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Studies of mouse gait to help in finding approaches to Alzheimer's disease

May 12th, 2023
Studies of mouse gait to help in finding approaches to Alzheimer's disease
The overall view of the open field arena with transparent floor as observed by the camera located underneath. (B) Tracked animal body parts: A- Snout, B- Left front paw, C- Right front paw, D- Body midpoint, E- Left hind paw, F- Right hind paw, G- Tail. Connections represent the animal movement network model, where nodes are associated with animal body parts and edges characterize their mutual dynamics. Highlighted edges form the network backbone consisting of links between various body parts and animal body midpoint, while secondary links denote all pairwise connections (not shown). Each link is characterized by some mutual movement metric, such as the detrended cross-correlation coefficient Rij or partial correlation Pij, respectively. Credit: Kazan Federal University

A new paper was placed in Frontiers in Neuroinformatics.

KFU's partners in this research were LETI University and Arbuzov Institute of Organic and Physical Chemistry.

Instrumental measurements and digital analysis of gait are important in studying neurodegenerative syndromes, so the workgroup decided to resort to animal testing.

Co-author, Lead Research Associate Yana Mukhamedshina explains, "According to statistics, about 1.248 million people in Russia are afflicted with Alzheimer's, and over 1 million—with Parkinson's disease. During the last 25 years, their prevalence has risen respectively by 2.4 percent and 15.7 percent. There is no data about their prevalence in animals."

Marker-free tracking analysis, which was used in this case, is based on non-detector observations of gait in transgenic mice with a chimeric mouse/human amyloid precursor protein (Mo/HuAPP695swe) and a mutant human presenilin 1 (PS1-dE9).

"The mathematical model is built on the basis of recurrent maps, in some approximation predicting where the observed object will be in the next step, taking into account some history of its motion. The closer the parameters of this display are to the true characteristics of motion, the more precisely it reproduces them and the more precisely it solves the problems of filtering (noise minimization in the monitored video recordings), interpolation (filling in the passages), and extrapolation (prediction of movement dynamics). In terms of formal mathematical description, this is the same problem of finding a model of motion," says Professor of LETI University Mikhail Bogachev.

With this approach, the analysis of video recordings of animal movements in an open field with a transparent floor is carried out using computerized methods. The recognition of the trajectories of movement of individual parts of the body of animals is realized using modern neural network algorithms of deep machine learning. Subsequently, the dynamic gait model is identified on the basis of the trajectory determination results.

Such mathematical models can be usfeul in clinical diagnostics of diseases with symptoms of locomotion disorders. The difficulty is that locomotion pathology cannot be fully studied with routine examinations or instrumental methods. That's why standardized mathematical methods are in demand.

More information:
Video-based marker-free tracking and multi-scale analysis of mouse locomotor activity and behavioral aspects in an open field arena: A perspective approach to the quantification of complex gait disturbances associated with Alzheimer's disease
www.frontiersin.org/articles/1 … nf.2023.1101112/full

Provided by Kazan Federal University

Citation: Studies of mouse gait to help in finding approaches to Alzheimer's disease (2023, May 12) retrieved 21 August 2025 from https://sciencex.com/wire-news/445321632/studies-of-mouse-gait-to-help-in-finding-approaches-to-alzheimer.html
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