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

Mapping morphological cortical networks with joint probability distributions from multiple morphological features

Morphological features sourced from structural magnetic resonance imaging can be used to infer human brain connectivity. Although integrating different morphological features may theoretically be beneficial for obtaining more precise morphological connectivity networks (MCNs), the empirical evidence to support this supposition is scarce. Moreover, the incorporation of different morphological features remains an open question. In this study, we proposed a method to construct cortical MCNs based on multiple morphological features. Specifically, we adopted a multi-dimensional kernel density estimation algorithm to fit regional joint probability distributions (PDs) from different combinations of four morphological features, and estimated inter-regional similarity in the joint PDs via Jensen-Shannon divergence. We evaluated the method by comparing the resultant MCNs with those built based on different single morphological features in terms of topological organization, test-retest reliability, biological plausibility, and behavioral and cognitive relevance. We found that, compared to MCNs built based on different single morphological features, MCNs derived from multiple morphological features displayed less segregated, but more integrated network architecture and different hubs, had higher test-retest reliability, encompassed larger proportions of inter-hemispheric edges and edges between brain regions within the same cytoarchitectonic class, and explained more inter-individual variance in behavior and cognition. These findings were largely reproducible when different brain atlases were used for cortical parcellation. Further analysis of macaque MCNs revealed weak, but significant correlations with axonal connectivity from tract-tracing, independent of the number of morphological features. Altogether, this paper proposes a new method for integrating different morphological features, which will be beneficial for constructing MCNs.

Cortical Morphological Networks Differ Between Gyri and Sulci

This study explored how the human cortical folding pattern composed of convex gyri and concave sulci affected single-subject morphological brain networks, which are becoming an important method for studying the human brain connectome. We found that gyri-gyri networks exhibited higher morphological similarity, lower small-world parameters, and lower long-term test-retest reliability than sulci-sulci networks for cortical thickness- and gyrification index-based networks, while opposite patterns were observed for fractal dimension-based networks. Further behavioral association analysis revealed that gyri-gyri networks and connections between gyral and sulcal regions significantly explained inter-individual variance in Cognition and Motor domains for fractal dimension- and sulcal depth-based networks. Finally, the clinical application showed that only sulci-sulci networks exhibited morphological similarity reductions in major depressive disorder for cortical thickness-, fractal dimension-, and gyrification index-based networks. Taken together, these findings provide novel insights into the constraint of the cortical folding pattern to the network organization of the human brain.

Gyrification across psychotic disorders: A bipolar-schizophrenia network of intermediate phenotypes study

BACKGROUND

The profiles of cortical gyrification across schizophrenia, bipolar I disorder, and schizoaffective disorder have been studied to a limited extent, report discordant findings, and are rarely compared in the same study. Here we assess gyrification in a large dataset of psychotic disorder probands, categorized according to the DSM-IV. Furthermore, we explore gyrification changes with age across healthy controls and probands.

METHODS

Participants were recruited within the Bipolar-Schizophrenia Network of Intermediate Phenotypes study and received T1-MPRAGE and clinical assessment. Gyrification was measured using FreeSurfer 7.1.0. Pairwise t-tests were conducted in R, and age-related gyrification changes were analyzed in MATLAB. P values <0.05 after false discovery rate correction were considered significant.

RESULTS

Significant hypogyria in schizophrenia, bipolar disorder, and schizoaffective disorder probands compared to controls was found, with a significant difference bilaterally in the frontal lobe between schizophrenia and bipolar disorder probands. Verbal memory was associated with gyrification in the right frontal and right cingulate cortex in schizophrenia. Age-fitted gyrification curves differed significantly among psychotic disorders and controls.

CONCLUSIONS

Findings indicate hypogyria in DSM-IV psychotic disorders compared to controls and suggest differential patterns of gyrification across the different diagnoses. The study extends age related models of gyrification to psychotic disorder probands and supports that age-related differences in gyrification may differ across diagnoses. Fitted gyrification curves among probands categorized by DSM-IV significantly deviate from controls, with the model capturing early hypergyria and later hypogyria in schizophrenia compared to controls; this suggests unique disease and age-related changes in gyrification across psychotic disorders.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Individual-based morphological brain network changes in children with Rolandic epilepsy

OBJECTIVE

To investigate the local cortical morphology and individual-based morphological brain networks (MBNs) changes in children with Rolandic epilepsy (RE).

METHODS

Based on the structural MRI data of 56 children with RE and 56 healthy controls (HC), we constructed four types of individual-based MBNs using morphological indices (cortical thickness [CT], fractal dimension [FD], gyrification index [GI], and sulcal depth [SD]). The global and nodal properties of the brain networks were analyzed using graph theory. The between-group difference in local morphology and network topology was estimated, and partial correlation analysis was further analyzed.

RESULTS

Compared with the HC, children with RE showed regional GI increases in the right posterior cingulate gyrus and SD increases in the right anterior cingulate gyrus and medial prefrontal cortex. Regarding the network level, RE exhibited increased characteristic path length in CT-based and FD-based networks, while decreased FD-based network node efficiency in the right inferior frontal gyrus. No significant correlation between altered morphological features and clinical variables was found in RE.

CONCLUSIONS

These findings indicated that children with RE have disrupted morphological brain network organization beyond local morphology changes.

SIGNIFICANCE

The present study could provide more theoretical basis for exploring the neuropathological mechanisms in RE.

Pilot study of circulating cell-free mitochondrial DNA in relation to brain structure in youth bipolar disorder

BACKGROUND

Mitochondrial dysfunction is implicated in the neuropathology of bipolar disorder (BD). Higher circulating cell-free mitochondrial DNA (ccf-mtDNA), generally reflecting poorer mitochondrial health, has been associated with greater symptoms severity in BD. The current study examines the association of serum ccf-mtDNA and brain structure in relation to youth BD. We hypothesized that higher ccf-mtDNA will be associated with measures of lower brain structure, particularly in the BD group.

METHODS

Participants included 40 youth (BD, n = 19; Control group [CG], n = 21; aged 13-20 years). Serum ccf-mtDNA levels were assayed. T1-weighted brain images were acquired using 3T-MRI. Region of interest (ROI) analyses examined prefrontal cortex (PFC) and whole brain gray matter, alongside exploratory vertex-wise analyses. Analyses examined ccf-mtDNA main-effects and ccf-mtDNA-by-diagnosis interaction effects controlling for age, sex, and intracranial volume.

RESULTS

There was no significant difference in ccf-mtDNA levels between BD and CG. In ROI analyses, higher ccf-mtDNA was associated with higher PFC surface area (SA) (β = 0.32 p < 0.001) and PFC volume (β = 0.32 p = 0.002) in the overall sample. In stratified analyses, higher ccf-mtDNA was associated with higher PFC SA within both subgroups (BD: β = 0.39 p = 0.02; CG: β = 0.24 p = 0.045). Higher ccf-mtDNA was associated with higher PFC volume within the BD group (β = 0.39 p = 0.046). In vertex-wise analyses, higher ccf-mtDNA was associated with higher SA and volume in frontal clusters within the overall sample and within the BD group. There were significant ccf-mtDNA-by-diagnosis interactions in three frontal and parietal clusters, whereby higher ccf-mtDNA was associated with higher neurostructural metrics in the BD group but lower neurostructural metrics in CG.

CONCLUSIONS

Contrasting our hypothesis, higher ccf-mtDNA was consistently associated with higher, rather than lower, regional neuralstructural metrics among youth with BD. While this finding may reflect a compensatory mechanism, future repeated-measures prospective studies evaluating the inter-relationship among ccf-mtDNA, mood, and brain structure across developmental epochs and illness stages are warranted.

Age-related differences in the intrinsic connectivity of the hippocampus and ventral temporal lobe in autistic individuals

Introduction

Although memory challenges in autistic individuals have been characterized recently, the functional connectivity of the hippocampus and ventral temporal lobe, two structures important for episodic and semantic memory functions, are poorly understood in autistic individuals. Moreover, age-related differences in the functional connectivity associated with these two memory networks are unrevealed.

Methods

The current study investigated age-related differences in intrinsic connectivity of the hippocampal and ventral temporal lobe (vTL) memory networks in well-matched ASD (n = 73; age range: 10.23-55.40 years old) and Non-ASD groups (n = 74; age range: 10.46-56.20 years old) from the open dataset ABIDE-I. Both theory-driven ROI-to-ROI approach and exploratory seed-based whole-brain approach were used.

Results and discussion

Our findings revealed reduced connectivity in ASD compared to Non-ASD peers, as well as an age-related reduction in the connectivity of hippocampal and vTL networks with triple networks, namely, the default mode network (DMN), the central executive network (CEN), and the salience network (SN), potentially underpinning their challenges in memory, language, and social functions. However, we did not observe reliable differences in age-related effects between the ASD and Non-ASD groups. Our study underscores the importance of understanding memory network dysfunctions in ASD across the lifespan to inform educational and clinical practices.

