Structural abnormalities of right fronto-parietal control network brain regions in migraineurs
Poster No:
2291
Submission Type:
Abstract Submission
Authors:
Xinrui Li1, Yue Zhang2, Xia Liu1, Yihe Zhang1, Yidan Qiu1, Xiaoqi Peng1, Ruiwang Huang1
Institutions:
1School of Psychology, Key Laboratory of Brain, South China Normal University, Guangzhou, Guangdong, 2Department of Radiology, Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
First Author:
Xinrui Li
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Co-Author(s):
Yue Zhang
Department of Radiology, Second Affiliated Hospital of Guangzhou University of Chinese Medicine
Guangzhou, China
Department of Radiology, Second Affiliated Hospital of Guangzhou University of Chinese Medicine
Guangzhou, China
Xia Liu
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Yihe Zhang
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Yidan Qiu
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Xiaoqi Peng
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Ruiwang Huang
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
School of Psychology, Key Laboratory of Brain, South China Normal University
Guangzhou, Guangdong
Introduction:
Migraine is a paroxysmal neurological disorder, accompanying with various symptoms, such as photophobia[1] and altered cognition[2]. The etiology of migraine remains unclear. Researches have focused mainly on neurophysiological mechanisms. Previous studies have found abnormal resting-state functional connectivity in the right fronto-parietal network (rFCN) in migraine patients[3]. The rFCN is mainly responsible for somatosensory and cognitive control[4], including the dorsolateral prefrontal cortex (dlPFC), insula, middle frontal gyrus (MFG) and supramarginal gyrus (SMG). However, few studies have found abnormal structure in the rFCN-related brain regions. The present study aims to investigate the structural changes in the rFCN-related brain regions in migraine patients, providing physiologic evidence of abnormalities in patients' somatosensory abilities.
Methods:
Participants
Twenty-five migraine patients (2M/23F, age 31.32 ± 8.38 years old) and 24 healthy controls (9M/15F, age 25.33 ± 4.46 years old) were recruited from the 2nd Affiliated Hospital of Guangzhou University of Chinese Medicine. The inclusion criteria for patients were as follows: (1) episodic migraine without aura, (2) 18-45 years old, (3) right-handed, (4) disease duration ≥ 6 months, and (5) attack frequency ≥ 1 day every month. Written informed consent was obtained from each subject before this study.
Data acquisition
All MRI data were obtained on a 3.0 T Siemens Verio MRI scanner with a 24-channel phased array head coil. The high resolution brain structural images were acquired using a T1-weighed 3D MP-RAGE sequence with the following parameters: repetition time (TR) = 1,900 ms, echo time (TE) = 2.27 ms, flip angle (FA) = 9°, data matrix = 256 × 256, field of view (FOV) = 256 mm × 256 mm, slice thickness = 1 mm, and 176 sagittal slices covering the whole brain.
Data analysis
The structural MRI data were preprocessed using FreeSurfer, mainly including removal of non-brain tissue, segmentation of white and gray matter, intensity normalization, tessellation of the gray/white matter boundary. We used two separate general linear models (GLM) to explore the differences in gray matter volume (GMV) and cortical thickness (CT) between the migraine patients and healthy subjects. In the calculations, We took age as a nuisance covariate. Statistical significant threshold was set at the vertex-level p < 0.001 with family wise error (FWE) correction at the cluster-level of p < 0.05. we applied partial correlation analysis to explore the relationship between the altered CT and Migraine Specific Quality-of-Life Questionnaire (MSQ) score in the migraineurs, taking age as nuisance covariate.
Twenty-five migraine patients (2M/23F, age 31.32 ± 8.38 years old) and 24 healthy controls (9M/15F, age 25.33 ± 4.46 years old) were recruited from the 2nd Affiliated Hospital of Guangzhou University of Chinese Medicine. The inclusion criteria for patients were as follows: (1) episodic migraine without aura, (2) 18-45 years old, (3) right-handed, (4) disease duration ≥ 6 months, and (5) attack frequency ≥ 1 day every month. Written informed consent was obtained from each subject before this study.
Data acquisition
All MRI data were obtained on a 3.0 T Siemens Verio MRI scanner with a 24-channel phased array head coil. The high resolution brain structural images were acquired using a T1-weighed 3D MP-RAGE sequence with the following parameters: repetition time (TR) = 1,900 ms, echo time (TE) = 2.27 ms, flip angle (FA) = 9°, data matrix = 256 × 256, field of view (FOV) = 256 mm × 256 mm, slice thickness = 1 mm, and 176 sagittal slices covering the whole brain.
Data analysis
The structural MRI data were preprocessed using FreeSurfer, mainly including removal of non-brain tissue, segmentation of white and gray matter, intensity normalization, tessellation of the gray/white matter boundary. We used two separate general linear models (GLM) to explore the differences in gray matter volume (GMV) and cortical thickness (CT) between the migraine patients and healthy subjects. In the calculations, We took age as a nuisance covariate. Statistical significant threshold was set at the vertex-level p < 0.001 with family wise error (FWE) correction at the cluster-level of p < 0.05. we applied partial correlation analysis to explore the relationship between the altered CT and Migraine Specific Quality-of-Life Questionnaire (MSQ) score in the migraineurs, taking age as nuisance covariate.
Results:
Fig. 1 shows that migraine patients had a significantly increased CT in the right supramarginal gyrus. The CT in the SMG was significantly and positively correlated with MSQ scale scores in the migraine subjects (r = 0.484, p = 0.017). We also found that the patients had a significantly increased GMV in the cMFG and rMFG, and a significantly reduced GMV in the precuneus compared with healthy controls. The detailed information is listed in Tables 1 and 2.
Conclusions:
The current study found cortical thickening in SMG in the migraine patients compared with the healthy controls, and the degree of cortical thickening is significantly positively correlated with the severity of the disease. Moreover, we found an increased GMV in the middle frontal region and a decreased GMV in the precuneus in the migraine patients, which are responsible for higher cognitive functions. We found structural changes in brain regions belonging to the rFCN, which may be related to abnormalities in sensory and cognitive control in migraine patients. The frontal-parietal control network (FPN) is a lateralized network. The left frontoparietal network is mainly responsible for language processing. We did not find similar structural change results in the left brain, which could also provide evidence for lateralization of the FCN.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 2
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making
Modeling and Analysis Methods:
Segmentation and Parcellation
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems
Novel Imaging Acquisition Methods:
Anatomical MRI 1
Keywords:
STRUCTURAL MRI
Other - Migraine, frontoparietal network
1|2Indicates the priority used for review
Provide references using author date format
Haupt, M. and A. L. Ruiz-Rizzo, et al. (2020). "Right-lateralized fronto-parietal network and phasic alertness in healthy aging." Sci Rep 10 (1): 4823.
Huang, L. and D. H. Juan, et al. (2017). "Duration and frequency of migraines affect cognitive function: evidence from neuropsychological tests and event-related potentials." J Headache Pain 18 (1): 54.
Li, Z. and L. Lan, et al. (2017). "The altered right frontoparietal network functional connectivity in migraine and the modulation effect of treatment." Cephalalgia 37 (2): 161-176.