We trained two monkeys on the DOTS task (, Roitman and Shadlen, 2002
). For both monkeys, performance accuracy and RT changed systematically as a function of motion strength (coherence; ). At 51.2% coherence, both monkeys nearly always made the correct choice with the shortest mean RT. At lower coherences, the probability of choosing the correct target decreased, while mean RT increased. Both the psychometric and chronometric functions were well described by a drift-diffusion model with asymmetric bounds (; Hanks et al., 2006
; Palmer et al., 2005
). In general, the fits indicated low thresholds for both monkeys and a slight bias toward T1 (rightward direction) for monkey F ().
Summary of behavioral measures during recording sessions
To determine the caudate’s role in perceptual decisions about motion direction, we examined 129 putative projection neurons whose activity was modulated during the DOTS task (n = 87 and 42 from monkeys C and F, respectively). These neurons showed a diversity of response properties with respect to motion strength, choice and the timing of task-related activation. Most neurons were sensitive to choice in at least one task epoch (the presence of at least one non-white entry for almost all cells in ). Choice-dependent activity was more likely to be larger for choices associated with target locations contralateral to the recording sites (the dominance of warm- over cool-color entries in ). Most neurons were also sensitive to motion strength in at least one task epoch (the presence of at least one non-white entry for almost all cells in ). The sign and strength of coherence modulation, quantified as the sign of the slope value from a linear regression of average firing rate with coherence as the regressor and visually represented by different colors (), varied from cell to cell (in rows), between trials with different choices for the same cell (first and second columns in the same panel), and across epochs within the same cell (across panels).
Of these diverse responses, we focused on three types of activity that relate to three computational elements necessary for effective perceptual decision-making: evidence accumulation, evaluation, and choice bias. For all subsequent analyses, data are combined from the two monkeys, in which we found similar frequencies of occurrence of each response type: Fisher’s exact test, p = 0.1116 and 0.1781 for the first two types of activity, respectively, and very low numbers of occurrence for Bias activity in both monkeys.
Evidence Accumulation: Neural activity modulated by motion strength and choice
The first type of task-dependent caudate activity was modulated by both choice and motion strength, including choice-dependent modulation by motion strength (blue circles in ). This activity was evident in several task epochs, from after stimulus onset to after reward delivery, for different subsets of neurons. This activity likely contributes to generating the current decision and possibly choice-specific evaluation.
An example neuron with Evidence Accumulation activity in the Stim epoch is shown in . When aligned on stimulus onset, the neuron’s activity was larger when the visual motion was leftward than when the motion was rightward (Wilcoxon rank-sum test, H0: equal median responses for the two directions, p < 0.0001). Thus for this cell in the Stim epoch, trials in which the monkey correctly chose the left choice target were designated as IN trials, and trials in which monkey correctly chose the right choice target were designated as OUT trials. When collapsed across coherence levels, the activity began to differentiate between IN and OUT trials soon after stimulus onset (tchoice = 210 ms). On IN trials, the activity tended to build up more rapidly for higher coherences (, solid lines; linear regression slope of the rate of rise in activity versus coherence = 3.24 spikes/s2/%coh, H0: slope = 0, F = 7.87, p = 0.0025; slope of a linear regression of average firing rate during the Stim epoch versus coherence = 0.31 spikes/s/%coh, H0: slope = 0, F = 19.09, p < 0.0001). In contrast, on OUT trials, activity was less extensively modulated but tended to be smaller for higher coherences (, dashed lines; slope of a linear regression of average firing rate versus coherence = −0.14 spikes/s/%coh, F = 8.00, p = 0.005). When aligned on saccade onset, the neuron’s activity did not converge to any particular value for either type of trials ().
