Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois.
Department of Psychiatry & Behavioral Health, University of Illinois Chicago, Chicago, Illinois.
Biol Psychiatry Cogn Neurosci Neuroimaging. 2024 Jan;9(1):101-111. doi: 10.1016/j.bpsc.2023.06.008. Epub 2023 Jul 17.
Recent studies have begun to examine how signals in the brain correspond to the underlying white matter structure using tools from the field of graph signal processing to quantify brain function alignment to brain network topology. Here, we applied this framework for the first time toward a transdiagnostic cohort of individuals with internalizing psychopathologies, including mood and anxiety disorders, to uncover how such alignment within the default mode network (DMN) is related to depression and rumination symptoms.
Both diffusion-weighted and resting-state functional magnetic resonance imaging were obtained from participants at baseline (n = 60 patients, n = 19 healthy control participants). Patients were randomized to 12 weeks of treatment with either a selective serotonin reuptake inhibitor or cognitive behavioral therapy, and symptom scales were readministered posttreatment (n = 46 patients at follow-up). Using graph signal processing methodology, we quantified the alignment of functional signals to their underlying white matter structural networks.
We found that signal alignment within the posterior DMN was decreased in patients with internalizing psychopathologies compared with healthy control participants and was inversely (negatively) correlated with baseline depression and rumination scales. Signal alignment within the posterior DMN was also correlated with the ratio of total within-DMN to extra-DMN functional connectivity for these regions.
These findings are consistent with previous literature regarding pathological promiscuity of posterior DMN connectivity and provide the first graph signal processing-based analyses in a transdiagnostic cohort of patients with internalizing psychopathologies.
最近的研究开始使用图信号处理领域的工具来检查大脑中的信号如何与潜在的白质结构相对应，以量化大脑功能与大脑网络拓扑的对齐方式。在这里，我们首次将该框架应用于患有内化性精神病理学（包括情绪和焦虑障碍）的跨诊断队列，以揭示默认模式网络（DMN）内的这种对齐方式与抑郁和沉思症状有何关联。
基线时（n=60 名患者，n=19 名健康对照参与者）从参与者那里同时获得扩散加权和静息态功能磁共振成像。患者被随机分配到接受选择性 5-羟色胺再摄取抑制剂或认知行为治疗 12 周，治疗后重新进行症状量表评估（n=46 名患者进行随访）。使用图信号处理方法，我们量化了功能信号与其潜在白质结构网络的对齐程度。
我们发现，与健康对照组相比，患有内化性精神病理学的患者的 DMN 后区的信号对齐程度降低，与基线抑郁和沉思量表呈负相关。DMN 后区的信号对齐程度也与这些区域的全脑内 DMN 与额外 DMN 功能连接的比值相关。
这些发现与以前关于 DMN 后部连接病理性混杂的文献一致，并为患有内化性精神病理学的跨诊断队列提供了首次基于图信号处理的分析。
