TY - GEN
T1 - Quantification of Aggregation and Associated Brain Areas in Drosophila Melanogaster
AU - Okuno, Takuto
AU - Hashimoto, Koichi
AU - Tanimoto, Hiromu
N1 - Funding Information:
Sirigrivatanawong (Tohoku University) for the initial work on TPro software and the source code. We thank T. Ichinose and V. Thoma (Tohoku University) for constructive comments and advices on the work and manuscript. K. Hashimoto (Tohoku University) acknowledges the support by JSPS KAKENHI Grant Number 16H06536.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - Social behavior requires the interaction among animals. Aggregation, spatial assembly of animals, facilitates inter-individual communication, and provides occasions of social interaction. To quantify aggregation in small animals such as insects it is necessary to detect individual animals at a high precision. By expanding the utility of recently developed machine vision software, we here track multiple individual Drosophila melanogaster and provide new metrics for quantifying aggregation. Flies in a circular arena immediately formed aggregation that is significantly higher than random distribution, and it developed over the course of 30 minutes. As the first step toward the identification of neural circuits underlying aggregation, we analyzed large trajectory data (18, 992 videos), where 2, 204 groups of neurons were genetically stimulated. Large-scale correlations of behavioral performance and labelled neurons identified brain areas associated with aggregation and isolation.
AB - Social behavior requires the interaction among animals. Aggregation, spatial assembly of animals, facilitates inter-individual communication, and provides occasions of social interaction. To quantify aggregation in small animals such as insects it is necessary to detect individual animals at a high precision. By expanding the utility of recently developed machine vision software, we here track multiple individual Drosophila melanogaster and provide new metrics for quantifying aggregation. Flies in a circular arena immediately formed aggregation that is significantly higher than random distribution, and it developed over the course of 30 minutes. As the first step toward the identification of neural circuits underlying aggregation, we analyzed large trajectory data (18, 992 videos), where 2, 204 groups of neurons were genetically stimulated. Large-scale correlations of behavioral performance and labelled neurons identified brain areas associated with aggregation and isolation.
KW - Drosophila melanogaster
KW - aggregation
KW - brain areas
KW - machine vision
UR - http://www.scopus.com/inward/record.url?scp=85067946518&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067946518&partnerID=8YFLogxK
U2 - 10.1109/PERCOMW.2019.8730594
DO - 10.1109/PERCOMW.2019.8730594
M3 - Conference contribution
AN - SCOPUS:85067946518
T3 - 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019
SP - 759
EP - 764
BT - 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019
Y2 - 11 March 2019 through 15 March 2019
ER -