Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex

Choroid plexus volume is increased in mood disorders and associates with circulating inflammatory cytokines

Depressed patients exhibit altered levels of immune-inflammatory markers both in the peripheral blood and in the cerebrospinal fluid (CSF) and inflammatory processes have been widely implicated in the pathophysiology of mood disorders. The Choroid Plexus (ChP), located at the base of each of the four brain ventricles, regulates the exchange of substances between the blood and CSF and several evidence supported a key role for ChP as a neuro-immunological interface between the brain and circulating immune cells. Given the role of ChP as a regulatory gate between periphery, CSF spaces and the brain, we compared ChP volumes in patients with bipolar disorder (BP) or major depressive disorder (MDD) and healthy controls, exploring their association with history of illness and levels of circulating cytokines. Plasma levels of inflammatory markers and MRI scans were acquired for 73 MDD, 79 BD and 72 age- and sex-matched healthy controls (HC). Patients with either BD or MDD had higher ChP volumes than HC. With increasing age, the bilateral ChP volume was larger in patients, an effect driven by the duration of illness; while only minor effects were observed in HC. Right ChP volumes were proportional to higher levels of circulating cytokines in the clinical groups, including IFN-γ, IL-13 and IL-17. Specific effects in the two diagnostic groups were observed when considering the left ChP, with positive association with IL-1ra, IL-13, IL-17, and CCL3 in BD, and negative associations with IL-2, IL-4, IL-1ra, and IFN-γ in MDD. These results suggest that ChP could represent a reliable and easy-to-assess biomarker to evaluate the brain effects of inflammatory status in mood disorders, contributing to personalized diagnosis and tailored treatment strategies.

Does Ipsilateral Remapping Following Hand Loss Impact Motor Control of the Intact Hand?

What happens once a cortical territory becomes functionally redundant? We studied changes in brain function and behavior for the remaining hand in humans (male and female) with either a missing hand from birth (one-handers) or due to amputation. Previous studies reported that amputees, but not one-handers, show increased ipsilateral activity in the somatosensory territory of the missing hand (i.e., remapping). We used a complex finger task to explore whether this observed remapping in amputees involves recruiting more neural resources to support the intact hand to meet greater motor control demands. Using basic fMRI analysis, we found that only amputees had more ipsilateral activity when motor demand increased; however, this did not match any noticeable improvement in their behavioral task performance. More advanced multivariate fMRI analyses showed that amputees had stronger and more typical representation-relative to controls' contralateral hand representation-compared with one-handers. This suggests that in amputees, both hand areas work together more collaboratively, potentially reflecting the intact hand's efference copy. One-handers struggled to learn difficult finger configurations, but this did not translate to differences in univariate or multivariate activity relative to controls. Additional white matter analysis provided conclusive evidence that the structural connectivity between the two hand areas did not vary across groups. Together, our results suggest that enhanced activity in the missing hand territory may not reflect intact hand function. Instead, we suggest that plasticity is more restricted than generally assumed and may depend on the availability of homologous pathways acquired early in life.

Early life stress modulates the genetic influence on brain structure and cognitive function in children

The enduring influence of early life stress (ELS) on brain and cognitive development has been widely acknowledged, yet the precise mechanisms underlying this association remain elusive. We hypothesize that ELS might disrupt the genome-wide influence on brain morphology and connectivity development, consequently exerting a detrimental impact on children's cognitive ability. We analyzed the multimodal data of DNA genotypes, brain imaging (structural and diffusion MRI), and neurocognitive battery (NIH Toolbox) of 4276 children (ages 9-10 years, European ancestry) from the Adolescent Brain Cognitive Development (ABCD) study. The genome-wide influence on cognitive function was estimated using the polygenic score (GPS). By using brain morphometry and tractography, we identified the brain correlates of the cognition GPSs. Statistical analyses revealed relationships for the gene-brain-cognition pathway. The brain structural variance significantly mediated the genetic influence on cognition (indirect effect = 0.016, PFDR < 0.001). Of note, this gene-brain relationship was significantly modulated by abuse, resulting in diminished cognitive capacity (Index of Moderated Mediation = -0.007; 95 % CI = -0.012 ∼ -0.002). Our results support a novel gene-brain-cognition model likely elucidating the long-lasting negative impact of ELS on children's cognitive development.

