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1 - 11 of 11 search results for `systems in neuroscience` |u:cbl.eng.cam.ac.uk

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  2. Neural Dynamics and Control Group

    https://cbl.eng.cam.ac.uk/hennequin/publications/schimel-iclr-2022/
    27 Jun 2024: Abstract. Understanding how neural dynamics give rise to behaviour is one of the most fundamental questions in systems neuroscience. ... Here, we introduce iLQR-VAE, a control-based approach to variational inference in nonlinear dynamical systems,

  3. Computational and Biological Learning Lab

    https://cbl.eng.cam.ac.uk/vacancies/blg-phd/
    27 Jun 2024: Research in computational neuroscience covers learning and memory in perceptual, cognitive, and motor systems. ... Requirements. Applicants must have. strong problem solving and mathematical skills. a keen interest in neuroscience.

  4. Neural Dynamics and Control Group

    https://cbl.eng.cam.ac.uk/hennequin/publications/kao-cur-op-neurobiol-2019/
    27 Jun 2024: TC Kao, and G Hennequin. Abstract. A major challenge in systems neuroscience is to understand how the dynamics of neural circuits give rise to behaviour. ... Although a rich engineering literature has grown over decades to facilitate the analysis of such

  5. Computational Learning and Memory Group

    https://cbl.eng.cam.ac.uk/lengyel/vacancies/blg-phd/
    27 Jun 2024: Research in computational neuroscience covers learning and memory in perceptual, cognitive, and motor systems. ... Requirements. Applicants must have. strong problem solving and mathematical skills. a keen interest in neuroscience.

  6. Neural Sensory Processing Group

    https://cbl.eng.cam.ac.uk/ahmadian/vacancies/blg-phd/
    27 Jun 2024: Research in computational neuroscience covers learning and memory in perceptual, cognitive, and motor systems. ... Requirements. Applicants must have. strong problem solving and mathematical skills. a keen interest in neuroscience.

  7. Neural Sensory Processing Group

    https://cbl.eng.cam.ac.uk/ahmadian/publications/
    27 Jun 2024: One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. ... A major open problem in systems neuroscience is to understand the relationship between behavior and the detailed spiking

  8. Neuroscience out of control Control-theoretic methods for…

    https://cbl.eng.cam.ac.uk/news/hennequin_cosyne_2019.pdf
    25 Jun 2024: connectivity matrix. short-term memory decision-making V1. Linear systems in neuroscience. τdx. ... connectivity matrix. short-term memory decision-making V1 M1. Linear systems in neuroscience.

  9. Neural Dynamics and Control Group

    https://cbl.eng.cam.ac.uk/hennequin/vacancies/blg-phd/
    27 Jun 2024: Research in computational neuroscience covers learning and memory in perceptual, cognitive, and motor systems. ... Requirements. Applicants must have. strong problem solving and mathematical skills. a keen interest in neuroscience.

  10. Neuroscience out of control:control-theoretic perspectives on neural…

    https://cbl.eng.cam.ac.uk/publications/kao-cur-op-neurobiol-2019.pdf
    25 Jun 2024: Corresponding author (g.hennequin@eng.cam.ac.uk). September 6, 2019. Summary. A major challenge in systems neuroscience is to understand how the dynamics of neural circuits give rise to ... Although a rich engineering literature has grown over decades to

  11. Chapter 3A Theoretical Framework for the Dynamicsof Multiple…

    https://cbl.eng.cam.ac.uk/publications/remme-book-chapter-2012.pdf
    25 Jun 2024: J Neurophysiol,81(3):1296–307. Crook, S., Ermentrout, G., and Bower, J. (1998). Dendritic and synaptic effects in systems ofcoupled cortical oscillators. ... Hippocampus, 15(7):950–62. Izhikevich, E. (2007). Dynamical Systems in Neuroscience: The

  12. ILQR-VAE : CONTROL-BASED LEARNING OF INPUT-DRIVEN DYNAMICS WITH…

    https://cbl.eng.cam.ac.uk/publications/schimel-iclr-2022.pdf
    25 Jun 2024: ABSTRACT. Understanding how neural dynamics give rise to behaviour is one of the mostfundamental questions in systems neuroscience. ... While iLQR-VAE could find applications in many fields as a general approach to learning stochasticnonlinear dynamical

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