Mertens L, Vennekens J, Op de Beeck H, Yargholi E, Van den Stock J
Tijdschr Psychiatr. 2023;65(10):646-650.
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.
在过去十年中，人工智能（AI）取得了巨大发展，并越来越多地应用于包括精神病学在内的一系列领域。人工智能涵盖多种模式，包括人工神经网络（ANNs），即部分基于大脑工作方式的计算机模型。人工神经网络自20世纪50年代就已存在，但直到21世纪10年代才成为“主流”。它们受大脑工作方式启发这一事实引发了一个问题，即它们是否也可用于模拟大脑的（功能）失调。这个问题促成了“计算精神病学”这一研究领域的出现。
本文旨在对人工神经网络及其在当代精神病学实践中的潜在应用进行通俗易懂的介绍。
通过文献综述并列举一些实例。
在本文中，我们试图通过一些具体例子概述什么是人工神经网络以及它们如何用于模拟大脑中的机制。我们依次讨论将人工神经网络作为人类视觉系统的模型、面孔失认症的模型、幻听的模型，最后作为自闭症谱系障碍的模型。我们还描述了这种方法的一些局限性。
目前，构建一个模拟整个大脑的计算机模型具有挑战性，但当前的模型有助于检验有关可能导致多种神经精神疾病的机制的假设。
