Machine Learning for Precision Neuropsychiatry ML4PNP

New Publication in Nature Communications Biology, Normative Modeling of Brain Dynamics

We are excited to share our latest publication in Communications Biology (Nature Portfolio):

Normative modeling of brain dynamics across the lifespan

Understanding variability in brain function is a central challenge in neuroscience and psychiatry. In this study, we introduce a large-scale normative modeling framework to characterize brain dynamics across the human lifespan using MEG data.

By leveraging multi-site datasets and advanced machine learning techniques, the study establishes normative ranges of oscillatory brain activity across different frequency bands. These models capture how brain dynamics evolve with age and provide a reference against which individual deviations can be quantified.

The results demonstrate that:

This work represents an important step toward precision neuropsychiatry, where individualized assessments of brain function can support diagnosis, prognosis, and treatment selection.

This publication is closely connected to ongoing efforts in the lab, including the MEGaNorm initiative, aimed at charting normative brain function at multiple temporal, spatial, and individual scales.

We invite you to read the full article here:
https://www.nature.com/articles/s42003-026-09825-2

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