Example neuron with Evidence Accumulation activity
Across the population, 47 neurons (n
= 37 and 10 for monkeys C and F, respectively) showed Evidence Accumulation activity in the Stim epoch (). Their activity became selective for choice with a median latency (tchoice
) of 170 ms (inter-quartile range, or IQR: 142.5–225 ms) after stimulus onset. This latency is slightly shorter than comparable data from area LIP, and, also unlike LIP neurons, these caudate neurons did not show a noticeable dip in activity after stimulus onset (Roitman and Shadlen, 2002
). Consistent with how these neurons were selected, the average firing rate during a 100-ms window before the median RT for each coherence level was positively modulated by coherence on IN trials and negatively modulated on OUT trials (slopes = 0.042 and −0.05 spikes/s/%coh, F
= 8.90 and 15.85, p
= 0.0031 and 0.0001, respectively; ). In addition, the time course of activity on IN trials showed gradual, coherence-dependent changes, consistent with temporal accumulation of evidence. Across neurons, the rate of change of activity during the Stim epoch on IN trials was positively modulated by coherence with a median slope of 0.79 spikes/s2
/%coh (two-sided sign test, p
< 0.0001; ). When tested in individual neurons, this effect was also significant in 26 out of 47 neurons with Evidence Accumulation activity in the Stim epoch. For OUT trials, the rate of change tended to be negatively modulated by coherence (median slope = −0.09 spikes/s2
= 0.018), but the effects were variable and reached significance for only four neurons ().
Popuglation summary of neurons with Evidence Accumulation activity
According to the drift-diffusion model, incoming motion information and noise together govern the rate of rise of the decision variable, which, in turn, determines RT (Gold and Shadlen, 2007
). Thus, the model predicts that for IN trials, the rate of rise should be inversely related to RT, regardless of coherence, and directly related to motion strength, but only insofar as coherence is related to RT. Evidence Accumulation activity in caudate was roughly consistent with these predictions. Specifically, when tested separately for each coherence, Evidence Accumulation activity during the Stim epoch was negatively correlated with RT on IN trials and positively correlated with RT on OUT trials, for all but the highest coherence (which had a more restricted range of RTs; ). Moreover, when tested separately for restricted ranges of RTs, the activity was not correlated with coherence, with a single exception for IN trials with long RTs (). Thus, the sensitivity of Evidence Accumulation activity to coherence and RT was consistent with a role in decision formation and not simply a reflection of motion stimulus itself.
Table 2 Summary statistics of regression analyses on average spike rate in the Stim epoch as a function of RT at different coherence levels.Data in “Slope (IN)” and “Slope (OUT)” columns are in the unit of spike/s2 and presented (more ...)
Table 3 Summary statistics of regression analyses on average spike rate in the Stim epoch as a function of coherence for trials with different RTs.Data in “Slope (IN)” and “Slope (OUT)” columns are in the unit of spike/s/%coh and (more ...)
Consistent with this idea, Evidence Accumulation activity tended to reflect the direction of the monkey’s choice and not simply the direction of the motion stimulus, which differed on error trials (). When the monkey chose the IN target (solid lines in ), activity was high regardless of whether the stimulus was moving towards (black lines, corresponding to correct trials) or away from (gray lines, error trials) that target. In contrast, when the monkey chose the OUT target (dashed lines), activity was lower regardless of whether the actual stimulus direction was towards (black lines, correct trials) or away from (gray lines, error trials) that target. To quantify these observations, we computed an ROC index comparing activity for IN versus OUT trials in a 400 ms window, separately for individual cells and for correct and error trials (using only trials with 3.2% or 6.4% coherence, which provided sufficient numbers of error trials). The value of this index tended to be >0.5, implying that for both correct and error trials, responses were greater for IN versus OUT choices (). Furthermore, the value of the ROC index tended to be smaller on error versus correct trials (; Wilcoxon paired signed rank test, H0: equal median, p = 0.0265 and 0.0002, for 3.2% and 6.4% coherence, respectively), which is consistent with the idea that the evidence that drives the decision variable in a drift-diffusion-type process tends to be noisier and therefore weaker on error trials.
