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The Journal of Neuroscience, December 1, 2001, 21(23):9403-9413
Voltage-Sensitive Dye Imaging of Neocortical Spatiotemporal
Dynamics to Afferent Activation Frequency
Diego
Contreras1 and
Rodolfo
Llinás2
1 Department of Neuroscience, School of Medicine,
University of Pennsylvania, Philadelphia, Pennsylvania 19104, and 2 Department of Physiology and Neuroscience, New York
University School of Medicine, New York, New York 10016
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ABSTRACT |
The spatial and temporal patterns of neocortex activation are
determined not only by the dynamic character of the input but also by
the intrinsic dynamics of the cortical circuitry. To study the role of
afferent input frequency on cortical activation dynamics, the
electrical activity of in vitro neocortex slices was
imaged during white-matter electrical stimulation. High-speed optical imaging was implemented using voltage-sensitive dyes in guinea pig
visual and somatosensory cortex slices concomitantly with intracellular
recordings. Single white-matter electrical stimuli activated
well-defined cortical sites with a radially oriented columnar
configuration. This configuration was followed, over the next few
milliseconds, by a lateral spread of excitation through cortical layers
5 and 6 and layers 2 and 3. Much of the optical response was eliminated
in low extracellular calcium, indicating that it was primarily
synaptically mediated.
Repetitive stimuli at 10 Hz reproduced the spatiotemporal pattern
observed for single stimuli. In contrast, repetitive stimulation in the
frequency range (~40 Hz) rapidly restrained the area of
excitation to a small columnar site directly above the stimulating electrode. Intracellular recordings from cells lateral to the activated
column revealed increased inhibitory synaptic activity and/or decreased
excitatory responses during the train at 40 Hz, but not during a 10 Hz
stimulation. Localized microinjections of GABAA antagonist
produced a reorganization of the geometrical activity pattern that was
dependent on the position of the microinjection site. These findings
indicate that the frequency-dependent spatial organization of neocortex
activation is determined by inhibitory sculpting attributable to
local network dynamics.
Key words:
optical; fluorescence; intracellular; cortex; voltage-sensitive dyes; ; binding; 40 Hz
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INTRODUCTION |
Neocortical network function has
traditionally been assumed to be determined by the integrate and fire
properties of local neurons and their connectivity (Calvin, 1975 ). In
such models, spatiotemporal patterns of cortical activation depend
solely on input dynamics and on the linear integrative properties of
the target neurons. However, because neurons are endowed with nonlinear dynamic properties (Llinás, 1988 ) and synaptic strength is known to be activity modulated (Zucker, 1989 ), network dynamics cannot be
defined solely on the basis of connectivity or single-stimulus activation.
One of the most dramatic examples of modulation of network dynamics
occurs in thalamocortical networks with the transition from wakefulness
to sleep. Thus, during slow-wave sleep (SWS) the spontaneous
electroencephalogram (EEG) is dominated by high-amplitude, low-frequency oscillatory activity of <15 Hz showing long-range synchronization (Steriade et al., 1993b ; Contreras et al., 1996 , 1997 ).
In contrast, during activated states (waking and paradoxical sleep),
magnetoencephalographic (Ribary et al., 1991 ) and EEG activity
are dominated by low-amplitude, high-frequency activity primarily at
the frequency range (30-50 Hz) (Steriade et al., 1993b ; Destexhe
et al., 1999 ) and display restricted spatial synchrony (Ribary et al.,
1991 ; Llinás and Ribary 1993 ; Steriade et al., 1996 ; Destexhe et
al., 1999 ; Traub et al., 1999 ). It has been argued that
spatially restricted fast oscillations are an essential step in the
cortical processing of inputs because they allow the formation of
groups of temporally coherent but spatially segregated clusters of
neurons (Llinás and Pare, 1991 ; Llinás et al., 1998 ; Singer, 1999 ; Varela, 1999 ; see also Laurent, 1999 ). For this hypothesis to be viable, the existence of spatially independent oscillatory clusters regulated by thalamocortical resonance must be
demonstrated. Such clusters should stabilize in a few re-entry cycles
and must coexist in coherence with each other independently of cluster
distance over the cortex, because the temporal binding would be
implemented at the thalamic level (Llinás et al., 1998 ). Here we present evidence that the first of these prerequisites (i.e.,
the generation of spatially segregated fast oscillating cortical
clusters) is obtainable by band afferent activation frequencies
(~40 Hz).
A key factor that could play a major role in shaping the cortical
activation geometry to afferent input frequency is the action of local
inhibitory neurons (Kawaguchi and Kubota 1993 ; Cauli et al., 1997 ;
DeFelipe, 1999 ; Gibson et al., 1999 ; Gupta et al., 2000 ). Indeed,
GABAergic inhibition has been shown to be critical in the stability of
cortical function, because its selective block induces epilepsy
(Prince, 1968 ; Connors, 1984 ; Steriade and Contreras, 1998 ; McCormick
and Contreras, 2001 ). Moreover, a subpopulation of layer 4 inhibitory
interneurons exhibits intrinsic oscillatory activity in the frequency band (Llinás et al., 1991 ). When local circuit synapses
are compared, excitatory connections into GABAergic interneurons
exhibit a more rapid and profound frequency-dependent depression
(Thomson and Deuchars, 1997 ; Galarreta and Hestrin, 1998 ) than do the
inhibitory outputs of those interneurons. In addition, it has been
shown recently that the output of interneurons with low-threshold spike
(LTS) firing characteristics onto spiny stellate cells facilitates
strongly when activated at 40 Hz, but not when activated at 10 Hz
(Gibson et al., 1999 ). Such interneurons are interconnected by chemical
and electrical junctions (Gibson et al., 1999 ). Because of all of the
characteristics mentioned above, it is reasonable to suggest that the
spatiotemporal properties of cortical responses to sustained input at
fast frequencies could in fact be shaped primarily by inhibitory circuits.
