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Periventricular and juxtacortical characterization of UManitoba-JHU functionally defined human white matter atlas networks
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BackgroundThe open-access UManitoba-JHU functionally defined human white matter (WM) atlas contains specific WM pathways and general WM regions underlying 12 functional brain networks in ICBM152 template space. However, it is not known whether any of these WM networks are disproportionately co-localized with periventricular and/or juxtacortical WM (PVWM and JCWM), which could potentially impact their ability to infer network-specific effects in future studies—particularly in patient populations expected to have disproportionate PVWM and/or JCWM damage.MethodsThe current study therefore identified intersecting regions of PVWM and JCWM (defined as WM within 5 mm of the ventricular and cortical boundaries) and: (1) the ICBM152 global WM mask, and (2) all 12 UManitoba-JHU WM networks. Dice Similarity Coefficient (DSC), Jaccard Similarity Coefficient (JSC), and proportion of volume (POV) values between PVWM (and JCWM) and each functionally defined WM network were then compared to corresponding values between PVWM (and JCWM) and global WM.ResultsBetween the 12 WM networks and PVWM, 8 had lower DSC, JSC, and POV; 1 had lower DSC and JSC, but higher POV; and 3 had higher DSC, JSC, and POV compared to global WM. For JCWM, all 12 WM networks had lower DSC, JSC, and POV compared to global WM.ConclusionThe majority of UManitoba-JHU functionally defined WM networks exhibited lower than average spatial similarity with PVWM, and all exhibited lower than average spatial similarity with JCWM. This suggests that they can be used to explore network-specific WM changes, even in patient populations with known predispositions toward PVWM and/or JCWM damage.
Title: Periventricular and juxtacortical characterization of UManitoba-JHU functionally defined human white matter atlas networks
Description:
BackgroundThe open-access UManitoba-JHU functionally defined human white matter (WM) atlas contains specific WM pathways and general WM regions underlying 12 functional brain networks in ICBM152 template space.
However, it is not known whether any of these WM networks are disproportionately co-localized with periventricular and/or juxtacortical WM (PVWM and JCWM), which could potentially impact their ability to infer network-specific effects in future studies—particularly in patient populations expected to have disproportionate PVWM and/or JCWM damage.
MethodsThe current study therefore identified intersecting regions of PVWM and JCWM (defined as WM within 5 mm of the ventricular and cortical boundaries) and: (1) the ICBM152 global WM mask, and (2) all 12 UManitoba-JHU WM networks.
Dice Similarity Coefficient (DSC), Jaccard Similarity Coefficient (JSC), and proportion of volume (POV) values between PVWM (and JCWM) and each functionally defined WM network were then compared to corresponding values between PVWM (and JCWM) and global WM.
ResultsBetween the 12 WM networks and PVWM, 8 had lower DSC, JSC, and POV; 1 had lower DSC and JSC, but higher POV; and 3 had higher DSC, JSC, and POV compared to global WM.
For JCWM, all 12 WM networks had lower DSC, JSC, and POV compared to global WM.
ConclusionThe majority of UManitoba-JHU functionally defined WM networks exhibited lower than average spatial similarity with PVWM, and all exhibited lower than average spatial similarity with JCWM.
This suggests that they can be used to explore network-specific WM changes, even in patient populations with known predispositions toward PVWM and/or JCWM damage.
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