Modeling the neurocognitive dynamics of language across the lifespan.

Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed between language comprehension and language production (LP). Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this variability. At the cognitive level, our findings suggest that LP is not an isolated function but is modulated throughout the lifespan by the extent of inter-cognitive synergy between semantic and domain-general processes. At the cerebral level, we show that default mode network (DMN) suppression coupled with fronto-parietal network (FPN) integration is the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related decline in LP. Relatedly, reduced DMN suppression in midlife could compromise the ability to manage the cost of FPN integration. This may prompt older adults to adopt a more cost-efficient compensatory strategy that maintains global homeostasis at the expense of LP performances. Taken together, we propose that midlife represents a critical neurocognitive juncture that signifies the onset of LP decline, as older adults gradually lose control over semantic representations. We summarize our findings in a novel synergistic, economical, nonlinear, emergent, cognitive aging model, integrating connectomic and cognitive dimensions within a complex system perspective.

HDR syndrome: Large cohort and systematic review.

HDR syndrome is a rare disease characterized by hypoparathyroidism, deafness, and renal dysplasia. An autosomal dominant disease caused by heterozygous pathogenic GATA3 variants, the penetrance of each associated condition is variable. Literature reviews have provided some answers, but many questions remain, in particular what the relationship is between genotype and phenotype. The current study examines 28 patients with HDR syndrome combined with an exhaustive review of the literature. Some conditions such as hearing loss are almost always present, while others described as rare initially, do not seem to be so rare after all (genital malformations and basal ganglia calcifications). By modeling pathogenic GATA3 variants found in HDR syndrome, we found that missense variations appear to always be located in the same area (close to the two Zinc Finger domain). We describe new pathogenic GATA3 variants, of which some seem to always be associated with certain conditions. Many audiograms were studied to establish a typical audiometric profile associated with a phenotype in HDR. As mentioned in the literature, hearing function should always be assessed as early as possible and follow up of patients with HDR syndrome should include monitoring of parathyroid function and vesicoureteral reflux in order to prevent complications.

Inter-regional correlation estimators for functional magnetic resonance imaging.

Functional magnetic resonance imaging (fMRI) functional connectivity between brain regions is often computed using parcellations defined by functional or structural atlases. Typically, some kind of voxel averaging is performed to obtain a single temporal correlation estimate per region pair. However, several estimators can be defined for this task, with various assumptions and degrees of robustness to local noise, global noise, and region size. In this paper, we systematically present and study the properties of 9 different functional connectivity estimators taking into account the spatial structure of fMRI data, based on a simple fMRI data spatial model. These include 3 existing estimators and 6 novel estimators. We demonstrate the empirical properties of the estimators using synthetic, animal, and human data, in terms of graph structure, repeatability and reproducibility, discriminability, dependence on region size, as well as local and global noise robustness. We prove analytically the link between regional intra-correlation and inter-region correlation, and show that the choice of estimator has a strong influence on inter-correlation values. Some estimators, including the commonly used correlation of averages (ca), are positively biased, and have more dependence to region size and intra-correlation than robust alternatives, resulting in spatially-dependent bias. We define the new local correlation of averages estimator with better theoretical guarantees, lower bias, significantly lower dependence on region size (Spearman correlation 0.40 vs 0.55, paired t-test T=27.2, p=1.1e-47), at negligible cost to discriminative power, compared to the ca estimator. The difference in connectivity pattern between the estimators is not distributed uniformly throughout the brain, but rather shows a clear ventral-dorsal gradient, suggesting that region size and intra-correlation plays an important role in shaping functional networks defined using the ca estimator, and leading to non-trivial differences in their connectivity structure. We provide an open source R package and equivalent Python implementation to facilitate the use of the new estimators, together with preprocessed rat time-series.

RIPOR2: A new gene of non-syndromic cochleovestibular dysfunction, discrepancy between human pathology and animal models.

Cochleovestibular dysfunctions are rare conditions misrecognized. A homozygous pathogenic variation c.1561C > T (p.Arg521*) in RIPOR2 (RHO family interacting cell polarization regulator 2) has been identified by WES in Tunisian siblings suffering from congenital bilateral profound hearing and vestibular dysfunctions. In contrast to the vestibular areflexia observed in our patients, deaf Ripor2 KO mouse model and our zebrafish model have normal vestibular function.

