Honors Theses
A Reverse Translational Approach to Identifying Cerebellar Deficits in the Ts65Dn Preclinical Mouse Model of Down Syndrome
Advisor
Aaron Sathyanesan
Department
Biology and Computer Science
Publication Date
4-22-2026
Document Type
Honors Thesis
Abstract
People with Down syndrome have motor deficits that impact their ability to perform functional tasks. To understand the basic neurobiological mechanisms that cause motor disabilities in Down syndrome, we measured kinematic data using the Ts65Dn mouse model of Down syndrome. To correlate motor deficits to potential neuronal activity deficits in cerebellar Purkinje neurons, we used genetically-encoded functional reporters via realtime fiber photometry. For kinematic data we successfully designed and constructed a transparent split-belt treadmill with a 45 degree mirror set up below the split-belt platform so that a single camera could record the mice from the side and below simultaneously. We have also successfully optimized the split-belt treadmill paradigm using parameters relevant to human gait analysis on the splitbelt. Using gathered videos from the split-belt treadmill, we trained a dataset that created a tracking model with the python-based pose-estimation pipeline DeepLabCut. Our method has high translational potential since the split-belt treadmill task has been routinely used to quantify gait and cerebellum-associated deficits in humans. Using the B-SOiD unsupervised learning and clustering algorithm, we found evidence of behavioral differences between euploid and trisomic mice in the various phases of the treadmill test. We are currently deriving correlations between kinematic and functional neuronal activity data to better understand which of the specific regions of the cerebellum are responsible for the motor deficits in Down syndrome.
Permission Statement
This item is protected by copyright law (Title 17, U.S. Code) and may only be used for noncommercial, educational, and scholarly purposes.
Keywords
Undergraduate research
eCommons Citation
Salisbury, Henry R., "A Reverse Translational Approach to Identifying Cerebellar Deficits in the Ts65Dn Preclinical Mouse Model of Down Syndrome" (2026). Honors Theses. 519.
https://ecommons.udayton.edu/uhp_theses/519
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