Institut National de la Santé et de la Recherche Médicale U. 371, Cerveau et Vision, 69675 Bron Cedex, France
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ABSTRACT |
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Nowak, L. G., M.H.J. Munk, A. C. James, P. Girard, and J. Bullier. Cross-correlation study of the temporal interactions between areas V1 and V2 of the macaque monkey. Cross-correlation studies performed in cat visual cortex have shown that neurons in different cortical areas of the same hemisphere or in corresponding areas of opposite hemispheres tend to synchronize their activities. The presence of synchronization may be related to the parallel organization of the cat visual system, in which different cortical areas can be activated in parallel from the lateral geniculate nucleus. We wanted to determine whether interareal synchronization of firing can also be observed in the monkey, in which cortical areas are thought to be organized in a hierarchy spanning different levels. Cross-correlation histograms (CCHs) were calculated from pairs of single or pairs of multiunit activities simultaneously recorded in areas V1 and V2 of paralyzed and anesthetized macaque monkeys. Moving bars and flashed bars were used as stimuli. The shift predictor was calculated and subtracted from the raw CCH to reveal interactions of neuronal origin in isolation. Significant CCH peaks, indicating interactions of neuronal origin, were obtained in 11% of the dual single-unit recordings and 46% of the dual multiunit recordings with moving bars. The incidence of nonflat CCHs with flashed bars was 29 and 78%, respectively. For the pairs of recording sites where both flashed and moving stimuli were used, the incidences of significant CCHs were very similar. Three types of peaks were distinguished on the basis of their width at half-height: T (<16 ms), C (between 16 and 180 ms), and H peaks (>180 ms). T peaks were very rarely observed (<1% in single-unit recordings). H peaks were observed in 7-16% of the single-unit CCHs, and C peaks in 6-16%, depending on the stimulus used. C and H peaks were observed more often when the receptive fields were overlapping or distant by <2°. To test for the presence of synchronization between neurons in areas V1 and V2, we measured the position of the CCH peak with respect to the origin of the time axis of the CCH. Only in the case of a few T peaks did we find displaced peaks, indicating a possible drive of the V2 neuron by the simultaneously recorded V1 cell. All the other peaks were either centered on the origin or overlapped the origin of time with their upper halves. Thus similarly to what has been reported for the cat, neurons belonging to different cortical areas in the monkey tend to synchronize the time of emission of their action potentials with three different levels of temporal precision. For peaks calculated from flashed stimuli, we compared the peak position with the difference between latencies of V1 and V2 neurons. There was a clear correlation for single-unit pairs in the case of C peaks. Thus the position of a C peak on the time axis appears to reflect the order of visual activation of the correlated neurons. The coupling strength for H peaks was smaller during visual drive compared with spontaneous activity. On the contrary, C peaks were seen more often and were stronger during visual stimulation than during spontaneous activity. This suggests that C-type synchronization is associated with the processing of visual information. The origin of synchronized activity in a serially organized system is discussed.
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INTRODUCTION |
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Synchronization of neuronal activities has been proposed to play a
fundamental role in information processing by allowing distributed
neuronal populations activated by a common stimulus to be bound
together into a single percept (Abeles 1982a;
Damasio 1990
; Milner 1974
; Singer
and Gray 1995
; von der Marlsburg 1981
). Related
to this proposal is the hypothesis that synchronization allows a
selection of postsynaptic neurons by virtue of a coincidence detection
mechanism (Abeles 1982a
; König et al.
1996
).
Synchronized activities have been demonstrated extensively for neurons
belonging to the same cortical area (for review: Fetz et al.
1991; Singer and Gray 1995
). However, if
synchronization signals the participation of different cells to the
same assembly, it also should be observed between different cortical
areas. In support of this notion, synchronization has been found in cat visual cortex between different areas of the same cortical hemisphere (Eckhorn et al. 1988
; Engel et al. 1991b
;
Katsuyama et al. 1996
; Nelson et al.
1992
) and between corresponding areas of opposite cortical
hemispheres (Engel et al. 1991a
; Nowak et al.
1995b
). In addition to synchronized gamma range oscillation
(Eckhorn et al. 1988
; Engel et al.
1991a
,b
; Nowak et al. 1995b
), nonoscillatory forms of synchronization also have been found that have been classified into three groups according to the width of the peak of the
cross-correlation histogram (Nelson et al. 1992
;
Nowak et al. 1995b
): a narrow type of peak (T for
"towers," a few milliseconds width) was observed mainly between
cells having overlapping receptive fields and similar orientation
preferences. An intermediate type of peak (C for "castles"), with
a temporal precision in the tens of milliseconds range, was found to
occur for cells independently of their receptive field separation,
provided it was not >8°. The third type of peak that was encountered
in these studies is one with a width of one or several hundred
milliseconds (H for "hills"). This kind of synchronization was
independent of the orientation preference of the recorded cells, and
was observed even for cells having large receptive field separations.
In the cat, however, there are numerous indications that, to a large
extent, information can be processed in parallel in different cortical
areas: the lateral geniculate nucleus projects to all the visual
cortical areas (Bullier 1986) and lesion or inactivation of area 17 does not produce a loss of response in extrastriate cortical
areas (reviewed in Bullier et al. 1994
). Thus it might be argued that the presence of synchronization between neurons of
different cortical areas basically reflects the parallel organization of cat visual system.
In contrast, several lines of evidence suggest that the primate visual
system is organized in a serial manner: extrastriate areas receive only
a sparse input from the LGN (Bullier and Kennedy 1983;
Hernández-Gonzáles et al. 1994
;
Wong-Riley 1976
); when area V1 of the macaque monkey is
inactivated, area V2 and areas of the occipito-temporal stream are
silenced (reviewed in Bullier et al. 1994
); also,
latencies of neurons in area V1 are shorter than those measured in
extrastriate cortex (reviewed in Nowak and Bullier
1997
). These observations are consistent with the idea that
neurons in V1 provide the drive to several cortical areas of the
extrastriate cortex. This, however, questions the possibility of
synchronization between neurons of areas located at different levels of
the cortical hierarchy.
We have addressed this issue in macaque monkey areas V1 and V2, which
clearly belong to different levels of the hierarchy, as evidenced by
the morphology of their connections (Felleman and Van Essen
1991), the latencies of the neuron responses to visual stimuli
(Raiguel et al. 1989
; Nowak et al.
