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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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Epileptic recruiting rhythm

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Dr. Rishabh Pathak


 

The term "epileptic recruiting rhythm" refers to a specific pattern observed in the electroencephalogram (EEG) during certain types of seizures, particularly focal seizures.

1.      Definition:

o    An epileptic recruiting rhythm is characterized by a progressive increase in amplitude and frequency of rhythmic activity observed in the EEG during a seizure. This pattern typically indicates the recruitment of additional cortical areas as the seizure evolves.

2.     EEG Characteristics:

o    The recruiting rhythm often starts with a focal onset and may evolve into a more generalized pattern. The evolution of the rhythm is a key feature that helps in identifying the ictal activity. The rhythm can include repetitive sharp waves or spikes that become more pronounced as the seizure progresses.

3.     Clinical Significance:

o    The presence of an epileptic recruiting rhythm can provide important information regarding the seizure's onset zone and its propagation. It may indicate the extent of cortical involvement and help differentiate between focal and generalized seizures.

4.    Associated Seizure Types:

o    This pattern is commonly seen in focal-onset seizures, particularly those that may generalize. It can also be observed in other types of seizures where there is a clear progression of ictal activity.

5.     Diagnosis and Management:

o    Recognizing an epileptic recruiting rhythm during EEG monitoring is crucial for the accurate diagnosis of epilepsy and for planning appropriate treatment strategies. It can guide clinicians in determining the most effective antiepileptic medications or the need for surgical intervention in refractory cases.

6.    Prognosis:

o    The presence of an epileptic recruiting rhythm can influence the prognosis of seizure control. Understanding the dynamics of this rhythm can help in tailoring treatment approaches to improve outcomes for patients with epilepsy.

In summary, the epileptic recruiting rhythm is an important EEG pattern that reflects the dynamic nature of seizure activity, providing insights into the seizure's onset and propagation. Recognizing this pattern is essential for accurate diagnosis and effective management of epilepsy.

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