Age-related decline in thickness and surface area in the cortical surface and hippocampus: lifespan trajectories and decade-by-decade analyses

Previous studies on age-related changes in cortical and hippocampal morphology were not designed or able to reveal the complex spatial patterns of changes across the lifespan. To this end, the current study examined these changes in a decade-by-decade manner by comparing consecutive age decades at the vertex-wise level. Additionally, the lifespan trajectories of cortical/hippocampal mean thickness and total surface area were modeled and plotted out to provide an overview of their age-related changes. Using two lifespan datasets (Ntotal = 1378; 18 ≤ age ≤ 100), vertex-wise thickness and surface area measurements were extracted from the cortical and unfolded hippocampal surfaces and analyzed using whole-brain/hippocampus vertex-wise analyses. Lifespan trajectories of cortical/hippocampal mean thickness and total surface area were modeled with generalized additive models for location, scale, and shape. These models revealed fairly linear declines in both cortical measures and inverted U-shaped trajectories for both hippocampal measures. Across the different age decades, the sizes and locations of cortical thinning clusters were highly variable across the age decades. No significant clusters of cortical surface area changes were observed across the age decades. Significant clusters of hippocampal surface area and thickness reduction were not observed until the 70s. Generally, the agreement between datasets on the hippocampal findings was much higher than those of the cortical surface. These findings revealed important nuances in the age-related changes of cortical and hippocampal morphology and cautioned against using lifespan trajectories to infer decade-by-decade changes in the cortical surface and the hippocampus.

Corticogenesis and folding process of the neopallium in the South American plains vizcacha, Lagostomus maximus

The plains vizcacha, Lagostomus maximus, is a precocial hystricomorph rodent with a gyrencephalic brain. This work aimed to perform a time-lapse analysis of the embryonic brain cortical development in the plains vizcacha to establish a species-specific temporal window for corticogenesis and the gyrencephaly onset. Additionally, a comparative examination with evolutionarily related rodents was conducted. Embryos from 40 embryonic days (ED) until the end of pregnancy ( ∼ $\sim $ 154 ED) were evaluated. The neuroanatomical examination determined transverse sulci at 80 ED and rostral lateral and caudal intraparietal sulci around 95 ED. Histological examination of corticogenesis showed emergence of the subplate at 43 ED and expansion of the subventricular zone (SVZ) and its division into inner and outer SVZs around 54 ED. The neocortical layers formation followed an inside-to-outside spatiotemporal gradient beginning with the emergence of layers VI and V at 68 ED and establishing the final six neocortical layers around 100 ED. A progressive increment of gyrencephalization index (GI) from 1.005 ± 0.003 around 70 ED, which reflects a smooth cortex, up to 1.07 ± 0.009 at the end of gestation, reflecting a gyrencephalic neuroanatomy, was determined. Contrarily, the minimum cortical thickness (MCT) progressively decreased from 61 ED up to the end of gestation. These results show that the decrease in the cortical thickness, which enables the onset of neocortical invaginations, occurs together with the expansion and subdivision of the SVZ. The temporal comparison of corticogenesis in plains vizcacha with that in relative species reflects a prenatal long process compared with other rodents that may give an evolutionary advantage to L. maximus as a precocial species.

Alcohol Use Disorder and Dementia: A Review

PURPOSE

By 2040, 21.6% of Americans will be over age 65, and the population of those older than age 85 is estimated to reach 14.4 million. Although not causative, older age is a risk factor for dementia: every 5 years beyond age 65, the risk doubles; approximately one-third of those older than age 85 are diagnosed with dementia. As current alcohol consumption among older adults is significantly higher compared to previous generations, a pressing question is whether drinking alcohol increases the risk for Alzheimer's disease or other forms of dementia.

SEARCH METHODS

Databases explored included PubMed, Web of Science, and ScienceDirect. To accomplish this narrative review on the effects of alcohol consumption on dementia risk, the literature covered included clinical diagnoses, epidemiology, neuropsychology, postmortem pathology, neuroimaging and other biomarkers, and translational studies. Searches conducted between January 12 and August 1, 2023, included the following terms and combinations: "aging," "alcoholism," "alcohol use disorder (AUD)," "brain," "CNS," "dementia," "Wernicke," "Korsakoff," "Alzheimer," "vascular," "frontotemporal," "Lewy body," "clinical," "diagnosis," "epidemiology," "pathology," "autopsy," "postmortem," "histology," "cognitive," "motor," "neuropsychological," "magnetic resonance," "imaging," "PET," "ligand," "degeneration," "atrophy," "translational," "rodent," "rat," "mouse," "model," "amyloid," "neurofibrillary tangles," "α-synuclein," or "presenilin." When relevant, "species" (i.e., "humans" or "other animals") was selected as an additional filter. Review articles were avoided when possible.

SEARCH RESULTS

The two terms "alcoholism" and "aging" retrieved about 1,350 papers; adding phrases-for example, "postmortem" or "magnetic resonance"-limited the number to fewer than 100 papers. Using the traditional term, "alcoholism" with "dementia" resulted in 876 citations, but using the currently accepted term "alcohol use disorder (AUD)" with "dementia" produced only 87 papers. Similarly, whereas the terms "Alzheimer's" and "alcoholism" yielded 318 results, "Alzheimer's" and "alcohol use disorder (AUD)" returned only 40 citations. As pertinent postmortem pathology papers were published in the 1950s and recent animal models of Alzheimer's disease were created in the early 2000s, articles referenced span the years 1957 to 2024. In total, more than 5,000 articles were considered; about 400 are herein referenced.

DISCUSSION AND CONCLUSIONS

Chronic alcohol misuse accelerates brain aging and contributes to cognitive impairments, including those in the mnemonic domain. The consensus among studies from multiple disciplines, however, is that alcohol misuse can increase the risk for dementia, but not necessarily Alzheimer's disease. Key issues to consider include the reversibility of brain damage following abstinence from chronic alcohol misuse compared to the degenerative and progressive course of Alzheimer's disease, and the characteristic presence of protein inclusions in the brains of people with Alzheimer's disease, which are absent in the brains of those with AUD.

Gender Incongruence and Autistic Traits: Cerebral and Behavioral Underpinnings

Gender dysphoria and autism spectrum disorder (ASD) co-occur at high rates. Yet, it is unknown whether gender dysphoria and ASD are associated with common or distinct neurobiological correlates or how they relate to experiences of gender-related body incongruence. Using the Social Responsiveness Scale, we assessed autistic traits in 99 transgender and 99 cisgender individuals and investigated their associations with gender-related body incongruence, measured via a visually based "Body Morph" test, and with cortical thickness in the brain. Autistic traits were significantly higher among transgender individuals, and those with higher autistic traits had higher body incongruence scoring. Among transgender individuals, higher autistic traits were linked with a thinner cortex bilaterally in the temporal pole and the superior and inferior temporal gyri. Autistic traits were only partly associated with cortical morphology patterns previously reported in transgender individuals; instead, they were primarily linked to temporal lobe areas mediating social cognition. While replicating the previous literature on the increased prevalence of autistic traits among transgender individuals, this study reports specific regions in the brains of transgender individuals where cortical thickness is associated with autistic traits.

Culture, prefrontal volume, and memory

Prior cross-cultural studies have demonstrated differences among Eastern and Western cultures in memory and cognition along with variation in neuroanatomy and functional engagement. We further probed cultural neuroanatomical variability in terms of its relationship with memory performance. Specifically, we investigated how memory performance related to gray matter volume in several prefrontal lobe structures, including across cultures. For 58 American and 57 Taiwanese young adults, memory performance was measured with the California Verbal Learning Test (CVLT) using performance on learning trial 1, on which Americans had higher scores than the Taiwanese, and the long delayed free recall task, on which groups performed similarly. MRI data were reconstructed using FreeSurfer. Across both cultures, we observed that larger volumes of the bilateral rostral anterior cingulate were associated with lower scores on both CVLT tasks. In terms of effects of culture, the relationship between learning trial 1 scores and gray matter volumes in the right superior frontal gyrus had a trend for a positive relationship in Taiwanese but not in Americans. In addition to the a priori analysis of select frontal volumes, an exploratory whole-brain analysis compared volumes-without considering CVLT performance-across the two cultural groups in order to assess convergence with prior research. Several cultural differences were found, such that Americans had larger volumes in the bilateral superior frontal and lateral occipital cortex, whereas Taiwanese had larger volumes in the bilateral rostral middle frontal and inferior temporal cortex, and the right precuneus.

Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers

Structural brain changes underly cognitive changes in older age and contribute to inter-individual variability in cognition. Here, we assessed how changes in cortical thickness, surface area, and subcortical volume, are related to cognitive change in cognitively unimpaired older adults using structural magnetic resonance imaging (MRI) data-driven clustering. Specifically, we tested (1) which brain structural changes over time predict cognitive change in older age (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers phosphorylated tau (p-tau) and amyloid-β (Aβ42), and (3) the degree of overlap between clusters derived from different structural features. In total 1899 cognitively healthy older adults (50 - 93 years) were followed up to 16 years with neuropsychological and structural MRI assessments, a subsample of which (n = 612) had CSF p-tau and Aβ42 measurements. We applied Monte-Carlo Reference-based Consensus clustering to identify subgroups of older adults based on structural brain change patterns over time. Four clusters for each brain feature were identified, representing the degree of longitudinal brain decline. Each brain feature provided a unique contribution to brain aging as clusters were largely independent across modalities. Cognitive change and baseline cognition were best predicted by cortical area change, whereas higher levels of p-tau and Aβ42 were associated with changes in subcortical volume. These results provide insights into the link between changes in brain morphology and cognition, which may translate to a better understanding of different aging trajectories.

