Application of the Flocking Method for Spatial Analysis of Brain Activity in Optogenetics Datasets

Margarita Zaleshina, Alexander Zaleshin

2023

Abstract

This work introduces a new approach for spatial analysis of assumed dynamics of neuronal activity in mouse brain images obtained by light-sheet fluorescence microscopy methods (LSM). In calculations we used flocking algorithms based on neuronal activity distributions from slice to slice with a time delay that occurs during scanning. We applied GDAL Tools and LF Tools in QGIS for topological processing of multi-page TIFF files with LSM datasets. As a result, we identified localizations of sites with small movements of group neuronal activity passing in the same locations (with retaining localization) from slice to slice. An important advantage of this result is the ability to reveal locations with pronounced neuronal activity in a sequence of several adjacent slices, as well as to identify set of sites with interslice activity.

Paper Citation

in Harvard Style

Zaleshina M. and Zaleshin A. (2023). Application of the Flocking Method for Spatial Analysis of Brain Activity in Optogenetics Datasets. In Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: NCTA; ISBN 978-989-758-674-3, SciTePress, pages 471-478. DOI: 10.5220/0012154100003595

in Bibtex Style

@conference{ncta23,
author={Margarita Zaleshina and Alexander Zaleshin},
title={Application of the Flocking Method for Spatial Analysis of Brain Activity in Optogenetics Datasets},
booktitle={Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: NCTA},
year={2023},
pages={471-478},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012154100003595},
isbn={978-989-758-674-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: NCTA
TI - Application of the Flocking Method for Spatial Analysis of Brain Activity in Optogenetics Datasets
SN - 978-989-758-674-3
AU - Zaleshina M.
AU - Zaleshin A.
PY - 2023
SP - 471
EP - 478
DO - 10.5220/0012154100003595
PB - SciTePress