Innovative graph analysis method to assess gene expression modulation after fine particles exposures of 3D human airway epithelia.

Environmental particles have dramatic consequences for health, especially for the most vulnerable people, such as asthmatics. To better understand the impact on gene expression modulation of fine particles (PM2.5-0.3) from different emission sources, a 3D-airway model, a human bronchial epithelium (MucilAir-HF™) reconstructed from primary cells from healthy (EpiH) or asthmatic (EpiA) donors, was used. Repeated air-liquid exposures were performed, and epithelia were sacrificed to extract RNAs and assess gene expression. Data were analyzed according to the emission sources, physiological status, and exposure doses using a recent model consisting in a graph analysis on pairwise expression ratio. The results were compared with those from the classical ΔΔCt method. The graph analysis method proved to have better statistical properties than the classical ΔΔCt method and demonstrated that repeated PM2.5-0.3 exposures induced a dose-dependent up-regulation of the metabolic gene (CYP1B1) and a down-regulation of the inflammation gene (CXCL10). These modulations were greater for "industrial" than for "urban traffic" fine particles, and the effects were found to be greater after exposure of EpiA than EpiH, thus emphasizing the importance of the epithelium's physiological status in sensitivity to particles. Our study is original in terms of the experimental conditions and the graphical statistical analysis model established. The results highlight the importance of particle chemistry on the modulation of cellular and molecular responses, which may vary according to the individual's vulnerability.

Functional Brain Dysconnectivity in Parkinson's Disease: A 5-Year Longitudinal Study.

BACKGROUND: Tracking longitudinal functional brain dysconnectivity in Parkinson's disease (PD) is a key element to decoding the underlying physiopathology and understanding PD progression. OBJECTIVES: The objectives of this follow-up study were to explore, for the first time, the longitudinal changes in the functional brain networks of PD patients over 5 years and to associate them with their cognitive performance and the lateralization of motor symptoms. METHODS: We used a 5-year longitudinal cohort of PD patients (n = 35) who completed motor and non-motor assessments and sequent resting state (RS) high-density electroencephalography (HD-EEG) recordings at three timepoints: baseline (BL), 3 years follow-up (3YFU) and 5 years follow-up (5YFU). We assessed disruptions in frequency-dependent functional networks over the course of the disease and explored their relation to clinical symptomatology. RESULTS: In contrast with HC (n = 32), PD patients showed a gradual connectivity impairment in α2 (10-13 Hz) and ß (13-30 Hz) frequency bands. The deterioration in the global cognitive assessment was strongly correlated with the disconnected networks. These disconnected networks were also associated with the lateralization of motor symptoms, revealing a dominance of the right hemisphere in terms of impaired connections in the left-affected PD patients in contrast to dominance of the left hemisphere in the right-affected PD patients. CONCLUSIONS: Taken together, our findings suggest that with disease progression, dysconnectivity in the brain networks in PD can reflect the deterioration of global cognitive deficits and the lateralization of motor symptoms. RS HD-EEG may be an early biomarker of PD motor and non-motor progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Oxidative potential and in vitro toxicity of particles generated by pyrotechnic smokes in human small airway epithelial cells.

Pyrotechnic smokes are widely used in civilian and military applications. The major issue arise from the release of particles after smoke combustion but the health risks related to their exposure are poorly documented whereas toxicity of airborne particles on the respiratory target are very well known. Therefore, this study aimed to explore the in vitro toxicity of the particle fraction of different pyrotechnic smokes. Particles from a red signalling smoke (RSS), an hexachloroethane-based obscuring smoke (HC-OS) and an anti-intrusion smoke (AIS) were collected from the cloud. RSS particles displayed the highest organic fraction (quinones and polycyclic aromatic hydrocarbons) of the three samples characterized. AIS particles contained K and cholesterol derivatives. HC-OS particles were mainly metallic with very high concentrations of Al, Fe and Ca. Intrinsic oxidative potential of smoke particles was measured with two assays. Depletions of DTT by RSS particles was greater than depletion obtained with AIS and HC-OS particles but depletion of acid ascorbic (AA) was only observed with HC-OS particles. In vitro toxicity was assessed by exposing human small airway epithelial cells (SAEC) to various concentrations of particles. After 24 h of exposure, cell viability was not affected but significant modifications of mRNA expression of antioxidant (SOD-1 and -2, catalase, HO-1, NQO-1) and inflammatory markers (IL-6, IL-8, TNF-α) were observed and were dependent on smoke type. Particles rich in metal, such as HC-OS, induced a greatest depletion of AA and a greatest inflammatory response, whereas particles rich in organic compounds, such as RSS, induced a greatest DTT depletion and a greatest antioxidant response. In conclusion, the three smoke particles have an intrinsic oxidative potential and triggered a cell adaptive response. Our study improved the knowledge of particle toxicity of pyrotechnic smokes and scientific approach developed here could be used to study other type of particles.

