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Use of a neural mass model for the analysis of effective connectivity among cortical regions based on high resolution EEG recordings.

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Use of a neural mass model for the analysis of effective connectivity among cortical regions based on high resolution EEG recordings. / Ursino, Mauro; Zavaglia, Melissa; Astolfi, Laura; Babiloni, Fabio.

In: BIOL CYBERN, Vol. 96, No. 3, 3, 2007, p. 351-365.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Ursino, M, Zavaglia, M, Astolfi, L & Babiloni, F 2007, 'Use of a neural mass model for the analysis of effective connectivity among cortical regions based on high resolution EEG recordings.', BIOL CYBERN, vol. 96, no. 3, 3, pp. 351-365. <http://www.ncbi.nlm.nih.gov/pubmed/17115218?dopt=Citation>

APA

Ursino, M., Zavaglia, M., Astolfi, L., & Babiloni, F. (2007). Use of a neural mass model for the analysis of effective connectivity among cortical regions based on high resolution EEG recordings. BIOL CYBERN, 96(3), 351-365. [3]. http://www.ncbi.nlm.nih.gov/pubmed/17115218?dopt=Citation

Vancouver

Ursino M, Zavaglia M, Astolfi L, Babiloni F. Use of a neural mass model for the analysis of effective connectivity among cortical regions based on high resolution EEG recordings. BIOL CYBERN. 2007;96(3):351-365. 3.

Bibtex

@article{a917582400924764a10307d0604de3fe,
title = "Use of a neural mass model for the analysis of effective connectivity among cortical regions based on high resolution EEG recordings.",
abstract = "Assessment of brain connectivity among different brain areas during cognitive or motor tasks is a crucial problem in neuroscience today. Aim of this work is to use a neural mass model to assess the effect of various connectivity patterns in cortical electroencephalogram (EEG) power spectral density, and investigate the possibility to derive connectivity circuits from EEG data. To this end, a model of an individual region of interest (ROI) has been built as the parallel arrangement of three populations, each described as in Wendling et al. (Eur J Neurosci 15:1499-1508, 2002). Connectivity among ROIs includes three parameters, which specify the strength of connection in the different frequency bands. The following main steps have been followed: (1) we analyzed how the power spectral density (PSD) is significantly modified by the kind of coupling hypothesized among the ROIs; (2) with the model, and using an automatic fitting procedure, we looked for a simple connectivity circuit able to reproduce PSD of cortical EEG in three ROIs during a finger-movement task. The estimated parameters represent the strength of connections among the ROIs in the different frequency bands. Cortical EEGs were computed with an inverse propagation algorithm, starting from measurement performed with 96 electrodes on the scalp. The present study suggests that the model can be used as a simulation tool, able to mimic the effect of connectivity on EEG. Moreover, it can be used to look for simple connectivity circuits, able to explain the main features of observed cortical PSD. These results may open new prospectives in the use of neurophysiological models, instead of empirical models, to assess effective connectivity from neuroimaging information.",
keywords = "Humans, Models, Theoretical, *Brain Mapping, Spectrum Analysis, *Models, Neurological, Cerebral Cortex/*physiology, *Electroencephalography, Neural Pathways/*physiology, Humans, Models, Theoretical, *Brain Mapping, Spectrum Analysis, *Models, Neurological, Cerebral Cortex/*physiology, *Electroencephalography, Neural Pathways/*physiology",
author = "Mauro Ursino and Melissa Zavaglia and Laura Astolfi and Fabio Babiloni",
year = "2007",
language = "English",
volume = "96",
pages = "351--365",
journal = "BIOL CYBERN",
issn = "0340-1200",
publisher = "Springer",
number = "3",

}

RIS

TY - JOUR

T1 - Use of a neural mass model for the analysis of effective connectivity among cortical regions based on high resolution EEG recordings.

AU - Ursino, Mauro

AU - Zavaglia, Melissa

AU - Astolfi, Laura

AU - Babiloni, Fabio

PY - 2007

Y1 - 2007

N2 - Assessment of brain connectivity among different brain areas during cognitive or motor tasks is a crucial problem in neuroscience today. Aim of this work is to use a neural mass model to assess the effect of various connectivity patterns in cortical electroencephalogram (EEG) power spectral density, and investigate the possibility to derive connectivity circuits from EEG data. To this end, a model of an individual region of interest (ROI) has been built as the parallel arrangement of three populations, each described as in Wendling et al. (Eur J Neurosci 15:1499-1508, 2002). Connectivity among ROIs includes three parameters, which specify the strength of connection in the different frequency bands. The following main steps have been followed: (1) we analyzed how the power spectral density (PSD) is significantly modified by the kind of coupling hypothesized among the ROIs; (2) with the model, and using an automatic fitting procedure, we looked for a simple connectivity circuit able to reproduce PSD of cortical EEG in three ROIs during a finger-movement task. The estimated parameters represent the strength of connections among the ROIs in the different frequency bands. Cortical EEGs were computed with an inverse propagation algorithm, starting from measurement performed with 96 electrodes on the scalp. The present study suggests that the model can be used as a simulation tool, able to mimic the effect of connectivity on EEG. Moreover, it can be used to look for simple connectivity circuits, able to explain the main features of observed cortical PSD. These results may open new prospectives in the use of neurophysiological models, instead of empirical models, to assess effective connectivity from neuroimaging information.

AB - Assessment of brain connectivity among different brain areas during cognitive or motor tasks is a crucial problem in neuroscience today. Aim of this work is to use a neural mass model to assess the effect of various connectivity patterns in cortical electroencephalogram (EEG) power spectral density, and investigate the possibility to derive connectivity circuits from EEG data. To this end, a model of an individual region of interest (ROI) has been built as the parallel arrangement of three populations, each described as in Wendling et al. (Eur J Neurosci 15:1499-1508, 2002). Connectivity among ROIs includes three parameters, which specify the strength of connection in the different frequency bands. The following main steps have been followed: (1) we analyzed how the power spectral density (PSD) is significantly modified by the kind of coupling hypothesized among the ROIs; (2) with the model, and using an automatic fitting procedure, we looked for a simple connectivity circuit able to reproduce PSD of cortical EEG in three ROIs during a finger-movement task. The estimated parameters represent the strength of connections among the ROIs in the different frequency bands. Cortical EEGs were computed with an inverse propagation algorithm, starting from measurement performed with 96 electrodes on the scalp. The present study suggests that the model can be used as a simulation tool, able to mimic the effect of connectivity on EEG. Moreover, it can be used to look for simple connectivity circuits, able to explain the main features of observed cortical PSD. These results may open new prospectives in the use of neurophysiological models, instead of empirical models, to assess effective connectivity from neuroimaging information.

KW - Humans

KW - Models, Theoretical

KW - Brain Mapping

KW - Spectrum Analysis

KW - Models, Neurological

KW - Cerebral Cortex/physiology

KW - Electroencephalography

KW - Neural Pathways/physiology

KW - Humans

KW - Models, Theoretical

KW - Brain Mapping

KW - Spectrum Analysis

KW - Models, Neurological

KW - Cerebral Cortex/physiology

KW - Electroencephalography

KW - Neural Pathways/physiology

M3 - SCORING: Journal article

VL - 96

SP - 351

EP - 365

JO - BIOL CYBERN

JF - BIOL CYBERN

SN - 0340-1200

IS - 3

M1 - 3

ER -