|
|
||||||||
The Journal of Neurophysiology Vol. 88 No. 1 July 2002, pp. 354-369
Copyright ©2002 by the American Physiological Society
Howard Hughes Medical Institute, Department of Physiology, W. M. Keck Foundation, Center for Integrative Neuroscience, and the Neuroscience Graduate Program, University of California, San Francisco, California 94143
| |
ABSTRACT |
|---|
|
|
|---|
Priebe, Nicholas J., Mark M. Churchland, and Stephen G. Lisberger. Constraints on the Source of Short-Term Motion Adaptation in Macaque Area MT. I. The Role of Input and Intrinsic Mechanisms. J. Neurophysiol. 88: 354-369, 2002. Neurons in area MT, a motion-sensitive area of extrastriate cortex, respond to a step of target velocity with a transient-sustained firing pattern. The transition from a high initial firing rate to a lower sustained rate occurs over a time course of 20-80 ms and is considered a form of short-term adaptation. The present paper asks whether adaptation is due to input-specific mechanisms such as short-term synaptic depression or if it results from intrinsic cellular mechanisms such as spike-rate adaptation. We assessed the contribution of input-specific mechanisms by using a condition/test paradigm to measure the spatial scale of adaptation. Conditioning and test stimuli were placed within MT receptive fields but were spatially segregated so that the two stimuli would activate different populations of inputs from the primary visual cortex (V1). Conditioning motion at one visual location caused a reduction of the transient firing to subsequent test motion at a second location. The adaptation field, estimated as the region of visual space where conditioning motion caused adaptation, was always larger than the MT receptive field. Use of the same stimulus configuration while recording from direction-selective neurons in V1 failed to demonstrate either adaptation or the transient-sustained response pattern that is the signature of short-term adaptation in MT. We conclude that the shift from transient to sustained firing in MT cells does not result from an input-specific mechanism applied to inputs from V1 because it operates over a wider range of the visual field than is covered by receptive fields of V1 neurons. We used a direct analysis of MT neuron spike trains for many repetitions of the same motion stimulus to assess the contribution to adaptation of intrinsic cellular mechanisms related to spiking. On a trial-by-trial basis, there was no correlation between number of spikes in the transient interval and the interval immediately after the transient period. This is opposite the prediction that there should be a correlation if spikes cause adaptation directly. Further, the transient was suppressed or extinguished, not delayed, in trials in which the neuron emitted zero spikes during the interval that showed a transient in average firing rate. We conclude that the transition from transient to sustained firing in neurons in area MT is caused by mechanisms that are neither input-specific nor controlled by the spiking of the adapting neuron. We propose that the short-term adaptation observed in area MT emerges from the intracortical circuit within MT.
| |
INTRODUCTION |
|---|
|
|
|---|
Our perception of the world
is not based simply on sensory information currently available from our
environment but also on the context in which we receive information. In
the "waterfall" illusion, for example, long-term exposure to motion
in one direction can induce the perception that a stationary stimulus
is moving in the opposite direction (Schrater and Simoncelli
1998
; Wohlgemuth 1911
). Stimulus context affects
our perception not only of visual motion but also of the orientation of
bars (Gibson and Radner 1937
), the pitch of a sound
(Stevens and Davis 1938
), and the position of an object
on the arm (Kilgard and Merzenich 1995
).
Adaptation is a property of neuronal responses that may mediate the
effect of context and recent sensory history on perception. In the
visual system, adaptation can have many time courses ranging from the
very long adaptation that produces the waterfall illusion to very short
time scales that alter the discrimination of the direction of motion
for a brief time (Takeuchi et al. 2001
). On the time
scale of tens of milliseconds, adaptation reduces the firing of visual
neurons from an initial transient to a subdued sustained response.
Retinal ganglion cells (Kaplan et al. 1993
; Victor 1987
), and many neurons in the lateral geniculate
nucleus (Saul and Humphrey 1990
) and primary visual
cortex (V1), show a transient-sustained firing pattern for a step
change in contrast (Kulikowski et al. 1979
;
Muller et al. 1999
; Nelson 1991
;
Tolhurst et al. 1980
), while neurons in visual area MT
show a similar response pattern for a step change in target speed
(Lisberger and Movshon 1999
).
At least three classes of mechanisms could contribute to the short-time-scale adaptation that produces the transient response of MT neurons: 1) input-specific mechanisms: adaptation in MT could be inherited from adaptation already present in the firing of its inputs or could be created by short-term depression in the synapses that transmit those inputs to MT. 2) Intrinsic spiking mechanisms of individual neurons: many excitatory cortical neurons exhibit spike frequency adaptation for a step of input current so that the response consists of a transient that decays to a lower sustained firing rate. 3) Circuit properties: adaptation might result from processing that has occurred within MT or from feedback from areas higher in the hierarchy of visual motion processing. Of course, this third class of mechanism would depend on circuit properties in or beyond MT but would still have to be implemented by cellular mechanisms operating on MT neurons. The goal of the present pair of papers was to constrain the mechanisms of adaptations through extracellular recordings from MT neurons in anesthetized macaque monkeys. This first paper provides evidence that is inconsistent with explanations for adaptation based on both input-specific mechanisms from primary visual cortex to MT and intrinsic mechanisms related to the spiking of MT neurons.
| |
METHODS |
|---|
|
|
|---|
Physiological preparation
Extracellular single-unit microelectrode recordings were made in the middle temporal visual area (MT) of nine anesthetized paralyzed monkeys (Macaca fascicularis, mulatta) and a single awake, behaving monkey (M. mulatta) and the primary visual cortex (V1) of two anesthetized paralyzed monkeys (M. mulatta). A minority of the data were obtained from the awake animal and are shown primarily to emphasize the similarity of the results.
