The Neurobiology of Life Course Socioeconomic Conditions and Associated Cognitive Performance in Middle to Late Adulthood.

Despite major advances, our understanding of the neurobiology of life course socioeconomic conditions is still scarce. This study aimed to provide insight into the pathways linking socioeconomic exposures-household income, last known occupational position, and life course socioeconomic trajectories-with brain microstructure and cognitive performance in middle to late adulthood. We assessed socioeconomic conditions alongside quantitative relaxometry and diffusion-weighted magnetic resonance imaging indicators of brain tissue microstructure and cognitive performance in a sample of community-dwelling men and women (N = 751, aged 50-91 years). We adjusted the applied regression analyses and structural equation models for the linear and nonlinear effects of age, sex, education, cardiovascular risk factors, and the presence of depression, anxiety, and substance use disorders. Individuals from lower-income households showed signs of advanced brain white matter (WM) aging with greater mean diffusivity (MD), lower neurite density, lower myelination, and lower iron content. The association between household income and MD was mediated by neurite density (B = 0.084, p = 0.003) and myelination (B = 0.019, p = 0.009); MD partially mediated the association between household income and cognitive performance (B = 0.017, p < 0.05). Household income moderated the relation between WM microstructure and cognitive performance, such that greater MD, lower myelination, or lower neurite density was only associated with poorer cognitive performance among individuals from lower-income households. Individuals from higher-income households showed preserved cognitive performance even with greater MD, lower myelination, or lower neurite density. These findings provide novel mechanistic insights into the associations between socioeconomic conditions, brain anatomy, and cognitive performance in middle to late adulthood.

Obstructive sleep apnea and cognitive functioning in the older general population: The moderating effect of age, sex, ApoE4, and obesity.

Research on the relationship between obstructive sleep apnea and cognitive functioning has yielded conflicting results, particularly in the older population, and moderators of this association have rarely been studied. Here we investigated the cross-sectional association between obstructive sleep apnea and cognitive functioning as well as the moderating effect of age, sex, apolipoprotein E4, and obesity on this association among community-dwelling older people. We analysed data from 496 participants (71.4 ± 4.4 years; 45.6% men) of the HypnoLaus study who underwent polysomnography and a battery of neuropsychological tests. The sample was categorised as no-to-mild obstructive sleep apnea (apnea-hypopnea index 0-14.9/h; reference), moderate obstructive sleep apnea (apnea-hypopnea index 15.0-29.9/h), or severe obstructive sleep apnea (apnea-hypopnea index ≥30/h). Regression and moderation analyses were performed with adjustment for confounders. Apolipoprotein E4 and obesity moderated the association between severe obstructive sleep apnea and processing speed, whereas no moderating effects were found for age and sex. In apolipoprotein E4 carriers only, severe obstructive sleep apnea was associated with lower performance in Stroop condition 1 (B = 3.13, p = 0.024). In obese participants only, severe obstructive sleep apnea was associated with lower performance in Stroop condition 1 (B = 3.02, p = 0.025) and Stroop condition 2 (B = 3.30, p = 0.034). Severe obstructive sleep apnea was also associated with lower executive function in the whole sample according to Stroop condition 3 (B = 3.44, p = 0.020) and Stroop interference score (B = 0.24, p = 0.006). Our findings support associations of severe obstructive sleep apnea (but not moderate obstructive sleep apnea) with lower performance in processing speed and executive function in the older general population. Apolipoprotein E4 and obesity appear to be vulnerability factors that strengthen the association between severe obstructive sleep apnea and lower performance in processing speed.

Diabetes mellitus in older persons with neurocognitive disorder: overtreatment prevalence and associated structural brain MRI findings.

