1Brain Sciences Center, Department of Veterans Affairs Medical Center, Minneapolis 55417; 2Department of Neuroscience, 3Department of Neurology, and 4Department of Psychiatry, University of Minnesota Medical School; and 5Cognitive Sciences Center, University of Minnesota, Minneapolis, Minnesota 55455
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ABSTRACT |
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Merchant, H.,
A. Battaglia-Mayer, and
A. P. Georgopoulos.
Effects of Optic Flow in Motor Cortex and Area 7a.
J. Neurophysiol. 86: 1937-1954, 2001.
Moving
visual stimuli were presented to behaving monkeys who fixated their
eyes and did not move their arm. The stimuli consisted of random dots
moving coherently in eight different kinds of motion (right, left, up,
downward, expansion, contraction, clockwise, and counterclockwise) and
were presented in 25 square patches on a liquid crystal display
projection screen. Neuronal activity in the arm area of the motor
cortex and area 7a was significantly influenced by the visual
stimulation, as assessed using an ANOVA. The percentage of cells with a
statistically significant effect of visual stimulation was 3 times
greater in area 7a (370/587, 63%) than in motor cortex (148/693,
21.4%). With respect to stimulus properties, its location and kind of
motion had differential effects on cell activity in the two areas.
Specifically, the percentage of cells with a significant stimulus
location effect was ~2.5 times higher in area 7a (311/370, 84%) than
in motor cortex (48/148, 32.4%), whereas the percentage of cells with
a significant stimulus motion effect was ~2 times higher in the motor
cortex (79/148, 53.4%) than in area 7a (102/370, 27.6%). We also
assessed the selectivity of responses to particular stimulus motions
using a Poisson train analysis and determined the percentage of cells that showed activation in only one stimulus condition. This percentage was 2 times higher in the motor cortex (73.7%) than in area 7a (37.7%). Of all kinds of stimulus motion tested, responses to expanding optic flow were the strongest in both cortical areas. Finally, we compared the activation of motor cortical cells during visual stimulation to that observed during force exertion in a center
out task. Of 514 cells analyzed for both the motor and
visual tasks, 388 (75.5%) showed a significant relation to either or
both tasks, as follows: 284/388 (73.2%) cells showed a significant
relation only to the motor task, 27/388 (7%) cells showed a
significant relation only to the visual task, whereas the remaining
77/388 (19.8%) cells showed significant relations to both tasks.
Therefore a total of 361/514 (70.2%) cells were related to the motor
task and 104/514 (20.2%) were related to the visual task. Finally,
with respect to receptive fields (RFs), there was no clear visual
receptive field structure in the motor cortical neuronal responses, in
contrast to area 7a where RFs were present and could be modulated by
the type of optic flow stimulus.
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INTRODUCTION |
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It is an essential aspect of
our interaction with the environment that we deal with objects in it
(i.e., reach, catch, etc.). Many times the subject and the object are
immobile but frequently the subject (i.e., during forward locomotion),
the object (i.e., a mosquito), or both (e.g., a catcher and a falling
ball) are in relative motion with respect to each other. Such cases are frequent and meaningful in the motor repertoire of an animal. This is
especially true for primates, given the exquisite development of their
visual system, which enables them to detect, analyze, and interact
effectively with objects around them. An additional advantage of the
primates is the excellent use they possess of the arm for reaching and
of the hand for grasping. It is not surprising that the conjunction of
outstanding visual and motor capacities confers to primates such an
exceptional status in visuomotor coordination. Now, a wealth of
evidence obtained during the last 30 years of research indicates that
area 7a of the posterior parietal lobe and the motor cortex play a
central node in visuomotor coordination. On the one hand, area 7a is
engaged in a wide variety of sensorimotor processes and responses to
visual moving stimuli, including optic flow (Andersen
1997; Motter and Mountcastle 1981
;
Mountcastle et al. 1975
; Siegel and Read
1997
). On the other hand, motor cortex is involved in several
aspects of movement initiation and control, including the motor command
itself as well as processes interposed between a stimulus and the
response to it (Alexander and Crutcher 1990a
,b
;
Evarts 1981
; Georgopoulos et al. 1982
,
1986
, 1989
, 1992
; Zhang et al. 1997
). In addition, responses of motor
cortical neurons to simple moving stimuli have been described
(Port et al. 2001
; Wannier et al. 1989
).
However, no detailed investigation of motor cortical responses to optic
flow stimuli have been performed. It would be of interest to know
whether such responses exist, and if so, to compare the functional
properties of motor cortex and area 7a during optic flow stimulation.
This information can provide important insights about the processing of
visual motion used in action. In the present study, we investigated the
responsiveness of cells in the motor cortex and area 7a to optic flow
visual stimuli. The results showed the following: 1) in both
cortical areas there are preferential responses to expanding optic
flow; 2) the large majority of neurons responded selectively
to one type of optic flow stimuli, particularly in the motor cortex; 3) the receptive field (RF) structure in area 7a neurons
could be modulated by the type of optic flow stimulus; 4)
there was no clear visual RF structure in the motor cortical neuronal
responses, and therefore the modulation of motor cortical cell activity
by optic flow stimuli did not depend on a RF structure; and
5) the magnitude of the effects of visual stimulation
observed, although smaller, was comparable to those observed in the
same motor cortical cells during force exertion on a manipulandum.
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METHODS |
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Animals
Two male monkeys (Macaca mulatta, 6 and 7 kg body wt) were used in this study. Animal care conformed to the principles outlined in the Guide for Care and Use of Laboratory Animals (National Institutes for Health publication no. 85-23, revised 1985). Animal studies protocols were approved by the local institutional review boards.
Visual stimuli
Stimuli were presented on a 69 cm × 69 cm tangent screen
placed 48.5 cm in front of the animal. Small square patches of random dots were presented successively at 25 different positions in a regular
5 × 5 grid (Fig. 1A).
The dots could move in eight different motion conditions (Fig.