1995a
), and the effects of inactivation of V1 on V2 neurons
(Girard and Bullier 1989
; Schiller and Malpeli
1977
). To test for the presence of action potential
synchronization between areas V1 and V2, we recorded single- and
multiunit activities and calculated cross-correlation histograms.
To test more precisely the relationship between the serial organization of areas V1 and V2 and the temporal coherence of their neuronal activities, we used flashes as stimuli in addition to moving bars. Using flashed stimuli enabled us to measure precisely the latencies of the responses. It was then possible to compare the latency difference between area V1 and area V2 neurons with the displacement of the cross-correlation histographic (CCH) peak to understand if the later reflects the order of their activation.
Finally, we wished to determine to what extent the different types of
CCH peaks are related to the processing of visual information. For that
purpose, we compared the peaks obtained during spontaneous activity
with those obtained during the responses to visual stimuli. Some of
these results have been presented in abstract or preliminary form
(Bullier et al. 1992; Munk et al. 1993
;
Nowak et al. 1994
).
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METHODS |
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Animal preparation, visual stimulation, and recording
Acute recordings were obtained from eight cynomolgus monkeys.
Details on the surgical procedures have been given in previous publications (Girard et al. 1992; Nowak et al.
1995a
). During recording, anesthesia was maintained with
nitrous oxide/oxygen (70/30%) supplemented by fentanyl (5 µg · kg
1 · h
1), whereas paralysis
was maintained by continuous injection of pancuronium bromide (Pavulon,
0.08 mg · kg
1 · h
1) in lactated
Ringer solution. In parallel, the animal received a constant perfusion
of 5% glucose (6-12 ml/h). Heart rate, end tidal CO2, and
reactions to cutaneous stimuli were monitored to ensure a proper degree
of analgesia.
Extracellular recordings of single and multiunits were obtained
simultaneously in areas V1 and V2 with two tungsten-in-glass microelectrodes (Merrill and Ainsworth 1972). For each
electrode, recorded sites were spaced apart by 80 or 100 µm in a
track. At each recorded site, single- and multiunit activities were
separated by window discriminators. TTL Pulses from the window
discriminators were acquired through a 1401 interface (CED) for on- and
off-line analysis using the software package Spike2 (CED).
Visual stimulation was produced by an optic bench and consisted of bars or spots that were flashed or moved across the receptive field of the recorded cells. When a moving bar was used as stimulus, the velocity was usually of 1°/s, the movement amplitude was between 3 and 6°, and a pause of 3 s separated the movement in one direction and its reverse. When the stimulus was flashed, its size was adjusted to cover at least partially the receptive field centers of both recorded cells; the shutter was kept open for 3 s and closed for 3 s. The color and orientation of the stimulus were adjusted to optimize the responses at both recording sites. When color preferences differed, the color of the stimulus was chosen as to give responses at each recording site. When orientation preferences differed, the stimulus orientation was set at an intermediate value between the two preferred orientations.
Computation and fitting of CCHs
CCHs were computed using the occurrences of spikes in the V1
neuron as trigger for the averaging. Thus time 0 in a CCH
represents the time of occurrence of an action potential in the cell
recorded in V1, and a positively displaced peak could indicate that the V2 cell was driven by the one recorded in V1. For computation and
fitting of CCHs, we used the procedures described in Nowak et
al. (1995b); these procedures are summarized briefly here. To
reveal the temporal interactions in their different ranges, the CCHs
were calculated with different time resolutions (5-ms binwidth and
window width of ±2.5 s and ±0.5 s; 1- or 2-ms binwidth and window
width of ±0.1 s). CCHs were normalized by the binwidth and by the
number of reference spikes, to give an ordinate in V2 spikes per second
per V1 spike (Abeles 1982b
).
A shift predictor correction procedure (Perkel et al.
1967) was used to separate the features of the CCHs that are
related to interactions of neuronal origin from those resulting from
the coactivation of the recorded cell by the visual stimulus (cf. Figs.
1 and
2). The shift
predictor corresponds to a CCH for which the occurrence times of the
action potentials in the V2 cell have been shifted by one stimulus
period with respect to those in V1. Given the long duration of the
stimulus period, the shifted CCH cannot contain features related to
neuronal interactions (neuronal interactions produce effects on a
shorter time scale: synaptic transmission takes place in the
millisecond time range; "secondary effects" that can contribute
to the CCH shape (Moore et al. 1970
), such as bursting
activities, display a time range that rarely outlasts a few hundred
milliseconds). The shift predictor was subtracted from the raw CCH to
reveal interactions of neuronal origin in isolation in the
"subtracted CCH." In the absence of interaction of neuronal
origin, the subtracted CCH appears flat (Fig. 1E). Another
CCH, called the "side peak," was obtained by subtracting two
adjacent shift predictors (1 with a 1-stimulus period shift, the 2nd
with a 2-stimulus periods shift). The side peak was used to determine
the noisiness resulting from the subtraction procedure and from the
variability of neuronal activity from one stimulation cycle to the
next.
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Quantitative analysis was done by fitting Gaussian curves to the peaks
in the subtracted CCH. The significance of the fitted structure was
determined by comparing its height with the height of the bins in the
side peak, recalculated to have a binwidth identical to the half-width
of the Gaussian fit (Nowak et al. 1995b). For the
significant peaks (Z score >3) (see Melssen and Epping 1987
), the following parameters were extracted from the fitted Gaussian: peak width, peak position, peak area, peak height, and
percentage engaged spikes (PES). The peak width was measured at the
half-height of the curve fitted to the peak. The peak position and
height were defined by the center and height of the Gaussian. The PES
is the ratio of the peak area (P) over the area of the shift
predictor below the peak (S) plus that of the peak
[PES = 100 P/(P + S)]. It
expresses the proportion of correlated spikes with respect to the total
number of spikes present in a time window corresponding to the width of
the subtracted CCH peak. In case the presence of more than one peak was
suspected in the CCH, the goodness of fit was compared for one versus
two fitted Gaussians. The parameters listed above then were extracted
from each of the Gaussian curves. The shape of the majority of broad
peaks (H peaks) clearly departs from a Gaussian. Instead it displays an
exponential shape (for example, Fig.