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MATERIALS AND METHODS |
Slice preparation and staining. Adult guinea pigs
were deeply anesthetized with sodium pentobarbital (50 mg/kg, i.p.) and decapitated after loss of limb-withdrawal reflex. Brains were removed
and transferred to chilled (4°C) Krebs-Ringer's solution containing
(in mM): 126 NaCl, 5 KCl, 2 CaCl2, 13 MgSO4, 12 KH2PO4, 26 NaHCO3, and 10 glucose saturated with a mixture
of 95% O2 and 5% CO2. In
the experiments in which no Ca2+ solution
was used, magnesium was increased by 2 mM, but
calcium chelators were not included. Coronal and sagittal slices (400 µm thick) were prepared from the visual and somatosensory cortex using a vibratome. Slices were stained with the voltage-sensitive dye
RH795 (Molecular Probes, Eugene, OR) (Grinvald et al., 1994 ) dissolved
(0.5 mg/ml) in normal Krebs-Ringer's medium with 0.5% of
dimethylsulfoxide. Slices were submerged for 4-5 min in the dye
solution before being transferred to the recording chamber. Recordings
were made in an interface-type chamber at 35 ± 0.5°C. Handling
and care of experimental animals was in agreement with the policy
established by New York University Medical Center and by the American
Physiological Society.
Optical recordings. A schematic drawing of the recording
set-up is shown in Figure
1A. An upright
microscope (Olympus BX50WI; Olympus Optical, Tokyo, Japan) was
mounted on an X-Y table (Warner Instruments, Hamden, CT), with the
recording chamber and micromanipulators attached to a rigid stand.
Epi-illumination was provided by a halogen lamp (12 V) driven by a
stable power supply (Kepco, Flushing, NY). Optical signals were
monitored with a fast CCD camera (HRDeltaron 1700; Fujix, Tokyo, Japan)
with a 128 × 128 pixel matrix and a total frame speed of 0.6 msec
(Matsumoto and Ichikawa, 1990 ). Although in a few instances the area
imaged was 8.2 × 8.2 mm, the imaged area was 4.3 × 4.3 mm
for the majority of the experiments, such that each pixel collected
light from a small region of 34 × 34 µm. The optical data sets
represent averages of either 8 or 16 trains of stimulation.
Fluorescence values are differential because each frame represents the
difference between the signal generated in response to stimulation
minus the value of a reference frame, multiplied by 400. A reference
frame was calculated as the average of 64 frames (0.6 msec integration
time) preceding the stimulation train. Stimuli (1-5 V, 100 µsec)
were applied by means of bipolar electrodes to the underlying white
matter.

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Figure 1.
A, Scheme of the setup arrangement
for optical recordings. The size of the field of view as well as filter
settings and wavelengths are indicated. B, Snapshots of
the response to a single electrical stimulus applied to the white
matter (guinea pig visual cortex slice) and recorded using differential
fluorescence (df) (left) and
F/F (right). The
responses were almost identical. The color scale from
blue to red represents a 0-0.48% change
in F/F and a 0-255 change in df. Layers are
indicated and are based on Nissl-stained sections. C,
Comparison of fluorescence values with intracellular membrane
potential. Fluorescence (recorded as df) and membrane potential
(Vm) in response to a single stimulus
to the white matter are shown. Top left, A snapshot of
activity (layers and stimulating electrode position are indicated) at
8.4 msec after the stimulus was applied to the white matter;
circles represent three arbitrary points where pixel
values were obtained. Intracellular recording was from position 2, as
indicated by the pipette. Top right, Time course and
amplitude of fluorescence values obtained at points 1-3. Bottom
left, Synaptic responses at three different
Vms to single stimuli applied to the white
matter. Bottom right, A comparison of the time course
and amplitudes of light and of a cell at rest ( 77 mV) recorded from
position 3. D, Depopolarizing and hyperpolarizing pulses
applied to the same cell as in C at various times during
the recording to verify that input resistance and action potential
characteristics are unaltered and the slice is healthy. The cell
depicted is a regular spiking cell from upper layer 6, with an input
resistance of 39 M . Scale bar: B, C, 1 mm.
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To determine whether the change in the amplitude of the fluorescence
signal F was significantly different from fractional fluorescence,
F/F (Grinvald et al., 1982 ), fractional fluorescence was
determined in a set of experiments (n = 5). As
illustrated in Figure 1B, the activation
spatiotemporal patterns was virtually identical with both methods.
Because the absolute fluorescence value is not relevant in this study
and because our aim was to investigate the patterns of cortical
activation, only F was used in the rest of the figures.
Intracellular recordings and electrical stimulation. Cells
were recorded intracellularly using sharp micropipettes (tip
resistances of between 40 and 80 M filled with 3 M potassium acetate). Electrodes were advanced
blindly using a hydraulic microdrive. Recordings were made using a
bridge amplifier (Cygnus Technology, Delaware Water Gap, PA) and were
digitized at 10 kHz using an analog-to-digital board (GW
Instruments, Somerville, MA) into a PC computer for offline analysis.
Analysis of intracellular data was done with home-written routines
using an Igor package (WaveMetrics Inc., Lake Oswego, OR).
Electrical stimulation was delivered by concentric bipolar electrodes
(platinum-iridium wire; 25 µm inner pole; 200 µm outer pole)
(model CBBRC75; Frederick Haer Co., Bowdoinham, ME) gently placed over
the surface of the white matter. Stimulation consisted of 100 µsec
pulses at 0.5-2 mA delivered through stimulus isolation units (World
Precision Instruments, Sarasota, FL).
