White Matter Brain Structure Predicts Language Performance and Learning Success

Individual differences in the ability to deal with language have long been discussed. The neural basis of these, however, is yet unknown. Here we investigated the relationship between long-range white matter connectivity of the brain, as revealed by diffusion tractography, and the ability to process syntactically complex sentences in the participants' native language as well as the improvement thereof by multi-day training. We identified specific network motifs that indeed related white matter tractography to individual language processing performance. First, for two such motifs, one in the left and one in the right hemisphere, their individual prevalence significantly predicted the individual language performance suggesting a predisposition for the individual ability to process syntactically complex sentences, which manifests itself in the white matter brain structure. Both motifs comprise a number of cortical regions, but seem to be dominated by areas known for the involvement in working memory rather than the classical language network itself. Second, we identified another left hemispheric network motif, whose change of prevalence over the training period significantly correlated with the individual change in performance, thus reflecting training induced white matter plasticity. This motif comprises diverse cortical areas including regions known for their involvement in language processing, working memory and motor functions. The present findings suggest that individual differences in language processing and learning can be explained, in part, by individual differences in the brain's white matter structure. Brain structure may be a crucial factor to be considered when discussing variations in human cognitive performance, more generally.

APOE ε4 effects on hippocampal atrophy in the healthy elderly reflect future cognitive decline

The APOE ϵ4 allele is the primary genetic risk factor for late onset Alzheimer's disease (AD). A cardinal problem in determining APOE ϵ4's effect on cognition and brain structure in older individuals is dissociating prodromal changes — linked to increased AD risk — from potential phenotypic differences. To address this, we used cognitive and neuroimaging data from a large cohort of cognitively normal 69-86 year-olds with up to 8 yearly follow-ups to investigate cross-sectional and longitudinal differences between APOE ϵ3/ϵ3 homozygotes and ϵ3/ϵ4 heterozygotes. Although we found a significant age-by-genotype interaction in right hippocampal volume, once our analyses were conditionalised by future diagnosis to account for prodromal mild cognitive impairment (MCI) and AD, this effect was no longer observed. Likewise, longitudinally, rate of hippocampal atrophy was determined not by genotype, but by future diagnosis. Thus, we provide direct evidence in support of the prodromal hypothesis of APOE ϵ4 on brain structure.

Study of Brain Structure and Function in Chronic Mountain Sickness Based on fMRI

Objective: Headache and memory impairment are the primary clinical symptoms of chronic mountain sickness (CMS). In this study, we used voxel-based morphometry (VBM) and the amplitude of the low-frequency fluctuation method (ALFF) based on blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) to identify changes in the brain structure and function caused by CMS.Materials and Methods: T1W anatomical images and a resting-state functional MRI (fMRI) of the whole brain were performed in 24 patients diagnosed with CMS and 25 normal controls matched for age, sex, years of education, and living altitude. MRI images were acquired, followed by VBM and ALFF data analyses.Results: Compared with the control group, the CMS group had increased gray matter volume in the left cerebellum crus II area, left inferior temporal gyrus, right middle temporal gyrus, right insula, right caudate nucleus, and bilateral lentiform nucleus along with decreased gray matter volume in the left middle occipital gyrus and left middle temporal gyrus. White matter was decreased in the bilateral middle temporal gyrus and increased in the right Heschl's gyrus. Resting-state fMRI in patients with CMS showed increased spontaneous brain activity in the left supramarginal gyrus, left parahippocampal gyrus, and left middle temporal gyrus along with decreased spontaneous brain activity in the right cerebellum crus I area and right supplementary motor area.Conclusion: Patients with CMS had differences in gray and white matter volume and abnormal spontaneous brain activity in multiple brain regions compared to the controls. This suggests that long-term chronic hypoxia may induce changes in brain structure and function, resulting in CMS.

Long-term association of pregnancy and maternal brain structure: the Rotterdam Study

The peripartum period is the highest risk interval for the onset or exacerbation of psychiatric illness in women’s lives. Notably, pregnancy and childbirth have been associated with short-term structural and functional changes in the maternal human brain. Yet the long-term effects of pregnancy on maternal brain structure remain unknown. We investigated a large population-based cohort to examine the association between parity and brain structure. In total, 2,835 women (mean age 65.2 years; all free from dementia, stroke, and cortical brain infarcts) from the Rotterdam Study underwent magnetic resonance imaging (1.5 T) between 2005 and 2015. Associations of parity with global and lobar brain tissue volumes, white matter microstructure, and markers of vascular brain disease were examined using regression models. We found that parity was associated with a larger global gray matter volume (β = 0.14, 95% CI = 0.09–0.19), a finding that persisted following adjustment for sociodemographic factors. A non-significant dose-dependent relationship was observed between a higher number of childbirths and larger gray matter volume. The gray matter volume association with parity was globally proportional across lobes. No associations were found regarding white matter volume or integrity, nor with markers of cerebral small vessel disease. The current findings suggest that pregnancy and childbirth are associated with robust long-term changes in brain structure involving a larger global gray matter volume that persists for decades. Future studies are warranted to further investigate the mechanism and physiological relevance of these differences in brain morphology.

