Research output: Contribution to journal › Article › peer-review
Neural-Computer Interfaces: Theory, Practice, Perspectives. / Dubynin, I; Zemlyanskov, M; Shalayeva, I; Gorskii, O; Grinevich, V; Musienko, P.
In: Applied sciences-Basel, Vol. 15, No. 16, 2025.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Neural-Computer Interfaces: Theory, Practice, Perspectives
AU - Dubynin, I
AU - Zemlyanskov, M
AU - Shalayeva, I
AU - Gorskii, O
AU - Grinevich, V
AU - Musienko, P
N1 - Times Cited in Web of Science Core Collection: 0 Total Times Cited: 0 Cited Reference Count: 256
PY - 2025
Y1 - 2025
N2 - This review outlines the technological principles of neural-computer interface (NCI) construction, classifying them according to: (1) the degree of intervention (invasive, semi-invasive, and non-invasive); (2) the direction of signal communication, including BCI (brain-computer interface) for converting neural activity into commands for external devices, CBI (computer-brain interface) for translating artificial signals into stimuli for the CNS, and BBI (brain-brain interface) for direct brain-to-brain interaction systems that account for agency; and (3) the mode of user interaction with technology (active, reactive, passive). For each NCI type, we detail the fundamental data processing principles, covering signal registration, digitization, preprocessing, classification, encoding, command execution, and stimulation, alongside engineering implementations ranging from EEG/MEG to intracortical implants and from transcranial magnetic stimulation (TMS) to intracortical microstimulation (ICMS). We also review mathematical modeling methods for NCIs, focusing on optimizing the extraction of informative features from neural signals-decoding for BCI and encoding for CBI-followed by a discussion of quasi-real-time operation and the use of DSP and neuromorphic chips. Quantitative metrics and rehabilitation measures for evaluating NCI system effectiveness are considered. Finally, we highlight promising future research directions, such as the development of electrochemical interfaces, biomimetic hierarchical systems, and energy-efficient technologies capable of expanding brain functionality.
AB - This review outlines the technological principles of neural-computer interface (NCI) construction, classifying them according to: (1) the degree of intervention (invasive, semi-invasive, and non-invasive); (2) the direction of signal communication, including BCI (brain-computer interface) for converting neural activity into commands for external devices, CBI (computer-brain interface) for translating artificial signals into stimuli for the CNS, and BBI (brain-brain interface) for direct brain-to-brain interaction systems that account for agency; and (3) the mode of user interaction with technology (active, reactive, passive). For each NCI type, we detail the fundamental data processing principles, covering signal registration, digitization, preprocessing, classification, encoding, command execution, and stimulation, alongside engineering implementations ranging from EEG/MEG to intracortical implants and from transcranial magnetic stimulation (TMS) to intracortical microstimulation (ICMS). We also review mathematical modeling methods for NCIs, focusing on optimizing the extraction of informative features from neural signals-decoding for BCI and encoding for CBI-followed by a discussion of quasi-real-time operation and the use of DSP and neuromorphic chips. Quantitative metrics and rehabilitation measures for evaluating NCI system effectiveness are considered. Finally, we highlight promising future research directions, such as the development of electrochemical interfaces, biomimetic hierarchical systems, and energy-efficient technologies capable of expanding brain functionality.
KW - neural-computer interfaces
KW - brain-computer interfaces
KW - computer-brain interfaces
KW - brain-brain interfaces
KW - agency
KW - modeling
KW - performance metrics
KW - perspectives
KW - BRAIN-MACHINE INTERFACES
KW - ELECTRONIC DURA-MATER
KW - SPINAL-CORD-INJURY
KW - MOTOR FUNCTION
KW - STIMULATION
KW - COMMUNICATION
KW - MODEL
KW - INFORMATION
KW - OPERATION
KW - RESPONSES
U2 - 10.3390/app15168900
DO - 10.3390/app15168900
M3 - Article
VL - 15
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
SN - 2076-3417
IS - 16
ER -
ID: 147897885