Data-driven analysis of motor activity implicates 5-HT2A neurons in backward locomotion of larval Drosophila.

ABSTRACT: Rhythmic animal behaviors are regulated in part by neural circuits called the central pattern generators (CPGs). Classifying neural population activities correlated with body movements and identifying the associated component neurons are critical steps in understanding CPGs. Previous methods that classify neural dynamics obtained by dimension reduction algorithms often require manual optimization which could be laborious and preparation-specific. Here, we present a simpler and more flexible method that is based on the pre-trained convolutional neural network model VGG-16 and unsupervised learning, and successfully classifies the fictive motor patterns in Drosophila larvae under various imaging conditions. We also used voxel-wise correlation mapping to identify neurons associated with motor

SUBMITTER: Park J 

PROVIDER: S-EPMC6037780 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature