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. 2014 Dec 16;111(50):18067-72.
doi: 10.1073/pnas.1414293111. Epub 2014 Dec 3.

Intrinsically organized resting state networks in the human spinal cord

Affiliations

Intrinsically organized resting state networks in the human spinal cord

Yazhuo Kong et al. Proc Natl Acad Sci U S A. .

Abstract

Spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals of the brain have repeatedly been observed when no task or external stimulation is present. These fluctuations likely reflect baseline neuronal activity of the brain and correspond to functionally relevant resting-state networks (RSN). It is not known however, whether intrinsically organized and spatially circumscribed RSNs also exist in the spinal cord, the brain's principal sensorimotor interface with the body. Here, we use recent advances in spinal fMRI methodology and independent component analysis to answer this question in healthy human volunteers. We identified spatially distinct RSNs in the human spinal cord that were clearly separated into dorsal and ventral components, mirroring the functional neuroanatomy of the spinal cord and likely reflecting sensory and motor processing. Interestingly, dorsal (sensory) RSNs were separated into right and left components, presumably related to ongoing hemibody processing of somatosensory information, whereas ventral (motor) RSNs were bilateral, possibly related to commissural interneuronal networks involved in central pattern generation. Importantly, all of these RSNs showed a restricted spatial extent along the spinal cord and likely conform to the spinal cord's functionally relevant segmental organization. Although the spatial and temporal properties of the dorsal and ventral RSNs were found to be significantly different, these networks showed significant interactions with each other at the segmental level. Together, our data demonstrate that intrinsically highly organized resting-state fluctuations exist in the human spinal cord and are thus a hallmark of the entire central nervous system.

Keywords: connectivity; fMRI; networks; resting state; spinal cord.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Dorsal (sensory) RSNs. These networks were identified using a group ICA in a restricted region that just included the spinal cord. (Left) A sagittal section of our T1-weighted template depicting the location of the displayed transversal sections (gray lines) from C4 to T1 as well as the excellent overlap with the group spinal cord mask (yellow). (Right) The dorsal RSNs are arranged in anatomical level order with each column corresponding to one component. Both the restricted rostro-caudal extension of each component and the unilateral occurrence are clearly evident. Each RSN map is thresholded at FDR P < 0.05 and shown in rostral-caudal direction with the component ranking number at the bottom. Note that component ordering is based on the amount of variance each component explains (in decreasing order).
Fig. 2.
Fig. 2.
Ventral (motor) RSNs. These networks were identified using a group ICA in a restricted region that just included the spinal cord. (Left) A sagittal section of our T1-weighted template depicting the location of the displayed transversal sections (gray lines) from C4 to T1 as well as the excellent overlap with the group spinal cord mask (yellow). (Right) The ventral RSNs are arranged in anatomical level order with each column corresponding to one component. Both the restricted rostro-caudal extension of each component and the mostly bilateral occurrence are clearly evident. Each RSN map is thresholded at FDR P < 0.05 and shown in rostral-caudal direction with the component ranking number at the bottom. Note that component ordering is based on the amount of variance each component explains (in decreasing order).
Fig. 3.
Fig. 3.
Intrinsic properties of visually identified RSNs. Depicted are comparisons of the spatial map regression coefficients (representing the degree of coactivation) and the component time series SD (representing the component strength). We observed significant differences for both metrics between dorsal and ventral RSNs (A and C), but not between left and right dorsal RSNs (B and D); note that the laterality analysis could not be done for ventral RSNs as these were predominantly bilateral. Error bars represent standard deviation.
Fig. 4.
Fig. 4.
RSN correlation matrix. This correlation matrix contains the full correlations between the time-courses of all visually identified dorsal and ventral components (see SI Appendix, Fig. S9 for partial correlations). Components were arranged in rostro-caudal anatomical order, similar to Figs. 1 and 2. For both dorsal and ventral RSNs, components are positively correlated at the same rostro-caudal level, but not correlated or even slightly negatively correlated to other levels. Interestingly, dorsal and ventral networks of the same level are positively correlated (box in lower left corner; except for T1 – component 4 and 36). Asterisks indicate correlations significant at P < 0.05 (FWE corrected using nonparametric permutation testing). Note that component ordering is based on the amount of variance each component explains (in decreasing order).

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