In acute experiments, anesthesia was induced with ketamine (5-15
mg/kg) and midazolam (0.7 mg/kg), and cannulae were inserted into the
saphenous vein and the trachea. The animal's head was then fixed in a
stereotaxic frame, and the surgery was continued under an anesthetic
regime of isofluorane (2%) inhaled in oxygen. A small craniotomy was
performed and the dura reflected, either directly above the superior
temporal sulcus (STS) for recordings in area MT or above the occipital
lobe for recordings in V1. The animal was maintained under anesthesia
using an intravenous opiate, sufentanil citrate (8-24 µg · kg
1 · h
1), for
the duration of the experiment. To minimize drift in eye position,
paralysis was maintained with an infusion of vecuronium bromide
(Norcuron, 0.1 mg · kg
1 · h
1). The animal was artificially ventilated
with medical grade air. Body temperature was kept at 37°C with a
thermostatically controlled heating pad. The electrocardiogram,
electroencephalogram, autonomic signs, and rectal temperature were
continuously monitored to ensure the anesthetic and physiological state
of the animal. The pupils were dilated using topical atropine and the
corneas were protected with +2D gas-permeable hard contact lenses.
Supplementary lenses were selected by direct ophthalmoscopy to make the
lens conjugate with the display. The locations of the foveae were
recorded using a reversible ophthalmoscope.
For recordings in area MT, tungsten-in-glass electrodes (Merrill
and Ainsworth 1972
) were introduced by a hydraulic microdrive into the anterior bank of the superior temporal sulcus (STS) and were
driven down through the cortex and across the lumen of the STS into MT.
The location of unit recordings in MT was confirmed by histological
examination of the brain after the experiment, using methods described
in Lisberger and Movshon (1999)
. For recordings in V1,
the electrode was introduced just posterior to the lunate sulcus. After
the electrode was in place, agarose was placed over the craniotomy to
protect the surface of the cortex and reduce pulsations. Single units
were isolated using a dual time-window discriminator (Bak Electronics,
DDIS-1), and action potentials were amplified conventionally and
displayed on an oscilloscope. Both a filtered version of the neural
signals and a tone indicating the acceptance of a waveform as an action
potential were played over a stereo audio monitor, and the time of each
accepted waveform was recorded to the nearest 10 µs for subsequent
analysis. The recording sessions lasted between 84 and 120 h. The
units included in this study are from 29 electrode penetrations in MT
at different sites in nine monkeys and 24 penetrations in V1 in two monkeys.
Experiments on the awake monkey were conducted using an experimental
and training protocol that has been described before (e.g.,
Lisberger and Westbrook 1985
) in a monkey that had been trained to fixate spot targets. Eye movements were measured with the
scleral search coil method (Judge et al. 1980
), using
eye coils that had been implanted with sterile procedure while the animal was anesthetized with isofluorane. In a separate surgery, stainless steel plates were secured to the skull and attached with
dental acrylic to a cylindrical receptacle that could be used for head
restraint. In addition, a craniotomy was performed over the STS and a
cylinder was attached to the surface of the skull (Crist Instruments).
During experiments, the head was immobilized by using a post to attach
the implanted receptacle to the ceiling of a specially-designed primate
chair. Microelectrodes were introduced through the cylinder into the
cortex and lowered into area MT using the same approach as in the acute
experiments. The animal was rewarded with juice for accurately fixating
a target at the center of the display. Experiments were run daily,
typically lasting 2-3 h.
All experiments in awake and anesthetized monkeys followed protocols that had received prior approval by the Institutional Animal Care and Use Committee at UCSF.
Stimulus presentation for acute experiments
After isolating a single unit in MT or V1, we mapped its receptive field on a tangent screen by hand. We recorded the spatial position of each single unit's receptive field and, for the majority of neurons, the size of the minimum response field. All of the neurons reported in this pair of papers had receptive field centers within 12° of the fovea.
After the receptive field location was determined, a mirror was
positioned such that a random-dot texture on a display oscilloscope fell within the receptive field of the isolated neuron. Visual stimuli
were then presented on an analog oscilloscope (Hewlett-Packard models
1304A and 1321B, P4 phosphor), using signals provided by D/A converter
outputs from a PC-based digital signal processing board (Spectrum
Signal Processing). This system affords extremely high spatial and
temporal resolution, allowing a frame refresh rate of 500 or 250 Hz and
a nominal spatial resolution of 64,000 × 64,000 pixels. The apparent
motion created by our display is effectively smooth at these sampling
rates (Churchland and Lisberger 2001
; Mikami et
al. 1986
). The display was positioned 65 cm from the animal and
subtended 20° horizontally by 20° vertically. Experiments were
performed in a dimly lit room. Due to the dark screen of the display,
background luminance was beneath the threshold of the photometer, less
than 1 mcd/m2.
Experiments consisted of a sequence of brief trials with an inter-trial interval of about 700 ms. All trials began with the appearance of a stationary, uniform random dot texture (0.75 dots/°2). Because many neurons in MT respond better if the moving texture is surrounded by a field of stationary dots, we used two nonoverlapping textures of the same dot density. A surround texture remained stationary for the duration of the trial, while a texture in the center of the screen moved. For all trials, the textures appeared and were stationary for 256 ms before starting to move. After the motion was completed, the dots remained visible for an additional 256 ms. Motion in the center texture was used to characterize the preferred direction by moving the texture in eight directions for either 512 or 256 ms. After the preferred direction was identified, the preferred speed of the neuron was measured by moving the center texture in the preferred direction at speeds of 0.125, 0.25, 0.5, 1, 2, 4, 8, 16, 32, 64, and 128°/s.
