Hariri Ahmad R
Department of Psychology and Neuroscience, Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina 27708, USA.
Annu Rev Neurosci. 2009;32:225-47. doi: 10.1146/annurev.neuro.051508.135335.
Neuroimaging, especially BOLD fMRI, has begun to identify how variability in brain function contributes to individual differences in complex behavioral traits. In parallel, pharmacological fMRI and multimodal PET/fMRI are identifying how variability in molecular signaling pathways influences individual differences in brain function. Against this background, functional genetic polymorphisms are being utilized to understand the origins of variability in signaling pathways as well as to model efficiently how such emergent variability impacts behaviorally relevant brain function. This article provides an overview of a research strategy seeking to integrate these complementary technologies and utilizes existing empirical data to illustrate its effectiveness in illuminating the neurobiology of individual differences in complex behavioral traits. The article also discusses how such efforts can contribute to the identification of predictive markers that interact with environmental factors to precipitate disease and to develop more effective and individually tailored treatment regimes.
神经成像技术,尤其是血氧水平依赖性功能磁共振成像(BOLD fMRI),已开始揭示大脑功能的变异性如何导致复杂行为特征的个体差异。与此同时,药物功能磁共振成像以及多模态正电子发射断层显像/功能磁共振成像(PET/fMRI)正在确定分子信号通路的变异性如何影响大脑功能的个体差异。在此背景下,功能性基因多态性正被用于理解信号通路变异性的起源,并有效模拟这种新出现的变异性如何影响与行为相关的大脑功能。本文概述了一种旨在整合这些互补技术的研究策略,并利用现有实证数据说明其在阐明复杂行为特征个体差异的神经生物学方面的有效性。本文还讨论了这些努力如何有助于识别与环境因素相互作用以引发疾病的预测标志物,并制定更有效且个性化的治疗方案。