1B): the four cardinal directions of translation (rightward,
leftward, upward, and downward), expansion, contraction, clockwise (CW)
rotation, and counterclockwise (CCW) rotation. Stimuli were
back-projected on the screen using a liquid crystal display projector
(NEC Multisync MT 820/1020) with a refresh rate of 60 Hz. The whole
screen subtended 71° of visual angle (DVA), at eye level. The small
square patches were 13.8 cm × 13.8 cm and subtended 16.2 DVA on a
side at the center of the screen; the DVA subtended was progressively
smaller away from the center of screen. Stimuli were presented within
such a patch for 400 ms, one patch at a time, with an inter-patch
presentation interval of 150 ms. The stimuli were composed of 30 white
dots moving within a square on a black background. Each dot was a
circle of 0.35 DVA in diameter and moved for a maximum lifetime of 400 ms, after which it was assigned to a new random location within a
square patch. If a moving dot traveled outside the patch displayed, it was relocated to a new random location within the square. The dots were
relocated asynchronously, to avoid coherent flickering of the stimuli.
This constant reshuffling essentially eliminated pattern and density
artifacts, because the pattern of dots was changing constantly and each
region within the square had approximately the same number of points at
any time. The linear (constant) velocity in the four directions of
translation (left-, right-, up-, and downward), and the directions of
expansion and contraction was 40 DVA/s; the angular speed in both
directions of rotation was 430°/s. These speeds were in the range of
values used in studies by other investigators (see, e.g.,
Graziano et al. 1994; Lagae et al. 1994
).
Since the main objective of this study was to evaluate the effect on
neuronal activity of the different kinds of stimulus motion, the
location of stimulation and their interaction, no special attempt was
made to define a velocity sensitivity curve.
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Statistical design
The eight different motion conditions were interleaved and
presented in a pseudorandom order. The 25 different patch locations were nested within each stimulus motion condition and were also presented pseudorandomly. A complete run consisted of the presentation of all conditions in three repetitions. We wanted to assess the statistical significance of the effect on cell activity of two factors,
namely stimulus motion condition (at k = 8 levels) and stimulus location (at m = 25 levels). The experimental
design above was a nested, complete factorial design in which all eight stimulus motion conditions were tested for each 1 of the 25 stimulus locations. These presentations were blocked in three repetitions. This
number of repetitions was chosen based on statistical considerations, namely that adequate degrees of freedom (DF) for the error terms would
be available to assess the effects of stimulus motion condition, stimulus location, and their interaction. Specifically, there were
eight stimulus motion conditions × 25 stimulus locations × 3 repetitions = 600 trials, yielding a total of
DFtotal = 599; the DF for the error term were
DFerror = DFtotal DFmotion
DFlocation
DFrepetition = 599
7
24
2 = 566; the DF of the F statistic for testing the
stimulus Motion effect were [7,566] and for testing the stimulus
Location effect [24,566]. These are more than adequate error DF for
the tests planned, and further increase in them (by increasing the
number of repetitions) would not have improved the sensitivity of the
F statistic used to assess the stimulus Motion and Location
effects. For example, suppose that the number of repetitions was
increased to a large number such that the error DF were now 10,000. In
this case, the values of the F statistic (at
= 0.05) for [7,566] and [7,10000] degrees of freedom are ~2.0263
and 2.0105, which is a rather trivial reduction in the F
value (i.e., increase in the sensitivity of the test), as compared with
the huge increase of the error degrees of freedom (stemming from the
increased number of repetitions) from 566 to 10,000. Similarly, the
corresponding values for the F testing the effect of
stimulus location for [24,566] and [24,10000] degrees of freedom
are and 2.0105 are ~1.5373 and 1.5184, which again are trivially
close to justify the increase in repetitions. Therefore three
repetitions were adequate for the purposes of this study.
Tasks
The monkeys (monkeys 1 and 2) were seated in a primate chair with the left arm loosely restrained. In the visual stimulation task, a yellow spot of 0.32 DVA diameter served as the fixation point (FP) and was presented in the center of the translucent tangent screen. The monkeys were trained to fixate this spot (within 2 DVA) for the duration of stimulus presentation. During that time, monkey 1 maintained the right hand in a relaxed position (monitored using a video camera), whereas monkey 2 maintained grasp of a vertical semi-isometric joystick with the right hand by exerting a constant pulling force on the joystick of ~0.22 N. First, the FP was turned on which the monkeys fixated; following attainment of fixation, 100-500 ms were allowed for monkey 2 to grasp the joystick. Then, stimuli were presented on the screen. A juice reward was delivered randomly every 1.1-3.3 s while fixation was maintained; if fixation was broken, the trial was aborted. The X-Y eye position was monitored using an oculometer (Dr. Bouis, Karlsruhe, Germany). Both the eye and the joystick position were sampled at 200 Hz; the tangential eye velocity was calculated by differentiating eye position.
In the center out motor task, the monkeys produced
semi-isometric force pulses on the joystick in eight radial directions, in response to the presentation of a peripheral target on an imaginary circle of 0.89 N radius. A force feedback cursor on the screen indicated the current net force exerted on the joystick; a constant upward bias of 0.108 N was applied, corresponding to a deflection of
the cursor of 0.85 DVA. A trial began with the appearance of a light
spot at the center of the screen that prompted the monkey to exert a
downward force of 0.108 N on the joystick to align the force feedback
cursor to the center spot within a circular force window of 0.217 N
radius. Then, after a variable delay of 1-3 s, a light spot appeared
on an imaginary circle of 6.8 DVA, which prompted the monkey to apply a
force pulse (>0.89 N) on the joystick such that the force feedback
cursor would move in the direction of the peripheral stimulus for the
monkey to obtain a liquid reward. Five repetitions of this task were
performed in a randomized block design.
Neural recordings
At the end of the training period, two stainless steel recording chambers were implanted, one in the arm representation of the motor cortex and the other in area 7a of the posterior parietal cortex. In addition, four titanium posts were positioned on the scull to support a halo used to immobilize the head during the experiment. These procedures were conducted under aseptic conditions and general anesthesia.
The electrical activity of single neurons in the motor cortex and area
7a was recorded extracellularly using a system with seven independently
movable microelectrodes (Uwe Thomas Recording, Marburg,
Germany) (see Lee et al. 1998; Mountcastle et al.
1991
). The electrodes were flexible quartz coated
platinum-tungsten alloy fibers with 1-3 M
of impedance at 1,000 Hz.
All the isolated neurons were recorded regardless of their activity
during the task and the recording sites changed from session to session.
