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

Journal of Neurophysiology
Neeraj Kumar, Pratik K Mutha

Abstract

The prediction of the sensory outcomes of action is thought to be useful for distinguishing self- vs. 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 just relying on sensory information for perceptual judgments, as is conventionally thought, then subjects adaptively transition to using other stable sensory...Continue Reading

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Citations

Feb 17, 2017·Journal of the International Neuropsychological Society : JINS·Pratik K MuthaKathleen Y Haaland
Mar 17, 2018·Nature Communications·Martha L StrengTimothy J Ebner
Feb 28, 2019·Frontiers in Psychology·Miya K Rand, Herbert Heuer
Jan 31, 2019·Frontiers in Cellular Neuroscience·Laurentiu S Popa, Timothy J Ebner

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Methods Mentioned

BETA
feature extraction

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