Data analysis. Bleaching and irregularities of the staining,
although not significant, were corrected off-line by normalizing the
imaged surface. Signals were smoothed with a three-dimensional (3-D) moving average of 3 × 3 × 3 points and with equal
weight to eliminate high-frequency noise. All optical data analyses
were performed with software written in Matlab (Mathworks Inc., Natick, MA).
Histological controls. Some slices (n = 4)
were fixated in formaldehyde (4%), resectioned, and stained with
cresyl violet to identify cortical layers.
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RESULTS |
Our database was obtained from 31 experiments. Coronal or sagittal
slices (400 µm thick) from the visual (n = 24) and
somatosensory (n = 9) cortex were used. The responses
to single and repetitive stimuli were similar for both orientations and
brain regions studied; therefore, they will be presented together.
Slices were stained with the voltage-sensitive dye RH795 (Molecular
Probes) and electrical stimuli (100 µsec; 0.5-2 mA) were delivered
to the subcortical white matter. Optical images were recorded with a
fast (1700 frames/sec) CCD camera (HRDeltaron) and intracellular
recordings (n = 26) were obtained from layers 2-6
using sharp micropipettes (40-80 M impedance). Only those
intracellular recordings having resting membrane potentials negative to
70 mV, stable for >15 min, and with input resistances of >20 M
were considered in the database.
Comparison of optical signals with intracellular voltage
The first set of experiments compared the time course and
amplitude of the voltage-sensitive dye signals with simultaneously obtained intracellular voltage recordings. With the voltage-sensitive dye RH795, membrane depolarization is accompanied by a decrease in
fluorescence (Grinvald et al., 1994 ), represented here as a positive
signal. Simultaneous intracellular and optical recordings (n = 12) indicated a close correlation between the two
types of signals (Fig. 1C) (Tanifuji et al., 1994 ; Antic et
al., 1999 ). In a representative case illustrated in Figure
1C, the intracellular response matched closely the
fluorescence signal of the recording site (position 2, indicating the
recording micropipette location). To analyze the ionic origin of the
voltage response, we imposed transmembrane potential
(Vm) changes in the recorded cell
using current-clamp DC injections. Membrane depolarization revealed that the initial depolarization was attributable to a short-lasting EPSP followed by a reversed biphasic IPSP.
These IPSPs had a reversal potential (EIPSP) of
73 mV and so were reversed at the resting potential ( 77 mV). The
matching of the intracellular and optical data (Fig. 1C) was
always best at resting Vm, indicating
that the Vm of the recorded cell was indeed representative of the population generating the optical signal.
The mean resting Vm (n = 26) was 78 ± 5 mV, which is negative to the
EIPSP and partially explains why the majority of
the optical images indicated depolarizing responses.
Because a certain decree of phototoxicity is expected from
voltage-sensitive dye activation (Momose-Sato et al., 1995 ), we tested
cell viability by determining changes in excitability using current-pulse injections (Fig. 1D). Depolarizing
pulses of increasing amplitudes were used to evaluate the frequency
response properties of the cell and to measure action potential
characteristics. Such pulses produced results that concurred with the
firing characteristics described previously in cortical cells in
vitro (Connors et al., 1982 ; McCormick et al., 1985 ) and in
vivo (Nunez et al., 1993 ) indicating no evidence of cytotoxicity.
In addition, input resistance was monitored using hyperpolarizing
current pulses. Such measurements were done repeatedly during the
recording of optical responses. The stability of the responses over
time indicated no obvious tissue damage imposed by our experimental procedure.
Optical responses were primarily generated by
synaptic activation
Electrical stimulation of the white matter underlying the cortical
mantle excites both cortical afferent (primarily consisting of
corticocortical and thalamocortical fibers) and efferent fibers. Thus,
optical responses may result from antidromic or orthodromic (monosynaptic and/or polysynaptic) activation. However, on occasion such electrical stimuli may also directly activate cells in layer 6 and
the basal dendrites of layer 5 cells.
To separate the synaptic and nonsynaptic (antidromic and direct)
contribution to the optical responses, we perfused the slice in medium
in which extracellular Ca2+ was
substituted with Mg2+ (4 mM;
n = 5) (Fig. 2) for a
period of 30-40 min before stimulation. Under this condition, most of
the optical response was eliminated, except for focal activation in
layer 6 and in layers 2 and 3 in the vertical axis above the
stimulating electrode with no horizontal displacement. Activation of
layers 2 and 3 was observed 1.8 msec after activation of layer 6. Indeed, vertical propagation with the
Ca2+-free medium occurred at
velocities similar to those seen for the control images.

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Figure 2.
Optical recordings are primarily generated by
orthodromic activation. Snapshots of the optical responses to a single
stimulus under control conditions (left) show that the
response was almost completely abolished after 30 min of perfusion in a
medium in which Ca2+ was substituted with
Mg2+ (right). Cortical layers and the
position of stimulating electrodes are indicated.
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We attributed the activation of layers 2 and 3 in the absence of
Ca2+ to antidromic invasion, because those
layers project to neighboring cortical regions and are the origin of
the callosal connectivity (Miller, 1975 ; Swadlow and Weyand, 1981 ;
Segraves and Rosenquist, 1982 ). A contributing factor may also be
dendritic backpropagation from layer 5 and layer 6 pyramidal neurons
(Stuart et al., 1997 ), although it is not known how much
backpropagation may occur based solely on dendritic
Na+ currents (Huguenard et al., 1989 ;
Schwindt and Crill, 1997 ), and most of the apical dendrite excitability
after somatic action potentials seems to be attributable to
Ca2+ electrogenesis (Yuste et al., 1994 ;
Helmchen et al., 1999 ; Svoboda et al., 1999 ).
