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Previous Article | Next Article
The Journal of Neuroscience, April 15, 2002, 22(8):3189-3205
The Timing of Response Onset and Offset in Macaque Visual Neurons
Wyeth Bair1, 2, James R. Cavanaugh2, Matthew A. Smith2, and J. Anthony Movshon1, 2 1 Howard Hughes Medical Institute and 2 Center for Neural Science, New York University, New York, New York 10003
ABSTRACT
TOP
ABSTRACT
INTRODUCTION
We used fast, pseudorandom temporal sequences of preferred and antipreferred stimuli to drive neuronal firing rates rapidly between minimal and maximal across the visual system. Stimuli were tailored to the preferences of cells recorded in the lateral geniculate nucleus (magnocellular and parvocellular), primary visual cortex (simple and complex), and the extrastriate motion area MT. We found that cells took longer to turn on (to increase their firing rate) than to turn off (to reduce their rate). The latency difference (onset minus offset) varied from several to tens of milliseconds across cell type and stimulus class and was correlated with spontaneous or driven firing rates for most cell classes. The delay for response onset depended on the nature of the stimulus present before the preferred stimulus appeared, and may result from persistent inhibition caused by antipreferred stimuli or from suppression that followed the offset of the preferred stimulus. The onset delay showed three distinct types of dependence on the temporal sequence of stimuli across classes of cells, implying that suppression may accumulate or wear off with time. Onset latency is generally longer, can be more variable, and has marked stimulus dependence compared with offset latency. This suggests an important role for offset latency in assessing the speed of information transmission in the visual system and raises the possibility that signal offsets provide a timing reference for visual processing. We discuss the origin of the delay in onset latency compared with offset latency and consider how it may limit the utility of certain feedforward circuits.
Key words: macaque monkey; primary visual cortex; area MT/V5; lateral geniculate nucleus; spike timing; response latency; integration time; inhibition; spontaneous activity; temporal dynamics
INTRODUCTION
In the earliest studies of neuronal response in the visual system, ON and OFF responses to light were recognized because light onset and offset both produced striking transient bursts of action potentials (Adrian and Matthews, 1927
). If it had been otherwise, if cells had produced ON responses only and did not adapt so much, then perhaps response offsets would have received more attention in the last 75 years. If asked whether neurons in the visual system turn on or turn off sooner after a scene change, one might guess the former because a brief pulse of light causes a response that rises rapidly and decays slowly, outlasting the flash (Adrian and Matthews, 1927
Here we study the latency of response onset and offset in several areas of the visual system because doing so offers a chance to interpret integration strategies in each area in the context of what is known about the other areas. To make this comparison across visual areas and cell classes, we attempt to generalize the notion of preferred, antipreferred, and null (or neutral) stimuli across three levels in the visual system. We optimized stimuli for the center-surround receptive fields (Barlow, 1953
In the retina and LGN, there is probably no strong opponency between the ON and OFF pathways (Casagrande and Norton, 1991
For all cell types that we studied, response onset came later than response offset. We discuss how much of the onset delay is caused by neuronal integration time (defined to be the time from initial depolarization to spike threshold, Nowak and Bullier, 1997
Some of these results have been published previously in abstract form (Bair et al., 2001
MATERIALS AND METHODS
Electrophysiology. We recorded extracellularly from single units in the dorsal LGN, primary visual cortex, and area MT of anesthetized, paralyzed, macaque monkeys (Macaca fascicularis). LGN, V1, and MT data were collected from 3, 16, and 13 monkeys, respectively. The numbers of animals for V1 and MT are large because data for this study was collected sporadically during experiments performed for other studies.
Detailed methods for this type of recording are available in Carandini et al. (1997)
1 · hr
Tungsten-in-glass microelectrodes (Merrill and Ainsworth, 1972
Visual stimuli. Visual stimuli were generated by custom software on a CRS 2/2 board (Cambridge Research Systems, Kent, UK) under the control of an Intel 86-based host computer. Stimuli were presented on a standard cathode ray tube at a resolution of 1024 × 731 pixels and a video frame rate of 100 Hz vertical refresh, with a mean luminance of 33 cd/m2. The display was gamma-corrected with a lookup table. We used a front surface mirror to bring the receptive field (RF) of each cell into register with the center of a video monitor placed between 80 and 180 cm from the animal's eye, where it subtended between 10 and 22°. The graphics board that generated our stimulus also generated synchronization pulses that were time-locked to the start of the first frame of our stimulus. These pulses were time-stamped and recorded by the same system used for collecting action potential times.
