Literature DB >> 15589194

Changes in neural complexity of the EEG during a visual oddball task.

Neil M Branston1, Wael El-Deredy, Francis P McGlone.   

Abstract

OBJECTIVE: Neural complexity (C(N)) was introduced by Tononi et al. in an information-theoretic framework to capture the balance between functional specialisation and integration in the brain. We hypothesised that C(N) should vary during cognitive processing, specifically during an oddball task.
METHODS: In 11 normal human subjects, we recorded from groups of EEG electrodes in the frontal (F), central-parietal (CP) and occipito-temporal (OT) regions during a visual oddball reward conditioning task and calculated C(N) in each region. Three types of visual stimulus (abstract shapes, called neutral, reward and penalty) were presented randomly in three blocks of trials. During the first block, subjects did not know the significance of the stimulus shapes. For the subsequent (conditioning) blocks, subjects were informed that whenever they saw reward or penalty patterns, they would win or lose money, respectively.
RESULTS: In regions CP and OT, C(N) was significantly larger in reward and penalty trials than in neutral during all blocks. During a trial, significant changes in C(N) occurred around the ERP peaks N1 and P300 and the effects of reward conditioning on C(N) could be distinguished from penalty.
CONCLUSIONS: Our findings support the above hypothesis, indicating that C(N) correlates with both the sensory and cognitive components of stimulus processing. SIGNIFICANCE: This study extends the scope of C(N) in the analysis of cognitive processing.

Entities:  

Mesh:

Year:  2005        PMID: 15589194     DOI: 10.1016/j.clinph.2004.07.015

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  3 in total

1.  Compromised sensitivity to monetary reward in current cocaine users: an ERP study.

Authors:  Rita Z Goldstein; Muhammad A Parvaz; Thomas Maloney; Nelly Alia-Klein; Patricia A Woicik; Frank Telang; Gene-Jack Wang; Nora D Volkow
Journal:  Psychophysiology       Date:  2008-05-30       Impact factor: 4.016

2.  The Effect of Electroencephalogram (EEG) Reference Choice on Information-Theoretic Measures of the Complexity and Integration of EEG Signals.

Authors:  Logan T Trujillo; Candice T Stanfield; Ruben D Vela
Journal:  Front Neurosci       Date:  2017-07-25       Impact factor: 4.677

3.  K-th Nearest Neighbor (KNN) Entropy Estimates of Complexity and Integration from Ongoing and Stimulus-Evoked Electroencephalographic (EEG) Recordings of the Human Brain.

Authors:  Logan T Trujillo
Journal:  Entropy (Basel)       Date:  2019-01-13       Impact factor: 2.524

  3 in total

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