Response to single stimuli
The optical response to a single white-matter stimulus (Fig.
3A, see also Fig.
1B for comparison with fractional fluorescence) was
characterized in both visual (n = 24) and somatosensory
(n = 9) cortical slices. Frequently the response
consisted of an initial layer 6 activation immediately above the
electrode (frame at 1.2 msec). This event was followed by a propagation
of activation toward layer 1 and a close to simultaneous horizontal
activation through layers 6 and 5 (see frame at 2.4 msec). After
reaching layers 2 and 3, the activation propagated horizontally through those layers as well (frame at 3.6 msec and after), albeit more slowly
than through deep layers. Responses were always larger in the deep (5 and 6) and superficial (2 and 3) layers than in layer 4 (see for
example frame at 6.0 msec), with maximum amplitude in layers 2 and
3.

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Figure 3.
A, Spatiotemporal patterns of
activation resulting from electrical stimulation of the white matter.
Optical recordings from guinea pig visual cortex are shown. Time is
indicated in milliseconds after the stimulus, and the position of the
stimulating electrode is indicated as well. The cortex is positioned
with layer 1 on the top and layer 6 on the
bottom. The color scale for fluorescence intensity is
arbitrary between 0 (blue) and 255 (red).
B, Activation profiles after a single electrical
stimulus was applied to the white matter. A visual cortex slice is
shown. Top left, A snapshot of activation at
t = 8.4 msec; layers are indicated. Bottom
left, Temporal evolution (x-axis) of activation
along a vertical line from layers 1-6
(y-axis). The overlying white line
is the summation of pixel values across time (from left
to right) and shows maxima in layers 2 and 3 with a
second peak in infragranular layers. Right, Temporal
evolution of the activity along a line of pixels parallel to the pial
surface within layers 2 and 3 (top) and layer 6 (bottom). Space is represented from left
(L) to right
(R) of the slice (x-axis); time
after stimulation is indicated on the y-axis. Profiles
show not only the extent and velocity of propagation but also the
duration of the activation of any given pixel.
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To measure the extent and the velocity of the propagation in different
directions and planes, we constructed activation profiles (Fig.
3B). These images represent fluorescence signal against time
from those pixels that fall under an arbitrary line drawn over the
slice image. Three activation profiles are represented in Figure
3B: one vertical (from layers 1-6, bottom left)
and two horizontal (layers 2 and 3, top right; layers 5 and
6, bottom right). The horizontal activation profiles were
traced left to right as indicated in Figure 3, right.
Because activation profiles represent space against time, the velocity
of propagation is given by the slope of the apparent activation front
(defined as the visible separation between activated and nonactivated
areas). If the velocity is uniform, the activation front is close to a straight line, which is the case for the propagation toward the left of
the slice in deep and superficial layers. If propagation velocity were
to be site-specific, then the apparent activation front in the profile
would show slope changes. Because space is represented on the
x-axis and time on the y-axis, an increase or
decrease in slope corresponds to a decrease or increase in propagation
velocity. Nonhomogeneous propagation fronts can be seen in both
horizontal profiles in Figure 3B when activation moves from
the center toward the right side of the slice.
To detect heterogeneities in the spatial and/or temporal distribution
of fluorescence, we integrated pixel values in the activation profiles
against time (overlying white lines in the profiles). This procedure
demonstrated that activation is not uniform in the vertical direction.
Indeed, as discussed above, infragranular and supragranular layers
showed larger activation than layer 4, with a maximum in layers 2 and
3. In contrast, horizontal activation profiles showed evenly
distributed activation with a bilaterally smooth decay from the center
of the slice, where the stimulating electrode was located. In most
experiments (n = 12), activation propagated vertically
from layers 6-1 at 265 ± 48 mm/sec (mean ± SD) and
horizontally through deep layers at 217 ± 53 mm/sec. Propagation
through layers 2 and 3 occurred at 181 ± 44 mm/sec. In some
cases, profiles such as those illustrated in Figure 3B indicate asymmetric activation in the horizontal plane. We attributed these asymmetries to slice section characteristics, because on some
occasions slices demonstrated symmetrical activation profiles (Fig.
4). The horizontal extent of propagation
measured from the activation profiles after single stimuli was 2.1 ± 0.4 mm in each direction from the stimulating electrode; the extent
of propagation was similar among slices, regardless of cortical
orientation and brain region.

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Figure 4.
A, Spatiotemporal characteristics
of activation depend on the frequency of stimulation. Snapshots at 7.2 msec after stimulation during the first (left) and fifth
(right) stimuli during trains at 10 (top
row) and 40 Hz (bottom row) are shown. The color
code for intensity ranges from 0 to 255. Responses to the first
stimulus were identical at both frequencies. The response to the fifth
stimulus did not change when stimulation was at 10 Hz; in contrast, the
activation area became smaller and the response amplitude became higher
during stimulation at 40 Hz. B, Temporal evolution of
the spatiotemporal properties of activation during repetitive
stimulation (arrowheads). Activation profile (as in Fig.
3B) across layers 2 and 3 in a visual cortical slice.
Distance is indicated on the y-axis, and time is
indicated on the x-axis. Activation spanned the entire
length (~2.2 mm) of the profile for each stimulus at 10 Hz but shrunk
progressively to ~1 mm during stimulation at 40 Hz.
