This article discusses the contribution of fMRI- and fMRI-EEG-neurofeedback into recovery of motor function in two subacute stroke patients during the early post-stroke period. Premotor and supplementary motor zones of the cortex were chosen as the targets of voluntary control. Patient 1 received 6 sessions of motor imagery-based fMRI neurofeedback of secondary motor areas activity and Patient 2 received a similar course with the addition of μ- and β-EEG activity suppression. Both reduced the motor deficit severity, improved on the quality of life, and increased the C3/C4 coherence to other central leads within EEG μ-band. Patient 1 reliably increased the fMRI signal in target areas and improved on the strength and speed of hand movements. Patient 2 (fMRI-EEG) mastered the EEG activity regulation to a greater degree. The authors conclude that pure fMRI neurofeedback and bi-modal fMRI-EEG neurofeedback produce different clinical effects in motor rehabilitation, which confirms the prospect of the closed-loop stroke treatment.
Similar content being viewed by others
References
Savelov AA, Shtark MB, Kozlova LI, Verevkin EG, Petrovskii ED, Pokrovskii MA, Rudych PD, Tsyrkin GM. Dynamics of Interactions between Cerebral Networks Derived from fMRI Data and Motor Rehabilitation during Stokes. Bull. Exp. Biol. Med. 2019;166(3):399-403. doi: https://doi.org/10.1007/s10517-019-04359-6
Koush Y, Ashburner J, Prilepin E, Sladky R, Zeidman P, Bibikov S, Scharnowski F, Nikonorov A, De Ville D.V. Open-NFT: An open-source Python/Matlab framework for real-time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis. Neuroimage. 2017;156):489-503. doi: https://doi.org/10.1016/j.neuroimage.2017.06.039
Liew SL, Rana M, Cornelsen S, Fortunato de Barros Filho M, Birbaumer N, Sitaram R, Cohen LG, Soekadar SR. Improving motor corticothalamic communication after stroke using real-time fMRI connectivity-based neurofeedback. Neurorehabil. Neural Repair. 2016;30(7):671-675. doi: https://doi.org/10.1177/1545968315619699
Lioi G, Butet S, Fleury M, Bannier E, Lécuyer A, Bonan I, Barillot C. A multi-target motor imagery training using bimodal EEG-fMRI neurofeedback: a Pilot study in chronic stroke patients. Front. Hum. Neurosci. 2020;14:37. doi: https://doi.org/10.3389/fnhum.2020.00037
Mihara M, Hattori N, Hatakenaka M, Yagura H, Kawano T, Hino T, Miyai I. Near-infrared spectroscopy-mediated neurofeedback enhances efficacy of motor imagery-based training in poststroke victims: a pilot study. Stroke. 2013;44(4):1091-1098. doi: https://doi.org/10.1161/STROKEAHA.111.674507
Sitaram R, Veit R, Stevens B, Caria A, Gerloff C, Birbaumer N, Hummel F. Acquired control of ventral premotor cortex activity by feedback training: an exploratory real-time FMRI and TMS study. Neurorehabil. Neural Repair. 2012;26(3):256-265. doi: https://doi.org/10.1177/1545968311418345
Wu Q, Yue Z, Ge Y, Ma D, Yin H, Zhao H, Liu G, Wang J, Dou W, Pan Y. Brain functional networks study of subacute stroke patients with upper limb dysfunction after comprehensive rehabilitation including BCI training. Front. Neurol. 2020;10:1419. doi: https://doi.org/10.3389/fneur.2019.01419
Author information
Authors and Affiliations
Corresponding author
Additional information
Translated from Byulleten’ Eksperimental’noi Biologii i Meditsiny, Vol. 171, No. 3, pp. 364-368, March, 2021
Rights and permissions
About this article
Cite this article
Bezmaternykh, D.D., Kalgin, K.V., Maximova, P.E. et al. Application of fMRI and Simultaneous fMRI-EEG Neurofeedback in Post-Stroke Motor Rehabilitation. Bull Exp Biol Med 171, 379–383 (2021). https://doi.org/10.1007/s10517-021-05232-1
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10517-021-05232-1