Code supporting: Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease. Cocuzza C.V.*, Chopra S., Segal, A., Labache, L., Chin, R., Joss, K., and Holmes, A.J. (2025). In bioRxiv (p. 2025.05.23.655864). https://doi.org/10.1101/2025.05.23.655864
To investigate brain network dynamics linked with dimensionally-based symptom profiles exhibited across a transdiagnostic cohort of participants with and without psychiatric diagnoses.
Corresponding author email: [email protected]
Repository contents:
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Note that all scripts below include detailed annotations throughout; other contextual details may be found in the Methods section of the manuscript
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NMF_Cocuzza.py: python functions to implement non-negative matrix factorization (approach used to quantify brain network reconfiguration dynamics)
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Fingerprints_Cocuzza.py: python functions relevant to our symptom profiling/fingerprinting pipeline (note: RStudio used in select steps; notes are included where appropriate)
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Data_Splitting_Cocuzza.py: python script on how we split data into train/test/validation to avoid data leakage (see manuscript Methods)
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Heatmap_NetColors_Cocuzza.py: python function to visualize network color labels on x/y axes of functional connectivity matrices
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.Rmd scripts: RStudio scripts that are helpful for some functions inside Fingerprints_Cocuzza.py. See usage notes in Fingerprints_Cocuzza.py for details. Note that these R scripts require adaptation to your machine (e.g., directories, etc.) and research study (e.g., dataset specifications).
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.npy, .csv, and .pkl files. These are helper files for running functions in Fingerprints_Cocuzza.py (see usage notes in that script). These are fully de-identified and can be reconstituted by openly available Transdiagnostic Connectome Project data (see below for links to OpenNeuro and NDA).
Outside resources relevant to manuscript:
- Transdiagnostic Connectome Project data via OpenNeuro and NIMH Data Archive
- Transdiagnostic Connectome Project code repository (including resources for the pre-processing pipeline used in the present manuscript)
- Cortical parcellation repository (note: 400 parcel resolution used in mansucript as well as 17 networks per Yeo et al. 2011), Yan et al., 2023, NeuroImage
- Subcortical atlas repository (note: scale II used in manuscript), Tian et al., 2021, Nature Neuroscience
- Cerebellum identification repository (note: see Buckner study for details on spatial autocorrelation regression), Buckner et al., 2011, Journal of Neurophysiology
- Brain Connectivity Toolbox (used in select analyses; see network efficiency and participation coefficient) for MATLAB and Python
- Human Connectome Project Workbench for projecting results onto cortical surfaces (i.e., brain visualizations)