Leigh Hochberg — accepted AI-conference papers

2024

Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark

Brianna M. Karpowicz, Joel Ye, Chaofei Fan, Pablo Tostado-Marcos, Fabio Rizzoglio, Clayton B Washington +16

NeurIPS 2024poster

Intracortical brain-computer interfaces (iBCIs) can restore movement and communication abilities to individuals with paralysis by decoding their intended behavior from neural activity recorded with an implanted device. While this activity yields high-performance decoding over short timescales, neura…

Cited by 1 Source ↗PDF ↗code ↗Scholar ↗

2023

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

Chaofei Fan, Nick Hahn, Foram Kamdar, Donald Avansino, Guy H Wilson, Leigh Hochberg +3

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…

Cited by 22 Source ↗PDF ↗code ↗Scholar ↗

2017

Multiscale Semi-Markov Dynamics for Intracortical Brain-Computer Interfaces

Daniel Milstein, Jason Pacheco, Leigh Hochberg, John D Simeral, Beata Jarosiewicz, Erik Sudderth

NeurIPS 2017poster

Intracortical brain-computer interfaces (iBCIs) have allowed people with tetraplegia to control a computer cursor by imagining the movement of their paralyzed arm or hand. State-of-the-art decoders deployed in human iBCIs are derived from a Kalman filter that assumes Markov dynamics on the angle of…

Cited by 9 Source ↗PDF ↗Scholar ↗