Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Neurosci Biobehav Rev. 2023 Jul;150:105193. doi: 10.1016/j.neubiorev.2023.105193. Epub 2023 Apr 21.
The human brain exhibits complex interactions across micro, meso-, and macro-scale organisational principles. Recent synergistic multi-modal approaches have begun to link micro-scale information to systems level dynamics, transcending organisational hierarchies and offering novel perspectives into the brain's function and dysfunction. Specifically, the distribution of micro-scale properties (such as receptor density or gene expression) can be mapped onto macro-scale measures from functional MRI to provide novel neurobiological insights. Methodological approaches to enrich functional imaging analyses with molecular information are rapidly evolving, with several streams of research having developed relatively independently, each offering unique potential to explore the trans-hierarchical functioning of the brain. Here, we address the three principal streams of research - spatial correlation, molecular-enriched network, and in-silico whole brain modelling analyses - to provide a critical overview of the different sources of molecular information, how this information can be utilised within analyses of fMRI data, the merits and pitfalls of each methodology, and, through the use of key examples, highlight their promise to shed new light on key domains of neuroscientific inquiry.
人类大脑表现出复杂的相互作用，涉及微观、中观和宏观尺度的组织原则。最近协同的多模态方法已经开始将微观信息与系统水平的动力学联系起来，超越了组织层次结构，并为大脑的功能和功能障碍提供了新的视角。具体来说，微观尺度特性（如受体密度或基因表达）的分布可以映射到从功能磁共振成像获得的宏观尺度测量值上，从而提供新的神经生物学见解。用分子信息丰富功能成像分析的方法学方法正在迅速发展，有几个研究方向相对独立地发展起来，每个方向都有独特的潜力来探索大脑的跨层次功能。在这里，我们研究了三个主要的研究方向——空间相关性、分子富集网络和基于计算机的全脑建模分析——为不同的分子信息来源提供了批判性的概述，如何在 fMRI 数据分析中利用这些信息，每种方法的优点和缺点，以及通过使用关键示例，强调它们有希望为神经科学研究的关键领域提供新的见解。
