What Static Connectivity Misses: Dynamic Alpha-Band Brain Network States in First-Episode Psychosis.

Overview

1. Laboratory of Psychophysiology and Cognitive Neuroscience, Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
2. Institute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland
3. MINDIG, 35000 Rennes, France
4. Department of Science, Landspitali University Hospital, 105 Reykjavik, Iceland
5. College of Health and Life Sciences, Institute of Health and Neurodevelopment, Aston University, Birmingham, UK
6. Department of Clinical Neurophysiology, Birmingham Women’s and Children’s NHS FT, Birmingham, UK
7. IRCCS Fondazione Santa Lucia, Rome, Italy

Abstract

This study investigates resting-state EEG alpha-band connectivity in first-episode psychosis (FEP) using a novel dynamic connectivity pipeline and examines its relationship with cognitive functioning and psychopathological scores. Data from 78 individuals with FEP and 60 healthy controls (CTR) were analyzed. Source estimation was performed using eLORETA, and connectivity was quantified with the weighted phase-lag index. Static connectivity matrices were assessed using graph theory and edge-wise metrics. Dynamic connectivity matrices were clustered into five distinct brain network states (BNS) using a modified k-means algorithm, from which temporal and graph theory metrics were extracted. Static connectivity metrics revealed lower alpha connectivity in FEP than in controls. The dynamic approach identified reduced variability in the characteristic path length within the default mode network–associated BNS 1 in FEP, suggesting diminished adaptive modulation of functional integration. Subgroup analysis by medication status uncovered distinct BNS signatures for medicated and unmedicated FEP. BNS metrics were correlated with social cognition measures in CTR and with positive formal thought disorder in FEP, whereas static metrics showed no such associations. These findings suggest that relative to static connectivity metrics, dynamic connectivity provides non-redundant information and underscores the impact of medication on neural dynamics in psychosis.

Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1007/s10548-026-01249-9.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

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Data

Datasets cited

• doi:10.18112/openneuro.ds003944.v1.0.1, at OpenNeuro; found in “Data Availability”
• doi:10.18112/openneuro.ds003947.v1.0.1, at OpenNeuro; found in “Data Availability”

Data Availability

The EEG data analyzed in this study are publicly available from the OpenNeuro database (https://doi.org/10.18112/OPENNEURO.DS003944.V1.0.1 and https://doi.org/10.18112/OPENNEURO.DS003947.V1.0.1). Analysis scripts are available from the corresponding author upon reasonable request.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

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Version 3, 28 September 2026

• Publisher: n/a → Springer Science+Business Media
• Funding: added Università degli Studi di Roma Tor Vergata; Région Bretagne

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 6 keywords, 13 MeSH terms, 119 references.

Cite

This paper

Aubonnet, R., Hassan, M., Gargiulo, P., Seri, S., & Di Lorenzo, G. (2026). What Static Connectivity Misses: Dynamic Alpha-Band Brain Network States in First-Episode Psychosis. Brain topography, 39(6), 96. https://doi.org/10.1007/s10548-026-01249-9

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