NEWS: We’ve moved! Starting summer 2023, we are now at Dartmouth College, in the Department of Psychological and Brain Sciences.
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
- 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 faculty. 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!