Learning for perceptual decisions in the human brain
Learning is thought to facilitate our ability to perform complex perceptual tasks and optimize brain circuits involved in decision making. However, little is known about the experience-dependent plasticity mechanisms that support our ability to make fine perceptual judgments. We combine behavioral measurements, multimodal brain imaging recordings and advanced computational approaches to investigate the brain mechanisms that support adaptive sensory coding for perceptual decisions. We take advantage of the complementary high spatial and temporal resolution of simultaneous EEG-fMRI recording to identify the spatiotemporal dynamics between cortical networks involved in perceptual and categorical learning. We demonstrate that learning acts on distinct recognition processes and shapes interactions across brain areas to support complex perceptual decisions. In particular, learning shapes decision criteria in fronto-parietal circuits while neural selectivity to object features in higher occipito-temporal circuits. Thus, our findings suggest that learning optimizes a distributed neural code for perceptual decisions in the human brain.
Keywords:
Learning,
Visual Perception,
fMRI,
brain imaging,
Categorization
Conference:
Belgian Brain Council, Liège, Belgium, 27 Oct - 27 Oct, 2012.
Presentation Type:
Oral Presentation (only for invited speakers)
Topic:
Higher Brain Functions in health and disease: cognition and memory
Citation:
Kourtzi
Z
(2012). Learning for perceptual decisions in the human brain.
Conference Abstract:
Belgian Brain Council.
doi: 10.3389/conf.fnhum.2012.210.00134
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Received:
23 Jul 2012;
Published Online:
12 Sep 2012.