3C). For these cases, the
fitted curve corresponds to a smoothed version of the broad peaks (3 bins running boxcar algorithm, usually 10 iterations). The significance
level is given by the Z score calculated for the highest bin
(binwidth, 5 ms) in the CCH. The peak height corresponded to the
highest bin of the smoothed version of the peak, the peak width to the width at half-height.
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For single-unit recordings, a minimal number of spikes is required to produce a significant CCH peak, i.e., a peak that stands above the noise level determined by the side peak. Below this minimum number of spikes, it becomes impossible to decide whether the CCH is flat or whether it could contain a peak. To evaluate this minimum number of spikes, we took single-unit CCHs presenting a significant peak, divided the corresponding recording period into smaller epochs (slices), and recalculated the CCH for each epoch. The slicing reduced the number of spikes available, therefore decreasing the signal-to-noise ratio of the peak versus the CCH baseline. The procedure was repeated until the peak could not be detected as significant by the fitting program. In these conditions, the CCHs of different slices may appear as flat, although a peak was present in the complete run. An additional factor that we took into account is the width of the shift predictor that gives an indication of the grouping of the spikes due to the visual stimulation. We calculated a "decision index," which is the product of the spike counts in the two channels divided by the width of the shift predictor (in milliseconds). This procedure, applied to 11 CCHs, showed that significant peaks cannot be detected anymore when this index was <100. This corresponds to 700 spikes from each unit for a 5-s-wide shift predictor peak or 300 spikes for a 1-s-wide shift predictor peak. Therefore whenever a single-unit CCH did not present a peak, we calculated the decision index. When this index was >100, the CCH was considered as flat. When it was <100, the CCH was considered as undecided and excluded from the sample.
The other problem we faced was that of instability in the firing rate
of some neurons. Such instability violated the stationarity rule for
random point processes (Cox and Lewis 1966) that is a prerequisite for averaging operations such as the calculation of CCHs.
Indices of instability were a wavy baseline and/or asymmetric side
peaks. We also checked for stability of recording by calculating rate
histograms (mean firing rate per stimulus over stimulus number). This
instability could be due to transient bursts of activity or, for
multiunit recordings, to changes in the composition of the contributing
units. By slicing the runs, it has been possible to recover stable
portions of initially instable recordings for 18 single-unit (su) pairs
and 55 multiunit (mu) pairs. In other cases, despite slicing, the CCHs
retained traces of instability. Due to instability, 131 mu CCHs have
been excluded from further analysis. Due to the instability or to
insufficient spike count, 198 su CCHs have been excluded from further analysis.
To separate the influence of the visual stimulation and that of the spontaneous activity on the features of the CCHs, we proceeded as follow: peristimulus time histograms (PSTHs) were calculated for both V1 and V2 cells from which we determined the time during which both neurons were activated by the stimulus. The action potentials from the V1 neurons that occurred during that period were isolated and used to calculate a CCH restricted to the visual response. The same procedure was used to calculate CCH obtained under spontaneous activity only: the action potentials in the V1 cell were isolated for a period during which neither cells were visually responsive as shown by the PSTHs. The baseline for the CCH calculated under spontaneous activity only is at 0 because the shift predictor also was subtracted in these cases. Because it is often difficult, with a flash response, to determine whether the activity after the transient response corresponds to a sustained response or to spontaneous activity, this analysis has been restricted to the moving bar stimuli.
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RESULTS |
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Recordings from 295 pairs of sites using moving bars as stimuli and 134 pairs of sites using flashes were obtained in eight monkeys. Both moving bars and flashes have been used for 132 pairs of sites.
Both su and mu activities were recorded at each site. CCHs were calculated either for pairs of su or for pairs of mu. Some of the CCHs were discarded from further analysis due to instability of the recording or, for some su recordings, to an insufficient number of spikes (see METHODS section). The database on which the present paper is based is composed of 175 su and 205 mu CCHs computed with moving bars and 56 su CCHs and 93 mu CCHs computed with flashes as stimuli.
The peak resulting from the coactivation of the cells by the visual stimulus was isolated by calculating the shift predictor. The shift predictor, in turn, was subtracted from the raw CCH to yield the subtracted (or net) CCH in which interactions of neuronal origin can be seen in isolation.
The shift predictor technique commonly is used in the case of moving
stimuli that produce rounded peaks in the CCH. However, flashed stimuli
produced sharp peaks in the CCHs. It was not clear whether the shift
predictor method could remove all the stimulus induced correlation in
these conditions (cf. Melssen and Epping 1987). Figure 1
shows that flat CCHs can be obtained with flashes: despite the
transience of the response (visible in the PSTHs, Fig. 1, A
and B) and the resulting sharp peak in the raw CCH (Fig. 1C), the shift predictor technique removed all
stimulus-induced peaks in the subtracted CCH (Fig. 1E),
which therefore appears as flat (as the overwhelming majority of su
cases with flashes).
A complementary control is presented in Fig. 2 for a pair of mu recordings. The flashing stimuli evoked responses that began with a transient (Fig. 2A, 1 and 2) while the CCH obtained for this pair presented a narrow peak. To determine whether the narrow peak was related to the transient response, we restricted the calculation of the CCH to two periods of the visual response. The first corresponds to the first second of the response, including the transient. The corresponding subtracted CCH contains a narrow peak above a broader pedestal (Fig. 2B2). However, the narrow peak also appears when the CCH (Fig. 2C2) is calculated for the sustained period of the visual response (1-3 s in Fig. 2A, 1 and 2) while the shift predictor appears flat for this time resolution (Fig. 2C1). These examples show that the presence of a peak in the CCHs is not necessarily associated with the presence of a transient in the flash response.
Three types of CCH peaks
Examples of subtracted CCHs computed between neurons in areas V1 and V2 appear in Fig. 3. All cases except Fig. 3F correspond to paired mu recordings. CCHs calculated from responses to a moving light bar are shown in Fig. 3, A and C. Other cases correspond to CCHs obtained with flashed bars. Figure 3 illustrates the different widths of peaks observed (note the different time scales) and the fact that peaks of different width can combine (Fig. 3, D-F), even for pairs of su recordings (Fig. 3F).
In cat visual cortex, CCH peaks obtained from recordings performed in
different cortical areas can be grouped in three different classes
according to their width at half-height (Nelson et al. 1992; Nowak et al. 1995b
). The distribution
histogram of the log values of the peak width at half-height, shown on
Fig. 4A, indicates that a
tripartite distribution of peak width exists in the monkey as well.
