Synchronization in Brain — Assessment by Electroencephalographic Signals

Ernesto Pereda; Joydeep Bhattacharya

doi:10.1007/3-540-45720-8_13

Synchronization in Brain — Assessment by Electroencephalographic Signals

Ernesto Pereda^*, Joydeep Bhattacharya

^*Corresponding author for this work

Academy of Music

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

Abstract

The interdependencies between the electroencephalograms of several cortical areas are measured in human adult subjects during different experimental situations by means of methods based on the theory of dynamical systems. Multiple cortical areas are found to be synchronized together while the brain was engaged in higher information processing task. An additional experiment showed that the interhemispheric synchronization between two central derivations significantly increases from awake state to slow wave sleep.

The results show that these new approaches succeed in disclosing the distinct connectivity patterns among neuronal assemblies conforming the cortical brain, thus stressing their ability in analyzing the functioning of the brain.

Original language	English
Title of host publication	Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence
Subtitle of host publication	6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13-15, 2001, Proceedings, Part I
Editors	José Mira, Alberto Prieto
Publisher	Springer
Pages	108-116
Number of pages	9
Edition	1st
ISBN (Electronic)	9783540457206
ISBN (Print)	9783540422358
DOIs	https://doi.org/10.1007/3-540-45720-8_13
Publication status	Published - 5 Jun 2001
Event	6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 - Granada, Spain Duration: 13 Jun 2001 → 15 Jun 2001 https://link.springer.com/book/10.1007/3-540-45720-8 (Conference Proceedings)

Publication series

Name	Lecture Notes in Computer Science
Volume	2084
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	IWANN: International Work-Conference on Artificial Neural Networks

Conference

Conference	6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001
Country/Territory	Spain
City	Granada
Period	13/06/01 → 15/06/01
Internet address	https://link.springer.com/book/10.1007/3-540-45720-8 (Conference Proceedings)

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10.1007/3-540-45720-8_13

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Pereda, E., & Bhattacharya, J. (2001). Synchronization in Brain — Assessment by Electroencephalographic Signals. In J. Mira, & A. Prieto (Eds.), Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence: 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13-15, 2001, Proceedings, Part I (1st ed., pp. 108-116). (Lecture Notes in Computer Science; Vol. 2084), (IWANN: International Work-Conference on Artificial Neural Networks). Springer. https://doi.org/10.1007/3-540-45720-8_13

Pereda, Ernesto ; Bhattacharya, Joydeep. / Synchronization in Brain — Assessment by Electroencephalographic Signals. Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence: 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13-15, 2001, Proceedings, Part I. editor / José Mira ; Alberto Prieto. 1st. ed. Springer, 2001. pp. 108-116 (Lecture Notes in Computer Science). (IWANN: International Work-Conference on Artificial Neural Networks).

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title = "Synchronization in Brain — Assessment by Electroencephalographic Signals",

abstract = "The interdependencies between the electroencephalograms of several cortical areas are measured in human adult subjects during different experimental situations by means of methods based on the theory of dynamical systems. Multiple cortical areas are found to be synchronized together while the brain was engaged in higher information processing task. An additional experiment showed that the interhemispheric synchronization between two central derivations significantly increases from awake state to slow wave sleep.The results show that these new approaches succeed in disclosing the distinct connectivity patterns among neuronal assemblies conforming the cortical brain, thus stressing their ability in analyzing the functioning of the brain.",

author = "Ernesto Pereda and Joydeep Bhattacharya",

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Pereda, E & Bhattacharya, J 2001, Synchronization in Brain — Assessment by Electroencephalographic Signals. in J Mira & A Prieto (eds), Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence: 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13-15, 2001, Proceedings, Part I. 1st edn, Lecture Notes in Computer Science, vol. 2084, IWANN: International Work-Conference on Artificial Neural Networks, Springer, pp. 108-116, 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, Granada, Spain, 13/06/01. https://doi.org/10.1007/3-540-45720-8_13

Synchronization in Brain — Assessment by Electroencephalographic Signals. / Pereda, Ernesto; Bhattacharya, Joydeep.
Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence: 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13-15, 2001, Proceedings, Part I. ed. / José Mira; Alberto Prieto. 1st. ed. Springer, 2001. p. 108-116 (Lecture Notes in Computer Science; Vol. 2084), (IWANN: International Work-Conference on Artificial Neural Networks).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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AB - The interdependencies between the electroencephalograms of several cortical areas are measured in human adult subjects during different experimental situations by means of methods based on the theory of dynamical systems. Multiple cortical areas are found to be synchronized together while the brain was engaged in higher information processing task. An additional experiment showed that the interhemispheric synchronization between two central derivations significantly increases from awake state to slow wave sleep.The results show that these new approaches succeed in disclosing the distinct connectivity patterns among neuronal assemblies conforming the cortical brain, thus stressing their ability in analyzing the functioning of the brain.

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Pereda E, Bhattacharya J. Synchronization in Brain — Assessment by Electroencephalographic Signals. In Mira J, Prieto A, editors, Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence: 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13-15, 2001, Proceedings, Part I. 1st ed. Springer. 2001. p. 108-116. (Lecture Notes in Computer Science). (IWANN: International Work-Conference on Artificial Neural Networks). doi: 10.1007/3-540-45720-8_13

Synchronization in Brain — Assessment by Electroencephalographic Signals

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