Brain CommunicationsNeurosciencePeer-reviewed journal article
Cerebellar Activity in PINK1 Knockout Rats during Volitional Gait
Valerie DeAngelo, Justin D. HilliardiD, Chia‐Han ChiangiD, Jonathan ViventiiD, George C. McConnelliD
Abstract
Preclinical models of Parkinsons disease are imperative to gain insight into the neural circuits that contribute to gait dysfunction in advanced stages of the disease. The PTEN-induced putative kinase 1 (P1) knockout (KO) early onset model of Parkinsons disease may be a useful rodent model to study the effects of neurotransmitter degeneration caused by loss of P1 function on brain activity during volitional gait. The goal of this study was to measure changes in neural activity at the cerebellar vermis (CBLv) at 8 months of age. Gait deficits, except run speed, were not significantly different from age-matched wild-type (WT) controls as previously reported. P1KO (n=4) and WT (n=4) rats were implanted with a micro-electrocorticographic array placed over CBLv lobules VI (a, b, and c) and VII. Local field potential recordings were obtained during volitional gait across a runway. Power spectral analysis and coherence analysis were used to quantify network oscillatory activity in frequency bands of interest. CBLv power was hypoactive in the beta (VIb, VIc, and VII) and alpha (VII) bands at CBLv lobules VIb, VIc, and VII in P1KO rats compared to WT controls during gait (p<0.05). These results suggest that gait improvement in P1KO rats at 8 months may be a compensatory mechanism attributed to movement corrections caused by decreased inhibition of the alpha band of CBLv lobule VII and beta band of lobules VIb, VIc, and VII. The P1KO model may be a valuable tool for understanding the circuit mechanisms underlying gait dysfunction in early-onset Parkinsons disease patients with functional loss of P1. Future studies investigating the CBLv as a potential biomarker and therapeutic target for the treatment of gait dysfunction in Parkinsons disease are warranted.
- organism: rat
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 4
- FWCI
- 1.07
- Field percentile
- top 23%
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