Literature DB >> 29311143

Neural Integration of Stimulus History Underlies Prediction for Naturalistically Evolving Sequences.

Brian Maniscalco1,2, Jennifer L Lee2, Patrice Abry3, Amy Lin1,4, Tom Holroyd5, Biyu J He6,2,7.   

Abstract

Forming valid predictions about the environment is crucial to survival. However, whether humans are able to form valid predictions about natural stimuli based on their temporal statistical regularities remains unknown. Here, we presented subjects with tone sequences with pitch fluctuations that, over time, capture long-range temporal dependence structures prevalent in natural stimuli. We found that subjects were able to exploit such naturalistic statistical regularities to make valid predictions about upcoming items in a sequence. Magnetoencephalography (MEG) recordings revealed that slow, arrhythmic cortical dynamics tracked the evolving pitch sequence over time such that neural activity at a given moment was influenced by the pitch of up to seven previous tones. Importantly, such history integration contained in neural activity predicted the expected pitch of the upcoming tone, providing a concrete computational mechanism for prediction. These results establish humans' ability to make valid predictions based on temporal regularities inherent in naturalistic stimuli and further reveal the neural mechanisms underlying such predictive computation.SIGNIFICANCE STATEMENT A fundamental question in neuroscience is how the brain predicts upcoming events in the environment. To date, this question has primarily been addressed in experiments using relatively simple stimulus sequences. Here, we studied predictive processing in the human brain using auditory tone sequences that exhibit temporal statistical regularities similar to those found in natural stimuli. We observed that humans are able to form valid predictions based on such complex temporal statistical regularities. We further show that neural response to a given tone in the sequence reflects integration over the preceding tone sequence and that this history dependence forms the foundation for prediction. These findings deepen our understanding of how humans form predictions in an ecologically valid environment.
Copyright © 2018 the authors 0270-6474/18/381541-17$15.00/0.

Entities:  

Keywords:  1/f activity; magnetoencephalography; naturalistic stimuli; predictive processing; scale-free dynamics

Mesh:

Year:  2018        PMID: 29311143      PMCID: PMC5815353          DOI: 10.1523/JNEUROSCI.1779-17.2017

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


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Review 3.  Evaluating the neurophysiological evidence for predictive processing as a model of perception.

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