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dc.contributor.authorGómez, C.
dc.contributor.authorLizier, J.
dc.contributor.authorSchaum, M.
dc.contributor.authorWollstadt, P.
dc.contributor.authorGrützner, C.
dc.contributor.authorUhlhaas, P.
dc.contributor.authorFreitag, C.
dc.contributor.authorSchlitt, S.
dc.contributor.authorBolte, Sven
dc.contributor.authorHornero, R.
dc.contributor.authorWibral, M.
dc.date.accessioned2018-02-06T10:02:04Z
dc.date.available2018-02-06T10:02:04Z
dc.date.created2018-02-06T09:25:46Z
dc.date.issued2014
dc.identifier.citationGómez, C. and Lizier, J. and Schaum, M. and Wollstadt, P. and Grützner, C. and Uhlhaas, P. and Freitag, C. et al. 2014. Reduced predictable information in brain signals in autism pectrum disorder. Frontiers in Neuroinformatics. 8 (FEB).
dc.identifier.urihttp://hdl.handle.net/20.500.11937/64630
dc.identifier.doi10.3389/fninf.2014.00009
dc.description.abstract

Autism spectrum disorder (ASD) is a common developmental disorder characterized by communication difficulties and impaired social interaction. Recent results suggest altered brain dynamics as a potential cause of symptoms in ASD. Here, we aim to describe potential information-processing consequences of these alterations by measuring active information storage (AIS)-a key quantity in the theory of distributed computation in biological networks. AIS is defined as the mutual information between the past state of a process and its next measurement. It measures the amount of stored information that is used for computation of the next time step of a process. AIS is high for rich but predictable dynamics. We recorded magnetoencephalography (MEG) signals in 10 ASD patients and 14 matched control subjects in a visual task. After a beamformer source analysis, 12 task-relevant sources were obtained. For these sources, stationary baseline activity was analyzed using AIS. Our results showed a decrease of AIS values in the hippocampus of ASD patients in comparison with controls, meaning that brain signals in ASD were either less predictable, reduced in their dynamic richness or both. Our study suggests the usefulness of AIS to detect an abnormal type of dynamics in ASD. The observed changes in AIS are compatible with Bayesian theories of reduced use or precision of priors in ASD. © 2014 Gómez, Lizier, Schaum, Wollstadt, Grützner, Uhlhaas, Freitag, Schlitt, Bölte, Horneroand Wibral.

dc.titleReduced predictable information in brain signals in autism pectrum disorder
dc.typeJournal Article
dcterms.source.volume8
dcterms.source.numberFEB
dcterms.source.issn1662-5196
dcterms.source.titleFrontiers in Neuroinformatics
curtin.accessStatusOpen access via publisher


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