Accepted_test

Identification and analysis of active neural cell ensembles associated with mice behavioral patterns
by Varekhina Alena | Institute of Information, Technology, Mathematics and Mechanics, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
Abstract ID: 619
Event: BGRS-abstracts
Sections: [Sym 10] Section “Neuroimaging and genotyping technologies for the diagnosis of neuropsychiatric disorders; methods of disease correction based on feedback technology; brain-computer interface technologies”

Calcium imaging is a method that allows recording calcium dynamics in neural cells not only in cultures, but also directly in the brain of the object of study. In this study, authors examined the relationship between animal behavior and the network calcium activity of neural cells. Neural impulses were recorded using an NVista HD head-mounted miniscope. The mouse with the miniscope was placed in a ring track and its activity was recorded too.

Video analysis allows identify groups of sequentially igniting cells (triples of active neurons). To establish the supposed signal propagation, triples with only two edges were considered. Further processing data allows extract cell ensembles that are statistically significant relative with mice behavior patterns. To demonstrate the significance of the relationship between combinations of triples cells and mouse behavior, the work of the algorithm on randomized graphs was studied.

Reproducible temporal relations in cell activation were restored. Results illustrated that there are triples of cells in definite configuration appears during a certain activity and their composition and frequency of activity differed from those in the randomized graph. Moreover, in randomized graph statistically significant triples appeared more than 4 times during the video were not found. This suggests that there is a pattern between signal transmissions in cells.  Obtained results can be used in the prediction of behavior patterns by the calcium dynamics of neural cells and the development of non-invasive brain-computer interfaces.