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Effortful control and resting state networks : A longitudinal EEG study. / Knyazev, Gennady G.; Savostyanov, Alexander N.; Bocharov, Andrey V. et al.

In: Neuroscience, Vol. 346, 27.03.2017, p. 365-381.

Research output: Contribution to journalArticlepeer-review

Harvard

Knyazev, GG, Savostyanov, AN, Bocharov, AV, Slobodskaya, HR, Bairova, NB, Tamozhnikov, SS & Stepanova, VV 2017, 'Effortful control and resting state networks: A longitudinal EEG study', Neuroscience, vol. 346, pp. 365-381. https://doi.org/10.1016/j.neuroscience.2017.01.031

APA

Knyazev, G. G., Savostyanov, A. N., Bocharov, A. V., Slobodskaya, H. R., Bairova, N. B., Tamozhnikov, S. S., & Stepanova, V. V. (2017). Effortful control and resting state networks: A longitudinal EEG study. Neuroscience, 346, 365-381. https://doi.org/10.1016/j.neuroscience.2017.01.031

Vancouver

Knyazev GG, Savostyanov AN, Bocharov AV, Slobodskaya HR, Bairova NB, Tamozhnikov SS et al. Effortful control and resting state networks: A longitudinal EEG study. Neuroscience. 2017 Mar 27;346:365-381. doi: 10.1016/j.neuroscience.2017.01.031

Author

BibTeX

@article{b2e0161781234c84bf6c16187278903e,
title = "Effortful control and resting state networks: A longitudinal EEG study",
abstract = "Resting state networks{\textquoteright} (RSNs) architecture is well delineated in mature brain, but our understanding of their development remains limited. Particularly, there are few longitudinal studies. Besides, all existing evidence is obtained using functional magnetic resonance imaging (fMRI) and there are no data on electrophysiological correlates of RSN maturation. We acquired three yearly waves of resting state EEG data in 80 children between 7 and 9 years and in 55 adults. Children's parents filled in the Effortful Control (EC) scale. Seed-based oscillatory power envelope correlation in conjunction with beamformer spatial filtering was used to obtain electrophysiological signatures of the default mode network (DMN) and two task-positive networks (TPN). In line with existing fMRI evidence, both cross-sectional comparison with adults and longitudinal analysis showed that the general pattern of maturation consisted in an increase in long-distance connections with posterior cortical regions and a decrease in short connections within prefrontal cortical areas. Latent growth curve analysis showed that EC scores were predicted by a linear increase over time in DMN integrity in alpha band and an increase in the segregation between DMN and TPN in beta band. These data confirm the neural basis of observed in fMRI research maturation-related changes and show that integrity of the DMN and sufficient level of segregation between DMN and TPN is a prerequisite for appropriate attentional and behavioral control.",
keywords = "children, EEG, effortful control, functional connectivity, longitudinal study, resting-state networks, Neural Pathways/growth & development, Alpha Rhythm, Humans, Male, Electroencephalography, Beta Rhythm, Signal Processing, Computer-Assisted, Cerebral Cortex/growth & development, Female, Executive Function/physiology, Child, Longitudinal Studies, INTRINSIC CONNECTIVITY NETWORKS, FUNCTIONAL CONNECTIVITY, SOURCE LOCALIZATION, MEDIAL PREFRONTAL CORTEX, GLOBAL SIGNAL, CORTICAL CORRELATION STRUCTURE, DEFAULT-MODE NETWORK, HIGH-DENSITY EEG, GAMMA-BAND RESPONSES, DEVELOPMENTAL-CHANGES",
author = "Knyazev, {Gennady G.} and Savostyanov, {Alexander N.} and Bocharov, {Andrey V.} and Slobodskaya, {Helena R.} and Bairova, {Nadezhda B.} and Tamozhnikov, {Sergey S.} and Stepanova, {Valentina V.}",
note = "Copyright {\textcopyright} 2017 IBRO. Published by Elsevier Ltd. All rights reserved.",
year = "2017",
month = mar,
day = "27",
doi = "10.1016/j.neuroscience.2017.01.031",
language = "English",
volume = "346",
pages = "365--381",
journal = "Neuroscience",
issn = "0306-4522",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Effortful control and resting state networks

T2 - A longitudinal EEG study

AU - Knyazev, Gennady G.