Parental education and income are linked to offspring cortical brain structure and psychopathology at 9-11 years

Background

A child's socioeconomic environment can shape central aspects of their life, including vulnerability to mental disorders. Negative environmental influences in youth may interfere with the extensive and dynamic brain development occurring at this time. Indeed, there are numerous yet diverging reports of associations between parental socioeconomic status (SES) and child cortical brain morphometry. Most of these studies have used single metric- or unimodal analyses of standard cortical morphometry that downplay the probable scenario where numerous biological pathways in sum account for SES-related cortical differences in youth.

Methods

To comprehensively capture such variability, using data from 9758 children aged 8.9-11.1 years from the ABCD Study®, we employed linked independent component analysis (LICA) and fused vertex-wise cortical thickness, surface area, curvature and grey-/white-matter contrast (GWC). LICA revealed 70 uni- and multimodal components. We then assessed the linear relationships between parental education, parental income and each of the cortical components, controlling for age, sex, genetic ancestry, and family relatedness. We also assessed whether cortical structure moderated the negative relationships between parental SES and child general psychopathology.

Results

Parental education and income were both associated with larger surface area and higher GWC globally, in addition to local increases in surface area and to a lesser extent bidirectional GWC and cortical thickness patterns. The negative relation between parental income and child psychopathology were attenuated in children with a multimodal pattern of larger frontal- and smaller occipital surface area, and lower medial occipital thickness and GWC.

Conclusion

Structural brain MRI is sensitive to SES diversity in childhood, with GWC emerging as a particularly relevant marker together with surface area. In low-income families, having a more developed cortex across MRI metrics, appears beneficial for mental health.

Cortical folding correlates to aging and Alzheimer's Disease's cognitive and CSF biomarkers

This manuscript presents the quantification and correlation of three aspects of Alzheimer's Disease evolution, including structural, biochemical, and cognitive assessments. We aimed to test a novel structural biomarker for neurodegeneration based on a cortical folding model for mammals. Our central hypothesis is that the cortical folding variable, representative of axonal tension in white matter, is an optimal discriminator of pathological aging and correlates with altered loadings in Cerebrospinal Fluid samples and a decline in cognition and memory. We extracted morphological features from T1w 3T MRI acquisitions using FreeSurfer from 77 Healthy Controls (age = 66 ± 8.4, 69% females), 31 Mild Cognitive Impairment (age = 72 ± 4.8, 61% females), and 13 Alzheimer's Disease patients (age = 77 ± 6.1, 62% females) of recruited volunteers in Brazil to test its discriminative power using optimal cut-point analysis. Cortical folding distinguishes the groups with reasonable accuracy (Healthy Control-Alzheimer's Disease, accuracy = 0.82; Healthy Control-Mild Cognitive Impairment, accuracy = 0.56). Moreover, Cerebrospinal Fluid biomarkers (total Tau, A[Formula: see text]1-40, A[Formula: see text]1-42, and Lipoxin) and cognitive scores (Cognitive Index, Rey's Auditory Verbal Learning Test, Trail Making Test, Digit Span Backward) were correlated with the global neurodegeneration in MRI aiming to describe health, disease, and the transition between the two states using morphology.

Brain age prediction across the human lifespan using multimodal MRI data

Measuring differences between an individual's age and biological age with biological information from the brain have the potential to provide biomarkers of clinically relevant neurological syndromes that arise later in human life. To explore the effect of multimodal brain magnetic resonance imaging (MRI) features on the prediction of brain age, we investigated how multimodal brain imaging data improved age prediction from more imaging features of structural or functional MRI data by using partial least squares regression (PLSR) and longevity data sets (age 6-85 years). First, we found that the age-predicted values for each of these ten features ranged from high to low: cortical thickness (R = 0.866, MAE = 7.904), all seven MRI features (R = 0.8594, MAE = 8.24), four features in structural MRI (R = 0.8591, MAE = 8.24), fALFF (R = 0.853, MAE = 8.1918), gray matter volume (R = 0.8324, MAE = 8.931), three rs-fMRI feature (R = 0.7959, MAE = 9.744), mean curvature (R = 0.7784, MAE = 10.232), ReHo (R = 0.7833, MAE = 10.122), ALFF (R = 0.7517, MAE = 10.844), and surface area (R = 0.719, MAE = 11.33). In addition, the significance of the volume and size of brain MRI data in predicting age was also studied. Second, our results suggest that all multimodal imaging features, except cortical thickness, improve brain-based age prediction. Third, we found that the left hemisphere contributed more to the age prediction, that is, the left hemisphere showed a greater weight in the age prediction than the right hemisphere. Finally, we found a nonlinear relationship between the predicted age and the amount of MRI data. Combined with multimodal and lifespan brain data, our approach provides a new perspective for chronological age prediction and contributes to a better understanding of the relationship between brain disorders and aging.

Midlife physical activity engagement is associated with later-life brain health

The relationship between midlife physical activity (PA), and cognition and brain health in later life is poorly understood with conflicting results from previous research. Investigating the contribution of midlife PA to later-life cognition and brain health in high-risk populations will propel the development of health guidance for those most in need. The current study examined the association between midlife PA engagement and later-life cognition, grey matter characteristics and resting-state functional connectivity in older individuals at high-risk for Alzheimer's disease. The association between midlife PA and later-life cognitive function was not significant but was moderated by later-life PA. Meanwhile, greater midlife moderate-to-vigorous PA was associated with greater grey matter surface area in the left middle frontal gyrus. Moreover, greater midlife total PA was associated with diminished functional connectivity between bilateral middle frontal gyri and middle cingulum, supplementary motor areas, and greater functional connectivity between bilateral hippocampi and right cerebellum, Crus II. These results indicate the potentially independent contribution of midlife PA to later-life brain health.

Efficacy of MRI data harmonization in the age of machine learning: a multicenter study across 36 datasets

Pooling publicly-available MRI data from multiple sites allows to assemble extensive groups of subjects, increase statistical power, and promote data reuse with machine learning techniques. The harmonization of multicenter data is necessary to reduce the confounding effect associated with non-biological sources of variability in the data. However, when applied to the entire dataset before machine learning, the harmonization leads to data leakage, because information outside the training set may affect model building, and potentially falsely overestimate performance. We propose a 1) measurement of the efficacy of data harmonization; 2) harmonizer transformer, i.e., an implementation of the ComBat harmonization allowing its encapsulation among the preprocessing steps of a machine learning pipeline, avoiding data leakage by design. We tested these tools using brain T1-weighted MRI data from 1740 healthy subjects acquired at 36 sites. After harmonization, the site effect was removed or reduced, and we showed the data leakage effect in predicting individual age from MRI data, highlighting that introducing the harmonizer transformer into a machine learning pipeline allows for avoiding data leakage by design.

Morphometric network-based abnormalities correlate with psychiatric comorbidities and gene expression in PCDH19-related developmental and epileptic encephalopathy

Protocadherin-19 (PCDH19) developmental and epileptic encephalopathy causes an early-onset epilepsy syndrome with limbic seizures, typically occurring in clusters and variably associated with intellectual disability and a range of psychiatric disorders including hyperactive, obsessive-compulsive and autistic features. Previous quantitative neuroimaging studies revealed abnormal cortical areas in the limbic formation (parahippocampal and fusiform gyri) and underlying white-matter fibers. In this study, we adopted morphometric, network-based and multivariate statistical methods to examine the cortex and substructure of the hippocampus and amygdala in a cohort of 20 PCDH19-mutated patients and evaluated the relation between structural patterns and clinical variables at individual level. We also correlated morphometric alterations with known patterns of PCDH19 expression levels. We found patients to exhibit high-significant reductions of cortical surface area at a whole-brain level (left/right pvalue = 0.045/0.084), and particularly in the regions of the limbic network (left/right parahippocampal gyri pvalue = 0.230/0.016; left/right entorhinal gyri pvalue = 0.002/0.327), and bilateral atrophy of several subunits of the amygdala and hippocampus, particularly in the CA regions (head of the left CA3 pvalue = 0.002; body of the right CA3 pvalue = 0.004), and differences in the shape of hippocampal structures. More severe psychiatric comorbidities correlated with more significant altered patterns, with the entorhinal gyrus (pvalue = 0.013) and body of hippocampus (pvalue = 0.048) being more severely affected. Morphometric alterations correlated significantly with the known expression patterns of PCDH19 (rvalue = -0.26, pspin = 0.092). PCDH19 encephalopathy represents a model of genetically determined neural network based neuropsychiatric disease in which quantitative MRI-based findings correlate with the severity of clinical manifestations and had have a potential predictive value if analyzed early.

