Department of Electrical & Electronics Engineering, Boğaziçi University, 34342, İstanbul, Turkey.
Department of Neurology, Bağılar Training and Research Hospital, 34212, İstanbul, Turkey.
Neurol Sci. 2024 Dec;45(12):5719-5730. doi: 10.1007/s10072-024-07688-1. Epub 2024 Jul 30.
Clinical cognitive decline, leading to Alzheimer's Disease Dementia (ADD), has long been interpreted as a disconnection syndrome, hindering the information flow capacity of the brain, hence leading to the well-known symptoms of ADD. The structural and functional brain connectome analyses play a central role in studies of brain from this perspective. However, most current research implicitly assumes that the changes accompanying the progression of cognitive decline are monotonous in time, whether measured across the entire brain or in fixed cortical regions. We investigate the structural and functional connectivity-wise reorganization of the brain without such assumptions across the entire spectrum. We utilize nodal assortativity as a local topological measure of connectivity and follow a data-centric approach to identify and verify relevant local regions, as well as to understand the nature of underlying reorganization. The analysis of our preliminary experimental data points to statistically significant, hyper and hypo-assortativity regions that depend on the disease's stage, and differ for structural and functional connectomes. Our results suggest a new perspective into the dynamic, potentially a mix of degenerative and compensatory, topological alterations that occur in the brain as cognitive decline progresses.
临床认知能力下降,导致阿尔茨海默病痴呆症(ADD),长期以来一直被解释为一种连接中断综合征,阻碍了大脑的信息流能力,从而导致 ADD 的明显症状。从这个角度来看,大脑的结构和功能连接组学分析起着核心作用。然而,大多数当前的研究都隐含地假设,无论在整个大脑还是在固定的皮质区域进行测量,与认知能力下降进展相关的变化在时间上都是单调的。我们在没有这些假设的情况下,在整个频谱上研究大脑的结构和功能连接的重新组织。我们利用节点聚集作为连接的局部拓扑度量,并采用以数据为中心的方法来识别和验证相关的局部区域,以及了解潜在重组的性质。对我们初步实验数据的分析表明,存在依赖于疾病阶段的、在结构和功能连接组中不同的、统计学上显著的超聚集和低聚集区域。我们的结果表明,随着认知能力下降的进展,大脑中可能存在混合退化和代偿性的动态拓扑变化的新视角。