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Energy Manifold Natural Gradient Descent: From Riemannian Optimization to Modern Neuroscience, NeuroAI and Quantum Physics

Dr. Rishabh Pathak
When Geometry, Energy, Artificial Intelligence and Neuroscience Converge Modern Artificial Intelligence is rapidly moving beyond the idea that learning simply means minimizing an error function. Increasingly, researchers are asking a deeper question: what is the structure of the space in which learning takes place? This question becomes particularly important when the system being modelled is constrained, nonlinear, dynamic, or governed by physical principles. A recent work titled “Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers” , by Zhangyong Liang and Huanhuan Gao, introduces Energy Manifold Natural Gradient Descent (EMNGD) , a mathematical framework that extends energy-based natural-gradient optimization from unconstrained Euclidean parameter spaces to constrained Riemannian parameter manifolds . At its core, the framework proposes a simple but powerful principle: An optimization algorithm should not only determine how to reduce error; it sh...
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How the Neural network circuits works in Parkinson's Disease?

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Dr. Rishabh Pathak

 


In Parkinson's disease, the neural network circuits involved in motor control are disrupted, leading to characteristic motor symptoms such as tremor, bradykinesia, and rigidity. The primary brain regions affected in Parkinson's disease include the basal ganglia and the cortex. Here is an overview of how neural network circuits work in Parkinson's disease:

1.     Basal Ganglia Dysfunction: The basal ganglia are a group of subcortical nuclei involved in motor control. In Parkinson's disease, there is a loss of dopamine-producing neurons in the substantia nigra, leading to decreased dopamine levels in the basal ganglia. This dopamine depletion results in abnormal signaling within the basal ganglia circuitry, leading to motor symptoms.

2.     Cortical Involvement: The cortex, particularly the motor cortex, plays a crucial role in initiating and coordinating voluntary movements. In Parkinson's disease, abnormal activity in the cortex, especially in the beta and gamma frequency bands, is observed and is associated with motor symptoms.

3.     Disrupted Neural Circuits: The communication between the basal ganglia, cortex, and other brain regions is disrupted in Parkinson's disease. This disruption leads to difficulties in initiating and controlling movements, resulting in the characteristic motor symptoms of the disease.

4.     Deep Brain Stimulation (DBS): Deep brain stimulation is a therapeutic approach that involves the implantation of electrodes in specific brain regions, such as the subthalamic nucleus (STN) or globus pallidus, to modulate neural activity and alleviate motor symptoms in Parkinson's disease. DBS works by delivering electrical impulses to targeted brain regions to normalize neural activity and improve motor function.

5.     Research Advances: Recent research has focused on decoding neural activity patterns associated with specific motor symptoms in Parkinson's disease. By understanding the neurophysiological fingerprints of tremor and bradykinesia, researchers aim to develop more targeted and personalized treatment strategies, such as closed-loop DBS paradigms that can adapt stimulation parameters based on real-time neural signals.

By studying the neural network circuits involved in Parkinson's disease and developing innovative treatment approaches, researchers aim to improve the management of motor symptoms and enhance the quality of life for individuals living with Parkinson's disease.

 

Lauro, P. M., Lee, S., Amaya, D. E., Liu, D. D., Akbar, U., & Asaad, W. F. (2023). Concurrent decoding of distinct neurophysiological fingerprints of tremor and bradykinesia in Parkinson’s disease. eLife, 12, e84135. https://doi.org/10.7554/eLife.84135

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