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Cohanpour, M.

Publications and source records attributed to Cohanpour, M..

2 recordsLinked to original sources

Distinct signatures of reward value and variance on spiking activity and functional interactions in monkey fronto-parietal areas

Theories of executive function propose that controlled information processing is costly and is allocated according to the behavioral benefits it brings. Computational theories predict that the benefits of new information depend on prior uncertainty, but the cellular effects of uncertainty on the executive network are incompletely understood. Using simultaneous recordings in monkeys, we reveal several mechanisms by which the fronto-parietal network reacts to uncertainty independently of average reward gains. We show that the variance of expected rewards, independently of the value of the rewards, was represented in single neuron and population spiking activity and local field potential (LFP) oscillations. Moreover, uncertainty asymmetrically affected the coherence between spikes and LFPs, selectively suppressing information transmission from the frontal to the parietal lobe but enhancing transmission from the parietal to the frontal lobe, consistent with Bayesian principles of optimal inference under uncertainty.

neuroscience

Frontal and parietal neurons encode reward prediction errors in multiple reference frames

Computing expectancy violations is essential for decision making and cognitive functions, but its neural mechanisms are incompletely understood. We describe a novel mechanism by which prefrontal and posterior parietal neurons encode reward prediction errors (RPEs) in their population but not single-neuron activity. Simultaneous recordings of neural populations showed that both areas co-activated information about experienced and expected rewards in a precise opponent organization. Neurons encoding expected rewards with positive (negative) scaling were reactivated simultaneously with those encoding experienced rewards with negative (positive) scaling. This opponent organization was mirrored in polarity-dependent noise correlations. Moreover, it extended to two types of expectancy information - based on task-relevant visual cues and statistically irrelevant reward history - allowing decoding of signed and unsigned RPE in two reference frames. Frontal and parietal areas implement canonical computations that facilitate contextual comparisons and the readout of multiple types of expectancy violations to flexibly serve behavioral goals.

neuroscience