The RF size was estimated by hand before beginning quantitative characterization with sinewave gratings. Quantitative estimates of RF properties were computed from tuning curves resulting from a series of randomly interleaved stimuli. Responses to drifting sinusoidal stimuli were quantified with DC (mean firing rate minus the baseline rate for a mean gray stimulus) and F1 (amplitude of the Fourier component of the response at the temporal frequency of the stimulus) tuning curves.
For V1 cells, drifting sinusoidal gratings were randomly interleaved under computer control to obtain response tuning curves first for orientation, next for spatial frequency, and then for temporal frequency. Next, we chose the smallest patch of optimized grating that elicited a response easily distinguishable from the spontaneous rate, and we alternated between adjusting the vertical and horizontal position of the patch by hand until the maximal response was obtained. At these coordinates, circular patches of various diameters were interleaved to obtain a tuning curve for size. The classical receptive field (CRF) of the V1 cell was defined to be the smallest circular patch that gave a response no <95% of the maximum.
Cells were classified as simple or complex on the basis of the modulation index computed at the optimal spatial frequency (Skottun et al., 1991
a/p, where p and a were the responses to preferred direction (that which gave the highest response) and the antipreferred direction (opposite to preferred), respectively, in excess of the spontaneous rate (Maunsell and Van Essen, 1983
LGN cells were characterized in a manner similar to V1 simple cells with two exceptions. First, LGN cells were mapped with a white noise stimulus in which squares in a 16 × 16 spatial grid were independently assigned zero or maximum luminance on every video frame on the basis of a pseudorandom number generator (Reid et al., 1997
Random sequence stimuli. After the initial characterization of a cell, we studied response timing using random binary and ternary stimulus sequences. For the binary sequences, either the preferred stimulus (P) or the antipreferred stimulus (A) was presented on each video frame (i.e., every 10 msec). The choice between A and P was governed by a pseudorandom sequence generated using the ran2 algorithm of Press et al. (1992)
For LGN cells, we ran binary sequences with three types of P and A stimuli: spots, annuli, and gratings. (1) Spots: P was a disk of maximum or minimum luminance (for ON or OFF cells, respectively) presented on a gray background and confined to the central region of the RF determined from the reverse-correlation map. A was the disk of opposite contrast to P. (2) Annuli: P was an annulus of maximum or minimum luminance that was confined to the surround determined from the spatial reverse-correlation, and A was the annulus of opposite luminance. (3) Gratings: P was a centered, circular patch of sinusoidal grating having optimal spatial period and phase and covering the RF center and surround. A was counterphase to P, i.e., it had 180° opposite phase.
For V1 simple cells, we used two sets of P and A stimuli. For both sets, P was the optimal sinusoidal grating confined to the CRF (see above), and A was either counterphase or orthogonally oriented to P. We will refer to these two stimuli as the phase and orientation stimuli, respectively. For V1 complex DS cells and for MT cells, P and A were optimal gratings that differed in their direction of movement: P moved in the preferred direction, and A moved in the opposite direction. The amount of movement between video frames was typically 90° of phase but was set to 45° if the cell responded poorly to 90° movements.
LGN m- and p-cells were distinguished on the basis of the presence of contrast gain control (of the type described by Shapley and Victor, 1978
Data analysis. For all analyses, the times of action potentials were expressed in milliseconds relative to the time at which the raster scan of the video display illuminated the center of the screen, where each neuronal receptive field had been centered. We determined the timing of our stimulus relative to the video synchronization pulses by plotting the luminance at the center of the screen (measured with a photometer) on an oscilloscope that was triggered by the video synchronization pulses. We then measured the timing of our data collection system by passing the video synchronization pulses through the same amplifiers and spike discrimination hardware that we used to detect action potentials. These two measurements allowed us to compensate all spike times for the delays associated with stimulus generation and data collection.
We estimated the mean instantaneous firing rate (i.e., the peristimulus time histogram at the millisecond resolution) associated with particular stimulus patterns that occurred at random in our binary and ternary sequences. For example, the sequence AP indicates 30 msec (three video frames) of the antipreferred stimulus followed by 20 msec (two frames) of the preferred stimulus. The time of occurrence of the transition, defined to be the time of appearance of the first frame of P, was taken as the reference time (t = 0). Spike train segments for each occurrence of a stimulus pattern were aligned to the reference time and averaged to estimate the mean instantaneous firing rate associated with that pattern. Average responses to stimulus transitions were always compared with the response for a reference pattern (the reference response) that had no transition. For example, the reference stimulus pattern for AP was 50 msec (five frames) of A. Figure 1 shows examples of responses to stimulus transitions and reference responses. Traces were smoothed with a Gaussian of SD 1 msec before further analysis.
