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I am looking to write my master's thesis next year about brain-inspired computing. Hence, I am looking to get a good overview of this domain.
Do you know of any comprehensive book that reviews topics in the area of brain-inspired computing (such as spiking neural networks)?
In spirit and scope, it should be similar to Ian Goodfellow's book deep learning.
The most popular theoretical framework in use currently, in the neuromorphic (brain-inspired) computing community is the Neural Engineering Framework (NEF). Neural Engineering by Chris Eliasmith and Charles Anderson explains the framework comprehensively.
As a follow up to that, How to Build a Brain by Chris Eliasmith describes the more recent and more high-level description of how to get spiking neural networks to actually perform multiple functions: the Semantic Pointer Architecture (SPA).
If you're looking for hardware descriptions too, the research publications on the chips Neurogrid, Brainscales, Braindrop, SpiNNaker, Loihi, TrueNorth etc. provide some good high-level descriptions of how to actually build the aforementioned chips.