BACKGROUND: Tight diabetes control is often applied in older persons with neurocognitive disorder resulting in increased hypoglycemic episodes but little is known about the pattern of brain injury in these overtreated patients. This study aims to: (a) quantify the prevalence of diabetes overtreatment in cognitively impaired older adults in a clinical population followed in an academic memory clinic (b) identify risk factors contributing to overtreatment; and (c) explore the association between diabetes overtreatment and specific brain region volume changes. METHODS: Retrospective study of older patients with type 2 diabetes and cognitive impairment who were diagnosed in a memory clinic from 2013 to 2020. Patients were classified into vulnerable and dependent according to their health profile. Overtreatment was defined when glycated hemoglobin was under 7% for vulnerable and 7.6% for dependent patients. Characteristics associated to overtreatment were examined in multivariable analysis. Grey matter volume in defined brain regions was measured from MRI using voxel-based morphometry and compared in patients over- vs. adequately treated. RESULTS: Among 161 patients included (median age 76.8 years, range 60.8-93.3 years, 32.9% women), 29.8% were considered as adequately treated, 54.0% as overtreated, and 16.2% as undertreated. In multivariable analyses, no association was observed between diabetes overtreatment and age or the severity of cognitive impairment. Among patients with neuroimaging data (N = 71), associations between overtreatment and grey matter loss were observed in several brain regions. Specifically, significant reductions in grey matter were found in the caudate (adj ß coeff: -0.217, 95%CI: [-0.416 to -0.018], p = .033), the precentral gyri (adj ßcoeff:-0.277, 95%CI: [-0.482 to -0.073], p = .009), the superior frontal gyri (adj ßcoeff: -0.244, 95%CI: [-0.458 to -0.030], p = .026), the calcarine cortex (adj ßcoeff:-0.193, 95%CI: [-0.386 to -0.001], p = .049), the superior occipital gyri (adj ßcoeff: -0.291, 95%CI: [-0.521 to -0.061], p = .014) and the inferior occipital gyri (adj ßcoeff: -0.236, 95%CI: [-0.456 to - 0.015], p = .036). CONCLUSION: A significant proportion of older patients with diabetes and neurocognitive disorder were subjected to excessively intensive treatment. The association identified with volume loss in several specific brain regions highlights the need to further investigate the potential cerebral damages associated with overtreatment and related hypoglycemia in larger sample.

Obstructive sleep apnoea and 5-year cognitive decline in the elderly.

BACKGROUND: The relationship between obstructive sleep apnoea (OSA) and cognitive decline remains controversial, especially in the elderly population. We used data from the HypnoLaus study to assess associations between OSA and longitudinal cognitive changes in a sample of community-dwelling elderly individuals. METHODS: We studied associations between polysomnographic OSA parameters (of breathing/hypoxaemia and sleep fragmentation) and cognitive changes over a 5-year period, after adjustment for potential confounders. The primary outcome was the annual change in cognitive scores. The moderating effects of age, sex and apolipoprotein E4 (ApoE4) status were also examined. RESULTS: 358 elderly individuals without dementia were included (mean±sd age 71.0±4.2 years; 42.5% males). A lower mean peripheral oxygen saturation (S pO2 ) during sleep was associated with a steeper decline in Mini-Mental State Examination (B= -0.12, p=0.004), Stroop test condition 1 (B=0.53, p=0.002) and Free and Cued Selective Reminding Test delayed free recall (B= -0.05, p=0.008). A longer time spent asleep with S pO2 <90% was associated with a steeper decline in Stroop test condition 1 (B=0.47, p=0.006). Moderation analysis showed that apnoea-hypopnoea index and oxygen desaturation index were associated with a steeper decline in global cognitive function, processing speed and executive function only in older participants, men and ApoE4 carriers. CONCLUSIONS: Our results provide evidence of the contribution of OSA and nocturnal hypoxaemia to cognitive decline in the elderly population.

Life-course socioeconomic conditions and cognitive performance in older adults: a cross-cohort comparison.

