Performance monitoring in monkey frontal eye field

Abstract

The frontal eye fields (FEF) are thought to mediate response selection during oculomotor decision tasks. In addition, many FEF neurons have robust postsaccadic responses, but their role in postchoice evaluative processes (online performance monitoring) is only beginning to become apparent. Here we report error-related neural activity in FEF while monkeys performed a biased speed-categorization task that enticed the animals to make impulsive errors. Twenty-three percent of cells in macaque FEF coded an internally generated error-related signal, and many of the same cells also coded task difficulty. The observed responses are primarily consistent with three related concepts that have been associated with performance monitoring: (1) response conflict; (2) uncertainty; and (3) reward prediction. Overall, our findings suggest a novel role for the FEF as part of the neural network that evaluates the preceding choice to optimize behavior in the future.

Keywords: conflict monitoring; decision-making; error-detection; performance monitoring; reward prediction; uncertainty.

Figure 1.

A, Macaque monkeys were trained to categorize the speed of moving random dots as either slow or fast relative to an arbitrary yet constant criterion speed that was learned by trial and error. Monkeys categorized speeds by making a saccade to the red and green targets to signal slow and fast stimulus speeds, respectively. The position of the red/green targets inside/outside the receptive field was randomized to distinguish category choice from saccade direction. Animals were free to indicate their choice any time after the onset of the motion stimulus. Auditory feedback was delivered after 400–1200 ms of continued fixation of the choice target. Reward was delivered after additional 300–600 ms fixation delay. B, Six different stimulus speeds were presented spaced equidistant around the category boundary. Based on the distance from the category bound, speeds were classified as “easy,” “intermediate,” and “difficult” (C). In blocks of 100–300 trials, animals were biased either toward the red or green target by giving more reward for correct saccades to targets of this color. The current reward schedule was never indicated but had to be inferred based on rewards received on previous trials.

Figure 2.

Recording sites were reconstructed based on stereotaxic MR images, chamber implantation coordinates and angles, MR images with plastic chambers in place (monkey L, right chamber; monkey F, left chamber only), and grid coordinates of the recording sites. Stereotaxically aligned coronal images were taken at the approximate anteroposterior position corresponding to the middle of the chamber. The diagram inset visualizes the tilt of the recording chamber. Sulci were reconstructed to resemble a view point along the electrode penetration pathway. The two chambers of monkey L were implanted at an angle approximately perpendicular to the cortical surface. As a result, the openings (black) and the fundi of the sulci (gray) are approximately overlapping, allowing a continuous penetration along the banks of the arcuate sulcus. The chamber in monkey F was implanted vertically. Hence, the openings of the sulci are more lateral than the fundi. MR image of monkey F with the chamber in place had a low signal-to-noise ratio and suffered from artifacts attributable to cortical screws. Hence, the reconstruction of the openings of the sulci is less accurate and was partially based on a extrapolation from a previous MR image without the chamber in place. In two of the chambers, microstimulation was used to verify the FEF by evoking microsaccades with a stimulation current of <50 μA (black dots). The response properties of neurons in a standard memory-guided saccade task were visualized using different semitransparent colors (see legend). Similar profiles of selectivity toward visual/memory (red) and motor (blue) were found in each recording location. The majority of the recording sites could be localized to the FEF. However, some sites were positioned in the surrounding periarcuate cortex, including area 46. Four recording sites in monkey F were reconstructed to vPM. Excluding these cells from the analysis had no qualitative influence on our results.

Figure 3.

A, Proportion of errors as a function of difficulty and reward bias (box-and-whisker plots indicate the 0.05, 0.25, 0.75, and 0.95 quantiles over recording sessions). Relative to the neutral condition (black), error rate approximately doubled when the reward schedule favored the wrong target (red). In contrast, error rate dropped when reward and stimulus speed favored the same response. B, Proportion of revised trials as a function of difficulty and accuracy of the initial choice (mean ± SE over recording sessions). Both animals almost exclusively revised wrong choices and were more likely to revise if the trial was easy.

Figure 4.

Spike raster (top), PSTH (medium), and horizontal eye position (bottom) aligned to saccade onset. An FEF example neuron increased firing rate after choice errors (A) and difficult (correct) trials (B) independent of saccade direction. C, Normalized firing rate of a second example neuron as a function of error and difficulty in the time window from 0 to 300 ms after saccade onset (mean ± SE). RF, Receptive field.

Figure 5.

A, Parameter estimates for ipsilateral and contralateral errors have a significant and robust correlation. B, Comparison of error cells identified with the standard test (red) and the balanced error test (green). Note that the balanced test is more rigorous and excludes many cells that pass the standard test for error cells.

Figure 6.

Reaction time and saccade velocity. A, B, Raw reaction time distributions for error (red) and correct (black) responses. C, D, Normalized reaction time (mean ± SE across recording sessions) as a function of task difficulty (x-axis) and outcome (error, red; correct, black). For each session, we fit reaction time as a linear function of task difficulty and outcome. One model included only main effects of task difficulty (β_d) and error (β_e). A second model included their interaction (β_d,e). To account for potentially unbalanced effects of time within the session, saccade direction, category choice, and the value of the chosen option, we included these variables as predictors in the model. For each session, normalized reaction time was defined as the parameter estimates for outcome and difficulty (β_d,e). Note that this is a purely additive normalization that subtracts mean and other potential confounds. For a balanced design, these values correspond to the corresponding group means minus the overall mean. The parameter estimates of error (β_e) and difficulty (β_d) were then fed into a two-tailed t test. The results of these tests is indicated in the top of each panel (difficulty, black; error, red). E, F, Raw main sequence of error and correct trials. G, H, Normalized peak saccade velocity (mean ± SE across recording sessions). Conventions as in C and D. Because of the different nature of the dependent variable, we added saccade amplitude and reaction time as predictors to the linear model.

