May 2025 - Comp-neuro - lists.cnsorg.org

Brains in Space - 20.05.25 - Thomas Wolbers (DZNE Magdeburg)

by Vinita Samarasinghe

It is time for *Brains in Space* again! This semester we invite you to talks by: Thomas Wolbers (DZNE Magdeburg), James McLaren (Universität Oldenburg), Xiangshuai Zeng (Ruhr University Bochum), and Lukas Kunz (Universität Bonn). The colloquium takes place virtually on Tuesday's from 16:00 to 17:30 (CEST) and the complete schedule can be found at https://www.ini.rub.de/teaching/courses/colloquium_brains_in_space_an_inter…. The first talk is on May 20th 2025 and is open to the public. Please feel free to forward this information to any of your colleagues who may be interested. May 20th: *Thomas Wolbers* - DZNE Magdeburg *Title:* Mechanisms of Navigational decline in human ageing Zoom link: https://ruhr-uni-bochum.zoom-x.de/j/67839364827?pwd=RfcIgK8OUfjkwWTNCf80ARX… [Meeting ID: 678 3936 4827; Passcode: 841644] We look forward to seeing you. Kind regards, Vinita -- Best, Vinita Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience <https://rub.de/cns> Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/73 Postfachnummer 110 Universitätstr. 150 44801 Bochum Tel: +49 (0)234 32 27996 Mobile: +49 (0)1512 7278698 Email: samarasinghe(a)ini.rub.de

May 6, 2025

World wide VVTNS series (fifth season): Wednesday, May 7, 2025, at 11:00 am EDT| Mark van Rossum, University of Nottingham

by David Hansel

[image: VVTNS.png] https://www.wwtns.online <https://streaklinks.com/A9c7PbbpKY7PxB6PaAJWGD3-/https%3A%2F%2Fwww.wwtns.on…> - on twitter: wwtns@TheoreticalWide You are cordially invited to the lecture Mark van Rossum University of Nottingham Energy efficient learning in neural networks The lecture will be held on zoom on Wednesday, May 7, 2025, at *11:00 am EDT * To receive the link: https://www.wwtns.online/register-page *Abstract: *The brain is one of the most energy intense organs. Some of this energy is used for neural information processing, however, fruitfly experiments have shown that also learning is metabolically costly. We will present estimates of this cost and introduce a general model of this cost, and compare it to costs in computers. Next, we turn to a supervised artificial network setting and explore a number of strategies that can save energy needed for plasticity. Either by modifying the objective function, by restricting plasticity, or by using less costly transient forms of plasticity. Finally, we will discuss adaptive strategies and possible relevance for biological learning. *About VVTNS : Launched as the World Wide Theoretical Neuroscience Seminar (WWTNS) in November 2020 and renamed in homage to Carl van Vreeswijk in Memoriam (April 20, 2022), Speakers have the occasion to talk about theoretical aspects of their work which cannot be discussed in a setting where the majority of the audience consists of experimentalists. The seminars, **held on Wednesdays at 11 am ET,** are 45-50 min long followed by a discussion. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.* ᐧ

May 4, 2025

2025 Gatsby Unit PhD Programme - Apply by 27 May

by Lin, I-Chun

We have an opportunity for students to join our PhD programme this September. PhD Programme in Theoretical Neuroscience and Machine Learning Deadline: Tuesday 27 May 2025 The Gatsby Computational Neuroscience Unit is a leading research centre focused on theoretical neuroscience and machine learning. We study (un)supervised and reinforcement learning in brains and machines; inference, coding and neural dynamics; Bayesian and kernel methods, and deep learning; with applications to the analysis of perceptual processing and cognition, neural data, signal and image processing, machine vision, network data and nonparametric hypothesis testing. The Unit provides a unique opportunity for a critical mass of theoreticians to interact closely with one another and with researchers at the Sainsbury WellcomeCentre for Neural Circuits and Behaviour (SWC), the Centre for Computational Statistics and Machine Learning (CSML) and related UCL departments such as Computer Science; Statistical Science; Artificial Intelligence; the ELLIS Unit at UCL; Neuroscience; and the nearby Alan Turing and Francis Crick Institutes. Our PhD programme provides a rigorous preparation for a research career. Students complete a 4-year PhD in either machine learning or theoretical/computational neuroscience, with minor emphasis in the complementary field. Courses in the first year provide a comprehensive introduction to both fields and systems neuroscience. Students are encouraged to work and interact closely with SWC/CSML researchers to take advantage of this uniquely multidisciplinary research environment. Applicants should have a strong analytical and quantitative background, a keen interest in neuroscience, machine learning or both, and a relevant first degree, for example in Mathematics, Statistics, Computer Science, Engineering, Physics, Neuroscience or Cognitive Psychology. Full funding is available regardless of nationality. The unit also welcomes applicants who have secured or are seeking funding from other sources. Applications should be submitted directly to us via the online portal. For programme details and how to apply, see www.ucl.ac.uk/gatsby/study-and-work/gatsby-unit-phd-programme<https://www.ucl.ac.uk/gatsby/study-and-work/gatsby-unit-phd-programme>. -- I-Chun Lin Scientific Programme Manager Gatsby Computational Neuroscience Unit, UCL

May 2, 2025