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Tracking Neuronal Connectivity from Electric Brain Signals to Predict Performance.

Fabrizio Vecchio¹, Francesca Miraglia^1,2, Paolo Maria Rossini²

¹1 Brain Connectivity Laboratory, IRCCS San Raffaele Pisana, Rome, Italy.

The Neuroscientist : a Review Journal Bringing Neurobiology, Neurology and Psychiatry

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Summary

Network neuroscience uses brain network analysis from electroencephalographic (EEG) signals to predict task performance. This approach monitors brain network organization and excitability in real-time for enhanced understanding.

Keywords:

EEG functional brain connectivity graph theory performance

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Area of Science:

Neuroscience
Network Science
Computational Neuroscience

Background:

The human brain is characterized by complex interconnected networks, forming the connectome.
Network neuroscience is an emerging field focused on analyzing these brain networks.
Understanding brain network dynamics is crucial for cognitive function and performance.

Purpose of the Study:

To summarize connectome analysis for predicting task performance.
To investigate the task-related dynamics of brain network organization using EEG signals.
To highlight the utility of real-time network monitoring for evaluating instantaneous brain efficacy.

Main Methods:

Application of network-based algorithms to electroencephalographic (EEG) signals.
Analysis of brain network configuration and excitability in millisecond time frames.
Online evaluation of instantaneous brain networks before, during, and after task performance.

Main Results:

Network-based algorithms provide parameters defining global brain organization.
EEG signal analysis allows for millisecond-time frame monitoring of network configuration and excitability.
Real-time evaluation of brain networks offers insights into instantaneous efficacy related to task performance.

Conclusions:

Connectome analysis, particularly using EEG-based network dynamics, can predict task performance.
Task-related changes in brain network organization are observable and quantifiable.
Real-time monitoring of brain networks provides valuable information on cognitive processes and performance.