Cortical network modulation during paced arm movements

S. F. Storti; E. Formaggio; P. Manganotti; G. Menegaz

doi:10.1109/EUSIPCO.2015.7362854

Cortical network modulation during paced arm movements

S. F. Storti, E. Formaggio, P. Manganotti, G. Menegaz

Istituto di Neuroriabilitazione Motoria San Camillo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper we investigate task-related changes in brain functional connectivity (FC) by applying different methods namely event-related desynchronization (ERD), coherence and graph-theoretical analysis to electroencephalographic (EEG) recordings. While ERD provides an estimate of the differences in power spectral densities between task and rest conditions, coherence allows assessing the level of synchronization between the recorded signals and graph analysis enables the estimation of the functional network topology. EEGs were recorded on 10 subjects during left/right arm movements. Conventional analysis showed a significant ERD in both alpha and beta bands over the sensorimotor cortex. Connectivity assessment highlighted that stronger connections are those involving the motor regions for which graph analysis revealed reduced accessibility and an increased cen-trality during the movement. This highlights that network analysis brings complementary knowledge with respect to established approaches for modeling motor-induced FC.

Original language	English
Title of host publication	2015 23rd European Signal Processing Conference, EUSIPCO 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2596-2600
Number of pages	5
ISBN (Print)	9780992862633
DOIs	https://doi.org/10.1109/EUSIPCO.2015.7362854
Publication status	Published - Dec 22 2015
Event	23rd European Signal Processing Conference, EUSIPCO 2015 - Nice, France Duration: Aug 31 2015 → Sep 4 2015

Other

Other	23rd European Signal Processing Conference, EUSIPCO 2015
Country	France
City	Nice
Period	8/31/15 → 9/4/15

Keywords

coherence
EEG power
ERD
functional connectivity
graph analysis

ASJC Scopus subject areas

Media Technology
Computer Vision and Pattern Recognition
Signal Processing

Access to Document

10.1109/EUSIPCO.2015.7362854

Fingerprint Dive into the research topics of 'Cortical network modulation during paced arm movements'. Together they form a unique fingerprint.

Cite this

Storti, SF, Formaggio, E, Manganotti, P & Menegaz, G 2015, Cortical network modulation during paced arm movements. in 2015 23rd European Signal Processing Conference, EUSIPCO 2015., 7362854, Institute of Electrical and Electronics Engineers Inc., pp. 2596-2600, 23rd European Signal Processing Conference, EUSIPCO 2015, Nice, France, 8/31/15. https://doi.org/10.1109/EUSIPCO.2015.7362854

@inproceedings{c10d11b33ae44471bb2c340ecb7c4405,

title = "Cortical network modulation during paced arm movements",

abstract = "In this paper we investigate task-related changes in brain functional connectivity (FC) by applying different methods namely event-related desynchronization (ERD), coherence and graph-theoretical analysis to electroencephalographic (EEG) recordings. While ERD provides an estimate of the differences in power spectral densities between task and rest conditions, coherence allows assessing the level of synchronization between the recorded signals and graph analysis enables the estimation of the functional network topology. EEGs were recorded on 10 subjects during left/right arm movements. Conventional analysis showed a significant ERD in both alpha and beta bands over the sensorimotor cortex. Connectivity assessment highlighted that stronger connections are those involving the motor regions for which graph analysis revealed reduced accessibility and an increased cen-trality during the movement. This highlights that network analysis brings complementary knowledge with respect to established approaches for modeling motor-induced FC.",

keywords = "coherence, EEG power, ERD, functional connectivity, graph analysis",

author = "Storti, {S. F.} and E. Formaggio and P. Manganotti and G. Menegaz",

year = "2015",

month = dec,

day = "22",

doi = "10.1109/EUSIPCO.2015.7362854",

language = "English",

isbn = "9780992862633",

pages = "2596--2600",

booktitle = "2015 23rd European Signal Processing Conference, EUSIPCO 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "23rd European Signal Processing Conference, EUSIPCO 2015 ; Conference date: 31-08-2015 Through 04-09-2015",

}

TY - GEN

T1 - Cortical network modulation during paced arm movements

AU - Storti, S. F.

AU - Formaggio, E.

AU - Manganotti, P.

AU - Menegaz, G.

PY - 2015/12/22

Y1 - 2015/12/22

N2 - In this paper we investigate task-related changes in brain functional connectivity (FC) by applying different methods namely event-related desynchronization (ERD), coherence and graph-theoretical analysis to electroencephalographic (EEG) recordings. While ERD provides an estimate of the differences in power spectral densities between task and rest conditions, coherence allows assessing the level of synchronization between the recorded signals and graph analysis enables the estimation of the functional network topology. EEGs were recorded on 10 subjects during left/right arm movements. Conventional analysis showed a significant ERD in both alpha and beta bands over the sensorimotor cortex. Connectivity assessment highlighted that stronger connections are those involving the motor regions for which graph analysis revealed reduced accessibility and an increased cen-trality during the movement. This highlights that network analysis brings complementary knowledge with respect to established approaches for modeling motor-induced FC.

AB - In this paper we investigate task-related changes in brain functional connectivity (FC) by applying different methods namely event-related desynchronization (ERD), coherence and graph-theoretical analysis to electroencephalographic (EEG) recordings. While ERD provides an estimate of the differences in power spectral densities between task and rest conditions, coherence allows assessing the level of synchronization between the recorded signals and graph analysis enables the estimation of the functional network topology. EEGs were recorded on 10 subjects during left/right arm movements. Conventional analysis showed a significant ERD in both alpha and beta bands over the sensorimotor cortex. Connectivity assessment highlighted that stronger connections are those involving the motor regions for which graph analysis revealed reduced accessibility and an increased cen-trality during the movement. This highlights that network analysis brings complementary knowledge with respect to established approaches for modeling motor-induced FC.

KW - coherence

KW - EEG power

KW - ERD

KW - functional connectivity

KW - graph analysis

UR - http://www.scopus.com/inward/record.url?scp=84963945149&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84963945149&partnerID=8YFLogxK

U2 - 10.1109/EUSIPCO.2015.7362854

DO - 10.1109/EUSIPCO.2015.7362854

M3 - Conference contribution

AN - SCOPUS:84963945149

SN - 9780992862633

SP - 2596

EP - 2600

BT - 2015 23rd European Signal Processing Conference, EUSIPCO 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 23rd European Signal Processing Conference, EUSIPCO 2015

Y2 - 31 August 2015 through 4 September 2015

ER -