Synopsis

A subgroup of patients with mild traumatic brain injury (mTBI) suffer from a series of post-concussion symptoms, such as headache, dizziness, and cognitive deficits. These patients also present altered neural connectivity compared to healthy controls (HC). In our study, we examined resting-state functional connectivity in 30 mTBI patients and 35 HC using independent component analysis. We found that patients showed lower functional connectivity in several resting-state networks, and the left frontoparietal network was associated with the level of dizziness in patients. We concluded that the alterations of resting-state neural networks may support post-concussion symptoms after mTBI.

Introduction

Methods

Participants: We included 35 healthy controls (HC) and 30 mTBI patients within 1 month of their injury. Patients with suspected intracranial hemorrhage were excluded. All participants signed informed consent forms approved by the institutional review board.

Psychological assessment: Before the acquisition of MRI data, participants performed self-report questionnaires, including Rivermead Post Concussion Symptoms Questionnaire(PCSQ) with three sub-domains³ (i.e., cognitive, emotion, and somatic), and Dizziness Handicap Inventory (DHI) with three sub-domains⁴ (i.e., functional, emotional, and physical). Participants’ cognitive functions were examined using Wechsler Adult Intelligence Scale (WAIS)-IV. The Working Memory index (WM) and Processing Speed index (PS) were calculated to represent the executive control abilities⁵.

MR acquisition: Images were acquired on a 3T MRI scanner (MAGNETOM Prisma, Siemens) using a 20-channel head coil. Structural 3D T1-weighted images were acquired using magnetization-prepared rapid acquisition with gradient echo (MPRAGE) sequence, with the following parameters: repetition time (TR)=2300ms, echo time (TE)=3.3ms, flip angle (FA)=8˚, 176 axial slices, field of view (FOV)=256×256×176mm³, voxel size=1x1x1mm³. During the resting-state functional images session, 190 echo-planar imaging (EPI) scans were acquired using the following parameters: TR=2000ms, TE=20ms, FA=90˚, 40 axial slices with slice thickness=3.5mm, FOV=210×210mm², voxel size=3.0x3.0x3.5mm³. In this scan session, participants were presented with a central fixation and instructed to stay awake with their eyes open.

Preprocessing: Preprocessing was conducted with SPM12 software which was implemented within MATLAB R2013b (The MathWorks, Inc., Natick, Massachusets, USA). The first 10 functional scans were discarded. The 180 functional scans were corrected for slice-timing and head motion. The structural scan was coregistrated to the mean image of realigned functional scans. The functional scans were normalized into MNI space using the function “old normalize” in SPM12, and then spatially smoothed using 6-mm full-width at half maximum (FWHM) Gaussian kernel.

Independent component analysis (ICA): The group spatial ICA was performed for all 65 participants using the GIFT software version 3.0b (http://mialab.mrn.org/software/gift/). The functional data were decomposed into 24 independent components with the infomax algorithm⁶. Single subject time courses and spatial maps were back-reconstructed. Finally, the spatial maps of components for each subject were z-transformed into ICA z-maps.

Statistics: One-sample T tests in each ICA z-map were performed to create binary component masks followed by the two-sample T tests in each ICA z-map for group comparison. Finally, partial correlation analyses between behavioral measures related to post-concussion symptoms and averaged z-value of components that revealed significant group differences were performed for the mTBI group, controlling for age, sex, and duration between injury and scanning date.

Results

Behaviors: Demographics and psychological assessment results are presented in Table 1. Compared to the HC, the mTBI showed higher PCSQ and DHI in either total scores or sub-domain scores. However, the WM and PS revealed no group difference.

Group ICA: We found 10 independent components showing significant differences between mTBI and HC. The spatial patterns of these components were extracted from results of one-sample T tests and shown in Fig.1. The group differences in each component are depicted in Fig.2 and listed in Table 2. Compared to the HC, the mTBI showed lower functional connectivity in 8 components, but showed higher functional connectivity in only 2 components.

Behaviors-ICs relationships: In partial correlation analyses, the physical sub-domain of DHI is negatively correlated with averaged z-value of left FPN (partial r=-0.400, p=0.039). Furthermore, the PS is positively correlated with averaged z-values of VAN (partial r=0.401, p=0.038) and of ECN-1 (partial r=0.434, p=0.024).

Discussion

Acknowledgements

References

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