cm) pond
turtles (Pseudemys scripta elegans) obtained from a
commercial supplier (William A. Lemberger, Oshkosh, WI). Surgical
procedures used to isolate the eyes and brain from the cranium as well
as the methods used to image the VSD signals with a 464-element silicon
photodiode array have been described previously (Wu and Cohen, 1993
;
Senseman, 1996
, 1999
). The isolated visual system is intact in the
sense that the normal afferent connections among the retina, lateral geniculate complex, and visual cortex are preserved (Kriegstein, 1987
).
Each of the 464 elements in the silicon photodiode array monitored a
150 × 150 × 700 µm volume of cortical tissue. All experimental protocols were approved by the university Institutional Animal Care and Use Committee and were performed within its established guidelines.
Visual stimulation. Brief light flashes
(~20 µsec duration) were presented to the contralateral eyecup
using a Grass Instruments (Quincy, MA) PS22D photostimulator coupled to
a flexible light guide. For diffuse illumination, the tip of a
relatively large-caliber (2.5-mm-diameter) metal-clad light guide was
positioned 1-2 cm from the eyecup to evenly illuminate the entire
retinal surface. Spot illumination was achieved by bringing a
smaller-bore (800-µm-diameter) metal clad fiber optic light guide to
within 0.5-1 mm of the retinal surface. At this distance, the spot
subtended ~15° of visual angle on the retinal surface, which is
relatively small given an acceptance angle of 165-192° for the
turtle eye (Northmore and Granda, 1991
).
Data analysis. For data analysis each detector in the
464-element photodiode array was treated as a pixel (picture element) in a 24 × 24 pixel video camera. An experimental trial thus
consisted of a series of 24 × 24 pixel images (frames) forming a
continuous movie. All movies were composed of 576 frames and were
recorded at an effective frame rate of 353 frames per second.
Individual movie frames were converted to vectors, and
Karhunen-Loéve (KL) decomposition was performed on this
collection of vectorized images to find a new coordinate basis using
the eigenvectors of the autocorrelation matrix (Sirovich, 1987
;
Sirovich et al., 1996
; Robbins, 1998
). KL decomposition, principal
component analysis, and singular value decomposition are related
statistical procedures that have long been used for the analysis of
signal waveforms of biological origin (Glaser and Ruchkin, 1976
;
Sirovich and Everson, 1992
). Each eigenvector or mode is a 24 × 24 pixel image showing the locations of coherent changes in membrane
potential within the cortical tissue. The relative importance of each
of these spatial patterns to the overall cortical response is given by
the corresponding eigenvalues of the autocorrelation matrix (Robbins
and Senseman, 1998
). KL decomposition is similar to Fourier analysis
insofar as both procedures can be thought of as a rotation of a
coordinate system. Although Fourier analysis rotates the coordinate
system onto a predetermined basis consisting of sine and cosine
functions, KL decomposition rotates the coordinate system onto a basis
that minimizes the total mean square error.
 |
RESULTS |
Modal character of coherent activity
When cortical VSD signals were viewed as unprocessed movies,
visually evoked responses usually appeared different in different experimental preparations. Even in the same preparation, cortical responses evoked by the same visual stimulus in sequential trials often
exhibited differences in their spatiotemporal characteristics (Senseman, 1996
, 1999
). Despite this variability, KL decomposition revealed that the cortical responses could be decomposed into a small
number (<10) of similar spatial patterns or modes. Figure 1 shows four spatial patterns
(M1,1, M1,2,
M2,1, and M2,2) calculated from
single trials in two different experimental preparations. We have
adopted a naming convention for the modes based on their spatial
organization. The first subscript indicates the number of maxima and
minima that are aligned with the minor axis of the dominant mode. The
second subscript indicates the number of maxima and minima that are
aligned with the major axis of the dominant mode.

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Figure 1.
