Monitoring and proactive control of visual search speed-accuracy tradeoff by supplementary eye field

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Neurophysiological mechanisms of speed-accuracy tradeoff (SAT) have only recently been investigated. Previous studies with macaque monkeys showed that SAT of inefficient visual search was accomplished by modulation of salience map evidence representations in frontal eye field (FEF) and superior colliculus (SC). Saccade initiation occurred when movement activity was either reduced or equivalent in Accurate-cued relative to Fast-cued trials. Targeting errors occurred when salience neurons in the FEF and the SC treated distractors as targets. Here, we report new observations about SAT performance and neurophysiological results from the supplementary eye field (SEF), located in medial frontal cortex, which contributes to executive control of gaze behavior but not to saccade target selection. In two monkeys, we found natural preference for quick responding, with more choice inaccuracies. On trials with choice errors, the monkeys often executed a post-primary saccade to the foregone target, which was generated later in the Accurate than the Fast condition. SEF neurons signaled choice errors, and the magnitude of this signal predicted whether the post-primary saccade was corrective in nature. In the Accurate condition, when slower responding was required, the rate of choice errors decreased, but the rate of premature timing errors increased. After timing errors, SEF neurons signaled negative reward prediction error at the time of expected reward. We assessed the distribution of signaling of choice errors and reward prediction errors across the sample of SEF neurons. Some neurons signaled both types of error, whereas others signaled either choice error or reward prediction error. We also found evidence for proactive control of response time. Baseline activity was a strong predictor of response time in both Fast and Accurate conditions. Taken together, these results indicate that SEF may be a source of the modulation observed in FEF and SC and inform new models of distributed decision making.