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Upcoming Events

  • Photo of Peter Dayan

    Quest | CBMM Seminar Series - Peter Dayan

    Date: November 14, 2023| 4pm EST
    Location: Singleton Auditorium, Building 46
    Peter Dayan’s research focuses on decision-making processes in the brain, the role of neuromodulators as well as neuronal malfunctions in psychiatric diseases. Dayan has long worked at the interface between natural and engineered systems for learning and choice, and is also regarded as a pioneer in the field of Artificial Intelligence.
  • Photo of Daniel Wolpert

    Quest | CBMM Seminar Series - Daniel Wolpert

    Date: December 5 2023 | 4pm EST
    Location: Singleton Auditorium, Building 46
    Daniel Wolpert FMedSci FRS. Daniel qualified as a medical doctor in 1989. He worked with John Stein and Chris Miall in the Physiology Department of Oxford University where he received his D.Phil. in 1992. He worked as a postdoctoral fellow in the Department of Brain and Cognitive Sciences at MIT in Mike Jordan's group and in 1995 joined the Sobell Department of Motor Neuroscience, Institute of Neurology as a Lecturer. In 2005 moved to the University of Cambridge where he was Professor of Engineering (1875) and a fellow of Trinity College and from 2013 the Royal Society Noreen Murray Research Professorship in Neurobiology. In 2018 Daniel joined the Zuckerman Mind Brain and Behavior Institute at Columbia University as Professor of Neuroscience and is vice-chair of the Department of Neuroscience. Daniel retains a part-time position as Director of Research at the Department of Engineering, University of Cambridge.
  • Photo of Yael Niv

    Quest | CBMM Seminar Series - Yael Niv

    Date: February 6, 2024 | 4pm EST
    Location: Singleton Auditorium, Building 46
    Research in the Niv lab focuses on the neural and computational processes underlying reinforcement learning and decision-making. We study the ongoing day-to-day processes by which animals and humans learn from trial and error, without explicit instructions, to predict future events and to act upon the environment so as to maximize reward and minimize punishment. In particular, we are interested in how attention and memory processes interact with reinforcement learning to create representations that allow us to learn to solve new tasks so efficiently.
  • photo of Tom Griffiths

    Quest | CBMM Seminar Series - Tom Griffiths

    Date: March 12, 2024 | 4pm EST
    Location: Singleton Auditorium, Building 46
    Tom Griffiths is interested in developing mathematical models of higher level cognition, and understanding the formal principles that underlie our ability to solve the computational problems we face in everyday life. His current focus is on inductive problems, such as probabilistic reasoning, learning causal relationships, acquiring and using language, and inferring the structure of categories. Griffiths tries to analyze these aspects of human cognition by comparing human behavior to optimal or "rational" solutions to the underlying computational problems. For inductive problems, this usually means exploring how ideas from artificial intelligence, machine learning, and statistics (particularly Bayesian statistics) connect to human cognition. These interests sometimes lead him into other areas of research such as nonparametric Bayesian statistics and formal models of cultural evolution.
  • photo of Melanie Mitchel

    Quest | CBMM Seminar Series - Melanie Mitchel

    Date: April 2, 2024 | 4pm EST
    Location: Singleton Auditorium, Building 46
    Melanie Mitchell is a Professor at the Santa Fe Institute. Her current research focuses on conceptual abstraction, analogy-making, and visual recognition in artificial intelligence systems. Melanie is the author or editor of six books and numerous scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems. Her book Complexity: A Guided Tour (Oxford University Press) won the 2010 Phi Beta Kappa Science Book Award and was named by as one of the ten best science books of 2009. Her latest book is Artificial Intelligence: A Guide for Thinking Humans (Farrar, Straus, and Giroux).
  • photo of Bruno Olshausen

    Quest | CBMM Seminar Series - Bruno Olshausen

    Date: May 7, 2024 | 4pm EST
    Location: Singleton Auditorium, Building 46
    Olshausen's research focuses on understanding the information processing strategies employed by the visual system for tasks such as object recognition and scene analysis. Computer scientists have long sought to emulate the abilities of the visual system in digital computers, but achieving performance anywhere close to that exhibited by biological vision systems has proven elusive. Dr. Olshausen's approach is based on studying the response properties of neurons in the brain and attempting to construct mathematical models that can describe what neurons are doing in terms of a functional theory of vision. The aim of this work is not only to advance our understanding of the brain but also to devise new algorithms for image analysis and recognition based on how brains work.

Past Events

  • photo of Mike Hasselmo

    Quest | CBMM Seminar Series - Mike Hasselmo

    Date: September 12, 2023 | 4pm EST
    Location: Singleton Auditorium, Building 46
    Recordings of neurons in cortical structures in behaving rodents show responses to dimensions of space and time relevant to encoding and retrieval of spatiotemporal trajectories of behavior in episodic memory. This includes the coding of spatial location by grid cells in entorhinal cortex and place cells in hippocampus, some of which also fire as time cells when a rodent runs on a treadmill (Kraus et al., 2013; 2015; Mau et al., 2018). Trajectory encoding also includes coding of the direction and speed of movement. Speed is coded by both firing rate and frequency of neuronal rhythmicity (Hinman et al., 2016, Dannenberg et al., 2020), and inactivation of input from the medial septum impairs the spatial selectivity of grid cells suggesting rhythmic coding of running speed is important for spatial coding by grid cells (Brandon et al., 2011; Robinson et al., 2023).
  • Photo of Dan Yamins

    Quest | CBMM Seminar Series - Dan Yamins

    Date: May 18, 2023 | 2:00PM EST
    Location: Singleton Auditorium, Building 46
    The emerging field of NeuroAI has leveraged techniques from artificial intelligence to model brain data. In this talk, Yamins will show that the connection between neuroscience and AI can be fruitful in both directions. Towards "AI driving neuroscience", he will discuss a new candidate universal principal for functional organization in the brain, based on recent advances in self-supervised learning, that explains both fine details as well as large-scale organizational structure in the vision system, and perhaps beyond.  In the direction of "neuroscience guiding AI", Yamins will present a novel cognitively-grounded computational theory of perception that generates robust new learning algorithms for real-world scene understanding.  Taken together, these ideas illustrate how neural networks optimized to solve cognitively-informed tasks provide a unified framework for both understanding the brain and improving AI.
  • photo of Eero Simoncelli

    Quest | CBMM Seminar Series - Eero Simoncelli

    Date: May 9, 2023, 4pm
    Location: Singleton Auditorium, Building 46
    Generally, inference problems in machine or biological vision rely on knowledge of prior probabilities. Recently, machine learning has resulted in dramatic improvements by using artificial neural networks. These prior probabilities are implicit and intertwined with the tasks for which they are optimized.