Abstract #2479

Towards Mapping the Resting-State Connectome of the Limbic System in Real-Time with Connectome-based Neurofeedback

Jeff Sharpe^1,2, Bruno Sa de la Rocque Guimaraes^1,3, and Stefan Posse^1,4

¹Neurology Department, University of New Mexico, Albuquerque, NM, United States, ²Computer Science Department, University of New Mexico, Albuquerque, NM, United States, ³Nuclear Engineering Department, University of New Mexico, Albuquerque, NM, United States, ⁴Physics and Astronomy Department, University of New Mexico, Albuquerque, NM, United States

Synopsis

In the present study we develop a real-time seed-based correlation analysis (SBC) pipeline with online regression to compute a connectome fingerprint matrix and characterize the performance of this methodology for quantifying intra- and inter-network connectivity dynamics across major resting state networks (RSNs) in healthy subjects. We assess the association between connectivity in the limbic system and intensity of self-induced mood states with neurofeedback based on the connectome matrix.

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