Contrasting Evolutionary Patterns of Functional Connectivity in Sensorimotor and Cognitive Regions after Stroke

No clue whatsoever. Your doctor will know however and if she doesn't ask her what she actually learned about stroke in medical school.
http://journal.frontiersin.org/article/10.3389/fnbeh.2016.00072/full?utm_source=newsletter&

Huaigui Liu^1†, Tian Tian^1†, Wen Qin^1,2†, Kuncheng Li² and Chunshui Yu^1,2*

• ¹Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
• ²Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China

The human brain is a highly connected and integrated system. Local stroke lesions can evoke reorganization in multiple functional networks. However, the temporally-evolving patterns in different functional networks after stroke remain unclear. Here, we aimed to investigate the dynamic evolutionary patterns of functional connectivity density (FCD) and strength (FCS) of the brain after subcortical stroke involving in the motor pathways. Eight male patients with left subcortical infarctions were longitudinally examined at five time points within a year. Voxel-wise FCD analysis was used to identify brain regions with significant dynamic changes. The temporally-evolving patterns in FCD and FCS in these regions were analyzed by a mixed-effects model. Associations between these measures and clinical variables were also explored in stroke patients. Voxel-wise analysis revealed dynamic FCD changes only in the sensorimotor and cognitive regions after stroke. FCD and FCS in the sensorimotor regions decreased initially, as compared to controls, remaining at lower levels for months, and finally returned to normal levels. In contrast, FCD and FCS in the cognitive regions increased initially, remaining at higher levels for months, and finally returned to normal levels. Most of these measures were correlated with patients’ motor scores. These findings suggest a network-specific dynamic functional reorganization after stroke. Besides the sensorimotor regions, the spared cognitive regions may also play an important role in stroke recovery.

Introduction

Motor pathways are frequently impaired in stroke patients with subcortical infarction. In most of these patients, the impaired motor function recovers in the first several months after stroke (Kwakkel et al., 2004), and this recovery has been attributed to a normalization of activity (Ward et al., 2003; Tombari et al., 2004; Kim et al., 2006) and connectivity (Golestani et al., 2013; Rehme and Grefkes, 2013) in the sensorimotor network (SMN). The human brain is composed of multiple highly connected and integrated functional networks. If a network is damaged, other networks may reorganize themselves to facilitate the functional recovery of the damaged network. This hypothesis is supported by findings of increased connectivity in several non-sensorimotor networks in patients with subcortical stroke (Wang et al., 2014). However, the dynamic connectivity changes of non-sensorimotor networks after subcortical stroke remain largely unknown.

In stroke patients, most resting-state functional connectivity studies are based on a priori selection of seed regions (Park et al., 2011; Xu et al., 2014), which cannot provide a full picture of connectivity changes in the whole brain. Moreover, previous studies only focused on functional connectivity strength (FCS) changes between brain regions, leaving post-stroke functional connectivity density (FCD) changes largely unknown. The FCD mapping is a newly developed data-driven method that measures the connectivity density of each voxel (Tomasi and Volkow, 2010). It is a plausible method to identify connectivity changes in the range of the whole brain.

In this study, we adopted a longitudinal design to investigate post-stroke connectivity changes and associations of these changes with motor recovery. First, we performed a voxel-wise FCD analysis to identify brain regions exhibiting longitudinal connectivity changes after subcortical infarctions involving the motor pathways. Second, we investigated post-stroke temporally-evolving patterns in FCD and functional connectivity strength (FCS) in these hub regions. Finally, we explored associations of these altered connectivity properties with clinical outcomes in stroke patients. We hypothesize that some non-SMN regions would also display longitudinal post-stroke connectivity changes based on clues from a cross-sectional study (Wang et al., 2014). We further hypothesize that the SMN and non-SMN regions would exhibit different evolutionary patterns following stroke.

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