About

Timothy Buschman is a Professor affiliated with the Princeton Neuroscience Institute at Princeton University. His research centers on understanding how the brain accomplishes executive control, which is the ability to internally guide actions toward a goal. His laboratory investigates the roles of key brain regions involved in executive control, specifically the prefrontal cortex, parietal cortex, and basal ganglia, and how their interactions give rise to complex, cognitive behaviors. The research employs a multidisciplinary approach, utilizing behavioral tasks designed to isolate cognitive functions, combined with large-scale electrophysiology and optogenetic techniques in non-human primate and rodent models. This allows for the recording and manipulation of neural circuits at the network and cell-type levels, providing insights into the fundamental mechanisms underlying cognition. His work aims to deepen understanding of these processes and explore their disruption in neuropsychiatric and neurodegenerative diseases such as autism, schizophrenia, and Parkinson's disease.

Research topics

• Psychology
• Neuroscience
• Computer Science
• Cognitive psychology
• Acoustics
• Computational biology
• Evolutionary biology
• Cognitive science
• Genetics
• Physics
• Biology
• Telecommunications
• Statistics
• Communication

Selected publications

• Shared mechanisms underlie the control of working memory and attention

  Nature · 2021 · 411 citations

  Senior authorCorresponding
  • Psychology
  • Cognitive psychology
  • Neuroscience
  DOI

• Is Activity Silent Working Memory Simply Episodic Memory?

  Trends in Cognitive Sciences · 2021 · 98 citations

  • Psychology
  • Cognitive psychology
  • Cognitive science
  DOI

• Rotational dynamics reduce interference between sensory and memory representations

  Nature Neuroscience · 2021 · 222 citations

  Senior authorCorresponding
  • Computer Science
  • Neuroscience
  • Psychology
  DOI

• Drifting codes within a stable coding scheme for working memory

  PLoS Biology · 2020 · 113 citations

  • Biology
  • Computational biology
  • Genetics

  Working memory (WM) is important to maintain information over short time periods to provide some stability in a constantly changing environment. However, brain activity is inherently dynamic, raising a challenge for maintaining stable mental states. To investigate the relationship between WM stability and neural dynamics, we used electroencephalography to measure the neural response to impulse stimuli during a WM delay. Multivariate pattern analysis revealed representations were both stable and dynamic: there was a clear difference in neural states between time-specific impulse responses, reflecting dynamic changes, yet the coding scheme for memorised orientations was stable. This suggests that a stable subcomponent in WM enables stable maintenance within a dynamic system. A stable coding scheme simplifies readout for WM-guided behaviour, whereas the low-dimensional dynamic component could provide additional temporal information. Despite having a stable subspace, WM is clearly not perfect-memory performance still degrades over time. Indeed, we find that even within the stable coding scheme, memories drift during maintenance. When averaged across trials, such drift contributes to the width of the error distribution.

  DOI

Recent grants

• Understanding the Network Mechanisms that Control Working Memory

  NIH · $546k · 2018–2020

• Developing an Adaptive Cognitive Prosthetic to Replace Damaged Brain Regions

  NIH · $2.4M · 2014–2019

• Understanding the Neural Mechanisms Controlling Brain-wide Dynamics

  NIH · $2.0M · 2022–2026

• Controlling Interareal Gamma Coherence by Optogenetics, Pharmacology and Behavior

  NIH · $750k · 2013–2017

• Understanding the Network Mechanisms that Control Working Memory

  NIH · $1.8M · 2019–2024

Frequent coauthors

• Earl K. Miller

  54 shared

• Camden J. MacDowell

  Johnson University

  26 shared

• Matthew F. Panichello

  Stanford University

  24 shared

• Jonas Rose

  Ruhr University Bochum

  13 shared

• Dimitris A. Pinotsis

  City, University of London

  12 shared

• Markus Siegel

  University of Tübingen

  11 shared

• Mark G. Stokes

  Mansfield University

  9 shared

• Mikael Lundqvist

  Karolinska Institutet

  8 shared

Labs

• Buschman LabPI

Education

• Ph.D., Brain and Cognitive Science

  Massachusetts Institute of Technology

  2008

• BSc, Biology

  California Institute of Technology

  2001

Awards & honors

• 2023 Troland Research Award

Similar researchers at Princeton University

• Jonathan Cohenh-162
• Michael Straussh-149
• Thomas E. Shenkh-136
• Michael Levineh-131
• Romain Teyssierh-130