Theoretical Neuroscience Podcast On low-dimensional manifolds in motor cortex - with Sara Solla - #36
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Jan 3, 2026 Sara Solla, a theoretical neuroscientist with a physics background, shares her journey from neural networks to pioneering manifold analyses of motor cortex activity. She explains how modern multi-electrode technology allows for population-level insights, revealing low-dimensional structures in motor tasks. Solla discusses the implications of these findings for brain-machine interfaces and how structured sensory inputs contribute to low-dimensional coding. Her experiences at Bell Labs and collaborations with notable figures add depth to the conversation, making complex concepts accessible.
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Low-Dimensional Manifolds Describe Motor Cortex
- Motor cortex population activity often lies on a low-dimensional manifold, sometimes as small as three dimensions.
- These latent variables capture coordinated patterns across many neurons and simplify comparing sessions and subjects.
Hopfield Talk Sparked A Career Shift
- A John Hopfield talk at a physics meeting inspired Sara Solla to switch toward neural networks research.
- That led her to IBM and to work on simulated annealing and networks at Bell Labs.
Origins Of 'Optimal Brain Damage' Pruning
- Sara Solla, Jan LeCun and John Denker developed the Optimal Brain Damage pruning idea in 1989.
- The method prunes weights by saliency (second derivative times weight squared) and became influential decades later.
