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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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Patterns of Change in White Mater

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Dr. Rishabh Pathak

White matter undergoes significant changes throughout development, reflecting the maturation and refinement of neural connections in the brain. Here are some key patterns of change in white matter:


1.  Increase in White Matter Volume: During early development, there is a rapid increase in white matter volume, reflecting the growth of myelinated axons and the establishment of neural pathways. This period of white matter expansion is crucial for enhancing connectivity between different brain regions.


2.   Myelination: Myelination, the process of insulating axons with myelin sheaths, continues throughout childhood and adolescence, leading to increased white matter integrity and faster neural transmission. Myelination enhances the efficiency of neural communication and supports cognitive functions.


3.     Pruning and Refinement: As the brain matures, there is a process of pruning and refinement in white matter connectivity. Unused or inefficient neural connections are eliminated, while stronger connections are reinforced through synaptic pruning and plasticity. This selective pruning optimizes neural networks for efficient information processing.


4.     Frontal Lobe Development: White matter changes in the frontal lobes, including the prefrontal cortex, are particularly pronounced during adolescence and early adulthood. The maturation of white matter tracts in the frontal lobes is associated with the development of executive functions, cognitive control, and decision-making abilities.


5.     Long-Distance Connections: White matter pathways that facilitate long-distance communication between brain regions show continued development and specialization across the lifespan. These long-range connections support complex cognitive processes, such as language, spatial reasoning, and social cognition.


6.  Age-Related Changes: While white matter volume generally increases during childhood and adolescence, there may be age-related declines in white matter integrity in older adulthood. Factors such as vascular health, inflammation, and neurodegenerative processes can contribute to white matter changes in aging brains.


Understanding the patterns of change in white matter provides insights into the dynamic nature of brain development and the role of white matter in supporting cognitive functions and neural communication. The maturation and plasticity of white matter pathways contribute to the structural foundation of the brain and underlie the complex network of connections that enable diverse cognitive abilities.

 

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