Edited by: Rick Dijkhuizen, University Medical Center Utrecht, Netherlands
Reviewed by: Alex R. Carter, Washington University in St. Louis, United States; Emmanuel Carrera, Hôpitaux Universitaires de Genève (HUG), Switzerland
†These authors have contributed equally to this work.
Specialty section: This article was submitted to Stroke, a section of the journal Frontiers in Neurology
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Functional connectivity maps using resting-state functional magnetic resonance imaging (rs-fMRI) can closely resemble task fMRI activation patterns, suggesting that resting-state brain activity may predict task-evoked activation or behavioral performance. However, this conclusion was mostly drawn upon a healthy population. It remains unclear whether the predictive ability of resting-state brain activity for task-evoked activation would change under different pathological conditions. This study investigated dynamic changes of coupling between patterns of resting-state functional connectivity (RSFC) and motion-related activation in different stages of cerebral stroke. Twenty stroke patients with hand motor function impairment were involved. rs-fMRI and hand motion-related fMRI data were acquired in the acute, subacute, and early chronic stages of cerebral stroke on a 3-T magnetic resonance (MR) scanner. Sixteen healthy participants were enrolled as controls. For each subject, an activation map of the affected hand was first created using general linear model analysis on task fMRI data, and then an RSFC map was determined by seeding at the peak region of hand motion activation during the intact hand task. We then measured the extent of coupling between the RSFC maps and motion-related activation maps. Dynamic changes of the coupling between the two fMRI maps were estimated using one-way repeated measures analysis of variance across the three stages. Moreover, imaging parameters were correlated with motor performances. Data analysis showed that there were different coupling patterns between motion-related activation and RSFC maps associating with the affected motor regions during the acute, subacute, and early chronic stages of stroke. Coupling strengths increased as the recovery from stroke progressed. Coupling strengths were correlated with hand motion performance in the acute stage, while coupling recovery was negatively correlated with the recovery outcome of hand motion performance in the early chronic stages. Couplings between RSFC and motion-related activation were dynamically changed with stroke progression, which suggested changes in the prediction of resting-state brain activity for task-evoked brain activity in different pathological states. The changes in coupling strength between these two types of brain activity implicate a reparative mechanism of brain injury and may represent a biomarker for predicting motor recovery in cerebral stroke.
Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI), as a non-invasive imaging technique, has become an effective tool for investigating the human brain, both in a clinical context and a research context. Conventional task-based fMRI can depict the topological pattern of stimulus or task-evoked brain activation through specific experimental designs, and has been used to estimate the function, and localize the eloquent regions of brain diseases (
The underlying physiological mechanism of resting-state brain activity is one of the main research priorities in the neuroimaging field. Although there is a large body of studies that have interrogating the relationship between resting-state brain activity and associated task-evoked brain activity using fMRI (
In this study, we carried out a longitudinal fMRI study on patients with cerebral stroke at different stages of progression. By observing the relationship between resting-state brain activity and task-evoked activation associated with hand motion, we were able to estimate the changes in dynamic coupling following cerebral stroke. We hypothesized that the coupling pattern between rs-fMRI and task-based fMRI would be influenced by the specific pathological condition involved, and that this would involve a time-dependent change following the recovery of motor function. Confirmation of these hypotheses would provide new insight into our understanding of the relationship between rs-fMRI and task-based fMRI under pathological conditions.
This study was approved by the local Ethical Committee and all subjects provided informed written consent. A total of 20 acute ischemic stroke patients with hand motor impairment (17 men, 3 women; age: 50.95 ± 11.40 years, age range: 30–71 years; 6 with right-side deficit) were enrolled in the Inpatient Department of Jingling Hospital (Nanjing, China) between January 2015 and July 2016. The inclusion criteria were as follows: (1) first-ever ischemic stroke, (2) unilateral hand motor deficit, (3) symptom onset <7 days, (4) age between 18 and 80 years, and (5) single stroke lesion located in the territory of the middle cerebral artery. The exclusion criteria were as follows: (1) hemorrhagic stroke, (2) bilateral stroke lesions on MRI, (3) language or cognitive deficits sufficient to affect informed consent, (4) other orthopedic, neurological, or psychiatric disease substantially affecting the arm, (5) contraindications for MRI examination, and (6) recurrent stroke during follow-up. In addition, 16 healthy subjects (12 men, 4 women; age: 54.25 ± 2.51 years; age range: 35–68 years) were included as an age-matched control group.