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Response to rhythmic input activation
The dependence of the activation pattern on white-matter
stimulation frequency was explored with two different frequencies, 10 and 40 Hz. These frequencies were chosen to mimic the prevailing rhythms present in vivo during SWS and activated states,
respectively (see the introductory remarks). During trains of
stimulation at 10 Hz, activation patterns extended laterally over a
large portion of the slice and remained constant throughout the train.
The extent and the velocity of propagation showed almost no change,
such that the first and fifth stimulus in a train produced similar optical images (Fig. 4A, 10 Hz). In contrast,
stimulation at 40 Hz progressively reduced the activation area to a
vertical column-like geometry that overlaid the stimulating electrode
(Fig. 4A, 40 Hz). The average area of activation
after repetitive stimulation at 40 Hz extended laterally for <0.5 mm
and showed higher peak amplitude than during the 10 Hz stimulation. On
occasion, such activity could be as wide as 1 mm, depending on stimulus
intensity (see Fig. 7 below).
The dynamics of the optical responses in the horizontal plane after
different activation frequencies are best illustrated by plotting
activation profiles (Fig. 4B). The activation profile depicted in Figure 4B represents fluorescence along
layers 2 and 3 in response to stimulation of the white matter. With
stimulation at 10 Hz (Fig. 4B, left), the
optical response after each stimulus spanned the entire length of the
tissue (~2 mm) for each response. At 40 Hz (Fig.
4B, right), a progressive decrease in the
lateral extent of the activation was observed to ~1 mm after the
fifth stimulus. There was also a marked increase in the amplitude of the optical signal in the center of the activated area. This was demonstrative of a powerful and localized temporal summation during the
40 Hz frequency stimulation.
Spatial interaction between two cortical activation sites
In light of the results shown above, we expected, as briefly
reported previously (Llinás et al., 1998 ), that responses should coalesce spatially when stimulation at 10 Hz is applied at more than
one site, whereas stimulation at ~40 Hz should give rise to
segregated response areas. The dynamics of the responses to more than
one stimulation site were studied by stimulating the white matter with
two electrodes separated by 1-4 mm. In the example shown in Figure
5, two stimulating electrodes were placed
in the white matter separated by 1.5 mm; trains of 10 stimuli at 10 Hz (Fig. 5, top) and 40 Hz (Fig. 5, bottom) were
applied, first with each of the electrodes individually
(Electrode 1 and Electrode 2) and then with both
simultaneously (Both). The response depicted in Figure 5 is
to the 10th stimulus. Stimulation with each of the electrodes alone
(Fig. 5, left and middle) gave rise to responses with the spatiotemporal pattern described above, namely, responses to
the 40 Hz train evolved toward a spatially restricted and
high-amplitude pattern, whereas responses at 10 Hz remained stable and
spread laterally. When stimulation was delivered through both
electrodes simultaneously (Fig. 5, Both), the responses to
10 Hz propagated horizontally and collided in the middle of the slice.
In contrast, the responses to the 40 Hz stimulation developed into two
segregated areas with high amplitude and separated by a region with no
optical signal.

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Figure 5.
Spatiotemporal aspects of activation with two
electrodes. A slice from the visual cortex was stimulated with two
electrodes in the white matter separated by 1.5 mm. The 3-D snapshots
illustrate the evolution of the optical response for the 10th stimulus
in a train at 10 Hz (top) and 40 Hz
(bottom). The responses to the 10th stimulus delivered
by each electrode and then the two simultaneously are illustrated.
During stimulation at 40 Hz, the activated areas remain segregated. The
position of stimulating electrode is indicated.
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Intracellular responses to repetitive stimulation
The cellular mechanisms underlying the optical responses described
above were investigated by comparing fluorescence signals with
intracellular recordings. Two sites were investigated (Fig. 6): one immediately above the stimulating
electrode (dotted lines, area 1) and one equidistant from
both electrodes (area 2). During the 10 Hz stimulation (Fig. 6,
LIGHT; 10 Hz), fluorescence signals remained almost
unchanged in amplitude and duration at both sites, with values from
site 2 having smaller amplitudes, slower rising phases, and longer
latencies (~2 or 3 msec) than values from site 1. In contrast, during
stimulation at 40 Hz (Fig. 6, LIGHT; 40 Hz), pixel values
did not remain constant; in site 1 there was strong temporal summation
and in site 2 there was a progressive decrease in amplitude. Variations
in the amplitude of the responses during the 40 Hz stimulation were
only attributable to the frequency of the stimulation, because the
first response for trains at both frequencies was virtually identical
(see superimposition of first and last responses at the bottom
right of Fig. 6).

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Figure 6.
Pixel values and intracellular
recordings during stimulation at different frequencies.
Fluorescence values (LIGHT) and intracellular
recordings (Vm) were obtained from
areas 1 and 2 (dotted lines) during stimulation at 10 and 40 Hz (A1 and A2, respectively, in
Vm). Bottom right,
Comparisons of the first (blue dot) and the last
(red dot) of the responses during the trains at the two
frequencies are superimposed. B, Cell from position 2 in
A2 (arrow). Increasing the intensity of
stimulation (from bottom up) triggered responses to all stimuli at 40 Hz. C, Different cells showing long-lasting inhibition
triggered by a 40 Hz stimulation.
