Bijan Pesaran

Sep 6, 2024 | nature.com | Omid G Sani |Bijan Pesaran |Maryam M. Shanechi

AbstractUnderstanding the dynamical transformation of neural activity to behavior requires new capabilities to nonlinearly model, dissociate and prioritize behaviorally relevant neural dynamics and test hypotheses about the origin of nonlinearity. We present dissociative prioritized analysis of dynamics (DPAD), a nonlinear dynamical modeling approach that enables these capabilities with a multisection neural network architecture and training approach.

Dec 20, 2023 | biorxiv.org | Bijan Pesaran |Maryam M. Shanechi |Nitin Sadras

AbstractThe detection of events in time-series data is a common signal-processing problem. When the data can be modeled as a known template signal with an unknown delay in Gaussian noise, detection of the template signal can be done with a traditional matched filter. However, in many applications, the event of interest is represented in multimodal data consisting of both Gaussian and point-process time series.