bioRxivNeurosciencePreprint
EEG biomarkers of reinforcement learning and motivation: A multi-task battery
Zeguo QiuiD, Muzhi WangiD, Haoyang LuiD, Yaniv AbiriD, Raziya Zharmakhan, Nikki Singh, Michaela PoppeiD, Luigi DegniiD, Quentin J. M. HuysiD
Abstract
Serotonin and dopamine make dissociable contributions to reinforcement learning (RL) sub-components, yet we lack neural biomarkers capable of detecting their differential effects. Here, we report the development of a five-task EEG battery designed to probe these dissociable RL mechanisms. Using a model-free analytical approach in healthy volunteers, we identify distinct neural markers across probabilistic instrumental learning, motivational vigour, Pavlovian-instrumental transfer, reversal learning, and a working memory-RL task. A centroparietal P300 tracked incremental learning across three paradigms and showed cross-task convergent validity. Readiness potentials and beta suppression indexed value-based motor preparation, while frontal theta captured Pavlovian-instrumental conflict. The largely independent pattern across markers supports the batterys capacity to detect selective pharmacological effects on distinct neural systems.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 0
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