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Intracellular recordings obtained from the same two areas (Fig. 6,
Vm) showed results that were similar
to those observed for the fluorescence signals. Stimulation at
10 Hz (Fig. 6, A1) generated depolarizing PSPs that did not
change in amplitude or duration with respect to the first response in
cells recorded from both area 1 and area 2. PSPs from the cell in area
2 showed a latency that was similar to that seen for the fluorescence
signal. Stimulation at 40 Hz generated synaptic responses in cells from area 1 showing different degrees of temporal summation (Fig. 6, A2 and C). We recorded two types of synaptic
responses from cells in area 2: (1) a marked depression of the synaptic
response (Fig. 6, A2) (n = 7) usually
between stimuli 4 and 7, or (2) a clear EPSP in response to each
stimulus but on a background of a growing IPSP triggered during the
train (Fig. 6C) (n = 3). The difference did
not depend on layer, electrophysiological cell type, or intensity of
stimulation. Additional experiments are necessary to clarify this issue.
Increasing the intensity of stimulation at 40 Hz led to the generation
of responses in the cells recorded from site 2 for all of the stimuli
in the train (Fig. 6B,
Vm). This was accompanied by the
generation of a corresponding optical signal at site 2 which, as shown
above, had no optical signal at a lower intensity of stimulation after
4 or 5 stimuli (data not shown). We attributed this effect to an
increase in the activated area because of stimulus current spread. This
is indeed equivalent to bringing the stimulating electrode closer to
site 2, thus converting the stimulus geometry similar to site 1. However, a similar increase in stimulation intensity only increased the
amplitude of the IPSP for those cells that responded with inhibition,
suggesting that there is more than simply the recruitment of more
afferent axons by current spread.
The drastic reduction of synaptic amplitude during stimulation at 40 Hz
was further analyzed by holding the cell at different Vms during the stimulus train (Fig.
7) (n = 5). Stimulation
at rest (Fig. 7A, 78 mV) elicited depolarizing PSPs
exclusively, which showed a marked depression during the train (Fig.
7C). DC depolarization to 53 mV (Fig. 7A-C,
top traces) revealed that the response to the first stimulus
consisted of a short EPSP with a peak latency of 5 msec; this EPSP was
sharply terminated by a fast IPSP with a peak latency of 9.5 msec and a
reversal potential of 72 mV. The reversal potential and short
duration suggest that the IPSP was caused by the activation of
GABAA receptors. At more positive
Vms, the synaptic response to the last
few stimuli of the train was almost completely abolished; however, a
depolarizing response could still be recorded with hyperpolarization.
This result indicated that the depression of the synaptic response occurred at the expense of the early EPSP. To verify this possibility, we scaled the amplitude of the response to the last stimulus with the
response to the first stimulus and superimposed the two (Fig. 7D). The superimposition showed that the response to the
last stimulus lacked the initial EPSP, reinforcing the notion that the
depression observed in site 2 during stimulation at 40 Hz is primarily
attributable to EPSP depression, which suggests a reduction of a
polysynaptic circuit or a very powerful synaptic shunt, probably at a
remote dendritic level.

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Figure 7.
Membrane polarization reveals
frequency-dependent depression of EPSP. A cell recorded intracellularly
from the column above the stimulating electrode is shown.
A, Electrical stimulation at 40 Hz was delivered to the
white matter while changing the Vm of the
cell with DC. Traces are displaced artificially for
clarity. Vm is indicated. B,
Detail of the responses from A, as indicated by the
black bar. C, Detail from the first,
middle, and last synaptic responses from trains in A and
B. Vertical dotted lines indicate the
peak of the EPSP and IPSP, respectively. Horizontal dotted
lines are the most depolarized and hyperpolarized
Vms because of DC injection.
D, Superimposition of the first and last responses
(dotted line, scaled to match amplitude of the first
response). The last response lacks the EPSP and consists almost
exclusively of an inverted IPSP. E, Comparison of the
train of responses with response to a single stimulus; the time course
of the response to a single shock matches the underlying shape of the
train.
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|
The response to a single stimulus showed an early EPSP followed by a
biphasic IPSP, probably attributable to the activation of
GABAA and GABAB receptors,
as has been described in vitro (Connors et al., 1988 ). The
presence of a long-lasting IPSP modulating the responses to the train
could be seen by superimposing a single stimulus to the train responses
(Fig. 7E).
Inhibition shapes spatiotemporal properties of
evoked responses
Finally, we blocked GABAA receptors with
bicuculline to test the role played by GABAergic inhibition in shaping
the spatiotemporal activation patterns described above. Two
methodologies were used: bath application by superfusion
(n = 6) and local application (n = 12)
of bicuculline through a micropipette inserted into the slice
parenchyma. After perfusion, a single stimulus caused an epileptogenic
high-amplitude wave that propagated primarily through layers 2 and 3 and layers 5 and 6, across the entire slice at ~0.1-0.3 mm/sec,
similar to that described using field potentials (Connors, 1984 ). In
contrast, local application did not alter the normal response to
stimulation, except for an expansion of the activation boundary at the
site of the injection (Fig. 8, Control). Indeed, when stimuli were delivered to the
immediate vicinity of the injection site, activation occurred in a
localized but almost explosive manner and had a long time course
(hundreds of milliseconds) such that the usual dynamic properties of
the cortical activation were obliterated. When the injection of
bicuculline was made at the boundary of the area that responds in
control conditions after a single stimulus, it produced an extension of the response to the single stimulus into the injection site (Fig. 8,
site b); this response showed a large amplitude and
persisted for 200-300 msec (Fig. 8, Bic position 1,
red line in plot). Finally, an injection was placed in a
site beyond the observable limit of the control activation wave (Fig.
8, site c). Activation after a single stimulus proceeded as
in the control but eventually invaded the injection area, although this
site was noncontiguous with the control activation region (Fig. 8,
Bic position 2, green line in plot).

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Figure 8.
Spatiotemporal properties of activation after a
single stimulus were altered by local injection of bicuculline.
