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Resting state functional connectivity in the human spinal cord.

Barry RL, Smith SA, Dula AN, Gore JC - Elife (2014)

Bottom Line: Functional magnetic resonance imaging using blood oxygenation level dependent (BOLD) contrast is well established as one of the most powerful methods for mapping human brain function.However, to date there have been no previous substantiated reports of resting state correlations in the spinal cord.In a cohort of healthy volunteers, we observed robust functional connectivity between left and right ventral (motor) horns, and between left and right dorsal (sensory) horns.

View Article: PubMed Central - PubMed

Affiliation: Vanderbilt University Institute of Imaging Science, Nashville, United States Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, United States robert.l.barry@vanderbilt.edu.

No MeSH data available.


Related in: MedlinePlus

A single-subject analysis of resting state functional connectivity with corresponding time series.For clarity, only outlines of the gray matter butterfly and surrounding white matter are shown (rostro-caudal from left to right). Red and yellow represent statistically significant positive correlation with the seed time series (using a two-sided 99.9% confidence interval where red is 3.29 < z ≤ 3.89 and yellow is z > 3.89), and blue represents negative correlation (z < −3.29). The seed voxel is selected in the right ventral horn in C5, and exhibits functional connectivity with the contralateral ventral horn in the same slice as well as adjacent slices. Such connectivity between ventral horns is observed across all subjects. In each of the four plots, a 3.5-min segment of the seed time course is shown in black and the time course of the corresponding region of interest is shown in magenta. The highest correlations are observed in the contralateral ventral horn on the same slice (z = 4.10) and on the adjacent slices (z = 4.38). Correlations with central gray matter (z = 2.55) and adjacent white matter (z = 0.84) are relatively low, which, given the small size of the spinal cord, suggest that such correlations are genuine and not dominated by widespread physiological noise.DOI:http://dx.doi.org/10.7554/eLife.02812.005
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fig3: A single-subject analysis of resting state functional connectivity with corresponding time series.For clarity, only outlines of the gray matter butterfly and surrounding white matter are shown (rostro-caudal from left to right). Red and yellow represent statistically significant positive correlation with the seed time series (using a two-sided 99.9% confidence interval where red is 3.29 < z ≤ 3.89 and yellow is z > 3.89), and blue represents negative correlation (z < −3.29). The seed voxel is selected in the right ventral horn in C5, and exhibits functional connectivity with the contralateral ventral horn in the same slice as well as adjacent slices. Such connectivity between ventral horns is observed across all subjects. In each of the four plots, a 3.5-min segment of the seed time course is shown in black and the time course of the corresponding region of interest is shown in magenta. The highest correlations are observed in the contralateral ventral horn on the same slice (z = 4.10) and on the adjacent slices (z = 4.38). Correlations with central gray matter (z = 2.55) and adjacent white matter (z = 0.84) are relatively low, which, given the small size of the spinal cord, suggest that such correlations are genuine and not dominated by widespread physiological noise.DOI:http://dx.doi.org/10.7554/eLife.02812.005