OBJECTIVES: Socioeconomic disadvantage predicts the level of cognitive performance in old age, but findings have been mixed for trajectories of performance. This study examined associations between life-course socioeconomic conditions, including social mobility, and cognitive performance assessed in terms of level and change, across multiple cognitive domains in two independent cohorts of older adults. METHODS: Data were from two Swiss population-based cohorts: CoLaus|PsyCoLaus (N = 1210, mean age 72 years) and Vivre/Leben/Vivere (N = 993, mean age 75 years). Verbal fluency, processing speed, cognitive flexibility, memory, and global cognitive performance were assessed at two time points, each spaced 6 years apart. Associations between socioeconomic conditions (father's occupation, parental education, own education, own occupation, household income, and social mobility) and cognitive performance were examined within each cohort, and using pooled data. Covariates included health behaviors, comorbidities, and depressive symptoms. RESULTS: Across cohorts, socioeconomic disadvantage predicted a lower level of performance across different cognitive domains, including processing speed, verbal fluency, and memory. Moreover, individuals who experienced life-course socioeconomic disadvantage performed worse than those who experienced upward social mobility. Associations between socioeconomic disadvantage and cognitive decline were less consistent. CONCLUSION: Life-course socioeconomic conditions predict performance level across different cognitive domains, and, to a lesser extent, performance trajectories.

Temporal Dynamics of Brain White Matter Plasticity in Sighted Subjects during Tactile Braille Learning: A Longitudinal Diffusion Tensor Imaging Study.

The white matter (WM) architecture of the human brain changes in response to training, though fine-grained temporal characteristics of training-induced white matter plasticity remain unexplored. We investigated white matter microstructural changes using diffusion tensor imaging at five different time points in 26 sighted female adults during 8 months of training on tactile braille reading. Our results show that training-induced white matter plasticity occurs both within and beyond the trained sensory modality, as reflected by fractional anisotropy (FA) increases in somatosensory and visual cortex, respectively. The observed changes followed distinct time courses, with gradual linear FA increase along the training in the somatosensory cortex and sudden visual cortex cross-modal plasticity occurring after braille input became linguistically meaningful. WM changes observed in these areas returned to baseline after the cessation of learning in line with the supply-demand model of plasticity. These results also indicate that the temporal dynamics of microstructural plasticity in different cortical regions might be modulated by the nature of computational demands. We provide additional evidence that observed FA training-induced changes are behaviorally relevant to tactile reading. Together, these results demonstrate that WM plasticity is a highly dynamic process modulated by the introduction of novel experiences.SIGNIFICANCE STATEMENT Throughout the lifetime the human brain is shaped by various experiences. Training-induced reorganization in white matter (WM) microstructure has been reported, but we know little about its temporal dynamics. To fill this gap, we scanned sighted subjects five times during tactile braille reading training. We observed different dynamics of WM plasticity in the somatosensory and visual cortices implicated in braille reading. The former showed a continuous increase in WM tissue anisotropy along with tactile training, while microstructural changes in the latter were observed only after the participants learned to read braille words. Our results confirm the supply-demand model of brain plasticity and provide evidence that WM reorganization depends on distinct computational demands and functional roles of regions involved in the trained skill.

Restoring statistical validity in group analyses of motion-corrupted MRI data.

Motion during the acquisition of magnetic resonance imaging (MRI) data degrades image quality, hindering our capacity to characterise disease in patient populations. Quality control procedures allow the exclusion of the most affected images from analysis. However, the criterion for exclusion is difficult to determine objectively and exclusion can lead to a suboptimal compromise between image quality and sample size. We provide an alternative, data-driven solution that assigns weights to each image, computed from an index of image quality using restricted maximum likelihood. We illustrate this method through the analysis of quantitative MRI data. The proposed method restores the validity of statistical tests, and performs near optimally in all brain regions, despite local effects of head motion. This method is amenable to the analysis of a broad type of MRI data and can accommodate any measure of image quality.

Signatures of life course socioeconomic conditions in brain anatomy.

Socioeconomic status (SES) plays a significant role in health and disease. At the same time, early-life conditions affect neural function and structure, suggesting the brain may be a conduit for the biological embedding of SES. Here, we investigate the brain anatomy signatures of SES in a large-scale population cohort aged 45-85 years. We assess both gray matter morphometry and tissue properties indicative of myelin content. Higher life course SES is associated with increased volume in several brain regions, including postcentral and temporal gyri, cuneus, and cerebellum. We observe more widespread volume differences and higher myelin content in the sensorimotor network but lower myelin content in the temporal lobe associated with childhood SES. Crucially, childhood SES differences persisted in adult brains even after controlling for adult SES, highlighting the unique contribution of early-life conditions to brain anatomy, independent of later changes in SES. These findings inform on the biological underpinnings of social inequality, particularly as they pertain to early-life conditions.

