Increased Brain Sensorimotor Network Activation after Incomplete Spinal Cord Injury

Abstract

After complete spinal cord injury (SCI), activation during attempted movement of paralyzed limbs is sharply reduced, but after incomplete SCI-the more common form of human injury-it is unknown how attempts to move voluntarily are accompanied by activation of brain motor and sensory networks. Here, we assessed brain activation during ankle movement in subjects with incomplete SCI, among whom voluntary motor function is partially preserved. Adults with incomplete SCI (n = 20) and healthy controls (n = 15) underwent functional magnetic resonance imaging that alternated rest with 0.3-Hz right ankle dorsiflexion. In both subject groups, ankle movement was associated with bilateral activation of primary and secondary sensory and motor areas, with significantly ( p < 0.001) greater activation in subjects with SCI within right hemisphere areas, including primary sensorimotor cortex and pre-motor cortex. This result was further evaluated using linear regression analysis with respect to core clinical variables. Poorer locomotor function correlated with larger activation within several right hemisphere areas, including pre-and post-central gyri, possibly reflecting increased movement complexity and effort, whereas longer time post-SCI was associated with larger activation in left post-central gyrus and bilateral supplementary motor area, which may reflect behaviorally useful adaptations. The results indicate that brain adaptations after incomplete SCI differ sharply from complete SCI, are related to functional behavioral status, and evolve with increasing time post-SCI. The results suggest measures that might be useful for understanding and treating incomplete SCI in human subjects.

Spinal Cord Injury Disrupts Resting-State Networks in the Human Brain

“…First, the sample size of the SCI subjects was low. Although the results in this study corroborate and extend knowledge shown by other researchers, 17,19,21,27,74,75 future studies with larger sample sizes must be performed as validation. Second, the sex ratios for the control groups and the SCI groups were not matched.…”

“…Although most attention and effort have focused on direct imaging of the spinal cord, there has been limited work on the effects of SCI on the brain. [17][18][19][20][21][22][23] A large network of circuits makes up ascending spinal cord tracts to the brain and includes the dorsal column, and the spinothalamic, spinocerebellar, cuneocerebellar, and spinoreticular tracts. 24 Select reports have suggested that SCI affects the brain and brain networks.…”

“…24 Select reports have suggested that SCI affects the brain and brain networks. 17,19,21,[25][26][27][28][29] For example, SCI has been associated with atrophy of cerebral white matter tracts, and the atrophy has been shown to correlate with performance. 29 Here, we show that SCI produced significant changes in select brain RS-fMRI networks.…”

“…19 Sharp and colleagues performed task-based fMRI on incomplete SCI subjects and found that patients with incomplete SCI had increased activation of ipsilateral post-central gyrus compared with controls. 21 Most recently, Kaushal and colleagues performed a graph-theory study of efficiency after remote complete SCI, and found that there were changes in whole-brain connectivity and in connectivity between the cerebellum and the cortex. 17 Here, we performed a seed-based correlation mapping using canonical RSNs in complete and incomplete SCI subjects.…”

Evaluating observed versus predicted forest biomass: R-squared, index of agreement or maximal information coefficient?

“…Alternatives have been proposed, such as the index of agreement (d), which can be interpreted as the relative prediction error (Willmott, 1981;Willmott & Wicks, 1980). Ever since, it has been popular in a variety of fields such as hydrology (Legates & McCabe, 1999;López-Moreno, Latron, & Lehmann, 2010), agriculture (Nendel et al, 2013), neurology (Ganpule et al, 2017), meteorology (Aschonitis et al, 2017;Morsy, El-Sayed, & Ouda, 2016), forest ecology (Ibrom et al, 2007;Ward, Bell, Clark, & Ram, 2013), or climate change (Bring & Destouni, 2014;Gaitan, Hsieh, & Cannon, 2014;Oyler, Ballantyne, Jencso, Sweet, & Running, 2015). The use of Willmott's d in remote sensing literature has, however, been marginal (Almeida et al, 2016;García et al, 2010;Grzegozewski, Johann, Uribe-Opazo, Mercante, & Coutinho, 2016;Wachholz de Souza, Mercante, Johann, Camargo Lamparelli, & Uribe-Opazo, 2015;Yebra & Chuvieco, 2009).…”