Research in the lab, led by John D. Murray, is in computational neuroscience. Topics of interest include neural circuit dynamics; cognitive functions such as decision making and working memory; reinforcement learning; neuro-AI; and computational psychiatry. We develop modeling and data-analytic approaches, frequently in collaboration with experimentalists.
We’re affiliated with the NeuroNex Working Memory consortium; and the AI Institute for Artificial and Natural Intelligence (ARNI).
News
- Apr 2024: Jacob Miller has an accepted an assistant professor position at University of Miami. Congratulations, Jacob!
- Feb 2024: “On the stability of canonical correlation analysis and partial least squares with application to brain-behavior associations” has been published in Communications Biology. Congratulations, Markus!
- Oct 2023: Warren Pettine has joined University of Utah as an assistant professor. Congratulations, Warren!
- Sep 2023: Three researchers have joined the lab: Katerina Capouskova (postdoc), Eun Tack Cho (PhD student), and Cove Geary (PhD student). Welcome!
- Jul 2023: An NIH Conte center grant was awarded to study the role of slow brain network fluctuations in cognition.
- Jul 2023: The lab has moved to Dartmouth College. Some lab members remain at Yale.
- Apr 2023: “Functional brain networks reflect spatial and temporal autocorrelation” has been published in Nature Neuroscience. Congratulations, Max!
- Mar 2023: “Human latent-state generalization through prototype learning with discriminative attention” has been published in Nature Human Behavior. Congratulations, Warren!
- Jan 2023: Taku Ito has joined IBM Research. Congratulations, Taku!
- Dec 2022: “Multitask representations in the human cortex transform along a sensory-to-motor hierarchy” has been published in Nature Neuroscience. Congratulations, Taku!
- Oct 2022: The lab was awarded a SFARI Human Cognitive and Behavioral Science grant, in collaboration with Suma Jacob, to study latent-state learning and generalization in autism spectrum disorder.
- Sep 2022: “Geometry of neural computations unifies working memory and planning” has been published in PNAS. Congratulations, Daniel!