DOI: 10.1111/ejn.70641 ISSN: 0953-816X

Distinct High‐Gamma Signals in Primate Prefrontal Cortex Differentiate Cue Information, Preference Revision, and Expected Reward During Value‐Based Decisions

Renée Johnston, Chadwick Boulay, Laurence Hunt, Steven W. Kennerley, Adam J. Sachs

ABSTRACT

Understanding how prefrontal cortex (PFC) signals evolve over time to support decision‐making requires characterizing both the spectral and temporal structure of neural activity. High‐gamma (Hγ) power in local field potentials (LFPs) reflects local population firing, yet its role in differentiating cue‐driven preference revision, reward expectation, and outcome‐related signals during reward‐guided decisions remains unclear. We recorded LFPs from the anterior cingulate cortex (ACC), dorsolateral PFC (DLPFC), and orbitofrontal cortex (OFC) in macaques performing a multicue reward‐based decision task in which up to four sequential cues indicated the expected reward associated with competing targets. Hγ power was extracted in sliding windows aligned to key task events, and support vector machine classifiers were used to decode cue‐driven preference revision, reward expectation, cue value level and position, target choice, and prediction‐error contrasts. Hγ responses robustly differentiated preference‐reversal from confirmation trials, with subject‐specific modulation patterns across PFC subregions. Cue value level and spatial position were reliably decoded across PFC, with stronger differentiation of cue value level in OFC and cue position in DLPFC. Around movement onset, Hγ activity differentiated high versus low expected reward across PFC, with decoding accuracies reaching 85% in ACC. Hγ was also modulated by unexpected reward omission, yielding 78% decoding accuracy from a single OFC channel. These findings demonstrate that Hγ activity across PFC subregions differentiates multiple computationally defined decision variables with distinct temporal profiles and overlapping regional contributions, highlighting Hγ as a robust marker of dynamic reward‐guided decision processes.

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