Blomsma N, de Rooy B, Gerritse F, van der Spek R, Tewarie P, Hillebrand A, Otte W M, Stam C J, van Dellen E
University Medical Center Utrecht, Department of Psychiatry, Brain Center, Utrecht, the Netherlands.
Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurology and Department of Clinical Neurophysiology and MEG center, Amsterdam Neuroscience, Amsterdam The Netherlands.
Netw Neurosci. 2022 Jun 1;6(2):301-319. doi: 10.1162/netn_a_00245. eCollection 2022 Jun.
Brain network characteristics' potential to serve as a neurological and psychiatric pathology biomarker has been hampered by the so-called thresholding problem. The minimum spanning tree (MST) is increasingly applied to overcome this problem. It is yet unknown whether this approach leads to more consistent findings across studies and converging outcomes of either disease-specific biomarkers or transdiagnostic effects. We performed a systematic review on MST analysis in neurophysiological and neuroimaging studies ( = 43) to study consistency of MST metrics between different network sizes and assessed disease specificity and transdiagnostic sensitivity of MST metrics for neurological and psychiatric conditions. Analysis of data from control groups (12 studies) showed that MST leaf fraction but not diameter decreased with increasing network size. Studies showed a broad range in metric values, suggesting that specific processing pipelines affect MST topology. Contradicting findings remain in the inconclusive literature of MST brain network studies, but some trends were seen: (1) a more linelike organization characterizes neurodegenerative disorders across pathologies, and is associated with symptom severity and disease progression; (2) neurophysiological studies in epilepsy show frequency band specific MST alterations that normalize after successful treatment; and (3) less efficient MST topology in alpha band is found across disorders associated with attention impairments.
脑网络特征作为神经和精神病理学生物标志物的潜力受到所谓阈值问题的阻碍。最小生成树(MST)越来越多地被用于克服这一问题。目前尚不清楚这种方法是否会在不同研究中产生更一致的结果,以及是否会得出疾病特异性生物标志物或跨诊断效应的趋同结果。我们对神经生理学和神经影像学研究中的MST分析进行了系统综述(n = 43),以研究不同网络规模之间MST指标的一致性,并评估MST指标对神经和精神疾病的疾病特异性和跨诊断敏感性。对对照组数据的分析(12项研究)表明,MST叶分数而非直径随网络规模的增加而降低。研究显示指标值范围广泛,表明特定的处理流程会影响MST拓扑结构。在MST脑网络研究的不确定文献中仍存在相互矛盾的结果,但可以看到一些趋势:(1)跨病理学的神经退行性疾病具有更线性的组织特征,且与症状严重程度和疾病进展相关;(2)癫痫的神经生理学研究显示,成功治疗后,特定频段的MST改变会恢复正常;(3)在与注意力障碍相关的各种疾病中,发现α频段的MST拓扑效率较低。