Aaron P. Batista

This study investigates how rare rewards affect performance and neural activity in rhesus monkeys during a color change detection task, finding detrimental changes in V4 population activity linked to perceptual choking.

The paper identifies distinct neural modes in the sensorimotor cortex that encode grasp force and timing during isometric grasps in tetraplegic individuals.

The paper shows that posture and goal information in motor cortex are organized in separate, orthogonal subspaces, with posture information being stable across tasks.

This study investigates how reward influences movement vigor through multiple mechanisms in motor cortical areas by analyzing neural activity in rhesus monkeys.

This study challenges monkeys to reverse natural neural activity time courses in motor cortex using a BCI, finding they cannot violate these time courses, supporting the idea that neural activity reflects network-level computations.

The paper trains an autoregressive Transformer on neural spiking data to decode motor behavior, showing broad utility across tasks but highlighting limitations in scaling.

The paper investigates how high rewards affect neural activity in Rhesus monkeys during a reaching task, finding that large rewards reduce neural information about movement plans.

This paper develops a theory explaining BCI learning through low-dimensional control strategies, validated with experimental data.

The paper shows that motor cortex maintains similar neural dynamics during motor execution and imagery by recreating missing components in a unique imagery subspace.

This paper infers control objectives from behavior in humans and monkeys using a generative model and behavioral signatures, validated through instructed tasks.

The paper shows that learning a new BCI map alters neural activity in a way that preserves performance on a familiar map, suggesting a mechanism for learning multiple motor behaviors without interference.

The paper investigates how internal states like arousal affect neural engagement during learning in non-human primates using a BCI paradigm, finding that abrupt changes in engagement influence learning speed for different task goals.