Comparison of Evidence Accumulation activity for error and correct trials with weak motion strength
Unlike the drift-diffusion models or LIP activity just before saccade onset, however, the average activity of these caudate neurons did not appear to rise to a common value just prior to saccade onset (Ratcliff and Rouder, 1998
; Roitman and Shadlen, 2002
). This observation was confirmed by several quantitative measures. First, population activity in the Sac epoch remained weakly modulated by coherence for IN trials (slope = 0.03 spikes/s/%coh, F
= 5.04, p
= 0.026; for OUT trials: slope = −0.0065 spikes/s/%coh, F
= 0.28, p
= 0.60; ). Second, activity of both the population and individual neurons tended to be positively modulated by coherence throughout the Stim epoch, regardless of whether the data were aligned to stimulus or saccade onset (). The drift-diffusion model, on the contrary, predicts that activity at higher coherences rises faster to the bound, resulting in a positive correlation with activity when aligned to stimulus onset but a negative correlation with activity when aligned to response onset (for an example of neural activity reaching a bound, see Roitman and Shadlen, 2002
, ). Third, we conducted the same analyses but with data grouped by RT, not coherence. We found a primarily negative relationship between RT (which is inversely related to coherence) and Stim epoch activity aligned to response onset, contrary to the model prediction (). Fourth, to detect the presence of a bound crossing in the activity of individual neurons, we used the following criteria: a negative slope in the relationship between coherence and neuronal activity −300 to −200 ms before saccade onset and zero slope at −100 to 0 ms before saccade onset. Only 4 out of 47 neurons met these criteria, not significantly above a 5% chance level (binomial cumulative probability, p
= 0.0845). Thus, although a subset of caudate neurons reflected the process of evidence accumulation, they did not appear to reflect the commitment to a categorical decision (i.e., threshold crossing), as has been reported for other brain areas like LIP and FEF (Hanes and Schall, 1996
; Roitman and Shadlen, 2002
Evidence Accumulation activity in the Stim epoch did not converge at a decision bound
Histogram of neurons showing Evidence Accumulation activity for each task epoch
We also observed Evidence Accumulation activity (i.e., coherence- and choice-dependent) in the Sac, Post, and Rew epochs in 76 neurons (n = 54 and 22 for monkeys C and F, respectively; and ). In our sample, across all epochs, positive modulation was more prevalent on IN trials and negative modulation was more prevalent on OUT trials (chi-square test, p = 0.0001 and 0.0031 for IN and OUT trials, respectively). Within the Stim and Post epochs, positive modulation was more prevalent on IN trials than on OUT trials (chi-square test, p < 0.0001 and p = 0.0076, respectively), whereas in the Sac and Rew epochs, the balance between positive and negative modulation was similar for both choices (p = 0.73 and p = 1.00, respectively). Thus, even after the decision was formed, the caudate continued to encode both the decision and the strength of the sensory evidence used to form the decision, until after the trial outcome was completed.
Evaluation: Neural activity modulated by motion strength similarly for both choices
The second type of activity was also modulated by coherence, but unlike the first type, had similar coherence modulation for the two choices. This activity also appeared in several task epochs, from motion viewing to reward delivery. This activity likely contributes to predicting and evaluating outcomes, possibly independent of choice.
An example neuron is shown in . This neuron was responsive from soon after stimulus onset until after reward delivery. On correct trials (), Stim, Sac, and Rew epoch activity was slightly larger for contralateral versus ipsilateral choices (two-sided rank sum test, H0: equal median responses for the two choices, p < 0.0001), but not during the Post epoch (p = 0.09). Stim epoch activity was modulated positively by coherence for both contralateral and ipsilateral choices (slope = 0.59 and 0.43 spikes/s/% coh, H0: slope = 0, F = 103.70 and 121.24, respectively, p < 0.0001). This choice-independent, positive coherence modulation continued through the time of the saccade (slope = 0.18 and 0.45 spikes/s/% coh, F = 7.65 and 65.70, p = 0.0061 and p < 0.0001 for the two choices, respectively) and into the postsaccade period (slope = 0.60 and 0.52 spikes/s/% coh, F = 154.24 and 121.78 for the two choices, respectively, p < 0.0001). After reward onset, the sign of coherence modulation reversed, with stronger responses on low-coherence trials (slope = −0.25 and −0.14 spikes/s/% coh, F = 120.85 and 69.38 for the two choices, respectively, p < 0.0001; ).
