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...
Epileptiform bursts are a specific EEG pattern characterized by a series of rapid, repetitive spikes or sharp waves that indicate abnormal electrical activity in the brain, typically associated with seizure activity. 1. Definition : o Epileptiform bursts consist of brief, high-frequency discharges that can appear as spikes or sharp waves. These bursts are indicative of underlying epileptic activity and can occur in various seizure types. 2. EEG Characteristics : o The bursts are often more monomorphic and stereotyped compared to non-epileptic bursts, exhibiting greater rhythmicity, especially in the faster frequency ranges. This distinct waveform helps differentiate them from other types of EEG activity, such as those seen in non-epileptic conditions. o Epileptiform bursts can vary in duration and frequency, and they may evolve into more complex patterns, such as ge...