Mind the gap: Performance metric evaluation in brain-age prediction.

Estimating age based on neuroimaging-derived data has become a popular approach to developing markers for brain integrity and health. While a variety of machine-learning algorithms can provide accurate predictions of age based on brain characteristics, there is significant variation in model accuracy reported across studies. We predicted age in two population-based datasets, and assessed the effects of age range, sample size and age-bias correction on the model performance metrics Pearson's correlation coefficient (r), the coefficient of determination (R2 ), Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). The results showed that these metrics vary considerably depending on cohort age range; r and R2 values are lower when measured in samples with a narrower age range. RMSE and MAE are also lower in samples with a narrower age range due to smaller errors/brain age delta values when predictions are closer to the mean age of the group. Across subsets with different age ranges, performance metrics improve with increasing sample size. Performance metrics further vary depending on prediction variance as well as mean age difference between training and test sets, and age-bias corrected metrics indicate high accuracy-also for models showing poor initial performance. In conclusion, performance metrics used for evaluating age prediction models depend on cohort and study-specific data characteristics, and cannot be directly compared across different studies. Since age-bias corrected metrics generally indicate high accuracy, even for poorly performing models, inspection of uncorrected model results provides important information about underlying model attributes such as prediction variance.

Sex- and age-specific associations between cardiometabolic risk and white matter brain age in the UK Biobank cohort.

Cardiometabolic risk (CMR) factors are associated with accelerated brain aging and increased risk for sex-dimorphic illnesses such as Alzheimer's disease (AD). Yet, it is unknown how CMRs interact with sex and apolipoprotein E-ϵ4 (APOE4), a known genetic risk factor for AD, to influence brain age across different life stages. Using age prediction based on multi-shell diffusion-weighted imaging data in 21,308 UK Biobank participants, we investigated whether associations between white matter Brain Age Gap (BAG) and body mass index (BMI), waist-to-hip ratio (WHR), body fat percentage (BF%), and APOE4 status varied (i) between males and females, (ii) according to age at menopause in females, and (iii) across different age groups in males and females. We report sex differences in associations between BAG and all three CMRs, with stronger positive associations among males compared to females. Independent of APOE4 status, higher BAG (older brain age relative to chronological age) was associated with greater BMI, WHR, and BF% in males, whereas in females, higher BAG was associated with greater WHR, but not BMI and BF%. These divergent associations were most prominent within the oldest group of females (66-81 years), where greater BF% was linked to lower BAG. Earlier menopause transition was associated with higher BAG, but no interactions were found with CMRs. In conclusion, the findings point to sex- and age-specific associations between CMRs and brain age. Incorporating sex as a factor of interest in studies addressing CMR may promote sex-specific precision medicine, consequently improving health care for both males and females.

Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs.

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.

Abnormal brain iron accumulation in obstructive sleep apnea: A quantitative MRI study in the HypnoLaus cohort.

Obstructive sleep apnea syndrome (OSA) may be a risk factor for Alzheimer's disease. One of the hallmarks of Alzheimer's disease is disturbed iron homeostasis leading to abnormal iron deposition in brain tissue. To date, there is no empirical evidence to support the hypothesis of altered brain iron homeostasis in patients with obstructive sleep apnea as well. Data were analysed from 773 participants in the HypnoLaus study (mean age 55.9 ± 10.3 years) who underwent polysomnography and brain MRI. Cross-sectional associations were tested between OSA parameters and the MRI effective transverse relaxation rate (R2*) - indicative of iron content - in 68 grey matter regions, after adjustment for confounders. The group with severe OSA (apnea-hypopnea index ≥30/h) had higher iron levels in the left superior frontal gyrus (F3,760  = 4.79, p = 0.003), left orbital gyri (F3,760  = 5.13, p = 0.002), right and left middle temporal gyrus (F3,760  = 4.41, p = 0.004 and F3,760  = 13.08, p < 0.001, respectively), left angular gyrus (F3,760  = 6.29, p = 0.001), left supramarginal gyrus (F3,760  = 4.98, p = 0.003), and right cuneus (F3,760  = 7.09, p < 0.001). The parameters of nocturnal hypoxaemia were all consistently associated with higher iron levels. Measures of sleep fragmentation had less consistent associations with iron content. This study provides the first evidence of increased brain iron levels in obstructive sleep apnea. The observed iron changes could reflect underlying neuropathological processes that appear to be driven primarily by hypoxaemic mechanisms.

