神经性厌食症认知的计算视角:系统综述。

Computational psychiatry (Cambridge, Mass.) Pub Date : 2025-04-07 eCollection Date: 2025-01-01 DOI:10.5334/cpsy.128
Marta Radzikowska, Alexandra C Pike, Sam Hall-McMaster
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引用次数: 0

摘要

神经性厌食症(AN)是一种严重的饮食失调,其特征是行为、认知和神经活动的持续变化,导致体重不足。最近,人们对使用计算方法来理解AN症状背后的认知机制越来越感兴趣,例如持续的减肥行为,围绕食物的严格规则和对体型的关注。我们的目的是系统地审查这一新兴领域的进展。基于使用系统和可重复标准选择的文章,我们确定了人工神经网络计算研究中的五个当前主题:1)强化学习;2)基于价值的决策;3)目标导向和习惯性控制行为;4)认知灵活性;5)基于理论的账目。除了描述和评估这些领域的见解外,我们还强调了该领域的方法学考虑,并概述了未来有希望的方向,以建立AN中(神经)计算变化的临床相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computational Perspectives on Cognition in Anorexia Nervosa: A Systematic Review.

Anorexia nervosa (AN) is a severe eating disorder, marked by persistent changes in behaviour, cognition and neural activity that result in insufficient body weight. Recently, there has been a growing interest in using computational approaches to understand the cognitive mechanisms that underlie AN symptoms, such as persistent weight loss behaviours, rigid rules around food and preoccupation with body size. Our aim was to systematically review progress in this emerging field. Based on articles selected using systematic and reproducible criteria, we identified five current themes in the computational study of AN: 1) reinforcement learning; 2) value-based decision-making; 3) goal-directed and habitual control over behaviour; 4) cognitive flexibility; and 5) theory-based accounts. In addition to describing and appraising the insights from each of these areas, we highlight methodological considerations for the field and outline promising future directions to establish the clinical relevance of (neuro)computational changes in AN.

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来源期刊
CiteScore
4.30
自引率
0.00%
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审稿时长
17 weeks
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