How neuromorphic computing could take us to the next level

IMAGE: Young, KA., Wise, JA., DeSaix, P., Kruse, DH., Poe, B., Johnson, E., Johnson, JE., Korol, O., Betts, JG., & Womble, M. (CC BY)

The place where computing and biology meet: a fascinating area of study based on creating models inspired by neuronal synapses into computing, and one of the most intriguing questions related to the transmission of information in a living organism.

The neuronal synapse is an extremely interesting mechanism: when two neurons transmit information between each other, they release a neurotransmitter in a synaptic space, which when it reaches the other neuron triggers the transmission. We still don’t understand why these neurons are not directly connected, why our neural circuits are made up of isolated cells, and why such a complex mechanism that generates this fuzzy connection is necessary, but what we do know is that this is the basis of how we remember, learn and transmit all kinds of impulses.

Traditionally, the difference between a living organism and a computer has been that living mechanisms transmit information through this fuzzy model, while the connections between the components of a computer are direct. So far, developing artificial neurons to simulate a synapse is still based on mathematics capable of modeling these connections by means of neural networks: the artificial neuron receives one or more inputs that represent excitatory postsynaptic potentials and inhibitory postsynaptic potentials in its dendrites…