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Figure 1. The estimation and comparison of response timing for turning on and turning off are demonstrated for an LGN p-cell. Top, Stimulus icons show preferred and antipreferred stimuli, P and A, one of which was chosen randomly for presentation every 10 msec. A, Average firing rate versus time is plotted for two 50 msec stimulus sequences, which are depicted below the abscissa. Solid lines indicate the stimulus and response for a transition from A to P (i.e., a change from the left to right stimulus icon, top), whereas dashed lines indicate the reference stimulus, 50 msec of A, and its response. Time 0 is when the transition to P occurred. Response latency was ~30 msec; therefore, the first and last 20 msec of the response traces are averages of responses to a random set of sequences that occurred before and after the 50 msec trigger sequences (see arrow and label ongoing random sequence) and should not be confused with spontaneous firing rate. Epochs of A were associated with near zero firing rate, and the onset of P caused a rapid rate increase (solid response curve). Response curves were based on 253 occurrences of the stimulus sequences (see Materials and Methods). B, Responses of the same cell to the PA transition (a change from the right to left stimulus icon, top) are shown in the format of A. Firing rate was high for P epochs and dropped rapidly after the transition to A. Response curves were based on 253 occurrences of the stimulus sequences. C, The difference between the response to the AP transition and to its reference stimulus (in A, solid minus dotted line) is plotted here as the thin line. The analogous difference between the traces in B is plotted as the thick line. These response difference traces allow direct comparison of the timing of the onset of signals evoked by the AP and PA stimulus transitions. We defined AP to be the difference in timing between the onsets of the AP and PA response (thick bar; see Materials and Methods).
The response difference trace for a stimulus transition was computed by subtracting the reference response from the response to the transition. Response onset latency was determined automatically by finding the maximum point on the response curve (or on the response difference curve) and searching backwards in time from the maximum for the first point that was above 5% of the maximum response. A similar procedure was used to find response offset latency, except the minimum point and the 5% drop to minimum were used. We also computed latencies for the rise (and fall) to 50% and found that our results were not significantly changed.
Our measure of the timing difference for turning on relative to turning off was
RESULTS
We measured response timing for 31 cells in the LGN (14 p-cells and 17 m-cells), 63 cells in V1 (18 simple, 11 complex non-DS, 34 complex DS), and 39 DS cells in MT. All cells were tested with random, binary sequences of visual stimuli in which either the preferred stimulus P or the antipreferred stimulus A appeared every 10 msec. We will begin by demonstrating the computation of our response timing measurements for the binary stimulus and will summarize these measurements across cell types. For each cell type, we will show how timing correlated with spontaneous and evoked firing rates. We will then assess the influence of antipreferred stimuli on response timing by comparing them with N, which are hypothetically neutral. Finally, we show that timing is influenced in different ways across areas and cell types by the temporal history of the stimulus.
Latency for response onsets and offsets
Figure 1 demonstrates our method for measuring onset and offset latency for an LGN p-cell that was tested with the phase stimulus. Every 10 msec, either the preferred stimulus P (the optimal sinusoidal grating) or the antipreferred stimulus A (the grating opposite in phase) was presented (Fig. 1, Top, right and left icons). We estimated the onset latency by comparing the response for the A-to-P (AP) transition with that for a reference stimulus that contained no transition to P. The AP transition was defined to be 30 msec of A followed by 20 msec of P, and the reference stimulus, lacking the transition, was 50 msec of A (Fig. 1A, solid and dashed lines, respectively; below abscissa). Because these 50 msec stimulus sequences appeared in an ongoing random sequence, the stimuli preceding and after them were random. In Figure 1A, the time at which the response to the AP transition (solid line) turns upward (open arrow) from the reference response (dashed line) is the onset latency. The latency is ~27 msec relative to the stimulus transition, which occurs at time 0. The upturn in the reference trace (dashed line) near 45 msec results from responses to random sequences that followed the trigger sequence and does not influence our timing measurements. We estimated the offset latency in a similar manner from the response to the P-to-A (PA) transition (30 msec of P followed by 20 msec of A) and its reference stimulus (50 msec of P) (Fig. 1B). The response to the PA transition diverges from the reference response ~25 msec after the stimulus transition (B, open arrow). To facilitate the comparison of onset and offset latencies, we plotted the AP response minus its reference response together with the PA response minus its reference. These response difference plots (Fig. 1C) make it apparent that the response decrease for the PA transition (thick line) occurred before the response increase for the AP transition (thin line) for this neuron.
