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Motor and Hippocampal Dependent Spatial Learning and Reference Memory Assessment in a Transgenic Rat Model of Alzheimer's Disease with Stroke

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Assessing post-stroke cognition in pre-clinical models: lessons and recommendations from a multi-center study.

G Brezzo^1,2, K A Zera³, D Straus^1,2

¹UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK.

Biorxiv : the Preprint Server for Biology

|June 6, 2025

Summary

Detecting cognitive deficits after stroke in mice is challenging. While the Barnes Maze showed promise, the Novel Object Recognition test did not reliably detect impairment, highlighting the need for improved preclinical stroke cognition study designs.

Keywords:

Cognitive behavioral testing multi-center trial neurofilament light chain post-stroke cognitive impairment stroke

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Area of Science:

Neuroscience
Translational Medicine
Animal Models

Background:

Cognitive decline is a major consequence of stroke, yet effective treatments are lacking.
Developing therapies requires reliable methods to detect post-stroke cognitive impairment in preclinical models.

Purpose of the Study:

To establish a robust multi-site method for detecting cognitive performance deficits after ischemic stroke in mice.
To evaluate the efficacy of Novel Object Recognition (NOR) and Barnes Maze (BM) tests in assessing post-stroke cognitive function.

Main Methods:

Ischemic stroke was induced in mice using three models: distal middle cerebral artery occlusion (dMCAO), dMCAO with hypoxia, and transient middle cerebral artery occlusion.
Cognitive function was assessed using NOR and BM tests at baseline, sub-acute (1-2 weeks), and chronic (8 weeks) post-stroke.
Histology, immunostaining, and plasma neurofilament light quantification were used to evaluate brain damage and neuronal loss.

Main Results:

The Novel Object Recognition test did not reliably detect cognitive deficits following stroke.
The Barnes Maze showed a promising signal for detecting cognitive impairment, though tested at a single site.
Histological analyses confirmed varying degrees of infarct size and neuronal damage across stroke models.

Conclusions:

Detecting cognitive impairment in preclinical stroke models presents significant challenges, impacting therapy development.
The Barnes Maze may offer a more sensitive measure of post-stroke cognitive deficits than NOR in certain contexts.
Recommendations are provided for optimizing the design and execution of multi-site preclinical stroke cognition studies.