This histogram contains data from mu and su recordings with flashed or
moving stimuli. Three modes and two gaps are visible. One gap
corresponds to a value of 16 ms (integer value of 101.2)
and the other to a value of 178 ms (integer value of
102.25). The peak width distributions are presented
separately for moving bars and flashed stimuli in Fig. 4, B
and C.
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Because of similarity with data obtained in cat visual cortex, the three classes of peaks have been given the same names. T peaks correspond to the class of narrow peaks (<16 ms wide), C peaks to peaks of intermediate width (16-178 ms), and the widest peaks (>178 ms) are grouped in the H category (Table 1). Within each class, the peak width tends to be broader with moving bars than with flashes, but this does not reach significance in paired tests (Wilcoxon paired test, P > 0.15 in all the cases).
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The relationship between peak width with moving bars and peak width with flashed stimuli for the pairs of units for which both types of stimuli were used is presented in Fig. 4D for C peaks and Fig. 4E for H peaks (the sample was too small in the case of T peaks). In the case of C peaks, there is a good correlation in most cases (r = 0.85 for peak width <120 ms with moving bars). No relationship between the widths measured for flashes and moving bars appears to hold for H peaks.
Incidence
The encounter rate of T, C, and H peaks for different stimuli is summarized in Fig. 5 and Table 1. Figure 5A, 1 and 2, presents the incidences of different peaks when the stimulus was a moving or a flashed bar. Most subtracted CCHs computed from su activities were flat. Under both stimulus conditions, the peaks that were most often encountered were of the H category. T peaks were only rarely observed. C peaks appeared with an intermediate probability. Note that the incidence rates of different peaks add up to >100%. This is due to the combination of peaks of different widths that often occurred in a single CCH (Figs. 3, D-F, and 12B).
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Comparing the incidence rates of Fig. 5A, 1 and
2, would suggest that flashed stimuli tend to produce more
CCHs with peaks than moving bars. To determine whether this is the
case, comparison must be restricted to the sample for which both moving
bars and flashes were used. The corresponding incidences are shown in
Fig. 5B1 for su and in Fig. 5B2 for mu
recordings. The only statistically significant difference was observed
for H peaks in mu recordings that are more frequent for flashed than
for moving stimuli (P = 0.001; 2 test).
Other peak types showed a similar trend, but the differences were not significant.
Peak position
We next wanted to test whether neural interactions revealed by the CCH peaks are such that spikes in V2 neurons tend to follow spikes in V1, as suggested by a serial model of organization, or whether the CCH peaks are usually centered at zero, like in cat cortex, meaning that the two sites show correlated discharges with no phase lag or phase lead.
The distribution of the peak positions for H peaks is shown in Fig. 6 and Table 1. For moving bar stimulation (Fig. 6A1), the peak positions are distributed symmetrically around time 0, which corresponds to the mode of the distribution. The median of the position for H peaks is not different from 0 (1 sample sign test, P = 0.8 for both su and mu). With flashes (Fig. 6A2), although the distribution is not symmetrical around 0, the median peak position does not significantly differ from 0 (P = 0.10 for su and P = 0.17 for mu).
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The distributions of peak positions are very broad in Fig. 6A, 1 and 2. One could argue that the tails of the distributions correspond to peaks that signal serial connections between the groups of recorded cells. However, the distribution of peak width also appears very broad (Fig. 4). Therefore to detect displaced peaks, it is necessary to normalize the position of the peaks with respect to their widths. For this, we calculated the displacement index (DI), which indicates whether the central part of the peak contains the origin of the time axis of the CCH: DI = peak position/0.5 * (peak width).
When this index takes a value between 1 and +1, it indicates that the
upper half of the CCH peak overlaps with the origin of time (as
illustrated in all examples of H peaks in Fig. 3). Such peaks are
considered signs of synchronized activity. It is clear that practically
all H peaks contain the origin of time within their upper half (Fig.
6B, 1 and 2), indicating that H peaks correspond
to synchronized activity within a time scale of hundred of milliseconds.
Figure 6C is a scatter plot of the peak positions for H peaks that were visible with both flashes and moving bars. The peak position tended to be maintained with both stimuli, but the correlation was not significant (mu: r = 0.352, P = 0.06).
Figure 7A, 1 and 2, shows the distributions of peak positions for C peaks. They are distributed symmetrically around the origin of time. For both stimulus conditions, the bulk of the peak positions is between ±30 ms. The medians (Table 1) do not differ significantly from 0 (moving bar: P = 0.34 for su and 0.23 for mu; flash: P = 0.51 for su, P > 0.9 for mu).
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In Fig. 7B, 1 and 2, are presented the distributions of displacement index for C peaks. Similarly to what has been obtained for H peaks, practically all C peaks overlap the origin of time with their upper half and therefore are considered to represent synchronization of activity within a time scale of tens of milliseconds.
The scatter plot in Fig. 7C shows that when C peaks were obtained with both flashed and moving bars, they tended to maintain a similar position (r = 0.527, P = 0.02).
The distributions of positions for T peaks are shown in Fig. 8A, 1 and 2. Only four T peaks have been obtained with flashes; this is too small a sample for any conclusive statement. It is worth mentioning, however, that two of these peaks display considerably long latencies (1 is illustrated in Fig. 3D). With moving bars, it can be seen that the majority of T peaks display positive latencies. However, presumably as a result of the small sample, the median peak position is not significantly different from 0 (P = 0.12 for mu).
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With flashes, two of four T peaks present a displacement index larger than one, in keeping with a drive of the V2 neurons by the one simultaneously recorded in V1 (Fig. 8B2). With moving bars, the origin of time is contained in the upper half of the T peaks in the majority of cases (6 of 8 cases, Fig. 8B1).
If we assume that the CCH peaks that overlap the origin of time with their upper half reflect synchronization of activities, then synchronization characterizes the temporal interactions for the majority of neurons in areas V1 and V2, when their activities are correlated by mechanisms of neuronal origin.
Peak position and visual latency
Because flashes were used as stimuli in a number of cases, it has been possible to determine to what extent the functional connectivity, which presumably is revealed by the position of the CCH peak, is related to the difference in visual latency between V1 and V2 cells, which reveals their activation orders. In other words, if the visual latencies of the two recorded neurons differ by N ms, is the peak of the CCH displaced by the same amount?
