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The Journal of Neuroscience 2023-05-24 | Journal article DOI: 10.1523/JNEUROSCI.1966-21.2022 Contributors : Sofia Isabel Ribeiro Pereira; Lorena Santamaria; Ralph Andrews; Elena Schmidt; Mark C.W. Van Rossum; Penelope Lewis Show more detail Source : check_circle Crossref Competitive plasticity to reduce the energetic costs of learning
Guido Van Rossum
I am a professor of Computational Neuroscience at the University of Nottingham and the Director of its Centre for Neural Computation. I have an MSc in Theoretical Physics from Utrecht Univerity and a PhD in Statistical Physics from University of Amsterdam. I have held research positions at the University of Pennsylvania and Brandeis University.
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The University of Nottingham's computational neuroscience research group, led by Mark van Rossum, Mark Humphries and Stephen Coombes, uniquely bridges psychology and mathematics.
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Mark C W van Rossum University of Nottingham | Notts · School of Psychology PhD Connect with experts in your field Join ResearchGate to contact this researcher and connect with your.
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Mark CW van Rossum The brain is not only constrained by energy needed to fuel computation, but it is also constrained by energy needed to form memories. Experiments have shown that learning simple conditioning tasks already carries a significant metabolic cost.
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Mark van Rossum - The GIRA s.r.l. | LinkedIn Mark van Rossum Denham, England, United Kingdom 2K followers 500+ connections Welcome back New to LinkedIn? Join now Join to follow The GIRA s.r.l..
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Mark van Rossum s director of the MSc in Computational Neuroscience, Cognition, and AI. This course allows for the first time in the UK a direct integration of computational neuroscience with… read more Research Summary Mark van Rossum started his computational neuroscience research after obtaining a PhD in theoretical physics.
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University of Nottingham - Cited by 7,380 - Computational neuroscience
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Mark C W van Rossum The influence of one extra static scatterer on multiple scattered classical waves is considered. It is shown how to connect two ``diffusions'' or ``ladders''.
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Arnd Roth and Mark C. W. van Rossum Modeling synaptic transmission between neurons is a challenging task. Since many physiological processes contribute to synaptic transmission (figure 6.1), computa-
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Girard, M., Jiang, J., & van Rossum, M. C. Estimating the energy requirements for long term memory formation Brains consume metabolic energy to process information, but also to store memories. The energy required for memory formation can be substantial, for instance in fruit flies memory formation leads to a shorter lifespan upon subsequent starvation (Mery.
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Name: Mark van Rossum Position: Reader in Bioinformatics Institute: School of Bioinformatics Research Interests and Approaches: Computational Neuroscience. Particular interests - learning and memory (biophysics up to systems level) - sensory coding and decoding - (Bayesian) data analysis Websites: homepages.inf.ed.ac.uk
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Mark Van Rossum. Overview. Bio. Network 50. Publications 92. Editorial Contributions 6. Impact. Loop is the open research network that increases the discoverability and impact of researchers and their work. Loop enables you to stay up-to-date with the latest discoveries and news, connect with researchers and form new collaborations.
Guido van Rossum Faces of Open Source
310. 2007. Fast propagation of firing rates through layered networks of noisy neurons. MCW van Rossum, GG Turrigiano, SB Nelson. Journal of neuroscience 22 (5), 1956-1966. , 2002. 259. 2002. Systematic biases in early ERP and ERF components as a result of high-pass filtering.
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Elife. 2020 Feb 13;9:e50804.doi: 10.7554/eLife.50804. Authors Ho Ling Li 1 , Mark Cw van Rossum 1 2 Affiliations 1School of Psychology, University of Nottingham, Nottingham, United Kingdom. 2School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom.
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Mark van Rossum, programme director. Mark directed the UK's first Doctoral Training Centre, has written over 70 papers, and has supervised over 20 PhD students. Related courses. Machine Learning in Science MSc. Learn how to apply machine learning and AI techniques to real scientific problems. Build vital skills to enhance your employability in.