A Computational Neural Model for Mapping Degenerate Neural Architectures

Degeneracy in biological systems refers to a many-to-one mapping between physical structures and their functional (including psychological) outcomes. Despite the ubiquity of the phenomenon, traditional analytical tools for modeling degeneracy in neuroscience are extremely limited. In this study, we generated synthetic datasets to describe three situations of degeneracy in fMRI data to demonstrate the limitations of the current univariate approach. We describe a novel computational approach for the analysis referred to as neural topographic factor analysis (NTFA). NTFA is designed to capture variations in neural activity across task conditions and participants. The advantage of this discovery-oriented approach is to reveal whether and how experimental trials and participants cluster into task conditions and participant groups. We applied NTFA on simulated data, revealing the appropriate degeneracy assumption …

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Recommended citation: @article{khan2022computational, title={A computational neural model for mapping degenerate neural architectures}, author={Khan, Zulqarnain and Wang, Yiyu and Sennesh, Eli and Dy, Jennifer and Ostadabbas, Sarah and van de Meent, Jan-Willem and Hutchinson, J Benjamin and Satpute, Ajay B}, journal={Neuroinformatics}, pages={1–15}, year={2022}, publisher={Springer} }