Theoretical neuroscience
by Peter Dayan, L. F. Abbott · first published 2001
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"Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory."--BOOK JACKET.
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…great slimmer one is "From Neuron to Brain" (advanced undergrad/early grad): http://www.amazon.com/Neuron-Brain-Cellular-Molecular-Approa... If you're more interested in the computational end, try "Theoretical Neuroscience": http://www.amazon.com/Theoretical-Neuroscience-Computational... And I'll also add in a great computational textbook on spike recording: http://www.amazon.com/Spikes-Exploring-Neural-Computational-...…
on “Ask HN: What is a good introduction to neuroscience?” ↗…"Thought-provoking, technically rigorous, enjoyable, somewhat comprehensive, and layman-compatible introduction to..", more or less. Some books I enjoyed (but which don't necessary achieve that status) are: - Theoretical Neuroscience by Dayan & Abbott (this has math - but it's quite polite about it, and remains readable if you skip the equations) - Handbook of Brain Theory and Neural Networks:http://mitpress.mit.edu/0262011972 But…
on “Ask HN: Is there a SICP of biology?” ↗Bear's Neuroscience: Exploring the Brain Purves's Neuroscience Kandel's Principles of Neural Science (grad level, but really the bible for neuro) Dayan and Abbot's Theoretical Neuroscience (good for compneuro) The Art of Electronics, 2nd edition (cheating here, but it's good to go back through the fundamentals before going into the edge cases that is neuro) In general, AI is so new that…
on “Personality Basins” ↗Um, Dayan & Abbott's "Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems" comes to mind. It's rather neuroscience heavy though. Then there is "Spikes: Exploring the neural code" https://mitpress.mit.edu/books/spikes…
on “Spiking Neural Networks” ↗…biological neurons to neural nets. Essentially the weights in the neural net end up corresponding to steady-state firing rates of populations of spiking neurons. See for example Chapter 7 of Dayan & Abbott's Theoretical Neuroscience.
on “Nobel Prize in Physics awarded to John Hopfield and Geoffrey Hinton [pdf]” ↗Not the original poster, but: - Theoretical Neuroscience Computational and Mathematical Modeling of Neural Systems - Peter Dayan, L. F. Abbott (2001) is quite good, more mathematical than computational. - Neuronal dynamics, available here: https://neuronaldynamics.epfl.ch/…
on “Continuous Thought Machines” ↗