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Behrsing, R.

Publications and source records attributed to Behrsing, R..

2 recordsLinked to original sources

Change in motor state equilibrium explains prokinetic effect of apomorphine on locomotion in experimental Parkinsonism

Gait impairments remain a major therapeutic challenge in Parkinsons disease (PD). Apomorphine is gaining renewed clinical attention with the expanding use of pump infusion systems. Yet, the specific role of apomorphine on the neural regulation of gait has remained poorly characterized, limiting its targeted use for symptom-specific therapy in PD. Here, we examined the neurobehavioral effects of apomorphine on runway locomotion in the unilateral 6-hydroxydopamine (6-OHDA) rat model. Therapeutic drug doses significantly increased total walking distance, related to reduced akinesia and prolonged gait episodes. Conversely, 3D kinematic analysis revealed reduced limb velocities under medication. At the neural level, therapy doses selectively enhanced cortical high-gamma rhythms without substantially altering beta or low-gamma activity. Instead, beta and low-gamma oscillations were consistently suppressed during motor activity in both medication ON and OFF conditions. Neurobehavioral correlations showed that transitions into gait were facilitated by reductions in beta and low-gamma activity, whereas transitions to akinesia were primarily suppressed when high-gamma activity was elevated. Our findings suggest that modulating cortical activity can aid ameliorating gait deficits in PD. We further propose that the complex therapy effects of apomorphine are best explained by a shift in motor-state equilibrium that is defined by the transitions of akinesia, stationary movements and gait. Together, these insights establish a mechanistic framework to guide the development of targeted gait therapies in PD.

neuroscience↗

Uncovering the Neural Fingerprint of Akinetic States in a Parkinsons Disease Rodent Model

Gait deficits present an unresolved therapeutic challenge in Parkinsons Disease. At the behavioral level, symptoms exhibit heterogeneity, including bradykinesia and hypokinesia during cyclical limb movement, as well as sudden interruptions in the gait sequence, also known as freezing of gait. The neural activities that drive these various deficits remain largely unknown. Here, we investigated the neural correlates of gait sequence interruptions with deep neurobehavioral phenotyping. For this, we transformed kinematic trajectories and cortical oscillations into continuous time series of multimodal feature vectors. Next, we applied machine learning, combining low-dimensional embedding with supervised classification, to identify cortical oscillation features that drive gait deficits. In a rodent Parkinsons disease model, our approach revealed that gait, akinesia, and stationary movements occupy prominently different regions in the low-dimensional embedding space. Among the predominant features separating the states, we found Hjorth complexity and mobility to modulate with the onset of akinetic episodes. Additionally, we validated our analysis approach in two Parkinson patients with freezing of gait, where neural features in STN recordings partially reflected the findings from ECoG measurements in rodents. The presented neurobehavioral phenotyping approach is translational and can easily generalize to the analysis of other complex movement disorders. Together, our results highlight specific features of neural oscillations as potential biomarkers that may support the development of adaptive closed-loop algorithms for gait therapy in PD.

neuroscience↗