The structure of the cerebral cortex across adult life: age-related patterns of surface area, thickness, and gyrification

Cortical gray matter structure in boys with Klinefelter syndrome

Klinefelter syndrome (KS, 47,XXY) is a common sex chromosome aneuploidy in males that is associated with a wide range of cognitive, social and emotional characteristics. The neural bases of these symptoms, however, are unclear. Brain structure in 19 pre- or early-pubertal boys with KS (11.5 ± 1.8 years) and 22 typically developing (control) boys (8.1 ± 2.3 years) was examined using surface-based analyses of cortical gray matter volume, thickness and surface area. Boys in the KS group were treatment-naïve with respect to testosterone replacement therapy. Reduced volume in the insula and dorsomedial prefrontal cortex was observed in the KS relative to the TD group, as well as increased volume in the parietal, occipital and motor regions. Further inspection of surface-based metrics indicated that whereas KS-associated increases in volume were driven by differences in thickness, KS-associated reductions in volume were associated with decreases in surface area. Exploratory analyses additionally indicated several correlations between brain structure and behavior, providing initial support for a neural basis of cognitive and emotional symptoms of this condition. Taken together, these data add support for a neuroanatomical phenotype of KS and extend previous studies through clarifying the precise neuroanatomical structural characteristics of that give rise to volumetric alterations.

The MRi-Share database: brain imaging in a cross-sectional cohort of 1870 university students

We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1870 young healthy adults, aged 18-35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility-weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early ageing.

Neuroanatomical norms in the UK Biobank: The impact of allometric scaling, sex, and age

Few neuroimaging studies are sufficiently large to adequately describe population‐wide variations. This study's primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40,028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry—the nonlinear scaling relationship between a region and brain size (e.g., total brain volume)—across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |β| = .13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. Finally, we contribute to the reproducibility of research on sex differences in the brain by replicating previous studies examining cerebral sex differences. This large‐scale study advances our understanding of age, sex, and brain allometry's impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size.

Relationship between local gyrification index and age, intelligence quotient, symptom severity with Autism Spectrum Disorder: A large-scale MRI study

Gyrification is one of the most important characteristics in the cerebral cortex and the local gyrification index (LGI) was used to quantify the regional changes in gyrification. The aim of this study was to evaluate LGI alterations in autism spectrum disorder (ASD) individuals in comparison with typically developing (TD) controls and the association of the LGI with age, intelligence quotient (IQ), and symptom severity in a large multicenter dataset. Structural MRI datasets selected from Autism Brain Imaging Data Exchange I and II (ABIDE I and ABIDE II) repository (606 ASD individuals and 765 age-matched TD controls) were used to calculate LGI values. The correlation between the LGI and age, IQ, and other clinical measurements were assessed. No differences in LGI were found between ASD individuals and TD controls after FDR multiple comparison correction, however, LGI decreased with age in both ASD and TD groups. In the TD group, a significant positive correlation was found between the LGI and full IQ (FIQ) in the parahippocampal gyrus, parsopercularis of left hemisphere and entorhinal cortex, parahippocampal, superior temporal gyrus of right hemisphere, but was not observed in the ASD group. Furthermore, a positive correlation between the LGI and Autism Diagnostic Interview-Revised (ADI-R) Repetitive and Restrictive Behaviors (RRB) score was found in the left inferior parietal lobule, lateral occipital cortex, superior frontal gyrus and right superior frontal gyrus, inferior temporal gyrus. In summary, these results demonstrate that the ASD is a truly heterogeneous neurodevelopmental disorder. Future investigations are required that group ASD patients into more homogeneous subtypes.

Evidence for cognitive and brain reserve supporting executive control of memory in lifelong bilinguals

Recent bilingualism research attempts to understand whether continually controlling multiple languages provides domain-general benefits to other aspects of cognition. Yet little attention has been given to whether this extends to resistance to proactive interference (PI), which involves the filtering of irrelevant memory traces in order to focus attention on relevant to-be-remembered information. The present study sought to determine whether bilingualism provides benefits to resistance to PI performance and brain structure in regions supporting executive control of memory. Eighty-two younger and older adult participants, half English monolinguals and half highly proficient Spanish-English bilinguals, completed directed forgetting and release from PI tasks and underwent an MRI scan that measured cortical volume, thickness, and white matter integrity. While behavioral performance between bilinguals and monolinguals did not differ, bilinguals displayed thinner cortex in brain regions related to resistance to PI, providing evidence for cognitive reserve, and showed positive relationships between white matter integrity and resistance to PI performance, indicative of brain reserve. This study is the first to demonstrate cognitive reserve and brain reserve in different brain structure indices within the same healthy participants and suggests that bilingualism supports important structural relationships between regions necessary for executive control of memory.

Age-related decline in the brain: a longitudinal study on inter-individual variability of cortical thickness, area, volume, and cognition

Magnetic Resonance Imaging (MRI) studies have shown that cortical volume declines with age. Although volume is a multiplicative measure consisting of thickness and area, few studies have focused on both its components. Information on decline variability and associations between person-specific changes of different brain metrics, brain regions, and cognition is sparse. In addition, the estimates have often been biased by the measurement error, because three repeated measures are minimally required to separate the measurement error from person-specific changes. With a sample size of N = 231, five repeated measures, and an observational time span of seven years, this study explores the associations between changes of different brain metrics, brain regions, and cognitive abilities in aging. Person-specific changes were obtained by latent growth curve models using Bayesian estimation. Our data indicate that both thickness and area are important contributors to volumetric changes. In most brain regions, area clearly declined on average over the years, while thickness showed only little decline. However, there was also substantial variation around the average slope in thickness and area. The correlation pattern of changes in thickness between brain regions was strong and largely homogenous. The pattern for changes in area was similar but weaker, indicating that factors affecting area may be more region-specific. Changes in thickness and volume were substantially correlated with changes in cognition. In some brain regions, changes in area were also related to changes in cognition. Overall, studying the associations between the trajectories of brain regions in different brain metrics provides insights into the regional heterogeneity of structural changes. SIGNIFICANCE STATEMENT: Many studies have described volumetric brain changes in aging. Few studies have focused on both its individual components: area and thickness. Longitudinal studies with three or more time points are highly needed, because they provide more precise average change estimates and, more importantly, allow us to quantify the associations between changes in the different brain metrics, brain regions, and other variables (e.g. cognitive abilities). Studying these associations is important because they can provide information regarding possible underlying factors of these changes. Our study, with a large sample size, five repeated measures, and an observational time span of seven years, provides new insights about the associations between person-specific changes in thickness, area, volume, and cognitive abilities.

Associations between long-term psychosis risk, probabilistic category learning, and attenuated psychotic symptoms with cortical surface morphometry

Neuroimaging studies have consistently found structural cortical abnormalities in individuals with schizophrenia, especially in structural hubs. However, it is unclear what abnormalities predate psychosis onset and whether abnormalities are related to behavioral performance and symptoms associated with psychosis risk. Using surface-based morphometry, we examined cortical volume, gyrification, and thickness in a psychosis risk group at long-term risk for developing a psychotic disorder (n = 18; i.e., extreme positive schizotypy plus interview-rated attenuated psychotic symptoms [APS]) and control group (n = 19). Overall, the psychosis risk group exhibited cortical abnormalities in multiple structural hub regions, with abnormalities associated with poorer probabilistic category learning, a behavioral measure strongly associated with psychosis risk. For instance, the psychosis risk group had hypogyria in a right posterior midcingulate cortical hub and left superior parietal cortical hub, as well as decreased volume in a right pericalcarine hub. Morphometric measures in all of these regions were also associated with poorer probabilistic category learning. In addition to decreased right pericalcarine volume, the psychosis risk group exhibited a number of other structural abnormalities in visual network structural hub regions, consistent with previous evidence of visual perception deficits in psychosis risk. Further, severity of APS hallucinations, delusional ideation, and suspiciousness/persecutory ideas were associated with gyrification abnormalities, with all domains associated with hypogyria of the right lateral orbitofrontal cortex. Thus, current results suggest that structural abnormalities, especially in structural hubs, are present in psychosis risk and are associated both with poor learning on a psychosis risk-related task and with APS severity.

In vivo biomarkers of structural and functional brain development and aging in humans

Brain aging is a major determinant of aging. Along with the aging population, prevalence of neurodegenerative diseases is increasing, therewith placing economic and social burden on individuals and society. Individual rates of brain aging are shaped by genetics, epigenetics, and prenatal environmental. Biomarkers of biological brain aging are needed to predict individual trajectories of aging and the risk for age-associated neurological impairments for developing early preventive and interventional measures. We review current advances of in vivo biomarkers predicting individual brain age. Telomere length and epigenetic clock, two important biomarkers that are closely related to the mechanistic aging process, have only poor deterministic and predictive accuracy regarding individual brain aging due to their high intra- and interindividual variability. Phenotype-related biomarkers of global cognitive function and brain structure provide a much closer correlation to age at the individual level. During fetal and perinatal life, autonomic activity is a unique functional marker of brain development. The cognitive and structural biomarkers also boast high diagnostic specificity for determining individual risks for neurodegenerative diseases.

New insights into the dynamic development of the cerebral cortex in childhood and adolescence: Integrating macro- and microstructural MRI findings

Through dynamic transactional processes between genetic and environmental factors, childhood and adolescence involve reorganization and optimization of the cerebral cortex. The cortex and its development plays a crucial role for prototypical human cognitive abilities. At the same time, many common mental disorders appear during these critical phases of neurodevelopment. Magnetic resonance imaging (MRI) can indirectly capture several multifaceted changes of cortical macro- and microstructure, of high relevance to further our understanding of the neural foundation of cognition and mental health. Great progress has been made recently in mapping the typical development of cortical morphology. Moreover, newer less explored MRI signal intensity and specialized quantitative T2 measures have been applied to assess microstructural cortical development. We review recent findings of typical postnatal macro- and microstructural development of the cerebral cortex from early childhood to young adulthood. We cover studies of cortical volume, thickness, area, gyrification, T1-weighted (T1w) tissue contrasts such a grey/white matter contrast, T1w/T2w ratio, magnetization transfer and myelin water fraction. Finally, we integrate imaging studies with cortical gene expression findings to further our understanding of the underlying neurobiology of the developmental changes, bridging the gap between ex vivo histological- and in vivo MRI studies.

Geometric deep learning on brain shape predicts sex and age

The complex relationship between the shape and function of the human brain remains elusive despite extensive studies of cortical folding over many decades. The analysis of cortical gyrification presents an opportunity to advance our knowledge about this relationship, and better understand the etiology of a variety of pathologies involving diverse degrees of cortical folding abnormalities. Hypothesis-driven surface-based approaches have been shown to be particularly efficient in their ability to accurately describe unique features of the folded sheet topology of the cortical ribbon. However, the utility of these approaches has been blunted by their reliance on manually defined features aiming to capture the relevant geometric properties of cortical folding. In this paper, we propose an entirely novel, data-driven deep-learning based method to analyze the brain's shape that eliminates this reliance on manual feature definition. This method builds on the emerging field of geometric deep-learning and uses traditional convolutional neural network architecture uniquely adapted to the surface representation of the cortical ribbon. This method is a complete departure from prior brain MRI CNN investigations, all of which have relied on three dimensional MRI data and interpreted features of the MRI signal for prediction. MRI data from 6410 healthy subjects obtained from 11 publicly available data repositories were used for analysis. Ages ranged from 6 to 89 years. Both inner and outer cortical surfaces were extracted using Freesurfer and then registered into MNI space. For purposes of method development, both a classification and regression challenge were introduced for network learning including sex and age prediction, respectively. Two independent graph convolutional neural networks (gCNNs) were trained, the first of which to predict subject's self-identified sex, the second of which to predict subject's age. Class Activation Maps (CAM) and Regression Activation Maps (RAM) were constructed respectively to map the topographic distribution of the most influential brain regions involved in the decision process for each gCNN. Using this approach, the gCNN was able to predict a subject's sex with an average accuracy of 87.99 % and achieved a Person's coefficient of correlation of 0.93 with an average absolute error 4.58 years when predicting a subject's age. We believe this shape-based convolutional classifier offers a novel, data-driven approach to define biomedically relevant features from the brain at both the population and single subject levels and therefore lays a critical foundation for future precision medicine applications.

Quantifying Age-Associated Cortical Complexity of Left Dorsolateral Prefrontal Cortex with Multiscale Measurements

BACKGROUND

Cortical complexity plays a central role in the diagnosis and prognosis of age-related diseases. However, little is known about the regional cortical complexity in the context of brain atrophy.

OBJECTIVE

We aimed to systematically examine the age-related changes of the cortical complexity of left dorsolateral prefrontal cortex (DLPFC) and its subregions.

METHODS

Two hundred and fourteen cognitively normal adults drawn from the Open Access Series of Imaging Studies (OASIS) were divided into four age groups: young, middle-aged, young-old, and old-old. Based on structural magnetic resonance imaging (sMRI) scans, the multiscale measures of cortical complexity included cortical thickness (mm), surface area (mm2), grey matter volume (mm3), density, gyrification index (GI), and fractal dimension (FD).

RESULTS

Advancing age was associated with reduced grey matter volume, pial surface area, density, and FD of left DLPFC, but correlated with increased cortical thickness and GI. Volumetric measures, cerebrospinal fluid volume in particular, showed better performance to discriminate young-old adults from old-old adults, while FD was more sensitive than the volumetric measures to discriminate young adults and middle-aged adults.

CONCLUSION

This is the first demonstration that chronological age has a pronounced and differential effect on the cortical complexity of left DLPFC. Our findings suggest that surface-based measures of cortical region, thickness, and gyrification in particular, could be considered as valuable imaging markers for the studies of aging brain and neurodegenerative diseases.

The development of structural covariance networks during the transition from childhood to adolescence

Structural covariance conceptualizes how morphologic properties of brain regions are related to one another (across individuals). It can provide unique information to cortical structure (e.g., thickness) about the development of functionally meaningful networks. The current study investigated how structural covariance networks develop during the transition from childhood to adolescence, a period characterized by marked structural re-organization. Participants (N = 192; scans = 366) completed MRI assessments between 8.5 and 14.5 years of age. A sliding window approach was used to create “age-bins”, and structural covariance networks (based on cortical thickness) were created for each bin. Next, generalized additive models were used to characterize trajectories of age-related changes in network properties. Results revealed nonlinear trajectories with “peaks” in mean correlation and global density that are suggestive of a period of convergence in anatomical properties across the cortex during early adolescence, prior to regional specialization. “Hub” regions in sensorimotor cortices were present by late childhood, but the extent and strength of association cortices as “hubs” increased into mid-adolescence. Moreover, these regional changes were found to be related to rates of thinning across the cortex. In the context of neurocognitive networks, the frontoparietal, default mode, and attention systems exhibited age-related increases in within-network and between-network covariance. These regional and modular developmental patterns are consistent with continued refinement of socioemotional and other complex executive functions that are supported by higher-order cognitive networks during early adolescence.

Apolipoprotein E homozygous ε4 allele status: Effects on cortical structure and white matter integrity in a young to mid-age sample

Apolipoprotein E (APOE) genotype is the strongest single gene predictor of Alzheimer's disease (AD) and has been frequently associated with AD-related brain structural alterations before the onset of dementia. While previous research has primarily focused on hippocampal morphometry in relation to APOE, sporadic recent findings have questioned the specificity of the hippocampus and instead suggested more global effects on the brain. With the present study we aimed to investigate associations between homozygous APOE ε4 status and cortical gray matter structure as well as white matter microstructure. In our study, we contrasted n = 31 homozygous APOE ε4 carriers (age=34.47 years, including a subsample of n = 12 subjects with depression) with a demographically matched sample without an ε4 allele (resulting total sample: N = 62). Morphometry analyses included a) Freesurfer based cortical segmentations of thickness and surface area measures and b) tract based spatial statistics of DTI measures. We found pronounced and widespread reductions in cortical surface area of ε4 homozygotes in 57 out of 68 cortical brain regions. In contrast, no differences in cortical thickness were observed. Furthermore, APOE ε4 homozygous carriers showed significantly lower fractional anisotropy in the corpus callosum, the right internal and external capsule, the left corona radiata and the right fornix. The present findings support a global rather than regionally specific effect of homozygous APOE ε4 allele status on cortical surface area and white matter microstructure. Future studies should aim to delineate the clinical implications of these findings.

Reorganization of brain structural networks in aging: A longitudinal study

Normal aging is characterized by structural and functional changes in the brain contributing to cognitive decline. Structural connectivity (SC) describes the anatomical backbone linking distinct functional subunits of the brain and disruption of this communication is thought to be one of the potential contributors for the age-related deterioration observed in cognition. Several studies already explored brain network's reorganization during aging, but most focused on average connectivity of the whole-brain or in specific networks, such as the resting-state networks. Here, we aimed to characterize longitudinal changes of white matter (WM) structural brain networks, through the identification of sub-networks with significantly altered connectivity along time. Then, we tested associations between longitudinal changes in network connectivity and cognition. We also assessed longitudinal changes in topological properties of the networks. For this, older adults were evaluated at two timepoints, with a mean interval time of 52.8 months (SD = 7.24). WM structural networks were derived from diffusion magnetic resonance imaging, and cognitive status from neurocognitive testing. Our results show age-related changes in brain SC, characterized by both decreases and increases in connectivity weight. Interestingly, decreases occur in intra-hemispheric connections formed mainly by association fibers, while increases occur mostly in inter-hemispheric connections and involve association, commissural, and projection fibers, supporting the last-in-first-out hypothesis. Regarding topology, two hubs were lost, alongside with a decrease in connector-hub inter-modular connectivity, reflecting reduced integration. Simultaneously, there was an increase in the number of provincial hubs, suggesting increased segregation. Overall, these results confirm that aging triggers a reorganization of the brain structural network.

Mapping the "Funny Bone": Neuroanatomical Correlates of Humor Creativity in Professional Comedians

What are the neuroanatomical correlates of expertise in a specific creative domain? Professional comedians, amateurs and controls underwent a T1 MRI anatomical scan. Measures of cortical surface area (gyrification and sulcal depth) and thickness were extracted for each participant. Compared to controls, professional comedians had a greater cortical surface area in the left inferior temporal gyrus, angular gyrus, precuneus and right medial prefrontal cortex. These regions have been previously implicated in abstract, divergent thinking and the default-mode network. The high degree of overlap between the regions of greater surface area in professional comedians with the regions showing greater activation in the same group during comedy improvisation in our previous work (particularly the temporal regions and angular gyrus) suggests that these regions may be specifically involved in humor creativity.

Neocortical Anatomy in the South American Plains Vizcacha, Lagostomus maximus, Reveals Different Strategies in Encephalic Development among Hystricomorpha and Myomorpha Rodents

Depending on the presence or absence of sulci and convolutions, the brains of mammals are classified as gyrencephalic or lissencephalic. We analyzed the encephalic anatomy of the hystricomorph rodent Lagostomus maximus in comparison with other evolutionarily related species. The encephalization quotient (EQ), gyrencephaly index (GI), and minimum cortical thickness (MCT) were calculated for the plains vizcacha as well as for other myomorph and hystricomorph rodents. The vizcacha showed a gyrencephalic brain with a sagittal longitudinal fissure that divides both hemispheres, and 3 pairs of sulci with bilateral symmetry; that is, lateral-rostral, intraparietal, and transverse sulci. The EQ had one of the lowest values among Hystricomorpha, while GI was one of the highest. Besides, the MCT was close to the mean value for the suborder. The comparison of EQ, GI, and MCT values between hystricomorph and myomorph species allowed the detection of significant variations. Both EQ and GI showed a significant increase in Hystricomorpha compared to Myomorpha, whereas a Pearson's analysis between EQ and GI depicted an inverse correlation pattern for Hystricomorpha. Furthermore, the ratio between MCT and GI also showed a negative correlation for Hystricomorpha and Myomorpha. Our phylogenetic analyses showed that Hystricomorpha and Myomorpha do not differ in their allometric patterning between the brain and body mass, GI and brain mass, and MCT and GI. In conclusion, gyrencephalic neuroanatomy in the vizcacha could have developed from the balance between the brain size, the presence of invaginations, and the cortical thickness, which resulted in a mixed encephalization strategy for the species. Gyrencephaly in the vizcacha, as well as in other Hystricomorpha, advocates in favor of the proposal that in the more recently evolved Myomorpha lissencephaly would have arisen from a phenotype reversal process.

Anterior Cingulate Structure and Perfusion is Associated with Cerebrospinal Fluid Tau among Cognitively Normal Older Adult APOEɛ4 Carriers

Evidence suggests the ɛ4 allele of the apolipoprotein E (APOE) gene may accelerate an age-related process of cortical thickening and cerebral blood flow (CBF) reduction in the anterior cingulate cortex (ACC). Although the neural basis of this association remains unclear, evidence suggests it might reflect early neurodegenerative processes. However, to date, associations between cerebrospinal fluid (CSF) biomarkers of neurodegeneration, such as CSF tau, and APOE-related alterations in ACC cortical thickness (CTH) and CBF have yet to be explored. The current study explored the interaction of CSF tau and APOE genotype (ɛ4+, ɛ4-) on FreeSurfer-derived CTH and arterial spin labeling MRI-measured resting CBF in the ACC (caudal ACC [cACC] and rostral ACC [rACC]) among a sample of 45 cognitively normal older adults. Secondary analyses also examined associations between APOE, CTH/CBF, and cognitive performance. In the cACC, higher CSF tau was associated with higher CTH and lower CBF in ɛ4+, whereas these relationships were not evident in ɛ4-. In the rACC, higher CSF tau was associated with higher CTH for both ɛ4+ and ɛ4-, and with lower CBF only in ɛ4+. Significant interactions of CSF tau and APOE on CTH/CBF were not observed in two posterior reference regions implicated in Alzheimer's disease. Secondary analyses revealed a negative relationship between cACC CTH and executive functioning in ɛ4+ and a positive relationship in ɛ4-. Findings suggest the presence of an ɛ4-related pattern of increased CTH and reduced CBF in the ACC that is associated with biomarkers of neurodegeneration and subtle decrements in cognition.

Generalizing Longitudinal Age Effects on Brain Structure - A Two-Study Comparison Approach

Cross-sectional studies indicate that normal aging is accompanied by decreases in brain structure. Longitudinal studies, however, are relatively rare and inconsistent regarding their outcomes. Particularly the heterogeneity of methods, sample characteristics and the high inter-individual variability in older adults prevent the deduction of general trends. Therefore, the current study aimed to compare longitudinal age-related changes in brain structure (measured through cortical thickness) in two large independent samples of healthy older adults (n = 161 each); the Longitudinal Healthy Aging Brain (LHAB) database project at the University of Zurich, Switzerland, and 1000BRAINS at the Research Center Juelich, Germany. Annual percentage changes in the two samples revealed stable to slight decreases in cortical thickness over time. After correction for major covariates, i.e., baseline age, sex, education, and image quality, sample differences were only marginally present. Results suggest that general trends across time might be generalizable over independent samples, assuming the same methodology is used, and similar sample characteristics are present.

Brain Structure and Subclinical Symptoms: A Dimensional Perspective of Psychopathology in the Depression and Anxiety Spectrum

Human psychopathology is the result of complex and subtle neurobiological alterations. Categorial DSM or ICD diagnoses do not allow a biologically founded and differentiated description of these diverse processes across a spectrum or continuum, emphasising the need for a scientific and clinical paradigm shift towards a dimensional psychiatric nosology. The subclinical part of the spectrum is, however, of special interest for early detection of mental disorders. We review the current evidence of brain structural correlates (grey matter volume, cortical thickness, and gyrification) in non-clinical (psychiatrically healthy) subjects with minor depressive and anxiety symptoms. We identified 16 studies in the depressive spectrum and 20 studies in the anxiety spectrum. These studies show effects associated with subclinical symptoms in the hippocampus, anterior cingulate cortex, and anterior insula similar to major depression and changes in amygdala similar to anxiety disorders. Precuneus and temporal areas as parts of the default mode network were affected specifically in the subclinical studies. We derive several methodical considerations crucial to investigations of brain structural correlates of minor psycho(patho)logical symptoms in healthy participants. And we discuss neurobiological overlaps with findings in patients as well as distinct findings, e.g. in areas involved in the default mode network. These results might lead to more insight into the early pathogenesis of clinical significant depression or anxiety and need to be enhanced by multi-centre and longitudinal studies.

Morphometric Analysis of Brain in Newborn with Congenital Diaphragmatic Hernia

Congenital diaphragmatic hernia (CDH) is a severe pediatric disorder with herniation of abdominal viscera into the thoracic cavity. Since neurodevelopmental impairment constitutes a common outcome, we performed morphometric magnetic resonance imaging (MRI) analysis on CDH infants to investigate cortical parameters such as cortical thickness (CT) and local gyrification index (LGI). By assessing CT and LGI distributions and their correlations with variables which might have an impact on oxygen delivery (total lung volume, TLV), we aimed to detect how altered perfusion affects cortical development in CDH. A group of CDH patients received both prenatal (i.e., fetal stage) and postnatal MRI. From postnatal high-resolution T2-weighted images, mean CT and LGI distributions of 16 CDH were computed and statistically compared to those of 13 controls. Moreover, TLV measures obtained from fetal MRI were further correlated to LGI. Compared to controls, CDH infants exhibited areas of hypogiria within bilateral fronto-temporo-parietal labels, while no differences were found for CT. LGI significantly correlated with TLV within bilateral temporal lobes and left frontal lobe, involving language- and auditory-related brain areas. Although the causes of neurodevelopmental impairment in CDH are still unclear, our results may suggest their link with altered cortical maturation and possible impaired oxygen perfusion.

Gray Matter Volume in Elderly adults With ADHD: Associations of Symptoms and Comorbidities With Brain Structures

Objective: To investigate total and selected region-of-interest-based gray matter volume (GMV) in older adults with ADHD. Method: Twenty-five elderly (≥65 years old) patients with ADHD and 34 healthy controls underwent 1.5-T magnetic resonance imaging (MRI). We used voxel-based morphometry to compare GMV between groups and performed a correlation analysis with ADHD symptoms and comorbidities. Results: Findings revealed a smaller total GMV in males with ADHD and a smaller GMV in the right medial frontal orbital area extending toward the medial frontal superior, the frontal superior, and the subgenual anterior cingulate cortex (ACC) besides correlations between inattentiveness and ACC (bilaterally) and left cerebellum, hyperactivity/impulsivity and the left frontal inferior orbital, depression and caudate (bilaterally), and the right inferior parietal lobule. Conclusion: Neural correlates in regions related to attention, executive control, and affective processing suggest that impairments in frontostriatal and frontoparietal-cerebellar areas observed in adults with ADHD persist into old age.

Cortical Gyrification Morphology in Individuals with ASD and ADHD across the Lifespan: A Systematic Review and Meta-Analysis

Autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are common neurodevelopmental disorders (NDDs) that may impact brain maturation. A number of studies have examined cortical gyrification morphology in both NDDs. Here we review and when possible pool their results to better understand the shared and potentially disorder-specific gyrification features. We searched MEDLINE, PsycINFO, and EMBASE databases, and 24 and 10 studies met the criteria to be included in the systematic review and meta-analysis portions, respectively. Meta-analysis of local Gyrification Index (lGI) findings across ASD studies was conducted with SDM software adapted for surface-based morphometry studies. Meta-regressions were used to explore effects of age, sex, and sample size on gyrification differences. There were no significant differences in gyrification across groups. Qualitative synthesis of remaining ASD studies highlighted heterogeneity in findings. Large-scale ADHD studies reported no differences in gyrification between cases and controls suggesting that, similar to ASD, there is currently no evidence of differences in gyrification morphology compared with controls. Larger, longitudinal studies are needed to further clarify the effects of age, sex, and IQ on cortical gyrification in these NDDs.

Surface-based single-subject morphological brain networks: Effects of morphological index, brain parcellation and similarity measure, sample size-varying stability and test-retest reliability

Morphological brain networks, in particular those at the individual level, have become an important approach for studying the human brain connectome; however, relevant methodology is far from being well-established in their formation, description and reproducibility. Here, we extended our previous study by constructing and characterizing single-subject morphological similarity networks from brain volume to surface space and systematically evaluated their reproducibility with respect to effects of different choices of morphological index, brain parcellation atlas and similarity measure, sample size-varying stability and test-retest reliability. Using the Human Connectome Project dataset, we found that surface-based single-subject morphological similarity networks shared common small-world organization, high parallel efficiency, modular architecture and bilaterally distributed hubs regardless of different analytical strategies. Nevertheless, quantitative values of all interregional similarities, global network measures and nodal centralities were significantly affected by choices of morphological index, brain parcellation atlas and similarity measure. Moreover, the morphological similarity networks varied along with the number of participants and approached stability until the sample size exceeded ~70. Using an independent test-retest dataset, we found fair to good, even excellent, reliability for most interregional similarities and network measures, which were also modulated by different analytical strategies, in particular choices of morphological index. Specifically, fractal dimension and sulcal depth outperformed gyrification index and cortical thickness, higher-resolution atlases outperformed lower-resolution atlases, and Jensen-Shannon divergence-based similarity outperformed Kullback-Leibler divergence-based similarity. Altogether, our findings propose surface-based single-subject morphological similarity networks as a reliable method to characterize the human brain connectome and provide methodological recommendations and guidance for future research.

Anti-seizure medication correlated changes of cortical morphology in childhood epilepsy with centrotemporal spikes

To investigate the morphological changes of cerebral cortex correlating with anti-seizure medication in Childhood Epilepsy with Centrotemporal Spikes (CECTS), and their relationships with seizure control. This study included a total of 188 children, including 62 patients with CECTS taking anti-seizure drugs, 56 patients with drug-naive, and 70 healthy controls. A portion of cases were also followed-up for longitudinal analysis. Cortical morphological parameters were quantitatively measured by applying surface-based morphometry analysis to high-resolution three-dimension T1 weighted images. Among the three groups, the morphological indices were compared to quantify any cortical changes affected by seizures and medication. The relationships among anti-seizure medication, seizure controls and cortical morphometry were investigated using causal mediator analysis. The Rolandic cortex of the drug-naive patients showed abnormal cortical thickness by comparing with that of healthy controls, and thinning by comparing with that of patients with medication. The cortical thickness in the Rolandic regions was negatively correlated with duration of medication and duration of seizure-free. Longitudinal analysis further demonstrated that the thickness of Rolandic cortex thinned in post-medication state relative to the pre-medication state. Mediation analysis revealed that morphological alteration of the Rolandic cortex might act as a mediator in the path of anti-seizure medication on seizure control. Our findings highlighted that anti-seizure medication was associated with regression of abnormal increment of cortical thickness in the Rolandic regions in CECTS. The neuroanatomical alteration might be a mediating factor in the process of seizure control by anti-seizure medication.