Clinical and imaging data were obtained at three time points: acute stage (3.75 ± 1.62 days after the onset of stroke; day range: 1–7), subacute stage (9.95 ± 2.16 days after stroke; day range: 7–14 days), early chronic stage (98.3 ± 8.39 days after stroke; day range: 87–116 days). The hand motor function of each patient was assessed using the Upper Limb Fugl-Meyer Assessment (UL-FMA) score, which ranges from 0 (complete hemiplegia) to 66 (normal performance) for the upper extremities. Mean UL-FMA scores at each time point were 36.1 ± 15.65 (range: 6–59), 43.6 ± 17.18 (range: 7–62), and 55.60 ± 11.49 (range: 27–66), respectively. The mean size of stroke lesions was 3.36 ± 2.08 ml (range: 0.61–6.44 ml). Demographic and clinical characteristics of stroke patients are shown in Table
Demographic and clinical data of stoke patients.
Patients ( |
Acute stage | Subacute stage | Early chronic stage |
---|---|---|---|
Age (years) | 50.95 ± 11.40 (32–71) | – | – |
Sex (male) | 17/20 | – | – |
Lesion side (left) | 14/20 | – | – |
Lesion volume (ml) | 3.36 ± 2.08 (0.61–6.44) | – | – |
Days after stroke | 3.75 ± 1.62 (1–7) | 9.95 ± 2.16 (7–14) | 98.3 ± 8.39 (87–116) |
UL-FMA | 36.1 ± 15.65 (6–59) | 43.6 ± 17.18 (7–62) | 55.60 ± 11.49 (27–66) |
All MR images were acquired using a 3.0-T whole-body scanner (Discovery MR 750, GE Healthcare, Milwaukee, WI, USA) with a 32-channel phased-array head coil. Participants were placed on the scanner gantry in a head-first supine position using plastic holders to minimize head motion and ear plugs to reduce scanner noise. A high-resolution 3D T1-weighted structural image was obtained in the transverse orientation using a 3D-BRAVO sequence with the following parameters: TR = 8.2 ms, TE = 3.2 ms, flip angle = 12°, FOV = 220 mm × 220 mm, matrix = 256 × 256, slice thickness = 1.0 mm. Resting-state and a subsequent task-fMRI data were acquired using a gradient-echo EPI sequence with the following scan parameters: TR = 2,000 ms, TE = 30 ms, flip angle = 80°, FOV = 240 mm × 240 mm, matrix = 64 × 64, slice thickness = 3.0 mm, no gap, slice number = 43. The scan range covered the whole brain tissue extending from the frontal–parietal cortex to the lower parts of the cerebellum. Each resting-state scan consisted of 205 volumes and lasted 6 min 50 s. Participants were instructed to keep their eyes closed, stay as motionless as possible, think of nothing in particular, and not fall asleep. For task fMRI scans, participants underwent a block-designed hand motion task. There were three types of blocks: a task block addressing performance in the affected hand (the right hand for healthy subjects), a task block addressing performance in the unaffected hand (the left hand for healthy subjects), and a control block with rest. During a task block, the participant was instructed to tap their fingers using their affected or unaffected hand with a frequency of 1 Hz. Each task was repeated five times pseudo-randomly and a total of 15 blocks were included in one session. Each block lasted 20 s and one task scan lasted 5 min, consisting of 150 volumes.
