[Artificial neural networks as a psychiatric instrument]

Artificial intelligence (AI) has evolved enormously over the past decade and is increasingly being applied to a range of domains, including psychiatry. AI encompasses several modalities, including artificial neural networks (ANNs), referring to computer models partly based on the workings of the brain. ANNs have existed since the ’50s, but only became ‘mainstream’ since the 2010s. The fact that they are inspired by the workings of the brain raises the question of whether they can also be used to model the (dys)functioning of the brain. This question led to the advent of the research field ‘computational psychiatry’.

This article aims at providing an accessible introduction to artificial neural networks, and potential applications hereof in contemporary psychiatric practice.

Literature review with some examples.

In this article we try to outline with some concrete examples what artificial neural networks are and how they can be used to model mechanisms in the brain. We successively discuss ANNs as a model of the human visual system, as a model of prosopagnosia and as a model of auditory hallucinations and finally as a model of autism spectrum disorder. We also describe a number of limitations of this approach.

A computer model that models the entire brain is challenging at present, but current models can help in testing hypotheses concerning possible mechanisms that give rise to a wide range of neuropsychiatric conditions.