Literature DB >> 21671745

Prediction error associated with the perceptual segmentation of naturalistic events.

Jeffrey M Zacks1, Christopher A Kurby, Michelle L Eisenberg, Nayiri Haroutunian.   

Abstract

Predicting the near future is important for survival and plays a central role in theories of perception, language processing, and learning. Prediction failures may be particularly important for initiating the updating of perceptual and memory systems and, thus, for the subjective experience of events. Here, we asked observers to make predictions about what would happen 5 sec later in a movie of an everyday activity. Those points where prediction was more difficult corresponded with subjective boundaries in the stream of experience. At points of unpredictability, midbrain and striatal regions associated with the phasic release of the neurotransmitter dopamine transiently increased in activity. This activity could provide a global updating signal, cuing other brain systems that a significant new event has begun.

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Year:  2011        PMID: 21671745     DOI: 10.1162/jocn_a_00078

Source DB:  PubMed          Journal:  J Cogn Neurosci        ISSN: 0898-929X            Impact factor:   3.225


  44 in total

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2.  Starting from scratch and building brick by brick in comprehension.

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5.  The Ebb and Flow of Experience Determines the Temporal Structure of Memory.

Authors:  David Clewett; Lila Davachi
Journal:  Curr Opin Behav Sci       Date:  2017-10-03

Review 6.  Semantic memory: A review of methods, models, and current challenges.

Authors:  Abhilasha A Kumar
Journal:  Psychon Bull Rev       Date:  2021-02

7.  Neural representations of events arise from temporal community structure.

Authors:  Anna C Schapiro; Timothy T Rogers; Natalia I Cordova; Nicholas B Turk-Browne; Matthew M Botvinick
Journal:  Nat Neurosci       Date:  2013-02-17       Impact factor: 24.884

8.  Event perception: Translations and applications.

Authors:  Lauren L Richmond; David A Gold; Jeffrey M Zacks
Journal:  J Appl Res Mem Cogn       Date:  2017-06

9.  Learning to represent reward structure: a key to adapting to complex environments.

Authors:  Hiroyuki Nakahara; Okihide Hikosaka
Journal:  Neurosci Res       Date:  2012-10-13       Impact factor: 3.304

10.  Statistical learning of temporal community structure in the hippocampus.

Authors:  Anna C Schapiro; Nicholas B Turk-Browne; Kenneth A Norman; Matthew M Botvinick
Journal:  Hippocampus       Date:  2015-10-13       Impact factor: 3.899

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