Structural alterations of the motor cortex and higher order cortical areas suggest early neurodevelopmental origin of catatonia in schizophrenia

The neurobiology of catatonia is still poorly understood. Particularly structural MRI studies yielded conflicting results. Heterogeneity of findings was suggested to stem from specifics of different rating scales. This study sought to test grey matter differences between patients with catatonia, patients without catatonia, and healthy controls using the two main instruments of catatonia rating. We included 98 patients with schizophrenia spectrum disorders and 42 healthy controls. Catatonia was measured using the Bush Francis Catatonia Rating Scale and the Northoff Catatonia Rating Scale. According to these scales, patients were classified into those with and those without catatonia. We tested whole brain grey matter volume, cortical thickness, and local gyrification across groups. Both catatonia rating scales correlated at tau = 0.65 but failed to classify identical subjects as catatonia patients. However, group differences in grey matter parameters were broadly similar with either rating scale to identify catatonia cases. Catatonia patients had reduced grey matter volume compared to controls in a large network including orbitofrontal cortex, cingulate, thalamus, and amygdala. While there was no group difference in cortical thickness, catatonia patients had increased local gyrification in premotor, motor, and parietal cortices compared to controls. Hypergyrification of the motor cortex and higher order cortical areas was found in catatonia patients compared to patients without catatonia. Both catatonia rating scales find similar symptom severity and group differences in grey matter indices. Catatonia is linked to reduced grey matter volume and increased local gyrification, suggesting some impact of early neurodevelopmental insults.

The longitudinal impact of type 2 diabetes on brain gyrification

Type 2 diabetes has an effect on brain structure, including cortical gyrification. The significance of these changes is better understood if assessed over time. However, there is a lack of studies assessing longitudinally the effect of this disease with complex aethology in gyrification. While changes in this feature have been associated mainly with genetic legacy, our study allowed to shed light on the effect of the variation of glycaemic profile over time in gyrification in this metabolic disease. In this longitudinal study, we analysed brain anatomical magnetic resonance images of 15 participants with type 2 diabetes and 13 healthy control participants to investigate the impact of this metabolic disease on the gyrification index over a 7-year period. We observed a significant interaction between time and group in six regions, four of which (left precentral gyrus, left gyrus rectus, left subcentral gyrus and sulci and right inferior temporal gyrus) showed an increase in gyrification in type 2 diabetes and a decrease in the control group and the two others (left pericallosal sulcus and right inferior frontal sulcus) the opposite pattern. The variation of the gyrification was correlated with the variation of the glycaemic profile. Following the interaction, the simple main effect of time in each group separately has shown that in the group with diabetes, there were more regions susceptible to alterations of gyrification. In sum, our results raise credit for the possibility that glycaemic control also might influence gyrification in type 2 diabetes.

Links between psychopathological symptoms and cortical thickness in men with severe alcohol use disorder: A Magnetic Resonance Imaging study

BACKGROUND

Anxiety and depression are psychopathological states frequently co-occurring with severe alcohol use disorder (SAUD). These symptoms generally disappear with abstinence but may persist in some patients, increasing the relapse risk.

METHODS

The cerebral cortex thickness of 94 male patients with SAUD was correlated with symptoms of depression and anxiety, both measured at the end (2-3 weeks) of the detoxification treatment. Cortical measures were obtained using surface-based morphometry implemented with Freesurfer.

RESULTS

Depressive symptoms were associated with reduced cortical thickness in the superior temporal gyrus of the right hemisphere. Anxiety level was correlated with lower cortical thickness in the rostral middle frontal region, inferior temporal region, and supramarginal, postcentral, superior temporal, and transverse temporal regions of the left hemisphere, as well as with a large cluster in the middle temporal region of the right hemisphere.

CONCLUSIONS

At the end of the detoxification stage, the intensity of depressive and anxiety symptoms is inversely associated with the cortical thickness of regions involved in emotions-related processes, and the persistence of the symptoms could be explained by these brain deficits.

Increased functional connectivity between the auditory cortex and the frontoparietal network compensates for impaired visuomotor transformation after early auditory deprivation

Early auditory deprivation leads to a reorganization of large-scale brain networks involving and extending beyond the auditory system. It has been documented that visuomotor transformation is impaired after early deafness, associated with a hyper-crosstalk between the task-critical frontoparietal network and the default-mode network. However, it remains unknown whether and how the reorganized large-scale brain networks involving the auditory cortex contribute to impaired visuomotor transformation after early deafness. Here, we asked deaf and early hard of hearing participants and normal hearing controls to judge the spatial location of a visual target. Compared with normal hearing controls, the superior temporal gyrus showed significantly increased functional connectivity with the frontoparietal network and the default-mode network in deaf and early hard of hearing participants, specifically during egocentric judgments. However, increased superior temporal gyrus-frontoparietal network and superior temporal gyrus-default-mode network coupling showed antagonistic effects on egocentric judgments. In deaf and early hard of hearing participants, increased superior temporal gyrus-frontoparietal network connectivity was associated with improved egocentric judgments, whereas increased superior temporal gyrus-default-mode network connectivity was associated with deteriorated performance in the egocentric task. Therefore, the data suggest that the auditory cortex exhibits compensatory neuroplasticity (i.e. increased functional connectivity with the task-critical frontoparietal network) to mitigate impaired visuomotor transformation after early auditory deprivation.

Data-driven multivariate identification of gyrification patterns in a transdiagnostic patient cohort: A cluster analysis approach

BACKGROUND

Multivariate data-driven statistical approaches offer the opportunity to study multi-dimensional interdependences between a large set of biological parameters, such as high-dimensional brain imaging data. For gyrification, a putative marker of early neurodevelopment, direct comparisons of patterns among multiple psychiatric disorders and investigations of potential heterogeneity of gyrification within one disorder and a transdiagnostic characterization of neuroanatomical features are lacking.

METHODS

In this study we used a data-driven, multivariate statistical approach to analyze cortical gyrification in a large cohort of N = 1028 patients with major psychiatric disorders (Major depressive disorder: n = 783, bipolar disorder: n = 129, schizoaffective disorder: n = 44, schizophrenia: n = 72) to identify cluster patterns of gyrification beyond diagnostic categories.

RESULTS

Cluster analysis applied on gyrification data of 68 brain regions (DK-40 atlas) identified three clusters showing difference in overall (global) gyrification and minor regional variation (regions). Newly, data-driven subgroups are further discriminative in cognition and transdiagnostic disease risk factors.

CONCLUSIONS

Results indicate that gyrification is associated with transdiagnostic risk factors rather than diagnostic categories and further imply a more global role of gyrification related to mental health than a disorder specific one. Our findings support previous studies highlighting the importance of association cortices involved in psychopathology. Explorative, data-driven approaches like ours can help to elucidate if the brain imaging data on hand and its a priori applied grouping actually has the potential to find meaningful effects or if previous hypotheses about the phenotype as well as its grouping have to be revisited.

Single-subject cortical morphological brain networks across the adult lifespan

Age-related changes in focal cortical morphology have been well documented in previous literature; however, how interregional coordination patterns of the focal cortical morphology reorganize with advancing age is not well established. In this study, we performed a comprehensive analysis of the topological changes in single-subject morphological brain networks across the adult lifespan. Specifically, we constructed four types of single-subject morphological brain networks for 650 participants (aged from 18 to 88 years old), and characterized their topological organization using graph-based network measures. Age-related changes in the network measures were examined via linear, quadratic, and cubic models. We found profound age-related changes in global small-world attributes and efficiency, local nodal centralities, and interregional similarities of the single-subject morphological brain networks. The age-related changes were mainly embodied in cortical thickness networks, involved in frontal regions and highly connected hubs, concentrated on short-range connections, characterized by linear changes, and susceptible to connections between limbic, frontoparietal, and ventral attention networks. Intriguingly, nonlinear (i.e., quadratic or cubic) age-related changes were frequently found in the insula and limbic regions, and age-related cubic changes preferred long-range morphological connections. Finally, we demonstrated that the morphological similarity in cortical thickness between two frontal regions mediated the relationship between age and cognition measured by Cattell scores. Taken together, these findings deepen our understanding of adaptive changes of the human brain with advancing age, which may account for interindividual variations in behaviors and cognition.

Structural brain changes in emotion recognition across the adult lifespan

Emotion recognition (ER) declines with increasing age, yet little is known whether this observation is based on structural brain changes conveyed by differential atrophy. To investigate whether age-related ER decline correlates with reduced grey matter (GM) volume in emotion-related brain regions, we conducted a voxel-based morphometry analysis using data of the Human Connectome Project-Aging (N = 238, aged 36-87) in which facial ER was tested. We expected to find brain regions that show an additive or super-additive age-related change in GM volume indicating atrophic processes that reduce ER in older adults. The data did not support our hypotheses after correction for multiple comparisons. Exploratory analyses with a threshold of P < 0.001 (uncorrected), however, suggested that relationships between GM volume and age-related general ER may be widely distributed across the cortex. Yet, small effect sizes imply that only a small fraction of the decline of ER in older adults can be attributed to local GM volume changes in single voxels or their multivariate patterns.

Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analyses

Converging evidence suggests that schizophrenia (SZ) with primary, enduring negative symptoms (i.e., Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the neurobiological underpinnings remain undetermined. In the largest dataset of DSZ and Non-Deficit (NDSZ), we conducted a meta-analysis of data from 1560 individuals (168 DSZ, 373 NDSZ, 1019 Healthy Controls (HC)) and a mega-analysis of a subsampled data from 944 individuals (115 DSZ, 254 NDSZ, 575 HC) collected across 9 worldwide research centers of the ENIGMA SZ Working Group (8 in the mega-analysis), to clarify whether they differ in terms of cortical morphology. In the meta-analysis, sites computed effect sizes for differences in cortical thickness and surface area between SZ and control groups using a harmonized pipeline. In the mega-analysis, cortical values of individuals with schizophrenia and control participants were analyzed across sites using mixed-model ANCOVAs. The meta-analysis of cortical thickness showed a converging pattern of widespread thinner cortex in fronto-parietal regions of the left hemisphere in both DSZ and NDSZ, when compared to HC. However, DSZ have more pronounced thickness abnormalities than NDSZ, mostly involving the right fronto-parietal cortices. As for surface area, NDSZ showed differences in fronto-parietal-temporo-occipital cortices as compared to HC, and in temporo-occipital cortices as compared to DSZ. Although DSZ and NDSZ show widespread overlapping regions of thinner cortex as compared to HC, cortical thinning seems to better typify DSZ, being more extensive and bilateral, while surface area alterations are more evident in NDSZ. Our findings demonstrate for the first time that DSZ and NDSZ are characterized by different neuroimaging phenotypes, supporting a nosological distinction between DSZ and NDSZ and point toward the separate disease hypothesis.

Association between circadian sleep regulation and cortical gyrification in young and older adults

The circadian system orchestrates sleep timing and structure and is altered with increasing age. Sleep propensity, and particularly REM sleep is under strong circadian control and has been suggested to play an important role in brain plasticity. In this exploratory study, we assessed whether surface-based brain morphometry indices are associated with circadian sleep regulation and whether this link changes with age. Twenty-nine healthy older (55-82 years; 16 men) and 28 young participants (20-32 years; 13 men) underwent both structural magnetic resonance imaging and a 40-h multiple nap protocol to extract sleep parameters over day and night time. Cortical thickness and gyrification indices were estimated from T1-weighted images acquired during a classical waking day. We observed that REM sleep was significantly modulated over the 24-h cycle in both age groups, with older adults exhibiting an overall reduction in REM sleep modulation compared to young individuals. Interestingly, when taking into account the observed overall age-related reduction in REM sleep throughout the circadian cycle, higher day-night differences in REM sleep were associated with increased cortical gyrification in the right inferior frontal and paracentral regions in older adults. Our results suggest that a more distinctive allocation of REM sleep over the 24-h cycle is associated with regional cortical gyrification in aging, and thereby point towards a protective role of circadian REM sleep regulation for age-related changes in brain organization.

Disrupted brain gray matter connectome in social anxiety disorder: a novel individualized structural covariance network analysis

Phenotyping approaches grounded in structural network science can offer insights into the neurobiological substrates of psychiatric diseases, but this remains to be clarified at the individual level in social anxiety disorder (SAD). Using a recently developed approach combining probability density estimation and Kullback-Leibler divergence, we constructed single-subject structural covariance networks (SCNs) based on multivariate morphometry (cortical thickness, surface area, curvature, and volume) and quantified their global/nodal network properties using graph-theoretical analysis. We compared network metrics between SAD patients and healthy controls (HC) and analyzed the relationship to clinical characteristics. We also used support vector machine analysis to explore the ability of graph-theoretical metrics to discriminate SAD patients from HC. Globally, SAD patients showed higher global efficiency, shorter characteristic path length, and stronger small-worldness. Locally, SAD patients showed abnormal nodal centrality mainly involving left superior frontal gyrus, right superior parietal lobe, left amygdala, right paracentral gyrus, right lingual, and right pericalcarine cortex. Altered topological metrics were associated with the symptom severity and duration. Graph-based metrics allowed single-subject classification of SAD versus HC with total accuracy of 78.7%. This finding, that the topological organization of SCNs in SAD patients is altered toward more randomized configurations, adds to our understanding of network-level neuropathology in SAD.

Mitochondrial function-associated genes underlie cortical atrophy in prodromal synucleinopathies

Isolated rapid eye movement sleep behaviour disorder (iRBD) is a sleep disorder characterized by the loss of rapid eye movement sleep muscle atonia and the appearance of abnormal movements and vocalizations during rapid eye movement sleep. It is a strong marker of incipient synucleinopathy such as dementia with Lewy bodies and Parkinson's disease. Patients with iRBD already show brain changes that are reminiscent of manifest synucleinopathies including brain atrophy. However, the mechanisms underlying the development of this atrophy remain poorly understood. In this study, we performed cutting-edge imaging transcriptomics and comprehensive spatial mapping analyses in a multicentric cohort of 171 polysomnography-confirmed iRBD patients [67.7 ± 6.6 (49-87) years; 83% men] and 238 healthy controls [66.6 ± 7.9 (41-88) years; 77% men] with T1-weighted MRI to investigate the gene expression and connectivity patterns associated with changes in cortical thickness and surface area in iRBD. Partial least squares regression was performed to identify the gene expression patterns underlying cortical changes in iRBD. Gene set enrichment analysis and virtual histology were then done to assess the biological processes, cellular components, human disease gene terms, and cell types enriched in these gene expression patterns. We then used structural and functional neighbourhood analyses to assess whether the atrophy patterns in iRBD were constrained by the brain's structural and functional connectome. Moreover, we used comprehensive spatial mapping analyses to assess the specific neurotransmitter systems, functional networks, cytoarchitectonic classes, and cognitive brain systems associated with cortical changes in iRBD. All comparisons were tested against null models that preserved spatial autocorrelation between brain regions and compared to Alzheimer's disease to assess the specificity of findings to synucleinopathies. We found that genes involved in mitochondrial function and macroautophagy were the strongest contributors to the cortical thinning occurring in iRBD. Moreover, we demonstrated that cortical thinning was constrained by the brain's structural and functional connectome and that it mapped onto specific networks involved in motor and planning functions. In contrast with cortical thickness, changes in cortical surface area were related to distinct genes, namely genes involved in the inflammatory response, and to different spatial mapping patterns. The gene expression and connectivity patterns associated with iRBD were all distinct from those observed in Alzheimer's disease. In summary, this study demonstrates that the development of brain atrophy in synucleinopathies is constrained by specific genes and networks.

Brain morphometry in older adults with and without dementia using extremely rapid structural scans

T1-weighted structural MRI is widely used to measure brain morphometry (e.g., cortical thickness and subcortical volumes). Accelerated scans as fast as one minute or less are now available but it is unclear if they are adequate for quantitative morphometry. Here we compared the measurement properties of a widely adopted 1.0 mm resolution scan from the Alzheimer's Disease Neuroimaging Initiative (ADNI = 5'12'') with two variants of highly accelerated 1.0 mm scans (compressed-sensing, CSx6 = 1'12''; and wave-controlled aliasing in parallel imaging, WAVEx9 = 1'09'') in a test-retest study of 37 older adults aged 54 to 86 (including 19 individuals diagnosed with a neurodegenerative dementia). Rapid scans produced highly reliable morphometric measures that largely matched the quality of morphometrics derived from the ADNI scan. Regions of lower reliability and relative divergence between ADNI and rapid scan alternatives tended to occur in midline regions and regions with susceptibility-induced artifacts. Critically, the rapid scans yielded morphometric measures similar to the ADNI scan in regions of high atrophy. The results converge to suggest that, for many current uses, extremely rapid scans can replace longer scans. As a final test, we explored the possibility of a 0'49'' 1.2 mm CSx6 structural scan, which also showed promise. Rapid structural scans may benefit MRI studies by shortening the scan session and reducing cost, minimizing opportunity for movement, creating room for additional scan sequences, and allowing for the repetition of structural scans to increase precision of the estimates.

Association between childhood maltreatment and cortical folding in women with eating disorders

Childhood maltreatment (CM) is associated with distinct clinical and biological characteristics in people with eating disorders (EDs). The measurement of local gyrification index (lGI) may help to better characterize the impact of CM on cortical structure. Thus, the present study investigated the association of CM with lGI in women with EDs. Twenty-six women with anorexia nervosa (AN) and 24 with bulimia nervosa (BN) underwent a 3T MRI scan. All participants filled in the Childhood Trauma Questionnaire. All neuroimaging data were processed by FreeSurfer. LGI maps underwent a general linear model to evaluate differences between groups with or without CM. People with AN and BN were merged together. Based on the Childhood Trauma Questionnaire cutoff scores, 24 participants were identified as maltreated and 26 as non-maltreated. Maltreated people with EDs showed a significantly lower lGI in the left middle temporal gyrus compared with non-maltreated people, whereas no differences emerged in the right hemisphere between groups. The present study showed that in people with EDs, CM is associated with reduced cortical folding in the left middle temporal gyrus, an area that could be involved in ED psychopathology. This finding corroborates the hypothesis of a 'maltreated ecophenotype', which argues that CM may allow to biologically, other than clinically, distinguish individuals with the same psychiatric disorder.