Excitatory/inhibitory imbalance in autism: the role of glutamate and GABA gene-sets in symptoms and cortical brain structure

Background: The excitatory/inhibitory (E/I) imbalance hypothesis posits that an imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) mechanisms underlies the behavioral characteristics of autism spectrum disorder (autism). However, how E/I imbalance arises and how it may differ across autism symptomatology and brain regions is not well understood. Methods: We used innovative analysis methods - combining competitive gene-set analysis and gene-expression profiles in relation to cortical thickness (CT)- to investigate the relationship between genetic variance, brain structure and autism symptomatology of participants from the EU-AIMS LEAP cohort (autism=360, male/female=259/101; neurotypical control participants=279, male/female=178/101) aged 6 to 30 years. Competitive gene-set analysis investigated associations between glutamatergic and GABAergic signaling pathway gene-sets and clinical measures, and CT. Additionally, we investigated expression profiles of the genes within those sets throughout the brain and how those profiles relate to differences in CT between autistic and neurotypical control participants in the same regions. Results: The glutamate gene-set was associated with all autism symptom severity scores on the Autism Diagnostic Observation Schedule-2 (ADOS-2) and the Autism Diagnostic Interview-Revised (ADI-R) within the autistic group, while the GABA set was associated with sensory processing measures (using the SSP subscales) across all participants. Brain regions with greater gene expression of both glutamate and GABA genes showed greater differences in CT between autistic and neurotypical control participants. Conclusions: Our results suggest crucial roles for glutamate and GABA genes in autism symptomatology as well as CT, where GABA is more strongly associated with sensory processing and glutamate more with autism symptom severity.

Age-Related Trajectories of Brain Structure–Function Coupling in Female Roller Derby Athletes

Contact and collision sports are believed to accelerate brain aging. Postmortem studies of the human brain have implicated tau deposition in and around the perivascular space as a biomarker of an as yet poorly understood neurodegenerative process. Relatively little is known about the effects that collision sport participation has on the age-related trajectories of macroscale brain structure and function, particularly in female athletes. Diffusion MRI and resting-state functional MRI were obtained from female collision sport athletes (n = 19 roller derby (RD) players; 23–45 years old) and female control participants (n = 14; 20–49 years old) to quantify structural coupling (SC) and decoupling (SD). The novel and interesting finding is that RD athletes, but not controls, exhibited increasing SC with age in two association networks: the frontoparietal network, important for cognitive control, and default-mode network, a task-negative network (permuted p = 0.0006). Age-related increases in SC were also observed in sensorimotor networks (RD, controls) and age-related increases in SD were observed in association networks (controls) (permuted p ≤ 0.0001). These distinct patterns suggest that competing in RD results in compressed neuronal timescales in critical networks as a function of age and encourages the broader study of female athlete brains across the lifespan.

Gut Microbiome, Inflammation, and Cerebrovascular Function: Link Between Obesity and Cognition

Obesity affects 13% of the adult population worldwide and this number is only expected to increase. Obesity is known to have a negative impact on cardiovascular and metabolic health, but it also impacts brain structure and function; it is associated with both gray and white matter integrity loss, as well as decreased cognitive function, including the domains of executive function, memory, inhibition, and language. Especially midlife obesity is associated with both cognitive impairment and an increased risk of developing dementia at later age. However, underlying mechanisms are not yet fully revealed. Here, we review recent literature (published between 2010 and March 2021) and discuss the effects of obesity on brain structure and cognition, with a main focus on the contributions of the gut microbiome, white adipose tissue (WAT), inflammation, and cerebrovascular function. Obesity-associated changes in gut microbiota composition may cause increased gut permeability and inflammation, therewith affecting cognitive function. Moreover, excess of WAT in obesity produces pro-inflammatory adipokines, leading to a low grade systemic peripheral inflammation, which is associated with decreased cognition. The blood-brain barrier also shows increased permeability, allowing among others, peripheral pro-inflammatory markers to access the brain, leading to neuroinflammation, especially in the hypothalamus, hippocampus and amygdala. Altogether, the interaction between the gut microbiota, WAT inflammation, and cerebrovascular integrity plays a significant role in the link between obesity and cognition. Future research should focus more on the interplay between gut microbiota, WAT, inflammation and cerebrovascular function to obtain a better understanding about the complex link between obesity and cognitive function in order to develop preventatives and personalized treatments.

Improving the Quantification of the Lateral Geniculate Nucleus in Magnetic Resonance Imaging Using a Novel 3D-Edge Enhancement Technique

The lateral geniculate nucleus (LGN) is a small, inhomogeneous structure that relays major sensory inputs from the retina to the visual cortex. LGN morphology has been intensively studied due to various retinal diseases, as well as in the context of normal brain development. However, many of the methods used for LGN structural evaluations have not adequately addressed the challenges presented by the suboptimal routine MRI imaging of this structure. Here, we propose a novel method of edge enhancement that allows for high reliability and accuracy with regard to LGN morphometry, using routine 3D-MRI imaging protocols. This new algorithm is based on modeling a small brain structure as a polyhedron with its faces, edges, and vertices fitted with one plane, the intersection of two planes, and the intersection of three planes, respectively. This algorithm dramatically increases the contrast-to-noise ratio between the LGN and its surrounding structures as well as doubling the original spatial resolution. To show the algorithm efficacy, two raters (MA and ML) measured LGN volumes bilaterally in 19 subjects using the edge-enhanced LGN extracted areas from the 3D-T1 weighted images. The averages of the left and right LGN volumes from the two raters were 175 ± 8 and 174 ± 9 mm3, respectively. The intra-class correlations between raters were 0.74 for the left and 0.81 for the right LGN volumes. The high contrast edge-enhanced LGN images presented here, from a 7-min routine 3T-MRI acquisition, is qualitatively comparable to previously reported LGN images that were acquired using a proton density sequence with 30–40 averages and 1.5-h of acquisition time. The proposed edge-enhancement algorithm is not limited only to the LGN, but can significantly improve the contrast-to-noise ratio of any small deep-seated gray matter brain structure that is prone to high-levels of noise and partial volume effects, and can also increase their morphometric accuracy and reliability. An immensely useful feature of the proposed algorithm is that it can be used retrospectively on noisy and low contrast 3D brain images previously acquired as part of any routine clinical MRI visit.