Structural control energy of resting-state functional brain states reveals less cost-effective brain dynamics in psychosis vulnerability

How the brain's white-matter anatomy constrains brain activity is an open question that might give insights into the mechanisms that underlie mental disorders such as schizophrenia. Chromosome 22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental disorder with an extremely high risk for psychosis providing a test case to study developmental aspects of schizophrenia. In this study, we used principles from network control theory to probe the implications of aberrant structural connectivity for the brain's functional dynamics in 22q11DS. We retrieved brain states from resting-state functional magnetic resonance images of 78 patients with 22q11DS and 85 healthy controls. Then, we compared them in terms of persistence control energy; that is, the control energy that would be required to persist in each of these states based on individual structural connectivity and a dynamic model. Persistence control energy was altered in a broad pattern of brain states including both energetically more demanding and less demanding brain states in 22q11DS. Further, we found a negative relationship between persistence control energy and resting-state activation time, which suggests that the brain reduces energy by spending less time in energetically demanding brain states. In patients with 22q11DS, this behavior was less pronounced, suggesting a deficiency in the ability to reduce energy through brain activation. In summary, our results provide initial insights into the functional implications of altered structural connectivity in 22q11DS, which might improve our understanding of the mechanisms underlying the disease.

Structural and functional connectivity in the default mode network in 22q11.2 deletion syndrome

Maria Carmela Padula, Marie Schaer, Maude Schneider, Dimitri Nestor Alice Van De Ville

Background: The neural endophenotype associated with 22q11.2 deletion syndrome (22q11DS) includes deviant cortical development and alterations in brain connectivity. Resting-state functional magnetic resonance imaging (fMRI) findings also reported disconnectivity within the default mode network (DMN). In this study, we explored the relationship between functional and structural DMN connectivity and their changes with age in patients with 22q11DS in comparison to control participants. Given previous evidence of an association between DMN disconnectivity and the manifestation of psychotic symptoms, we further investigated this relationship in our group of patients with 22q11DS. Methods: T1-weighted, diffusion, and resting-state fMRI scans were acquired from 41 patients with 22q11DS and 43 control participants aged 6 to 28 years. A data-driven approach based on independent component analysis (ICA) was used to identify the DMN and to define regions of interest for the structural and functional connectivity analysis. Prodromal psychotic symptoms were assessed in adolescents and adults using the positive symptom scores of the Structured Interview of Prodromal Syndromes (SIPS). Connectivity measures were compared between groups and correlated with age. Repeating the between-group analysis in three different age bins further assessed the presence of age-related alterations in DMN connectivity. Structural and functional connectivity measures were then correlated with the SIPS scores. Results: A simultaneous reduction of functional and structural connectivity between core medial nodes of the DMN was observed. Furthermore, structural connectivity measures significantly increased with age in the control group but not in patients with 22q11DS, suggesting the presence of an age-related alteration of the DMN structural connections. No correlations were found between the DMN disconnectivity and expression of prodromal symptoms in 22q11DS. Conclusions: These findings indicate the presence of functional and structural DMN disconnectivity in 22q11DS and that patients with 22q11DS fail to develop normal structural connections between medial DMN nodes. This suggests the presence of altered neurodevelopmental trajectories in 22q11DS.

BioMed Central2015

Traces Of Human Functional Activity: Moment-To-Moment Fluctuations In Fmri Data

Luca Dodero, Djalel Eddine Meskaldji, Dimitri Nestor Alice Van De Ville

Dynamic functional connectivity (dFC) measured by functional magnetic resonance imaging (fMRI) shows evidence of large-scale networks with highly dynamic (re) configurations. We propose a novel approach to extract traces of human brain function by the construction of a trajectory in a meaningful low-dimensional space. This allows studying dFC in more detail and identify possible meaningful brain states from the moment-to-moment fluctuations of the brain signals during resting state or naturalistic conditions such as passive movie watching. Specifically, we explored dynamic organization of sub-networks derived from the time-dependent graph Laplacian in combination with Riemannian manifold distance to measure dissimilarity over time of dFC and to subsequently build the trajectory of brain activity. As a proof-of-principle, we show results for an fMRI dataset containing both rest and movie epochs in 15 healthy participants. The movie condition varied (i.e., fearful, joyful, and neutral movie excerpts) and clearly influenced the subsequent resting-state period in terms of FC brain state.

IEEE2016

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

Maria Carmela Padula, Marie Schaer, Dimitri Nestor Alice Van De Ville, Daniela Maria Zöller

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.