Network anatomy in logopenic variant of primary progressive aphasia

The logopenic variant of primary progressive aphasia (lvPPA) is a neurodegenerative syndrome characterized linguistically by gradual loss of repetition and naming skills resulting from left posterior temporal and inferior parietal atrophy. Here, we sought to identify which specific cortical loci are initially targeted by the disease (epicenters) and investigate whether atrophy spreads through predetermined networks. First, we used cross-sectional structural MRI data from individuals with lvPPA to define putative disease epicenters using a surface-based approach paired with an anatomically fine-grained parcellation of the cortical surface (i.e., HCP-MMP1.0 atlas). Second, we combined cross-sectional functional MRI data from healthy controls and longitudinal structural MRI data from individuals with lvPPA to derive the epicenter-seeded resting-state networks most relevant to lvPPA symptomatology and ascertain whether functional connectivity in these networks predicts longitudinal atrophy spread in lvPPA. Our results show that two partially distinct brain networks anchored to the left anterior angular and posterior superior temporal gyri epicenters were preferentially associated with sentence repetition and naming skills in lvPPA. Critically, the strength of connectivity within these two networks in the neurologically-intact brain significantly predicted longitudinal atrophy progression in lvPPA. Taken together, our findings indicate that atrophy progression in lvPPA, starting from inferior parietal and temporoparietal junction regions, predominantly follows at least two partially nonoverlapping pathways, which may influence the heterogeneity in clinical presentation and prognosis.

Cortical and subcortical brain morphometry abnormalities in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia

Neuroimaging studies have documented morphometric brain abnormalities in schizophrenia, but less is known about them in individuals at clinical high-risk for psychosis (CHR-P), including how they compare with those observed in early schizophrenia (ESZ). Accordingly, we implemented multivariate profile analysis of regional morphometric profiles in CHR-P (n = 89), ESZ (n = 93) and healthy controls (HC; n = 122). ESZ profiles differed from HC and CHR-P profiles, including 1) cortical thickness: significant level reduction and regional non-parallelism reflecting widespread thinning, except for entorhinal and pericalcarine cortex, 2) basal ganglia volume: significant level increase and regional non-parallelism reflecting larger caudate and pallidum, and 3) ventricular volume: significant level increase with parallel regional profiles. CHR-P and ESZ cerebellar profiles showed significant non-parallelism with HC profiles. Regional profiles did not significantly differ between groups for cortical surface area or subcortical volume. Compared to CHR-P followed for ≥18 months without psychosis conversion (n = 31), CHR-P converters (n = 17) showed significant non-parallel ventricular volume expansion reflecting specific enlargement of lateral and inferolateral regions. Antipsychotic dosage in ESZ was significantly correlated with frontal cortical thinning. Results suggest that morphometric abnormalities in ESZ are not present in CHR-P, except for ventricular enlargement, which was evident in CHR-P who developed psychosis.

Relationship between function and structure in the visual cortex in healthy individuals and in patients with severe mental disorders

Patients with schizophrenia spectrum disorders (SCZ_spect) and bipolar disorders (BD) show impaired function in the primary visual cortex (V1), indicated by altered visual evoked potential (VEP). While the neural substrate for altered VEP in these patients remains elusive, altered V1 structure may play a role. One previous study found a positive relationship between the amplitude of the P100 component of the VEP and V1 surface area, but not V1 thickness, in a small sample of healthy individuals. Here, we aimed to replicate these findings in a larger healthy control (HC) sample (n = 307) and to examine the same relationship in patients with SCZ_spect (n = 30) or BD (n = 45). We also compared the mean P100 amplitude, V1 surface area and V1 thickness between controls and patients and found no significant group differences. In HC only, we found a significant positive P100-V1 surface area association, while there were no significant P100-V1 thickness relationships in HC, SCZ_spect or BD. Together, our results confirm previous findings of a positive P100-V1 surface area association in HC, whereas larger patient samples are needed to further clarify the function-structure relationship in V1 in SCZ_spect and BD.

Adolescent brain development in girls with Turner syndrome

Turner syndrome (TS) is a common sex chromosome aneuploidy in females associated with various physical, cognitive, and socio-emotional phenotypes. However, few studies have examined TS-associated alterations in the development of cortical gray matter volume and the two components that comprise this measure-surface area and thickness. Moreover, the longitudinal direct (i.e., genetic) and indirect (i.e., hormonal) effects of X-monosomy on the brain are unclear. Brain structure was assessed in 61 girls with TS (11.3 ± 2.8 years) and 55 typically developing girls (10.8 ± 2.3 years) for up to 4 timepoints. Surface-based analyses of cortical gray matter volume, thickness, and surface area were conducted to examine the direct effects of X-monosomy present before pubertal onset and indirect hormonal effects of estrogen deficiency/X-monosomy emerging after pubertal onset. Longitudinal analyses revealed that, whereas typically developing girls exhibited normative declines in gray matter structure during adolescence, this pattern was reduced or inverted in TS. Further, girls with TS demonstrated smaller total surface area and larger average cortical thickness overall. Regionally, the TS group exhibited decreased volume and surface area in the pericalcarine, postcentral, and parietal regions relative to typically developing girls, as well as larger volume in the caudate, amygdala, and temporal lobe regions and increased thickness in parietal and temporal regions. Surface area alterations were predominant by age 8, while maturational differences in thickness emerged by age 10 or later. Taken together, these results suggest the involvement of both direct and indirect effects of X-chromosome haploinsufficiency on brain development in TS.

Structural neuroimaging phenotypes and associated molecular and genomic underpinnings in autism: a review

Autism has been associated with differences in the developmental trajectories of multiple neuroanatomical features, including cortical thickness, surface area, cortical volume, measures of gyrification, and the gray-white matter tissue contrast. These neuroimaging features have been proposed as intermediate phenotypes on the gradient from genomic variation to behavioral symptoms. Hence, examining what these proxy markers represent, i.e., disentangling their associated molecular and genomic underpinnings, could provide crucial insights into the etiology and pathophysiology of autism. In line with this, an increasing number of studies are exploring the association between neuroanatomical, cellular/molecular, and (epi)genetic variation in autism, both indirectly and directly in vivo and across age. In this review, we aim to summarize the existing literature in autism (and neurotypicals) to chart a putative pathway from (i) imaging-derived neuroanatomical cortical phenotypes to (ii) underlying (neuropathological) biological processes, and (iii) associated genomic variation.

Neutrophil-to-Lymphocyte Ratio Amplifies the Effects of Aging on Decrements in Grip Strength and Its Functional Neural Underpinnings

The neutrophil-to-lymphocyte ratio (NLR) is a trans-prognostic biomarker of physiologic stress and inflammation linked to muscle weakness in older adults. Generation of grip force coincides with sustained activity in the primary sensorimotor cortex (SM1). The current study investigates whether whole-brain functional connectivity, that is, degree centrality (CD) of SM1 relates to grip strength and whether both functional measures are predicted by advancing age as a function of the NLR. A structural regression model investigated the main and interactive effects of age and NLR on grip strength and CD of SM1 in 589 adults aged 21-85 years (M = 45.87, SD = 18.06). The model including the entire sample had a good fit (χ 2(4) = 1.63, p = .804). In individuals aged 50 years and older, age predicted lower grip strength and SM1 CD as a function of increasing NLR. In a model stratified by sex, the effect of age, NLR, and their interaction on grip strength are significant for older men but not older women. Analyses support CD of SM1 at rest as a neural biomarker of grip strength. Grip and its neural underpinnings decrease with advancing age and increasing NLR in mid to late life. Age-related decrements in grip strength and functional connectivity of brain regions involved in the generation of dynamic grip appear to be accelerated as a function of systemic physiological stress and inflammation, particularly in older men.

Different MRI structural processing methods do not impact functional connectivity computation

Resting-state functional magnetic resonance imaging (rs-fMRI) has become an increasingly popular technique. This technique can assess several features of brain connectivity, such as inter-regional temporal correlation (functional connectivity), from which graph measures of network organization can be derived. However, these measures are prone to a certain degree of variability depending on the analytical steps during preprocessing. Many studies have investigated the effect of different preprocessing steps on functional connectivity measures; however, no study investigated whether different structural reconstructions lead to different functional connectivity metrics. Here, we evaluated the impact of different structural segmentation strategies on functional connectivity outcomes. To this aim, we compared different metrics computed after two different registration strategies. The first strategy used structural information from the 3D T1-weighted image (unimodal), while the second strategy implemented a multimodal approach, where an additional registration step used the information from the T2-weighted image. The impact of these different approaches was evaluated on a sample of 58 healthy adults. As expected, different approaches led to significant differences in structural measures (i.e., cortical thickness, volume, and gyrification index), with the maximum impact on the insula cortex. However, these differences were only slightly translated to functional metrics. We reported no differences in graph measures and seed-based functional connectivity maps, but slight differences in the insula when we compared the mean functional strength for each parcel. Overall, these results suggested that functional metrics are only slightly different when using a unimodal compared to a multimodal approach, while the structural output can be significantly affected.

