Timothy J. Buschman

This study shows that mice and artificial neural networks reuse modular neuronal subspaces to perform complex cognitive tasks.

This study shows that Shank3 mutations disrupt cortex-wide dynamics, leading to impaired motor planning in mice.

The paper shows that motivational states modulate attractor dynamics in the medial prefrontal cortex during working memory tasks, revealing how internal states control neural dynamics and cognitive function.

This paper shows that human ventrolateral prefrontal cortex (VLPFC) develops distinct category-selective representations that undergo prolonged, hemisphere-specific refinement, unlike ventral temporal cortex which shows early, stable organization.

This study shows that the brain uses shared neural subspaces to flexibly perform and combine multiple tasks by reusing representations across different task-related information.

The paper shows that working memory readout in the frontal eye field varies with theta rhythm phases, linked to performance in a visual memory task.

The paper identifies multiplexed subspace networks in the brain that allow regions to interact with multiple networks simultaneously, supporting cognitive flexibility.

This study identifies the neural mechanisms of swap errors in working memory by analyzing neural population recordings in monkeys performing multi-stimulus tasks.

This study investigates how the brain learns and uses attentional templates in decision-making tasks, showing that templates are represented in prefrontal and parietal cortex and transform stimuli into value representations.

The paper investigates how monkeys switch between learned rules and continuously update them during a perceptual categorization task, revealing distinct computational processes for rule switching and rule learning.

The paper analyzes spiking and LFP data from monkey prefrontal cortex to show task-related reductions in spike variability can co-exist with intermittent spiking.

The paper shows individual differences in behavior and functional connectivity are explained by variability in the sampling of cortex-wide neural dynamics.

The paper shows that sensory representations rotate in neural space to form independent memory representations, reducing interference with future sensory inputs in mice.

This study investigates how prefrontal cortex controls working memory by selecting and transforming memory representations in monkeys during task-switching.

The paper proposes spatial computing as a mechanism for WM control, finding low-dimensional spatial activity that encodes control-related information in prefrontal cortex.

This paper introduces an adaptive closed-loop stimulation system that learns to generate specific neural activity patterns in real-time.

The paper investigates how delay-period BOLD activity in frontal, parietal, and occipital cortex relates to attractor dynamics in visual working memory, finding that diffusion explains more variance in frontal and parietal activity, while drift explains more in occipital cortex.

The paper identifies low-dimensional spatio-temporal motifs that explain most variance in cortex-wide neural activity across different behavioral states in mice.

The paper investigates how working memory maintains stable mental states through dynamic neural activity, finding that while the coding scheme is stable, memories drift over time.

This study shows error-correcting attractor dynamics reduce noise effects in working memory by pulling memories toward stable representations in both humans and monkeys.

This paper introduces a flexible working memory model that maintains arbitrary inputs through random recurrent connections between structured and unstructured neural layers, but with limited memory capacity due to interference.

The paper shows that neurons with different intrinsic timescales contribute to distinct phases of working memory processing in primates.

The paper investigates how working memory load affects neuronal coupling in a primate brain network using a predictive coding model and cross-spectral density analysis.