• Home
  • People
    Current Members
    Lab Alumni
  • Research
    Overview
    Highlights
    Methods & Tools
  • Publications
  • News
  • Resources
  • Join Us
  • Home
  • People
    Current Members
    Lab Alumni
  • Research
    Overview
    Highlights
    Methods & Tools
  • Publications
  • News
  • Resources
  • Join Us
Home > Journal Club & Teaching

Journal Club & Teaching

Facemap: a framework for modeling neural activity based on orofacial tracking

Abstract

Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relate them to neural activity. Here we developed Facemap, a framework consisting of a keypoint tracker and a deep neural network encoder for predicting neural activity. Our algorithm for tracking mouse orofacial behaviors was more accurate than existing pose estimation tools, while the processing speed was several times faster, making it a powerful tool for real-time experimental interventions. The Facemap tracker was easy to adapt to data from new labs, requiring as few as 10 annotated frames for near-optimal performance. We used the keypoints as inputs to a deep neural network which predicts the activity of ~50,000 simultaneously-recorded neurons and, in visual cortex, we doubled the amount of explained variance compared to previous methods. Using this model, we found that the neuronal activity clusters that were well predicted from behavior were more spatially spread out across cortex. We also found that the deep behavioral features from the model had stereotypical, sequential dynamics that were not reversible in time. In summary, Facemap provides a stepping stone toward understanding the function of the brain-wide neural signals and their relation to behavior.


Atika Syeda, Lin Zhong, Renee Tung, Will Long, Marius Pachitariu & Carsen Stringer. Facemap: a framework for modeling neural activity based on orofacial tracking. Nature Neuroscience, 2023-11. [LINK]


Speaker: Nan Huang

Time: 9:00 am, 2024/03/04

Location: CIBR A622


  • People
  • Research
  • Publications
  • News
  • Resources
  • Join Us
  • 北京脑科学与类脑研究所 - 周景峰实验室
  • Chinese Institute for Brain Research, Beijing
  • Bldg 3, 9 Yike Rd, ZGC Life Sci Park, Changping, Beijing 102206

2024 © Zhou Lab - Chinese Institute for Brain Research, Beijing - 京ICP备18029179号 ❀