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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.

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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.

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  • $\begingroup$ Hello. Welcome to Artificial Intelligence SE. Thanks for trying to contribute to our site! It may be a good idea to provide links to the cited books or their pdfs, if available. $\endgroup$
    – nbro
    Commented Jul 21, 2021 at 18:10

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