Midlife dynamics of white matter architecture in lexical production.

We aimed to examine the white matter changes associated with lexical production difficulties, beginning in midlife with increased naming latencies. To delay lexical production decline, middle-aged adults may rely on domain-general and language-specific compensatory mechanisms proposed by the LARA model (Lexical Access and Retrieval in Aging). However, the white matter changes supporting these mechanisms remains largely unknown. Using data from the CAMCAN cohort, we employed an unsupervised and data-driven methodology to examine the relationships between diffusion-weighted imaging and lexical production. Our findings indicate that midlife is marked by alterations in brain structure within distributed dorsal, ventral, and anterior cortico-subcortical networks, marking the onset of lexical production decline around ages 53-54. Middle-aged adults may initially adopt a "semantic strategy" to compensate for lexical production challenges, but this strategy seems compromised later (ages 55-60) as semantic control declines. These insights underscore the interplay between domain-general and language-specific processes in the trajectory of lexical production performance in healthy aging and hint at potential biomarkers for language-related neurodegenerative pathologies.

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.

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.

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.

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.

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.

Functional brain networks reflect spatial and temporal autocorrelation.

High-throughput experimental methods in neuroscience have led to an explosion of techniques for measuring complex interactions and multi-dimensional patterns. However, whether sophisticated measures of emergent phenomena can be traced back to simpler, low-dimensional statistics is largely unknown. To explore this question, we examined resting-state functional magnetic resonance imaging (rs-fMRI) data using complex topology measures from network neuroscience. Here we show that spatial and temporal autocorrelation are reliable statistics that explain numerous measures of network topology. Surrogate time series with subject-matched spatial and temporal autocorrelation capture nearly all reliable individual and regional variation in these topology measures. Network topology changes during aging are driven by spatial autocorrelation, and multiple serotonergic drugs causally induce the same topographic change in temporal autocorrelation. This reductionistic interpretation of widely used complexity measures may help link them to neurobiology.

Recurrent Benign Paroxysmal Positional Vertigo in DFNB16 Patients with Biallelic STRC Gene Deletions.

OBJECTIVE: Deletions of STRC gene (DFNB16) account for 12% of isolated congenital mild to moderate hearing loss (HL). In mice, the stereocilin protein, encoded by STRC , is present in the vestibular kinocilium embedded in the otoconial membrane of the utricular macula. Despite this, effects on vestibular function have not been widely investigated. The aim of this study was to investigate the prevalence of benign paroxysmal positional vertigo (BPPV) in a cohort of DFNB16 patients. STUDY DESIGN: Observational descriptive epidemiological study. SETTING: Single-center study, in a tertiary referral center. PATIENTS: Older than 5 years, with a genetic diagnosis of HL related to biallelic STRC gene deletions, diagnosed between 2015 and 2021. INTERVENTION: Patients or their parents were interviewed to determine whether they had experienced vertigo or episodes of BPPV. MAIN OUTCOME MEASURE: Criteria were at least five acute episodes of rotatory vertigo, each lasting less than 1 minute, episodes triggered by changes in specific head position, and an absence of neurological symptoms. RESULTS: Sixty-four patients having mild (33%) to moderate (66%) HL were included. Median age was 15 years (range, 6-48 yr). Prevalence of BPPV was 39% (25 of 64). Median age of first onset was 13 years (range, 3-18 yr). CONCLUSIONS: This study showed recurrent BPPV and early age of onset in patients with biallelic STRC gene deletions. BPPV may be associated with the HL phenotype in patients with STRC gene deletions. It is important to inform patients and families of this potential risk such that appropriate management can be proposed.

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.