An artificial neural network (ANN) is a statistical model designed by simulating the neurons of a human brain such that the model functions in a humanlike manner ( Ogedjo et al., 2022 ) . ANNs are designed in a similar way to the human brains as they contain neural hubs linked like a web. The cerebrum of a human has billions of cells called neurons. An ANN is comprised of thousands of fake neurons known as preparing units, which are linked by hubs. Similar to humans who require rules to prepare an outcome, ANNs apply multiple learning rules called backpropagation, to consummate their outcomes.

The neurons in the ANN are impacted by the biological neurons. Both artificial and biological neural networks are linked in a graphical format by nodes where the signals can be transmitted. Processing in artificial neural networks is done in a series manner whereas in biological processing is done in parallel. The artificial neural network functions synchronously whereas the human brain functions asynchronously. Artificial neural networks are time-autonomous and cannot channel their information sources, whereas biological neural networks are made of oscillators which enable them to channel inputs.