Functional connectivity drives stroke recovery: shifting the paradigm from correlation to causation

神经功能成像 中风恢复 心理学 神经科学 脑磁图 功能磁共振成像 皮质脊髓束 冲程(发动机) 因果关系(物理学) 物理医学与康复 认知心理学 康复 神经影像学 医学 磁共振成像 脑电图 磁共振弥散成像 机械工程 物理 量子力学 工程类 放射科
作者
Jessica M. Cassidy,Jasper I Mark,Steven C. Cramer
出处
期刊:Brain [Oxford University Press]
卷期号:145 (4): 1211-1228 被引量:17
标识
DOI:10.1093/brain/awab469
摘要

Abstract Stroke is a leading cause of disability, with deficits encompassing multiple functional domains. The heterogeneity underlying stroke poses significant challenges in the prediction of post-stroke recovery, prompting the development of neuroimaging-based biomarkers. Structural neuroimaging measurements, particularly those reflecting corticospinal tract injury, are well-documented in the literature as potential biomarker candidates of post-stroke motor recovery. Consistent with the view of stroke as a ‘circuitopathy’, functional neuroimaging measures probing functional connectivity may also prove informative in post-stroke recovery. An important step in the development of biomarkers based on functional neural network connectivity is the establishment of causality between connectivity and post-stroke recovery. Current evidence predominantly involves statistical correlations between connectivity measures and post-stroke behavioural status, either cross-sectionally or serially over time. However, the advancement of functional connectivity application in stroke depends on devising experiments that infer causality. In 1965, Sir Austin Bradford Hill introduced nine viewpoints to consider when determining the causality of an association: (i) strength; (ii) consistency; (iii) specificity; (iv) temporality; (v) biological gradient; (vi) plausibility; (vii) coherence; (viii) experiment; and (ix) analogy. Collectively referred to as the Bradford Hill Criteria, these points have been widely adopted in epidemiology. In this review, we assert the value of implementing Bradford Hill’s framework to stroke rehabilitation and neuroimaging. We focus on the role of neural network connectivity measurements acquired from task-oriented and resting-state functional MRI, EEG, magnetoencephalography and functional near-infrared spectroscopy in describing and predicting post-stroke behavioural status and recovery. We also identify research opportunities within each Bradford Hill tenet to shift the experimental paradigm from correlation to causation.
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