Neural networks involved in mathematical thinking: evidence from linear and non-linear analysis of electroencephalographic activity

Using linear and non-linear methods, electroencephalographic (EEG) signals were measured at various brain regions to provide information regarding patterns of local and coordinated activity during performance of three arithmetic tasks (number comparison, single-digit multiplication, and two-digit mu...

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Bibliographic Details
Published in:Neuroscience letters 2005-01, Vol.373 (3), p.212-217
Main Authors: Micheloyannis, Sifis, Sakkalis, Vagelis, Vourkas, Michalis, Stam, Cornelis J., Simos, Panagiotis G.
Format: Article
Language:English
Subjects:
Adult
Analysis of Variance
Biological and medical sciences
Coherence
Electroencephalography
Electroencephalography - methods
Female
Fundamental and applied biological sciences. Psychology
Humans
Linear Models
Male
Mathematics
Nerve Net - physiology
Non-linear synchronization
Nonlinear Dynamics
Power spectrum
Thinking - physiology
Vertebrates: nervous system and sense organs
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Summary:Using linear and non-linear methods, electroencephalographic (EEG) signals were measured at various brain regions to provide information regarding patterns of local and coordinated activity during performance of three arithmetic tasks (number comparison, single-digit multiplication, and two-digit multiplication) and two control tasks that did not require arithmetic operations. It was hypothesized that these measures would reveal the engagement of local and increasingly complex cortical networks as a function of task specificity and complexity. Results indicated regionally increased neuronal signalling as a function of task complexity at frontal, temporal and parietal brain regions, although more robust task-related changes in EEG-indices of activation were derived over the left hemisphere. Both linear and non-linear indices of synchronization among EEG signals recorded from over different brain regions were consistent with the notion of more “local” processing for the number comparison task. Conversely, multiplication tasks were associated with a widespread pattern of distant signal synchronizations, which could potentially indicate increased demands for neural networks cooperation during performance of tasks that involve a greater number of cognitive operations.
ISSN:0304-3940
1872-7972
DOI:10.1016/j.neulet.2004.10.005