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Neural representations of metacognitive learning and the organization of future decision-making

Poster Session C - Sunday, March 8, 2026, 5:00 – 7:00 pm PDT, Fairview/Kitsilano Ballroom

Yoshinori Nanjo¹ (); ¹RIKEN Center for Brain Science, Japan, ²Hitotsubashi University, Japan

Self-estimation of our cognition is a hallmark of adaptive decision-making. Metacognition allows us to monitor internal computations and regulate cognitive control, yet how such self-estimation is calibrated through experience and deployed to shape future decisions remains poorly understood. We combined a random-dot motion discrimination with incentivized confidence reports to test whether discrepancies between expected and expressed self-estimation generate prediction-error signals that update an internal mapping from sensory evidence to self-estimation, and to identify the cortical representations of this learning. Participants made perceptual choices and reported confidence on each trial while recording neural activity using functional magnetic resonance imaging (fMRI). A computational learning account in which prediction-error signals updated an internal evaluation criterion explained progressive calibration of self-estimation in the absence of changes in perceptual sensitivity and captured prospective carryover to future choice policy, expressed as modulations of response caution and weighting of sensory evidence. Neuroimaging revealed cortical representations of self-estimation learning: pregenual anterior cingulate encoded prediction-error magnitude at evaluation; anterior prefrontal cortex encoded the prospective influence of these signals on later adjustments; and dorsal anterior cingulate expressed control-related implementation. Task-dependent functional coupling between anterior prefrontal and cingulate territories during evaluation predicted the magnitude and direction of subsequent policy change, and across participants, neural sensitivity to self-estimation learning correlated with the degree of behavioral reorganization. These findings show that metacognitive evaluation of our cognition is adaptively calibrated through learning and prospectively deployed, providing a cortical mechanism by which self-evaluation organizes future decision-making.

Topic Area: THINKING: Decision making