Data-driven analysis of motor activity implicates 5-HT2A neurons in backward locomotion of larval Drosophila.
Sci Rep
; 8(1): 10307, 2018 07 09.
Article
en En
| MEDLINE
| ID: mdl-29985473
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 patterns. By applying these methods to neurons targeted by 5-HT2A-GAL4, which we generated by the CRISPR/Cas9-system, we identified two classes of interneurons, termed Seta and Leta, which are specifically active during backward but not forward fictive locomotion. Optogenetic activation of Seta and Leta neurons increased backward locomotion. Conversely, thermogenetic inhibition of 5-HT2A-GAL4 neurons or application of a 5-HT2 antagonist decreased backward locomotion induced by noxious light stimuli. This study establishes an accelerated pipeline for activity profiling and cell identification in larval Drosophila and implicates the serotonergic system in the modulation of backward locomotion.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Proteínas de Drosophila
/
Receptor de Serotonina 5-HT2A
/
Drosophila
/
Locomoción
/
Neuronas Motoras
Tipo de estudio:
Prognostic_studies
Límite:
Animals
Idioma:
En
Revista:
Sci Rep
Año:
2018
Tipo del documento:
Article
País de afiliación:
Japón