Decoding personalized motor cortical excitability states from human electroencephalography
Abstract Brain state-dependent transcranial magnetic stimulation (TMS) requires real-time identification of cortical excitability states. Current approaches deliver TMS during brain states that correlate with motor cortex (M1) excitability at the group level. Here, we hypothesized that machine learn...
Main Authors: | Sara J. Hussain, Romain Quentin |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-04-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-022-10239-3 |
Similar Items
-
Causal decoding of individual cortical excitability states
by: J. Metsomaa, et al.
Published: (2021-12-01) -
Decoding of covert vowel articulation using electroencephalography cortical currents
by: Natsue eYoshimura, et al.
Published: (2016-05-01) -
Decoding visual colour from scalp electroencephalography measurements
by: Hajonides, J, et al.
Published: (2021) -
Combined transcranial magnetic stimulation and electroencephalography reveals alterations in cortical excitability during pain
by: Nahian Shahmat Chowdhury, et al.
Published: (2023-11-01) -
Decoding visual colour from scalp electroencephalography measurements
by: Jasper E. Hajonides, et al.
Published: (2021-08-01)