Decomposed linear dynamical systems for C. elegans functional connectivity
Eva Yezerets, Noga Mudrik, Yenho Chen, Christopher Rozell, Adam Charles · COSYNE 2023
Recent work has indicated that functional connections between C. elegans neurons can be clustered by their role in behavior, i.e. forward vs. reverse crawling vs. turning (Linderman et al. 2019). Furthermore they show how data-driven dynamical systems, e.g., the recurrent switching linear dynamical systems (rSLDS), can be learned in an unsupervised way from whole-brain recordings (Kato et al. 2015). However, these approaches ascribe a discrete overall state to the system at each time point, potentially missing different dimensions of variability in the data. For example, such models cannot fle
Sat, Mar 11, 2023