Translingual neural stimulation induces brain network changes in patients with mild-to-moderate TBI
Poster No:
373
Submission Type:
Abstract Submission
Authors:
Daniel Chu1, Jiancheng Hou2, Veena Nair1, Nagesh Adluru1, Yuri Danilov1, Kurt Kaczmarek1, Mary Meyerand1, Mitchell Tyler1, Vivek Prabhakaran1
Institutions:
1University of Wisconsin-Madison, Madison, WI, 2Fujian Normal University, Fuzhou, Fujian
First Author:
Co-Author(s):
Introduction:
Traumatic brain injury (TBI) is a form of external acquired injury to the brain and is commonly associated with cognitive, emotional, social, and physical deficits (McDonald, 2013). A general deficit to the mild-to-moderate TBI (mmTBI) is balance injuries (Li et al., 2013). Translingual neural stimulation (TLNS), provided via the Portable Neuromodulation Stimulator, is a novel therapeutic intervention that combines the superficial electrical stimulation of facial and trigeminal nerves with physical therapy that focuses on reduction of balance and gait deficits (Danilov et al., 2015). A recent seed-based resting-state functional connectivity (RSFC) study demonstrated positive effects of TLNS on brain plasticity of somatosensory input, visual-vestibular interaction, and balance control in mmTBI patients (Hou et al., 2022). However, the alterations within and between whole-brain functional networks affected by TLNS on mmTBI patients are still unclear. The current study aims to examine the network FC changes and its correlations to behavioral testings of gait and balance between pre- and post-TLNS intervention in mmTBI patients.
Methods:
The current study included RS-fMRI dataset collected by 3T MRI scanner with nine mmTBI patients. An experimental PoNS device (V2.5) was utilized to deliver the TLNS. All participants received both Sensory Organization Test (SOT) and Dynamic Gait Index (DGI) testing pre- and post-intervention as part of the behavioral assessment. Preprocessing for RS-fMRI data (pr- and post-intervention, respectively, for each patient) was performed using the Data Processing and Analysis of Brain Imaging (DPABI) toolbox (V6.0, http://rfmri.org/dpabi) (Yan et al., 2016), which includes slice timing, realignment, regressing out head motion parameters, normalization and smoothing. The symmetric correlation matrices for a 160 x 160 (25,600 unique pariwise) network FC was generated by the Dosenbach atlas. Paired t-test between post- vs. pre- intervention was performed to compare network FC changes. False discovery rate (FDR) corrected p < .05 was used for multiple comparisons correction. Moreover, the correlation analysis between SOT change (or DGI; post- minus pre-) and network FC change (post- minus pre-) was corrected at p < .05 with SPSS V23.
Results:
Compared to pre-intervention, the post-intervention induced significantly increased: (1) behavioral scores on SOT and DGI; (2) intra-network FC in the somatosensory network (SMN), default mode network (DMN), frontoparietal network (FPN), visual network (VN) and dorsal attention network (DAN); (3) inter-network FC between the SMN and FPN (see Figures 1 and Table 1). Moreover, the behavioral SOT change had significantly negative correlation with the inter-network FC change between SMN and FPN, while the behavioral DGI change had significantly positive correlation with the intra-network FC change within SMN.
·Figure 1. The matrix of network functional connectivity (FC) differences between post- vs. pre-intervention. Color bar represents Fisher’s z-transformed Pearson correlation coefficient.
·Table 1. The significant network functional connectivity differences between post- vs. pre-intervention
Conclusions:
The increased intra- and inter-network FC at SMN and FPN indicate that TLNS intervention is an effective in increasing somatosensory processing, vestibular-visual interaction, executive control and flexible shifting (Li et al., 2021). The increased intra-network FC at VN, DAN and DMN refers to improved visual attention, motor perception, control monitoring, goal-directed tasks, visual-guided actions and cognitive control (Yan et al., 2019). Moreover, the positive correlation between intra-SMN change and behavioral DGI change illustrates the association with increased network FC and behavioral improvement that relates to gait and stability. However, the negative correlation between inter-FPN and SMN change and behavioral SOT change indicates the association with less FC alteration but greater cognitive efficiency such as somatosensory, vision, or vestibular balance. In conclusion, the present study shows evidence that TLNS is an effective approach to improve balance and gait abilities, which also induce brain network plasticity, in mmTBI patients.
Brain Stimulation:
Non-invasive Magnetic/TMS
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Keywords:
FUNCTIONAL MRI
Movement Disorder
Plasticity
Trauma
1|2Indicates the priority used for review
Provide references using author date format
Hou, J. et al. (2022), ‘Translingual neural stimulation affects resting-state functional connectivity in mild-moderate traumatic brain injury’, Journal of Neuroimaging, vol. 32, no. 6, pp. 1193-1200.
Li, L. et al. (2021), ‘Eight-week antidepressant treatment reduces functional connectivity in first-episode drug-naive patients with major depressive disorder’, Human Brain Mapping, vol. 42, pp. 2593-2605.
Li, Y. et al. (2013), ‘Individual structural differences in left inferior parietal area are associated with school childrens' arithmetic scores’, Frontiers in Human Neuroscience, vol. 7, pp. 844.
McDonald, S. (2023), ‘Impairments in social cognition following severe traumatic brain injury’, Journal of International Neuropsychology, vol. 19, pp. 231-246.
Yan, C. et al. (2016), ‘DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging’, Neuroinformatics, vol. 14, pp. 339-351.
Yan, C. et al. (2019), ‘Reduced default mode network functional connectivity in patients with recurrent major depressive disorder’, Proceedings of the National Academy of Sciences, vol. 116, pp. 9078-9083.