Abstract
The concept of redundancy is a critical resource of the brain enhancing the resilience to neural damages and dysfunctions. In the present work, we propose a graph-based methodology to investigate the connectivity redundancy in brain networks. By taking into account all the possible paths between pairs of nodes, we considered three complementary indexes, characterizing the network redundancy (i) at the global level, i.e. the scalar redundancy (ii) across different path lengths, i.e. the vectorial redundancy (iii) between node pairs, i.e. the matricial redundancy. We used this procedure to investigate the functional connectivity estimated from a dataset of high-density EEG signals in a group of healthy subjects during a no-task resting state. The statistical comparison with a benchmark dataset of random networks, having the same number of nodes and links of the EEG nets, revealed a significant (p <0.05) difference for all the three indexes. In particular, the redundancy in the EEG networks, for each frequency band, appears radically higher than random graphs, thus revealing a natural tendency of the brain to present multiple parallel interactions between different specialized areas. Notably, the matricial redundancy showed a high (p <0.05) redundancy between the scalp sensors over the parieto-occipital areas in the Alpha range of EEG oscillations (7.5-12.5 Hz), which is known to be the most responsive channel during resting state conditions.
| Original language | English |
|---|---|
| Article number | 1250158 |
| Journal | International Journal of Bifurcation and Chaos |
| Volume | 22 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 2012 |
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Keywords
- brain connectivity
- EEG
- graph theory
- multiple pathways
- resting state
ASJC Scopus subject areas
- Applied Mathematics
- General
- Engineering(all)
- Modelling and Simulation
Cite this
Redundancy in functional brain connectivity from eeg recordings. / De Vico Fallani, Fabrizio; Toppi, Jlenia; Di Lanzo, Claudia; Vecchiato, Giovanni; Astolfi, Laura; Borghini, Gianluca; Mattia, Donatella; Cincotti, Febo; Babiloni, Fabio.
In: International Journal of Bifurcation and Chaos, Vol. 22, No. 7, 1250158, 07.2012.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Redundancy in functional brain connectivity from eeg recordings
AU - De Vico Fallani, Fabrizio
AU - Toppi, Jlenia
AU - Di Lanzo, Claudia
AU - Vecchiato, Giovanni
AU - Astolfi, Laura
AU - Borghini, Gianluca
AU - Mattia, Donatella
AU - Cincotti, Febo
AU - Babiloni, Fabio
PY - 2012/7
Y1 - 2012/7
N2 - The concept of redundancy is a critical resource of the brain enhancing the resilience to neural damages and dysfunctions. In the present work, we propose a graph-based methodology to investigate the connectivity redundancy in brain networks. By taking into account all the possible paths between pairs of nodes, we considered three complementary indexes, characterizing the network redundancy (i) at the global level, i.e. the scalar redundancy (ii) across different path lengths, i.e. the vectorial redundancy (iii) between node pairs, i.e. the matricial redundancy. We used this procedure to investigate the functional connectivity estimated from a dataset of high-density EEG signals in a group of healthy subjects during a no-task resting state. The statistical comparison with a benchmark dataset of random networks, having the same number of nodes and links of the EEG nets, revealed a significant (p <0.05) difference for all the three indexes. In particular, the redundancy in the EEG networks, for each frequency band, appears radically higher than random graphs, thus revealing a natural tendency of the brain to present multiple parallel interactions between different specialized areas. Notably, the matricial redundancy showed a high (p <0.05) redundancy between the scalp sensors over the parieto-occipital areas in the Alpha range of EEG oscillations (7.5-12.5 Hz), which is known to be the most responsive channel during resting state conditions.
AB - The concept of redundancy is a critical resource of the brain enhancing the resilience to neural damages and dysfunctions. In the present work, we propose a graph-based methodology to investigate the connectivity redundancy in brain networks. By taking into account all the possible paths between pairs of nodes, we considered three complementary indexes, characterizing the network redundancy (i) at the global level, i.e. the scalar redundancy (ii) across different path lengths, i.e. the vectorial redundancy (iii) between node pairs, i.e. the matricial redundancy. We used this procedure to investigate the functional connectivity estimated from a dataset of high-density EEG signals in a group of healthy subjects during a no-task resting state. The statistical comparison with a benchmark dataset of random networks, having the same number of nodes and links of the EEG nets, revealed a significant (p <0.05) difference for all the three indexes. In particular, the redundancy in the EEG networks, for each frequency band, appears radically higher than random graphs, thus revealing a natural tendency of the brain to present multiple parallel interactions between different specialized areas. Notably, the matricial redundancy showed a high (p <0.05) redundancy between the scalp sensors over the parieto-occipital areas in the Alpha range of EEG oscillations (7.5-12.5 Hz), which is known to be the most responsive channel during resting state conditions.
KW - brain connectivity
KW - EEG
KW - graph theory
KW - multiple pathways
KW - resting state
UR - http://www.scopus.com/inward/record.url?scp=84864818355&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864818355&partnerID=8YFLogxK
U2 - 10.1142/S0218127412501581
DO - 10.1142/S0218127412501581
M3 - Article
AN - SCOPUS:84864818355
VL - 22
JO - International Journal of Bifurcation and Chaos in Applied Sciences and Engineering
JF - International Journal of Bifurcation and Chaos in Applied Sciences and Engineering
SN - 0218-1274
IS - 7
M1 - 1250158
ER -