Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 73,850 bioRxiv papers from 321,349 authors.

Hierarchical recurrent state space models reveal discrete and continuous dynamics of neural activity in C. elegans

By Scott Linderman, Annika Nichols, David Blei, Manuel Zimmer, Liam Paninski

Posted 29 Apr 2019
bioRxiv DOI: 10.1101/621540

Modern recording techniques enable large-scale measurements of neural activity in a variety of model organisms. The dynamics of neural activity shed light on how organisms process sensory information and generate motor behavior. Here, we study these dynamics using optical recordings of neural activity in the nematode C. elegans. To understand these data, we develop state space models that decompose neural time-series into segments with simple, linear dynamics. We incorporate these models into a hierarchical framework that combines partial recordings from many worms to learn shared structure, while still allowing for individual variability. This framework reveals latent states of population neural activity, along with the discrete behavioral states that govern dynamics in this state space. We find stochastic transition patterns between discrete states and see that transition probabilities are determined by both current brain activity and sensory cues. Our methods automatically recover transition times that closely match manual labels of different behaviors, such as forward crawling, reversals, and turns. Finally, the resulting model can simulate neural data, faithfully capturing salient patterns of whole brain dynamics seen in real data.

Download data

  • Downloaded 3,376 times
  • Download rankings, all-time:
    • Site-wide: 1,069 out of 73,896
    • In neuroscience: 149 out of 13,276
  • Year to date:
    • Site-wide: 1,129 out of 73,896
  • Since beginning of last month:
    • Site-wide: 1,129 out of 73,896

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


PanLingua

Sign up for the Rxivist weekly newsletter! (Click here for more details.)


News