A Computational Cognitive and Visual Neuroscience Laboratory
PI: David J. Freedman, Ph.D.
Through experience, we learn to interpret the sights and sounds around us and to make decisions that move us closer to achieving our goals. Our ability to learn from and adapt to our ever changing environment is a foundation of complex behavior, as it allows us to make sense of incoming sensory stimuli and to plan successful actions. To study these questions, our laboratory uses advanced neurophysiological and behavioral techniques, in parallel with machine learning approaches for studying cognitive computations in artificial neural networks. Together, our work is providing insights into the brain mechanisms of visual learning, recognition and decision making.Learn more
Nick Masse’s new paper on mechanisms of activity-silent working memory is in press at Nature Neuroscience!
Congrats to postdoc Christopher Hauser on a fantastic score on his Kirschstein NRSA proposal
Our new paper from Nick Masse and Greg Grant in press at PNAS, revealing a novel strategy for alleviating catastrophic forgetting in artificial neural networks.
FreedmanLab alum Guilhem Ibos named CNRS Faculty at Institut de Neurosciences de la Timone
David Freedman named a Vannevar Bush Faculty Fellow by the USA Department of Defense
A review with Guilhem Ibos in Neuron on spatial and cognitive functions of parietal cortex
Congrats to graduate student Jeff Johnston on his predoctoral Kirschstein NRSA!