After texture direction and speed had been optimized for the neuron
under study, we conducted an iterative recording procedure to center
the receptive field on our display. We divided the center texture into
small units that were either 2 or 4° across and measured the response
of the neuron for motion of each small texture. We then determined the
spatial extent of the receptive field using an on-line analysis routine
and, if necessary, adjusted the mirror to better center our visual
stimulus on the neuron's receptive field. If the position of the
mirror had been changed, we once again determined the spatial extent of
the receptive field on our monitor. Because the response strength of
many neurons in area MT depends on the size of the moving texture
(Allman et al. 1985a
,b
), we also optimized the size of
the texture by adjusting the center and surround textures so that that
moving texture subtended 2.5, 5, 10, 15, and 20°. Once we were
satisfied that the stimulus had been optimized for the response
preferences of the neuron under study, we conducted the experiments
described in RESULTS.
Stimulus presentation for awake animal
The presentation of stimuli for the awake animal was similar.
Minor differences were: dot density in the textures was 0.25 dots/°2; the moving textures were not
surrounded by a field of stationary dots; instead of using anesthesia
and paralysis to prevent the eyes from moving, recordings were made
while the monkey fixated a stationary spot and ignored the motion of
the eccentric texture. Fixation was excellent, so that smooth eye
motion under such conditions was minimal, on the order of 1% of the
stimulus speed (see Churchland and Lisberger 2001
,
monkey M, for a full analysis).
Data acquisition and analysis
Experiments were controlled by a computer program running on a UNIX workstation and a Windows NT PC running the real-time extension RTX (VenturCom). The two computers were networked together: the UNIX workstation provided an interface for programming target motion and customizing it during recording from a neuron, while the PC provided real-time control of target motion and data acquisition. The times of spikes were recorded by the PC and sent over the network to the UNIX workstation, which combined them with codes indicating the target motion that had been commanded and stored both for subsequent analysis. For the recordings made in the awake monkey, analog voltages proportional to horizontal and vertical eye position and eye velocity were sampled at 1,000 Hz on each channel and stored for subsequent verification of good fixation.
In both anesthetized and awake recordings, each experiment consisted of a list of trials, where each trial presented a different target motion. A different seed was used to create the pseudorandom sequence of initial dot positions in each trial. As a result, every trial presented a different texture, even for repetitions of the same target motion. Trials were sequenced by shuffling the list and presenting the trials in a random order until all the trials in the list had been presented. The list was then shuffled and repeated again until enough repetitions of each stimulus had been obtained. In the awake recordings, the monkey was required to fixate a stationary spot with an accuracy of 2°. If the monkey broke fixation, the trial was aborted and placed at the end of the list to be presented again before the list was shuffled and repeated.
Data were analyzed by aligning all the responses to identical trajectories of target motion on the onset of target motion and accumulating poststimulus time histograms with a binwidth of 1 ms. For the purposes of presentation, the histograms were built with a binwidth of 8 or 16 ms. Background responses were eliminated by creating a histogram for trials that presented a stationary stimulus, computing the mean firing rate during the interval when other stimuli were moving, and subtracting this scalar from the firing rate in every bin of every other histogram. We then measured firing rate from the background-corrected histograms to determine the stimulus selectivity of each neuron and to quantify the results of each experiment. Specific analyses are presented at the relevant places in RESULTS.
To determine whether neurons should be included in our analysis, we
estimated the directional selectivity using a directional index (DI)
|
(1) |
For the analysis shown in the final section of RESULTS, it
was important that the excitability of the neuron did not change over
the course of the recording. To assay whether a neuron's responses
were stationary, we measured the number of spikes recorded during the
period 150-250 ms after motion was initiated for each presentation of
motion in the preferred direction. We then fit first-, second-, and
third-order polynomials to the number of spikes found in the sequence
of trials, ordered by the time of stimulus presentation
|
(2) |
|
(3) |
|
(4) |
| |
RESULTS |
|---|
|
|
|---|
Properties of transient responses in MT neurons
Many neurons in area MT undergo a short-term adaptation that
shapes the temporal dynamics of their response to moving stimuli (Lisberger and Movshon 1999
). As illustrated in Fig.
1A, the average response to a
step of target speed consists of an initial transient followed by a
rapid decrease to a sustained firing rate that remains steady for the
duration of the motion. The transient represents the unadapted response
of the neuron to motion, while the sustained phase represents the
adapted response of the neuron.
|
To describe the time course and amplitude of the adaptation we sought
to understand, we begin with a thorough analysis of the transition from
the transient high firing rate to the lower sustained responses of MT
neurons and the time-dependent recovery from adaptation. For each MT
neuron we recorded with a transient response, we made histograms like
that in Fig. 1A describing the time average of the response
to steps of target velocity of the neuron's preferred direction and
speed. We then fit the transition from transient firing to sustained
firing with single exponentials of the form
|
(5) |
is the time constant of the exponential. Fits were made
over a 200-ms interval starting from the peak of the neuron's
response. Equation 5 typically provided an excellent fit to
our data, as shown by the solid curve overlying the histogram in Fig.
