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Event-related network changes unfold the dynamics of cortical integration during face processing
Antonio Maffei1, Paola Sessa1,2
1Padova Neuroscience Center (PNC), University of Padova, Padova, Italy.
Psychophysiology
|February 7, 2021
Summary
Face perception involves a dynamic brain network. Key hubs emerge in occipital and temporal regions, showing how the brain processes faces rapidly and efficiently.
Area of Science:
- Neuroscience
- Cognitive Science
- Computational Neuroscience
Background:
- Face perception relies on a network of brain regions including occipital, parietal, and temporal cortices.
- The dynamic interplay within this neural network during face processing remains poorly understood.
Purpose of the Study:
- To characterize the network behavior during face perception using graph theory.
- To investigate the dynamic changes in connectivity and topology of brain networks elicited by facial expressions.
Main Methods:
- Electroencephalography (EEG) was used to record brain activity.
- Time-varying connectivity was estimated and analyzed using graph-theoretical measures (node centrality, global topology).
- Granger causality was employed to link network dynamics with event-related potentials (ERPs).
Main Results:
- Face perception involves a dynamic network architecture with emerging hubs in occipital and temporal regions.
- Node centrality peaked around the time of the face-sensitive N170 component.
- Network analysis revealed a small-world organization crucial for integration during face processing, from stimulus onset to ~200 ms.
Conclusions:
- Face processing is supported by dynamic network reorganization, not a static architecture.
- The findings link network-level dynamics to local neural responses, providing insights into distributed processing mechanisms.
- The study highlights the importance of dynamic hub emergence and small-world topology in efficient face perception.
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