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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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Clinical Significance of Mittens

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Dr. Rishabh Pathak

The clinical significance of mittens in EEG recordings has evolved over time. Here are the key points regarding their clinical relevance:

1. Normal Variants

    • Current Understanding: Mittens are now considered normal variants in EEG patterns, particularly in adults. They are typically benign and do not indicate any underlying pathology when observed in the context of normal sleep.

2. Historical Context

    • Previous Associations: Historically, mittens were believed to be markers of various neurological and psychiatric conditions, including thalamic tumors, epilepsy, parkinsonism, eating disorders, mood disorders, and psychosis. Early EEG research suggested correlations between the morphology of the mitten pattern and these conditions.

3. Misinterpretation Risks

    • Potential for Misdiagnosis: There is a risk of misinterpreting the mitten pattern as epileptiform activity, which could lead to incorrect diagnoses. This highlights the importance of distinguishing mittens from pathological findings such as interictal epileptiform discharges (IEDs).

4. Research Limitations

    • Methodological Concerns: The earlier associations of mittens with various clinical conditions may have been influenced by methodological issues in research, such as small sample sizes, lack of control groups, and changes in diagnostic criteria over time. Modern approaches have not replicated these interpretations, reinforcing the view of mittens as benign.

5. Recognition and Distinction

    • Importance in Clinical Practice: The primary clinical significance of mittens today lies in their recognition and the ability to distinguish them from epileptiform abnormalities. Accurate identification helps prevent misdiagnosis and ensures appropriate clinical management.

Summary

Mittens are now recognized as normal EEG variants, primarily associated with NREM sleep. While they were once thought to indicate various neurological and psychiatric disorders, current understanding emphasizes their benign nature and the importance of distinguishing them from pathological patterns to avoid misdiagnosis.

 

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