Figure 7.

Analysis of postdecision eye movements. A, B, Timing of subsequent saccades as a function of time after the execution of the choice saccade separated by outcome (error, red; correct, black; revised, blue). The cumulative distribution plots reveal subsequent waves of eye movements separated by ∼300 ms. C, D, Timing and amplitude of the first two sets of saccades for a random sample of trials. This figure reveals three different types of postdecision saccades: (1) type 1, small fixational eye movements; (2) type 2a and 2b, large saccades that move the eye out of the fixation window; and (3) type 3, compensation for initially hypometric choice saccades (only present in animal L). E, F, Density distribution of the latencies of type 2 break saccades indicate clear differences between all trial 3 types (blue, revised; red, error; black, correct). The differences between error and correct trials reflect the fact that subjects were required to maintain fixation to collect the reward after the delivery of positive auditory feedback. After negative feedback, the animals could not be encouraged to maintain fixation. Revised trials (type 2b) are by definition earlier than regular break saccades (type 2a).

Figure 8.

A, Across the population, parameter estimates for error and task difficulty exhibit a significant positive correlation. Positive parameters indicate stronger firing after errors and difficult trials. B, Normalized firing rates as a function of difficulty and error for 32 neurons with a main effect error or an interaction of error and difficulty (mean ± SE). The data were split in two groups depending on whether the parameter estimate for error was positive (gray) or negative (black). C, Number of cells with error-related and difficulty signals as a function of direction selectivity in the memory-guided saccade task. Note that many cells had significant directionally tuned activity in more than one epoch. Hence, the numbers in the different columns do not add up to the total number of cells. Note that error-related and difficulty signals are present in all cell types, regardless of directional tuning. D, Choice probabilities (area under the curve of ROC) as a function of difficulty for all neurons with a significant main effect of balanced error or an interaction of balanced error and difficulty. Firing rate was normalized by subtracting out all predictors of the “drop” model except difficulty, error, and their interaction. The residual firing rate was then divisively normalized to an SD of 1. In addition, normalization involved multiplication with the sign of the parameter of the error regressor to enable the averaging of cells with firing-rate increase and decrease in the same plot. Choice probabilities were computed within each level of difficulty. Errors on easy trials were rare, and here we included the ROC values only if more than four errors were observed for a particular difficulty. The bars in the top part of the panel indicate the outcome of a paired t test between the ROC values observed for different difficulty levels. *p = 0.05, **p = 0.01, and ***p = 0.001. Our results show that the separation of firing rates is stronger for easy compared with medium and difficult trials. E, Normalized population responses for correct, error, and revised trials as a function of task difficulty. The sample includes cells that had a significant effect of balanced error or an interaction of error and difficulty and at least one revised trial. The analysis window included times from −200 to 0 ms before the execution of a revised saccade. For trials without a revised saccade, we randomly picked a time from one of the revised trials. A population-based one-sided one-sample t test showed that responses were significantly stronger before revised than unrevised errors (t = 2.1395, df = 25, p = 0.02117). Very similar results were found in the standard saccade-locked window from 0 to 300 ms after onset of the choice saccade. However, the effect did not reach significance in this window (p < 0.1). F, Cells with error-related and difficulty signals were observed in all three animals without specific clustering to a particular part of the dorsolateral PFC. Two error/difficulty cells were reconstructed in the vPM. Excluding the vPM cells did not affect the main findings. ant, Anterior; post, posterior.

Figure 9.

Relative timing of error and difficulty signal in the FEF. Time point t includes spikes from t − 100ms to t + 100 ms. A, B, Proportion of cells with a significant effect of error (red) and difficulty (black) as a function of time from stimulus and saccade onset. C, Earliest onset of the error and difficulty signal relative to saccade onset for all cells with both effects. The two variables are significantly correlated. Difficulty signals emerge 50 ms earlier than error signals. D–F, Same conventions as in A–C but for balanced error/difficulty. The timing differences observed for the unbalanced tests are no longer significant.

Figure 10.

A, Error rate for subsets of trials defined by normalized firing rate. Normalization was performed in the same way as for the ROC analysis, i.e., based on the residuals of a model that excluded error, difficulty, and their interaction. Note that, as for the ROC analysis, the residuals were multiplied with the sign of the parameter of the error regressor to combine cells with firing-rate increase and decrease in the same analysis. The values on the y-axis indicate the fraction of errors in the trials that exceeded the firing-rate criterion defined on the x-axis. For example, when the x-axis equals zero, the data displayed on the y-axis include all trials. Hence, the value of ∼0.2 on the y-axis indicates that, across all trials, mean error rate for the included recording sessions was ∼20%. For trials in the top 10 percentiles (x-axis equal to 0.9), mean error rate increased to ∼35%. The analysis was performed for all cells that had a significant main effect of error or a significant interaction of error and difficulty. Results of individual cells are depicted in gray, and the grand average is indicated in black. Instances in which the error rate is significantly larger than chance are indicated by black dots. The x-axis ends at 0.95 because, for higher values, the number of eligible trials is too small to yield reliable estimates. However, the trend continues and the mean error rate keeps rising if the x-axis is extended beyond 0.95 (data not shown). B, Effect of the chosen value. Normalized firing rate as a function of error and difficulty split by the value of the chosen target (black, large reward; gray, small reward). The traces from individual neurons were multiplied by −1 if the parameter estimate for error was positive. This way, all normalized firing rates are larger for correct trials. An open circle indicates a nonsignificant outcome. *p = 0.05.