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Confronting the connectivity crisis in human M/EEG research.
Ole Jensen1, Hyojin Park2, Oscar Ferrante3
1Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK; Oxford Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK.
Trends in Cognitive Sciences
|September 19, 2025
Summary
Researchers need standardized methods for measuring brain connectivity using M/EEG data. Developing community-driven, validated connectivity metrics will improve replicability in cognitive and clinical neuroscience.
Area of Science:
- Cognitive Neuroscience
- Neuroimaging
Background:
- The field of cognitive neuroscience relies heavily on M/EEG data.
- Current measures of task-related inter-regional brain connectivity lack standardization.
- This hinders generalization across different tasks and research settings.
Purpose of the Study:
- To address the lack of standardized connectivity measures in M/EEG research.
- To advocate for community-driven efforts in validating these metrics.
- To establish robust and replicable frameworks for cognitive and clinical applications.
Main Methods:
- Systematic testing and validation of connectivity metrics.
- Utilization of shared datasets and standardized protocols.
- Community-driven collaborative approach.
Main Results:
- The study highlights a critical need for consensus on connectivity measures.
- It proposes a framework for systematic validation.
- The goal is to enhance the reliability and generalizability of findings.
Conclusions:
- Standardized, validated connectivity metrics are essential for M/EEG research.
- Community collaboration is key to achieving robust and replicable neuroscience.
- This will advance both fundamental cognitive understanding and clinical applications.