Influence of the environmental relative humidity on the inflammatory response of skin model after exposure to various environmental pollutants.

The skin is an essential barrier, protecting the body against the environment and its numerous pollutants. Several environmental pollutants are known to affect the skin, inducing premature aging through mechanisms including oxidative stress, inflammation, and impairment of skin functions. Even climate conditions can impact the skin. Therefore, using a Reconstructed Human Epidermis (RHE), we tested the effect of two samples of fine particulate matters (PM0.3-2.5 - one metals-rich sample and the other organic compounds-rich), two Volatile Organic Compounds mixtures (VOCs - from a solvent-based paint and a water-based paint) and Tobacco Smoke (TS). All pollutants affected cellular functionality, but to a lesser extent for the water-based paint VOC. This effect was enhanced when RHE were preconditioned for 2 h by a semi-dry airflow (45% relative humidity) before pollutants application, compared to preconditioning by a humid airflow (90% relative humidity). In the absence of preconditioning, IL-1α, IL-6, IL-8, and RANTES were almost systematically induced by pollutants. When RHE were preconditioned by a semi-dry or humid airflow before being subjected to pollutants, the increase of IL-1α, IL-8, and RANTES falls into two groups. Similarly to RHE not treated with pollutants, RHE treated with VOCs after preconditioning by a semi-dry airflow showed increased IL-1α, IL-8, and RANTES release. On the contrary, RHE treated with PM or TS after preconditioning by a semi-dry airflow show a lower increase in IL-1α, IL-8, and RANTES compared to preconditioning by a humid airflow. The effect of real environmental relative humidity conditions of the air, combined with acute exposure to various environmental pollutants, seemed to relate mainly to structural changes of the skin, determining the outcome of the inflammatory response depending on the physicochemical characteristics of pollutants.

Auditory processing disorder in children: the value of a multidisciplinary assessment.

PURPOSE: Auditory processing disorder (APD) may affect 0.2-5% of the paediatric population. The diagnosis of APD remains difficult because of polymorphic symptoms possibly entangled with other difficulties. The purpose of this study was to evaluate a new multi-disciplinary assessment in the French language. METHODS: The battery of tests was composed of: (a) APD targeted speech assessment: speech perception in noise, a dichotic test, temporal processing tests (patterns); (b) Psychometric assessment: sustained auditory attention, sustained visual attention, evaluation of cognitive functions; (c) phonemic identification and discrimination; (d) ENT examination, tonal and vocal audiometry and ABR recordings. The diagnosis was made if two of the targeted speech tests were 2 standard deviations (SDs) below the mean or if only one of the tests was 3 SDs below. The auditory attention tests, as well as the phonemic identification and discrimination tests were complementary to the diagnostic battery. However, they did not allow for the diagnosis of APD. RESULTS: 50 children suspected of APD benefited from this protocol, and 12 were excluded from the study. A diagnosis of APD was confirmed in 17 children (45%). 59% of the patients had associated disorders. The most effective tests for diagnosing APD were dichotic testing (p = 0.001) and pattern recognition (frequency, p = 0.001). The sustained auditory attention test (p = 0.01) and the phonemic identification and discrimination test reinforced the diagnosis of APD. CONCLUSION: It seems important to evaluate children suspected of APD with a multi-disciplinary protocol. It makes it possible to diagnose APD children, but also to identify attentional difficulties and cognitive disorders that may be associated.

Functional connectivity is preserved but reorganized across several anesthetic regimes.