Visual latencies were determined as described in Nowak et al.
(1995a) for the ON and OFF responses to
the flash. The latency of the V1 cell was subtracted from that of the
V2 cell. When this latency difference takes a negative value, it
indicates that the V2 cell was activated before the V1 cell recorded at
the same time.
The relationship between latency difference and peak position in the case of T peaks is examined in Fig. 9A, 1 and 2. The sample size is not large enough for a statistical test, but it is interesting to notice the similar values obtained in several cases.
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Figure 9B, 1 and 2, shows the relationship between latency difference and CCH peak position for the C peaks. For mu CCHs, a weak but significant correlation is observed for ON responses (r = 0.404, P = 0.04). However, in a mu recording, the cell that provides the earliest response determines the latency of the PSTH but does not necessarily contribute to the CCH peak. su cases should give a more precise measurement of the relationship between visual response latency and CCH peak position. Indeed, there appears to be a good correlation between these two variables when su only are tested (Fig. 9B1). The correlation coefficient was 0.78 in that case (P = 0.02).
Figure 9C, 1 and 2, illustrates the relationship between peak position and latency difference in the case of H peaks. There were no significant correlations for either su or mu recordings.
In summary, these data indicate that, at least for the C and presumably the T peaks, the position of the peak in a CCH is linked to the difference of response latencies of the recorded cells. Although peaks contained the origin of time in the majority of the cases and were considered by this criterion to represent synchronized activity, the peak position of the CCH takes a value that is related to the order of activation of the recorded cells. This apparent contradiction possibly results from the fact that the delay that takes place in a serial connection is likely to be smaller that the width of a CCH peak (see DISCUSSION).
Coupling strength
The strength of the CCH peaks was quantified by three measures: the peak height; the peak area, which is the number of spikes present in a peak per trigger spike; and the PES (percent engaged spikes), which expresses the number of correlated spikes over the total number of spikes (both correlated and uncorrelated) that appeared during a time window equal to the full width of the peak. Coupling strength data are summarized in Fig. 10 and Table 2.
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Comparing su with mu CCH peaks shows that both peak height (Fig. 10A, 1 and 2) and area (Fig. 10B, 1 and 2) are higher for mu than for su recordings (Mann-Whitney U test, P < 0.05 in all the cases except for C with flash: P = 0.1; T peaks have not been tested due to small sample size). This is to be expected because, on average, more than one pair of units contribute to the peak obtained in a mu recording: by making the ratio of the median values of the peak areas, it appears that the number of pairs would range between 1.6 (H peaks, moving bar) and 3.6 (H peaks, flash). However, not all neurons contributing to a mu recording appear to be synchronized: this can be deduced by comparing the ratio presented above with the ratio of the number of mu spikes over su spikes accumulated during a recording, which gives the number of neurons contributing to a mu recording. This ratio is close to 8 (7.7 for V1, 8.25 for V2).
The proportion of spikes that are engaged in a correlation of neuronal origin represents only a small fraction of the total number of spikes. This is revealed by the percentage of engaged spikes (Fig. 10C, 1 and 2) that takes median values between 10 and 17% for su pairs, depending on the stimulus and peak types, and between 6 and 13% for mu pairs (Table 2). The PES is lower for mu than for su (Mann-Whitney U test, P < 0.005 for all types of peaks). This results from the fact that in a mu recording, not all the cells contribute to the peak but all contribute to the shift predictor.
Comparing coupling strength between different types of peaks does not show significant differences between the heights of C and H peaks. Peak areas of C and H peaks differ mainly because of the differences in peak widths. No significant differences are observed between the PES of the three peak types.
Comparing coupling strength between flashed and moving stimuli indicates how it is influenced by the type of stimulus used. There was no effect on the peak area or peak height of H peaks. For C peaks, the peak area and peak height appeared different for flashed bars and moving bars (P = 0.01, Wilcoxon paired test), suggesting that the absolute coupling strength is larger with flashes than with moving stimulus. The relative coupling strength, measured by the PES, was larger for flashed compared with moving bars for both C peaks (P = 0.005) and H peaks (P = 0.0002). For H peaks, the difference in PES value must be due to the smaller response generated by flashed stimuli compared with moving bars because the stimulus type did not influence H peak areas.
Receptive field properties
No significant effects on encounter rates were observed with
respect to the presence of orientation selectivity, to the differences in optimal orientation for pairs of sites with oriented receptive field, or to differences in color selectivity. This possibly is related
to the small sample of T peaks, the incidence of which showed the
strongest dependency on receptive field properties in earlier studies
(Nelson et al. 1992; Nowak et al. 1995b
).
We only found an effect of the respective positions of the receptive
fields of the recorded cells. Altogether, the probability to obtain a
significant correlation, whatever the peak type, was significantly
higher when receptive fields overlapped (incidence of nonflat CCHs for
mu recordings: 65.4%, vs. 45.9% for nonoverlapping receptive fields,
P = 0.008 in a 2 test) or when they were
separated by <2° (incidence of nonflat CCHs for mu recordings:
63.9%, vs. 31.1% for receptive fields separations between 2 and 5 degrees, P = 0.0001). The effects of receptive fields
separation and overlap are presented separately for C and H peaks in
Fig. 11. There was a higher encounter
rate of C peaks when the receptive fields overlapped, totally or
partially (P = 0.02; Fig. 11B). A similar
effect was observed in the case of H peaks: although not significant
(P = 0.1), there was a tendency for sites with
overlapping receptive fields to be coupled more often by H peaks (Fig.
11B). Also, sites with receptive field center separations
<2° had a higher encounter rate of H peaks than sites with
separations above this value (P = 0.001, Fig.
11A).
|
CCH peaks and visual drive
The effects of the visual stimulation on the probability to observe a peak and on its strength were examined by comparing CCHs calculated for a period restricted to the visual response of the cell with CCHs calculated for a period restricted to the spontaneous activity. Figure 12 illustrates this with an example representative of the general tendency observed: the responses of the neurons to the moving bar are represented by the PSTHs in Fig. 12A, a and b. The periods of recorded activity of the neurons are divided into a visual drive period (VD) and a spontaneous activity period (SA) and the CCHs displayed for each of the two periods in Fig. 12, B and C. Figure 12B shows that during the visual response, the sites are synchronized by a H and a C peak. During spontaneous activity (Fig. 12C), the C peak is absent and the size of the H peak is increased.
|
Three types of stimulus dependency were observed: some peaks were
present only during the visual response and absent during the
spontaneous activity, like the C peak of Fig. 12. A minority of peaks
showed the opposite behavior. Finally some peaks were present during
both the visual drive and the spontaneous activity, like the H peak of
Fig. 12. The incidence of peaks displaying one of these three behaviors
is summarized in Table 3 and in Fig. 13Aa for mu and Fig.