Example neuron with Evaluation activity
This coherence-dependent activity at the end of the trial (in the Rew epoch) reflected both the predicted and actual outcome. For correct (rewarded) trials, this activity was inversely related to the probability of reward, computed from the coherence-dependent performance in the same recording session (). The activity for error trials was comparable to the activity on correct trials in the Stim and Sac epochs (). However, after visual error feedback indicating that no reward would be delivered, activity was briefly suppressed. The relationship between post-feedback activity and motion coherence/reward probability was not consistent (, open symbols), possibly due to smaller number of error trials and/or floor effect. Nevertheless, these features are consistent with a representation of reward prediction error: reward expectation was computed during motion viewing based on the strength of the sensory evidence, maintained during the delay after a decision was made, and then compared to the actual outcome (Sutton and Barto, 1998
Across the population, 48 neurons (n = 36 and 12 for monkeys C and F, respectively) showed Evaluation activity, in a single or multiple task epochs, with the exact pattern varying considerably (, red circles). Both positive and negative coherence modulations were observed with similar overall prevalence across task epochs (n = 30 and 40, respectively; ). However, the distribution of each kind of modulation in particular task epochs differed (chi-square test, p = 0.028): positive modulation was observed slightly more frequently in the Stim epoch, whereas negative modulation was observed more frequently in the Post and Rew epochs.
Population summary of Evaluation activity
Consistent with a possible evaluative role, neurons with this kind of activity tended to respond differently to the actual feedback (correct or error) received at the end of the trial (). To control for possible differential responses due to more trivial reasons, such as licking, auditory solenoid/tone onset, and the presence of return saccades, we compared the proportion of neurons with a significant difference between reward and feedback responses between two groups: those with Evaluation activity (ALL) and those without Evaluation activity (CTRL). This analysis revealed a significantly larger proportion of neurons with Evaluation activity showing different reward and feedback responses (chi-square test, p = 0.0005). The proportion was also significantly larger if we limited our analysis to neurons with Evaluation activity only in the Sac, Post, or Rew epochs (p = 0.0049, 0.0006, and 0.0277, respectively).
Bias: Neural activity before motion onset that is predictive of choice
The third type of activity emerged before motion stimulus onset and was predictive of monkey’s choice, especially when motion evidence was weak. This activity likely represents an initial choice bias that combines with incoming sensory evidence to form a decision.
An example neuron with Bias activity is shown in . This neuron was classified as exhibiting Evidence Accumulation activity in the Stim epoch. Here we show that its activity before motion onset (in the Pre epoch) was also choice dependent. On 3.2% coherence trials (, blue), the neuron tended to be more active when monkey ultimately chose the IN choice target than when he chose the OUT choice target (compare solid and dotted blue lines). In other words, on trials in which pre-stimulus activity of this neuron was high, the monkey was predisposed to make an IN choice. In contrast, pre-stimulus activity did not distinguish between choices on high-coherence trials (, red). Thus, when sorted by choice, Pre epoch activity on trials in which weak sensory evidence was presented tended to be higher when the monkey ultimately made an IN choice versus an OUT choice.
To assess quantitatively the Pre epoch activity’s choice selectivity, we computed an ROC-based predictive index (). For this quantity, a value of 0.5 implies that the activity is not predictive of the monkey’s choice (e.g., at stimulus onset on 51.2% coherence trials). A value of 1.0 implies that the activity fully predicts the monkey’s choice (e.g., before saccade onset on 51.2% coherence trials). Consistent with a representation of choice bias, the Pre epoch activity of the example neuron had predictive indices larger than 0.5 for low-coherence trials (0–12.8% coherence, bootstrap method, p < 0.05). In contrast, predictive indices were ~0.5 for high-coherence trials, in which the strong motion evidence dominates the decision process and thus overwhelms any relationship between pre-stimulus activity and the monkey’s final choice. The average predictive index in the 400-ms window before stimulus onset was negatively related to coherence (slope from a linear regression with coherence as the regressor = −0.0021 /%coh, H0: slope = 0, F = 10.84, p = 0.046).
