scholarly journals A longitudinal study of white matter functional network in mild traumatic brain injury

2020 ◽  
Author(s):  
Xiaoyan Jia ◽  
Xuebin Chang ◽  
Lijun Bai ◽  
Yulin Wang ◽  
Debo Dong ◽  
...  

AbstractThe mild traumatic brain injury (mTBI) results in traumatic axonal injury, which damages the long-distance white matter (WM) connections and thus disrupts the functional connectome of large-scale brain networks that support cognitive function. Patterns of WM structural damage following mTBI were well documented using diffusion tensor imaging, however, the functional organization of WM and its association with grey matter functional networks (GM-FNs) and cognitive assessments remains unknown. The present study adopted resting-state functional magnetic resonance imaging to explore WM functional properties in mTBI patients (113 acute patients, 56 chronic patients, 47 healthy controls (HCs)). Eleven large-scale WM functional networks (WM-FNs) were constructed by the k-means clustering algorithm which carried out in voxel-wise WM functional connectivity (FC). Compared to HCs, acute mTBI patients showed enhanced FC between inferior fronto-occipital fasciculus (IFOF) WM-FN and primary sensorimotor WM-FNs, and cortical primary sensorimotor GM-FNs. And FC between IFOF WM-FN and anterior cerebellar GM-FN was positively correlated with information processing speed. Moreover, all of these WM-FNs abnormalities were returned to the normal level at the chronic stage. Our findings suggest the compensatory mechanism of cognitive deficits in the acute stage and its involvement in facilitating recovery from cognitive deficits in the chronic stage. The convergent damage of the IFOF network highlighted its key role in our understanding of the pathophysiology mechanism of mTBI patients and thus might be regarded as a biomarker in the acute stage and a potential indicator of treatment effect.

PLoS ONE ◽  
2016 ◽  
Vol 11 (3) ◽  
pp. e0151489 ◽  
Author(s):  
Zhongqiu Wang ◽  
Wenzhong Wu ◽  
Yongkang Liu ◽  
Tianyao Wang ◽  
Xiao Chen ◽  
...  

Brain Injury ◽  
2016 ◽  
Vol 30 (12) ◽  
pp. 1501-1514 ◽  
Author(s):  
Ramtilak Gattu ◽  
Faith W. Akin ◽  
Anthony T. Cacace ◽  
Courtney D. Hall ◽  
Owen D. Murnane ◽  
...  

Brain Injury ◽  
2013 ◽  
Vol 27 (12) ◽  
pp. 1415-1422 ◽  
Author(s):  
Areeba Adnan ◽  
Adrian Crawley ◽  
David Mikulis ◽  
Morris Moscovitch ◽  
Brenda Colella ◽  
...  

Brain ◽  
2014 ◽  
Vol 137 (7) ◽  
pp. 1876-1882 ◽  
Author(s):  
Tero Ilvesmäki ◽  
Teemu M. Luoto ◽  
Ullamari Hakulinen ◽  
Antti Brander ◽  
Pertti Ryymin ◽  
...  

2017 ◽  
Vol 34 (2) ◽  
pp. 291-299 ◽  
Author(s):  
Juan J. Herrera ◽  
Kurt Bockhorst ◽  
Shakuntala Kondraganti ◽  
Laura Stertz ◽  
João Quevedo ◽  
...  

2021 ◽  
Author(s):  
Paulo Branco ◽  
Noam Bosak ◽  
Jannis Bielefeld ◽  
Olivia Cong ◽  
Yelena Granovsky ◽  
...  

Mild traumatic brain injury, mTBI, is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute post-injury pain is important since it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 172 patients with mTBI, following a motorized vehicle collision and used a machine learning approach to extract white matter structural and resting state fMRI functional connectivity measures to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamic-cortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in two independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6-months after the collision still predicted mTBI pain at that timepoint (n = 36). These white-matter connections were associated with two nociceptive psychophysical outcomes tested at a remote body site – namely conditioned pain modulation and magnitude of suprathreshold pain–, and with pain sensitivity questionnaire scores. Our validated findings demonstrate a stable white-matter network, the properties of which determine a significant amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.


2016 ◽  
Vol 33 (22) ◽  
pp. 2000-2010 ◽  
Author(s):  
Elisabeth A. Wilde ◽  
Xiaoqi Li ◽  
Jill V. Hunter ◽  
Ponnada A. Narayana ◽  
Khader Hasan ◽  
...  

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