Biology subjects

De Sa, R.

Publications and source records attributed to De Sa, R..

4 recordsLinked to original sources

bioRxiv2025

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↗

bioRxiv2025

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↗

bioRxiv2024

Early intrinsic plasticity of ACC engram neurons defines memory formation and precision

Neocortical memory engrams are thought to stabilize and mature via enhanced interconnectivity during the so-called systems-consolidation process 1,2. While synaptic plasticity of these engram connections is considered an important mechanism for storing memories 3,4, it cannot fully account for the dynamic vividness of remote, cortically-based memories. Indeed, cell-intrinsic plasticity has been touted as the crucial early priming mechanism that renders nascent engram neurons susceptible to ongoing plastic processes while providing flexibility for later encoding events 5-7. Here, we reveal that learning-related neuron-wide intrinsic excitability (IE) plasticity of nascent cortical engram neurons is a permissive mechanism for the formation and specificity of remote associative memories. Using a c-fos-dependent genetic and viral system for the targeted labeling of engram neurons in the anterior cingulate cortex (ACC) combined with ex vivo electrophysiology, we found that contextual fear learning triggered a time-dependent increase in their IE signature expressed over days during the early, but not late, phase of memory formation. Remarkably, chemogenetically hyperpolarizing engram neurons during this early plastic phase enhanced their maturation, increasing the strength and context-precision of consolidated memories and preventing memory disturbance caused by an interference event. Altogether, our findings identify cell-intrinsic plasticity within nascent ACC engram neurons as an essential tagging mechanism whose features determine the fate and dynamic content of remote memories.

neuroscience↗

bioRxiv2023

Refined movement analysis in the Staircase test reveals differential motor deficits in mouse models of stroke

Accurate assessment of post-stroke deficits is vital in translational research. Recent advances in machine learning provide unprecedented precision in quantifying rodent motor behavior post-stroke. However, the extent to which these tools can detect lesion-specific upper extremity deficits remains unclear. Using proximal middle cerebral artery occlusion (MCAO) and cortical photothrombosis (PT), we assessed post-stroke impairments in mice through the Staircase test. Lesion locations were identified using 7T-MRI. Machine learning was applied to reconstruct kinematic trajectories using MouseReach, a data-processing toolbox. This yielded 30 refined outcome parameters effectively capturing motor deficits. Lesion reconstructions located ischemic centers in the striatum (MCAO) and sensorimotor cortex (PT). Pellet retrieval was altered in both cases but did not correlate with stroke volume or ischemia extent. Instead, cortical ischemia was characterized by increased hand slips and modified reaching success. Striatal ischemia led to progressively prolonged reach durations, mirroring delayed symptom onset in basal ganglia strokes. In summary, refined machine learning-based movement analysis revealed specific deficits in mice after cortical and striatal ischemia. These findings emphasize the importance of thorough behavioral profiling in preclinical stroke research to increase translational validity of behavioral assessments.

neuroscience↗