Left, Snapshots of the control response to a single
stimulus applied to the white matter; time after stimulus is indicated
on the left. Middle, Pattern of
propagation after local injection of bicuculline (dotted
circle) in position b. Right,
Pattern of propagation after local injection of bicuculline
(dotted circle) in position c. Values
from pixels located in positions a
(blue), b (red), and
c (green) along the path of
propagation are plotted on the right. Note that the
pixel values are plotted against the 0-255 color scale represented on
the left. Activation invaded areas farther away from the
stimulation site according to the location of the bicuculline
injection.
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|
 |
DISCUSSION |
The main thrust of this work was aimed at understanding the
dynamics of cortical activation in response to different input frequencies. Our results show that the cortical spatiotemporal activation patterns, after stimulation of the underlying white matter,
are critically determined by the stimulus frequency. We also show that
cortical activation patterns are partially dependent on local
GABAA gated inhibition. In addition, the results
were independent of orientation of the slice plane or brain region. Therefore, we concluded that the cortical spatiotemporal patterns described here must reflect a general property of at least primary sensory regions of the neocortex.
The origin of the optical signal
Most of the optical signal from the neocortex recorded using
voltage-sensitive dyes originates from dendrites of pyramidal and spiny
stellate cells (Grinvald et al., 1994 ; Yuste et al., 1997 ). An
additional source of the optical signal is the depolarization of
non-neuronal elements such as glial cells during repetitive stimulation
(Konnerth et al., 1987 ; Salzberg, 1989 ). A possible explanation for the
lower amplitude of signals in layer 4 reported here is the presence of
strong local inhibition activated by layer 6 input (Bolz and Gilbert,
1986 ). This assumption is corroborated by the finding that adding
bicuculline increased the amplitude of layer 4 activation (Fig. 8).
The advantage of voltage-sensitive dye imaging over field potentials or
current-source density analysis is that
Vm is recorded directly and
simultaneously from a large number of cells. Other publications have
elegantly addressed the differences between local field potentials and
optical signals (Salzberg et al., 1973 ; Albowitz and Kuhnt, 1993a ).
Horizontal propagation
Our results show propagation patterns in agreement with previous
voltage-dependent dye measurements from the visual (Albowitz and Kuhnt,
1993a ; Tanifuji et al., 1994 ; Nelson and Katz, 1995 ) and auditory
(Kubota et al., 1997 ) cortices and with the detailed analysis of the
visual cortex microcircuitry using voltage-sensitive dyes (Yuste et
al., 1997 ). In contrast, our experiments measured activity over a
broader field of view and revealed lateral activation of 2 mm in each
direction, more than double that found in previous studies for the
visual cortex (Tanifuji et al., 1994 ; Nelson and Katz, 1995 ) or the
auditory cortex (Kubota et al., 1997 ).
Our measurements of horizontal conduction velocities show higher values
than those reported by others (Tanifuji et al., 1994 ), probably because
we did not use bicuculline in our control experiments. Bicuculline
enhances the optical signal but generates a significant reduction of
propagation velocities and changes the distribution of activity in
horizontal propagation (Nelson and Katz, 1995 ) (our unpublished
observations). Indeed, we expect the velocities to increase during
cortical activation, such as occurs under the influence of
neuromodulation (McCormick, 1992 ), a situation in which neurons are
depolarized and thus closer to firing threshold.
Propagation of activity in the horizontal direction may be attributable
to (1) divergent translaminar connections or (2) horizontal intralaminar connections. Divergent translaminar projections originate from all cortical layers and terminate preferentially in layers 2 and 3 (Fitzpatrick et al., 1996 ; Somogyi et al., 1998 ). Horizontal intralaminar projections are most prominent in layers 2 and 3 and are
absent in layer 4 (Gilbert 1992 ; Fitzpatrick et al., 1996 ; Somogyi et
al., 1998 ). Alternatively, activity may propagate through regenerative
loops using both vertical interlaminar connections and horizontal
intralaminar projections (Tanifuji et al., 1994 ). Our data do not allow
discrimination between the different alternatives, but because
propagation velocities in the vertical and horizontal directions were
of the same order of magnitude, it seems unlikely that the horizontal
propagation that we measured was attributable to complex regenerative circuits.
Antidromic versus orthodromic activation: the synaptic origin of
the optical signal
Comparison of the fluorescence responses to
Vm recorded intracellularly showed
that the optical recordings primarily reflect synaptically derived
potentials ranging from 5 to 20 mV in amplitude and very little
contribution of action potentials. This finding is in agreement with
previous reports (Albowitz and Kuhnt 1993a ,b ; Tanifuji et al., 1994 ;
Cohen and Yarom, 2000 ). Our results showed that in the absence of
extracellular calcium, most of the optical response is absent. The
remaining fluorescence (Fig. 2) consisted of a brief optical signal
originating in layer 6 followed by layers 2 and 3. This low
Ca2+ response may be attributable to (1)
orthodromic activation of presynaptic terminals of corticocortical or
thalamocortical afferents or (2) antidromic activation neurons in
layers 2-6 in conjunction with some degree of dendritic
backpropagation of the action potential (Stuart et al., 1997 ). We favor
the second alternative because: (1) The results show absence of lateral
spread both in superficial and deep layers and absence of layer 4 activity. This finding also excludes a presynaptic origin because
thalamocortical presynaptic terminals should be visible in layer 4. In
addition, the neurons in layers 5 and 6 and layers 2 and 3 have axon
collaterals with abundant lateral spread inconsistent with the
spatially restricted signal shown here. (2) The slow time course of the
response (>3 msec to reach layers 2 and 3) is consistent with some
contribution of dendritic backpropagation from layers 5 and 6. Given
the absence of Ca2+ in the bath, the
contribution of backpropagation to the response would be supported by
the different types of Na+ conductances
present in the apical dendrites (Huguenard et al., 1989 ; Schwindt and
Crill, 1997 ).
