TY - JOUR

T1 - Neuroimaging Study of Alpha and Beta EEG Biofeedback Effects on Neural Networks

AU - Shtark, Mark B.

AU - Kozlova, Lyudmila I.

AU - Bezmaternykh, Dmitriy D.

AU - Mel’nikov, Mikhail Ye

AU - Savelov, Andrey A.

AU - Sokhadze, Estate M.

PY - 2018/6

Y1 - 2018/6

N2 - Neural networks interaction was studied in healthy men (20–35 years old) who underwent 20 sessions of EEG biofeedback training outside the MRI scanner, with concurrent fMRI–EEG scans at the beginning, middle, and end of the course. The study recruited 35 subjects for EEG biofeedback, but only 18 of them were considered as “successful” in self-regulation of target EEG bands during the whole course of training. Results of fMRI analysis during EEG biofeedback are reported only for these “successful” trainees. The experimental group (N = 23 total, N = 13 “successful”) upregulated the power of alpha rhythm, while the control group (N = 12 total, N = 5 “successful”) beta rhythm, with the protocol instructions being as for alpha training in both. The acquisition of the stable skills of alpha self-regulation was followed by the weakening of the irrelevant links between the cerebellum and visuospatial network (VSN), as well as between the VSN, the right executive control network (RECN), and the cuneus. It was also found formation of a stable complex based on the interaction of the precuneus, the cuneus, the VSN, and the high level visuospatial network (HVN), along with the strengthening of the interaction of the anterior salience network (ASN) with the precuneus. In the control group, beta enhancement training was accompanied by weakening of interaction between the precuneus and the default mode network, and a decrease in connectivity between the cuneus and the primary visual network (PVN). The differences between the alpha training group and the control group increased successively during training. Alpha training was characterized by a less pronounced interaction of the network formed by the PVN and the HVN, as well as by an increased interaction of the cerebellum with the precuneus and the RECN. The study demonstrated the differences in the structure and interaction of neural networks involved into alpha and beta generating systems forming and functioning, which should be taken into account during planning neurofeedback interventions. Possibility of using fMRI-guided biofeedback organized according to the described neural networks interaction may advance more accurate targeting specific symptoms during neurotherapy.

AB - Neural networks interaction was studied in healthy men (20–35 years old) who underwent 20 sessions of EEG biofeedback training outside the MRI scanner, with concurrent fMRI–EEG scans at the beginning, middle, and end of the course. The study recruited 35 subjects for EEG biofeedback, but only 18 of them were considered as “successful” in self-regulation of target EEG bands during the whole course of training. Results of fMRI analysis during EEG biofeedback are reported only for these “successful” trainees. The experimental group (N = 23 total, N = 13 “successful”) upregulated the power of alpha rhythm, while the control group (N = 12 total, N = 5 “successful”) beta rhythm, with the protocol instructions being as for alpha training in both. The acquisition of the stable skills of alpha self-regulation was followed by the weakening of the irrelevant links between the cerebellum and visuospatial network (VSN), as well as between the VSN, the right executive control network (RECN), and the cuneus. It was also found formation of a stable complex based on the interaction of the precuneus, the cuneus, the VSN, and the high level visuospatial network (HVN), along with the strengthening of the interaction of the anterior salience network (ASN) with the precuneus. In the control group, beta enhancement training was accompanied by weakening of interaction between the precuneus and the default mode network, and a decrease in connectivity between the cuneus and the primary visual network (PVN). The differences between the alpha training group and the control group increased successively during training. Alpha training was characterized by a less pronounced interaction of the network formed by the PVN and the HVN, as well as by an increased interaction of the cerebellum with the precuneus and the RECN. The study demonstrated the differences in the structure and interaction of neural networks involved into alpha and beta generating systems forming and functioning, which should be taken into account during planning neurofeedback interventions. Possibility of using fMRI-guided biofeedback organized according to the described neural networks interaction may advance more accurate targeting specific symptoms during neurotherapy.

KW - Alpha training

KW - Beta rhythm

KW - Brain networks

KW - EEG

KW - EEG biofeedback

KW - fMRI

KW - DEFAULT MODE NETWORK

KW - ADHD

KW - METAANALYSIS

KW - EFFICACY

KW - AFFECTIVE-DISORDERS

KW - CONNECTIVITY

KW - RHYTHM

KW - NEUROFEEDBACK

KW - FMRI

KW - BRAIN

UR - http://www.scopus.com/inward/record.url?scp=85048365558&partnerID=8YFLogxK

U2 - 10.1007/s10484-018-9396-2

DO - 10.1007/s10484-018-9396-2

M3 - Article

C2 - 29926265

AN - SCOPUS:85048365558

VL - 43

SP - 169

EP - 178

JO - Applied Psychophysiology Biofeedback

JF - Applied Psychophysiology Biofeedback

SN - 1090-0586

IS - 2

ER -