Theoretical Neuroscience
Peter Dayan
Theoretical Neuroscience - A book resource
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More resources on Computational Neuroscience
Computational Neuroscience
This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning. We will make use of Matlab/Octave/Python demonstrations and exercises to gain a deeper understanding of concepts and methods introduced in the course. The course is primarily aimed at third- or fourth-year undergraduates and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.
Brian2 Simulator
Python-based neural simulator, free
NEURON Simulator
Free software for modeling neurons
Neuromatch Academy
Free computational neuroscience tutorials and courses
Neural Networks Chapter 1
3Blue1Brown intro to neural networks relevant to comp neuro
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