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...
Studying biomechanics is essential for several reasons, as it provides valuable insights into the mechanical aspects of living organisms, particularly the human body. Here are some key reasons why studying biomechanics is important: 1. Understanding Human Movement : Biomechanics helps us understand how the musculoskeletal system functions during various activities such as walking, running, jumping, and sports movements. By analyzing the forces, torques, and motions involved in human movement, researchers can gain insights into optimal performance, injury prevention, and rehabilitation strategies. 2. Injury Prevention and Rehabilitation : By studying biomechanics, researchers can identify risk factors for injuries, assess movement patterns that contribute to overuse injuries, and develop effective rehabilitation programs. Understanding the biomechanical mechanisms of injury can help in designing interventions to prevent injuries and p...