Comparing Evolutionary Processes of Artificial and Biological Neural Networks

Perspectives on the study and application of artificial and biological neural network

Over the years, evolution, or the process of living organisms adapting to their environment over time, was widely studied. Darwin’s hypothesis from the middle 1800s was based on research that shows that all biological species, such as humans, adapt continuously to changing environmental conditions.

Researchers have developed advanced computational techniques in recent years based on artificial neuronal networks. These are inspired by the biological neural networks of the brain. Artificial neural network models are trained to optimize millions synaptic weights across millions of observations to make accurate predictions and classify data.

Princeton University researchers recently conducted a study that compared the evolution of artificial and biological neural network. The paper published in Neuron compares the evolution and psychology theory of biological neural networks to that of artificial neural networks.


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