1A. Using the parameters from the fits, we defined the
transient-sustained ratio (TSR) as
|
(6) |
To assess the time course of recovery of the neuron from its adapted state, we used a condition/test paradigm that consisted of sequential presentation of two stimulus motions. We measured the effect of the initial motion (the conditioning motion) on the neuron's response to the subsequent motion (the test motion). If the conditioning motion did not cause adaptation, then the response to the test stimulus would be the same as if there had been no conditioning motion at all: the neuron would display its stereotypical transient firing rate. If the conditioning stimulus did adapt the neuron, then the transient response to the test stimulus would be reduced: reduction to the level of the sustained rate would represent maximal adaptation.
In the experiments used to demonstrate the temporal properties of the recovery from adaptation, the conditioning and test motions were delivered at the same locations in the receptive field and were always of the direction and speed that drove the largest response of the neuron. The response to each test motion was calculated by subtracting the response to conditioning motion alone from the response to conditioning/test motion. We initially used conditioning and test motions that were only 64 ms in duration because these seemed sufficient to document the adaptation of a transient with a duration less than 64 ms: subsequent experiments use longer duration motions and demonstrated that the adaptation is specific to the transient response.
The recovery from adaptation is shown in Fig. 2A for an example MT neuron. When the test motion occurred immediately after the end of the conditioning motion (traces labeled CTI = 0), the response to the conditioning/test motion (histogram) followed the response to the conditioning motion (bold, continuous trace) nicely in the first half of the response before the response to the test motion would have begun. In the second half of the response, which should have been driven by the test motion, the response to conditioning/test motion was only slightly larger than that to the conditioning motion alone, indicating that the response to the test motion was strongly attenuated. As the conditioning/test interval (CTI) increased from 32 to 64 ms and eventually to 256 ms, the size of the response to the test motion gradually recovered. We quantified the time course of the recovery from adaptation by measuring the difference in mean firing rate between the responses to the conditioning/test stimulus and the test stimulus alone during the 64-ms interval starting 64 ms after the onset of the test motion. Plotting this difference firing rate as a function of the CTI (Fig. 2B) revealed that recovery was complete for this example neuron within 256 ms and was fit well by an exponential with a time constant of 73 ms (continuous curve in Fig. 2B). We measured the time constant of recovery from adaptation for 86 MT neurons and found a broad distribution with a mean of 86 ms (median =78 ms) as shown in the histogram of Fig. 2C.
|
Lisberger and Movshon (1999)
linked adaptation to the
transition from transient to sustained response by showing that the amount of adaptation demonstrated by two-step stimuli was strongly correlated with the transient-sustained ratio of the neuron under study. We obtained the same strong correlation in our larger sample of
neurons. Lisberger and Movshon (1999)
also found that
the adaptation demonstrated in Fig. 2 was very similar when the
conditioning motion was a step of target speed with a duration of 512 ms, implying that brief motion was sufficient to fully adapt the neural
response. In the present series of two papers, we have taken advantage
of the same experimental design to probe the stimulus selectivity of
the adaptation. We have systematically varied the visual properties of
the conditioning motion while probing the adaptation with a test motion
consisting of the preferred stimulus for the neuron under study.
Experimental design for evaluating input-specific mechanisms of adaptation
Two input-specific mechanisms could account for the adaptation
observed in area MT: short-term depression of the efficacy of synapses
that provide input from V1 to area MT (Chance et al. 1998
; Kayser et al. 2001
) or adaptation
occurring at the level of V1 and simply replayed in area MT. To
investigate whether either of these input-based mechanisms underlies
the adaptation observed in area MT, we took advantage of the fact that
the receptive fields of MT neurons are large in comparison to those of
V1 neurons at corresponding eccentricities and the common assumption
that MT neurons have larger receptive fields because they pool the
responses of neurons in V1 that have different receptive field
locations. We performed condition/test experiments in MT using small
textures designed to stimulate two different sets of inputs from V1 to MT. We induced adaptation with conditioning motion in one part of the
receptive field of an MT neuron and probed adaptation with test motion
in a different part of the receptive field. If adaptation in MT occurs
in the input pathway from V1 to MT, then adaptation should not transfer
from one portion of an MT receptive field to another. If adaptation is
derived from mechanisms that operate within area MT, then adaptation
should transfer from one location to another within a single MT
receptive field. In the next sections of RESULTS, we
demonstrate that adaptation in area MT transfers between spatial
locations that activate different neurons in V1. We also confirm that
the motion adaptation present in MT neuron responses is not present in
the direction-selective neurons in V1.
Spatial transfer of adaptation in MT neurons
Figure 3 illustrates the results of an experiment that tests the spatial extent of the transfer of adaptation. First, we mapped the receptive field of each of 67 neurons in area MT by placing small (4 × 4°) textures at 25 different locations on our display and measuring the response to motion across each location. These responses are summarized in the histograms at each of the 25 locations in Fig. 3A and in the continuous map derived in Fig. 3B. All of our neurons had receptive field centers located within 10° of the fovea (Fig. 3A, ×), and their receptive fields typically covered 2 × 2 or 3 × 3 of the small textures used for mapping. After the spatial extent of the neuron's receptive field had been determined, we chose two locations that were separated by at least 2° (1.2° in awake animals) and where motion excited the neuron approximately equally. For the neuron used to create Fig. 3, the locations of the two textures are indicated by the gray and black dashed boxes. Corresponding black and gray bars have been placed below the histograms in Fig. 3, C-H, to indicate the times when each of the stimuli was moving. At their closest point, the distance between the two textures was 2.6°. Because the center of the receptive field for this neuron was 6° from the fovea, 2.6° is about four times larger than one receptive field width in area V1.