Baseline Cortical Thickness Reductions in Clinical High Risk for Psychosis: Brain Regions Associated with Conversion to Psychosis Versus Non-Conversion as Assessed at One-Year Follow-Up in the Shanghai-At-Risk-for-Psychosis (SHARP) Study

OBJECTIVE

To assess cortical thickness (CT) and surface area (SA) of frontal, temporal, and parietal brain regions in a large clinical high risk for psychosis (CHR) sample, and to identify cortical brain abnormalities in CHR who convert to psychosis and in the whole CHR sample, compared with the healthy controls (HC).

METHODS

Magnetic resonance imaging, clinical, and cognitive data were acquired at baseline in 92 HC, 130 non-converters, and 22 converters (conversion assessed at 1-year follow-up). CT and SA at baseline were calculated for frontal, temporal, and parietal subregions. Correlations between regions showing group differences and clinical scores and age were also obtained.

RESULTS

CT but not SA was significantly reduced in CHR compared with HC. Two patterns of findings emerged: (1) In converters, CT was significantly reduced relative to non-converters and controls in the banks of superior temporal sulcus, Heschl's gyrus, and pars triangularis and (2) CT in the inferior parietal and supramarginal gyrus, and at trend level in the pars opercularis, fusiform, and middle temporal gyri was significantly reduced in all high-risk individuals compared with HC. Additionally, reduced CT correlated significantly with older age in HC and in non-converters but not in converters.

CONCLUSIONS

These results show for the first time that fronto-temporo-parietal abnormalities characterized all CHR, that is, both converters and non-converters, relative to HC, while CT abnormalities in converters relative to CHR-NC and HC were found in core auditory and language processing regions.

Physical aspects of cortical folding

The characteristically folded surface of the human brain is critical for brain function and allows for higher cognitive abilities. Recent mostly computational research advances have shown that mechanical instabilities play a crucial role during early brain development and cortical folding. However, it is difficult to investigate such mechanisms in vivo. To experimentally gain deeper insights into the physical mechanisms that underlie the development of brain shape, we use a setup of swelling polymers. We investigate the influence of cortical thickness and the stiffness ratio between cortex and subcortex on the resulting surface pattern by taking the initially smooth fetal brain geometry at week 22 into consideration. The gel specimens possess a two-layered structure accounting for gray and white matter tissue and yield complex surface morphologies that well resemble patterns in the human brain. The results are in good agreement with analytical predictions. Through the variation of cortical thickness and stiffness, it is possible to reproduce cortical malformations such as polymicrogyria and lissencephaly. The results suggest that wrinkling with subsequent transition into folding is the driving instability mechanism during brain development. In addition, the experiments provide valuable insights towards the distinction between wrinkling and creasing instabilities. Taken together, the presented swelling experiments impressively demonstrate the purely physical aspects of brain shape and constitute a valuable tool to advance our understanding of human brain development.

Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques

Brain age prediction studies aim at reliably estimating the difference between the chronological age of an individual and their predicted age based on neuroimaging data, which has been proposed as an informative measure of disease and cognitive decline. As most previous studies relied exclusively on magnetic resonance imaging (MRI) data, we hereby investigate whether combining structural MRI with functional magnetoencephalography (MEG) information improves age prediction using a large cohort of healthy subjects (N = 613, age 18-88 years) from the Cam-CAN repository. To this end, we examined the performance of dimensionality reduction and multivariate associative techniques, namely Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA), to tackle the high dimensionality of neuroimaging data. Using MEG features (mean absolute error (MAE) of 9.60 years) yielded worse performance when compared to using MRI features (MAE of 5.33 years), but a stacking model combining both feature sets improved age prediction performance (MAE of 4.88 years). Furthermore, we found that PCA resulted in inferior performance, whereas CCA in conjunction with Gaussian process regression models yielded the best prediction performance. Notably, CCA allowed us to visualize the features that significantly contributed to brain age prediction. We found that MRI features from subcortical structures were more reliable age predictors than cortical features, and that spectral MEG measures were more reliable than connectivity metrics. Our results provide an insight into the underlying processes that are reflective of brain aging, yielding promise for the identification of reliable biomarkers of neurodegenerative diseases that emerge later during the lifespan.

Degeneration of gray and white matter differs between hypometabolic and hypermetabolic brain regions in a patient with ALS-FTD: a longitudinal MRI - PET multimodal study

OBJECTIVE

[18F]-fluoro-2-deoxy-d-glucose positron emission tomography (18F-FDG PET) imaging and magnetic resonance imaging (MRI) of brain in ALS patients with frontotemporal lobe dementia (ALS-FTD) reveal hypometabolism and hypermetabolism, as well as gray matter (GM) and white matter (WM) abnormalities in different brain regions, respectively. Hypometabolism arising from neuronal dysfunction or loss is the most recognized pathophysiologic change in neurodegeneration, whereas mechanisms underlying hypermetabolism remain unclear. We hypothesize that hypometabolic and hypermetabolic brain regions in ALS-FTD represent differential degeneration of GM and WM structures, as revealed by co-registered MRI in a two time-point longitudinal multimodal study. Methods: A 69-year-old female with ALS-FTD underwent 18F-FDG PET, diffusion tensor imaging (DTI), and T1-weighted MRI at baseline (15 months after symptom onset), and 20.4 months later. Cerebral glucose metabolism rate, cortical thickness, cortical area, and WM network changes were measured longitudinally. Results and conclusion: The patient had symptoms and signs of bulbar-onset upper motor neuron (UMN)-predominant ALS with language and behavioral dysfunction. Evaluation at baseline showed bulbar dysfunction, and impaired language and executive function. At follow-up, worsened bulbar and other motor functions, and prominent FTD both reflected significant progression. Cortical thickness and surface area showed differential involvement in the hypometabolic and hypermetabolic regions. WM connections from frontal regions to other brain regions were completely absent by graph theory-based network analysis when compared to temporal regions indicating prominent frontal lobe degeneration. Structural neuroimaging reveals different patterns of GM and WM involvement in the hypometabolic and hypermetabolic brain regions in a patient with ALS-FTD.

Cortical gyrification morphology in PTSD: A neurobiological risk factor for severity?

Post-traumatic stress disorder (PTSD) is a prevalent psychiatric disorder, particularly among military personnel and veterans. Cortical gyrification, as a specific metric derived from structural MRI, is an index of the convoluted folding and patterning of the gyri and sulci, and is thought to facilitate the efficiency of local neuronal wiring. It has the potential to act as a neurobiological risk factor for emergent psychiatric disorders – to date, it has been understudied in PTSD. Here, using a local measure of the degree of gyrification (local Gyrification Index, lGI) we investigate cortical gyrification morphology in 48 adult male soldiers with (n = 23) and without (n = 25) a PTSD diagnosis. We also examine the relation between lGI and PTSD severity within the PTSD group. General linear models yielded significant between-group differences with greater lGI found in PTSD in a cluster located in the medial occipito-parietal lobe on the left hemisphere and reduced lGI in a cluster located on the lateral surface of the parietal lobe on the right hemisphere. Brain-behaviour analyses within the PTSD group yielded significant positive associations between lGI and PTSD severity in a cluster located in the frontal cortex of the left hemisphere and scattered clusters located within all lobes of the right hemisphere. After accounting for the effects of comorbid psychiatric symptoms common in PTSD, the associations in the right hemisphere reduced to clusters only located in the frontal lobe, while the cluster in the left hemisphere remained significant. Our results suggest that atypical cortical gyrification in parietal and occipital regions may be implicated in the psychopathology of PTSD diagnosis, and properties of prefrontal gyrification associated with the emergent severity of PTSD after trauma. The importance of these regions in PTSD may be attributed to a pre-existing neurobiological risk factor, or neuromorphological changes after trauma precipitating emergent psychiatric illness. Our brain-behaviour relations provide support for the existing literature by highlighting the importance of the frontal lobe in the pathogenesis of PTSD. Future large-scale longitudinal studies including female participants may infer causal implications of atypical gyrification in PTSD and shed light on the potential effect of sex on this brain metric.