Each electrode signal was amplified, filtered, and monitored using display oscilloscopes (Tektronix 2232). The action potentials were isolated using a dual-amplitude window discriminator (Bak Electronics, Germantown, MD) and multispike discriminators (MSD, Alpha-Omega Engineering, Nazareth, Israel). The presentation of the visual stimuli, behavioral control, and data collection was carried out by a personal computer. On-line raster displays were generated on a computer monitor. Finally, the depth from the top of neural activity at which each cell was recorded was noted and retained in a separate record.
The recording area was identified by marking the center of the recording chamber with a stainless steel pin placed directly in the brain, just before the monkey was killed with an overdose of pentobarbital sodium. Due to the large number of penetrations, no histological reconstruction of the recording sites was attempted. However, the entry points of the penetrations were plotted on the cortical surface, based on the entry points of the pins above demarcating the recording area. This, together with the recording depth, provided adequate information on the cortical areas sampled.
Electromyographic (EMG) activity
The EMG was recorded in the same two monkeys in separate
sessions from the neural recordings using intramuscular, multistranded, teflon-coated wire electrodes (Schwartz et al. 1988).
EMG activity of the following muscles was recorded in the first monkey,
contralateral to the recording side: rhomboideus major, trapezius,
deltoideus (anterior, middle, and posterior), pectoralis major, triceps
brachii, biceps brachii, extensor digitorum communis, and forearm
flexor (unspecified). The same muscles were recorded from in the second monkey, with the addition of supraspinatus, infraspinatus, and latissimus dorsi. The EMG signal was amplified, rectified, filtered, and sampled at 200 Hz. To assess the variability of the EMG signal, we
computed the coefficient of variation (CV) of the average EMG recorded
during the last 300 ms of the 400-ms-long visual stimulation at each of
the 25 patch locations for each stimulus motion condition
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General data analysis
An initial three-factor ANOVA (Repetition, stimulus Location and
stimulus Motion condition) was performed for each neuron to identify
cells whose activity changed significantly during repeated stimulus
presentations (i.e., cells with a statistically significant effect of
Repetition); this was taken to indicate an instability of cell's
responsiveness to the stimuli, and, therefore these cells were excluded
from further analyses. The frequency of discharge (based on spike
counts) during the last 300 ms of the 400-ms-long visual stimulation
period was the dependent variable. The spike counts were square-root
transformed to stabilize the variance (Cox and Lewis
1966; Snedecor and Cochran 1989
; Tukey 1977
). A total 1,110 cells were recorded in motor cortex (593 in monkey 1 and 517 in monkey 2) and 959 in area
7a (526 in monkey 1 and 433 in monkey 2). Of
these, 693 cells in motor cortex and 587 in area 7a did not show a
statistically significant effect of Repetition and were analyzed
further. A second, repeated measures ANOVA was then used to assess the
statistical significance of the Motion condition and Location effects.
The results of this ANOVA were consistent between monkeys in both
cortical areas and were combined.
A similar analysis was performed on the motor cortical cell activity
during the center out task, as follows. The square-rooted frequency of discharge (based on spike counts) during the
time period from the onset of the peripheral stimulus until the
delivery of reward (total experimental time, TET) was computed, and an
ANOVA was performed to identify cells whose activity changed over time,
using Repetition and Direction as factors. Of a total 941 motor
cortical cells recorded during this task (447 in monkey 1 and 494 in monkey 2), 761 did not show a statistically
significant effect of Repetition and were analyzed further by
performing a second, repeated measures ANOVA to assess the statistical
significance of Direction on cell activity as well as the change in
activity during TET from that observed during the control period (CP;
500 ms preceding the onset of the peripheral stimulus), defined as a
TET-CP contrast. Cells that showed any significant effect of the
factors tested (i.e., Direction, Change from the control period, or
their Interaction) were deemed to be significantly related to the motor
task. The results of this ANOVA were consistent between monkeys and
were combined. The program 2V of the BMDP/Dynamic statistical package
(BMDP Statistical Sotfware, Los Angeles 1992) was used to execute the
ANOVA. The level of statistical significance to reject the null
hypothesis for all statistical analyses was set at
= 0.05.
Analyses of response magnitude during visual stimulation
The following measures of the magnitude of cell response were calculated for those cells that showed a significant stimulus motion condition effect in the motor cortex and area 7a. 1) The discharge frequency of a cell was averaged across the 25 stimulus locations and the 3 repetitions, thus yielding 8 values, 1 for each stimulus motion condition. These values were ranked, with rank 1 denoting the highest activity. Then, the percentage of times for which each condition was ranked 1 was calculated. This provided a nonparametric, robust measure of preference of a particular stimulus motion in the population. 2) A measure of preference based on both the rank and discharge rate was computed by multiplying the number of times for which a particular stimulus motion condition was 1 times the average frequency of discharge during that condition.
Comparison of motor cortical response magnitude in the visual and motor tasks
Three measures were calculated to compare the magnitude of response between the visual and motor tasks: 1) the average discharge rate during the control period of the motor task; 2) the maximum of eight average discharge rates (1 per force direction), from the onset of the peripheral stimulus to the time that the force exerted exceeded the threshold in the motor task; and 3) the maximum average rate among the eight stimulus motion conditions. To account for possible variation of response due to the location of the stimulus, the maximum response in a given condition was calculated 1st, from among the 25 locations. This last measure was also computed for area 7a cell during the visual task. A paired t-test was used to assess the statistical significance of the differences tested.
Finally, the data analyzed came from tasks that comprised directional
variables; therefore several directional analyses were carried out, as
follows. 1) In the motor center out task, the
presence of directional tuning was assessed using bootstrap (Lurito et al. 1991
) and, if present, the preferred
direction was calculated. 2) In the visual task, there were
two distinct cases. First, the direction of the center of the
stimulated patch was calculated using the center of the display as the
origin of the unit circle. Since the aim of this analysis was to
compare directional responses in the center
out task to
directional responses in other tasks, the length of the vector from the
center of the display to the center of a patch was ignored, and only the direction of the vector was retained. Then the directional tuning
and preferred direction were assessed as described above. Finally, the
second case in the visual task concerns the stimulus motion condition
itself. Specifically, directional tuning and preferred direction was
assessed using the left-, right-, up-, and downward directions of
stimulus motion (across all patches) as the directional variable.
Effect of transformation
The statistical analyses above were performed on square-rooted
discharge rates. Although this is an appropriate transformation (Cox and Lewis 1966; Snedecor and Cochran
1989
; Tukey 1977
), we also analyzed the data
without any transformation with very similar results (see Neural
responses to optic flow stimuli).
