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...
Functional Magnetic Resonance Imaging (fMRI) is a non-invasive neuroimaging technique that measures brain activity by detecting changes in blood flow and oxygen levels in response to neural activity. fMRI is widely used in neuroscience and cognitive psychology to study brain function and connectivity during various tasks, behaviors, and resting states. Key features of fMRI include: 1. Principle of fMRI : o fMRI is based on the principle that changes in neural activity are accompanied by changes in blood flow and oxygenation levels in the brain. o When a specific brain region becomes active, it requires more oxygenated blood to support the increased metabolic demands of neural activity. o The fMRI scanner detects these changes in blood oxygen level-dependent (BOLD) signals, providing a measure of brain activity in different regions. 2. Task-Based fMRI : o ...