Disentangling resting-state BOLD variability and PCC functional connectivity in 22q11.2 deletion syndrome

Although often ignored in fMRI studies, moment-to-moment variability of blood oxygenation level dependent (BOLD) signals reveals important information about brain function. Indeed, higher brain signal variability has been associated with better cognitive performance in young adults compared to children and elderly adults. Functional connectivity, a very, common approach in resting-state fMRI analysis, is scaled for variance. Thus, alterations might be confounded or driven by BOLD signal variance alterations. Chromosome 22q11.2 deletion syndrome (22q11.2DS) is a neurodevelopmental disorder that is associated with a vast cognitive and clinical phenotype. To date, several resting-state fMRI studies reported altered functional connectivity in 22q11.2DS, however BOLD signal variance has not yet been analyzed. Here, we employed PLS correlation analysis to reveal multivariate patterns of diagnosis-related alterations and age-relationship throughout the cortex of 50 patients between 9 and 25 years old and 50 healthy controls in the same age range. To address how functional connectivity in the default mode network is influenced by BOLD signal fluctuations, we conducted the same analysis on seed-to-voxel connectivity of the posterior cingulate cortex (PCC) and compared resulting brain patterns. BOLD signal variance was lower mainly in regions of the default mode network and in the dorsolateral prefrontal cortex, but higher in large parts of the temporal lobes. In those regions, BOLD signal variance was correlated with age in healthy controls, but not in patients, suggesting deviant developmental trajectories from child- to adulthood. Positive connectivity of the PCC within the default mode network as well as negative connectivity towards the frontoparietal network were weaker in patients with 22q11.2DS. We furthermore showed that lower functional connectivity of the PCC was not driven by higher BOLD signal variability. Our results confirm the strong implication of BOLD variance in aging and give an initial insight in its relationship with functional connectivity in the DMN.

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

Nora Leonardi, Jonas Richiardi, Dimitri Nestor Alice Van De Ville

Functional connectivity (FC) as measured by correlation between NM BOLD time courses of distinct brain regions has revealed meaningful organization of spontaneous fluctuations in the resting brain. However, an increasing amount of evidence points to non-stationarity of FC; i.e., FC dynamically changes over time reflecting additional and rich information about brain organization, but representing new challenges for analysis and interpretation. Here, we propose a data-driven approach based on principal component analysis (PCA) to reveal hidden patterns of coherent FC dynamics across multiple subjects. We demonstrate the feasibility and relevance of this new approach by examining the differences in dynamic FC between 13 healthy control subjects and 15 minimally disabled relapse-remitting multiple sclerosis patients. We estimated whole-brain dynamic FC of regionally-averaged BOLD activity using sliding time windows. We then used PCA to identify FC patterns, termed "eigenconnectivities", that reflect meaningful patterns in FC fluctuations. We then assessed the contributions of these patterns to the dynamic FC at any given time point and identified a network of connections centered on the default-mode network with altered contribution in patients. Our results complement traditional stationary analyses, and reveal novel insights into brain connectivity dynamics and their modulation in a neurodegenerative disease. (C) 2013 Elsevier Inc. All rights reserved.

Elsevier2013

Recovery of the default mode network after demanding neurofeedback training occurs in spatio-temporally segregated subnetworks

Sven Haller, Rotem Roza Kopel, Dimitri Nestor Alice Van De Ville

The default mode (DM) network is a major large-scale cerebral network that can be identified with functional magnetic resonance imaging (fMRI) during resting state. Most studies consider functional connectivity networks as stationary phenomena. Consequently, the transient behavior of the DM network and its subnetworks is still largely unexplored. Most functional connectivity fMRI studies assess the steady state of resting without any task. To specifically investigate the recovery of the DM network during the transition from activation to rest, we implemented a cognitively demanding real-time fMRI neurofeedback task that targeted down-regulation of the primary auditory cortex. Each of twelve healthy subjects performed 16 block-design fMRI runs (4 runs per day repeated on 4 days) resulting 192 runs in total. The analysis included data-driven independent component analysis (ICA) and high-resolution latency estimation between the four components that corresponded to subnetworks of the DM network. These different subnetworks reemerged after regulation with an average time lag or 3.3 s and a time lag of 4.4 s between the first and fourth components; i.e., the DM recovery first shifts from anterior to posterior, and then gradually focuses on the ventral part of the posterior cingulate cortex, which is known to be implicated in internally directed cognition. In addition, we found less reactivation in the early anterior subnetwork as regulation strength increased, but more reactivation with larger regulation for the late subnetwork that encompassed the ventral PCC. This finding confirms that the level of task engagement influences inversely the subsequent recovery of regions related to attention compared to those related to internally directed cognition. (C) 2012 Elsevier Inc. All rights reserved.

Elsevier2012

Neural substrates of psychosis revealed by altered dependencies between brain activity and white-matter architecture in individuals with 22q11 deletion syndrome

Karin Bortolin, Farnaz Delavari, Emeline Mullier, Maria Giulia Preti, Dimitri Nestor Alice Van De Ville

Background: Dysconnectivity has been consistently proposed as a major key mechanism in psychosis. Indeed, disruptions in large-scale structural and functional brain networks have been associated with psychotic symptoms. However, brain activity is largely constrained by underlying white matter pathways and the study of function-structure dependency, compared to conventional unimodal analysis, allows a biologically relevant assessment of neural mechanisms. The 22q11.2 deletion syndrome (22q11DS) constitutes a remarkable opportunity to study the pathophysiological processes of psychosis. Methods: 58 healthy controls and 57 deletion carriers, aged from 16 to 32 years old, underwent resting-state functional and diffusion-weighted magnetic resonance imaging. Deletion carriers were additionally fully assessed for psychotic symptoms. Firstly, we used a graph signal processing method to combine brain activity and structural connectivity measures to obtain regional structural decoupling indexes (SDIs). We use SDI to assess the differences of functional structural dependency (FSD) across the groups. Subsequently we investigated how alterations in FSDs are associated with the severity of positive psychotic symptoms in participants with 22q11DS. Results: In line with previous findings, participants in both groups showed a spatial gradient of FSD ranging from sensory-motor regions (stronger FSD) to regions involved in higher-order function (weaker FSD). Compared to controls, in participants with 22q11DS, and further in deletion carriers with more severe positive psychotic symptoms, the functional activity was more strongly dependent on the structure in parahippocampal gyrus and subcortical dopaminergic regions, while it was less dependent within the cingulate cortex. This analysis revealed group differences not otherwise detected when assessing the structural and functional nodal measures separately. Conclusions: Our findings point toward a disrupted modulation of functional activity on the underlying structure, which was further associated to psychopathology for candidate critical regions in 22q11DS. This study provides the first evidence for the clinical relevance of function-structure dependency and its contribution to the emergence of psychosis.