Intrinsic modes with the same structure are
observed in different experimental preparations. Cortical response was
evoked in both preparations by diffuse light flashes. A,
The image at left shows a photograph of the experimental
preparation in which the right cerebral cortex has been unfolded for
optical recording. The image of mode M1,1 has
been superimposed on the photograph to indicate the area imaged by the
photodiode array. The dark circular object at the
top left of the preparation is the attached eye. The
anterior chamber has been removed to form an eyecup. The four
photomicrographs at the top right show the locations of
the most prominent cortical modes on the unfolded cortical sheet. For
clarity the modes are also shown below each photomicrograph.
B, Similar to A but showing the results
obtained from the left cerebral cortex in a different experimental
preparation. In both Figures 1 and 4, the modes are displayed as
contour maps that were generated by Mathematica 3.0 (Wolfram Research
Inc.) using standard bilinear interpolation. The meaning of the
color bar is as follows. Cortical areas that were less
than ± 10% of the maximum coherence were not colored and appear
white or clear. Each color increment to
the right of the central white box on the
color scale indicates a 10% increase or decrease in the magnitude of
coherent activity.
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The spatial pattern labeled M1,1 was always the most
significant, capturing 70-90% of the total response energy. M1,1 has an ovoid shape, with its major axis aligned tangentially at a 15-30° angle to the rostral
caudal axis.
M1,1 is the only spatial pattern in which the
coherent activity is unimodal, signifying that the changes in
intracellular membrane potential captured by this mode always occur in
the same direction irrespective of whether the network was depolarizing
or repolarizing.
Three additional patterns of spatially coherent activity
(M1,2, M2,1, and
M2,2) are also shown in Figure 1. Because these
modes collectively captured only 10-25% of the response energy, their
contributions were largely obscured by M1,1.
M1,2 and M2,1 have antisymmetric bimodal distributions. The maximum and minimum of
M1,2 are approximately circular, whereas the maximum
and minimum of M2,1 are more elongated. The line
separating the maximum and minimum of M2,1 is
approximately parallel to the major axis of M1,1 and
nearly perpendicular to the line separating the maximum and minimum of
M1,2. The bimodal distributions of both
M1,2 and M2,1 indicate that
changes in cell membrane potential are inversely correlated across their respective axes. M2,2 is the most
distinctive mode by virtue of its four-way antisymmetry having two
maxima and two minima arranged opposite each other.
Relationship of the modes to the original data
Figure 2 illustrates the
relationship between the KL modes and the original data. The three
largest modes (M1,1, M1,2, and
M2,1) computed for a response evoked by a diffuse
light flash are shown in Figure 2A, whereas the
projections of the original data set onto these three modes are
displayed as time series in Figure 2B. We use the
term "projection" to refer to a time series. The amplitude of each
projection gives the relative contribution of the corresponding mode to
the overall response at any given point in time. To illustrate the
fidelity with which these three modes recreated the original response,
selected frames from two movies are shown in Figure 2C. The
images in the row labeled Orig were generated from the
original VSD signals, whereas the images in the row labeled
Eigen were reconstructed using only the three images in
Figure 2A and the three projections in Figure 2B (Robbins and Senseman, 1998
). Movies of the
data and reconstructions can be found at
http://vip.cs.utsa.edu/cortex/JNS/index.html.

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Figure 2.
Correspondence between the first three KL modes
and the original data. A, Modes
M1,1, M1,2, and
M2,1 for a response evoked by a diffuse white
light flash for trial 3404 as in Figure 1B.
B, Time series display of the projections of the
original data set onto M1,1,
M1,2, and M2,1. The time
of stimulus onset is indicted by the small dot.
C, Four frames from a movie generated directly from the
VSD signals (Orig) compared with four images computed
using only the first three modes (Eigen) in
A and their projections shown in B at
times 181 msec (a), 343 msec
(b), 615 msec (c), and 748 msec (d) after stimulation.
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As reported previously (Senseman, 1999
), diffuse retinal stimulation
initially depolarizes cortical cells in the rostral pole of the visual
cortex and then spreads into the caudal pole, giving the visual
impression of a wave of excitation moving over the cortical surface.
