Decoding the future from past experience: learning shapes predictions in early visual cortex

Journal of Neurophysiology
Caroline D B LuftZoe Kourtzi

Abstract

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory r...Continue Reading

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Citations

Apr 16, 2016·Annals of the New York Academy of Sciences·Charan Ranganath, Liang-Tien Hsieh
Mar 12, 2019·Frontiers in Psychology·Caroline Di Bernardi LuftJoydeep Bhattacharya
May 25, 2021·PLoS Computational Biology·Kristjan Kalm, Dennis Norris

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Software Mentioned

MATLAB
EyeNal Data Analysis
Psychtoolbox
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