Multiparametric and multilevel characterization of morphological alterations in patients with transient ischemic attack

Transient ischemic attack (TIA), an important risk factor for stroke, is associated with widespread disruptions of functional brain architecture. However, TIA-related structural alterations are not well established. By analyzing structural MRI data from 50 TIA patients versus 40 healthy controls (HCs), here we systematically investigated TIA-related morphological alterations in multiple cortical surface-based indices (cortical thickness [CT], fractal dimension [FD], gyrification index [GI], and sulcal depth [SD]) at multiple levels (local topography, interregional connectivity and whole-brain network topology). For the observed alterations, their associations with clinical risk factors and abilities as diagnostic and prognostic biomarkers were further examined. We found that compared with the HCs, the TIA patients showed widespread morphological alterations and the alterations depended on choices of morphological index and analytical level. Specifically, the patients exhibited: (a) regional CT decreases in the transverse temporal gyrus and lateral sulcus; (b) impaired FD- and GI-based connectivity mainly involving visual, somatomotor and ventral attention networks and interhemispheric connections; and (c) altered GI-based whole-brain network efficiency and decreased FD-based nodal centrality in the middle frontal gyrus. Moreover, the impaired morphological connectivity showed high sensitivities and specificities for distinguishing the patients from HCs. Altogether, these findings demonstrate the emergence of morphological index-dependent and analytical level-specific alterations in TIA, which provide novel insights into neurobiological mechanisms underlying TIA and may serve as potential biomarkers to help diagnosis of the disease. Meanwhile, our findings highlight the necessity of using multiparametric and multilevel approaches for a complete mapping of cerebral morphology in health and disease.

Midlife aerobic exercise and brain structural integrity: Associations with age and cardiorespiratory fitness

Lower midlife physical activity is associated with higher risk of neurodegenerative disease in late life. However, it remains unknown whether physical exercise and fitness are associated with brain structural integrity during midlife. The purpose of this study was to compare brain structures between middle-aged aerobically trained adults (MA), middle-aged sedentary (MS), and young sedentary (YS) adults. Thirty MA (54±4 years), 30 MS (54±4 years), and 30 YS (32±6 years) participants (50% women) underwent measurements of brain volume, cortical thickness, and white matter (WM) fiber integrity using MRI. MA participants had aerobic training for 24.8±9.6 years and the highest cardiorespiratory fitness level (i.e., peak oxygen uptake: VO2peak) among all groups. Global WM integrity, as assessed with fractional anisotropy (FA) from diffusion tensor imaging, was lower in the MS compared with the YS group. However, global FA in the MA group was significantly higher than that in the MS group (P<0.05) and at a similar level to the YS group. Furthermore, tract-based spatial statistical analysis demonstrated that FA in the anterior, superior, and limbic WM tracts (e.g., the genu of the corpus callosum, superior longitudinal fasciculus, uncinate fasciculus) was higher in the MA compared with MS groups, and positively associated with VO2peak, independently from age and sex. From cortical thickness analysis, MS and MA participants showed thinner prefrontal and parieto-temporal areas than the YS group. On the other hand, the MA group exhibited thicker precentral, postcentral, pericalcarine, and lateral occipital cortices than the MS and YS groups. But, the insula and right superior frontal gyrus showed thinner cortical thickness in the MA compared with the MS groups. Collectively, these findings suggest that midlife aerobic exercise is associated with higher WM integrity and greater primary motor and somatosensory cortical thickness.

Dynamic changes of region-specific cortical features and scalp-to-cortex distance: implications for transcranial current stimulation modeling

BACKGROUND

Transcranial current stimulation in rehabilitation is a fast-growing field featured with computational and biophysical modeling. Cortical features and scalp-to-cortex distance (SCD) are key variables for determining the strength and distribution of the electric field, yet longitudinal studies able to capture these dynamic changes are missing. We sought to investigate and quantify the ageing effect on the morphometry and SCD of left primary motor cortex (M1) and dorsolateral prefrontal cortex (DLPFC) in normal ageing adults and mild cognitive impairment (MCI) converters.

METHODS

Baseline, 1-year and 3-year follow-up structural magnetic resonance imaging scans from normal ageing adults (n = 32), and MCI converters (n = 22) were drawn from the Open Access Series of Imaging Studies. We quantified the changes of the cortical features and SCDs of left M1 and DLPFC, including grey matter volume, white matter volume, cortical thickness, and folding. Head model was developed to simulate the impact of SCD on the electric field induced by transcranial current stimulation.

RESULTS

Pronounced ageing effect was found on the SCD of left DLPFC in MCI converters. The SCD change of left DLPFC from baseline to 3-year follow-up demonstrated better performance to discriminate MCI converters from normal ageing adults than the other morphometric measures. The strength of electric field was consequently decreased with SCD in MCI converters.

CONCLUSION

Ageing has a prominent, but differential effect on the region-specific SCD and cortical features in older adults with cognitive impairments. Our findings suggest that SCD, cortical thickness, and folding of the targeted regions could be used as valuable imaging markers when conducting transcranial brain stimulation in individuals with brain atrophy.

Beyond volumetry: Considering age-related changes in brain shape complexity using fractal dimensionality

Gray matter volume for cortical, subcortical, and ventricles all vary with age. However, these volumetric changes do not happen on their own, there are also age-related changes in cortical folding and other measures of brain shape. Fractal dimensionality has emerged as a more sensitive measure of brain structure, capturing both volumetric and shape-related differences. For subcortical structures it is readily apparent that segmented structures do not differ in volume in isolation-adjacent regions must also vary in shape. Fractal dimensionality here also appears to be more sensitive to these age-related differences than volume. Given these differences in structure are quite prominent in structure, caution should be used when examining comparisons across age in brain function measures, as standard normalisation methods are not robust enough to adjust for these inter-individual differences in cortical structure.

Problems experienced by children from families with histories of substance misuse: An ABCD study®

BACKGROUND

There are significant knowledge gaps of the vulnerabilities faced by youth from families with histories of alcohol or substance misuse. This study aimed to provide a comprehensive assessment of problems experienced by substance-naive children with positive family histories of substance misuse (FHP).

METHODS

Baseline data from up to 11,873 children (52.1 % male), aged 9.0-10.9 years (M = 9.9 ± 0.6), enrolled in the US-based Adolescent Brain Cognitive Development Study® were utilized. Mixed models tested cross-sectional associations between family history of substance misuse, assessed categorically and continuously, with neurobiological, cognitive, behavioral, and psychological outcomes, when controlling for confounding factors, including family history of psychopathology, and correcting for multiple comparisons.

RESULTS

One in four (26.3 %) youth were categorized as FHP (defined as ≥ one parent or ≥ two grandparents with misuse history). Controlling for confounding, FHP youth exhibited thinner whole cortices and greater surface area in frontal and occipital regions than youth with no such history (|ds|≥0.04, ps<.001). FHP youth experienced greater psychopathology and sleep disturbance (|ds|≥0.36, ps<.001) and were more likely to be diagnosed with multiple mental disorders (odds ratios≥1.22, ps<.001), with severity of effects dependent on family history density of substance misuse. Differences in cognition, impulsivity, and motivation were non-significant. Psychopathology, mental disorders, and sleep disturbance were negatively correlated with various neural indices (|rs|=0.01-0.05, ps<.05).

CONCLUSIONS

At age 9-10 years, FHP youth can experience numerous problems, with psychopathology and mental disorders being some of the most significant. Therefore, prevention efforts should target psychopathology vulnerabilities in FHP children.

Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders : Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group

Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = -0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.

