Literature DB >> 21859598

Inter-individual differences in fMRI entropy measurements in old age.

Moses O Sokunbi1, Roger T Staff, Gordon D Waiter, Trevor S Ahearn, Helen C Fox, Ian J Deary, John M Starr, Lawrence J Whalley, Alison D Murray.   

Abstract

We investigated the association between individual differences in cognitive performance in old age and the approximate entropy (ApEn) measured from functional magnetic resonance imaging (fMRI) data acquired from 40 participants of the Aberdeen Birth Cohort 1936 (ABC1936), while undergoing a visual information processing task: inspection time (IT). Participants took a version of the Moray House Test (MHT) No. 12 at age 11, a valid measure of childhood intelligence. The same individuals completed a test of non-verbal reasoning (Raven's Standard Progressive Matrices [RPM]) aged about 68 years. The IT, MHT and RPM scores were used as indicators of cognitive performance. Our results show that higher regional signal entropy is associated with better cognitive performance. This finding was independent of ability in childhood but not independent of current cognitive ability. ApEn is used for the first time to identify a potential source of individual differences in cognitive ability using fMRI data.

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Year:  2011        PMID: 21859598     DOI: 10.1109/TBME.2011.2164793

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  23 in total

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4.  Willingness towards cognitive engagement: a preliminary study based on a behavioural entropy approach.

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Journal:  Exp Brain Res       Date:  2019-01-31       Impact factor: 1.972

5.  Rostro-caudal Architecture of the Frontal Lobes in Humans.

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6.  Multiple time scale complexity analysis of resting state FMRI.

Authors:  Robert X Smith; Lirong Yan; Danny J J Wang
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8.  Brain entropy mapping using fMRI.

Authors:  Ze Wang; Yin Li; Anna Rose Childress; John A Detre
Journal:  PLoS One       Date:  2014-03-21       Impact factor: 3.240

9.  Network complexity as a measure of information processing across resting-state networks: evidence from the Human Connectome Project.

Authors:  Ian M McDonough; Kaoru Nashiro
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10.  Nonlinear complexity analysis of brain FMRI signals in schizophrenia.

Authors:  Moses O Sokunbi; Victoria B Gradin; Gordon D Waiter; George G Cameron; Trevor S Ahearn; Alison D Murray; Douglas J Steele; Roger T Staff
Journal:  PLoS One       Date:  2014-05-13       Impact factor: 3.240

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