Department of Psychology, The Ohio State University, Columbus, Ohio 43210.
Cognitive Science Program, Indiana University, Bloomington, Indiana 47401.
J Neurosci. 2024 Jun 19;44(25):e1701232024. doi: 10.1523/JNEUROSCI.1701-23.2024.
Decreased neuronal specificity of the brain in response to cognitive demands (i.e., neural dedifferentiation) has been implicated in age-related cognitive decline. Investigations into functional connectivity analogs of these processes have focused primarily on measuring segregation of nonoverlapping networks at rest. Here, we used an edge-centric network approach to derive entropy, a measure of specialization, from spatially overlapping communities during cognitive task fMRI. Using Human Connectome Project Lifespan data (713 participants, 36-100 years old, 55.7% female), we characterized a pattern of nodal despecialization differentially affecting the medial temporal lobe and limbic, visual, and subcortical systems. At the whole-brain level, global entropy moderated declines in fluid cognition across the lifespan and uniquely covaried with age when controlling for the network segregation metric modularity. Importantly, relationships between both metrics (entropy and modularity) and fluid cognition were age dependent, although entropy's relationship with cognition was specific to older adults. These results suggest entropy is a potentially important metric for examining how neurological processes in aging affect functional specialization at the nodal, network, and whole-brain level.
大脑对认知需求的反应（即神经去分化）的神经元特异性降低与年龄相关的认知能力下降有关。对这些过程的功能连接类似物的研究主要集中在测量静息时非重叠网络的分离上。在这里，我们使用基于边缘的网络方法从认知任务 fMRI 期间空间重叠的社区中得出熵，这是一种专业化的度量。使用人类连接组计划寿命数据（713 名参与者，年龄 36-100 岁，女性占 55.7%），我们描述了一种节段去专业化模式，该模式会对内侧颞叶和边缘、视觉和皮质下系统产生不同的影响。在全脑水平上，全局熵调节了整个生命周期中流体认知能力的下降，并且当控制网络分离度量模块性时，全局熵与年龄具有独特的相关性。重要的是，这两个度量（熵和模块性）与流体认知之间的关系是年龄依赖性的，尽管熵与认知的关系是特定于老年人的。这些结果表明，熵是一种检查衰老过程中的神经过程如何影响节点、网络和全脑水平的功能专业化的潜在重要指标。
