Learning-dependent plasticity with and without training in the human brain.

Proceedings of the National Academy of Sciences of the United States of America
Jiaxiang Zhang, Zoe Kourtzi

Abstract

Long-term experience through development and evolution and shorter-term training in adulthood have both been suggested to contribute to the optimization of visual functions that mediate our ability to interpret complex scenes. However, the brain plasticity mechanisms that mediate the detection of objects in cluttered scenes remain largely unknown. Here, we combine behavioral and functional MRI (fMRI) measurements to investigate the human-brain mechanisms that mediate our ability to learn statistical regularities and detect targets in clutter. We show two different routes to visual learning in clutter with discrete brain plasticity signatures. Specifically, opportunistic learning of regularities typical in natural contours (i.e., collinearity) can occur simply through frequent exposure, generalize across untrained stimulus features, and shape processing in occipitotemporal regions implicated in the representation of global forms. In contrast, learning to integrate discontinuities (i.e., elements orthogonal to contour paths) requires task-specific training (bootstrap-based learning), is stimulus-dependent, and enhances processing in intraparietal regions implicated in attention-gated learning. We propose that long-term experience...Continue Reading

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Citations

Jul 19, 2013·The Journal of Neuroscience : the Official Journal of the Society for Neuroscience·Jiaxiang ZhangJames B Rowe
May 2, 2012·Neural Plasticity·Annette Sterr, Adriana Bastos Conforto
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Apr 25, 2014·Annals of the New York Academy of Sciences·Kazuhisa ShibataTakeo Watanabe
Apr 29, 2014·Frontiers in Computational Neuroscience·Rodrigo SigalaPetra Ritter
Sep 25, 2014·Annual Review of Psychology·Takeo Watanabe, Yuka Sasaki
Jun 1, 2016·Cerebral Cortex·Shu-Guang KuaiZoe Kourtzi
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Jul 21, 2017·Annual Review of Vision Science·Barbara Dosher, Zhong-Lin Lu
Nov 24, 2020·Journal of Cognitive Neuroscience·Robert M Mok, Bradley C Love

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