Topic: whole-brain recordings

Switching linear dynamical system (SLDS) models are widely used for modeling neural and behavioral time series data [Glaser et al., 2020, Linderman et al., 2019, Nair et al., 2022, Zoltowski et al., 2022]. These models characterize high-dimensional time series through a combination of discrete and continuous latent states. The continuous states offer a low-dimensional representation of the data, while the discrete state defines how the continuous states evolve over time. Together, they provide quantitative and interpretable summaries of multidimensional time series. Unfortunately, fitting thes

Natural behavior requires flexible adjustments, for example when navigating complex environments or escaping predators. Previously, whole-brain recordings in C. elegans uncovered that a large proportion of neuronal activity relates to motor commands. However, the role of these distributed motor commands remains elusive.Here, we investigate changes in a C. elegans motor behavior and the corresponding distributed dynamics upon an environmental change. We find that environments that make movement more difficult provoke longer backwards movement, so-called “reversals”. Importantly, this prolongati