Editing Neuromorphic computing (section)

==Neurological inspiration==
Neuromorphic engineering is for now set apart by the inspiration it takes from what is known about the structure and operations of the [[brain]]. Neuromorphic engineering translates what we know about the brain's function into computer systems. Work has mostly focused on replicating the analog nature of [[biological computation]] and the role of [[neuron]]s in [[cognition]].{{citation needed|date=February 2025}}

The biological processes of neurons and their [[synapse]]s are dauntingly complex, and thus very difficult to artificially simulate. A key feature of biological brains is that all of the processing in neurons uses analog [[Cell signalling|chemical signals]]. This makes it hard to replicate brains in computers because the current generation of computers is completely digital. However, the characteristics of these  chemical signals can be abstracted into mathematical functions that closely capture the essence of the neuron's operations.{{citation needed|date=February 2025}}

The goal of neuromorphic computing is not to perfectly mimic the brain and all of its functions, but instead to extract what is known of its structure and operations to be used in a practical computing system. No neuromorphic system will claim nor attempt to reproduce every element of neurons and synapses, but all adhere to the idea that computation is highly [[distributed processing|distributed]] throughout a series of small computing elements analogous to a neuron. While this sentiment is standard, researchers chase this goal with different methods.<ref>{{Cite journal | doi = 10.1088/1741-2560/13/5/051001| title = Large-scale neuromorphic computing systems| journal = Journal of Neural Engineering| volume = 13| pages = 1–15| year = 2016| last1 = Furber | first1 = Steve| issue = 5| pmid = 27529195| bibcode = 2016JNEng..13e1001F| doi-access = free}}</ref> Anatomical neural wiring diagrams that are being imaged by electron microscopy<ref>{{cite journal |last1=Devineni |first1=Anita |title=A complete map of the fruit-fly |journal=Nature |date=2 October 2024 |volume=634 |issue=8032 |pages=35–36 |doi=10.1038/d41586-024-03029-6|pmid=39358530 }}</ref> and functional neural connection maps that could be potentially obtained via intracellular recording at scale<ref>{{cite journal |last1=Wang |first1=Jun |last2=Jung |first2=Woo-Bin |last3=Gertner |first3=Rona |last4=Park |first4=Hongkun |last5=Ham |first5=Donhee |title=Synaptic connectivity mapping among thousands of neurons via parallelized intracellular recording with a microhole electrode array |journal=Nature Biomedical Engineering |date=2025 |doi=10.1038/s41551-025-01352-5 |pmid=39934437 |url=https://www.nature.com/articles/s41551-025-01352-5|url-access=subscription }}</ref> can be used to better inspire, if not exactly mimicked, neuromorphic computing systems with more details.