Gamma Rhythm Analysis and Simulation Using Neuron Models

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Gamma Rhythm Analysis and Simulation Using Neuron Models. / Sevasteeva, Evgeniia S.; Plotnikov, Sergei A.; Belov, Dmitry R.

In: IFAC-PapersOnLine, Vol. 55, No. 20, 01.07.2022, p. 576-581.

Research output: Contribution to journal › Conference article › peer-review

Author

Sevasteeva, Evgeniia S. ; Plotnikov, Sergei A. ; Belov, Dmitry R. / Gamma Rhythm Analysis and Simulation Using Neuron Models. In: IFAC-PapersOnLine. 2022 ; Vol. 55, No. 20. pp. 576-581.

BibTeX

@article{70f048c6058d409098ef3adaa4c8305d,

title = "Gamma Rhythm Analysis and Simulation Using Neuron Models",

abstract = "Neural oscillations are electrical activities of the brain measurable at different frequencies. This paper studies the interaction between the fast and slow processes in the brain. We recorded signals intracranially from the simple Wistar rats, performed the signal processing, and computed the correlation between envelopes of the high-frequency gamma rhythm and a low-frequency signal. The analysis shows that the low-frequency signal (delta rhythm) modulates the gamma rhythm with a small time delay. Further, we used simple excitable neuron models, namely FitzHugh-Nagumo and Hindmarsh-Rose, to simulate the gamma rhythm. The low-frequency signal delta rhythm can be used as the input to affect the threshold and simulate gamma rhythm using these neuron models.",

keywords = "Correlation, Electrocorticogram, FitzHugh-Nagumo model, Gamma rhythm, Hindmarsh-Rose model, Oscillation",

author = "Sevasteeva, {Evgeniia S.} and Plotnikov, {Sergei A.} and Belov, {Dmitry R.}",

note = "Publisher Copyright: {\textcopyright} 2022 The Authors.; 10th Vienna International Conference on Mathematical Modelling, MATHMOD 2022 ; Conference date: 27-07-2022 Through 29-07-2022",

year = "2022",

month = jul,

day = "1",

doi = "10.1016/j.ifacol.2022.09.157",

language = "English",

volume = "55",

pages = "576--581",

journal = "IFAC-PapersOnLine",

issn = "2405-8971",

publisher = "Elsevier",

number = "20",

}

RIS

TY - JOUR

T1 - Gamma Rhythm Analysis and Simulation Using Neuron Models

AU - Sevasteeva, Evgeniia S.

AU - Plotnikov, Sergei A.

AU - Belov, Dmitry R.

PY - 2022/7/1

Y1 - 2022/7/1

N2 - Neural oscillations are electrical activities of the brain measurable at different frequencies. This paper studies the interaction between the fast and slow processes in the brain. We recorded signals intracranially from the simple Wistar rats, performed the signal processing, and computed the correlation between envelopes of the high-frequency gamma rhythm and a low-frequency signal. The analysis shows that the low-frequency signal (delta rhythm) modulates the gamma rhythm with a small time delay. Further, we used simple excitable neuron models, namely FitzHugh-Nagumo and Hindmarsh-Rose, to simulate the gamma rhythm. The low-frequency signal delta rhythm can be used as the input to affect the threshold and simulate gamma rhythm using these neuron models.

AB - Neural oscillations are electrical activities of the brain measurable at different frequencies. This paper studies the interaction between the fast and slow processes in the brain. We recorded signals intracranially from the simple Wistar rats, performed the signal processing, and computed the correlation between envelopes of the high-frequency gamma rhythm and a low-frequency signal. The analysis shows that the low-frequency signal (delta rhythm) modulates the gamma rhythm with a small time delay. Further, we used simple excitable neuron models, namely FitzHugh-Nagumo and Hindmarsh-Rose, to simulate the gamma rhythm. The low-frequency signal delta rhythm can be used as the input to affect the threshold and simulate gamma rhythm using these neuron models.

KW - Correlation

KW - Electrocorticogram

KW - FitzHugh-Nagumo model

KW - Gamma rhythm

KW - Hindmarsh-Rose model

KW - Oscillation

UR - http://www.scopus.com/inward/record.url?scp=85142292951&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/08ff83dc-928c-34b7-a0c2-caf19c7baa2c/

U2 - 10.1016/j.ifacol.2022.09.157

DO - 10.1016/j.ifacol.2022.09.157

M3 - Conference article

AN - SCOPUS:85142292951

VL - 55

SP - 576

EP - 581

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8971

IS - 20

T2 - 10th Vienna International Conference on Mathematical Modelling

Y2 - 27 July 2022 through 29 July 2022

ER -

ID: 100731037