ArticleScientific reports2017
Decoding finger movement in humans using synergy of EEG cortical current signals.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 37 citations in OpenAlex.
- Dynamic Information Flow Based on EEG and Diffusion MRI in Stroke: A Proof-of-Principle Study.Frontiers in neural circuits · 2018Trial
- Gesture encoding in human left precentral gyrus neuronal ensembles.Communications biology · 2025Article
- In vivo electrophysiology recordings and computational modeling can predict octopus arm movement.Bioelectronic medicine · 2025Article
- Single unit electrophysiology recordings and computational modeling can predict octopus arm movement.bioRxiv : the preprint server for biology · 2024Article
- Decoding reach-to-grasp from EEG using classifiers trained with data from the contralateral limb.Frontiers in human neuroscience · 2023Article
- Reconstructing Synergy-Based Hand Grasp Kinematics from Electroencephalographic Signals.Sensors (Basel, Switzerland) · 2022Article
- Clustered event related spectral perturbation (ERSP) feature in right hand motor imagery classification.Frontiers in neuroscience · 2022Article
- Brain-inspired spiking neural networks for decoding and understanding muscle activity and kinematics from electroencephalography signals during hand movements.Scientific reports · 2021Article
- Investigation of Delayed Response during Real-Time Cursor Control Using Electroencephalography.Journal of healthcare engineering · 2020Article
- The Effect of ICA and Non-negative Matrix Factorization Analysis for EMG Signals Recorded From Multi-Channel EMG Sensors.Frontiers in neuroscience · 2020Article
- MEG Source Imaging and Group Analysis Using VBMEG.Frontiers in neuroscience · 2019Article
- Perspective-Taking in Sentence Comprehension: Time and Empathy.Frontiers in psychology · 2018Article
- Multidimensional dynamic characterization and decoding of finger movements using magnetoencephalography.Imaging neuroscience (Cambridge, Mass.)Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The synchronized activity of neuronal populations across multiple distant brain areas may reflect coordinated interactions of large-scale brain networks. Currently, there is no established method to investigate the temporal transitions between these large-scale networks that would allow, for example, to decode finger movements. Here we applied a matrix factorization method employing principal component and temporal independent component analyses to identify brain activity synchronizations. In accordance with previous studies investigating "muscle synergies", we refer to this activity as "brain activity synergy". Using electroencephalography (EEG), we first estimated cortical current sources (CSs) and then identified brain activity synergies within the estimated CS signals. A decoding analysis for finger movement in eight directions showed that such CS synergies provided more information for dissociating between movements than EEG sensor signals, EEG synergy, or CS signals, suggesting that temporal activation patterns of the synchronizing CSs may contain information related to motor control. A quantitative analysis of features selected by the decoders further revealed temporal transitions among the primary motor area, dorsal and ventral premotor areas, pre-supplementary motor area, and supplementary motor area, which may reflect transitions in motor planning and execution. These results provide a proof of concept for brain activity synergy estimation using CSs.
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