MRI data preprocessing was conducted using SPM8
The first five images were removed to ensure steady-state longitudinal magnetization for rs-fMRI data. Then, slice-timing and realignment were performed for task- and rs-fMRI data. Translation or rotation parameters in any given data set did not exceed ±1.5 mm or ±1.5°. To avoid tissue misclassification caused by the infarcted tissue during image normalization, a cost-function method was used to remove the influence of lesions (
For task-data, and for each subject, the task conditions were convolved with the canonical hemodynamic response function and modeled as regressors in the general linear model. For each subject, the BOLD activation of each hand motion was estimated using a first-level analysis of variance (ANOVA) with task condition as the main factor: affected hand finger tapping task (AHFT) vs. control and unaffected hand finger tapping task (UHFT) vs. control. The
For rs-fMRI, the BOLD signal of each voxel was first detrended to eliminate the linear trend and then a temporal band pass filter (0.01–0.08 Hz) was used to reduce low-frequency drift and high-frequency physiological noise. Finally, sources of spurious variance, including head motion parameters, white matter signals, and cerebrospinal signals, were removed by linear regression. A seed-based RSFC analysis was then calculated with voxel-wise Pearson’s correlation using the REST toolkit (
To describe the features of “coupling” between motion-related activation and resting-state brain activity, we investigated the relationship between these two modalities within the sensorimotor region. We combined voxels within the ipsilesional brain regions of task-evoked activation (
In accordance with previous studies performing across-modality analysis (
The peak motion-related activation value of the AHFT and the peak RSFC strength, within the group-specific mask, were extracted for each patient. One-way repeated measures ANOVA and multiple comparisons (
One-way repeated measures ANOVA and multiple comparisons (
Pearson correlation analysis was used to investigate the relationships between functional imaging parameters (peak motion-related activation, peak RSFC strength, and coupling strength) and the UL-FMA score across the three stages.
There was a significant increase in UL-FMA scores during the longitudinal following (
The group motion-related activation maps of the AHFT and UHFT at each stage (
Changes of motion-related activation and resting-state functional connectivity (RSFC) in healthy controls and stroke patients across three stages of progression.
Comparative results of voxel-wise one-way repeated measures analysis of variance (ANOVA) (
Comparing results of the motion-related activation and RSFC of the ipsilesional sensorimotor cortex among three stages.
Motion-related activation |
RSFC |
|||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Peak MNI coordinate (mm) | Peak | Peak | Cluster size | Peak MNI coordinate (mm) | Peak | Peak | Cluster size | |||||
ANOVA | −33 | −21 | 51 | 14.72 | 273 | −30 | −24 | 63 | 10.03 | 20 | ||
Subacute vs. acute | −48 | −24 | 60 | −2.73 | 19 | −27 | 0 | 60 | −3.60 | 7 | ||
Early chronic vs. subacute | −30 | −21 | 51 | 4.31 | 769 | −30 | −24 | 57 | 4.31 | 113 | ||
Early chronic vs. acute | −48 | −18 | 57 | 5.32 | 1,338 | −39 | −18 | 54 | 3.79 | 72 |
The group RSFC maps of the ipsilesional sensorimotor cortex at each stage (
The coupling strength of the ipsilesional sensorimotor cortex at each time point was 0.52 ± 0.29, 0.54 ± 0.29, and 0.72 ± 0.16, respectively. The coupling strength increased significantly following motor function recovery (
Alterations of coupling strength between motion-related activation and resting-state functional connectivity within the group-specific mask in healthy controls and stroke patients among three stages of progression. Upper row: changes in coupling strength across the three stages (
The results of the cross-subject correlation analysis for the three stages are shown in Figure
The results of across-subject correlation analysis at the three stages.
