Resting state functional magnetic resonance imaging (rsfMRI) and tractography, derived from diffusion weighted imaging (DWI), are well-established neuroimaging techniques to investigate respectively brain functional connectivity (FC) and structural connectivity (SC) (van den Heuvel et al., 2009). The aim of this work was exploring the correlation between FC and SC within the default mode network (DMN), the left lateral network (LLN) and the right lateral network (RLN). In a sample of 19 healthy subjects, the RSNs were extracted at group level through the spatial independent component analysis (ICA), according to Dipasquale et al. (2015). DMN, LLN and RLN were selected and then divided into their spatial nodes, defined as anatomically separated clusters. For each subject, FC strength was calculated as the Pearson correlation coefficient (transformed in Z-score) between the pairs of rsfMRI signal time courses associated to the pairs of the RSN nodes. Averaging these values across subjects, group FC indexes were obtained. The same pairs of clusters were also used as seed and target regions in single subject probabilistic tractography. For each reconstructed tract the number of voxels above-threshold (15%) (Khalsa et al., 2014) was adopted as SC index. Averaging these values across subjects, the group SC indexes were obtained for each RSN. Finally, FC and SC indexes were correlated by Pearson correlation coefficient. As a result, we observed a positive FC-SC correlation in LLN (statistically significant, p<0.05) and in RLN. Regarding the DMN, no significant FC-SC correlation was found, even though it revealed high values of FC and SC separately. Our results suggest that combining FC and SC indexes allows to evaluate if a high communication level within RSNs is determined by direct white matter fiber pathways or rather by collateral circuits not detectable with the available tractographic techniques.
Correlation of Brain Structural and Functional Connectivity Indexes
PELIZZARI, LAURA;SCACCIANOCE, ELISA;LAGANA', MARIA MARCELLA;DIPASQUALE, OTTAVIA;COSTANTINI, ISA;BASELLI, GIUSEPPE
2015-01-01
Abstract
Resting state functional magnetic resonance imaging (rsfMRI) and tractography, derived from diffusion weighted imaging (DWI), are well-established neuroimaging techniques to investigate respectively brain functional connectivity (FC) and structural connectivity (SC) (van den Heuvel et al., 2009). The aim of this work was exploring the correlation between FC and SC within the default mode network (DMN), the left lateral network (LLN) and the right lateral network (RLN). In a sample of 19 healthy subjects, the RSNs were extracted at group level through the spatial independent component analysis (ICA), according to Dipasquale et al. (2015). DMN, LLN and RLN were selected and then divided into their spatial nodes, defined as anatomically separated clusters. For each subject, FC strength was calculated as the Pearson correlation coefficient (transformed in Z-score) between the pairs of rsfMRI signal time courses associated to the pairs of the RSN nodes. Averaging these values across subjects, group FC indexes were obtained. The same pairs of clusters were also used as seed and target regions in single subject probabilistic tractography. For each reconstructed tract the number of voxels above-threshold (15%) (Khalsa et al., 2014) was adopted as SC index. Averaging these values across subjects, the group SC indexes were obtained for each RSN. Finally, FC and SC indexes were correlated by Pearson correlation coefficient. As a result, we observed a positive FC-SC correlation in LLN (statistically significant, p<0.05) and in RLN. Regarding the DMN, no significant FC-SC correlation was found, even though it revealed high values of FC and SC separately. Our results suggest that combining FC and SC indexes allows to evaluate if a high communication level within RSNs is determined by direct white matter fiber pathways or rather by collateral circuits not detectable with the available tractographic techniques.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