A comprehensive evaluation of multicentric reliability of single-subject cortical morphological networks on traveling subjects

Despite the prevalence of research on single-subject cerebral morphological networks in recent years, whether they can offer a reliable way for multicentric studies remains largely unknown. Using two multicentric datasets of traveling subjects, this work systematically examined the inter-site test-retest (TRT) reliabilities of single-subject cerebral morphological networks, and further evaluated the effects of several key factors. We found that most graph-based network measures exhibited fair to excellent reliabilities regardless of different analytical pipelines. Nevertheless, the reliabilities were affected by choices of morphological index (fractal dimension > sulcal depth > gyrification index > cortical thickness), brain parcellation (high-resolution > low-resolution), thresholding method (proportional > absolute), and network type (binarized > weighted). For the factor of similarity measure, its effects depended on the thresholding method used (absolute: Kullback-Leibler divergence > Jensen-Shannon divergence; proportional: Jensen-Shannon divergence > Kullback-Leibler divergence). Furthermore, longer data acquisition intervals and different scanner software versions significantly reduced the reliabilities. Finally, we showed that inter-site reliabilities were significantly lower than intra-site reliabilities for single-subject cerebral morphological networks. Altogether, our findings propose single-subject cerebral morphological networks as a promising approach for multicentric human connectome studies, and offer recommendations on how to determine analytical pipelines and scanning protocols for obtaining reliable results.

Network anatomy in logopenic variant of primary progressive aphasia

The logopenic variant of primary progressive aphasia (lvPPA) is a neurodegenerative syndrome characterized linguistically by gradual loss of repetition and naming skills, resulting from left posterior temporal and inferior parietal atrophy. Here, we sought to identify which specific cortical loci are initially targeted by the disease (epicenters) and investigate whether atrophy spreads through pre-determined networks. First, we used cross-sectional structural MRI data from individuals with lvPPA to define putative disease epicenters using a surface-based approach paired with an anatomically-fine-grained parcellation of the cortical surface (i.e., HCP-MMP1.0 atlas). Second, we combined cross-sectional functional MRI data from healthy controls and longitudinal structural MRI data from individuals with lvPPA to derive the epicenter-seeded resting-state networks most relevant to lvPPA symptomatology and ascertain whether functional connectivity in these networks predicts longitudinal atrophy spread in lvPPA. Our results show that two partially distinct brain networks anchored to the left anterior angular and posterior superior temporal gyri epicenters were preferentially associated with sentence repetition and naming skills in lvPPA. Critically, the strength of connectivity within these two networks in the neurologically-intact brain significantly predicted longitudinal atrophy progression in lvPPA. Taken together, our findings indicate that atrophy progression in lvPPA, starting from inferior parietal and temporo-parietal junction regions, predominantly follows at least two partially non-overlapping pathways, which may influence the heterogeneity in clinical presentation and prognosis.

Neuroanatomical Correlates of Emotion-Related Impulsivity

BACKGROUND

Emotion-related impulsivity (ERI) refers to chronically poor self-control during periods of strong emotion. ERI robustly predicts psychiatric disorders and related problems, yet its neuroanatomical correlates are largely unknown. We tested whether local brain morphometry in targeted brain regions that integrate emotion and control could explain ERI severity.

METHODS

One hundred twenty-two adults (ages 18-55 years) with internalizing or externalizing psychopathology completed a structural magnetic resonance imaging (MRI) scan, the Three-Factor Impulsivity Index, and the Structured Clinical Interview for DSM-5. The Three-Factor Impulsivity Index measures two types of ERI and a third type of impulsivity not linked to emotion. Cortical reconstruction yielded cortical thickness and local gyrification measurements. We evaluated whether morphometry in the orbitofrontal cortex (OFC), insula, amygdala, and nucleus accumbens was associated with ERI severity. Hypotheses and analyses were preregistered.

RESULTS

Lower cortical gyrification in the right lateral OFC was associated with high ERI severity in a full, preregistered model. Separate examinations of local gyrification and cortical thickness also showed a positive association between gyrification in the left lateral OFC and ERI. An integrated measure of hemispheric imbalance in lateral OFC gyrification (right < left) correlated with ERI severity. These findings were specific to ERI and did not appear with non-emotion-related impulsivity.

CONCLUSIONS

Local gyrification in the lateral OFC is associated with ERI severity. The current findings fit with existing theories of OFC function, strengthen the connections between the transdiagnostic literature in psychiatry and neuroscience, and may guide future treatment development.

Increased cortical surface area but not altered cortical thickness or gyrification in bipolar disorder following stabilisation from a first episode of mania

BACKGROUND

Despite reports of altered brain morphology in established bipolar disorder (BD), there is limited understanding of when these morphological abnormalities emerge. Assessment of patients during the early course of illness can help to address this gap, but few studies have examined surface-based brain morphology in patients at this illness stage.

METHODS

We completed a secondary analysis of baseline data from a randomised control trial of BD individuals stabilised after their first episode of mania (FEM). The magnetic resonance imaging scans of n = 35 FEM patients and n = 29 age-matched healthy controls were analysed. Group differences in cortical thickness, surface area and gyrification were assessed at each vertex of the cortical surface using general linear models. Significant results were identified at p < 0.05 using cluster-wise correction.

RESULTS

The FEM group did not differ from healthy controls with regards to cortical thickness or gyrification. However, there were two clusters of increased surface area in the left hemisphere of FEM patients, with peak coordinates falling within the lateral occipital cortex and pars triangularis.

CONCLUSIONS

Cortical thickness and gyrification appear to be intact in the aftermath of a first manic episode, whilst cortical surface area in the inferior/middle prefrontal and occipitoparietal cortex is increased compared to age-matched controls. It is possible that increased surface area in the FEM group is the outcome of abnormalities in a premorbidly occurring process. In contrast, the findings raise the hypothesis that cortical thickness reductions seen in past studies of individuals with more established BD may be more attributable to post-onset factors.

No signs of neurodegenerative effects in 15q11.2 BP1-BP2 copy number variant carriers in the UK Biobank

The 15q11.2 BP1-BP2 copy number variant (CNV) is associated with altered brain morphology and risk for atypical development, including increased risk for schizophrenia and learning difficulties for the deletion. However, it is still unclear whether differences in brain morphology are associated with neurodevelopmental or neurodegenerative processes. This study derived morphological brain MRI measures in 15q11.2 BP1-BP2 deletion (n = 124) and duplication carriers (n = 142), and matched deletion-controls (n = 496) and duplication-controls (n = 568) from the UK Biobank study to investigate the association with brain morphology and estimates of brain ageing. Further, we examined the ageing trajectory of age-affected measures (i.e., cortical thickness, surface area, subcortical volume, reaction time, hand grip strength, lung function, and blood pressure) in 15q11.2 BP1-BP2 CNV carriers compared to non-carriers. In this ageing population, the results from the machine learning models showed that the estimated brain age gaps did not differ between the 15q11.2 BP1-BP2 CNV carriers and non-carriers, despite deletion carriers displaying thicker cortex and lower subcortical volume compared to the deletion-controls and duplication carriers, and lower surface area compared to the deletion-controls. Likewise, the 15q11.2 BP1-BP2 CNV carriers did not deviate from the ageing trajectory on any of the age-affected measures examined compared to non-carriers. Despite altered brain morphology in 15q11.2 BP1-BP2 CNV carriers, the results did not show any clear signs of apparent altered ageing in brain structure, nor in motor, lung or heart function. The results do not indicate neurodegenerative effects in 15q11.2 BP1-BP2 CNV carriers.

The structural basis of age-related decline in global motion perception at fast and slow speeds

A decrease in global motion perception (GMP) has been reported in older adults, and this age-related decline in GMP varies with the speed of global motion. However, no studies have investigated whether the asynchronous age-related decline in GMP is related to degenerative changes in brain structure. In this study, the random dot kinematogram paradigm and structural magnetic resonance imaging were used to investigate the asynchronous aging of GMP at fast and slow speeds (called fast GMP and slow GMP, respectively) and their relationships with brain structure. Ninety-four older adults (65.74 ± 4.50 yrs) and 90 younger adults (22.83 ± 4.84 yrs) participated in the experiment. The results showed that older adults had higher motion coherence thresholds (MCT) than younger adults at both fast and slow speeds. Brain-behavior correlation analyses of younger adults revealed that none of the correlations between morphological measures and MCTs survived correction for multiple comparisons. For older adults, slow MCT was correlated with cortical thickness in the bilateral V4v, V5/MT+, left V7, V8, LO, and surface area in the right V7. Fast MCT was significantly correlated with gray matter volume in the right V7 and thickness in the left V5/MT+. These results support the view that global motion extraction occurs within two speed-tuned systems that are at least partially independent in terms of their neural substrates, which deteriorate with age at different speeds. Aging of GMP is also associated with morphological changes in the visual cortex. Age-related cerebral atrophy in the dorsal stream may impair both fast and slow GMP, whereas aging of the ventral stream specifically impairs slow GMP.