Poisson train analysis
The specificity of a cell response to a particular stimulus
condition was assessed using the Poisson train analysis (Hanes et al. 1995). This analysis determines how improbable it is
that the number of spikes within a specific time interval is a chance occurrence. For this purpose, the actual number of spikes within a time
interval is compared with the number of spikes predicted by the Poisson
distribution derived from the mean discharge rate during the entire
time period (400 ms in this case). The measure of improbability is the
surprise index (SI) defined as
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The spike train analysis was applied for each motion condition,
collapsing the times of occurrence of action potentials across repetitions (n = 3) and stimulus Locations
(n = 25). We used the algorithm of Hanes et al.
(1995) to detect an activation above randomness, as follows.
The mean discharge rate (r) was computed for the 400 ms of
stimulus presentation. The first two consecutive spikes that had a mean
discharge rate greater or equal to r was found, and the time
between these two spikes was defined as the initial T value.
Then, the next spike was identified and the interspike interval
between this and the previous spike was added to T. The corresponding SI was calculated. This was repeated until the end of the
spike train; the spike at the end of the interval T with the
maximum SI was defined as the end of the burst. Next, the SI
was calculated for the interval T from the last to the first spike. Then, the spikes from the beginning were removed until the end
of the spike train, computing the corresponding SI in each step. The
spike at which SI was maximized was defined as the beginning of the
burst. If the SI from the beginning to the end of the burst was >5.3
(corresponding to P = 0.005), then the particular
Motion condition was deemed to have a significant effect on cell
activity. If this criterion was not fulfilled, it was assumed that
there was no response to the stimulus for that case. We found few cases
with more than one significant burst, and in this situation we choose
the longest burst as the period of activation.
Response latency analysis
The onset time of increase in activity for the cells analyzed was determined from the results of the Poisson train analysis above. Specifically, the onset time of a significant increase in cell of activity was taken to be the beginning of the burst or activation. Similarly, the offset times were determined and the duration of the response calculated. These different measures were compared between areas and among stimulus motion conditions.
Visual RF analysis
The following double Gaussian function (Barlow
1989) was used
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RESULTS |
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Neural responses to optic flow stimuli (Fig. 2)
The total number of cells with a statistically significant effect of visual stimulation in the ANOVA was three times greater in area 7a (370/587, 63%) than in motor cortex (148/693, 21.4%). The number of significant neurons to stimulus Motion condition, stimulus Location, and/or stimulus Motion condition × Location interaction are listed in Table 1. The proportion of cells with significant effects of different factors was not the same in both cortical areas, with a higher effect of Stimulus Location in area 7a and a larger effect of Motion condition in motor cortex. Overall, 79/148 (53.4%) motor cortical neurons and 102/370 (27.6%) neurons in area 7a showed a statistically significant effect of Motion condition; and 48/148 (32.4%) motor cortical neurons and 311/370 (84%) neurons in area 7a that showed a statistically significant effect of stimulus Location.
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The results above were obtained by performing statistical analyses on square-rooted discharge rates. Although this is an appropriate transformation (see METHODS), we also analyzed the data without any transformation and obtained very similar results.
Onset latencies
Figure 3, A and B, shows the distribution of the response onset and duration for cells that showed a significant effect in the Poisson train analysis. The onset latency of response was significantly longer in the motor cortex (221.9 ± 6.07 ms; mean ± SE, n = 150) than in area 7a (180.1 ± 3.86 ms, n = 353; t-test, P < 0.0001). On the other hand, the duration of the response did not differ significantly between the two areas (69.02 ± 1.95 ms for the motor cortex and 72.7 ± 1.02 ms in area 7a; t-test, P = 0.074).
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A different question concerns possible differences in onset times among stimulus motion conditions. Figure 3, C and D, shows cumulative functions of onset times separately for each stimulus motion condition. It can be seen that in the motor cortex (Fig. 3C) there was an a appreciable spread of these functions; the rank order of the eight stimulus motion conditions at the level of the median was as follows (rank 1 being the earliest): leftward, expansion, CCW, contraction, upward, downward, CW, and rightward motion (medians: 181, 194, 201, 213.5, 231.5, 249, 255, and 259.5 ms, respectively). By contrast, in area 7 (Fig. 3D) the cumulative functions were very close; the rank order of the eight stimulus motion conditions at the level of the median was as follows: downward, rightward, contraction, leftward, CCW, upward, CW, and expansion motion (medians: 144, 145.5, 151, 154, 154, 155, 157, and 167 ms, respectively).
The cumulative functions of the response duration for each stimulus motion condition were close in both areas, as can be seen in Fig. 3, E and F. In the motor cortex (Fig. 3E) the rank order of the eight stimulus motion conditions at the level of the median was as follows (rank 1 being the earliest): CW, rightward, contraction, leftward, downward, CCW, upward, and expansion motion (medians: 55, 60, 60.5, 63, 64.5, 67, 70, and 74.5 ms, respectively). Furthermore, in area 7a (Fig. 3F) the cumulative functions were closer than in motor cortex. The rank order of the response duration of the eight stimulus motion conditions in this area was as follows: downward, leftward, expansion, upward, contraction, CW, CCW, and rightward (medians: 62, 66, 66, 67, 67, 67, 68, and 71 ms, respectively).
Finally, the potential association between onset latency and response
magnitude was assessed by performing a correlation analysis (Fig.
4, A and B). There
were weak but statistically significant correlations in the two areas
studied but also of different sign. Specifically, for the motor
cortex, r = 0.158 (P = 0.022, n = 211), and for area 7, r = 0.077
(P = 0.011, n = 1,100).
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Relative effect of type of stimulus motion
A different question concerns the relative strength of the
responses with respect to the various kinds of stimulus motion. Two
analyses were performed for this problem, for cells with a statistically significant Motion condition effect, as follows. In one
analysis, the mean firing rates for the eight stimulus motion
conditions were ranked, and the times for which a given stimulus
condition was ranked first counted across cells. In the second
analysis, Tukey tests (Zar 1996) were performed and the times counted for which the firing rate for a given stimulus condition was significantly larger than every other (taken pairwise). Overall, the ranking and Tukey test showed that the responses to expanding optic
flow were the strongest, particularly in the motor cortex. In addition,
there was also a strong response to the rightward motion in area 7a,
i.e., toward the contralateral side. The results of the ranking are
shown in Fig. 5 for the motor cortex
(Fig. 5A) and area 7a (Fig. 5B). These results
were highly congruent with those obtained in the Tukey tests in both
cortical areas (Spearman's rank correlation
= 0.945, P = 0.0004 for the motor cortex, and
= 0.727, P = 0.027 for area 7a). The corresponding total
discharge frequency (i.e., number of cells × mean discharge rate
per cell) is illustrated in Fig. 5C for the motor cortical population and in Fig. 5D for the population of area 7a
cells.
