Title: Neural basis for skilled movements Abstract: Generating behavior is an incredible achievement of the nervous system, considering the range of possible actions and the complexity of musculoskeletal arrangements. Motor control involves understanding the surrounding environment, selecting appropriate plans, converting those plans into motor commands, and adaptively reacting to feedback. This seminar will review efforts…

Title: 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…

Title: 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…

Title: 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…

Title: 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…

Title: 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…

Title: 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…

Title: "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.

Title: 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…