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...
The lateral prefrontal cortex (LPFC) plays a crucial role in various cognitive functions, particularly those related to executive control, working memory, decision-making, and goal-directed behavior. Here are key functions associated with the lateral prefrontal cortex: 1. Executive Functions : o The LPFC is central to executive functions, which encompass higher-order cognitive processes involved in goal setting, planning, problem-solving, cognitive flexibility, and inhibitory control. o It is responsible for coordinating and regulating other brain regions to support complex cognitive tasks, such as task switching, attentional control, and response inhibition, essential for adaptive behavior in changing environments. 2. Working Memory : o The LPFC is critical for working memory processes, which involve the temporary storage and manipulation of information to guide behavior and decis...