Home > Publications Database > Refined movement analysis in the staircase test reveals differential motor deficits in mouse models of stroke. > print

001     271972
005     20250202000614.0
024 7 _ |a pmc:PMC11418716
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024 7 _ |a 10.1177/0271678X241254718
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037 _ _ |a DZNE-2024-01114
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Skrobot, Matej
|0 0000-0001-6686-1880
|b 0
245 _ _ |a Refined movement analysis in the staircase test reveals differential motor deficits in mouse models of stroke.
260 _ _ |a London
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520 _ _ |a Accurate assessment of post-stroke deficits is crucial in translational research. Recent advances in machine learning offer precise quantification of rodent motor behavior post-stroke, yet detecting lesion-specific upper extremity deficits remains unclear. Employing proximal middle cerebral artery occlusion (MCAO) and cortical photothrombosis (PT) in mice, we assessed post-stroke impairments via the Staircase test. Lesion locations were identified using 7 T-MRI. Machine learning was applied to reconstruct forepaw kinematic trajectories and feature analysis was achieved with MouseReach, a new data-processing toolbox. Lesion reconstructions pinpointed ischemic centers in the striatum (MCAO) and sensorimotor cortex (PT). Pellet retrieval alterations were observed, but were unrelated to overall stroke volume. Instead, forepaw slips and relative reaching success correlated with increasing cortical lesion size in both models. Striatal lesion size after MCAO was associated with prolonged reach durations that occurred with delayed symptom onset. Further analysis on the impact of selective serotonin reuptake inhibitors in the PT model revealed no clear treatment effects but replicated strong effect sizes of slips for post-stroke deficit detection. In summary, refined movement analysis unveiled specific deficits in two widely-used mouse stroke models, emphasizing the value of deep behavioral profiling in preclinical stroke research to enhance model validity for clinical translation.
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650 _ 7 |a Machine learning
|2 Other
650 _ 7 |a motor deficits
|2 Other
650 _ 7 |a rodent models
|2 Other
650 _ 7 |a stroke
|2 Other
650 _ 7 |a translational research
|2 Other
650 _ 2 |a Animals
|2 MeSH
650 _ 2 |a Mice
|2 MeSH
650 _ 2 |a Disease Models, Animal
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Infarction, Middle Cerebral Artery: diagnostic imaging
|2 MeSH
650 _ 2 |a Infarction, Middle Cerebral Artery: physiopathology
|2 MeSH
650 _ 2 |a Infarction, Middle Cerebral Artery: complications
|2 MeSH
650 _ 2 |a Stroke: physiopathology
|2 MeSH
650 _ 2 |a Stroke: diagnostic imaging
|2 MeSH
650 _ 2 |a Stroke: complications
|2 MeSH
650 _ 2 |a Mice, Inbred C57BL
|2 MeSH
650 _ 2 |a Magnetic Resonance Imaging: methods
|2 MeSH
650 _ 2 |a Machine Learning
|2 MeSH
650 _ 2 |a Movement: physiology
|2 MeSH
700 1 _ |a Sa, Rafael De
|b 1
700 1 _ |a Walter, Josefine
|b 2
700 1 _ |a Vogt, Arend
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700 1 _ |a Paulat, Raik
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700 1 _ |a Lips, Janet
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700 1 _ |a Mosch, Larissa
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700 1 _ |a Mueller, Susanne
|0 0000-0001-8777-4823
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700 1 _ |a Dominiak, Sina
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700 1 _ |a Sachdev, Robert
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700 1 _ |a Boehm-Sturm, Philipp
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700 1 _ |a Dirnagl, Ulrich
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700 1 _ |a Endres, Matthias
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700 1 _ |a Harms, Christoph
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700 1 _ |a Wenger, Nikolaus
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773 _ _ |a 10.1177/0271678X241254718
|g Vol. 44, no. 9, p. 0271678X241254718
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|t Journal of cerebral blood flow & metabolism
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910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
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