AU - Savostyanov, Alexander N.

AU - Bocharov, Andrey V.

AU - Slobodskaya, Helena R.

AU - Bairova, Nadezhda B.

AU - Tamozhnikov, Sergey S.

AU - Stepanova, Valentina V.

N1 - Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

PY - 2017/3/27

Y1 - 2017/3/27

N2 - Resting state networks’ (RSNs) architecture is well delineated in mature brain, but our understanding of their development remains limited. Particularly, there are few longitudinal studies. Besides, all existing evidence is obtained using functional magnetic resonance imaging (fMRI) and there are no data on electrophysiological correlates of RSN maturation. We acquired three yearly waves of resting state EEG data in 80 children between 7 and 9 years and in 55 adults. Children's parents filled in the Effortful Control (EC) scale. Seed-based oscillatory power envelope correlation in conjunction with beamformer spatial filtering was used to obtain electrophysiological signatures of the default mode network (DMN) and two task-positive networks (TPN). In line with existing fMRI evidence, both cross-sectional comparison with adults and longitudinal analysis showed that the general pattern of maturation consisted in an increase in long-distance connections with posterior cortical regions and a decrease in short connections within prefrontal cortical areas. Latent growth curve analysis showed that EC scores were predicted by a linear increase over time in DMN integrity in alpha band and an increase in the segregation between DMN and TPN in beta band. These data confirm the neural basis of observed in fMRI research maturation-related changes and show that integrity of the DMN and sufficient level of segregation between DMN and TPN is a prerequisite for appropriate attentional and behavioral control.

AB - Resting state networks’ (RSNs) architecture is well delineated in mature brain, but our understanding of their development remains limited. Particularly, there are few longitudinal studies. Besides, all existing evidence is obtained using functional magnetic resonance imaging (fMRI) and there are no data on electrophysiological correlates of RSN maturation. We acquired three yearly waves of resting state EEG data in 80 children between 7 and 9 years and in 55 adults. Children's parents filled in the Effortful Control (EC) scale. Seed-based oscillatory power envelope correlation in conjunction with beamformer spatial filtering was used to obtain electrophysiological signatures of the default mode network (DMN) and two task-positive networks (TPN). In line with existing fMRI evidence, both cross-sectional comparison with adults and longitudinal analysis showed that the general pattern of maturation consisted in an increase in long-distance connections with posterior cortical regions and a decrease in short connections within prefrontal cortical areas. Latent growth curve analysis showed that EC scores were predicted by a linear increase over time in DMN integrity in alpha band and an increase in the segregation between DMN and TPN in beta band. These data confirm the neural basis of observed in fMRI research maturation-related changes and show that integrity of the DMN and sufficient level of segregation between DMN and TPN is a prerequisite for appropriate attentional and behavioral control.

KW - children

KW - EEG

KW - effortful control

KW - functional connectivity

KW - longitudinal study

KW - resting-state networks

KW - Neural Pathways/growth & development

KW - Alpha Rhythm

KW - Humans

KW - Male

KW - Electroencephalography

KW - Beta Rhythm

KW - Signal Processing, Computer-Assisted

KW - Cerebral Cortex/growth & development

KW - Female

KW - Executive Function/physiology

KW - Child

KW - Longitudinal Studies

KW - INTRINSIC CONNECTIVITY NETWORKS

KW - FUNCTIONAL CONNECTIVITY

KW - SOURCE LOCALIZATION

KW - MEDIAL PREFRONTAL CORTEX

KW - GLOBAL SIGNAL

KW - CORTICAL CORRELATION STRUCTURE

KW - DEFAULT-MODE NETWORK

KW - HIGH-DENSITY EEG

KW - GAMMA-BAND RESPONSES

KW - DEVELOPMENTAL-CHANGES

UR - http://www.scopus.com/inward/record.url?scp=85012248792&partnerID=8YFLogxK

U2 - 10.1016/j.neuroscience.2017.01.031

DO - 10.1016/j.neuroscience.2017.01.031

M3 - Article

C2 - 28153691

AN - SCOPUS:85012248792

VL - 346

SP - 365

EP - 381

JO - Neuroscience

JF - Neuroscience

SN - 0306-4522

ER -

ID: 9410743