Figure 2 shows response difference plots for cells from LGN, V1, and MT that were tested with random, binary sequences of P and A stimuli that were suited to the properties of the cells on the basis of initial characterization with sinusoidal stimuli. The phase stimulus, presented to LGN p- and m-cells and to V1 simple cells (A-C, respectively), covered the classical center and surround of the LGN RF and was restricted to the CRF for V1 cells. V1 simple cells were also tested with the orientation stimulus (D), which differed from the phase stimulus only by a 90° rotation of the antipreferred sinusoid. V1 complex DS cells (E) and MT cells (F) were tested with the direction stimulus (icon above E), which was an optimally oriented grating that moved in either the preferred or opposite direction every 10 msec. For each example in Figure 2, the response difference trace for the PA transition (thick lines) dropped from zero before the trace for the AP transition rose (thin lines). We quantified the offset and onset times for each cell from the respective response difference plots as the time to reach 5% of the maximum excursion from zero (see Materials and Methods).
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Figure 2. Response decreases occurred sooner than response increases when switching between P and A. For five classes of neurons, response difference plots (defined in Fig. 1) for PA and AP transitions (thick and thin lines, respectively) are shown for example cells responding to binary random sequences of optimized sinusoidal grating stimuli. A, Difference plots for an LGN p-cell responding to the phase stimulus (transitions between opposite phases, icons, top of left column) show that the PA response occurred before the AP response. B, For an LGN m-cell responding to the phase stimulus, a smaller timing asymmetry is present. The sign reversal at ~40 msec resulted from the combination of the transient nature of the m-cell response and the chance transitions that followed the reference stimuli (e.g., 50 msec of A was sometimes followed by P and vice versa). C, Difference plots for a V1 simple cell responding to the phase stimulus show a timing asymmetry larger than that observed for the LGN cells in A and B. D, Responses of a V1 cell to transitions between orthogonal orientations (icons in center) also show a large timing asymmetry. Responses of a V1 complex DS cell (E) and an MT cell (F) to transitions between opposite directions of motion (icons, top of right column) show a timing asymmetry as well.
Onset latency is plotted against offset latency for all cells in Figure 3. The points fell mainly above the diagonal line of equality, indicating that offset time was less than onset time. For each cell class, onset and offset times were significantly correlated (Pearson's r ranged from 0.60 to 0.97, p < 0.004, for each cell class). Our median LGN onset latencies (24 and 34 msec for m- and p-cells, respectively) fell within the range of medians reported by Maunsell et al. (1999)
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Figure 3. A comparison of onset and offset latencies across cell types and stimulus categories. The latency of the response to the transition from antipreferred to preferred (onset latency) is plotted against the latency of the response to the opposite stimulus transition (preferred to antipreferred, offset latency). Nearly all points fell above the diagonal line of equality, indicating that onset latency is longer than offset latency. The mean onset and offset latencies for each cell class and stimulus type are reported in Table 1.
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Table 1. Average response offset and onset latencies for the data plotted in Figure 3 Our offset latencies, being consistently smaller than onset latencies, were smaller than the minimum latency values reported in nearly all previous extracellular studies of these visual areas in the macaque monkey. Specifically, our earliest offset latencies were between 15 and 20 msec in the LGN and between 20 and 25 msec in V1 and MT (Fig. 3, horizontal axis; see Table 1 for mean values). This is not inconsistent with physical limitations of the circuitry, and, given early responses in the LGN, is consistent with there being only several milliseconds of delay from LGN to cortex (Reid and Alonso, 1995
To quantify the difference between onset and offset latency for each cell, we defined
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Figure 4. The distribution of the timing asymmetry,
Response latencies in V1 are known to be widely distributed, and Figure 4, D and E, shows that
In summary, for almost all of our cells, responses turned off faster than they turned on: only rarely was
Eleven non-DS complex cells were tested with the orientation stimulus, but none responded to the fast changes between preferred and antipreferred stimuli in a manner similar to that of the other cell types. In particular, their firing rates decreased for both PA and AP transitions. Results for these cells cannot be compared directly to those presented here; therefore, complex non-DS cells are not included in our analysis.
