Literature DB >> 26350626

Prior probability modulates anticipatory activity in category-specific areas.

Sabrina Trapp1, Jöran Lepsien2, Sonja A Kotz2,3, Moshe Bar4.   

Abstract

Bayesian models are currently a dominant framework for describing human information processing. However, it is not clear yet how major tenets of this framework can be translated to brain processes. In this study, we addressed the neural underpinning of prior probability and its effect on anticipatory activity in category-specific areas. Before fMRI scanning, participants were trained in two behavioral sessions to learn the prior probability and correct order of visual events within a sequence. The events of each sequence included two different presentations of a geometric shape and one picture of either a house or a face, which appeared with either a high or a low likelihood. Each sequence was preceded by a cue that gave participants probabilistic information about which items to expect next. This allowed examining cue-related anticipatory modulation of activity as a function of prior probability in category-specific areas (fusiform face area and parahippocampal place area). Our findings show that activity in the fusiform face area was higher when faces had a higher prior probability. The finding of a difference between levels of expectations is consistent with graded, probabilistically modulated activity, but the data do not rule out the alternative explanation of a categorical neural response. Importantly, these differences were only visible during anticipation, and vanished at the time of stimulus presentation, calling for a functional distinction when considering the effects of prior probability. Finally, there were no anticipatory effects for houses in the parahippocampal place area, suggesting sensitivity to stimulus material when looking at effects of prediction.

Entities:  

Keywords:  Anticipation; Bayesian; Fusiform face area; Likelihood; Predictive coding; Statistical learning

Mesh:

Year:  2016        PMID: 26350626     DOI: 10.3758/s13415-015-0373-4

Source DB:  PubMed          Journal:  Cogn Affect Behav Neurosci        ISSN: 1530-7026            Impact factor:   3.282


  41 in total

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3.  Bayesian integration in sensorimotor learning.

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5.  Top-down activation of shape-specific population codes in visual cortex during mental imagery.

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6.  Category expectation modulates baseline and stimulus-evoked activity in human inferotemporal cortex.

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7.  Less is more: expectation sharpens representations in the primary visual cortex.

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8.  The parahippocampal cortex mediates spatial and nonspatial associations.

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Review 9.  Expectation (and attention) in visual cognition.

Authors:  Christopher Summerfield; Tobias Egner
Journal:  Trends Cogn Sci       Date:  2009-08-27       Impact factor: 20.229

10.  Concurrent repetition enhancement and suppression responses in extrastriate visual cortex.

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  9 in total

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2.  P300 amplitude variations, prior probabilities, and likelihoods: A Bayesian ERP study.

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Review 3.  Integrating predictive frameworks and cognitive models of face perception.

Authors:  Sabrina Trapp; Stefan R Schweinberger; William G Hayward; Gyula Kovács
Journal:  Psychon Bull Rev       Date:  2018-12

4.  Neuroimaging results suggest the role of prediction in cross-domain priming.

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5.  Expectation affects learning and modulates memory experience at retrieval.

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6.  Bayesian decision-making under stress-preserved weighting of prior and likelihood information.

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Journal:  Sci Rep       Date:  2020-12-08       Impact factor: 4.379

Review 7.  Predicting Affective Information - An Evaluation of Repetition Suppression Effects.

Authors:  Sabrina Trapp; Sonja A Kotz
Journal:  Front Psychol       Date:  2016-09-09

Review 8.  Evaluating the neurophysiological evidence for predictive processing as a model of perception.

Authors:  Kevin S Walsh; David P McGovern; Andy Clark; Redmond G O'Connell
Journal:  Ann N Y Acad Sci       Date:  2020-03-08       Impact factor: 5.691

9.  Object recognition is enabled by an experience-dependent appraisal of visual features in the brain's value system.

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  9 in total

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