Under anesthesia, systemic variables and CBF are modified. How does this alter the connectivity measures obtained with rs-fMRI? To tackle this question, we explored the effect of four different anesthetics on Long Evans and Wistar rats with multimodal recordings of rs-fMRI, systemic variables and CBF. After multimodal signal processing, we show that the blood-oxygen-level-dependent (BOLD) variations and functional connectivity (FC) evaluated at low frequencies (0.031-0.25 â€‹Hz) do not depend on systemic variables and are preserved across a large interval of baseline CBF values. Based on these findings, we found that most brain areas remain functionally active under any anesthetics, i.e. connected to at least one other brain area, as shown by the connectivity graphs. In addition, we quantified the influence of nodes by a measure of functional connectivity strength to show the specific areas targeted by anesthetics and compare correlation values of edges at different levels. These measures enable us to highlight the specific network alterations induced by anesthetics. Altogether, this suggests that changes in connectivity could be evaluated under anesthesia, routinely used in the control of neurological injury.

Impact of pesticide coexposure: an experimental study with binary mixtures of lambda-cyhalothrin (LCT) and captan and its impact on the toxicokinetics of LCT biomarkers of exposure.

This study aimed at gaining more insights into the impact of pesticide coexposure on the toxicokinetics of biomarkers of exposure. This was done by conducting an in vivo experimental case-study with binary mixtures of lambda-cyhalothrin (LCT) and captan and by assessing its impact on the kinetic profiles of LCT biomarkers of exposure. Groups of male Sprague-Dawley rats were exposed orally by gavage to LCT alone (2.5 or 12.5 mg/kg bw) or to a binary mixture of LCT and captan (2.5/2.5 or 2.5/12.5 or 12.5/12.5 mg/kg bw). In order to establish the temporal profiles of the main metabolites of LCT, serial blood samples were taken, and excreta (urine and feces) were collected at predetermined intervals up to 48 h post-dosing. Major LCT metabolites were quantified in these matrices: 3-(2-chloro-3,3,3-trifluoroprop-1-enyl)-2,2-dimethyl-cyclopropane carboxylic (CFMP), 3-phenoxybenzoic acid (3-PBA), 4-hydroxy-3-phenoxybenzoic acid (4-OH3PBA). There was no clear effect of coexposure at the low LCT dose on the kinetics of CFMP and 3-PBA metabolites, based on the combined assessment of temporal profiles of these metabolites in plasma, urine and feces; however, plasma levels of 3-PBA were diminished in the coexposed high-dose groups. A significant effect of coexposure on the urinary excretion of 4-OH3PBA was also observed while fecal excretion was not affected. The temporal profiles of metabolites in plasma and in excreta were further influenced by the LCT dose. In addition, the study revealed kinetic differences between metabolites with a faster elimination of 3-PBA and 4-OH3BPA compared to CFMP. These results suggest that the pyrethroid metabolites CFMP and 3-PBA, mostly measured in biomonitoring studies, remain useful as biomarkers of exposure in mixtures, when pesticide exposure levels are below the reference values. However, the trend of coexposure effect observed in the benzyl metabolite pathway (in particular 4-OH3BPA) prompts further investigation.

Topological disintegration of resting state functional connectomes in coma.

Graph theory has been playing an increasingly important role in understanding the organizational properties of brain networks, subsequently providing new tools for the search of neural correlates of consciousness, particularly in the context of patients recovering from severe brain injury. However, this approach is not without challenges, as it usually relies on arbitrarily fixing a threshold in order to retain the strongest connections proportionally equal across subjects. This method increases the comparability between individuals or groups but it risks the inclusion of false positive and therefore spurious connections, especially in the context of brain disorders. Resting state data acquired in 25 coma patients and 22 healthy subjects was compared. We obtained a representative fixed density of significant connections by first applying a p-value-based threshold on healthy subjects' networks and then choosing a threshold at which all individuals exhibited meaningful connections. The obtained threshold (i.e. 10%) was used to construct graphs in the patient group. The findings showed that coma patients have lower number of significant connections with approximately 50% of them not fulfilling the criteria of the fixed density threshold. The remaining patients with relatively preserved global functional connectivity had sufficient significant connections between regions, but showed signs of major whole-brain network reorganization. These results warrant careful consideration in the construction of functional connectomes in patients with disorders of consciousness and set the scene for future studies investigating potential clinical implications of such an approach.