The relationship between
A linear system would not have a latency asymmetry,
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Figure 5. A system with a high threshold takes longer to turn on than to turn off. If the input in A, plotted as a function of time, is delayed and smoothed by convolution with a boxcar function, the trace in B results. The delay from the rise in the input to the rise in the output is equal to that from the fall in the input to the fall in the output. However, if the system responds only when the output is above a high threshold (dashed line), the latency to response onset (ton) is longer than the latency to offset (toff) by an amount approximately equal to the time to rise to threshold. Thus,
A plot of
The association of low firing rate with large
Assessing the influence of the antipreferred stimulus
To test the hypothesis that the antipreferred stimulus contributed to the delay of response onset, we compared responses to AP transitions with those to null-to-preferred (NP) transitions. The N was either a mean gray field or, for DS cells, a static grating, and N can be thought of as a candidate neutral stimulus for the cell being tested. Each cell was tested with a random, ternary sequence in which A, N, or P was presented with equal probability every 10 msec. Average responses and response difference traces were computed for the NP and PN transitions by the same methods used for AP and PA transitions, with N taking the place of A.
Figure 7A-F shows results for the cell types and stimuli that were examined previously in Figure 2. Each panel shows the familiar AP and PA response difference traces and the new NP and PN traces. In Figure 7C, where the traces are labeled, the firing rate of a V1 simple cell decreased for transitions from the preferred stimulus to the antipreferred (PA) (downward deflected black line) and to the null stimulus (PN) (downward deflected gray line). The response decrease began at about the same time regardless of whether A or N was the final stimulus. However, the timing of rate increases caused by transitions to the preferred stimulus depended on whether the initial stimulus was N or A: the responses to the NP transition (thick gray line) occurred sooner than the response to the AP transition (thin black line). All six examples in Figure 7 showed qualitatively similar behavior. The onset latency after antipreferred stimuli was longer than that after null stimuli, whereas the offset latency (after preferred) was approximately the same for PA and PN transitions. The latter observation is consistent with the idea that offset latency is determined by the loss of excitation (or activation of inhibition) caused by removal of the preferred stimulus. If A has a stronger influence than N, it does not act rapidly enough to advance the timing of the initial decline in firing rate when P is removed.
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Figure 6. Firing rate is negatively correlated with
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Figure 7. The response to a preferred stimulus is delayed more when it follows an antipreferred stimulus than when it follows a null stimulus. A-F, For six example cells, black lines show response difference traces for PA and AP transitions (medium and thin lines, respectively), and gray lines show response differences for PN and NP transitions (medium and thick lines, respectively). Cell types (top left corners) and stimulus categories match those in Figure 2. The phase stimulus applies to A-C, the orientation stimulus to D, and the direction stimulus to E and F. Bars in C indicate the latency of the NP (gray bar) and AP (open bar) responses relative to the PA latency. G, For all cells tested with ternary stimuli,
We compared the onset timing for NP transitions to AP transitions quantitatively using
A cell-by-cell comparison of
We have just observed that responses to preferred stimuli were delayed more by A than by N stimuli, and we also observed that firing rate was related to response timing (Fig. 6). We will now examine the relationship between firing rate and delay for N and A stimuli. The mean firing rate in response to NP and AP transitions is plotted as a function of time in Figure 8A for a V1 complex DS cell. The firing rate just before the response to the AP transition (black lines below arrow) was lower than the rate just before the response to the NP transition (gray lines below arrow). This was typical across cell types, but a few counterexamples were present. Figure 8B shows a counterexample for which the firing rate just before the response to the AP transition was higher on average than the rate for the NP transition, yet the NP response still occurred sooner. For each cell, we computed the firing rates in the 10 msec period before the onset of response to the NP and AP transitions and subtracted the rate for the AP case from the rate for the NP case. Figure 8C shows the ratio of the timing measures,
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Figure 8. Comparing firing rates for antipreferred and null stimuli. A, Average responses for AP (black line) and NP (gray line) transitions and for reference stimuli (dashed lines of corresponding color; see Fig. 1A for stimulus timing). Before the response to the preferred stimulus, the rate associated with N (gray lines below arrow) is higher than that associated with A (black lines below arrow). This trend held for 31 of 34 cells tested with the ternary, direction stimulus. Responses include at least 225 occurrences of each pattern. B, Format like A, but for one of three DS cells that had a higher firing rate before the AP response transition (black lines) than before the NP transition (gray lines). Responses include at least 450 occurrences of each pattern. C, The ratio
In summary, for the ternary sequences, antipreferred stimuli suppressed firing rate and delayed the onset of firing more than did null stimuli that were randomly interleaved with them. There was a mild tendency for cells with larger differences in firing rate to have larger timing differences in response to N and A stimuli by our ratio measure. It is unlikely that the change in firing rate caused the change in timing, because if this were so, the scatter of points in Figure 8C should go through unity for a rate difference of zero, but it did not. These results suggest that the antipreferred stimulus, and not just the lack of the preferred stimulus, contributed to the delay and that the magnitude of the delay may provide information beyond that carried by spike rate to distinguish the effects of various antipreferred and null stimuli.
