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Unveiling Hidden Neural Codes: SIMPL – A Scalable and Fast Approach for Optimizing Latent Variables and Tuning Curves in Neural Population Data

Dr. Rishabh Pathak
This research paper presents SIMPL (Scalable Iterative Maximization of Population-coded Latents), a novel, computationally efficient algorithm designed to refine the estimation of latent variables and tuning curves from neural population activity. Latent variables in neural data represent essential low-dimensional quantities encoding behavioral or cognitive states, which neuroscientists seek to identify to understand brain computations better. Background and Motivation Traditional approaches commonly assume the observed behavioral variable as the latent neural code. However, this assumption can lead to inaccuracies because neural activity sometimes encodes internal cognitive states differing subtly from observable behavior (e.g., anticipation, mental simulation). Existing latent variable models face challenges such as high computational cost, poor scalability to large datasets, limited expressiveness of tuning models, or difficulties interpreting complex neural network-based functio...
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How do cortical thickness, stiffness, and growth play a role in the folding process of the brain?

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Dr. Rishabh Pathak

Cortical thickness, stiffness, and growth are key factors that play crucial roles in the folding process of the brain. Here is an explanation of how each of these factors influences cortical folding:


1.  Cortical Thickness: The thickness of the cortex, the outer layer of the brain, directly influences the folding patterns of the brain surface. Thicker cortices tend to have longer intersulcal distances and may even suppress the formation of folds entirely. On the other hand, thinner cortices are associated with increased gyrification and the formation of more convoluted brain surfaces with smaller folds. Variations in cortical thickness can lead to different folding patterns and impact the overall morphology of the brain.


2.   Stiffness: The stiffness of the cortical tissue compared to the subcortical tissue also plays a significant role in cortical folding. The stiffness ratio between the cortex and subcortex influences the surface morphology of the brain. While the cortex is expected to be denser and have a higher mechanical stiffness due to the presence of neuronal cell bodies and synapses, the actual stiffness difference between the cortex and subcortex is relatively small. This stiffness ratio can affect the folding patterns, but it is not the sole driving force behind cortical folding.


3. Growth: Growth-induced processes in the brain, such as differential growth between the cortex and subcortex, can lead to the development of cortical folds. Abnormal growth rates can result in different behaviors of the brain tissue. Slow cortical growth can lead to a more fluid-like behavior in the subcortex, potentially suppressing folding, while fast cortical growth can create elastic solid-like behavior, provoking the formation of secondary folds. The growth ratio between the cortex and subcortex is a critical parameter in controlling irregular surface morphologies and secondary folding in the brain.


In summary, cortical thickness, stiffness, and growth are interconnected factors that influence the folding process of the brain. Understanding how these parameters interact and affect brain development is essential for unraveling the mechanisms behind cortical folding and associated neurological conditions.

 

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