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Krishna V. Shenoy

4 accepted papers

2023

Plug-and-Play Stability for Intracortical Brain-Computer Interfaces: A One-Year Demonstration of Seamless Brain-to-Text Communication

NeurIPS 2023spotlight

Intracortical brain-computer interfaces (iBCIs) have shown promise for restoring rapid communication to people with neurological disorders such as amyotrophic lateral sclerosis (ALS). However, to maintain high performance over time, iBCIs typically need frequent recalibration to combat changes in t…

2021

Neural Latents Benchmark ‘21: Evaluating latent variable models of neural population activity

NeurIPS 2021poster

Advances in neural recording present increasing opportunities to study neural activity in unprecedented detail. Latent variable models (LVMs) are promising tools for analyzing this rich activity across diverse neural systems and behaviors, as LVMs do not depend on known relationships between the act…

Cited by 98SourcecodeScholar
2020

Organizing recurrent network dynamics by task-computation to enable continual learning

NeurIPS 2020poster

Biological systems face dynamic environments that require continual learning. It is not well understood how these systems balance the tension between flexibility for learning and robustness for memory of previous behaviors. Continual learning without catastrophic interference also remains a challeng…

Cited by 93SourcePDFScholar
2015

High-dimensional neural spike train analysis with generalized count linear dynamical systems

NeurIPS 2015spotlight

Latent factor models have been widely used to analyze simultaneous recordings of spike trains from large, heterogeneous neural populations. These models assume the signal of interest in the population is a low-dimensional latent intensity that evolves over time, which is observed in high dimension…