In our samples, 79 neurons showed statistically significant choice-dependent activity in the Stim epoch, out of which nine neurons had a predictive index in the Pre epoch that was significantly >0.5 on trials with low, but not high, coherence (5 in monkey C and 4 in monkey F, bootstrap method, p < 0.05; and ). Although these neurons were encountered infrequently (11%), their occurrences were significantly above a 5% chance level (binomial cumulative probability, p = 0.006). Furthermore, six of these neurons also showed Evidence Accumulation activity in the Stim epoch (), supporting the idea that the Bias activity contributes to actual decision formation. The remaining three neurons showed choice-dependent, but not coherence-modulated, activity in the Stim epoch. None showed Evaluation activity in any epoch.
Caudate activity is task dependent
In LIP, the only other neural structure examined with the RT version of the DOTS task used here, neural activity reflecting evidence accumulation was observed exclusively in neurons with memory-period activity during a MGS task (Roitman and Shadlen, 2002
). In other words, for LIP, neural responses on the MGS task are highly predictive of neural responses on the DOTS task. We did not observe such a tight link for caudate neurons.
On the contrary, we found that caudate activity can differ considerably between the two tasks. We encountered a substantial number of neurons that responded on only one task. In monkey C, for which the MGS task was also used to search for neurons, we encountered 11 neurons with activity that was modulated on the MGS, but not DOTS, task. Of the 74 neurons that were recorded on both tasks, 15 neurons showed modulated activity on the DOTS, but not the MGS, task. Of the 59 neurons modulated on both tasks, 41 had responses that were selective for the spatial location of the saccade target. In most of these cases, the spatial preferences tended to be congruent across tasks. For example, the choice target/motion direction associated with larger activity in the Stim epoch of the DOTS task also tended to elicit larger responses during the visual (“V”) epoch of the MGS task (, similar colors in the two corresponding columns).
We found no clear relationship between particular patterns of activation on the MGS task and Evidence Accumulation and Evaluation activity on the DOTS task. shows response profiles from the MGS task plotted separately for neurons with the two types of activity in different DOTS task epochs. In this display, direction-modulated activity is shown in red and task-modulated but non-directional activity is shown in black. Rows with only white entries across columns visually represent a subset of cells that were modulated on the DOTS, but not the MGS, task. The ratio of red-to-black entries visually represents the prevalence of spatial selectivity in task-modulated activity. This ratio tended to be higher for neurons with Evidence Accumulation activity (1.6, 1.3, 1.6, and 2.2 for epochs V, M, S, R, respectively; ) than for neurons with Evaluation activity (0.7, 0.5, 1.0, and 0.4, respectively; ), suggesting that the former neuron group was more likely to show spatially selective activity on the MGS task. Beyond this general trend, there was no other clear pattern to the relationship between MGS responses and DOTS responses, consistent with a previous report of the context dependence of caudate activity (Hikosaka et al., 1989
Distribution of neurons in caudate
The caudate receives inputs from multiple cortical areas, including LIP, FEF, and SEF (Calzavara et al., 2007
; Parthasarathy et al., 1992
; Saint-Cyr et al., 1990
; Stanton et al., 1988
). The terminal fields of these inputs cover partially overlapping regions within the caudate, but with a coarse topographical pattern along the anterior-posterior (AP) axis. We examined whether our neuronal data were sensitive to this topography by comparing spatial distributions of recording sites corresponding to two groups of neurons: those with either Evidence Accumulation or Evaluation activity, versus those without either category of activity (). We found that these distributions almost completely overlapped for the Stim, Sac, and Post epochs. In contrast, decision-related activity during the Rew epoch was observed in neurons located slightly more posterior than neurons without such activity, but the distributions still overlapped strongly (, median: AC+1 and AC+3, respectively; Wilcoxon rank sum test, p
= 0.0004). The median AP locations associated with Evidence Accumulation and Evaluation activity across epochs were not significantly different (data not shown, Wilcoxon rank sum test, p
= 0.2146). Thus, Evidence Accumulation and Evaluation activity was present in neurons distributed widely along the AP axis.
Distribution of neurons along the anterior-posterior (AP) axis