13Ab for su pairs.1 Fifty-seven
percent of the C peaks were present only during the visual response and
absent during spontaneous activity, whereas 70% of the mu H peaks that
were present with the visual stimulation remained during spontaneous
activity. With respect to their stimulus dependency, H and C peaks
differed significantly (P = 0.002 in a 2
test on pooled su and mu).
|
|
In 28 cases, the original CCH consisted of combination of a C and a H peak (as in Fig. 3, E and F). We examined these cases to determine whether peaks switch type depending on the presence of a visual stimulation. We found such switching in only two cases. The most often encountered pattern (12/28) consisted in a H peak being present during both visual drive and spontaneous activity and a C peak present during visual stimulation only (as in Fig. 12).
C and H peaks also differed with respect to the effect of the visual stimulation on their coupling strengths. To assess the changes in coupling strength, we computed a coupling strength ratio (CSR), which is the ratio of the peak height measured during visual drive over the sum of the peak height during spontaneous activity and visual drive [CSR = PHvd/(PHvd + PHsa)]. The index is 0 for peaks present only during spontaneous activity; it is 1 for peaks present only during visual drive; and a value of 0.5 corresponds to a peak height unchanged in both conditions. The data are summarized in Fig. 13Ba for C peaks and 13Bb for H peaks. Considering only the C peaks that were present with both spontaneous activity and visual drive (0 < CSR < 1, 40.7% of the mu cases), a tendency can be observed for the CSR to be >0.5 (mean CSR = 0.59, Fig. 13Ba). Hence, the height of the C peaks obtained with the visual response was larger on average than that for the spontaneous activity period (Wilcoxon paired test, P = 0.03 for mu).
H peaks that were present during both the visual response and the spontaneous activity period showed an opposite behavior (mean CSR = 0.42, Fig. 13Ba), and the height of the H peaks obtained during the period of visual response was smaller than the one obtained during the spontaneous activity (P = 0.007 for mu). Importantly, there was no correlation between the CSR and either the strength of the visual response or the level of spontaneous activity.
In summary, C peaks appear to be strongly associated to the presence of a visual stimulus, both in terms of incidence and coupling strength, whereas H peaks, although they tend to remain during both spontaneous activity and visual response, nevertheless appear stronger during spontaneous activity.
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DISCUSSION |
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Three types of temporal correlation between areas V1 and V2 of the macaque
The cross-correlation method reveals the temporal coherence in the
firing of neurons. Two different types of temporal coherence must be
distinguished (Aertsen and Arndt 1993; Dickson
and Gerstein 1974
; Perkel et al. 1967
). The
first one, called "stimulus-locked temporal coherence," results
from the coactivation of the two recorded cells by the stimulation and
is not directly related to neuronal interactions. It appears in
isolation in the shift predictor (Figs. 1 and 2).
The second type of temporal coherence is the "neurally related temporal coherence," which we referred also to as "correlation of neuronal origin." This type of temporal coherence does not need a stimulus to be generated, as it can be observed with spontaneous activity (Fig. 12C). When visual stimulation is used, the neurally related temporal coherence needs to be distinguished from the stimulus-locked temporal coherence. The shift predictor allows such a distinction and its subtraction from the raw CCH shows in the subtracted CCH the temporal coherence of neuronal origin in isolation (Figs. 1 and 2). Although, in terms of coupling strength, it represents usually <20% of the stimulus-locked coherence (Fig. 10), the neurally related temporal coherence has received much of the interest of the studies on neuronal interaction and synchronization; our study deals with it as well.
The results of the present study show that the activities of neurons
simultaneously recorded in areas V1 and V2 of the macaque monkey are
correlated by mechanisms of neuronal origin in ~10% of the cases (su
pairs). These correlations are revealed in the CCHs by peaks the widths
of which are distributed in a trimodal fashion (T, C, and H peaks, Fig.
4). Three modes of neuronal correlation have been reported previously
in the cat for the interactions between areas 17 and 18 of the same
hemisphere (Nelson et al. 1992) and between areas 17 of
both hemispheres (Nowak et al. 1995b
). A bipartite or
tripartite distribution of peak width also has been reported in several
cross-correlation studies concerning neurons recorded within the same
cortical area (Aertsen et al. 1991
; Eggermont
1992
; Gochin et al. 1991
; Hata et al.
1991
; Krüger and Mayer 1990
; Murphy
et al. 1985
; Swadlow et al. 1998
).
The reason why CCH peaks have different widths might be related to
different types and amount of burstiness. This is supported by the fact
that the autocorrelation histograms (ACHs) calculated for the recorded
units always showed features that were apparent in the CCH. In general,
when an H peak was observed in the CCH, there was also an H-like
structure in the ACH of at least one of the two recorded units. A
similar observation holds for C peaks (see also Gochin et al.
1991; Nowak et al. 1995b
). Bursts lasting 10 ms
to several hundred milliseconds, presumably resulting from network
properties, have been identified in cat cortex (Bowman et al.
1995
; DeBusk et al. 1997
; Legendy and
Salcman 1985
; Noda and Adey 1970
). It has been
shown that compensating for the presence of these bursts results in a
narrowing of the CCH peaks (Eggermont and Smith 1996
;
Eggermont et al. 1993
).
The encounter rate for T peaks in monkey (<1% in su runs; Fig. 5) is
much lower than in cat (11% for CCHs computed between areas 17 and 18, 17% between areas 17 of opposite cortical hemispheres). T peaks in the
cat show the strongest dependency on the receptive field separation and
properties (Nelson et al. 1992; Nowak et al.
1995b
) and appear to be generated by the direct reciprocal connections between the two recorded sites (Munk et al.
