Multi-resource-cost Optimization for Neural Networks Models Working Group (NNMS)
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: Scope of the working group, example project, and literature Short Description: From Nikolaus Kriegeskorte's (Professor of Psychology and of Neuroscience (in the Mortimer B. Zuckerman Mind Brain Behavior Institute) lab, Eivinas Butkus (grad student) will show an example of a modeling project optimizing energetic demands along with accuracy in a vision task, and Josh…
CTN: Wei Ji Ma
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: Efficient coding in reward neurons Abstract: Two of the greatest triumphs of computational neuroscience have been efficient coding accounts of tuning properties of sensory neurons and reinforcement learning accounts of dopaminergic neurons in the midbrain. At first glance, these theories seem to have no connection, but I will argue that they do. One can…
CTN: Quentin Huys (Seminar Speaker)
To Be DeterminedTitle: Translating computational mechanisms to clinical applications Computational psychiatry is a rapidly growing field attempting to translate advances in computational neuroscience and machine learning into improved outcomes for patients suffering from mental illness. In this lecture, I will provide an overview over recent approaches for translating computational research into an understanding of symptoms, and mechanisms…
CTN: Guillaume Hennequin
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: A recurrent network model of planning explains hippocampal replay and human behaviour Abstract: When faced with a novel situation, humans often spend substantial periods of time contemplating possible futures. For such planning to be rational, the benefits to behaviour must compensate for the time spent thinking. I will show how we recently captured these features…
Canceled CTN: Bob Datta
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle and Abstract: TBD
CTN: Stefano Fusi
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: The Geometry of Abstraction Abstract: I'll first discuss the theoretical framework introduced in Bernardi et al. 2020, Cell, in which we propose a possible definition of abstract representations. I'll go into the details of the most up-to-date conceptual framework, discuss the computational relevance of the representational geometry and the cross-validated measures of representational geometry that we…
CTN: Peter Dayan
Jerome L. Greene Science Center 3227 Broadway 9th FL Lecture Hall, New York, NY, United StatesTitle: Risking your Tail: Curiosity, Danger & Exploration Abstract: Risk and reward are critical balancing determinants of adaptive behaviour, associated respectively with neophobia and neophilia in the case of exploration. There are rather great differences in how individuals engage with novelty - with substantial consequences for what they are able to learn. Here, we consider…
Zuckerman Institute Demo Day
Lightning AI 50 West 23 Street 7th FL, New York, NY, United StatesDr. Richard Lange
Zuckerman Institute - L3-079 3227 Broadway, New York, NY, United StatesTitle: "What Bayes can and cannot tell us about the neuroscience of vision" Nikolaus Kriegeskorte's Group is hosting Dr.Richard Lange, Assistant Professor in the Department of Computer Science at Rochester Institute of Technology. He will be giving a talk at Zuckerman Institute.
Continual Learning Working Group Talk
CEPSR 620 Schapiro 530 W. 120th StTitle: Continual learning, machine self-reference, and the problem of problem-awareness Abstract: Continual learning (CL) without forgetting has been a long-standing problem in machine learning with neural networks. Here I will bring a new perspective by looking at learning algorithms (LAs) as memory mechanisms with their own decision making problem. I will present a natural solution to CL…
CTN Claudia Clopath
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: Feedback-based motor control can guide plasticity and drive rapid learning Abstract: Animals use afferent feedback to rapidly correct ongoing movements in the presence of a perturbation. Repeated exposure to a predictable perturbation leads to behavioural adaptation that counteracts its effects. Primary motor cortex (M1) is intimately involved in both processes, integrating inputs from various sensorimotor brain…
CTN: Sebastian Seung
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: Insights into vision from interpreting a neuronal wiring diagram Host: Marcus Triplett Abstract: In 2023, the FlyWire Consortium released the neuronal wiring diagram of an adult fly brain. This contains as a corollary the first complete wiring diagram of a visual system, which has been used to identify all 200+ cell types that are intrinsic to the…