The spread of excitation is not captured by any single mode but,
rather, is described by the temporal interactions between all three
modes. The initial depolarization observed in the rostral pole at 181 msec after stimulation (Fig. 2B, a) is largely attributable to contributions from M1,1 and
M1,2 with relatively little contribution from
M2,1. At 748 msec after stimulation (Fig.
2B, d), M1,2 is almost
solely responsible for the response, whereas the contributions from
M1,1 and M2,1 are negligible.
Between 181 msec (Fig. 2B, a) and 343 msec
after stimulation (Fig. 2B, b), when the
initial wave of depolarization is spreading caudally, all three modes make significant, time-varying contributions.
It is important to remember that the modes represent patterns of
correlated activity rather than membrane depolarization or hyperpolarization. Consequently, the projections presented in Figure
2B should not be viewed as time records of membrane
potential. Rather, each projection simply shows the time-varying
weighting of its corresponding modal pattern in the overall response.
For example, when the projection for bimodal mode,
M1,2, changes from positive to negative, the red
maximum in the top right corner goes from enhancing to suppressing the
response, whereas the blue minimum in the bottom left corner goes from
depressing the response to enhancing it. It should also be noted that
each individual VSD signal reflects a local change in
membrane potential involving a few hundred cortical cells. Each
projection, on the other hand, reflects a global change in
membrane potential taking place coherently in tens of thousands of
cortical cells within the much larger cortical area encompassed by the mode.
This ability of the KL modes and their projections to capture global
relationships can be used to isolate and compare different aspects of
an evoked cortical response. For example, in the response illustrated
in Figure 2, several VSD signals exhibited oscillations (Fig.
3A). Visually evoked
oscillatory activity has been observed in the cortices of both mammals
(Singer and Gray, 1995
; Castelo-Branco et al., 1998
) and turtles
(Prechtl et al., 1997
). To analyze the complex patterns observed in
response to looming stimuli, Prechtl et al. (1997)
used taper filters
to separate the response into frequency sub-bands. They then searched
for spatial correlations within the different sub-bands.

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Figure 3.
Power spectrum analysis of the projection of trial
3404 of Figure 2 onto mode M1,1 reveals
characteristic frequencies at 11 and 19 Hz. A, VSD
signals showing oscillatory changes in membrane potential in response
to a diffuse white light flash. B, The recording
locations of the photodiode array are shown superimposed on a
photomicrograph of the preparation. The horizontal box
indicates the recording locations of the VSD signal presented in
A. C, Projection of the experimental trial onto mode
M1,1. Vertical dotted lines show
the time period used for the power spectrum analysis. D,
The power spectrum of the waveform in C shows prominent
peaks at 11 and 19 Hz. The asterisk indicates line noise
contamination at 60 Hz. A 70 msec median filter was applied to the
waveform in C before the power spectrum calculation. The
small dots below the waveforms in A and
C show the onset of the diffuse light flash to the
contralateral eyecup.
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An alternative approach is to separate out the spatial correlations
first and then perform a Fourier analysis on the resulting projections.
Figure 3C shows the projection of mode
M1,1 onto all 464 VSD signals recorded in this trial
(including the eight signals shown in Fig. 3A). Fourier
analysis performed on the portion of the projection between the
dotted lines gave the spectrum shown in Figure
3D. The two sharp peaks indicate that mode
M1,1 has two characteristic frequencies, 11 and 19 Hz. Prechtl et al. (1997)
observed high-frequency activity with
spectral peaks near 10 and 20 Hz in response to looming stimulus. However, the frequency distribution of the correlation they reported was obtained by computing correlations within frequency sub-bands and
cannot be directly compared with Figure 3D.
Constancy of the spatial organization
The spatial organization of modes was preserved when the
parameters of the light flash were varied, as shown in Figure
4. Diffuse flashes of red and blue light
evoked patterns of coherent activity similar to those evoked by white
light (Fig. 4, top). Perhaps more surprisingly, the spatial
organization of the modes is maintained when visual stimulation was
switched from diffuse light flashes to small light spots projected onto
different retinal locations (Fig. 4, middle).

