Introduction to Neurophysics (2023)
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<br>Syllabus
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<br>Neurophysics is a one-semester course focusing on analyzing neuroscience 
<br>phenomena from the perspective of physics. The background knowledge of the 
<br>course is minimal: basic linear algebra and dynamical-system analysis would be 
<br>fine. However, the topics addressed in this course can be truly challenging and 
<br>most of them are still rolling in the research frontiers.  
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<br>Textbook: Neuronal Dynamics (Cambridge University Press) by Gerstner, Kistler, 
<br>Naud and Paninski, available online (https://neuronaldynamics.epfl.ch/)
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<br>Classes: 13:20 – 16:20 on Tuesdays
<br>Report: due on Week 16
<br>Grades: term paper (100%)
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<br>Note:
<br>(1) This course follows a 16-week syllabus with extra online resources.
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<br>https://www.youtube.com/@prof-hedgehog
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<br>(2) AI tools (like ChatGPT) are allowed but detail explanations needed.
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<br>Week 1
<br>Course introduction
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<br>Week 2
<br>Brain intro
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<br>Week 3
<br>Action potential and integrate-and-fire model
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<br>Week 4
<br>Ion channels and Hodgkin-Huxley model
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<br>Week 5
<br>國慶日
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<br>Week 6
<br>Bifurcations in neuron models
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<br>Week 7
<br>Synapses and dendrites
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<br>Week 8
<br>me<x>taneurons
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<br>Week 9
<br>U(1) neuronal network
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<br>Week 10
<br>Decision making – excitation/inhibition neurons
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<br>Week 11
<br>Associative memory
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<br>Week 12
<br>Hopfield Network
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<br>Week 13
<br>Hebbian Learning
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<br>Week 14
<br>Principal component analysis (PCA)
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<br>Week 15
<br>BCM theory
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<br>Week 16
<br>Final Reports discussions
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