Individual neurons in the cingulate cortex encode action monitoring, not selection, during adaptive decision-making

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Abstract

The cingulate cortex contributes to complex, adaptive behaviors, but the exact nature of its contributions remains unresolved. Proposals from previous studies, including evaluating past actions or selecting future ones, have been difficult to distinguish in part because of an incomplete understanding of the task-relevant variables that are encoded by individual cingulate neurons. In this study, we recorded from individual neurons in parts of both the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) in 2 male rhesus monkeys performing a saccadic reward task. The task required them to use adaptive, feedback-driven strategies to infer the spatial location of a rewarded saccade target in the presence of different forms of uncertainty. We found that task-relevant, spatially selective feedback signals were encoded by the activity of individual neurons in both brain regions, with stronger selectivity for spatial choice and reward-target signals in PCC and stronger selectivity for feedback in ACC. Moreover, neurons in both regions were sensitive to sequential effects of feedback that partly reflected sequential behavioral patterns. However, neither brain region exhibited systematic modulations by the blockwise conditions that governed the reliability of the trial-by-trial feedback and drove adaptive behavioral patterns. There was also little evidence that single-neuron responses in either brain region directly predicted the extent to which feedback and contextual information were used to inform choices on the subsequent trial. Thus, certain cingulate neurons encode diverse, evaluative signals needed for adaptive, feedback-driven decision-making, but those signals may be integrated elsewhere in the brain to guide actions.

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Li, Y. S., Nassar, M. R., Kable, J. W., & Gold, J. I. (2019). Individual neurons in the cingulate cortex encode action monitoring, not selection, during adaptive decision-making. Journal of Neuroscience, 39(34), 6668–6683. https://doi.org/10.1523/JNEUROSCI.0159-19.2019

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