Adaptive reliance on the most stable sensory predictions enhances perceptual feature extraction of moving stimuli

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dc.contributor.author Kumar, Neeraj
dc.contributor.author Mutha, Pratik K.
dc.date.accessioned 2016-02-12T12:21:33Z
dc.date.available 2016-02-12T12:21:33Z
dc.date.issued 2016-03-25
dc.identifier.citation Kumar, Neeraj and Mutha, Pratik K., “Adaptive reliance on the most stable sensory predictions enhances perceptual feature extraction of moving stimuli”, Journal of Neurophysiology, DOI: 10.1152/jn.00850.2015, vol. 115, no. 3, pp. 1654-1663,25, Mar. 2016.
dc.identifier.issn 0022-3077
dc.identifier.uri http://dx.doi.org/10.1152/jn.00850.2015
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/2092
dc.description.abstract Predicting the sensory outcomes of action is thought to be useful for distinguishing self- versus externally-generated sensations, correcting movements when sensory feedback is delayed and learning predictive models for motor behavior. Here we show that aspects of another fundamental function, perception, are enhanced when they entail the contribution of predicted sensory outcomes, and that this enhancement relies on the adaptive use of the most stable predictions available. We combined a motor learning paradigm that imposes new sensory predictions with a dynamic visual search task to first show that perceptual feature extraction of a moving stimulus is poorer when it is based on sensory feedback that is misaligned with those predictions. This was possible because our novel experimental design allowed us to override the "natural" sensory predictions present when any action is performed, and separately examine the influence of these two sources on perceptual feature extraction. We then show that if the new predictions induced via motor learning are unreliable, rather than relying just on sensory information for perceptual judgments as is conventionally thought, subjects adaptively transition to using other, stable sensory predictions to maintain greater accuracy in their perceptual judgments. Finally, we show that when sensory predictions are not modified at all, these judgments are sharper when subjects combine their natural predictions with sensory feedback. Collectively, our results highlight the crucial contribution of sensory predictions to perception and also suggest that the brain intelligently integrates the most stable predictions available with sensory information to maintain high fidelity in perceptual decisions. en_US
dc.description.statementofresponsibility by Neeraj Kumar and Pratik K Mutha
dc.format.extent vol. 115, no. 3, pp. 1654-1663
dc.language.iso en_US en_US
dc.publisher American Physical Society en_US
dc.subject Stable sensory predictions en_US
dc.subject Extraction of moving stimuli en_US
dc.subject Adaptive reliance en_US
dc.subject Motor control en_US
dc.subject Perception en_US
dc.subject Sensory predictions en_US
dc.subject Forward model en_US
dc.subject Motor learning en_US
dc.title Adaptive reliance on the most stable sensory predictions enhances perceptual feature extraction of moving stimuli en_US
dc.type Article en_US
dc.relation.journal Journal of Neurophysiology


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