Biology subjects

Chehade, H. D.

Publications and source records attributed to Chehade, H. D..

5 recordsLinked to original sources

bioRxiv2026

Time Course and Microcircuit Mechanisms of Primary Motor Cortex Dysfunction in Progressive Parkinsonism

Dysfunction of the primary motor cortex (M1) has long been implicated in the pathophysiology of Parkinsons disease (PD), mostly as a link by which abnormal basal ganglia and thalamic activities are translated into motor symptoms. However, emerging evidence suggests that M1 neurons also exhibit maladaptive changes in advanced parkinsonism. Here, using a progressive mouse model of nigrostriatal neurodegeneration (i.e., the MitoPark mice, MP), we found that M1 neurons develop age- and striatal dopamine-dependent synaptic and cellular adaptations as parkinsonism progresses. The optogenetic, electrophysiological, pharmacological, and CRISPR-mediated genetic studies demonstrated that impaired 5-GABAA receptor-mediated inhibition and excessive activation of NMDA receptors of M1 pyramidal neurons are key microcircu it mechanisms underlying cortical circuit remodeling during progressive striatal dopamine (DA) loss. Furthermore, we found that treatment with L-DOPA at early or late stages of parkinsonism can prevent or rescue, respectively, the synaptic and cellular adaptations in M1. Together, the present study demonstrates the time course and the underlying molecular and microcircuit mechanisms of cortical network dysfunction during the development of parkinsonism.

neuroscience↗

bioRxiv2026

Emergence of Task-Related Motor Cortical Dysfunction in Mice with Progressive Parkinsonism

There are substantial functional changes in the primary motor cortex (M1) in Parkinsons disease (PD). However, the temporal relationship between midbrain dopaminergic (DA) neurodegeneration, M1 circuit dysfunction, and Parkinsonian motor symptoms remains poorly understood. Using a genetic mouse model of progressive nigrostriatal DA degeneration ("MitoPark" mice), we determine the time course of M1 cellular dysfunction and skilled movement impairment as the midbrain DA neurons gradually degenerate. M1 pyramidal neuronal subtypes were identified using AAV-mediated retrograde labeling. During progressive DA loss, MitoPark mice developed gradually impaired performance in a reach-to-grasp single-food-pellet task. These impairments were detectable at a moderate motor stage of Parkinsonism. In vivo GCaMP6f imaging revealed that impaired skilled movement was associated with reduced cellular activity and movement responsiveness of M1 pyramidal neurons at a moderate motor stage of Parkinsonism. While both the corticospinal (CSp) and intratelencephalic (IT) neurons send glutamatergic inputs to the striatum, only the CSp neurons showed a selective and significant reduction in cellular activity and movement responsiveness during reaches. At the population level, we found that M1 pyramidal neurons include heterogeneous functional clusters with distinct temporal profiles in response to skilled movement. While movement encoding by different functional clusters is longitudinally stable in control mice, it degrades and diverges significantly in MitoPark mice. The impaired stability is further supported by a longitudinal analysis of individual neuronal activity related to movements. Together, these results provide novel insights into the emergence of M1 circuit pathophysiology at cellular and neural population levels during progressive Parkinsonism.

neuroscience↗

bioRxiv2024

Sub-second characterization of locomotor activities of mouse models of Parkinsonism

The degeneration of midbrain dopamine (DA) neurons disrupts the neural control of natural behavior, such as walking, posture, and gait in Parkinsons disease. While some aspects of motor symptoms can be managed by dopamine replacement therapies, others respond poorly. Recent advancements in machine learning-based technologies offer opportunities to better understand the organizing principles of behavior modules at fine time scales and its dependence on dopaminergic modulation. In the present study, we applied the motion sequencing (MoSeq) platform to study the spontaneous locomotor activities of neurotoxin and genetic mouse models of Parkinsonism as the midbrain DA neurons progressively degenerate. We also evaluated the treatment efficacy of levodopa (L-DOPA) on behavioral modules at fine time scales. We revealed robust changes in the kinematics and usage of the behavioral modules that encode spontaneous locomotor activity. Further analysis demonstrates that fast behavioral modules with higher velocities were more vulnerable to loss of DA and preferentially affected at early stages of Parkinsonism. Last, L-DOPA effectively improved the velocity, but not the usage and transition probability, of behavioral modules in Parkinsonian animals. In conclusion, the hypokinetic phenotypes in Parkinsonism involve the decreased velocities of behavioral modules and their disrupted temporal organization during movement. Moreover, we showed that the therapeutic effect of L-DOPA is mainly mediated by its effect on the velocities of behavior modules at fine time scales. This work documents robust changes in the velocity, usage, and temporal organization of behavioral modules and their responsiveness to dopaminergic treatment under the Parkinsonian state. Significance StatementParkinsons disease is the second largest neurodegenerative disease without a cure. Detection of subtle Parkinsonian signs is critical for disease-modification by applying early interventions. The present work explores the possibility of using machine learning-based approaches for early detection of subtle behavioral changes in Parkinsonian animals and evaluating the therapeutic efficacy of dopaminergic medications.

neuroscience↗

bioRxiv2024

Motor Cortical Neuronal Hyperexcitability Associated with α-Synuclein Aggregation

Dysfunction of the cerebral cortex is thought to underlie motor and cognitive impairments in Parkinson disease (PD). While cortical function is known to be suppressed by abnormal basal ganglia output following dopaminergic degeneration, it remains to be determined how the deposition of Lewy pathology disrupts cortical circuit integrity and function. Moreover, it is also unknown whether cortical Lewy pathology and midbrain dopaminergic degeneration interact to disrupt cortical function in late-stage. To begin to address these questions, we injected -synuclein (Syn) preformed fibrils (PFFs) into the dorsolateral striatum of mice to seed Syn pathology in the cortical cortex and induce degeneration of midbrain dopaminergic neurons. Using this model system, we reported that Syn aggregates accumulate in the motor cortex in a layer- and cell-subtype-specific pattern. Particularly, intratelencephalic neurons (ITNs) showed earlier accumulation and greater extent of Syn aggregates relative to corticospinal neurons (CSNs). Moreover, we demonstrated that the intrinsic excitability and inputs resistance of Syn aggregates-bearing ITNs in the secondary motor cortex (M2) are increased, along with a noticeable shrinkage of cell bodies and loss of dendritic spines. Last, neither the intrinsic excitability of CSNs nor their thalamocortical input was altered by a partial striatal dopamine depletion associated with Syn pathology. Our results documented motor cortical neuronal hyperexcitability associated with Syn aggregation and provided a novel mechanistic understanding of cortical circuit dysfunction in PD.

neuroscience↗

bioRxiv2024

Open-Source Platform for Kinematic Analysis of Mouse Forelimb Movement

We present an open-source behavioral platform and software solution for studying fine motor skills in mice performing reach-to-grasp task. The behavioral platform uses readily available and 3D-printed components and was designed to be affordable and universally reproducible. The protocol describes how to assemble the box, train mice to perform the task and process the video with the custom software pipeline to analyze forepaw kinematics. All the schematics, 3D models, code and assembly instructions are provided in the open GitHub repository. Graphical abstract

neuroscience↗