A correlational study between microstructural, macrostructural and functional age-related changes in the human visual cortex

Age-related changes in the human brain can be investigated from either structural or functional perspectives. Analysis of structural and functional age-related changes throughout the lifespan may help to understand the normal brain development process and monitor the structural and functional pathology of the brain. This study, combining dedicated electroencephalography (EEG) and magnetic resonance imaging (MRI) approaches in adults (20-78 years), highlights the complex relationship between micro/macrostructural properties and the functional responses to visual stimuli. Here, we aimed to relate age-related changes of the latency of visual evoked potentials (VEPs) to micro/macrostructural indexes and find any correlation between micro/macrostructural features, as well. We studied age-related structural changes in the brain, by using the MRI and diffusion-weighted imaging (DWI) as preferred imaging methods for extracting brain macrostructural parameters such as the cortical thickness, surface area, folding and curvature index, gray matter volume, and microstructural parameters such as mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). All the mentioned features were significantly correlated with age in V1 and V2 regions of the visual cortex. Furthermore, we highlighted, negative correlations between structural features extracted from T1-weighted images and DWI. The latency and amplitude of the three dominants peaks (C1, P1, N1) of the VEP were considered as the brain functional features to be examined for correlation with age and structural features of the corresponding age. We observed significant correlations between mean C1 latency and GM volume averaged in V1 and V2. In hierarchical regression analysis, the structural index did not contribute to significant variance in the C1 latency after regressing out the effect of age. However, the age explained significant variance in the model after regressing out the effect of structural feature.

Exploring the heterogeneous morphometric data in essential tremor with probabilistic modelling

Essential tremor (ET) is a prevalent movement disorder characterized by marked clinical heterogeneity. Here, we explored the morphometric underpinnings of this cross-subject variability on a cohort of 34 patients with right-dominant drug-resistant ET and 29 matched healthy controls (HCs). For each brain region, group-wise morphometric data was modelled by a multivariate Gaussian to account for morphometric features' (co)variance. No group differences were found in terms of mean values, highlighting the limits of more basic group comparison approaches. Variance in surface area was higher in ET in the left lingual and caudal anterior cingulate cortices, while variance in mean curvature was lower in the right superior temporal cortex and pars triangularis, left supramarginal gyrus and bilateral paracentral gyrus. Heterogeneity further extended to the right putamen, for which a mixture of two Gaussians fitted the ET data better than a single one. Partial Least Squares analysis revealed the rich clinical relevance of the ET population's heterogeneity: first, increased head tremor and longer symptoms' duration were accompanied by broadly lower cortical gyrification. Second, more severe upper limb tremor and impairments in daily life activities characterized the patients whose morphometric profiles were more atypical compared to the average ET population, irrespective of the exact nature of the alterations. Our results provide candidate morphometric substrates for two different types of clinical variability in ET. They also demonstrate the importance of relying on analytical approaches that can efficiently handle multivariate data and enable to test more sophisticated hypotheses regarding its organization.

Motor symptoms in Parkinson's disease are related to the interplay between cortical curvature and thickness

INTRODUCTION

Brain atrophy in Parkinson's disease occurs to varying degrees in different brain regions, even at the early stage of the disease. While cortical morphological features are often considered independently in structural brain imaging studies, research on the co-progression of different cortical morphological measurements could provide new insights regarding the progression of PD. This study's aim was to examine the interplay between cortical curvature and thickness as a function of PD diagnosis, motor symptoms, and cognitive performance.

METHODS

A total of 359 de novo PD patients and 159 healthy controls (HC) from the Parkinson's Progression Markers Initiative (PPMI) database were included in this study. Additionally, an independent cohort from four databases (182 PD, 132 HC) with longer disease durations was included to assess the effects of PD diagnosis in more advanced cases. Pearson correlation was used to determine subject-specific associations between cortical curvature and thickness estimated from T1-weighted MRI images. General linear modeling (GLM) was then used to assess the effect of PD diagnosis, motor symptoms, and cognitive performance on the curvature-thickness association. Next, longitudinal changes in the curvature-thickness correlation as well as the predictive effect of the cortical curvature-thickness association on changes in motor symptoms and cognitive performance across four years were investigated. Finally, Akaike information criterion (AIC) was used to build a GLM to model PD motor symptom severity cross-sectionally.

RESULTS

A significant interaction effect between PD motor symptoms and age on the curvature-thickness correlation was found (β_standardized = 0.11; t(350) = 2.12; p = 0.03). This interaction effect showed that motor symptoms in older patients were related to an attenuated curvature-thickness association. No significant effect of PD diagnosis was observed for the PPMI database (β = 0.03; t(510) = 0.35; p = 0.72). However, in patients with a longer disease duration, a significant effect of diagnosis on the curvature-thickness association was found (β_standardized = 0.31; t(306.7) = 3.49; p = 0.0006). Moreover, rigidity, but not tremor, in PD was significantly related to the curvature-thickness correlation (β_standardized = 0.11, t(350) = 2.24, p = 0.03; β_standardized = -0.03, t(350) = -0.58, p = 0.56, respectively). The curvature-thickness association was attenuated over time in both PD and HC, but the two groups did not show a significantly different effect (β_standardized = 0.03, t(184.7) = 0.78, p = 0.44). No predictive effects of the CC-CT correlation on longitudinal changes in cognitive performance or motor symptoms were observed (all p-values > 0.05). The best cross-sectional model for PD motor symptoms included the curvature-thickness correlation, cognitive performance, and putamen dopamine transporter (DAT) binding, which together explained 14 % of variance.

CONCLUSION

The association between cortical curvature and thickness is related to PD motor symptoms and age. This research shows the potential of modeling the curvature-thickness interplay in PD.

Assessment of Characteristics of Imaging Biomarkers for Quantifying Anterior Cingulate Cortex Changes: A Twin Study of Middle- to Advanced-Aged Populations in East Asia

Background and Objectives: Our aim was to assess genetic and environmental effects on surface morphological parameters for quantifying anterior cingulate cortex (ACC) changes in middle- to advanced-age East Asians using twin analysis. Materials and Methods: Normal twins over 39 years old comprising 37 monozygotic pairs and 17 dizygotic pairs underwent 3-dimensional (3D) T1-weighted imaging of the brain at 3T. Freesurfer-derived ACC parameters including thickness, standard deviation of thickness (STDthickness), volume, surface area, and sulcal morphological parameters (folding, mean, and Gaussian curvatures) were calculated from 3D T1-weighted volume images. Twin analysis with a model involving phenotype variance components of additive genetic effects (A), common environmental effects (C), and unique environmental effects (E) was performed to assess the magnitude of each genetic and environmental influence on parameters. Results: Most parameters fit best with an AE model. Both thickness (A: left 0.73/right 0.71) and surface area (A: left 0.63/right 0.71) were highly heritable. STDthickness was low to moderately heritable (A: left 0.48/right 0.29). Volume was moderately heritable (A: left 0.37). Folding was low to moderately heritable (A: left 0.44/right 0.28). Mean curvature (A: left 0.37/right 0.65) and Gaussian curvature (A: right 0.79) were moderately to highly heritable. Right volume and left Gaussian curvature fit best with a CE model, indicating a relatively weak contribution of genetic factors to these parameters. Conclusions: When assessing ACC changes in middle- to advanced-age East Asians, one must keep in mind that thickness and surface area appear to be strongly affected by genetic factors, whereas sulcal morphological parameters tend to involve environmental factors.

The effects of epigenetic age and its acceleration on surface area, cortical thickness, and volume in young adults

DNA methylation age has been used in recent studies as an epigenetic marker of accelerated cellular aging, whose contribution to the brain structural changes was lately acknowledged. We aimed to characterize the association of epigenetic age (i.e. estimated DNA methylation age) and its acceleration with surface area, cortical thickness, and volume in healthy young adults. Using the multi-tissue method (Horvath S. DNA methylation age of human tissues and cell types. 2013. Genome Biol 14), epigenetic age was computed with saliva sample. Epigenetic age acceleration was derived from residuals after adjusting epigenetic age for chronological age. Multiple regression models were computed for 148 brain regions for surface area, cortical thickness, and volume using epigenetic age or accelerated epigenetic age as a predictor and controlling for sex. Epigenetic age was associated with surface area reduction of the left insula. It was also associated with cortical thinning and volume reduction in multiple regions, with prominent changes of cortical thickness in the left temporal regions and of volume in the bilateral orbital gyri. Finally, accelerated epigenetic age was negatively associated with right cuneus gyrus volume. Our findings suggest that understanding the mechanisms of epigenetic age acceleration in young individuals may yield valuable insights into the relationship between epigenetic aging and the cortical change and on the early development of neurocognitive pathology among young adults.