Unraveling brain interactions in vision: The example of crowding.

Crowding, the impairment of target discrimination in clutter, is the standard situation in vision. Traditionally, crowding is explained with (feedforward) models, in which only neighboring elements interact, leading to a "bottleneck" at the earliest stages of vision. It is with this implicit prior that most functional magnetic resonance imaging (fMRI) studies approach the identification of the "neural locus" of crowding, searching for the earliest visual area in which the blood-oxygenation-level-dependent (BOLD) signal is suppressed under crowded conditions. Using this classic approach, we replicated previous findings of crowding-related BOLD suppression starting in V2 and increasing up the visual hierarchy. Surprisingly, under conditions of uncrowding, in which adding flankers improves performance, the BOLD signal was further suppressed. This suggests an important role for top-down connections, which is in line with global models of crowding. To discriminate between various possible models, we used dynamic causal modeling (DCM). We show that recurrent interactions between all visual areas, including higher-level areas like V4 and the lateral occipital complex (LOC), are crucial in crowding and uncrowding. Our results explain the discrepancies in previous findings: in a recurrent visual hierarchy, the crowding effect can theoretically be detected at any stage. Beyond crowding, we demonstrate the need for models like DCM to understand the complex recurrent processing which most likely underlies human perception in general.

Mapping grip force to motor networks.

AIM: There is ongoing debate about the role of cortical and subcortical brain areas in force modulation. In a whole-brain approach, we sought to investigate the anatomical basis of grip force whilst acknowledging interindividual differences in connectivity patterns. We tested if brain lesion mapping in patients with unilateral motor deficits can inform whole-brain structural connectivity analysis in healthy controls to uncover the networks underlying grip force. METHODS: Using magnetic resonance imaging (MRI) and whole-brain voxel-based morphometry in chronic stroke patients (n=55) and healthy controls (n=67), we identified the brain regions in both grey and white matter significantly associated with grip force strength. The resulting statistical parametric maps (SPMs) provided seed areas for whole-brain structural covariance analysis in a large-scale community dwelling cohort (n=977) that included beyond volume estimates, parameter maps sensitive to myelin, iron and tissue water content. RESULTS: The SPMs showed symmetrical bilateral clusters of correlation between upper limb motor performance, basal ganglia, posterior insula and cortico-spinal tract. The covariance analysis with the seed areas derived from the SPMs demonstrated a widespread anatomical pattern of brain volume and tissue properties, including both cortical, subcortical nodes of motor networks and sensorimotor areas projections. CONCLUSION: We interpret our covariance findings as a biological signature of brain networks implicated in grip force. The data-driven definition of seed areas obtained from chronic stroke patients showed overlapping structural covariance patterns within cortico-subcortical motor networks across different tissue property estimates. This cumulative evidence lends face validity of our findings and their biological plausibility.

Brain plasticity dynamics during tactile Braille learning in sighted subjects: Multi-contrast MRI approach.

A growing body of empirical evidence supports the notion of diverse neurobiological processes underlying learning-induced plasticity changes in the human brain. There are still open questions about how brain plasticity depends on cognitive task complexity, how it supports interactions between brain systems and with what temporal and spatial trajectory. We investigated brain and behavioural changes in sighted adults during 8-months training of tactile Braille reading whilst monitoring brain structure and function at 5 different time points. We adopted a novel multivariate approach that includes behavioural data and specific MRI protocols sensitive to tissue properties to assess local functional and structural and myelin changes over time. Our results show that while the reading network, located in the ventral occipitotemporal cortex, rapidly adapts to tactile input, sensory areas show changes in grey matter volume and intra-cortical myelin at different times. This approach has allowed us to examine and describe neuroplastic mechanisms underlying complex cognitive systems and their (sensory) inputs and (motor) outputs differentially, at a mesoscopic level.

