Episodes, events, and models
We describe a novel computational theory of how individuals segment perceptual information into representations of events. The theory is inspired by recent findings in the cognitive science and cognitive neuroscience of event segmentation. In line with recent theories, it holds that online event seg...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2015-10-01
|
Series: | Frontiers in Human Neuroscience |
Subjects: | |
Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnhum.2015.00590/full |
id |
doaj-3e5b138edb304625a362b676dfd1717f |
---|---|
record_format |
Article |
spelling |
doaj-3e5b138edb304625a362b676dfd1717f2020-11-25T02:20:39ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612015-10-01910.3389/fnhum.2015.00590159116Episodes, events, and modelsSangeet eKhemlani0Anthony eHarrison1J. Gregory Trafton2Naval Research LaboratoryNaval Research LaboratoryNaval Research LaboratoryWe describe a novel computational theory of how individuals segment perceptual information into representations of events. The theory is inspired by recent findings in the cognitive science and cognitive neuroscience of event segmentation. In line with recent theories, it holds that online event segmentation is automatic, and that event segmentation yields mental simulations of events. But it posits two novel principles as well: first, discrete episodic markers track perceptual and conceptual changes, and can be retrieved to construct event models. Second, the process of retrieving and reconstructing those episodic markers is constrained and prioritized. We describe a computational implementation of the theory, as well as a robotic extension of the theory that demonstrates the processes of online event segmentation and event model construction. The theory is the first unified computational account of event segmentation and temporal inference. We conclude by demonstrating now neuroimaging data can constrain and inspire the construction of process-level theories of human reasoning.http://journal.frontiersin.org/Journal/10.3389/fnhum.2015.00590/fullepisodic memoryevent segmentationMental Modelstemporal reasoningMDS robotACT-R/E |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sangeet eKhemlani Anthony eHarrison J. Gregory Trafton |
spellingShingle |
Sangeet eKhemlani Anthony eHarrison J. Gregory Trafton Episodes, events, and models Frontiers in Human Neuroscience episodic memory event segmentation Mental Models temporal reasoning MDS robot ACT-R/E |
author_facet |
Sangeet eKhemlani Anthony eHarrison J. Gregory Trafton |
author_sort |
Sangeet eKhemlani |
title |
Episodes, events, and models |
title_short |
Episodes, events, and models |
title_full |
Episodes, events, and models |
title_fullStr |
Episodes, events, and models |
title_full_unstemmed |
Episodes, events, and models |
title_sort |
episodes, events, and models |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Human Neuroscience |
issn |
1662-5161 |
publishDate |
2015-10-01 |
description |
We describe a novel computational theory of how individuals segment perceptual information into representations of events. The theory is inspired by recent findings in the cognitive science and cognitive neuroscience of event segmentation. In line with recent theories, it holds that online event segmentation is automatic, and that event segmentation yields mental simulations of events. But it posits two novel principles as well: first, discrete episodic markers track perceptual and conceptual changes, and can be retrieved to construct event models. Second, the process of retrieving and reconstructing those episodic markers is constrained and prioritized. We describe a computational implementation of the theory, as well as a robotic extension of the theory that demonstrates the processes of online event segmentation and event model construction. The theory is the first unified computational account of event segmentation and temporal inference. We conclude by demonstrating now neuroimaging data can constrain and inspire the construction of process-level theories of human reasoning. |
topic |
episodic memory event segmentation Mental Models temporal reasoning MDS robot ACT-R/E |
url |
http://journal.frontiersin.org/Journal/10.3389/fnhum.2015.00590/full |
work_keys_str_mv |
AT sangeetekhemlani episodeseventsandmodels AT anthonyeharrison episodeseventsandmodels AT jgregorytrafton episodeseventsandmodels |
_version_ |
1724870846012456960 |