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Figure 4.
Comparison of modal organization across
trials. All of the modes presented in this figure were obtained in the
experimental preparation shown in Figure 1B. Each
row shows the modes calculated from a data set
corresponding to a different stimulus condition. The
curves in the middle column represent the
projections of the corresponding data sets onto the coordinate system
formed by the modes from the diffuse white light trial shown in the
top row. Plotted in this way, each cortical movie
appears as a curve in three-dimensional space. For one trial, the start
(S), finish (F), and
direction of travel (arrow) of the response trajectory
have been indicated. The bar charts in the right
column represent the fraction of energy captured by projecting
a single experimental trial onto modes M1,1,
M1,2, and M2,1. The
orange bar shows the projections on the KL modes
computed from the trial's own data.The green bar shows the trial's projection
onto the modes computed from the diffuse white light flash. In each
case the lightest section represents the energy captured
by the projection on mode M1,1, the
medium shade represents the energy captured by the
projection on mode M1,2, and the darkest
shade represents the energy captured by the projection on mode
M2,1. The top section compares
results for responses obtained with diffuse light flashes composed of
different spectral energies (colors). Each series of
modes was calculated from a single experimental trial. The top
row shows modes from trial 3404 as in the previous figures. The
unfiltered output of a xenon lamp is labeled White.
Red and Blue illumination were produced
by passing the output of the xenon strobe through a bandpass
interference filter (±25 nm full width at half-maximum) centered at
650 or 400 nm, respectively. The middle section compares
responses obtained with spot illumination at three retinal locations.
To compensate for the lower signal-to-noise ratios of the VSD signals
evoked by spot illumination, the modes were computed from two
experimental trials combined into a single data set. However, the time
course of the projections shown in the signature curves
and the energy distribution of the projections shown by the bar
charts are presented for the individual trials that were used
to analyze the spot illumination. The bottom section
compares the spatial organization of M1,1,
M1,2, M2,1, and
M2,2 for trial 3404 with the normal modes of a
rectangular membrane (Drum).
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Although these changes in stimulus quality had little effect on the
overall spatial organization of the cortical modes, we found that
changing the stimulus parameters systematically altered the relative
contributions of each of the modes made during the course of the
response. These changes can be distinguished most easily by plotting
the three projections against one another in a common coordinate system
(basis), as shown in Figure 4, middle column, yellow curves.
For this comparison, we used the modes generated by a diffuse white
light flash as the common coordinate system, because this trial had VSD
signals with the highest signal-to-noise ratios. Each point on a curve
represents the three values of the projections on
M1,1, M1,2, and
M2,1 for a particular frame. As a movie plays, the
points corresponding to frame projections of the corresponding data set
form a curve or response trajectory. By inspection, it can be seen that
the projection curves have different shapes depending on the stimulus parameters. These shapes appear to be a stimulus signature
and potentially provide a method of classification of responses. The response trajectories for diffuse light stimulation show an open loop
shape independent of the spectral energy of the light flash. In
contrast, the shapes of the trajectories for responses evoked by spot
stimuli have a clearly different character that depends on the location
of the retinal stimulation.
The curves in Figure 4 were computed by projecting all of
the trials onto the modes obtained from the diffuse white light flash
trial. Projecting onto a common coordinate system is only meaningful if
the common basis captures sufficient energy across all the data sets
being compared. The stacked bar charts in Figure 4,
right, provide a quantitative assessment of the total
response energy distribution. The orange column in each pair
shows the fraction of energy captured by the three modes computed from
each trial, whereas the green column in each pair shows the
fraction of energy captured by the three modes computed from the
diffuse white light trial.
