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Sensorimotor brain-computer interface performance depends on signal-to-noise ratio but not connectivity of the mu rhythm in a multiverse analysis of longitudinal data.
Kapralov, Nikolai; Jamshidi Idaji, Mina; Stephani, Tilman; Studenova, Alina; Vidaurre, Carmen; Ros, Tomas; Villringer, Arno; Nikulin, Vadim.
Afiliación
  • Kapralov N; Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, Leipzig, 04103, GERMANY.
  • Jamshidi Idaji M; BIFOLD, Straße des 17. Juni 135, Berlin, Berlin, 10587, GERMANY.
  • Stephani T; Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, Leipzig, 04103, GERMANY.
  • Studenova A; Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, Leipzig, 04103, GERMANY.
  • Vidaurre C; Basque Center on Cognition Brain and Language, Mikeletegi Pasealekua, 69, San Sebastian, 20009, SPAIN.
  • Ros T; University of Geneva, 24 rue du Général-Dufour, Geneva, 1211, SWITZERLAND.
  • Villringer A; Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, Leipzig, 04103, GERMANY.
  • Nikulin V; Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1A, Leipzig, 04103, GERMANY.
J Neural Eng ; 2024 Sep 12.
Article en En | MEDLINE | ID: mdl-39265614
ABSTRACT

OBJECTIVE:

Serving as a channel for communication with locked-in patients or control of prostheses, sensorimotor brain-computer interfaces (BCIs) decode imaginary movements from the recorded activity of the user's brain. However, many individuals remain unable to control the BCI, and the underlying mechanisms are unclear. The user's BCI performance was previously shown to correlate with the resting-state signal-to-noise ratio (SNR) of the mu rhythm and the phase synchronization (PS) of the mu rhythm between sensorimotor areas. Yet, these predictors of performance were primarily evaluated in a single BCI session, while the longitudinal aspect remains rather uninvestigated. In addition, different analysis pipelines were used to estimate PS in source space, potentially hindering the reproducibility of the results.

APPROACH:

To systematically address these issues, we performed an extensive validation of the relationship between pre-stimulus SNR, PS, and session-wise BCI performance using a publicly available dataset of 62 human participants performing up to 11 sessions of BCI training. We performed the analysis in sensor space using the surface Laplacian and in source space by combining 24 processing pipelines in a multiverse analysis. This way, we could investigate how robust the observed effects were to the selection of the pipeline. MAIN

RESULTS:

Our results show that SNR had both between- and within-subject effects on BCI performance for the majority of the pipelines. In contrast, the effect of PS on BCI performance was less robust to the selection of the pipeline and became non-significant after controlling for SNR.

SIGNIFICANCE:

Taken together, our results demonstrate that changes in neuronal connectivity within the sensorimotor system are not critical for learning to control a BCI, and interventions that increase the SNR of the mu rhythm might lead to improvements in the user's BCI performance.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Neural Eng Asunto de la revista: NEUROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Neural Eng Asunto de la revista: NEUROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Reino Unido