Yueming Wang

This paper introduces HABITS, an autonomous system for mouse behavior testing that optimizes cognitive paradigms through machine-teaching algorithms, resulting in more efficient training and novel behavioral outcomes.

The paper uses Utah array recordings to show that the human motor cortex encodes handwriting through a sequence of primitive neural states, improving trajectory reconstruction accuracy by 84%.

The paper separates behaviorally-relevant from irrelevant neural signals in motor cortex, revealing complex encoding and simple linear decoding mechanisms.

The paper proposes a multi-domain EEG analysis method using ResNet50 to detect acute cocaine and methamphetamine abuse in mice, achieving an F1-score of 95.10%.