In all experimental trials, M1,1,
M1,2, and M2,1 captured at least
96% of the response energy when the trial was projected onto its own
basis (Fig. 4, orange columns). As expected, less of the
response was captured by projections onto the common basis (Fig. 4,
green columns). However, in all cases the common basis still
captured at least 90% of the total response energy (Fig. 4,
dotted line).
 |
DISCUSSION |
The main finding of this study is that neuronal networks in the
turtle cerebral cortex behave in a modal manner during visual processing. We believe this is the first empirical evidence of modal
behavior in a large-scale population of cortical cells. In our efforts
to understand the functional significance of this modal behavior, we
noticed an obvious resemblance in the spatial organization of our
cortical modes with the normal modes of a vibrating membrane
the drum
serving as the standard example in classical physics (Kac, 1966
).
Figure 4, bottom, compares M1,1, M1,2, M2,1, and
M2,2 of the diffuse white light trial with the
similarly named normal modes of a rectangular drum whose width
(w) is 70% of its height (h). The drum modes are
given by the equation Mm,n = sin(m
x/w) × sin(n
y/h) for all positive integers m and
n.
Relating the global behavior of the cortical network to that of a drum
was heuristically useful in analyzing and interpreting our experimental
results. For example, the normal modes of a musical drum are intrinsic
properties of the drum, being determined only by its physical
characteristics (i.e., shape, tension, and material properties) and not
by how the drum is struck (Kac, 1966
). Musical drums produce different
sounds when they are struck differently by changing the relative
contribution each mode makes to overall response. This is precisely
what we observed when we excited the cortex using different visual stimuli.
That a basis computed from a single trial can capture >90% of the
response energy for a series of responses evoked by a variety of visual
stimuli suggests that M1,1, M1,2, and M2,1 are relatively stable, intrinsic
properties of the global cortical circuitry in the turtle. It would not
make sense to project the results obtained in one trial onto a basis computed from a different trial if the patterns of coherent activity (modes) changed significantly from one trial to the next.
The ability to compare cortical responses evoked by a variety of
stimuli by projecting them onto a common basis appears to be the most
immediate benefit of this framework, because it provides guidance in
how to conduct comparisons across experimental preparations. Because
the shape and physical characteristics of the drum determine its modal
morphologies, the normal modes of approximately similar drums will have
approximately similar shapes. However, some variation in modal
structure would be expected from drum to drum because of differences in
construction and materials. Consequently, it seems more reasonable to
compare a collection of drums not on the basis of their modal structure
but, rather, on the basis of their sounds, i.e., their response signatures.
It follows then that if the goal is to understand how a certain
population of cortical neurons responds differentially to different
stimuli, we should expect the intrinsic cortical modes to exhibit some
degree of variability in their spatial organization from preparation to
preparation because of genetic, developmental, and environmental
differences. However, the qualitative shapes of the projection
trajectories might be sufficiently similar that it will be possible to
identify species-specific response signatures for different sensory stimuli.
In summary, cortical responses in the turtle, evoked by brief light
flashes, exhibit a spatial organization of coherent activity that
superficially resembles the normal modes of a drum. Because the modes
calculated from one trial in a preparation appear to capture a
significant portion of the energy of other trials, data sets from the
same preparation can be projected onto a common coordinate system for
comparison. The observation of modal behavior and the drum heuristic
provide a useful framework in which to plan, organize, and interpret
neurophysiological experiments designed to characterize the behavior of
large-scale cortical networks during the processing of sensory information.
 |
FOOTNOTES |
Received Oct. 28, 1998; revised Feb. 11, 1999; accepted Feb 17, 1999.
This work was supported by National Institutes of Health Grant G12
RR13646, National Science Foundation Grant ACI-9721348, Office of Naval
Research Grant N00014-97-0029, and the University of Texas at San
Antonio Office of the Provost. We thank L. Cohen for the generous
donation of the data acquisition software and P. Ulinski for thoughtful
criticism of an early version of this manuscript.
Movies of the data and reconstructions can be found at
http://vip.cs.utsa.edu/cortex/JNS/index.html.
Correspondence should be addressed to: David M. Senseman, Division of
Life Sciences, The University of Texas at San Antonio, San Antonio, TX 78249.
 |
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Copyright © 1999 Society for Neuroscience 0270-6474/99/$05.00/0
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