Background & Aims
Central Neuropathic Pain (CNP) is a debilitating chronic condition that affects approximately half of individuals with spinal cord injury (SCI). It is often described as the worst consequence after SCI and significantly limits functionality and rehabilitation, as well as increasing suicide risk. Current treatments for CNP are limited, and the underlying mechanisms of this condition are poorly understood.
One of the rising research directions in pain study in the recent years is the examination of flexibility as a resilience driver in pain prevention and management. While behavioral and cognitive flexibility have already been associated with resilience to pain, our study suggests a way to examine the association of systematic flexibility of brain connections with resilience to pain. We hypothesized that whole brain inter-region dynamic connectivity will be more flexible and have more variabilty in its shifts in individuals without CNP compared to those with CNP.
Methods
36 individuals with spinal cord injury were recruited from the neurological rehabilitation center, 24 with CNP and 12 without CNP. The participants underwent an fMRI resting-state scan, which was then pre-processed and analyzed using data-driven dynamic functional connectivity tools.
First, we used group independent components analysis to decipher independent sources of signal across the whole brain. Components then underwent selection for noise-sourced components which left 42 neural-sourced components, which then were labeled in accordance with their respective functional roles.
The 10 minute scan was then broken into many short sliding windows of 44 seconds, each constituting a 42X42 matricx of connectivity. Then, the windows were clustered into meta-states of connectivity using k-means mathematical methods.
The groups with and without CNP were then statistically compared in transition and variability of moving between states using independent sample t-tests.
Results
As hypothesized, we found that the group without CNP showed more frequent transitions between connectivity states (T=2.381, p-value= 0.013) and more diverse states visited (T=2.133, p-value=0.032) compared to the group with CNP.
Additionally, we found significant differences between the groups in the mean time spent in specific connectivity states. The group without CNP spent significantly more time in a state chacterized by negative dosrolateral-medial prefrontal connectivity compared to the group with CNP. Conversely, the group with CNP spent significantly more time in a state characterized by positive medial prefrontal- Insular connectivity, compared to the group without CNP.
Conclusions
Our results have shown that individuals who did not develop post-SCI CNP presented much more frequent and diverse transitions between connectivity patterns compared to those with post-SCI CNP, suggesting a connectivity flexibility marker of resilience. This resonates with previous studies that showed cognitive and behavioral flexibility as predictors of resilience to different aspects of pain.
This result can serve both as a biomarker predictor of developing CNP if tested in the acute phase. Moreover, It can serve as basis for personalized treatment plan, if used for example, to guide Transcranial magnetic simulation treatment, by use of network control theory to guide the treatment in moving between desired states and transition patterns.
References
– N. A. Silva, N. Sousa, R. L. Reis, A. J. Salgado, From basics to clinical: A comprehensive review on spinal cord injury. Prog. Neurobiol. 114, 25–57 (2014)
– N. B. Finnerup, Neuropathic pain and spasticity: Intricate consequences of spinal cord injury. Spinal Cord 55, 1046–1050 (2017).
-C. E. Hulsebosch, Central neuropathic pain after spinal cord injury: Therapeutic opportunities. A brief history and temporal progression of the pathophysiology from acute trauma to chronic conditions (Elsevier Inc., 2022) https:/doi.org/10.1016/B978-0-12-818662-6.00002-9.
– Hutchison RM, Womelsdorf T, Allen EA, et al. Dynamic functional connectivity: Promise, issues, and interpretations. Neuroimage. 2013;80:360-378. doi:10.1016/j.neuroimage.2013.05.079
– Kucyi A, Davis KD. The dynamic pain connectome. Trends Neurosci. 2015;38(2):86-95. doi:10.1016/j.tins.2014.11.006
– Uddin LQ. Cognitive and behavioural flexibility: neural mechanisms and clinical considerations. Nat Rev Neurosci. 2021;22(3):167-179. doi:10.1038/s41583-021-00428-w
– Damaraju, E., Allen, E. A., Belger, A., Ford, J. M., McEwen, S., Mathalon, D. H., … & Calhoun, V. D. (2014). Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia. NeuroImage: Clinical, 5, 298-308.
Presenting Author
Yvgeny Lerer
Poster Authors
Topics
- Assessment and Diagnosis