Group independent components underpin responses to items from a depression scale.

IF 3.8 4区 医学 Q1 Medicine Acta Neuropsychiatrica Pub Date : 2024-02-01 Epub Date: 2023-04-24 DOI:10.1017/neu.2023.22
Drozdstoy Stoyanov, Vladimir Khorev, Rossitsa Paunova, Sevdalina Kandilarova, Semen Kurkin, Vince D Calhoun
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Abstract

Objective: The aim of the present study is to investigate the brain circuits or networks that underpin diagnostically specific tasks by means of group independent component analysis for FMRI toolbox (GIFT). We hypothesised that there will be neural network patterns of activation and deactivation, which correspond to real-time performance on clinical self-evaluation scales.

Methods: In total, 20 healthy controls (HC) and 22 patients with major depressive episode have been included. All subjects were scanned with functional magnetic resonance imaging (fMRI) with paradigm composed of diagnostic clinical self-assessment depression scale contrasted to neutral scale. The data were processed with group independent component analysis for functional MRI toolbox and statistical parametric mapping.

Results: The results have demonstrated that there exist positively or negatively modulated brain networks during processing of diagnostic specific task questions for depressive disorder. There have also been confirmed differences in the networks processing diagnostic versus off blocks between patients and controls in anterior cingulate cortex and middle frontal gyrus. Diagnostic conditions (depression scale) when contrasted to neutral conditions demonstrate differential activity of right superior frontal gyrus and right middle cingulate cortex in the comparison of patients with HC.

Conclusion: Potential neuroimaging of state-dependent biomarkers has been directly linked with clinical assessment self-evaluation scale, administered as stimuli simultaneously with the fMRI acquisition. It may be regarded as further evidence in support of the convergent capacity of both methods to distinguish groups by means of incremental translational cross-validation.

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群体独立成分是对抑郁量表项目反应的基础。
研究目的本研究旨在通过FMRI工具箱(GIFT)的组独立成分分析,研究支撑特定诊断任务的大脑回路或网络。我们假设,激活和失活的神经网络模式与临床自我评估量表的实时表现相对应:方法:共纳入 20 名健康对照组(HC)和 22 名重度抑郁症患者。所有受试者均接受了功能磁共振成像(fMRI)扫描,范式由诊断性临床自我评估抑郁量表和中性量表组成。数据经功能磁共振成像工具箱的组独立成分分析和统计参数映射处理:结果表明,在处理抑郁障碍的特定诊断任务问题时,大脑网络存在正向或负向调节。在前扣带回皮层和额叶中回,患者和对照组在处理诊断与非诊断区块时的网络差异也得到了证实。诊断性条件(抑郁量表)与中性条件的对比显示,在患者与对照组的对比中,右侧额上回和右侧扣带中叶皮层的活动存在差异:状态依赖性生物标志物的潜在神经成像与临床评估的自我评价量表直接相关,在进行 fMRI 采集的同时进行刺激。这可以被视为支持这两种方法通过增量转化交叉验证来区分群体的趋同能力的进一步证据。
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来源期刊
Acta Neuropsychiatrica
Acta Neuropsychiatrica 医学-精神病学
CiteScore
8.50
自引率
5.30%
发文量
30
审稿时长
6-12 weeks
期刊介绍: Acta Neuropsychiatrica is an international journal focussing on translational neuropsychiatry. It publishes high-quality original research papers and reviews. The Journal''s scope specifically highlights the pathway from discovery to clinical applications, healthcare and global health that can be viewed broadly as the spectrum of work that marks the pathway from discovery to global health.
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