Mentions: Functional images were preprocessed to mitigate rigid-body motion and physiological noise, and spatially interpolated to match the digital resolution of the T2*-weighted anatomical images (Figure 2). A 14-step standardized analysis protocol (described in 'Materials and methods') was used for each of the 22 subjects studied. In each subject, temporal signal-to-noise ratio (TSNR) was measured in spinal gray matter upon completion of the functional-to-anatomical affine registration (step #9) as well as after the application of CSF and white matter ‘regressors of no interest’ (steps #11 and #12). Across all 22 subjects, we observed a 30% increase in median TSNR (from 29.3 to 38.1) after the application of these few regressors, demonstrating the importance of characterizing and removing structured noise sources (Xie et al., 2012). After band-pass filtering to isolate the frequency range of interest (0.01–0.08 Hz), single-subject analyses show that statistically significant correlations are measurable between selected regions and are reproducible across subjects. As an illustrative example with the corresponding time series, an analysis performed on one subject (female, 23 years old) demonstrates connectivity with the contralateral ventral horns in the same slice and with adjacent slices when a seed region is selected in the center of the right ventral horn (Figure 3). A stringent threshold of /z/ > 3.29 (a two-tailed 99.9% confidence interval) was selected to show that connectivity is focused in the gray matter horns and not in central gray matter (connecting left and right sides and largely dominated by the central canal) nor adjacent white matter, which provides evidence that such gray matter correlations cannot be simply attributed to spatially correlated physiological noise and more likely represent genuine functional connectivity. Further examples of within-slice connectivity analyses in single subjects confirm that reproducible focal connectivity is found between ventral horns (Figure 4A–F) and between dorsal horns (Figure 4G–J). There is also evidence of plausible connectivity with central gray matter (Figure 4K) and between ventral and dorsal horns (Figure 4L), but these correlations are less consistent across all slices and not statistically significant at the group level. To quantify the occurrence of within-slice correlations between gray matter sub-regions across slices, we averaged time courses within each respective gray matter sub-region (defined in step #14) and considered only positive correlations at a more conventional 95% confidence interval (z > 1.65; one-tailed). Across all 264 slices (12 slices/subject × 22 subjects), we observed that 67% of slices (177 of 264) exhibit significant correlations between ventral horns and 37% of slices (97 of 264) exhibit significant correlations between dorsal horns. In comparison, a markedly fewer number of slices (only 1 in 5) exhibited significant correlations between the remaining four pairs: 21% between left ventral and left dorsal horns (55 of 264), 21% between left ventral and right dorsal horns (55 of 264), 20% between right ventral and left dorsal horns (54 of 264), and 23% between right ventral and right dorsal horns (62 of 264).10.7554/eLife.02812.004Figure 2.Functional weighted spinal cord images at 7 Tesla.


Resting state functional connectivity in the human spinal cord.

Barry RL, Smith SA, Dula AN, Gore JC - Elife (2014)

A single-subject analysis of resting state functional connectivity with corresponding time series.For clarity, only outlines of the gray matter butterfly and surrounding white matter are shown (rostro-caudal from left to right). Red and yellow represent statistically significant positive correlation with the seed time series (using a two-sided 99.9% confidence interval where red is 3.29 < z ≤ 3.89 and yellow is z > 3.89), and blue represents negative correlation (z < −3.29). The seed voxel is selected in the right ventral horn in C5, and exhibits functional connectivity with the contralateral ventral horn in the same slice as well as adjacent slices. Such connectivity between ventral horns is observed across all subjects. In each of the four plots, a 3.5-min segment of the seed time course is shown in black and the time course of the corresponding region of interest is shown in magenta. The highest correlations are observed in the contralateral ventral horn on the same slice (z = 4.10) and on the adjacent slices (z = 4.38). Correlations with central gray matter (z = 2.55) and adjacent white matter (z = 0.84) are relatively low, which, given the small size of the spinal cord, suggest that such correlations are genuine and not dominated by widespread physiological noise.DOI:http://dx.doi.org/10.7554/eLife.02812.005
© Copyright Policy - open-access
Related In: Results  -  Collection