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Selectivity of cell response
We used the Poisson train analysis (Hanes et al.
1995) (see METHODS) to assess the presence of a
neural response to a particular Motion condition, and, consequently,
determine the specificity of the cell activity to the Motion conditions
used. The results showed that 152/693 (21.9%) of the neurons in the
motor cortex and 353/587 (60.1%) of the neurons in area 7a showed
statistically significant responses for at least one Motion condition.
As can be observed in Fig. 6, the
majority of cells in motor cortex, 112/152 (73.7%), showed activation
in only one stimulus condition, whereas 133/353 (37.7%) of the neurons
in area 7a showed the same type of selectivity. In addition, 124/353
(35.1%) of neurons in area 7a responded to more than 3 stimulus Motion
conditions, including 22 neurons that responded to all Motion
conditions. No such neurons were observed in the motor cortex. Overall,
the distribution of neurons with significant responses to one or more
stimulus Motion condition (see Fig. 6) were differed significantly
between the two cortical areas (
2 = 79, DF = 7, P < 10
10). Furthermore, the response to expansion
was the most prevalent within the motor cortical cells that showed
significant responses to only one stimulus Motion condition, but not
clear prevalence was observed in the same type of neurons in area 7a
(Table 2,
2 = 17.6, DF = 7, P = 0.014).
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As mentioned above, the monkeys were required to fixate their eyes on a
central spot during stimulus presentation. The interpretation of the
results above obviously depends on that condition being fulfilled.
Indeed, the eyes remained fixated as required. This is illustrated in
Fig. 7, which shows the relative
frequency distribution of the X-Y eye position for all
stimulus presentations. Adherence to fixation was also corroborated by
the results of an analysis of eye velocity: we found that >99.2% of
the tangential eye velocity values recorded during visual stimulus
presentation were <150 DVA/s, a threshold commonly used to detect the
occurrence of a saccade (Siegel and Read 1997). This
percentage was >93.2% using a lower threshold of <50 DVA/s
(Read and Siegel 1997
).
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Visual RFs in motor cortex
In general, there was not an obviously discernible visual RF structure in the neuronal responses of motor cortex (Fig. 8). However, for a detailed analysis, we used two different kinds of nonlinear regression (a double Gaussian and a polynomial) on the mean firing rate observed at the 25 stimulus locations. This analysis was performed on each of the eight Motion conditions for 75 neurons that showed significant effect in Stimulus Location and/or Motion condition × Location interaction in the ANOVA (total cases 600, see Table 1). For the double Gaussian regression, the median percent of variance accounted for (coefficient of determination, R2) was 19%; the 25th and 75th percentiles were 1% (lack of convergence) and 32%, respectively. For the polynomial regression, the median R2 was 21%; the 25th and 75th percentiles were 12 and 27%, respectively. In addition, only 6.3% (38/600) of the cases in the double Gaussian and 5.2% (31/600) in the polynomial fitting were significant in the bootstrap (P < 0.05). These results indicate that, although there can be some orderly variation in the spatial profile of cell response in few neurons, for most cells this was not the case. Therefore the modulation of motor cortical cell activity by optic flow stimuli described above does not reflect a RF structure.
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Visual RF structure in the area 7a
In contrast to the motor cortex, cells in area 7a typically showed clear cut RFs (see Figs. 9-11). The double Gaussian and polynomial regressions were performed in a total of 2,648 cases (8 Motion conditions × 331 neurons with significant effects in Stimulus Location and/or Motion condition × Location interaction in the ANOVA; see Table 1). For the double Gaussian regression, the median R2 was 28%, and the 25th and 75th percentiles were 7 and 44%, respectively. For the polynomial regression, the median R2 was 30%, and the 25th and 75th percentiles were 18 and 40%, respectively. In addition, 21.6% (572/2648) of the cases in the double Gaussian and 22.5% (597/2648) in the polynomial regression were significant in the bootstrap (P < 0.05). Therefore the RF structure observed with the visual inspection of the rasters was well explained by the two types of nonlinear regressions. However, we used the results of the double Gaussian regression for further analysis, since the parameters of this regression can be used directly to compare the visual RFs across neurons and conditions, and there was not a clear difference in the R2 obtained with both regressions.
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The regression models above were also evaluated by plotting the
residuals against the predicted value (Draper and Smith
1981) that showed that they were distributed approximately
evenly above and below zero without any particular pattern. This
indicates that the models were adequate, that is that no additional
terms were needed. This is not surprising since these models were
essentially constructed for curve-fitting and therefore contained
enough free parameters. Then the appropriateness of the model implies
that the R2 can, in this case, serve
as a proper assessment of the goodness-of-fit of the model.
Visual RF size in the area 7a
The half-height areas of the RFs, defined as the 50% of the maximum response in the significant Gaussian regressions with a positive depth of the tuning, k (excitatory responses, see METHODS), presented a wide range of values. We included only those neurons with a RF center inside the stimulation area for a total of 351 cases. The median of the half-height areas was 1022.1 DVA2 and the 25th and 75th percentiles were 239.2 and 1,360.6 DVA2, respectively. These areas did not change as a function of the RF center eccentricity (Fig. 12A). However, as is shown in Fig. 12B, the distribution of the center of the RFs in the horizontal axis (y0) was slightly skewed to the right (contralateral to the recording sites). Bilateral RFs were common.
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Density plots of neurons with positive (351 cases, 160 neurons; Fig. 13A) and negative (67 cases, 52 neurons; Fig. 13B) k values were obtained pulling together the half-height areas of significant RF. It is clear from Fig. 13A that the more dense portion of the visual field represented in area 7a is around 10 DVA, corresponding to the region of central vision, and that even if there is a small bias toward the right side there is a bilateral representation of the visual field. In addition, neurons with negative k spare the central location, where the FP is presented, at least in some Motion conditions.
