Generating dynamical neuroimaging spatiotemporal representations (DyNeuSR) using topological data analysis

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Summary

To develop biologically-grounded psychiatric diagnosis, researchers and clinicians need tools for distilling complex high-dimensional neuroimaging data into simple yet interactive and clinically relevant representations. Further, for translational outcomes, these representations should be conceivable at the single participant level. TDA techniques such as Mapper allow generation of these representations. Here, we introduce a set of tools that can facilitate wider acceptance of Mapper within the neuroscience community and provide a series of easy-to-follow steps for visualizing Mapper-generated graphical representations. We provide detailed examples to reveal the “under-the-hood” workings of Mapper.  

Presentations/Papers

  1. Geniesse, C., Sporns, O., Petri, G., Saggar, M. (in-press) Generating dynamical neuroimaging spatiotemporal representations (DyNeuSR) using topological data analysis. Network Neuroscience

  2. Saggar, M., Sporns, O., Gonzalez-Castillo, J., Bandettini, P.A., Carlsson, G., Glover, G., Reiss, A.L. (2018) Towards a new approach to reveal dynamical organization of the brain using topological data analysis. Nature Communications. doi:10.1038/s41467-018-03664-4

Code and Notebooks

https://braindynamicslab.github.io/dyneusr/

Collaborators

Funding