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fig3: A single-subject analysis of resting state functional connectivity with corresponding time series.For clarity, only outlines of the gray matter butterfly and surrounding white matter are shown (rostro-caudal from left to right). Red and yellow represent statistically significant positive correlation with the seed time series (using a two-sided 99.9% confidence interval where red is 3.29 < z ≤ 3.89 and yellow is z > 3.89), and blue represents negative correlation (z < −3.29). The seed voxel is selected in the right ventral horn in C5, and exhibits functional connectivity with the contralateral ventral horn in the same slice as well as adjacent slices. Such connectivity between ventral horns is observed across all subjects. In each of the four plots, a 3.5-min segment of the seed time course is shown in black and the time course of the corresponding region of interest is shown in magenta. The highest correlations are observed in the contralateral ventral horn on the same slice (z = 4.10) and on the adjacent slices (z = 4.38). Correlations with central gray matter (z = 2.55) and adjacent white matter (z = 0.84) are relatively low, which, given the small size of the spinal cord, suggest that such correlations are genuine and not dominated by widespread physiological noise.DOI:http://dx.doi.org/10.7554/eLife.02812.005
Mentions: Functional images were preprocessed to mitigate rigid-body motion and physiological noise, and spatially interpolated to match the digital resolution of the T2*-weighted anatomical images (Figure 2). A 14-step standardized analysis protocol (described in 'Materials and methods') was used for each of the 22 subjects studied. In each subject, temporal signal-to-noise ratio (TSNR) was measured in spinal gray matter upon completion of the functional-to-anatomical affine registration (step #9) as well as after the application of CSF and white matter ‘regressors of no interest’ (steps #11 and #12). Across all 22 subjects, we observed a 30% increase in median TSNR (from 29.3 to 38.1) after the application of these few regressors, demonstrating the importance of characterizing and removing structured noise sources (Xie et al., 2012). After band-pass filtering to isolate the frequency range of interest (0.01–0.08 Hz), single-subject analyses show that statistically significant correlations are measurable between selected regions and are reproducible across subjects. As an illustrative example with the corresponding time series, an analysis performed on one subject (female, 23 years old) demonstrates connectivity with the contralateral ventral horns in the same slice and with adjacent slices when a seed region is selected in the center of the right ventral horn (Figure 3). A stringent threshold of /z/ > 3.29 (a two-tailed 99.9% confidence interval) was selected to show that connectivity is focused in the gray matter horns and not in central gray matter (connecting left and right sides and largely dominated by the central canal) nor adjacent white matter, which provides evidence that such gray matter correlations cannot be simply attributed to spatially correlated physiological noise and more likely represent genuine functional connectivity. Further examples of within-slice connectivity analyses in single subjects confirm that reproducible focal connectivity is found between ventral horns (Figure 4A–F) and between dorsal horns (Figure 4G–J). There is also evidence of plausible connectivity with central gray matter (Figure 4K) and between ventral and dorsal horns (Figure 4L), but these correlations are less consistent across all slices and not statistically significant at the group level. To quantify the occurrence of within-slice correlations between gray matter sub-regions across slices, we averaged time courses within each respective gray matter sub-region (defined in step #14) and considered only positive correlations at a more conventional 95% confidence interval (z > 1.65; one-tailed). Across all 264 slices (12 slices/subject × 22 subjects), we observed that 67% of slices (177 of 264) exhibit significant correlations between ventral horns and 37% of slices (97 of 264) exhibit significant correlations between dorsal horns. In comparison, a markedly fewer number of slices (only 1 in 5) exhibited significant correlations between the remaining four pairs: 21% between left ventral and left dorsal horns (55 of 264), 21% between left ventral and right dorsal horns (55 of 264), 20% between right ventral and left dorsal horns (54 of 264), and 23% between right ventral and right dorsal horns (62 of 264).10.7554/eLife.02812.004Figure 2.Functional weighted spinal cord images at 7 Tesla.

Bottom Line: Functional magnetic resonance imaging using blood oxygenation level dependent (BOLD) contrast is well established as one of the most powerful methods for mapping human brain function.However, to date there have been no previous substantiated reports of resting state correlations in the spinal cord.In a cohort of healthy volunteers, we observed robust functional connectivity between left and right ventral (motor) horns, and between left and right dorsal (sensory) horns.

View Article: PubMed Central - PubMed

Affiliation: Vanderbilt University Institute of Imaging Science, Nashville, United States Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, United States robert.l.barry@vanderbilt.edu.

No MeSH data available.


Related in: MedlinePlus