Role of inhibition on the geometry of cortical activation
Our experimental design was also aimed at determining the
contribution of GABA-mediated inhibition to the geometry of cortical activation. GABAA blockers (such as bicuculline)
have been shown to increase both the optical response amplitude as well
as the area of cortical activation after a single stimulus (Albowitz and Kuhnt, 1993a ,b ; Tanifuji et al., 1994 ). However, in those studies
bicuculline was applied to the bath, blocking inhibition throughout the
entire slice; therefore, the propagating excitation was abnormally
large in extent and amplitude. Here we applied bicuculline at
restricted small areas in the depth of the cortical tissue, which did
not interfere with normal propagation in the rest of the slice. Our
results show that synaptic activation after application of a single
stimulus to the white matter reaches beyond the area observed by the
optical signals. Such activity is not visible in control conditions
probably because of powerful local inhibition that restricts local
excitatory re-entry. In support of this interpretation, we found that
the GABA antagonist injection sites placed beyond the outer edge of the
optical response were eventually invaded by activity and that, as
expected, such activation had the long-delay characteristic of
polysynaptic re-entry loops (Fig. 8, right).
Our results also suggest that although inhibition is important in the
normal distribution of cortical activation, it plays a crucial role in
the geometry of the band activation pattern. Indeed it seems to be
the basic sculpting mechanism for band activation (Llinás,
1990 ), as suggested by the intrinsic oscillatory properties of the
sparsely spiny GABAergic interneurons in layers 3 and 4 (Llinás
et al., 1991 ). Those cells were shown to have oscillatory intrinsic
activity supported by persistent sodium conductances that could be
blocked by tetrodotoxin (Llinás et al., 1991 ). In addition, it
has been shown recently (Gibson et al., 1999 ) that activation of a
particular set of inhibitory interneurons (LTS neurons) is strongly
potentiated for input frequencies at ~40 Hz, which suggests that this
type of interneuron may play an important role in the
frequency-dependent geometry of cortical activation.
Input frequency determines spatiotemporal pattern of
cortical activation
The finding that repetitive stimulation may alter the dynamic
architecture of cortical activation indicates that frequency has
intrinsic significance in cortical function. In agreement with recent
findings showing that thalamic neurons can also oscillate at frequency (Contreras et al., 1992 ; Pinault and Deschenes, 1992 ;
Steriade et al., 1993a ; Pedroarena and Llinás, 1997 ), it was
proposed that oscillations result in the generation of spatially restricted thalamocortical oscillatory columns by resonant
thalamocortical activity (Llinás, 1990 ; Llinás et al.,
1991 , 1998 ; Ribary et al., 1991 ; Pedroarena and Llinás, 1997 ).
Our results show that restricted, discrete regions of activation of
cortex, as observed in vivo, may be obtained by activation
at band frequencies. Because we could obtain such patterns with
nonspecific stimulation of the white matter in slices, it is reasonable
to suppose that the spatiotemporal differences observed in
vivo are attributable, at least in part, to a fundamental property
of cortical circuits.
The columnar organization of thalamocortical band activity
It has been known since the groundbreaking experiments of
Mountcastle (1957) and Hubel and Wiesel (1962) that physiological cortical responses demonstrate columnar organization. Cortical columns
(300-600 µm in diameter) are defined functionally by the grouping of
neurons with similar properties and were first described in the
somatosensory cortex of the cat and monkey (Mountcastle, 1957 ; Powell
and Mountcastle, 1959 ). Columnar organization is maintained by the
characteristics of afferent inflow and by the subsequent intracortical
processing; the relative importance of each in shaping cortical columns
varies with cortical area (Mountcastle, 1997 ). The anatomical basis for
columnar organization is the clustered nature of thalamocortical input
(Jones, 1983 ) and the local intracortical connections in the vertical
axis (Lorente de No, 1938 ; Szentagothai, 1975 ), which engage neurons in
all layers during activation. Cortical columns may be regarded as
modules for distributed coherent information processing and, if so,
their functional isolation would be fundamental in neocortical
functioning. We have shown here that band frequency is critical in
determining the formation of patches of activation that resemble
cortical columns, although the areas reported here are of slightly
larger diameter (up to 1 mm).
In summary, the central finding in this study relates to the presence
of separable clusters of cortical activity that are defined by the
dynamics of the afferent input frequency, in particular by band
activity. This clustering seems to be independent of neighboring
structures and to be operant in a horizontally isotropic manner (Fig.
5). Given that spatial focusing of cortical activation during a 40 Hz
stimulation can occur after just a few stimuli, such spatial filtering
could be established very rapidly in an in vivo situation.
We may imagine a scenario in which corticothalamic network activity at
the band could support the varied and ever-changing activity
necessary for the generation of consciousness in the vertebrate brain
(Llinás et al., 1998 ).
 |
FOOTNOTES |
Received June 26, 2001; revised Sept. 18, 2001; accepted Sept. 18, 2001.
This work was supported by the Human Frontier Science Organization, by
the Research Foundation of the University of Pennsylvania, and by
National Institutes of Health/National Institute of Neurological Disorders and Stroke Grant NS13742. We thank Joseph Frey for his technical assistance and Elena Leznik and Francisco Urbano for their
help in experiments and analysis.
Correspondence should be addressed to R. Llinás, Department of
Physiology and Neuroscience, New York University School of Medicine,
550 First Avenue, New York, NY 10016. E-mail:
Llinar01{at}endeavor.med.nyu.edu.
 |
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