1995
). It is possible that the low encounter rate of T peaks in
the monkey areas V1 and V2 is related to the highly modular nature of
their connections, which makes recording from directly interconnected neurons a more difficult task than in the cat cortex. It also should be
noted that narrow CCH peaks seem to be less common for interareal than
for intraareal interactions (Cardoso de Oliveira et al.
1997
; Roe and Ts'o 1997
).
A number of studies have described a fourth type of synchronization,
the synchronization of gamma range (30-80 Hz) oscillations. In cat
visual cortex, such oscillatory synchronization has been shown in the
local field potential and in mu recordings within cat area 17 (Eckhorn et al. 1988; Gray et al. 1989
)
as well as between different cortical areas (Eckhorn et al.
1988
; Engel et al. 1991a
,b
; Nowak et al.
1995b
). In the monkey cortex, oscillatory activity and
synchronization has been demonstrated within visual and sensorimotor
areas in su and mu activities as well as in the local field potential
(Eckhorn et al. 1993
; Frien et al. 1994
; Kreiter and Singer 1992
; Livingstone
1996
; Murthy and Fetz 1992
; Rougeul et
al. 1979
; Sanes and Donoghue 1993
).
We did not observe oscillatory synchronization, except in a single case
(of >500 CCHs). We also checked whether oscillatory firing was present
in su recordings by computing ACHs for >200 su and found only a single
case of gamma range oscillation. This very rare occurrence could be
related to the fact that we computed ACHs and CCHs over a large number
of repetitions of the stimulus to get a large enough signal-to-noise
ratio. Such averaging might lead to the waning of the oscillatory
activity, as reported by Kreiter and Singer (1992) and
Livingstone (1996)
in their studies from monkey visual
cortex. However, calculating CCHs on the basis of one or a few stimulus
repeats was unpractical in our case because it resulted in a
signal-to-noise ratio that was too low to allow the detection of
significant interactions (see METHODS).
Beside differences in anesthesia and visual stimuli, species difference
might constitute a possible explanation of our failure to record
synchronized oscillation between macaque areas V1 and V2. Most of the
reports on synchronized gamma range activity were obtained in the cat
(e.g., Eckhorn et al. 1988; Gray et al.
1989
), whereas its presence in monkey proved to be more
controversial (cf. Tovee and Rolls 1992
; Young et
al. 1992
). It is noteworthy that in our preceding study on
cortico-cortical interactions in the cat (Nowak et al.
1995b
), 20% of the significant CCH peaks corresponded to
synchronized gamma range oscillations. Although for the present study
we used the same protocols for animal preparation, recording, visual
stimulation, data analysis, and, in four cases (not reported in this
study), the same anesthetics, we found almost no synchronized oscillations.
Synchronization in a serially organized system
The monkey visual system classically is thought as being organized
in a serial manner. Anatomic studies showed that in the primate,
contrary to other orders, the LGN input is focused onto area V1, and
functional studies based on inactivation indeed showed that activity in
area V2 is entirely dependent on the activity coming from V1 (reviewed
in Bullier et al. 1994). One therefore would expect that
neurally correlated activity in V1 and V2 displays signs of this organization.
T peaks that do not contain the origin of time in their upper half
(displacement index > 1, Fig. 8B) could be considered
as representing serial connections (either mono- or polysynaptic). In
this study, such peaks have been observed in only four cases in a total
of >500 CCHs. They were displaced in the positive direction, indicating a possible connection from V1 to V2. Two T peaks showed exceptionally high values of the peak position (Fig. 8A2).
These two peaks remained when the run was sliced into smaller periods and are therefore unlikely to represent artifacts. They may represent instances of synfire chains (Abeles et al. 1993;
Vaadia et al. 1991
).
At the population level, the median peak position for C and H peaks in
the present study is not significantly different from 0. In addition,
the upper half of the CCH peaks overlaps the origin of time in 94% of
the cases (all peaks together). Similarly to what has been reported
previously in the cat (Nelson et al. 1992; Nowak
et al. 1995b
), this indicates that the majority of neurons in
macaque areas V1 and V2 synchronize their activities, when these are
correlated by mechanisms of neuronal origin.
For C peaks, however, a correlation was observed between the position of the peak on the time axis and the difference in visual latencies to flashed stimuli (Fig. 9). This suggests that the position of a C peak is somehow related to the respective order of activation of the V1 and V2 neurons that are correlated.
There is some ambiguity in stating that C peaks represent instances of
synchronized activity on the one hand and that they reflect the order
of activation of the cells on the other. Measurements of visual
response latencies show that, on average, V2 neurons are activated 10 ms later than neurons in area V1 (Raiguel et al. 1989;
Nowak et al. 1995a
) while the median of the axonal delay between these two areas is ~2 ms (F.-M. Huppé, P. Girard, and J. Bullier, unpublished data). This suggests that the
latency of the serial links between areas V1 and V2 is at least one
order of magnitude smaller than the median width for C peaks. It is therefore possible that burstiness, which may account for their width,
masks the presence of a serial link (see also Creutzfeldt et al.
1980
). Nevertheless, if the C peaks that are not exactly centered on the origin of time do correspond to hidden serial connections, it has to be noted that similar numbers of these are
displaced to the right or to the left. In that respect, the position of
a C peak on the time axis does not conform with a serial
organization for areas V1 and V2.
Origin of synchronization and the effects of visual stimulation
Neuronal synchronization commonly is observed in cortex, and areas
V1 and V2 are no exceptions to this rule. The occurrence of
synchronization between areas V1 and V2 is not incompatible with their
functional and anatomic relationship if one considers the temporal
aspects of the visual responses: first, although visual response
latencies in V1 are shorter than in V2, the overlap of latencies is so
large that >40% of V2 cells already have started responding when 50%
of V1 cells have not responded (Nowak et al. 1995a).
Second, when a neuron is activated by a visual stimulus, its response
does not stop after its first spike. Instead it continues to fire for a
prolonged length of time in such a way that there is a large overlap
between the periods of responses of neurons in V1 and V2 (see Figs. 1,
2, and 12). Altogether, there is a large temporal window during which
neurons in both areas are simultaneously active. Then if mechanisms
that can sustain it are at work, these activities might become synchronized.
