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Maximizing negative correlations in resting-state functional connectivity MRI by time-lag.

Goelman G, Gordon N, Bonne O - PLoS ONE (2014)

Bottom Line: The application of spatial smoothing and global signal correction increased the number of significant positive connections but their effect on negative connections was complex.This effect was evident in all four types of analyses (with and without global signal correction and spatial smoothing) but was most significant in the analysis with no correction for the global signal.Similarly, negative correlations could result from spatially inhomogeneous responses of rCBV or rCBF alone.

View Article: PubMed Central - PubMed

Affiliation: MRI/MRS Lab, The Human Biology Research Center, Department of Medical Biophysics, Hadassah Hebrew University Medical Center, Jerusalem, Israel.

ABSTRACT
This paper aims to better understand the physiological meaning of negative correlations in resting state functional connectivity MRI (r-fcMRI). The correlations between anatomy-based brain regions of 18 healthy humans were calculated and analyzed with and without a correction for global signal and with and without spatial smoothing. In addition, correlations between anatomy-based brain regions of 18 naïve anesthetized rats were calculated and compared to the human data. T-statistics were used to differentiate between positive and negative connections. The application of spatial smoothing and global signal correction increased the number of significant positive connections but their effect on negative connections was complex. Positive connections were mainly observed between cortical structures while most negative connections were observed between cortical and non-cortical structures with almost no negative connections between non-cortical structures. In both human and rats, negative connections were never observed between bilateral homologous regions. The main difference between positive and negative connections in both the human and rat data was that positive connections became less significant with time-lags, while negative connections became more significant with time-lag. This effect was evident in all four types of analyses (with and without global signal correction and spatial smoothing) but was most significant in the analysis with no correction for the global signal. We hypothesize that the valence of r-fcMRI connectivity reflects the relative contributions of cerebral blood volume (CBV) and flow (CBF) to the BOLD signal and that these relative contributions are location-specific. If cerebral circulation is primarily regulated by CBF in one region and by CBV in another, a functional connection between these regions can manifest as an r-fcMRI negative and time-delayed correlation. Similarly, negative correlations could result from spatially inhomogeneous responses of rCBV or rCBF alone. Consequently, neuronal regulation of brain circulation may be deduced from the valence of r-fcMRI connectivity.

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Significant connections within the 57 predefined human regions for the –S-G analysis.Significant connections are presented as 2D projections on top of T1-weighted coronal and axial MRI images. ROIs are annotated using numbers provided in Table 1. A & B. Positive connections. C & D. Negative connections.
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pone-0111554-g002: Significant connections within the 57 predefined human regions for the –S-G analysis.Significant connections are presented as 2D projections on top of T1-weighted coronal and axial MRI images. ROIs are annotated using numbers provided in Table 1. A & B. Positive connections. C & D. Negative connections.

Mentions: Figures 2–5 show the significant positive (A & B) and significant negative (C & D) connections in the human data, each for a different analysis. In figure 6 we show the numbers of significant positive and significant negative connections that were obtained by these analyses in the human data. Whereas spatial smoothing and correction for the global signal increased the number of positive connections, the effect on the negative connections was more complex. To better quantify the differences between the analyses, we calculated the percentage of common connections (positive and negative separately) between the analyses. Table 3 shows that whereas most of the positive connections were common regardless of the analysis used, different negative connections were obtained when a correction for global signal was applied.


Maximizing negative correlations in resting-state functional connectivity MRI by time-lag.

Goelman G, Gordon N, Bonne O - PLoS ONE (2014)

Significant connections within the 57 predefined human regions for the –S-G analysis.Significant connections are presented as 2D projections on top of T1-weighted coronal and axial MRI images. ROIs are annotated using numbers provided in Table 1. A & B. Positive connections. C & D. Negative connections.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4232255&req=5

pone-0111554-g002: Significant connections within the 57 predefined human regions for the –S-G analysis.Significant connections are presented as 2D projections on top of T1-weighted coronal and axial MRI images. ROIs are annotated using numbers provided in Table 1. A & B. Positive connections. C & D. Negative connections.
Mentions: Figures 2–5 show the significant positive (A & B) and significant negative (C & D) connections in the human data, each for a different analysis. In figure 6 we show the numbers of significant positive and significant negative connections that were obtained by these analyses in the human data. Whereas spatial smoothing and correction for the global signal increased the number of positive connections, the effect on the negative connections was more complex. To better quantify the differences between the analyses, we calculated the percentage of common connections (positive and negative separately) between the analyses. Table 3 shows that whereas most of the positive connections were common regardless of the analysis used, different negative connections were obtained when a correction for global signal was applied.

Bottom Line: The application of spatial smoothing and global signal correction increased the number of significant positive connections but their effect on negative connections was complex.This effect was evident in all four types of analyses (with and without global signal correction and spatial smoothing) but was most significant in the analysis with no correction for the global signal.Similarly, negative correlations could result from spatially inhomogeneous responses of rCBV or rCBF alone.

View Article: PubMed Central - PubMed

Affiliation: MRI/MRS Lab, The Human Biology Research Center, Department of Medical Biophysics, Hadassah Hebrew University Medical Center, Jerusalem, Israel.

ABSTRACT
This paper aims to better understand the physiological meaning of negative correlations in resting state functional connectivity MRI (r-fcMRI). The correlations between anatomy-based brain regions of 18 healthy humans were calculated and analyzed with and without a correction for global signal and with and without spatial smoothing. In addition, correlations between anatomy-based brain regions of 18 naïve anesthetized rats were calculated and compared to the human data. T-statistics were used to differentiate between positive and negative connections. The application of spatial smoothing and global signal correction increased the number of significant positive connections but their effect on negative connections was complex. Positive connections were mainly observed between cortical structures while most negative connections were observed between cortical and non-cortical structures with almost no negative connections between non-cortical structures. In both human and rats, negative connections were never observed between bilateral homologous regions. The main difference between positive and negative connections in both the human and rat data was that positive connections became less significant with time-lags, while negative connections became more significant with time-lag. This effect was evident in all four types of analyses (with and without global signal correction and spatial smoothing) but was most significant in the analysis with no correction for the global signal. We hypothesize that the valence of r-fcMRI connectivity reflects the relative contributions of cerebral blood volume (CBV) and flow (CBF) to the BOLD signal and that these relative contributions are location-specific. If cerebral circulation is primarily regulated by CBF in one region and by CBV in another, a functional connection between these regions can manifest as an r-fcMRI negative and time-delayed correlation. Similarly, negative correlations could result from spatially inhomogeneous responses of rCBV or rCBF alone. Consequently, neuronal regulation of brain circulation may be deduced from the valence of r-fcMRI connectivity.

Show MeSH