|
Figure 3, C and D, shows that the neuron had similar responses to motion in each patch alone: large transients followed by sustained firing. When motion of the adapting stimulus at the gray site was followed immediately by motion of a test stimulus at the black site (histogram in Fig. 3E), the early part of the response matched the response to the adapting stimulus presented alone (thick gray trace in Fig. 3E). The later part of the response, which was driven by the motion of the test stimulus, failed to show a second transient, and the firing rate simply continued at approximately the sustained level from the early part of the response. To isolate the response to the test motion after adaptation, we subtracted the response to the conditioning motion (Fig. 3C) from the response to the sequence of conditioning and test motions (Fig. 3E). The resulting "difference" histogram (Fig. 3G) reveals that the response to the test motion consisted of a small sustained response without any transient. For comparison, the response to the test motion without prior adaptation had a large transient (Fig. 3D). Figure 3, D, F, and H, shows the results of the same analysis when the presentation order was reversed so that motion at the black location provided the conditioning stimulus and motion at the gray location the test stimulus. The difference histogram (Fig. 3H) again revealed that the isolated response to the test motion after adaptation had only a small transient response and was very different from the control response to the same motion (Fig. 3C).
Adaptation in one spatial location significantly reduced the amplitude of the transient response to motion in another location for most of the neurons in our sample population. We quantified this effect by comparing the transient-sustained ratio of each neuron in the absence and presence of conditioning motion. We used Eq. 6 to compute the transient-sustained ratio, but we obtained the values of fmax and fsus by measurement from the difference firing rates calculated as illustrated in Fig. 3, G and H, fmax was taken as the peak response in any 32-ms interval within 150 ms after test motion began; fsus was defined as the average firing rate during the period 150 to 250 ms after the motion in the test location began. In Fig. 4A, all MT neurons lie below the line of slope 1, indicating that the adaptation from the conditioning motion at one site caused a decrease in the transient-sustained ratio for a test motion at another site. The decrease was statistically significant in 52 of the 67 MT neurons tested in this experiment (filled symbols, P < 0.05, paired t-test) and was clearly present in neurons recorded in both anesthetized (squares) and awake (triangles) monkeys. We did not test for differences between neurons recorded in these two preparations because we could not compensate for effects of differences in the exact stimulus conditions and in the criteria for selecting neurons for study.
|
The degree of the transfer of adaptation from motion in one spatial
location to another was quantified further by computing the transient
index (TI) as
|
(7) |
0.24 and 0.32 when the test motion was in the locations indicated, the black and gray
bars and squares, respectively. Across our sample, there was a broad
range of values of TI (Fig. 4B), and the mean TI was 0.23. Thus the adaptation induced by conditioning motion in one portion of
the receptive field caused, on average, a 77% reduction (100 × [1.0-0.23]) in the amplitude of the transient caused by subsequent
test motion at a different location.
Motion in the conditioning patch had a much smaller effect on the
sustained firing rate evoked by the test motion (Fig. 4C). For this measure, the points plotted much closer to the line of slope
one, and the difference was statistically significant in only 6 of 67 MT neurons (
, P < 0.05, paired t-test).
Thus adaptation induced by motion at one site altered selectively the
transient response to motion at a different site.
The data in Fig. 4 were computed after isolating the adapted response to the test motion by computing the difference between the firing rate evoked by the conditioning/test motion and the firing rate evoked by the conditioning motion alone (as in Fig. 3). This subtraction ought to be the correct way to isolate the adapted response because it removes the tail of firing rate that is related to the end of the conditioning motion and reveals the onset of the response to the test motion. However, it also incorporates an assumption of linearity in the responses of the neurons and might underestimate the true value of TI. To place an upper limit on the size of the transient response to the test motion after adaptation, we also computed TI from the response to conditioning motion followed by test motion without subtracting the response to conditioning motion alone. We made the measurement at the same latency used for the measurements that appear in Fig. 4. For this conservative estimate of the effect of conditioning motion on test response, the mean value of TI was 0.47. We conclude that the adaptation induced by conditioning motion in one portion of the receptive field caused at least a 53% reduction in the amplitude of the transient caused by the subsequent test motion at a different location and probably as much as a 77% reduction.
Time course of recovery from adaptation in MT neurons
In 24 neurons, we studied the time course of recovery from
adaptation to ask whether the recovery followed the same time course when the test and conditioning motions were in different locations as
it did when they were in the same location (Lisberger and
Movshon 1999
). The data in Fig. 5
show an example of the histograms accumulated for one neuron in this
experiment. These experiments were similar to those in Fig. 2 in that
we varied the interval between the offset of the conditioning motion
and the onset of the test motion. However, conditioning and test
motions were 256-ms duration (instead of 64 ms) and appeared in
separate spatial locations in the visual field. As expected, Fig.
5A shows that the transient response to the test motion was
strongly attenuated when the CTI between the end of the conditioning
motion and the start of the test motion was zero, but the conditioning
motion did not cause any effect on the sustained response to subsequent
test motion. The transient response recovered gradually as the CTI was
increased from 32 to 256 ms.
|
To summarize the recovery from adaptation, for each of the 24 neurons tested, we measured the TI from the difference firing rate (conditioning/test minus conditioning motion alone) at each CTI. We then fit the relationship between TI and CTI with an exponential of amplitude 1.0 to measure how quickly the transient response of each neuron recovered. For each neuron, we compared the time constant of recovery for conditioning/test motions at different spatial locations with that for conditioning/test motions at the same spatial location. With the exception of a few neurons, we found good general agreement between the time constants of recovery for conditioning/test stimuli at the same versus different locations (Fig. 5B). Four of the five exceptions recovered much faster for conditioning/test stimuli at the same location than they did for conditioning/test stimuli at different locations. These exceptions might be the reflection of different mechanisms of adaptation for the conditioning/test stimuli at the same versus different locations, but might also result from the use of different durations of the conditioning and test motions for the different experiments. Overall, the similarity in the recovery from adaptation favors the conclusion that there is a common underlying mechanism of adaptation that operates across the spatial extent of the receptive field.
