Software

The analysis of moment-to-moment changes in co-activation patterns (CAPs) in functional MRI (fMRI) has been useful for studying dynamic properties of neural activity. This method is based on clustering fMRI time-frames into several recurrent spatial patterns within and across subjects. Studies have also focused on quantifying properties of the temporal organization of CAPs, such as fractional occupancy and dwell time. The analyses of co-activations are computationally intensive, requiring the clustering of high-dimensional data concatenated over subjects. Further, while a variety of analytic choices are involved in studying CAPs, the field lacks a unified open-source platform to allow a robust feature selection required for reproducible mappings of brain and behavioral measurements. We are currently developing BrainCAP, an open-source Python-based toolkit for quantifying CAPs from fMRI data in cross-sectional and longitudinal studies.

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