How the AP delay depends on antipreferred duration
We have seen that the response to the onset of a preferred stimulus was delayed when that onset followed an antipreferred stimulus that was at least 30 msec in duration. If the response was delayed because of suppression caused by the antipreferred pulse, then changing the duration of the antipreferred pulse might reveal the time course of the suppressive signal. Two scenarios are schematized in Figure 9, where panel A shows four stimulus sequences with antipreferred pulses (plotted downward) of various lengths. Panel B shows the time course of a hypothetical suppressive signal that simply integrates over the epoch of the A pulse. Traces are aligned to the AP stimulus transition (open arrow), so the longest duration A pulse (thick line in A) has created the strongest suppression (thick line in B) when the stimulus is about to change back to preferred. Alternatively, if a transient suppressive signal was associated with the onset of the antipreferred stimulus, a longer antipreferred epoch would result in weaker suppression (Fig. 9C, thick line), and a shorter A epoch could cause stronger suppression (thin lines in A and C). We examined the time course of suppression by measuring responses that followed antipreferred epochs of various lengths. In our stimulus, the number of times that a sequence occurred declined exponentially with length; therefore, we limited our analysis to relatively short sequences for which timing could be measured accurately.
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Figure 9. Two conceptual models of suppression activated during an antipreferred pulse make opposite predictions. A, Four stimulus sequences with various duration A pulses are aligned to the AP transition (open arrow). Thicker traces show stimuli with longer A pulses. Stimulus traces are offset vertically for clarity here, but traces in B and C have no vertical offset. B, The time course of suppression that resulted from a sustained integration of the A pulses is plotted with lines of the same thickness used for the stimuli in A. The stimuli were convolved with the gray step function, which models suppression that accumulates over time. The suppression was larger for longer A pulses (downward indicates stronger suppression). C, When the stimuli were convolved with a fast, transient function (gray line), suppression for longer A pulses had decayed more than that for shorter pulses at the time of the AP transition (right ends of lines). This trend is opposite to that in B.
A series of 60 msec stimulus sequences is plotted in Figure 10 (B, gray inset). The first sequence (thickest line) consists of an antipreferred epoch of duration TA = 40 msec followed by a preferred epoch of 20 msec. Successively thinner lines indicate stimuli with successively shorter antipreferred epochs, i.e., smaller values of TA. The dashed line is the reference stimulus, which has no antipreferred pulse. For these sequences, responses of an LGN p-cell to the phase stimulus are plotted versus time, relative to the AP transition, in Figure 10A (time scale differs from stimulus inset). The response traces dropped from the reference response (dashed line) at times that reflected the onsets of the antipreferred pulses, but unlike the stimulus traces in the inset, the responses did not rise at the same time. As TA became shorter, the response to the AP transition occurred later, i.e., the thinner lines rise later, as indicated by the gray arrow. Thus, short, i.e., recently applied, A pulses were the most effective for delaying response onset in the LGN, consistent with transient suppression schematized in Figure 9C.
