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.

Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias

“…Last, in contrast to most previous pupillometry studies294243 we comprehensively quantified the predictive effects of pupil-linked arousal on the parameters of choice beyond the current trial, thereby complementing recent work on the effects of pupil-linked arousal on learning940. Taken together, our results critically advance the understanding of how internal decision uncertainty is encoded in pupil-linked arousal in humans, in a way that builds a direct bridge to single-unit recording studies of decision uncertainty in animals2202122.…”

Visuomotor Functions in the Frontal Lobe

“…Such signals are likely the source of an ERP component known as the error-related and feedback-related negativity (Godlove et al 2011, Phillips & Everling 2014) because it occurs after and is modulated by the conditions in which an error is performed (Gehring et al 2012). The cerebral source of this error may be more extensive, though, as error signals have been described in the FEF (Teichert et al 2014). Other neurons in the SEF-but not in the ACC-are modulated by conflict between Target selection times across the visual pathway.…”

Implicit value updating explains transitive inference performance: The betasort model

“…These pulses were recorded by the computer using a hardware timer and stored together with the eye movement data. Unless otherwise noted, the apparatus was identical to that described by Teichert et al (2014).…”