Centro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso, Valparaíso, Chile.
Biomedical Research Doctorate Program, University of the Basque Country (UPV/EHU), Leioa, Spain.
Brain Connect. 2021 Nov;11(9):734-744. doi: 10.1089/brain.2020.0982. Epub 2021 May 28.
Brain interdependencies can be studied from either a structural/anatomical perspective ("structural connectivity") or by considering statistical interdependencies ("functional connectivity" [FC]). Interestingly, while structural connectivity is by definition pairwise (white-matter fibers project from one region to another), FC is not. However, most FC analyses only focus on pairwise statistics and they neglect higher order interactions. A promising tool to study high-order interdependencies is the recently proposed O-Information, which can quantify the intrinsic statistical synergy and the redundancy in groups of three or more interacting variables. We analyzed functional magnetic resonance imaging (fMRI) data obtained at rest from 164 healthy subjects with ages ranging in 10 to 80 years and used O-Information to investigate how high-order statistical interdependencies are affected by age. Older participants (from 60 to 80 years old) exhibited a higher predominance of redundant dependencies compared with younger participants, an effect that seems to be pervasive as it is evident for all orders of interaction. In addition, while there is strong heterogeneity across brain regions, we found a "redundancy core" constituted by the prefrontal and motor cortices in which redundancy was evident at all the interaction orders studied. High-order interdependencies in fMRI data reveal a dominant redundancy in functions such as working memory, executive, and motor functions. Our methodology can be used for a broad range of applications, and the corresponding code is freely available. Impact statement Past research has showcased multiple changes to the brain's structural and functional properties caused by aging. Here we expand prior work through recent advancements in multivariate information theory, which provide richer and more theoretically principled analyses than existing alternatives. We show that the brains of older participants contain more redundant information at multiple spatial scales-that is, activation in different brain regions is less diverse, compared with younger participants-and identify a "redundancy core" constituted by prefrontal and motor cortices, which might explained impaired performance in the old population in functions such as working memory and executive control.
大脑的相互依存关系可以从结构/解剖学的角度（“结构连接”）或通过考虑统计相互依存关系（“功能连接”[FC]）来研究。有趣的是，虽然结构连接从定义上讲是两两的（白质纤维从一个区域投射到另一个区域），但 FC 不是。然而，大多数 FC 分析仅侧重于两两统计，而忽略了更高阶的相互作用。一种研究高阶相互依存关系的有前途的工具是最近提出的 O 信息，它可以量化三组或更多相互作用变量的内在统计协同作用和冗余性。我们分析了从 164 名年龄在 10 岁至 80 岁之间的健康受试者在静息状态下获得的功能磁共振成像（fMRI）数据，并使用 O 信息来研究高阶统计相互依存关系如何受年龄影响。与年轻参与者相比，年龄较大的参与者（60 至 80 岁）表现出更高的冗余依赖性优势，这种效应似乎是普遍存在的，因为在所有交互阶次上都很明显。此外，虽然大脑区域之间存在很强的异质性，但我们发现了一个由前额叶和运动皮层组成的“冗余核心”，在所有研究的交互阶次上都存在冗余性。fMRI 数据中的高阶相互依存关系揭示了工作记忆、执行和运动等功能中的主导冗余性。我们的方法可用于广泛的应用，相应的代码是免费提供的。