Comparison of receptive and adaptation fields in MT neurons
We define the receptive field as the part of the visual field in which test motions alone evoked responses in the neuron, and we define the adaptation field as the part of the visual field where conditioning motion caused a reduction in the transient response to subsequent test motion near the center of the receptive field. To measure the adaptation field of the neuron, conditioning motion was placed at different spatial locations around a central test location. For five neurons, we used eight conditioning motion locations surrounding the center of the response field at a single distance. For the neuron illustrated in Fig. 6 and for eight other neurons, we used 24 different conditioning locations at three distances and eight angles relative to the testing location in the center of the receptive field. The five histograms in Fig. 6, A-E, show the results for five of these conditioning motion locations. In Fig. 6, A and E, the conditioning location (bold square) was entirely outside the receptive field (dashed circle), and the response to the motion at the test location (less bold square) showed a large transient even when the test motion immediately followed the conditioning motion. However, when the conditioning motion was placed inside the receptive field of the MT neuron, there was a reduction in the amplitude of the transient evoked by the test motion (Fig. 6, B-D). The reduction was most complete for the conditioning motion location that evoked the largest response itself (Fig. 6C).
|
Each neuron's adaptation field was constructed by measuring the effect
of the location of conditioning motion on the transient response to the
test motion. To summarize the results of this experiment for each
neuron, we created graphs such as that in Fig. 6F. This
graph plots the transient index measured for each conditioning motion
location versus the response evoked by the conditioning motion at that
location. The latter was quantified by measuring the average firing
rate over the interval from 150 to 250 ms after the onset of the
conditioning stimulus. For the neuron illustrated in Fig. 6, the amount
of adaptation was closely related to the size of the response evoked by
the adapting stimulus alone. There was an inverse relationship between
the transient index and the response to the conditioning motion
(correlation coefficient of
0.82). The same result was obtained in
all 14 neurons we studied, with all but 1 neuron showing correlation coefficients between
0.4 and
1.0 (Fig. 6H) that were
statistically significant (2-tailed t-test,
P < 0.05). In Fig. 6F, we have emphasized the relationship between the amount of adaptation and the response caused by conditioning motion, but it is also important to note a
number of sites that plot at 0.0 on the x axis but below 1.0 on the y axis. These points represent conditioning motion
locations that evoked little or no response but still caused
substantial adaptation of the response to the testing motion.
To quantify the sizes of the receptive and adaptation fields, we fit
each with two-dimensional Gaussian functions with the same value of
along each axis (Britten and Heuer 1999
). These are
summarized in Fig. 6G, which shows contour plots derived
from of the Gaussian fits to the response to the conditioning motion (continuous contours) and to 1 minus the transient index (dashed contours) for the same neural responses shown in the top
panels. The two contour plots are centered at the same location.
However, the adaptation field was larger than the receptive field for
the neuron illustrated in Fig. 6: for each contour value (e.g., 0.9, 0.6, and 0.3), the contour for adaptation lies outside that for the
response evoked by the conditioning motion itself. We observed the same
result for all 14 neurons tested in this experiment: in a plot of the
value of SD used for the Gaussian fit for adaptation as a function of
that for the response (Fig. 6I), each neuron plotted above
the line of slope 1. However, the adaptation field was never more than
two times the size of the receptive field for the 14 neurons we studied
in area MT. Thus adaptation in MT is on a spatial scale that is
slightly larger than that of the receptive fields in MT.
Absence of spatial transfer of adaptation in V1
Can the large spatial scale of adaptation in MT be attributed to a
similar scale of adaptation in V1? Many researchers have shown that the
responses of V1 neurons to stimuli inside their receptive fields can be
modified by stimuli outside their receptive fields (Cavanaugh et
al. 1998
; Hubel and Wiesel 1965
; Knierim and van Essen 1992
; Walker et al. 1999
;
Zipser et al. 1996
). We therefore measured the effect of
conditioning motion outside the receptive field on responses to motion
inside a V1 receptive field. Stimuli presented to V1 neurons were
comparable to those used in MT: direction tuning was assessed with the
motion of a 5 × 5° dot pattern with a dot density of 0.75 dots/°2. Of the 393 V1 neurons we isolated, we
restricted our analysis to the 63 neurons whose directional index
exceeded 0.5 (see METHODS). As previously reported
(Movshon and Newsome 1996
), the majority of the
direction-selective neurons were found either directly above layer 4 or
in layer 6 of cortex. The center of the receptive fields of the neurons
recorded from in V1 varied from 1 to 5° eccentric, and the receptive
field diameters were less than 1°.
The design of the conditioning/test experiment was the same in V1 as it
had been in MT. First, we measured the responses of V1 neurons to test
motion placed directly in the receptive field of the neuron (fine
dashed box at center of Fig.