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Position invariance of optic flow selective responses in area 7a
Cells in area 7a with significant RF structure in the double Gaussian regression were also classified with respect to their selectivity to stimulus motion. The results of this classification showed that 106/244 (43.4%) of neurons had significant RFs to only one stimulus Motion condition, and that the number of neurons with significant RFs in different stimulus Motion Conditions decreased as the number of stimulus Motion Conditions increased. Examples of cells with a significant RFs in only one stimulus Motion condition (Fig. 9), to two stimulus Motion conditions (Fig. 10), and to all stimulus Motion condition (Fig. 11) are illustrated.
We performed an ANOVA on the cells with consistent responses during
radial or circular motion (as assessed by the Poisson train analysis)
and with significant RFs in the double Gaussian regression, to
determine the presence of position invariance of the response across
their RF. In this ANOVA we used the stimulus Location inside the RF as
a factor and the discharge rate as the dependent variable. We found
that 62.1% (82/132) of the cases did not show a significant effect of
stimulus Location inside the RF, 12.1% (16/132) showed significant
responses, and 25.8% (34/132) showed small RFs corresponding to only
one location, and therefore the ANOVA could not be performed. These
findings suggest that, in a large proportion of area 7a neurons, the
responses during circular or radial motion stimulation do not depend on a linear summation of translation stimuli (Lagae et al.
1994), since these cells showed responses that were position
invariant across the RF.
Finally, some cells in area 7a showed significant RFs in the rightward
and leftward Motion conditions and showed an opponent vector
organization (Motter and Mountcastle 1981;
Steinmetz et al. 1987
). We defined as inward opponent
vector cells to those neurons with significantly larger responses in
the left stimulated portion of the rightward direction and
significantly larger responses in the right stimulated portion of the
leftward direction (ANOVA). Conversely, outward opponent vector cells
showed significantly larger responses in the right of the rightward
direction and larger responses in the left of the leftward direction.
The results indicated that 10 neurons showed inward (Fig. 10,
A and B) and 4 neurons outward (Fig.
10C) opponent vector responses. In contrast, no neurons with
responses during upward and downward Motion stimulation showed this
type of opponent vector response organization.
Comparison of visual and motor effects on motor cortical neuronal activity
A different question concerns the magnitude of cell response
during stimulus presentation, as compared with the changes in cell
activity during force production by the contralateral hand. This was
evaluated using a center out, force exertion task. Of
514 motor cortical cells studied in both the motor and visual tasks,
388 (75.5%) showed a significant relation to either or both tasks, as
follows: 284/388 (73.2%) cells showed a significant relation only to
the motor task, 27/388 (7%) cells showed a significant relation only
to the visual task, whereas the remaining 77/388 (19.8%) cells showed
significant relations to both tasks. Therefore a total of 361/514
(70.2%) cells were related to the motor task, 104/514 (20.2%) were
related to the visual task, and 49/514 (9.6%) did not show a
significant relation to either task. These results are illustrated in
Fig. 14 in the form of Venn diagrams.
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The magnitude of motor cortical cell response was evaluated for the 77 cells that showed significant changes in activity in both tasks, as
described in METHODS. We found that these changes (mean ± SE) were comparable, although significantly higher in the
motor (19.1 ± 1.9 imp/s) than in the visual task (14.1 ± 1.0 imp/s; P = 0.0015, paired t-test); both
of these values were significantly higher that the average activity
(5.9 ± 0.7) during the control period of the motor task
(P < 1010 for both tasks). For
comparison, the average discharge rate of area 7a cells during the
visual task (17.3 ± 2.4 imp/s, n = 102 stimulus
Motion condition cells in the ANOVA above) was similar to the responses
of motor cortical cells observed in the visual task (P = 0.107, independent samples t-test), but slightly smaller than the responses of the same cells tested in the motor task (P = 0.004, independent samples t-test).
These results are illustrated in Fig.
15.
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Finally, we analyzed more specifically the neuronal responses with
respect to the directional domain (see METHODS). In the center out task, 213/514 (41.4%) showed a significant directional effect in the ANOVA, and of those 190/213 (89.2%) were
directionally tuned. In the visual task, stimulus location analysis,
only 27/514 (5.2%) showed a significant effect of stimulus direction
in the ANOVA, and of those only 1/27 (3.7%) was directionally tuned
(see METHODS); in the visual task, motion condition
analysis (using the 4 cardinal stimulus motions), 49/514 (9.5%) showed a significant stimulus motion effect in the ANOVA, and none were tuned.
EMG activity
There were practically no significant effects of stimulus
motion presentation on muscular activity. The ANOVA and Tukey tests performed on the EMG activity of 13 shoulder, upper arm, and forearm muscles showed that only one muscle (anterior deltoid) in one monkey
showed a significant Motion condition effect with a preference for
rightward motion; however, the same muscle did not show any effect in
the other monkey. This lack of a significant EMG change, as compared
with the significant cell responses, could be due to a possible high
variability in the EMG signal. However, this was not the case, for the
geometric mean of the coefficient of variation for the EMG of all the
muscles studied in both monkeys (see METHODS) was a modest
11%. In contrast, all muscles showed statistically significant changes
during the center out task (ANOVA).
Recording sites
The present results came from cells recorded in the primary motor cortex and area 7a. Photographs of the recording sites are shown in Fig. 16. Although no histological reconstruction of the recording sites was possible, several lines of evidence indicate that the presumed area 7a cells were indeed from that area. Specifically, 1) the entry points of the penetrations were on the exposed surface of area 7a, 2) penetrations were close to being perpendicular to the cortical surface, and 3) the depth of recordings were usually within 2 mm from the top of neural activity (median = 1,290 µm), both for those cells recorded from more centrally located penetrations and from those recorded from more anterior or posterior penetrations. In addition, the functional properties of cells recorded from more anterior or posterior penetrations were very similar to the rest of the group. Even when data from such anterior or posterior penetrations were removed from the sample, the remaining data were again very similar to those of the whole sample.
