Interpreting Neurone Signals using Deep Learning

Neurons send and receive information. Although neurons come in many different types, they generally have three parts: a dendrite which receives a signal, a cell body called a soma which computes the signal, and an axon which sends a signal out. The neurons of your brain connect to each other to send and receive signals through axon-dendrite connections called synapse. Action potentials cause synapses to release neurotransmitters. These small molecules bind to receptors on dendrites, opening channels that cause current to flow across the neuron’s membrane. When a neuron receives the ‘right’ combination of spatiotemporal synaptic input, it initiates an action potential. Elon Musk's startup company, Neuralink, introduced a prototype to place electrodes near neurons in order to detect action potentials. Recording from many neurons allows us to digitise the information represented by those cells. In the movement-related areas of the brain, for example, neurons represent intended movements. There are neurons in the brain that carry information about everything we see, feel, touch, or think. An intelligent model can learn and classify all these information. Such information not only help to provide proper treatment for brain damage, Alzheimer and improve the bionic eyes technologies, also could be used to send information into human's brain. This can be a new milestone in human civilisation.