神经预测的途径：抑郁症治疗反应预测的机遇与挑战
Pathways to Neuroprediction: Opportunities and challenges to prediction of treatment response in depression.
作者信息
Langenecker Scott A, Crane Natania A, Jenkins Lisanne M, Phan K Luan, Klumpp Heide
机构信息
The University of Illinois at Chicago.
出版信息
Curr Behav Neurosci Rep. 2018 Mar;5(1):48-60. Epub 2018 Jan 24.
Abstract
PURPOSE OF REVIEW
We set out to review the current state of science in neuroprediction, using biological measures of brain function, with task based fMRI to prospectively predict response to a variety of treatments.
RECENT FINDINGS
Task-based fMRI neuroprediction studies are balanced between whole brain and ROI specific analyses. The predominant tasks are emotion processing, with ROIs based upon amygdala and subgenual anterior cingulate gyrus, both within the salience and emotion network. A rapidly emerging new area of neuroprediction is of disease course and illness recurrence. Concerns include use of open-label and single arm studies, lack of consideration of placebo effects, unbalanced adjustments for multiple comparisons (over focus on type I error), small sample sizes, unreported effect sizes, overreliance on ROI studies.
SUMMARY
There is a need to adjust neuroprediction study reporting so that greater coherence can facilitate meta analyses, and increased funding for more multiarm studies in neuroprediction.
摘要
综述目的
我们着手回顾神经预测领域的科学现状，利用基于任务的功能磁共振成像（fMRI）对脑功能进行生物学测量，以前瞻性地预测对各种治疗的反应。
最新发现
基于任务的fMRI神经预测研究在全脑分析和感兴趣区域（ROI）特定分析之间取得了平衡。主要任务是情绪处理，ROI基于杏仁核和膝下前扣带回，均位于突显和情绪网络内。神经预测一个迅速兴起的新领域是疾病进程和疾病复发。存在的问题包括使用开放标签和单臂研究、未考虑安慰剂效应、对多重比较的调整不均衡（过度关注I型错误）、样本量小、未报告效应量、过度依赖ROI研究。
总结
有必要调整神经预测研究报告，以便更高的一致性能够促进荟萃分析，并增加对神经预测中更多多臂研究的资金投入。
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