Introduction: Language impairments often result from severe neurological disorders, driving the development of neural prosthetics utilizing electrophysiological signals to restore comprehensible ...

Average decoding scores for modality-agnostic decoders (green), compared to modality-specific decoders trained on data from subjects viewing images (orange) or on data from subjects viewing captions ...

Although large language models (LLMs) such as GPT-4 and LLaMA are rapidly reimagining modern-day applications, their inference is slow and difficult to optimize because it is based on autoregressive ...

Panel A: Setup of the main fMRI experiment. Subjects were seeing images and captions in random alternation. Whenever the current stimulus matched the previous stimulus, the subjects were instructed to ...

Our ECoG to Speech decoding framework is initially described in A Neural Speech Decoding Framework Leveraging Deep Learning and Speech Synthesis. We present a novel deep learning-based neural speech ...

A collection of practical AI engineering examples, demos, and proof-of-concepts for modern AI applications. This repository serves as a playground for experimenting with cutting-edge AI techniques and ...