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注意缺陷多动障碍男孩和持续性抑郁障碍男孩额顶网络的神经特征差异。

Distinct Neural Profiles of Frontoparietal Networks in Boys with ADHD and Boys with Persistent Depressive Disorder.

机构信息

Department of Paediatrics, University of Melbourne, Melbourne, Australia.

Washington University in St. Louis, St. Louis, MO, USA.

出版信息

Cogn Affect Behav Neurosci. 2022 Oct;22(5):1183-1198. doi: 10.3758/s13415-022-00999-w. Epub 2022 Mar 29.


DOI:10.3758/s13415-022-00999-w
PMID:35349053
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10149107/
Abstract

Working memory deficits are common in attention-deficit/hyperactivity disorder (ADHD) and depression-two common neurodevelopmental disorders with overlapping cognitive profiles but distinct clinical presentation. Multivariate techniques have previously been utilized to understand working memory processes in functional brain networks in healthy adults but have not yet been applied to investigate how working memory processes within the same networks differ within typical and atypical developing populations. We used multivariate pattern analysis (MVPA) to identify whether brain networks discriminated between spatial versus verbal working memory processes in ADHD and Persistent Depressive Disorder (PDD). Thirty-six male clinical participants and 19 typically developing (TD) boys participated in a fMRI scan while completing a verbal and a spatial working memory task. Within a priori functional brain networks (frontoparietal, default mode, salience), the TD group demonstrated differential response patterns to verbal and spatial working memory. The PDD group showed weaker differentiation than TD, with lower classification accuracies observed in primarily the left frontoparietal network. The neural profiles of the ADHD and PDD differed specifically in the SN where the ADHD group's neural profile suggests significantly less specificity in neural representations of spatial and verbal working memory. We highlight within-group classification as an innovative tool for understanding the neural mechanisms of how cognitive processes may deviate in clinical disorders, an important intermediary step towards improving translational psychiatry.

摘要

工作记忆缺陷在注意缺陷多动障碍(ADHD)和抑郁症中很常见 - 这两种常见的神经发育障碍具有重叠的认知特征,但临床表现不同。多变量技术以前曾用于了解健康成年人功能性大脑网络中的工作记忆过程,但尚未应用于研究相同网络中的工作记忆过程在典型和非典型发育人群中的差异。我们使用多元模式分析(MVPA)来确定 ADHD 和持续性抑郁障碍(PDD)中的大脑网络是否可以区分空间与言语工作记忆过程。36 名男性临床参与者和 19 名典型发育(TD)男孩在完成言语和空间工作记忆任务的同时进行了 fMRI 扫描。在预先确定的功能性大脑网络(额顶叶、默认模式、突显)中,TD 组表现出对言语和空间工作记忆的不同反应模式。与 TD 相比,PDD 组的分化能力较弱,主要在前额顶叶网络中观察到较低的分类准确性。ADHD 和 PDD 的神经特征在 SN 中存在差异,其中 ADHD 组的神经特征表明,空间和言语工作记忆的神经表示特异性明显降低。我们强调了组内分类作为一种理解认知过程在临床障碍中可能偏离的神经机制的创新工具,这是改善转化精神病学的重要中间步骤。

相似文献

[1]
Distinct Neural Profiles of Frontoparietal Networks in Boys with ADHD and Boys with Persistent Depressive Disorder.

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[2]
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[3]
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[8]
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[10]
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引用本文的文献

[1]
Insights into structural deviations in attention deficit hyperactivity disorder (ADHD) and comorbidities using big data-derived brain charts: a cross-sectional study.

Quant Imaging Med Surg. 2025-9-1

[2]
Working Memory-Related Neurofunctional Correlates Associated with the Frontal Lobe in Children with Familial vs. Non-Familial Attention Deficit/Hyperactivity Disorder.

Brain Sci. 2023-10-18

[3]
Cognitive flexibility: neurobehavioral correlates of changing one's mind.

Cereb Cortex. 2023-4-25

本文引用的文献

[1]
Which multiband factor should you choose for your resting-state fMRI study?

Neuroimage. 2021-7-1

[2]
Dynamic functional connectome predicts individual working memory performance across diagnostic categories.

Neuroimage Clin. 2021

[3]
Towards precise resting-state fMRI biomarkers in psychiatry: synthesizing developments in transdiagnostic research, dimensional models of psychopathology, and normative neurodevelopment.

Curr Opin Neurobiol. 2020-12

[4]
Irritability, Depressed Mood, Inattention and Spatial Working Memory in Children and Adolescents with Major Depressive Disorder With/Without Persistent Depressive Disorder.

Child Psychiatry Hum Dev. 2021-10

[5]
Does higher sampling rate (multiband + SENSE) improve group statistics - An example from social neuroscience block design at 3T.

Neuroimage. 2020-6

[6]
Machine Learning With Neuroimaging: Evaluating Its Applications in Psychiatry.

Biol Psychiatry Cogn Neurosci Neuroimaging. 2020-8

[7]
The Salience Network: A Neural System for Perceiving and Responding to Homeostatic Demands.

J Neurosci. 2019-11-1

[8]
Inhibition-related modulation of salience and frontoparietal networks predicts cognitive control ability and inattention symptoms in children with ADHD.

Mol Psychiatry. 2021-8

[9]
Peeling the Onion of Brain Representations.

Annu Rev Neurosci. 2019-7-8

[10]
Brain network functional connectivity and cognitive performance in major depressive disorder.

J Psychiatr Res. 2018-11-22

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