Improvement of spasticity following intermittent theta burst stimulation in multiple sclerosis is associated with modulation of resting-state functional connectivity of the primary motor cortices.

BACKGROUND: Intermittent theta burst stimulation (iTBS) of the primary motor cortex improves transiently lower limbs spasticity in multiple sclerosis (MS). However, the cerebral mechanisms underlying this effect have never been investigated. OBJECTIVE: To assess whether modulation of spasticity induced by iTBS is underlined by functional reorganization of the primary motor cortices. METHODS: A total of 17 patients with MS suffering from lower limbs spasticity were randomized to receive real iTBS or sham iTBS during the first half of a 5-week indoor rehabilitation programme. Spasticity was assessed using the Modified Ashworth Scale and the Visual Analogue Scale at baseline, after the stimulation session and at the end of the rehabilitation programme. Resting-state functional magnetic resonance imaging (fMRI) was performed at the three time points, and brain functional networks topology was analysed using graph-theoretical approach. RESULTS: At the end of stimulation, improvement of spasticity was greater in real iTBS group than in sham iTBS group ( p = 0.026). iTBS had a significant effect on the balance of the connectivity degree between the stimulated and the homologous primary motor cortex ( p = 0.005). Changes in inter-hemispheric balance were correlated with improvement of spasticity (rho = 0.56, p = 0.015). CONCLUSION: This longitudinal resting-state fMRI study evidences that functional reorganization of the primary motor cortices may underlie the effect of iTBS on spasticity in MS.

Depletion of brain functional connectivity enhancement leads to disability progression in multiple sclerosis: A longitudinal resting-state fMRI study.

BACKGROUND: The compensatory effect of brain functional connectivity enhancement in relapsing-remitting multiple sclerosis (RRMS) remains controversial. OBJECTIVE: To characterize the relationships between brain functional connectivity changes and disability progression in RRMS. METHODS: Long-range connectivity, short-range connectivity, and density of connections were assessed using graph theoretical analysis of resting-state functional magnetic resonance imaging (fMRI) data acquired in 38 RRMS patients (disease duration: 120 ± 32 months) and 24 controls. All subjects were explored at baseline and all patients and six controls 2 years later. RESULTS: At baseline, levels of long-range and short-range brain functional connectivity were higher in patients compared to controls. During the follow-up, decrease in connections' density was inversely correlated with disability progression. Post-hoc analysis evidenced differential evolution of brain functional connectivity metrics in patients according to their level of disability at baseline: while patients with lowest disability at baseline experienced an increase in all connectivity metrics during the follow-up, patients with higher disability at baseline showed a decrease in the connectivity metrics. In these patients, decrease in the connectivity metrics was associated with disability progression. CONCLUSION: The study provides two main findings: (1) brain functional connectivity enhancement decreases during the disease course after reaching a maximal level, and (2) decrease in brain functional connectivity enhancement participates in disability progression.

Nodal approach reveals differential impact of lateralized focal epilepsies on hub reorganization.

The impact of the hemisphere affected by impairment in models of network disease is not fully understood. Among such models, focal epilepsies are characterised by recurrent seizures generated in epileptogenic areas also responsible for wider network dysfunction between seizures. Previous work focusing on functional connectivity within circumscribed networks suggests a divergence of network integrity and compensatory capacity between epilepsies as a function of the laterality of seizure onset. We evaluated the ability of complex network theory to reveal changes in focal epilepsy in global and nodal parameters using graph theoretical analysis of functional connectivity data obtained with resting-state fMRI. Graphs of functional connectivity networks were derived from 19 right and 13 left focal epilepsy patients and 15 controls. Topological metrics (degree, local efficiency, global efficiency and modularity) were computed for a whole-brain, atlas-defined network. We also calculated a hub disruption index for each graph metric, measuring the capacity of the brain network to demonstrate increased connectivity in some nodes for decreased connectivity in others. Our data demonstrate that the patient group as a whole is characterised by network-wide pattern of reorganization, even while global parameters fail to distinguish between groups. Furthermore, multiple metrics indicate that epilepsies with differently lateralized epileptic networks are asymmetric in their burden on functional brain networks; with left epilepsy patients being characterised by reduced efficiency and modularity, while in right epilepsy patients we provide the first evidence that functional brain networks are characterised by enhanced connectivity and efficiency at some nodes whereas reduced in others.

