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Human inferences about sequences: A minimal transition probability model

The brain constantly infers the causes of the inputs it receives and uses these inferences to generate statistical expectations about future observations. Experimental evidence for these expectations and their violations include explicit reports, sequential effects on reaction times, and mismatch or... Full description

Journal Title: BioRxiv Nov 25, 2016
Main Author: Meyniel, Florent
Other Authors: Maheu, Maxime , Dehaene, Stanislas
Format: Electronic Article Electronic Article
Language: English
Subjects:
Quelle: © ProQuest LLC All rights reserved
ID: DOI: 10.1101/068346
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recordid: proquest2070370386
title: Human inferences about sequences: A minimal transition probability model
format: Article
creator:
  • Meyniel, Florent
  • Maheu, Maxime
  • Dehaene, Stanislas
subjects:
  • Electrophysiology
  • Bayesian Analysis
  • Functional Magnetic Resonance Imaging
ispartof: BioRxiv, Nov 25, 2016
description: The brain constantly infers the causes of the inputs it receives and uses these inferences to generate statistical expectations about future observations. Experimental evidence for these expectations and their violations include explicit reports, sequential effects on reaction times, and mismatch or...
language: eng
source: © ProQuest LLC All rights reserved
identifier: DOI: 10.1101/068346
fulltext: fulltext_linktorsrc
url: Link


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titleHuman inferences about sequences: A minimal transition probability model
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identifierDOI: 10.1101/068346
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abstractThe brain constantly infers the causes of the inputs it receives and uses these inferences to generate statistical expectations about future observations. Experimental evidence for these expectations and their violations include explicit reports, sequential effects on reaction times, and mismatch or...
copCold Spring Harbor
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doi10.1101/068346
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date2016-11-25