Abstract
AbstractMice adeptly use their whiskers to touch, recognize, and learn about objects in their environment. This behavior is enabled by computations performed by populations of neurons in the somatosensory cortex. To understand these computations, we trained mice to use their whiskers to recognize different shapes while we recorded activity in the barrel cortex, which processes whisker input. Here, we present a large dataset of high-speed video of the whiskers, along with rigorous tracking of the entire extent of multiple whiskers and every contact they made on the shape. We used spike sorting to identify individual neurons, which responded with precise timing to whisker contacts and motion. These data will be useful for understanding the behavioral strategies mice use to explore objects, as well as the neuronal dynamics that mediate those strategies. In addition, our carefully curated labeled data could be used to develop new computer vision algorithms for tracking body posture, or for extracting responses of individual neurons from large-scale neural recordings.
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献