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DISCUSSION |
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Methodological considerations
Optic flow corresponds to the changes in the optic array
induced by the relative motion between the subject and the environment. Information about optic flow is indispensable for encoding direction of
heading, orientation, and visual navigation in three dimensional space,
controlling posture and locomotion, and for the perception of moving
objects and the selection of motor actions that allow the appropriate
interaction with them (Koenderink 1986; Lee
1976
, 1980
). The objective of the present study
was to investigate the neuronal responses in area 7a and motor cortex
to optic flow stimuli and to stimulus presentation at different parts
of the visual field. Specifically, we wanted to assess these responses
with respect to a good variety of stimulus motion characteristics and a
detailed coverage of the visual field. These considerations led to the
experimental design we used, namely the delivery of stimuli of 8 different kinds of motion to each one of 25 square patches covering a
good area of the visual field. The stimuli consisted of random dots
moving coherently to produce standard optic flow patterns, including
translation, rotation, and radial motion. Since these stimuli were
shown in patches of the visual field, one at a time, the resulting
situation can be best described, in a natural setting, as an occluded
optic flow stimulation, such as seen, for example, in a pilot of a
plane during a flight: in this case, the full optic flow is occluded by
the plane except for the patch of the cockpit window. Although this
design provided the needed framework for our study, and has been used
in previous studies (Lagae et al. 1994
; Raiguel
et al. 1997
), it should be noted that it is different from
other designs of studies aimed to investigate responses to optic flow
or RF structure that have employed full field stimulation, static
stimuli, or stimuli consisting of moving bars (see Responses to
optic flow in area 7a). Our findings demonstrated the
presence of clear responses of motor cortical cells to rectilinear,
expanding, contracting, and rotatory (CW, CCW) optic flow stimuli that
were presented passively, in the absence of a motor response. In
addition, these results indicate that neurons in area 7a also respond
to partial field optic flow stimuli, which qualitatively confirm
findings of previous studies (Read and Siegel 1997
;
Siegel and Read 1997
). These findings, and the
comparison of the functional properties of both cortical areas during
optic flow stimulation, will be discussed separately.
Motor cortical responses to optic flow
More than 20% of the motor cortical cells were modulated by optic flow stimuli. The proportion of the cells with significant stimulus Motion condition effects were approximately two times higher than those with stimulus Location effects. Interestingly, of all kinds of stimulus motion tested, responses to expanding optic flow were the strongest and the more prevalent.
The responses of motor cortical cells to optic flow stimuli, although of smaller magnitude, were comparable with those observed in the same cells during force exertion on a manipulandum. As expected, the large majority (361/514 = 70.2%) of cells were active in the latter task, and, of those, 77/361 (24.8%) responded to visual stimuli (Fig. 15). These findings establish visual motion information as a robust input to motor cortex.
Motor cortical responses to stimuli moving passively across the visual
field, that is in the absence of anticipated response, were described
previously (Port et al. 2001; Wannier et al.
1989
). However, several important features distinguish the
present study from those previous ones. First, optic flow stimuli were
not used in either of those studies. Second, in the study by
Wannier et al. (1989)
visual stimulation consisted of
moving the hand or a hand-held blinking light in front of monkeys that
were not required to fixate their eyes; therefore the kind of stimulus
motion delivered was not precisely controlled, and retinotopic
information was not available. By contrast, in the present experiments
both the kind of stimulus motion and the retinal location of the
stimuli presented were precisely controlled. Finally, in both previous and the present study cell responses to moving visual stimuli were not
associated with EMG activation.
With respect to the kinds of stimulus motion tested, all are typical
elements of natural motions of objects in three-dimensional space.
Therefore the motor cortical responses observed could reflect the
availability to this structure of information concerning object motion
that would apparently be very useful in planning a movement in relation
to that object. Now, unlike other motions, expansion also provides
information about the direction of heading. This literally
"egocentric" case is unique because of the possibility of
collision: action by the subject (i.e., approach or avoidance) would be
in order. In that respect this situation differs qualitatively from
that of rectilinear and/or rotatory stimulus motion in which case
stimuli can be observed passively and action can be initiated by, but
not forced on, the subject. In summary, then, if we assume an immobile
observer, expanding optic flow would indicate, first of all, that a
surface is approaching, and, second, would provide information on the
direction of its approach. It is noteworthy that this kind of stimulus
motion, conveying directional approach information, was effective in
driving motor cortical cells and exerted, in fact, the strongest and
most numerous effects. It is also remarkable that these effects were
exerted in the absence of any required motor response. These findings
suggest that directional approach information is available to the motor
cortex for potential, but not obligatory, use in preparing a motor
response. Of course, it is possible that the stimuli might have
triggered neural events in the motor cortex in preparation of a motor
response to interact with the stimulus in a certain part of the visual
field even if not demanded by the experimenter. However, only few
neurons that were directionally tuned in the center out
task were also tuned in the visual task, which suggests that the
observed responses to optic flow stimuli were not related to the
preparation of an intended motor response. Finally, the modulation of
motor cortical cell activity by optic flow stimuli described above did not depend on a RF structure.
Responses to optic flow in area 7a
In the present study we found that ~60% of the neurons in area 7a were influenced by optic flow stimulation. Approximately three times more neurons were influenced by the location of the stimulus than by the kind of stimulus motion. In fact, a group of neurons in area 7a showed clear RF when stimulated with optic flow stimuli. The size, distribution, and modulation of the RF position by the type of stimulus Motion condition were characterized. In relation to the stimulus Motion condition effect, responses to expanding optic flow were the strongest.
Responses of area 7a cells to optic flow stimuli has been reported
previously (Read and Siegel 1997; Siegel and Read
1997
), and those findings were qualitatively replicated in the
present study. For example, Siegel and Read (1997)
found
that ~40% of the cells in this area were sensitive to certain types
of optic flow such as translation, expansion, contraction, rotation,
and spiral motion. There were two major differences between the
experimental design of those previous studies (Read and Siegel
1997
; Siegel and Read 1997
) and this one. First,
the speed of the stimuli differed, namely it ranged from ~8 to ~27
DVA/s (see Fig. 2 in Siegel and Read 1997
), whereas it
was fixed at 40 DVA/s in the present study; and second, in both of the
former studies the monkeys performed a task that required a motor
response to detect a change from a structured optic flow field motion
to an unstructured motion, whereas in the present study the monkeys
just maintained fixation. Although the results obtained in both studies
are qualitatively similar, the substantial differences above do not
permit a detailed quantitative comparison.
Several studies have determined the RF size and position of area 7a
cells using static or moving visual stimuli (Andersen et al.