Differences in cortical structure between cognitively normal East Asian and Caucasian older adults: a surface-based morphometry study

There is a growing literature on the impact of ethnicity on brain structure and function. Despite the regional heterogeneity in age-related changes and non-uniformity across brain morphometry measurements in the aging process, paucity of studies investigated the difference in cortical anatomy between the East Asian and Caucasian older adults. The present study aimed to compare cortical anatomy measurements, including cortical thickness, volume and surface area, between cognitively normal East Asian (n = 171) and Caucasian (n = 178) older adults, using surface-based morphometry and vertex-wise group analysis of high-dimensional structural magnetic resonance imaging (MRI) data. The East Asian group showed greater cortical thickness and larger cortical volume in the right superior temporal gyrus, postcentral gyrus, bilateral inferior temporal gyrus, and inferior parietal cortex. The Caucasian group showed thicker and larger cortex in the left transverse temporal cortex, lingual gyrus, right lateral occipital cortex, and precentral gyrus. Additionally, the difference in surface area was discordant with that in cortical thickness. Differences in brain structure between the East Asian and Caucasian might reflect differences in language and information processing, but further studies using standardized methods for assessing racial characteristics are needed. The research results represent a further step towards developing a comprehensive understanding of differences in brain structure between ethnicities of older adults, and this would enrich clinical research on aging and neurodegenerative diseases.

Age-related decrements in cortical gyrification: Evidence from an accelerated longitudinal dataset

Cortical gyrification has been found to decrease due to aging, but thus far this has only been examined in cross-sectional samples. Interestingly, the topography of these age-related differences in gyrification follows a distinct gradient along the cortex relative to age effects on cortical thickness, likely suggesting a different underlying neurobiological mechanism. Here I examined several aspects of gyrification in an accelerated longitudinal dataset of 280 healthy adults aged 45-92 with an interval between first and last MRI sessions of up to 10 years (total of 815 MRI sessions). Results suggest that age changes in sulcal morphology underlie these changes in gyrification.

Prospective Study Examining the Effects of Extreme Drinking on Brain Structure in Emerging Adults

BACKGROUND

Emerging adulthood is a critical neurodevelopment period in which extreme drinking has a potentially pronounced neurotoxic effect. Therefore, extreme drinking, even a single episode, could be particularly harmful to the developing brain's structure. Relatedly, heavy alcohol use in emerging adults has been associated with structural brain damage, especially in the corpus callosum. However, it is unclear whether and how much a single extreme drinking episode would affect brain morphometry.

METHODS

For the first time in the literature, the current study prospectively examined the impact of an extreme drinking episode (i.e., twenty-first birthday celebration) on the brain morphometry of emerging adults immediately following their birthday celebration (n = 50) and approximately 5 weeks post-birthday celebration (n = 29).

RESULTS

We found evidence that a single extreme drinking episode was associated with structural changes immediately post-birthday celebration. Specifically, higher twenty-first birthday estimated blood-alcohol concentration was associated with decreased volume of the posterior and central corpus callosum immediately post-birthday celebration. This extreme drinking episode was not associated with further structural changes, or recovery, 5 weeks post-twenty-first birthday celebration.

CONCLUSIONS

Overall, results suggest that a single episode of heavy drinking in emerging adulthood may be associated with immediate structural changes of the corpus callosum. Thus, emerging adulthood, which is characterized by high rates of extreme drinking, could be a critical period for targeted prevention and intervention.

Is cardiovascular fitness associated with structural brain integrity in midlife? Evidence from a population-representative birth cohort study

Improving cardiovascular fitness may buffer against age-related cognitive decline and mitigate dementia risk by staving off brain atrophy. However, it is unclear if such effects reflect factors operating in childhood (neuroselection) or adulthood (neuroprotection). Using data from 807 members of the Dunedin Study, a population-representative birth cohort, we investigated associations between cardiovascular fitness and structural brain integrity at age 45, and the extent to which associations reflected possible neuroselection or neuroprotection by controlling for childhood IQ. Higher fitness, as indexed by VO2Max, was not associated with average cortical thickness, total surface area, or subcortical gray matter volume including the hippocampus. However, higher fitness was associated with thicker cortex in prefrontal and temporal regions as well as greater cerebellar gray matter volume. Higher fitness was also associated with decreased hippocampal fissure volume. These associations were unaffected by the inclusion of childhood IQ in analyses. In contrast, a higher rate of decline in cardiovascular fitness from 26 to 45 years was not robustly associated with structural brain integrity. Our findings are consistent with a neuroprotective account of adult cardiovascular fitness but suggest that effects are not uniformly observed across the brain and reflect contemporaneous fitness more so than decline over time.

Toward a more reliable characterization of fractal properties of the cerebral cortex of healthy subjects during the lifespan

The cerebral cortex manifests an inherent structural complexity of folding. The fractal geometry describes the complexity of structures which show self-similarity in a proper interval of spatial scales. In this study, we aimed at evaluating in-vivo the effect of different criteria for selecting the interval of spatial scales in the estimation of the fractal dimension (FD) of the cerebral cortex in T₁-weighted magnetic resonance imaging (MRI). We compared four different strategies, including two a priori selections of the interval of spatial scales, an automated selection of the spatial scales within which the cerebral cortex manifests the highest statistical self-similarity, and an improved approach, based on the search of the interval of spatial scales which presents the highest rounded R²_adj coefficient and, in case of equal rounded R²_adj coefficient, preferring the widest interval in the log–log plot. We employed two public and international datasets of in-vivo MRI scans for a total of 159 healthy subjects (age range 6–85 years). The improved approach showed strong associations of FD with age and yielded the most accurate machine learning models for individual age prediction in both datasets. Our results indicate that the selection of the interval of spatial scales of the cerebral cortex is thus critical in the estimation of FD.

Temporally and sex-specific effects of maternal perinatal stress on offspring cortical gyrification and mood in young adulthood

Maternal stress during pregnancy and shortly thereafter is associated with altered offspring brain development that may increase risk of mood and anxiety disorders. Cortical gyrification is established during the prenatal period and the first 2 years of life and is altered in psychiatric disorders. Here, we sought to characterize the effects of perinatal stress exposure on offspring gyrification patterns and mood dysregulation in young adulthood. Participants included 85 young adults (56.5% women; 23–24 years) from the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) with perinatal stress data across four distinct timepoints and structural MRI data from young adulthood. Perinatal stress exposure was measured as maternal stress during first and second half of pregnancy, first 6 months, and 6–18 months after birth. Cortical gyrification and mood dysregulation were quantified using local gyrification index (LGI), computed with Freesurfer, and the Profile of Mood States questionnaire, respectively. Perinatal stress predicted cortical gyrification in young adulthood, and its timing influenced location, direction, and sex‐specificity of effects. In particular, whereas early prenatal stress was associated with sex‐dependent medium‐to‐large effects in large temporal, parietal, and occipital regions (f² = 0.19–0.38, p < .001), later perinatal stress was associated with sex‐independent small‐to‐medium effects in smaller, more anterior regions (f² = 0.10–0.19, p < .003). Moreover, in females, early prenatal stress predicted higher LGI in a large temporal region, which was further associated with mood disturbance in adulthood (r = 0.399, p = .006). These findings point out the long‐term implications of perinatal stress exposure for cortical morphology and mood dysregulation.

Cortical gyrification and its relationships with molecular measures and cognition in children with the FMR1 premutation

Neurobiological basis for cognitive development and psychiatric conditions remains unexplored in children with the FMR1 premutation (PM). Knock-in mouse models of PM revealed defects in embryonic cortical development that may affect cortical folding. Cortical-folding complexity quantified using local gyrification index (LGI) was examined in 61 children (age 8–12 years, 19/14 male/female PM carriers, 15/13 male/female controls). Whole-brain vertex-wise analysis of LGI was performed for group comparisons and correlations with IQ. Individuals with aberrant gyrification in 68 cortical areas were identified using Z-scores of LGI (hyper: Z ≥ 2.58, hypo: Z ≤ − 2.58). Significant group-by-sex-by-age interaction in LGI was detected in right inferior temporal and fusiform cortices, which correlated negatively with CGG repeat length in the PM carriers. Sixteen PM boys (hyper/hypo: 7/9) and 10 PM girls (hyper/hypo: 2/5, 3 both) displayed aberrant LGI in 1–17 regions/person while 2 control boys (hyper/hypo: 0/2) and 2 control girls (hyper/hypo: 1/1) met the same criteria in only 1 region/person. LGI in the precuneus and cingulate cortices correlated positively with IQ scores in PM and control boys while negatively in PM girls and no significant correlation in control girls. These findings reveal aberrant gyrification, which may underlie cognitive performance in children with the PM.

Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

A Longitudinal Study of Local Gyrification Index in Young Boys With Autism Spectrum Disorder

Local gyrification index (LGI), a metric quantifying cortical folding, was evaluated in 105 boys with autism spectrum disorder (ASD) and 49 typically developing (TD) boys at 3 and 5 years-of-age. At 3 years-of-age, boys with ASD had reduced gyrification in the fusiform gyrus compared with TD boys. A longitudinal evaluation from 3 to 5 years revealed that while TD boys had stable/decreasing LGI, boys with ASD had increasing LGI in right inferior temporal gyrus, right inferior frontal gyrus, right inferior parietal lobule, and stable LGI in left lingual gyrus. LGI was also examined in a previously defined neurophenotype of boys with ASD and disproportionate megalencephaly. At 3 years-of-age, this subgroup exhibited increased LGI in right dorsomedial prefrontal cortex, cingulate cortex, and paracentral cortex, and left cingulate cortex and superior frontal gyrus relative to TD boys and increased LGI in right paracentral lobule and parahippocampal gyrus, and left precentral gyrus compared with boys with ASD and normal brain size. In summary, this study identified alterations in the pattern and development of LGI during early childhood in ASD. Distinct patterns of alterations in subgroups of boys with ASD suggests that multiple neurophenotypes exist and boys with ASD and disproportionate megalencephaly should be evaluated separately.

Patterns of Cortical Folding Associated with Autistic Symptoms in Carriers and Noncarriers of the 22q11.2 Microdeletion

22q11.2 deletion syndrome (22q11.2DS) is a genetic condition accompanied by a range of psychiatric manifestations, including autism spectrum disorder (ASD). It remains unknown, however, whether these symptoms are mediated by the same or distinct neural mechanisms as in idiopathic ASD. Here, we examined differences in lGI associated with ASD in 50 individuals with 22q11.2DS (n = 25 with ASD, n = 25 without ASD) and 81 individuals without 22q11.2DS (n = 40 with ASD, n = 41 typically developing controls). We initially utilized a factorial design to identify the set of brain regions where lGI is associated with the main effect of 22q11.2DS, ASD, and with the 22q11.2DS-by-ASD interaction term. Subsequently, we employed canonical correlation analysis (CCA) to compare the multivariate association between variability in lGI and the complex clinical phenotype of ASD between 22q11.2DS carriers and noncarriers. Across approaches, we established that even though there is a high degree of clinical similarity across groups, the associated patterns of lGI significantly differed between carriers and noncarriers of the 22q11.2 microdeletion. Our results suggest that ASD symptomatology recruits different neuroanatomical underpinnings across disorders and that 22q11.2DS individuals with ASD represent a neuroanatomically distinct subgroup that differs from 22q11.2DS individuals without ASD and from individuals with idiopathic ASD.

Association of Epigenetic Metrics of Biological Age With Cortical Thickness

IMPORTANCE

Magnetic resonance imaging (MRI) studies of aging adults have shown substantial intersubject variability across various brain metrics, and some of this variability is likely attributable to chronological age being an imprecise measure of age-related change. Accurately quantifying one's biological age could allow better quantification of healthy and pathological changes in the aging brain.

OBJECTIVE

To investigate the association of DNA methylation (DNAm)-based biological age with cortical thickness and to assess whether biological age acceleration compared with chronological age captures unique variance in cortical thinning.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used high-resolution structural brain MRI data collected from a sample of healthy aging adults who were participating in a larger ongoing neuroimaging study that began in May 2014. This population-based study accrued participants from the greater Omaha, Nebraska, metropolitan area. One hundred sixty healthy adults were contacted for the MRI component, 82 of whom participated in both DNAm and MRI study components. Data analysis was performed from March to June 2019.

MAIN OUTCOMES AND MEASURES

Vertexwise cortical thickness, DNAm-based biological age, and biological age acceleration compared with chronological age were measured. A pair of multivariable regression models were computed in which cortical thickness was regressed on DNAm-based biological age, controlling for sex in the first model and also controlling for chronological age in the second model.

RESULTS

Seventy-nine adult participants (38 women; mean [SD] age, 43.82 [14.50] years; age range, 22-72 years) were included in all final analyses. Advancing biological age was correlated with cortical thinning across frontal, superior temporal, inferior parietal, and medial occipital regions. In addition, biological age acceleration relative to chronological age was associated with cortical thinning in orbitofrontal, superior and inferior temporal, somatosensory, parahippocampal, and fusiform regions. Specifically, for every 1 year of biological age acceleration, cortical thickness would be expected to decrease by 0.024 mm (95% CI, -0.04 to -0.01 mm) in the left orbitofrontal cortex (partial r, -0.34; P = .002), 0.014 mm (95% CI, -0.02 to -0.01 mm) in the left superior temporal gyrus (partial r, -0.36; P = .001), 0.015 mm (95% CI, -0.02 to -0.01 mm) in the left fusiform gyrus (partial r, -0.38; P = .001), 0.015 mm (95% CI, -0.02 to -0.01 mm) in the right fusiform gyrus (partial r, -0.43; P < .001), 0.019 mm (95% CI, -0.03 to -0.01 mm) in the right inferior temporal sulcus (partial r, -0.34; P = .002), and 0.011 mm (95% CI, -0.02 to -0.01 mm) in the right primary somatosensory cortex (partial r, -0.37; P = .001).

CONCLUSIONS AND RELEVANCE

To our knowledge, this is the first study to investigate vertexwise cortical thickness in relation to DNAm-based biological age, and the findings suggest that this metric of biological age may yield additional insight on healthy and pathological cortical aging compared with standard measures of chronological age alone.

An automated machine learning approach to predict brain age from cortical anatomical measures

The use of machine learning (ML) algorithms has significantly increased in neuroscience. However, from the vast extent of possible ML algorithms, which one is the optimal model to predict the target variable? What are the hyperparameters for such a model? Given the plethora of possible answers to these questions, in the last years, automated ML (autoML) has been gaining attention. Here, we apply an autoML library called Tree-based Pipeline Optimisation Tool (TPOT) which uses a tree-based representation of ML pipelines and conducts a genetic programming-based approach to find the model and its hyperparameters that more closely predicts the subject's true age. To explore autoML and evaluate its efficacy within neuroimaging data sets, we chose a problem that has been the focus of previous extensive study: brain age prediction. Without any prior knowledge, TPOT was able to scan through the model space and create pipelines that outperformed the state-of-the-art accuracy for Freesurfer-based models using only thickness and volume information for anatomical structure. In particular, we compared the performance of TPOT (mean absolute error [MAE]: 4.612 ± .124 years) and a relevance vector regression (MAE 5.474 ± .140 years). TPOT also suggested interesting combinations of models that do not match the current most used models for brain prediction but generalise well to unseen data. AutoML showed promising results as a data-driven approach to find optimal models for neuroimaging applications.

Age-related differences in myeloarchitecture measured at 7 T

We have used the magnetisation transfer (MT) MRI measure as a primary measure of myelination in both the gray matter (GM) of the 78 cortical automated anatomical labeling (AAL) regions of the brain, and the underlying white matter in each region, in a cohort of healthy adults (aged 19-62 year old). The results revealed a significant quadratic trend in myelination with age, with average global myelination peaking at 42.9 year old in gray matter, and at 41.7 year old in white matter. We also explored the possibility of using the Nuclear Overhauser Enhancement (NOE) effect, which is acquired in a similar method to MT, as an additional measure of myelination. We found that the MT and NOE signals were strongly correlated in the brain and that the NOE effects displayed similar (albeit weaker) parabolic trends with age. We also investigated differences in cortical thickness with age, and confirmed a previous result of a linear decline of 4.5 ± 1.2 μm/y.