Two mechanisms can explain the neurally related synchronization of
neuronal activities. The first one is the common input hypothesis
(Perkel et al. 1967), which postulates that neurons are
synchronized by the common inputs they receive from neurons with
bifurcating axons terminating in both structures. It is important to
realize that, with the exception of the lateral geniculate nucleus,
almost all the structures that project to area V1 also project to V2
and that some connections are made by bifurcating axons (Kennedy
and Bullier 1985
; Rockland and Drash 1996
;
Rockland et al. 1994
). This concerns several subcortical
structures, like the pulvinar and the claustrum, and also a number of
areas that project in a feedback manner like areas MT and V4.
The second mechanism that can explain the presence of synchronized
activity is of a more subtle nature and has been described in modeling
studies (Arnoldi and Brauer 1996; Bush and
Douglas 1991
; Bush and Sejnowski 1996
;
Hansel and Sompolinski 1996
; Koch and Schuster
1992
; König and Schillen 1991
). These
studies have shown that two groups of neurons (with or without
pacemaker properties) connected by axons having a finite conduction
delay nevertheless can synchronize their activities. This is the
consequence of the divergent nature of the connectivity, together with
a prominent role played by inhibitory interneurons. This constitutes an
emergent property of the cortical network.
Whether one or both of these mechanisms can explain the synchronization
between areas V1 and V2 in the monkey cannot be determined at present.
However, our previous study on interhemispheric synchronization in the
cat (Munk et al. 1995) provides some indications. This study was based on the effect of cortical lesions and the transection of the callosal connections on the different types of neuronal correlation. We concluded that T peaks result mainly from the direct
reciprocal connections between the two cortical areas. C peaks appeared
to be reduced strongly in occurrence and strength after lesion of areas
providing monosynaptic feedback inputs, which led us to conclude that
this type of correlation at least is facilitated by common inputs from
higher cortical areas. The fact that C peaks are observed even between
neurons with nonoverlapping receptive fields (Nelson et al.
1992
; Nowak et al. 1995b
; this study) is
consistent with the loose retinotopic organization of feedback
connections (Salin and Bullier 1995
). The H type
correlation appeared to involve both monosynaptic and polysynaptic
corticocortical connections.
The influence of visual stimulation might help to determine
further the origin of cortical synchronization. In the present study,
we observed that 70% of the H peaks that are present during the visual
response still are present during spontaneous activity. On average,
these peaks were stronger during the spontaneous activity than during
the visual response (Figs. 12 and 13). In unanesthetized cat, broad
peaks appear during sleep in both the CCH and the ACH of cortical
neurons (Noda and Adey 1970) but disappear during waking. H peaks also present similarities with the broad CCH peaks observed by Amzica and Steriade (1995)
that appear
during the slow cortical oscillations associated with sleep
(Steriade et al. 1993
). Together with a lack of obvious
dependency on receptive field properties (Nelson et al.
1992
; Nowak et al. 1995b
; this study), this
suggests that at least some of the H peaks are related to the
sleep/wake cycle of the animal. The width of H peaks may reflect the
temporal dispersion of activity in the polysynaptic network involving
both the cortex and the thalamus (Amzica and Steriade
1995
).
However, there was a number of cases for which H peaks were clearly
stronger during the visual response and, in ~30% of the cases, they
were absent during spontaneous activity (Fig. 13). Broad peaks, similar
to H peaks, also have been observed in awake behaving animals
performing tasks requiring a high level of attention (Aertsen et
al. 1991; Gochin et al. 1991
) and cannot,
therefore, be associated with sleep or anesthesia. This suggests that
there might be two different types of H peaks, one associated with
sleep or anesthesia, the other associated with sensory processing.
Their similarities in terms of width led us to group them together, but
they might differ with respect to other aspects that remain to be determined.
Contrary to the general tendency observed with H peaks, the majority of
C peaks appeared to be stronger during visual stimulation with >50%
of them being present only during this period. This indicates that
these peaks are associated with the processing of visual information.
In this respect, C peaks appear to be similar to the synchronized gamma
range oscillation that also appear preferentially during the visual
stimulation (Engel et al. 1991a,b
; Gray et al. 1989
; Livingstone 1996
; Nowak et al.
1995b
). Therefore C peaks may represent, at least for some of
them, the signature of common inputs provided by feed back connections,
which would be gated by the presence of visual stimulation.
Conclusion
It has been proposed that synchronization of neuronal activity
could solve the so-called binding problem (Abeles 1982a;
Damasio 1990
; Milner 1974
; Singer
and Gray 1995
; von der Marlsburg 1981
). The
plausibility of this proposal is supported by our results demonstrating
the presence of synchronization between two areas that otherwise, on
the basis of other evidences, have been proposed to be organized
serially. On the other hand, synchronization also could be considered
as the side effect of the functioning of the cortical network and might
not convey any specific information by itself (Bush and
Sejnowski 1996
; Gawne and Richmond 1993
;
Shadlen and Newsome 1994
). In any case, the presence of
synchronization between areas V1 and V2, together with previous
findings indicating a quasisimultaneity in their activations
(Bullier and Nowak 1995
), suggests that they are not
only two successive relay stations for visual information processing.
Instead, this indicates that neurons in areas V1 and V2 share common
neuronal influences in such a way that the processing that takes place
in area V1 is not independent from the one taking place in area V2.
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ACKNOWLEDGMENTS |
---|
We thank N. Chounlamountri for help during the experiments, P.-M. Chorrier for help with the mechanics, and C. Urquizar for help with the electronics.
This work was supported by Human Frontier Science Program Organizational Grant RG 55/94. M.H.J. Munk was supported by the Fyssen Foundation. L. G. Nowak was supported by a fellowship from the Ministère de la Recherche et de la Technologie and by a fellowship from the Fyssen foundation.
Present addresses: L. G. Nowak, Section of Neurobiology, Yale University School of Medicine, C303 Sterling Hall of Medicine, 333 Cedar St., New Haven, CT 06510; M.H.G. Munk, Max Planck Institute for Brain Research, Deutschordenstrasse 46, D 60528 Frankfurt/M, Germany; and A. C. James, Developmental Neurobiology RSBS ANU, GPO Box 475, Canberra, ACT 2601, Australia.
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FOOTNOTES |
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Address for reprint requests: J. Bullier, Cerveau et Cognition, Faculté de Médecine de Toulouse-Rangueil 133, route de Narbonne, 31062 Toulouse Cedex, France.
1 The sample size was too small for T peaks for statistical tests.
Received 13 November 1997; accepted in final form 4 November 1998.
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REFERENCES |
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