1990; Motter and Mountcastle 1981
; Motter
et al. 1987
; Robinson et al. 1978
). For example,
Robinson et al. (1978)
used a static 3 × 3 DVA
spot of white light and found that the majority of area 7a cells
possessed large, frequently bilateral RFs with a clear bias to the
contralateral visual hemifield. The results of the present study
confirmed these findings using optic flow stimuli, and, in addition,
indicated that the RF size did not vary with stimulus eccentricity
(Fig. 12, A and B), a phenomenon already observed
in MST neurons (Raiguel et al. 1997
). In addition, we
found that most of the RFs in area 7a showed a excitatory peak. When
all these RFs were superimposed, it was found that the foveal region
(10 DVA diameter circle) was most densely mapped (Fig. 13A).
However, other neurons showed an inhibitory peak in their RF, which
could include the foveal region; this means that these neuons did not
respond to stimulation of the foveal region, a phenomenon called foveal
sparing and fully characterized by Mountcastle and collaborators
(Motter and Mountcastle 1981
; Motter et al. 1987
).
An important feature of area 7a cells is their responsiveness to moving
as compared with static visual stimuli. Most of these cells are
sensitive to the direction of bars being translated across the visual
field, and a subset of these cells respond selectively to stimuli
moving toward the FP (inward opponent vector neurons) or away the FP
(outward opponent vector neurons) (Motter and Mountcastle 1981; Motter et al. 1987
). The opponent vector
organization observed in area 7a was considered well suited to be
involved in the analysis of optic flow during locomotion or in the
manipulation of objects by the hands (Motter and Mountcastle
1981
; Steinmetz et al. 1987
). However, in a
recent study in which the response of area 7a cells to translating bars
and optic flow stimuli was compared, it was found that, in general,
neurons with opponent vector organization did not respond to expanding
or contracting optic flow stimuli (Siegel and Read
1997
). Therefore these observations suggest that two types of
high-order visual motion processing can occur in area 7a; namely
1) the encoding of spatial information from motion during
optic flow stimulation and 2) the processing of objects moving inward or outward across the peripheral edges of the visual fields, i.e., toward or away from the center of gaze (opponent vector
organization). In the present study we observed both types of
high-order processing, namely cells that responded to small field
radial optic flow stimuli (Fig. 9B), and cells in which the
RF changed position in an opponent vector organization, particularly within the leftward and rightward motion conditions (Fig. 10,
A-C). The inward or outward opponent vector cells did not
respond to expanding or contracting optic flow stimuli, a finding that
supports the idea that such responses are probably related to the
processing of objects moving in relation to the subject.
The results of the analysis of the RF structure in area 7a in this and
earlier studies (Motter and Mountcastle 1981;
Motter et al. 1987
; Mountcastle et al.
1975
) suggest that the RF size and position are a function of
the behavioral state of the subject and the stimulus parameters used.
Indeed, we found that the location of the RF could be influenced by the
kind of stimulus Motion condition; for example, the RF could be
relocated, depending on the opponent vector organization of the
response to left- and rightward stimuli (Fig. 10, A-C),
whereas, in other cases, the RF was similar size and location in all
stimulus Motion conditions (Fig. 11, A and B).
Comparison between motor cortex and area 7a
There were three times more neurons responding to optic flow
stimuli in area 7a than in the motor cortex. This in fact is not
surprising, since for over 30 yr area 7a have been considered an
important associative node involved in visual motion processing and as
part of the visual dorsal stream. Responses to optic flow stimuli have
been described in several other brain areas including the middle
temporal (MT) area (Lagae et al. 1994), the medial superior temporal (MST) area (Duffy and Wurtz 1991a
,b
;
Graziano et al. 1994
; Lagae et al. 1994
,
Orban et al. 1995
; Saito et al. 1986
;
Tanaka and Saito 1989
; Tanaka et al.
1986
, 1989
), the ventral intraparietal area
(Schaafsma and Duysens 1996
), and the anterior superior
temporal polysensory area (Anderson and Siegel 1999
). With respect to the extent of the visual field stimulated, both whole
field and partial field stimulations have been used.
Information on onset times of neuronal changes in activity indicates
that the motor cortical sensitivity to moving visual stimuli could be
mediated by corticocortical circuits. Very short onset times to the
presentation of such stimuli have been reported for areas MT
(Lagae et al. 1994) and MST (Duffy and Wurtz
1997
; Lagae et al. 1994
), with median values of
<100 ms, for speeds of motion comparable with that used in the present
study (e.g., 40 DVA/s for rectilinear, expansion, and contraction
stimuli). We observed longer onset times in area 7a with a mean of
180.1 ms. Thus the motor cortical mean onset time of 221.9 ms observed in the present study is ~40 ms longer than that in area 7a, and both
motor and parietal onset times are longer than those observed in areas
MT and MST above. Although the exact corticocortical pathways for
transmission of stimulus motion information are not known, the ordering
of the onset times above suggests a progression from temporal to
parietal to frontal areas. However, there seems to be an increase in
the specificity of neuronal responses to moving visual stimuli, from
temporal to frontal areas: typically cells in MT (Lagae et al.
1994
), MST (Duffy and Wurtz 1991a
,b
; Graziano et al. 1994
; Lagae et al. 1994
;
Orban et al. 1995
; Saito et al. 1986
;
Tanaka and Saito 1989
; Tanaka et al.
1986
, 1989
), and area 7a respond to more than
one kind of optic flow stimuli, whereas in motor cortex most cells
responded to just one kind. For example, we found that only 37.79% of
cells in area 7a responded consistently to only one kind of stimulus
motion as compared with 73.7% in motor cortex. This indicates a
segregation at the motor cortical level of subsets of cells that are
selective for a particular type of motion, which, in turn, suggests
that, e.g., objects moving in different ways might engage
nonoverlapping sets of motor cortical cells for possible action.
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ACKNOWLEDGMENTS |
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We thank D. N. Lee for advice on aspects of the visual stimuli used.
This work was supported by National Institute of Mental Health Grant PSMH-48185, the United States Department of Veterans Affairs, and the American Legion Brain Sciences Chair.
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FOOTNOTES |
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Address for reprint requests: A. P. Georgopoulos, Brain Sciences Center (11B), VAMC, One Veterans Dr., Minneapolis, MN 55417 (E-mail: omega{at}umn.edu).
Received 14 November 2000; accepted in final form 21 May 2001.
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REFERENCES |
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