**7. Neuromorphic circuits**

The creation of brain-inspired computing systems necessitates the careful design of circuit blocks that exhibit specific elements of neuromorphic functions, such as plasticity and learning, in addition to device engineering. The individual synapses, for instance, must act as electrical connections between two neurons and change their weight in accordance with particular learning criteria that are inspired by the brain. This is one of the biggest challenges with neuromorphic computing is trying to replicate the human "connectome," or the physical wiring of the nervous system. Reverse-engineering the brain on solid-state devices (SSD) is still a long way off, despite advances in our understanding of how the wiring of the brain carries out higher-level processes (**Figure 6**).

 By digitally transferring biological neuronal network models onto electronic devices, neuromorphic computing explicitly aims to appropriate the biological connectome of the brain. Neuro-electronic interfaces are brain-computer interfaces that transmit data from the brain to outside equipment. Because there are currently no suitable neuro-electronic interfaces, digital brain mimicry is difficult.

 On the other hand, it has been demonstrated that time has a significant impact on synaptic plasticity in the brain. For instance, the human brain's spike-timing dependent plasticity (STDP) is a weight update mechanism where the amount of time between pre- and postsynaptic spikes determines the weight change's magnitude and sign, i.e., potentiation for the pre-synaptic spike coming before the postsynaptic spike and depression for the postsynaptic spike coming before the pre-synaptic spike [ 217 ]. Time calculation between a pair or triplet of spikes is a key component of other, more complex synaptic weight updating algorithms [ 218 – 220 ]. These plasticity rules typically call for the development of intricate circuits utilising CMOS devices [ 221 – 223 ] or nanoscale devices, such as PCM [ 224 – 226 ] or RRAM [ 24 , 64 , 224 , 227 – 229 ] technology. Plastic synapses based on PCM and RRAM often include one or more transistors in a hybrid design to enable a controllable computation of time within the circuit block, although examples of time-sensitive synapses that have been described [ 230 , 231 ].