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Figure 10. Latency depends on the duration of the antipreferred stimulus, and the dependency shows several trends across cell classes. A, LGN p-cell average responses for five stimulus sequences (see stimulus inset below A) for counterphase stimulus. The response delay increased (gray arrow) as the antipreferred epoch was shortened. This trend occurred for all p- and m-cells. Responses include at least 250 occurrences for each pattern. B, Responses for this V1 simple cell to the counterphase stimulus showed a trend opposite to that for LGN: the response delay decreased (gray arrow) as the antipreferred epoch was shortened. This was representative of more than half of V1 cells, whereas others showed a trend similar to that in the LGN. Responses include at least 250 occurrences for each pattern. C, Responses for a V1 complex DS cell to the direction stimulus show a third trend: response latency first increased (shorter arrow) and then decreased as the antipreferred epoch was shortened (longer arrow). Responses include at least 188 occurrences for each pattern. This was typical of V1 complex DS cells and MT cells. D, Responses are shown for six stimuli (gray inset), which each have 30 msec of P before the A epoch. The fifth stimulus (thinnest line) is unchanged from the top panels. As TA shortens, the response to the AP transition first shifts rightward and then leftward, consistent with the behavior in C. Responses include 12, 24, 48, 94, and 192 occurrences for the thickest to thinnest lines, respectively.
Some V1 simple cells tested with the phase stimulus behaved like the example LGN cell just described, whereas others showed a second trend that is depicted in Figure 10B. For this cell, responses to the AP transition occurred earlier for sequences with shorter epochs of antipreferred stimuli (Fig. 10B, gray arrow). This trend is consistent with suppression that accumulates over the time scale tested, as depicted in Figure 9B. We observed similar results for 20 V1 cells tested with the orientation stimulus. Cells tested with both stimuli behaved similarly, i.e., onset time either increased as in A or decreased as in B for both.
We observed a third trend for DS cells tested with the direction stimulus in V1 and MT. This is exemplified by data from a V1 complex DS cell in Figure 10C. As TA decreased from 40 to 30 msec, the response latency increased (short gray arrow), but further reduction of TA caused a decrease in latency (long gray arrow). The response for TA = 10 msec was shifted abruptly to the left (thin line).
For each cell, we computed the onset latency of the average response for TA = 40 msec and used this as a reference time. Onset latencies for TA = 30, 20, and 10 msec were expressed relative to the reference time. These data are plotted in Figure 11 for each cell that provided clear response onsets for all four TA values. For the LGN, response latency increased at shorter TA for almost every cell that we studied, and the increase was greater on average for m-cells (black lines) than for p-cells (Fig. 11A, gray lines) (see legend for statistics). The average change in onset latency for m- and p-cells is plotted in the inset at the bottom of A. For V1 simple cells tested with the phase stimulus, the results varied widely across cells (Fig. 11B). For shorter A pulses, onset latency increased for some cells but decreased for others. The thick line shows data for the example in Figure 10B. No average across cells is shown because it would not reflect the diversity found in V1 simple cells. Results for simple cells tested with the orientation stimulus showed a similar diversity (C). Complex DS cells in V1 and cells in MT that were tested with the direction stimulus showed behavior similar to each other (Fig. 11D) and were less diverse than V1 simple cells. There was an initial increase followed by a larger decrease in latency as TA decreased from 40 to 10 msec. Average changes in latency are plotted in the inset in D. The data in Figure 11 show that the signals from preferred and antipreferred stimuli do not interact in the same way across cortical areas and cell types, at least at the time scale of tens of milliseconds.
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Figure 11. Summary of duration dependence of latency across cell classes. Relative latencies for 5% rise-to-peak are plotted against the duration of the antipreferred stimulus, TA, that preceded the AP transition. All values are given relative to the value for TA = 40 msec. A, Each line emanating from the point (40,0) shows data for a p-cell (gray lines) or an m-cell (black lines). For nearly all LGN cells, latency increased as TA decreased. The average relative latencies are plotted for p-cells (gray line) and m-cells (black line) in the inset (error bars show ±1 SEM). m-cells on average had significantly longer relative latencies (t test; p < 0.00001; 7.0 > 3.7 msec; TA = 10 msec). Results shown here are for counterphase stimuli. Cell counts appear in parentheses. B, Similar data are plotted for V1 simple cells tested with counterphase stimuli. These plots show that V1 had more diverse behavior than the LGN. Latency could increase or decrease as TA decreased. The thick line corresponds to the example data in Figure 10B for which the latency decreased with TA. C, Similar to B, but for V1 simple cells tested with the orthogonal orientation stimulus. The thick line here and in B show data collected from the same cell. D, For V1 complex cells (black lines) and MT cells (gray lines) tested with the direction stimulus, response latency first increased and then decreased as TA was reduced from 40 to 10 msec. The inset shows the average relative latency for MT cells and V1 complex DS cells.
