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 history and development of Brain-Computer Interfaces (BCIs) span over fifty years, highlighting significant milestones that have shaped the field. Early Foundations (1920s - 1970s) 1. 1924 - First EEG Recording : Hans Berger was the first to record human brain activity using electroencephalography (EEG). His work led to the identification of brain wave patterns, such as alpha and beta waves, laying the groundwork for future BCI development. 2. 1930s - Electrocorticography Development : W. Penfield and Herbert Jasper pioneered the use of electrocorticography (ECoG) for detecting epileptic foci, introducing invasive techniques for measuring brain signals directly from the surface of the brain. 3. 1960s - Initial BCI Concepts : Research on direct brain control of external devices began to emerge, signaling the initial conceptual development of BCIs. Researchers started exploring how si...