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Lecture Introduction to Computational Neuroscience, 14. Lesson
Mallot, Hanspeter (2018)
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mla
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Mallot H. "Lecture Introduction to Computational Neuroscience, 14. Lesson.", timms video, Universität Tübingen (2018): https://timms.uni-tuebingen.de:443/tp/UT_20181130_002_compneuro_0001. Accessed 22 Aug 2019.
apa
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Mallot, H. (2018). Lecture Introduction to Computational Neuroscience, 14. Lesson. timms video: Universität Tübingen. Retrieved August 22, 2019 from the World Wide Web https://timms.uni-tuebingen.de:443/tp/UT_20181130_002_compneuro_0001
harvard
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Mallot, H. (2018). Lecture Introduction to Computational Neuroscience, 14. Lesson [Online video]. 30 November. Available at: https://timms.uni-tuebingen.de:443/tp/UT_20181130_002_compneuro_0001 (Accessed: 22 August 2019).
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title: Lecture Introduction to Computational Neuroscience, 14. Lesson
alt. title:
creator: Mallot, Hanspeter (author)
subjects: Neurobiologie, Computational Neuroscience, Lecture, Vorlesung, Complex numbers, Eigenfunction of convolution, Convolution with a Gaussian
description: Vorlesung im WiSe 2018-2019; Freitag, 30. November 2018
abstract: The course will provide an overview over the field of computational neuroscience focussing on four topics: (i) biophysics of excitable membranes: Hodgekin-Huxley theory of the action potential and cable theory of passive conduction, (ii) receptive fields including linear systems and Fourier theory, (iii) neural networks and basics of statistical learning theory, and (iv) neural coding. The focus of the course is on central neuroscience mechanisms; mathematical formalizations are presented on a medium level that should be accessable with highschool or introductory BSc level knowledge of mathematics.
publisher: ZDV Universität Tübingen
contributor: ZDV Universität Tübingen (producer)
creation date: 2018-11-30
dc type: image
localtype: video
identifier: UT_20181130_002_compneuro_0001
language: eng
rights: Url: https://timmsstatic.uni-tuebingen.de/jtimms/TimmsDisclaimer.html?637020625824825086