Tracking Neuronal Connectivity from Electric Brain Signals to Predict Performance

Francesca Miraglia, Paolo Maria Rossini, Fabrizio Vecchio

Risultato della ricerca: Contributo in rivistaArticolo in rivista

10 Citazioni (Scopus)

Abstract

The human brain is a complex container of interconnected networks. Network neuroscience is a recent venture aiming to explore the connection matrix built from the human brain or human “Connectome.” Network-based algorithms provide parameters that define global organization of the brain; when they are applied to electroencephalographic (EEG) signals network, configuration and excitability can be monitored in millisecond time frames, providing remarkable information on their instantaneous efficacy also for a given task’s performance via online evaluation of the underlying instantaneous networks before, during, and after the task. Here we provide an updated summary on the connectome analysis for the prediction of performance via the study of task-related dynamics of brain network organization from EEG signals.
Lingua originaleEnglish
pagine (da-a)86-93
Numero di pagine8
RivistaNeuroscientist
Volume25
DOI
Stato di pubblicazionePubblicato - 2019

Keywords

  • EEG
  • Neurology (clinical)
  • Neuroscience (all)
  • functional brain connectivity
  • graph theory
  • performance

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