Brain Networks Responsible for Sense of Agency: An EEG Study.
BACKGROUND
Self-agency (SA) is a person's feeling that his action was generated by himself. The neural substrates of SA have been investigated in many neuroimaging studies, but the functional connectivity of identified regions has rarely been investigated. The goal of this study is to investigate the neural network related to SA.


METHODS
SA of hand movements was modulated with virtual reality. We examined the cortical network relating to SA modulation with electroencephalography (EEG) power spectrum and phase coherence of alpha, beta, and gamma frequency bands in 16 right-handed, healthy volunteers.


RESULTS
In the alpha band, significant relative power changes and phase coherence of alpha band were associated with SA modulation. The relative power decrease over the central, bilateral parietal, and right temporal regions (C4, Pz, P3, P4, T6) became larger as participants more effectively controlled the virtual hand movements. The phase coherence of the alpha band within frontal areas (F7-FP2, F7-Fz) was directly related to changes in SA. The functional connectivity was lower as the participants felt that they could control their virtual hand. In the other frequency bands, significant phase coherences were observed in the frontal (or central) to parietal, temporal, and occipital regions during SA modulation (Fz-O1, F3-O1, Cz-O1, C3-T4L in beta band; FP1-T6, FP1-O2, F7-T4L, F8-Cz in gamma band).


CONCLUSIONS
Our study suggests that alpha band activity may be the main neural oscillation of SA, which suggests that the neural network within the anterior frontal area may be important in the generation of SA.
Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong Si, Gyeonggi-Do, Republic of Korea; Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.
Suk Yun
SY
Kang
Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea.
Chang-Hwan
CH
Im
Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea.
Miseon
M
Shim
Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America; Department of Neurology, University of California San Diego, San Diego, California, United States of America.
Fatta B
FB
Nahab
Department of Biomedical Engineering, Yonsei University, Wonju-si, Kangwon-do, Republic of Korea.
Jihye
J
Park
Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea; Department of Biomedical Engineering, Yonsei University, Wonju-si, Kangwon-do, Republic of Korea.
Do-Won
DW
Kim
Signal Processing and Instrumentation Section, Division of Computational Bioscience, Center for Information Technology, National Institutes of Health, Bethesda, Maryland, United States of America.
John
J
Kakareka
Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.
Nathanial
N
Miletta
Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.
Mark
M
Hallett
D000328:Adult; D001921:Brain / Q000502:physiology*; D063132:Connectome / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D064368:Healthy Volunteers; D006801:Humans; D008297:Male; D020377:Self Efficacy; D055815:Young Adult