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Angle Basis: a Generative Model and Decomposition for Functional Connectivity
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  • Anton Orlichenko ,
  • Gang Qu ,
  • Ziyu Zhou ,
  • Zhengming Ding ,
  • Yu-Ping Wang
Anton Orlichenko
Tulane University

Corresponding Author:[email protected]

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Ziyu Zhou
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Zhengming Ding
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Yu-Ping Wang
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In this paper we present a new decomposition and generative model for functional connectivity (FC), achieve 10x data compression, 97.3% identifiability, and modest improvent on FC-based predictive tasks. Additionally we are able to generate synthetic subjects with user-inputted clinical characteristics.
fMRI and phenotype data came from the Neurodevelopmental Genomics: Trajectories of Complex Phenotypes database of genotypes and phenotypes repository, dbGaP Study Accession ID phs000607.v3.p2, as well as the Bipolar and Schizophrenia Network for Intermediate Phenotypes study (http://b-snip.org/).
Additional data from OpenNeuro study ds004144 on fibromyalgia is included in the linked-to code.