7A) and moving in the
neuron's preferred direction and speed. Next, we measured the response
of the neuron to test motion immediately preceded by conditioning
motion in one of eight locations surrounding the test motion (bold
dashed boxes in Fig. 7A). The locations of the conditioning
motion were not customized for the size of the V1 receptive fields but
rather were the same locations used for conditioning motion in
recordings from neurons in MT: a separation of at least 1.2° was
maintained between the conditioning and test motions. We were able to
record responses in the conditioning/test experiment from 39 of the 63 direction-selective neurons. We studied only direction-selective
neurons because these are the neurons that project from V1 to MT
(Movshon and Newsome 1996
).
|
Direction-selective neurons in V1 did not show any consistent adaptation when test motion within the receptive field was applied immediately after conditioning motion outside the classical receptive field. For example, the V1 neuron shown in Fig. 7B had a typical response profile: a large response to the test motion alone (Fig. 7B, center) and an equally large response after conditioning motion at eight surrounding locations (Fig. 7B, surrounding histograms). In each of the eight surrounding histograms, the conditioning motion, presented at times indicated by the bold horizontal bars below the histograms, also failed to cause any response because it was out of the receptive field. Note also that the neuron illustrated in Fig. 7B responded with a brief burst of spikes after the appearance of a stationary texture well before any part of the texture began to move. This neuron's response is typical of the responses found in V1 in that it lacks the transient response that is observed in area MT. Figure 7C shows results for the V1 neuron that showed the largest transient response in our sample. Again, responses to test motion were not significantly altered by the presence of preceding motion outside the classically defined receptive field.
To quantify the effect of conditioning motion outside the
classical receptive field on the response of V1 neurons to test motion
inside the receptive field, we again isolated the response to the test
motion by subtracting the response to the conditioning motion along
from that for each conditioning/test stimulus. We then measured the
peak firing rate in a sliding 32-ms bin for the test motion alone and
for the isolated responses to test motion after conditioning motion in
each location. In the polar plots we used to summarize these data
(Figs. 8, A and B),
the dashed circles indicate the 95% confidence intervals (mean ± SE) for the peak firing rate during test motion alone. Each symbol
shows the response for test motion following conditioning motion at a
single location, with the symbol plotted at an angle indicating the
location of the conditioning motion, and a distance from the center of
the graph indicating the peak firing rate. For these two neurons, and
all other neurons, the effects of conditioning motion on the test
response were small and irregular. To assess whether the effect of
conditioning motion on the test response was statistically significant,
we did paired t-tests for each set of conditioning and test
motion. Given that eight different comparisons were made, we used a
criterion of P < 0.018 to determine significance
(Bonferroni's correction, correlation = 0.5) (Miller 1981
), instead of the usual P < 0.05. Neither
of the units shown in Fig. 8, A and B, and only 2 of the 39 neurons in our population, showed significant effects of
conditioning motion at any location using this criterion.
|
It is possible that adaptation might be consistently present in a
restricted location, but not reach statistical significance in tests
based on all conditioning locations. To evaluate this possibility, we
analyzed the data in two additional ways. 1) To test for a
significant effect of the position of the conditioning stimulus, we
used circular statistics (Rayleigh's test) to test for an effect of
location of the conditioning stimulus (Batschelet 1981
).
This analysis revealed the 3 of 39 neurons had statistically significant effects of conditioning location. The effects were all
small. 2) To test for a relationship between the site of an effective conditioning stimulus and the preferred direction of the
neuron, we rotated the polar graphs for all 39 neurons we studied so
that the conditioning site located in the preferred direction of motion
relative to the center of the receptive field was plotted to the right.
We then normalized each response by the response of the same neuron to
the test motion alone and averaged. This revealed a uniform
distribution with a normalized transient response amplitude of one at
every site of conditioning motion (open triangles Fig. 8C).
Input-specific adaptation might not be excluded by our data if the inputs from V1 neurons were organized so that the spatial locations of maximum adaptation in V1 were aligned in the inputs from V1 to each MT neuron. To determine the maximum adaptation that could arise from this organization, we rotated the polar plots so that the conditioning location that induced maximal adaptation of the test response was plotted to the right. We then normalized each neuron's responses for the maximum and averaged across neurons. This revealed about 40% adaptation of the transient response at the site of the maximal adaptation, normalized transient response amplitudes close to one at all other sites, and a hint of enhancement at the conditioning locations opposite to the maximal adaptation (open triangles, Fig. 8D). We think that the reduction of the transient response at one location in Fig. 8D results from response variability rather than from conditioning. If it were caused by conditioning, then conditioning motion at neighboring locations also should have caused adaptation. We therefore conclude that the spatial extent of adaptation in V1 is limited to the classical response field.
Quantitative comparison of adaptation fields of MT and V1 neurons
Figure 8, C and D, also plots the results of the same analyses described in the preceding text, of the spatial extent of adaptation, for MT neurons. When the adaptation fields were rotated so that the preferred direction of motion was to the right (Fig. 8C), MT neurons (filled circles) showed approximately the same adaptation for all locations of the conditioning motion and much more adaptation than did V1 neurons (open triangles) at all locations. When the adaptation fields were rotated so that the location of the conditioning motion causing the largest adaptation was plotted to the right (Fig. 8D), MT neurons (filled circles) showed the largest adaptation for the conditioning location, as expected given the way the graph was created, and as found for V1 neurons (open triangles). However, MT neurons showed adaptation at all other locations of conditioning motion, while V1 neurons did not.