Peak MNI coordinate (mm) |
Peak |
Cluster size | |||
---|---|---|---|---|---|
Acute stage | −27 | −24 | 54 | 0.67 | 68 |
Subacute stage | −39 | −24 | 60 | 0.73 | 143 |
Early chronic stage | −36 | −27 | 54 | 0.76 | 222 |
Changes in the correlation coefficient between peak motion-related activation, peak RSFC strength, coupling strength, and the UL-FMA score during the three different stages are shown in Figure
Alterations in the correlation coefficient between functional parameters [peak motion-related activation, peak resting-state functional connectivity (RSFC), and coupling strength] and Upper Limb Fugl-Meyer Assessment (UL-FMA) at the corresponding stage of progression. The peak motion-related activation and coupling strength during the acute stage was positively correlated to the UL-FMA scores at the corresponding stage (
Relationship between functional imaging parameters and clinical outcome.
This study, for the first time, described the relationship between hand motion induced activation and RSFC in stroke patients by combining task-based fMRI and rs-fMRI. Our main novel findings were as follows: (1) compared with healthy controls, stroke patients showed reduced motion-related activation and coupling strength during the acute and subacute stages; (2) compared with the acute stage, motion-related activation and RSFC strength significantly increased in the ipsilesional sensorimotor cortex during the early chronic stage; and (3) coupling strength between motion-related activation and RSFC in the ipsilesional sensorimotor cortex was significantly increased following motor function recovery from the acute stage to the early chronic stage in stroke patients with motor impairment. Moreover, alterations in coupling strength were associated with motor recovery. Collectively, these findings indicated that the coupling relationship between task-based fMRI and rs-fMRI in stroke patients was influenced by different stages of pathological progression.
As two main functional imaging parameters, task-based fMRI and rs-fMRI can both provide useful information relating to cortical reorganization in stroke patients. In accordance with previous research (
In this study, a change in time-dependent coupling was identified between motion-related activation and RSFC in the ipsilesional sensorimotor cortex following the recovery of hand motor function. This finding further strengthens the viewpoint that functional restoration of the ipsilesional sensorimotor cortex is a key process for effective recovery of motor function (
Although the specific relationships between rs-fMRI and task-based fMRI still remain unclear, recent research has suggested that rs-fMRI and task-based fMRI signals might be governed by a common physiological mechanism (
Previous studies have indicated that the changes of functional imaging parameters in the first few days after stroke were sensitive enough to predict subsequent motor function outcome (
There are some limitations to this study which need to be considered when interpreting our conclusions. First, although only patients with single stroke lesion within the territory of the middle cerebral artery were enrolled, the relative heterogeneity in lesion volume might have impacted upon the results of our study. Second, due to the differences in motor impairment, there may be disparity in terms of task performance for each patient. Although the task performance of each patient was visually monitored during the fMRI scan, inconsistencies in task performance may have influenced the results relating to motion-related activation. Third, although we adopted a longitudinal study design, a 3-month follow-up period, with three time points, is relatively short. A longer follow-up period, with a greater number of time points, will be helpful in fully elucidating the relationship between task-based fMRI and rs-fMRI in future studies.
In summary, in this study, we first illustrated the altered coupling between motion-related activation and RSFC in the ipsilesional sensorimotor cortex for stroke patients with hand motor impairment. Our findings demonstrated that coupling strength gradually increased following motor recovery after stroke. We also identified a clear linear relationship between the alterations in coupling patterns and motor recovery scores. These findings further extend our understanding of the role played by the ipsilesional sensorimotor cortex in the process of motor recovery following stroke. Generally, monitoring the coupling alteration between motion-related activation and RSFC in the ipsilesional sensorimotor cortex may be a complementary tool for evaluating and predicting motor recovery in stroke patients with motor impairment.
This study was approved by the Internal Review Board of Jinling Hospital and written informed consent was obtained from each participant.
ZZ and GL conceived and designed the research. JD, JH, QX, FY, FZ, X-jD, and XL recruited the subjects, collected the data, performed the analysis, and generated the images. JH and ZZ wrote the paper. All authors read and approved the final draft.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The Supplementary Material for this article can be found online at
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