Structural covariance of the neostriatum with regional gray matter volumes

Abstract

The caudate and putamen nuclei have been traditionally divided into dorsal and ventral territories based on their segregated patterns of functional and anatomical connectivity with distributed cortical regions. Activity-dependent structural plasticity may potentially lead to the development of regional volume correlations, or structural covariance, between the different components of each cortico-striatal circuit. Here, we studied the whole-brain structural covariance patterns of four neostriatal regions belonging to distinct cortico-striatal circuits. We also assessed the potential modulating influence of laterality, age and gender. T1-weighted three-dimensional magnetic resonance images were obtained from ninety healthy participants (50 females). Following data pre-processing, the mean signal value per hemisphere was calculated for the 'seed' regions of interest, located in the dorsal and ventral caudate and the dorsal-caudal and ventral-rostral putamen. Statistical parametric mapping was used to estimate whole-brain voxel-wise structural covariance patterns for each striatal region, controlling for the shared anatomical variance between regions in order to obtain maximally specific structural covariance patterns. As predicted, segregated covariance patterns were observed. Age was found to be a relevant modulator of the covariance patterns of the right caudate regions, while laterality effects were observed for the dorsal-caudal putamen. Gender effects were only observed via an interaction with age. The different patterns of structural covariance are discussed in detail, as well as their similarities with the functional and anatomical connectivity patterns reported for the same striatal regions in other studies. Finally, the potential mechanisms underpinning the phenomenon of volume correlations between distant cortico-striatal structures are also discussed.

Structural covariance of neostriatal and limbic regions in patients with obsessive–compulsive disorder

“…6 Importantly, within the context of activitydependent structural plasti city, 11,12 this association between functional connectivity and structural covariance suggests that interindividual variability in functional brain networks should result in similarly variable patterns of structural covariance. 13 In agreement with this, brain disorders selectively affecting nodal regions within func tional networks simultaneously disrupt both functional con nectivity and structural covariance patterns.…”

“…13 Therefore, structural covariance provides a specific and distinctive measurement that should aid in the comprehensive characterization of networklevel brain fea tures. Specifically, in comparison with functional connectivity, structural covariance assesses brain connectivity on a different time scale; while functional connectivity reflects a state feature, which may oscillate across different states (i.e., at rest v. task performance), structural covariance may better represent more stable (e.g., maturational or traitlike) connectivity features.…”

“…26 In this context, the assessment of structural covariance should inform about the existence of stable inter regional connectivity alterations, probably stemming from maturational abnormalities or persistent and enduring func tional connectivity changes that should underpin the expres sion of OCD symptoms across different scenarios. The nor mal patterns of structural covariance within frontostriatal circuits have been recently described, 13 showing partial over lap with the functional connectivity patterns that characterize these circuits. 30 Likewise, structural covariance of the amyg dala has been previously explored; 31 however, in contrast to findings reported in functional connectivity studies, 32,33 there have been no reports of specific structural covariance pat terns associated with different amygdala subregions.…”

“…Likewise, sociodemographic variables, especially age, have been found to modulate regional volumes within striatal regions in patients with OCD 19,34 and structural covariance patterns. 13 Assessment of age effects was of particular interest for the purpose of this study, as it may help to discriminate alterations of maturational origin from causes associated with the course of the disorder (i.e., shared history of coactivation between 2 regions).…”

“…Based on previous functional connectivity 21,30 and structural covariance 13 studies, all of the striatal seeds were defined using the dorsoventral boundaries of caudate and putamen nuclei initially proposed by Postuma and Dagher. 36 Striatal seeds of interest were the DC, VC, DCP and VRP.…”