Unsupervised quantification of naturalistic animal behaviors for gaining insight into the brain

Michael H. McCullough, Geoffrey J. Goodhill

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations

Abstract

Neural computation has evolved to optimize the behaviors that enable our survival. Although much previous work in neuroscience has focused on constrained task behaviors, recent advances in computer vision are fueling a trend toward the study of naturalistic behaviors. Automated tracking of fine-scale behaviors is generating rich datasets for animal models including rodents, fruit flies, zebrafish, and worms. However, extracting meaning from these large and complex data often requires sophisticated computational techniques. Here we review the latest methods and modeling approaches providing new insights into the brain from behavior. We focus on unsupervised methods for identifying stereotyped behaviors and for resolving details of the structure and dynamics of behavioral sequences.

Original languageEnglish
Pages (from-to)89-100
Number of pages12
JournalCurrent Opinion in Neurobiology
Volume70
DOIs
StatePublished - Oct 2021

Fingerprint

Dive into the research topics of 'Unsupervised quantification of naturalistic animal behaviors for gaining insight into the brain'. Together they form a unique fingerprint.

Cite this