Hubs of brain functional networks are radically reorganized in comatose patients.

Human brain networks have topological properties in common with many other complex systems, prompting the following question: what aspects of brain network organization are critical for distinctive functional properties of the brain, such as consciousness? To address this question, we used graph theoretical methods to explore brain network topology in resting state functional MRI data acquired from 17 patients with severely impaired consciousness and 20 healthy volunteers. We found that many global network properties were conserved in comatose patients. Specifically, there was no significant abnormality of global efficiency, clustering, small-worldness, modularity, or degree distribution in the patient group. However, in every patient, we found evidence for a radical reorganization of high degree or highly efficient "hub" nodes. Cortical regions that were hubs of healthy brain networks had typically become nonhubs of comatose brain networks and vice versa. These results indicate that global topological properties of complex brain networks may be homeostatically conserved under extremely different clinical conditions and that consciousness likely depends on the anatomical location of hub nodes in human brain networks.

Graph-based methods coupled with specific distributional distances for adversarial attack detection.

Artificial neural networks are prone to being fooled by carefully perturbed inputs which cause an egregious misclassification. These adversarial attacks have been the focus of extensive research. Likewise, there has been an abundance of research in ways to detect and defend against them. We introduce a novel approach of detection and interpretation of adversarial attacks from a graph perspective. For an input image, we compute an associated sparse graph using the layer-wise relevance propagation algorithm (Bach et al., 2015). Specifically, we only keep edges of the neural network with the highest relevance values. Three quantities are then computed from the graph which are then compared against those computed from the training set. The result of the comparison is a classification of the image as benign or adversarial. To make the comparison, two classification methods are introduced: (1) an explicit formula based on Wasserstein distance applied to the degree of node and (2) a logistic regression. Both classification methods produce strong results which lead us to believe that a graph-based interpretation of adversarial attacks is valuable.

Acute and repeated exposures of normal human bronchial epithelial (NHBE) cells culture to particles from a coloured pyrotechnic smoke.

Coloured pyrotechnic smokes are frequently used in the military field and occasionally by civilians, but their health hazards have been little studied. The main concern could rise from inhalation of smoke particles. Our previous study showed that acute exposure to particles from a red signalling smoke (RSS) induced an antioxidant and inflammatory responses in small airway epithelial cells. The aim of this study was to further explore the toxicity of RSS particles at a more proximal level of the respiratory tract, using normal human bronchial epithelial cells grown at the Air-Liquid Interface. Acute exposure (24 h) induced an oxidative stress that persisted 24 h post-exposure, associated with particle internalization and epithelium morphological changes (cuboidal appearance and loss of cilia). Repeated exposures (4×16h) to RSS particles did not trigger oxidative stress but cell morphological changes occurred. Overall, this study provides a better overview of the toxic effects of coloured smoke particles.

Nodal-statistics-based equivalence relation for graph collections.

Node role explainability in complex networks is very difficult yet is crucial in different application domains such as social science, neurosciences, or computer science. Many efforts have been made on the quantification of hubs revealing particular nodes in a network using a given structural property. Yet, in several applications, when multiple instances of networks are available and several structural properties appear to be relevant, the identification of node roles remains largely unexplored. Inspired by the node automorphically equivalence relation, we define an equivalence relation on graph nodes associated with any collection of nodal statistics (i.e., any functions on the node set). This allows us to define new graph global measures: the power coefficient and the orthogonality score to evaluate the parsimony and heterogeneity of a given nodal statistics collection. In addition, we introduce a new method based on structural patterns to compare graphs that have the same vertices set. This method assigns a value to a node to determine its role distinctiveness in a graph family. Extensive numerical results of our method are conducted on both generative graph models and real data concerning human brain functional connectivity. The differences in nodal statistics are shown to be dependent on the underlying graph structure. Comparisons between generative models and real networks combining two different nodal statistics reveal the complexity of human brain functional connectivity with differences at both global and nodal levels. Using a group of 200 healthy controls connectivity networks, our method computes high correspondence scores among the whole population to detect homotopy and finally quantify differences between comatose patients and healthy controls.