Absence of transient responses to motion onset in V1 neurons
Most direction-selective V1 neurons did not show the transient response to a step of target speed that is the signature of adaptation in MT. To quantify the apparent difference, we used a stimulus consisting of a 5 × 5° patch of dots moving with the preferred direction and speed of the V1 neuron under study and measured the transient-sustained ratio. Figure 9 shows histograms from five V1 neurons and five MT neurons. While a few V1 neurons responded with small transients to the onset of stimulus motion (e.g., Fig. 9A, top left histogram), the majority of V1 neurons did not show transient responses. Neurons were chosen for illustration in Fig. 9 by ordering them according to the value of transient-sustained ratio. The histograms at the top of each column show the responses of the neurons that had the largest transient-sustained ratio in our sample from V1 and MT, while the third histograms in each column approximate the median response.
|
Figure 10B summarizes the
difference in the distribution of transient-sustained ratios in V1 and
MT. As before, transient-sustained ratio was calculated by Eq. 6: fmax was taken as the peak
response in any 32-ms interval within 150 ms after motion began;
fsus was defined as the average firing
rate during the period 150 to 250 ms after the motion began. One V1
neuron had a transient-sustained ratio more than 2 and a few had
transient-sustained ratios as high as 1.4. However, the population of
V1 neurons is grouped around a transient-sustained ratio of 1 with a
mean value of 1.02. For MT neurons, transient-sustained ratios could be
larger than 6 and the mean value was 1.93. The lack of transient
responses to the onset of motion in V1 neurons may be surprising, since there are many reports of transient responses to flashed stimuli (Muller et al. 1999
; Nelson 1991
;
Tolhurst et al. 1980
). The lack of transient responses
for our stimuli may be a result of using a low dot density of 0.75 dots/°2: V1 neurons may have only responded
when an individual dot crossed their receptive fields. Because the dot
texture for each presentation was randomly changed, the time that a dot
would cross the receptive field of a V1 neuron would be different for
each trial. Whatever the basis for the lack of transient response to
the onset of motion, direction-selective neurons in V1 do not show the
transient firing that is observed in MT when they are tested with the
same visual stimuli.
|
Direct test of intrinsic spiking-related mechanisms of adaptation
The previous sections showed that the amount of adaptation of MT neurons responses caused by conditioning motion at a given site in the receptive field was related to the size of the response caused by the conditioning motion. However, data presented so far do not distinguish whether the adaptation was a direct effect of the neuronal response or if the key factor was the location of the conditioning motion relative to the center of the receptive field. This is a subtle difference in terms of phenomenology but a critical one in terms of constraining the mechanism of adaptation in MT.
To assay whether the neuron's own activity causes adaptation, we used
two approaches that took advantage of the trial-by-trial variability of
the response during the initial transient (Softky and Koch
1992
). For each neuron, we first defined a transient interval
starting at the onset of the response and having a duration set to the
time constant of the decay of firing rate from Eq. 5
(vertical dashed lines for an example neuron in Fig. 10A),
and a subsequent interval as the next 16 ms. We then counted the number of spikes in each of these two intervals for every trial and asked if
they were correlated. If short-term adaptation results from the
neuron's own activity, then the number of spikes in the subsequent interval should be related to the number of spikes in the transient interval. Figure 10B uses the size of each symbol to
indicate the number of instances of a given combination of number of
spikes in the transient (x axis) and subsequent
(y axis) intervals. Spike counts in the transient interval
ranged from zero to five, but there was not a strong relationship
between the number of spikes during the transient interval and the
subsequent interval. The correlation coefficient was 0.13 and was not
significantly different from zero (t-test, P > 0.05) (Sokal and Rohlf 1995
).
We recorded a sufficient number of repeats of the preferred stimulus (more than 65) to perform this analysis in 66 neurons. However, only 35 of the 66 neurons were admitted for the analysis by the criterion that their excitability remained stationary for the recording period (see METHODS). It is important that the neuronal response remain stationary for the duration of the recording because such fluctuations in excitability can cause inaccurate overestimates of correlations. The histogram in Fig. 10C shows that the distribution of correlation coefficients was centered near zero and only two neurons had statistically significant, positive correlations (filled histogram bar).
We used a second analysis to demonstrate directly that the transition from transient to sustained firing is not produced by a neuron's own spikes. If spikes caused adaptation, then for trials in which there were no spikes produced during the transient interval, the firing rate should be higher in the subsequent interval. The transient should simply be delayed. Figure 11A shows the distribution of spike counts during the transient interval for the same neuron whose data are shown in Fig. 10, A and B. Of 265 trials, there were 26 trials in which no spikes were observed during the transient interval. Figure 11B shows the response histogram created for those 26 trials. Following the period in which there were no spikes, the response of the neuron followed very nearly the average response for all other trials. The lack of a large delayed transient indicates that the neuron has undergone adaptation during the transient period despite not having produced any spikes. The response of the neuron following the transient period also indicates that the neuron was capable of a normal response and was not somehow impaired during that trial.
|
We were able to perform this analysis for 25 neurons that had at least four trials with no spikes during the transient period. For each neuron, we computed the mean firing rate for the 16-ms interval immediately after the initial transient period separately for trials with and without firing in the transient period. In general, the firing rate after a transient interval with spikes was the same or higher than the firing rate after a transient interval without spikes so that most points in Fig. 11C plot above the line of slope one. The effect of the presence or absence of spikes in the transient interval on subsequent firing was statistically significant in 4 of the 25 neurons (Fig. 11C, filled symbols). In each instance, these neurons had a higher firing rate after the transient period when there were spikes during the transient period, the opposite of the result predicted if spikes in the transient interval cause short-term adaptation.
One final prediction of adaptation based on intrinsic spiking mechanisms in MT neurons would be that the background firing rate after the stimulus might be depressed relative to befor