The changes in onset latency with antipreferred pulse duration can be related back to our estimates of
Finally, for the stimulus sequences just examined, two factors were changing at once: the duration, TA, of A and the duration, TP, of P that preceded A. A set of control sequences in which TP was held constant at 30 msec are shown in the gray inset in Figure 10D. The rightward and then leftward shift in the latency of the AP responses to these stimuli (Fig. 10D, gray arrows) was similar to that observed in C. The longest stimulus sequence (100 msec) occurred only 12 times. The infrequent occurrence of the longer sequences made them less useful than the constant length sequences (Fig. 10, top inset) for accurate estimation of response trends. Nevertheless, the shifts in latency for the longer sequences were qualitatively similar to those for the shorter sequences for the cell types described here. This is not to say that the sequence before the antipreferred pulses had no significant effect on responses. The sequence history affected the responses, but a full account of this is not attempted here. We simply demonstrate that onset latency showed history dependence that characterized and differentiated between cell classes.
DISCUSSION
We found that nearly all neurons in the LGN, V1, and MT responded more rapidly to a stimulus transition from preferred to antipreferred than to the opposite transition. The generality of this observation might be questioned because our rapidly changing stimulus differs from commonly used stimuli that flash on for ~1 sec after several seconds of homogeneous background. Published data for standard stimuli, however, suggest that
The
10 msec (our unpublished observations). Here, we have used optimal spatial frequencies, high temporal frequencies, and fast motion, which shorten neuronal integration time (Shapley and Victor, 1978
The offset latencies that we found suggest that information from the photoreceptors can reach LGN within 15-20 msec and V1 and MT within 20-25 msec. We believe that the rapid, dynamic nature of our stimuli and the measurement of offset rather than onset latency was responsible for revealing these short latencies. Response decreases have been reported to have exceptionally short latencies in visual cortex (Bartlett and Doty, 1974
Spontaneous rate
We found an inverse correlation between
Several studies have shown that neurons with stronger inhibition or lower spontaneous rates have more specific trigger features, i.e., are more narrowly tuned (Pettigrew et al., 1968
A versus N stimuli
Do antipreferred stimuli delay response onset? Lisberger and Movshon (1999)
The origin of
We found similarities and significant differences in
For 30 msec antipreferred pulses, the average
If LGN principle cells relay retinal spikes with near 1:1 transmission, as observed for some LGN X cells in cat (Cleland et al., 1971
Overall, we speculate that part of
10 msec, on average. Volgushev et al. (1995)
álek et al., 1997
Intracellular studies of cat simple cells have shown that hyperpolarization follows the removal of an excitatory stimulus (Creutzfeldt and Ito, 1968
As mentioned above, it is possible that part of
The distributions of
For DS cells, we observed an interesting trend in onset latency as a function of antipreferred duration. As A duration decreased, a reversal in latency occurred: responses after 10 msec of A came sooner than those after 40 msec of A (Fig. 10C). Perhaps a transient suppression is activated (as depicted in Fig. 9C) for longer A pulses, but the 10 msec pulse is simply not long enough to activate the suppressive mechanism (i.e., implying that the thinnest line in Fig. 9C would not make its downward deflection). If this trend is a signature of the interaction of opponent directional signals, it is surprising that it is similar in V1 and MT in light of evidence that opponency is stronger in MT than in V1 (Qian and Andersen, 1994
Response offset: the first sign of change
Response latency is usually calculated for increases in firing rate (Raiguel et al., 1989
Offset latency may be more than just a useful tool for studying visual processing. The earliest cortical signals to indicate a change in the visual scene will arise in neurons that lose their preferred stimulus when the scene changes. Therefore, we propose that the offset of the responses of strongly driven cells to the previous scene acts as a reference signal for the visual system to interpret the waves of action potentials that follow a sudden scene change. The change may be induced by a sudden change in the environment or an eye movement. Response onset is known to carry information about stimulus features in vision (Gawne et al., 1996
FOOTNOTES Received Aug. 17, 2001; revised Dec. 26, 2001; accepted Jan. 23, 2002.
This work was supported by National Institutes of Health Grant EY02017. Adam Kohn gave us comments on this manuscript, and he and Najib Majaj provided useful discussion and assisted with data collection. Hysell Oviedo and Alex Reyes provided insight from in vitro data, and Suzanne Fenstemaker provided assistance with histology.
Correspondence should be addressed to Wyeth Bair, Center for Neural Science, New York University, 4 Washington Place, Room 809, New York, NY 10003. E-mail: wyeth{at}cns.nyu.edu.
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