Literature DB >> 1436649

Dimensional analysis of the human EEG and intelligence.

W Lutzenberger1, N Birbaumer, H Flor, B Rockstroh, T Elbert.   

Abstract

The purpose of this study was the determination of the relationship between the dimensional complexity of the electroencephalogam (EEG) and the level of intelligence in humans. In two experiments 34 male subjects were divided into two groups, with high and low levels of intelligence (as measured by the intelligence quotient (IQ)). During a resting phase and various mental imagery conditions the EEG was recorded from several scalp sites. Nonlinear analysis, based on the theory of deterministic chaos, revealed that subjects with high IQs demonstrate higher dimensional complexity of the EEG attractors than subjects with low IQs only during resting conditions. During performance of the imagery tasks the less intelligent subjects increase the complexity of electrical brain dynamics such that IQ-dependency vanishes. The gross (mass) neuronal manifestation of general intelligence seems to depend on task conditions and may be related to the individual brain dynamics only when no specific task is present.

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Year:  1992        PMID: 1436649     DOI: 10.1016/0304-3940(92)90221-r

Source DB:  PubMed          Journal:  Neurosci Lett        ISSN: 0304-3940            Impact factor:   3.046


  8 in total

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Review 2.  "Dynamic" connectivity in neural systems: theoretical and empirical considerations.

Authors:  Michael Breakspear
Journal:  Neuroinformatics       Date:  2004

3.  Genetic influences on dynamic complexity of brain oscillations.

Authors:  Andrey P Anokhin; Viktor Müller; Ulman Lindenberger; Andrew C Heath; Erin Myers
Journal:  Neurosci Lett       Date:  2006-01-27       Impact factor: 3.046

4.  Surrogate data analysis of sleep electroencephalograms reveals evidence for nonlinearity.

Authors:  J Fell; J Röschke; C Schäffner
Journal:  Biol Cybern       Date:  1996-07       Impact factor: 2.086

5.  Nonlinear analysis of sleep EEG in depression: calculation of the largest lyapunov exponent.

Authors:  J Röschke; J Fell; P Beckmann
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  1995       Impact factor: 5.270

6.  Intelligence and eeg measures of information flow: efficiency and homeostatic neuroplasticity.

Authors:  R W Thatcher; E Palmero-Soler; D M North; C J Biver
Journal:  Sci Rep       Date:  2016-12-20       Impact factor: 4.379

Review 7.  The clinical use of quantitative EEG in cognitive disorders.

Authors:  Paulo Afonso de Medeiros Kanda; Renato Anghinah; Magali Taino Smidth; Jorge Mario Silva
Journal:  Dement Neuropsychol       Date:  2009 Jul-Sep

8.  Spatiotemporal complexity patterns of resting-state bioelectrical activity explain fluid intelligence: Sex matters.

Authors:  Joanna Dreszer; Marek Grochowski; Monika Lewandowska; Jan Nikadon; Joanna Gorgol; Bibianna Bałaj; Karolina Finc; Włodzisław Duch; Patrycja Kałamała; Adam Chuderski; Tomasz Piotrowski
Journal:  Hum Brain Mapp       Date:  2020-08-18       Impact factor: 5.038

  8 in total

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