Mean Oxygen Saturation during Sleep Is Related to Specific Brain Atrophy Pattern.

OBJECTIVE: There is much controversy about the neurobiological mechanisms underlying the effects of sleep-disordered breathing on the brain. The aim of this study was to investigate the association between markers of sleep-related hypoxemia and brain anatomy. METHODS: We used data from a large-scale cohort from the general population (n = 775, 50.6% males, age range = 45-86 years, mean age = 60.3 ± 9.9) that underwent full polysomnography and brain magnetic resonance imaging to correlate respiratory variables with regional brain volume estimates. RESULTS: After adjusting for age, gender, and cardiovascular risk factors, only mean oxygen saturation during sleep was associated with bilateral volume of hippocampus (right: p = 0.001; left: p < 0.001), thalamus (right: p < 0.001; left: p < 0.001), putamen (right: p = 0.001; left: p = 0.001), and angular gyrus (right: p = 0.011; left: p = 0.001). We observed the same relationship in left hemispheric amygdala (p = 0.010), caudate (p = 0.008), inferior frontal gyrus (p = 0.004), and supramarginal gyrus (p = 0.003). The other respiratory variables-lowest oxygen saturation, percentage of sleep time with oxygen saturation < 90%, apnea-hypopnea index, and oxygen desaturation index-did not show any significant association with brain volumes. INTERPRETATION: Lower mean oxygen saturation during sleep was associated with atrophy of cortical and subcortical brain areas known for high sensitivity to oxygen supply. Their vulnerability to hypoxemia may contribute to behavioral phenotype and cognitive decline in patients with sleep-disordered breathing. ANN NEUROL 2020;87:921-930.

Correction: Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Prior to and following the publication of this article the authors noted that the complete list of authors was not included in the main article and was only present in Supplementary Table 1. The author list in the original article has now been updated to include all authors, and Supplementary Table 1 has been removed. All other supplementary files have now been updated accordingly. Furthermore, in Table 1 of this Article, the replication cohort for the row Close relative in data set, n (%) was incorrect. All values have now been corrected to 0(0%). The publishers would like to apologise for this error and the inconvenience it may have caused.

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (ß = -0.71 to -1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (ß = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10-6, 1.7 × 10-9, 3.5 × 10-12 and 1.0 × 10-4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes.

[Cancer-related cognitive impairment in older adults]. / Troubles neurocognitifs chez les personnes âgées avec maladie oncologique.

Chemotherapy is associated with transient or permanent cognitive dysfunction ranging from subjective complaints to measurable deficits in working memory, attention and language. Given that old age may be related to cognitive decline, the interaction between chemotherapy-induced cognitive impairment and the effects of age is of growing concern in view of our aging population. Chemotherapy-associated cognitive dysfunction may have an additive impact on pre-existing age-related cognitive performance decline, which calls for awareness in its detection, to reduce impact on quality of life and improve management of older patients. We discuss here the « chemobrain ¼, concept, review the existing evidence about pathophysiology, neuroimaging and cognitive phenotype and propose practical tools for routine detection in the outpatient setting.

Les chimiothérapies peuvent induire une dysfonction cognitive transitoire ou permanente, pouvant aller d'une plainte cognitive subjective à une atteinte réelle de la mémoire de travail, de l'attention ou du langage. L'interaction entre l'atteinte cognitive attribuée à ces thérapies et celle liée à l'âge est une question grandissante compte tenu du vieillissement de la population. Elle justifie une attention particulière à la détection précoce de troubles cognitifs afin d'en réduire l'impact négatif sur la qualité de vie et optimiser la prise en charge médicale. Dans cet article, nous abordons le concept de « chemobrain ¼, et en revoyons les connaissances actuelles de physiopathologie, de neuro-imagerie ainsi que les phénotypes neuropsychologiques, afin de proposer quelques outils de détection et de prise en charge au cabinet.

hMRI - A toolbox for quantitative MRI in neuroscience and clinical research.

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.