Discover the research areas of the Shaikh Lab in the Department of Neurology at Case Western Reserve University School of Medicine.
Perception and Action in Parkinson's Disease
The brain learns from past perceptions to enhance future actions, but this process is compromised in Parkinson's disease (PD), hindering daily tasks. Our research investigated this impairment across spatial, visual, and eye movement domains. Through spatial navigation experiments using virtual reality, we uncovered abnormal perceptions in PD. By employing deep brain stimulation (DBS) models and neuroimaging, we identified brain regions and modulation techniques to enhance spatial perception, potentially reducing falls. These findings laid the groundwork for innovative applications of brain neuromodulation, like DBS, to prevent falls and increase longevity in the elderly.
Visual perception relies on the interplay between prior experiences' cognitive influence and real-time visual input encoding. In PD, strong visual priors can lead to hallucinations. Through DBS, we identified methods to modulate these priors. Stimulating cortico-subthalamic projections reinstated crucial bottom-up visual encoding. These breakthroughs lay the groundwork for using focused DBS neuromodulation to address visual hallucinations, with potential applications in treating hallucinations across various neuropsychiatric conditions prevalent in veterans.
Our research elucidated the mechanisms behind abnormal binocular control, which contributes to reading difficulty and double vision in around one-third of PD patients. We identified subthalamic regions modifiable via DBS to address eye misalignment. These findings offer innovative avenues for DBS treatment targeting visuospatial and visuomotor dysfunction across various neurodegenerative conditions.
The image presents an overview of our lab's setup, featuring an immersive virtual reality system combined with an en bloc motion simulator (resembling a flight simulator) on the right. In the background, a mathematical model of vestibular perception is depicted, with its outputs predicting experimental outcomes. Central to our research endeavors is the integration of psychophysics and motor experiments with advanced neuromimetic computational simulations, propelling us towards pioneering discoveries.
Customized Remote Rehab (Adaptive Bike)
We combine artificial intelligence, wearable sensing, and adaptive control systems modeling to develop and validate an innovative rehabilitation technique: the adaptive bike. This bike dynamically adjusts pedal resistance based on the user's behavioral output. Patients wear inertial moment units and pedal a stationary bike, with the wearables capturing patient-specific motor outputs. These outputs inform clinical measures and serve as the controller for the adaptive bike, allowing its resistance to adapt to the patient's movements. This methodology eliminates the need for in-person rehabilitation sessions, enabling remote precision care delivery. Our project aims to create clinical tools facilitating remote care delivery, utilizing a user-friendly, in-home infrastructure depicted in the schematic diagram below.
Translational Neurology of Eye Movement Disorders
Our lab is one of the few worldwide to study the neuro-ophthalmology of eye movements utilizing computational and engineering approaches. We have practiced a multidisciplinary approach—experimental examination of the eye movement disorder, simulating the phenomenology with conductance-based neuromimetic computational models of brain circuits, and simulation of novel therapeutic effects, and then applying the theoretical concept to design the optimal therapeutic candidate for the treatment of disabling disorder as opsoclonus, oculopalatal tremor, or nystagmus. This approach has discovered the rationale for using various drugs such as beta-blockers, primidone, and benzodiazepine to treat opsoclonus, quinine for oculopalatal tremor, and levetiracetam for acquired pendular nystagmus.
The image above serves as the cover for an e-book edited by Dr. Shaikh, encapsulating our lab's philosophy. It illustrates the normal physiological interaction between the inferior olive and the cerebellum (top left), alongside a simulation of neuronal activity in an advanced neuromimetic model (top right). Subsequently, the same model is "lesioned" to induce pseudo-hypertrophy of the inferior olive (bottom right), resulting in synchronous discharges and triggering the syndrome of oculopalatal tremor (bottom left).
Integrative Network Theory in Dystonia
The third most common movement disorder causing abnormal twisting and turning of the body, dystonia, is traditionally considered a basal ganglia disorder, while contemporary theories emphasize the cerebellum’s role. Our multidisciplinary approach using motion capture techniques with wearable sensors, machine learning, single-unit electrophysiology, and local field potentials suggested that dystonia is due to abnormal brain network function converting a movement velocity signal to a stabilizing position for balance and coordination.
Our studies emphasized the significance of multi-level feedback from the cerebellum, basal ganglia, and proprioception in dystonia. This innovative framework, radically different from traditional beliefs, provided an integrative model for reconciling many conflicting views. The results have profound implications for interpreting basic and clinical studies and identifying other therapeutic targets, raising new prospects for non-invasive and surgical interventions for treating dystonia, which is common and severely disabling in Veterans and non-Veterans.
The image above illustrates our innovative approach, merging single-unit recordings from the human brain, local field potential measures from the basal ganglia, and computational simulations. This strategic translational method harnesses cutting-edge computational and neural engineering techniques to analyze and address debilitating diseases that impair brain function.