Sex- and age-based differences in fetal and early childhood hippocampus maturation: a cross-sectional and longitudinal analysis

The hippocampus, essential for cognitive and affective processes, develops exponentially with differential trajectories seen in girls and boys, yet less is known about its development during early fetal life until early childhood. In a cross-sectional and longitudinal study, we examined the sex-, age-, and laterality-related developmental trajectories of hippocampal volumes in fetuses, infants, and toddlers associated with age. Third trimester fetuses (27-38 weeks' gestational age), newborns (0-4 weeks' postnatal age), infants (5-50 weeks' postnatal age), and toddlers (2-3 years postnatal age) were scanned with magnetic resonance imaging. A total of 133 datasets (62 female, postmenstrual age [weeks] M = 69.38, SD = 51.39, range = 27.6-195.3) were processed using semiautomatic segmentation methods. Hippocampal volumes increased exponentially during the third trimester and the first year of life, beginning to slow at approximately 2 years. Overall, boys had larger hippocampal volumes than girls. Lateralization differences were evident, with left hippocampal growth beginning to plateau sooner than the right. This period of rapid growth from the third trimester, continuing through the first year of life, may support the development of cognitive and affective function during this period.

Traveling waves shape neural population dynamics enabling predictions and internal model updating

The brain generates predictions based on statistical regularities in our environment. However, it is unclear how predictions are optimized through iterative interactions with the environment. Because traveling waves (TWs) propagate across the cortex shaping neural excitability, they can carry information to serve predictive processing. Using human intracranial recordings, we show that anterior-to-posterior alpha TWs correlated with prediction strength. Learning about priors altered neural state space trajectories, and how much it altered correlated with trial-by-trial prediction strength. Learning involved mismatches between predictions and sensory evidence triggering alpha-phase resets in lateral temporal cortex, accompanied by stronger alpha phase-high gamma amplitude coupling and high-gamma power. The mismatch initiated posterior-to-anterior alpha TWs and change in the subsequent trial's state space trajectory, facilitating model updating. Our findings suggest a vital role of alpha TWs carrying both predictions to sensory cortex and mismatch signals to frontal cortex for trial-by-trial fine-tuning of predictive models.

Noninvasive Gamma Sensory Stimulation May Reduce White Matter and Myelin Loss in Alzheimer's Disease

BACKGROUND

Patients with Alzheimer's disease (AD) demonstrate progressive white matter atrophy and myelin loss. Restoring myelin content or preventing demyelination has been suggested as a therapeutic approach for AD.

OBJECTIVE

Herein, we investigate the effects of non-invasive, combined visual and auditory gamma-sensory stimulation on white matter atrophy and myelin content loss in patients with AD.

METHODS

In this study, we used the magnetic resonance imaging (MRI) data from the OVERTURE study (NCT03556280), a randomized, controlled, clinical trial in which active treatment participants received daily, non-invasive, combined visual and auditory, 40 Hz stimulation for six months. A subset of OVERTURE participants who meet the inclusion criteria for detailed white matter (N = 38) and myelin content (N = 36) assessments are included in the analysis. White matter volume assessments were performed using T1-weighted MRI, and myelin content assessments were performed using T1-weighted/T2-weighted MRI. Treatment effects on white matter atrophy and myelin content loss were assessed.

RESULTS

Combined visual and auditory gamma-sensory stimulation treatment is associated with reduced total and regional white matter atrophy and myelin content loss in active treatment participants compared to sham treatment participants. Across white matter structures evaluated, the most significant changes were observed in the entorhinal region.

CONCLUSIONS

The study results suggest that combined visual and auditory gamma-sensory stimulation may modulate neuronal network function in AD in part by reducing white matter atrophy and myelin content loss. Furthermore, the entorhinal region MRI outcomes may have significant implications for early disease intervention, considering the crucial afferent connections to the hippocampus and entorhinal cortex.

Type 2 Diabetes and Biomarkers of Brain Structure, Perfusion, Metabolism, and Function in Late Mid-Life: A Multimodal Discordant Twin Study

BACKGROUND

Type 2 diabetes (T2D) is associated with an increased risk of dementia and early features may become evident even in mid-life. Characterizing these early features comprehensively requires multiple measurement modalities and careful selection of participants with and without T2D.

OBJECTIVE

We conducted a cross-sectional multimodal imaging study of T2D-discordant twins in late mid-life to provide insights into underlying mechanisms.

METHODS

Measurements included computerized cognitive battery, brain MRI (including arterial spin labelling, diffusion tensor, resting state functional), fluorodeoxyglucose (FDG)-PET, and retinal optical coherence tomography.

RESULTS

There were 23 pairs, mean age 63.7 (±6.1) years. In global analyses, T2D was associated with poorer attention (β= -0.45, p <0.001) and with reduced FDG uptake (β= -5.04, p = 0.02), but not with cortical thickness (p = 0.71), total brain volume (p = 0.51), fractional anisotropy (p = 0.15), mean diffusivity (p = 0.34), or resting state activity (p = 0.4). Higher FDG uptake was associated with better attention (β= 3.19, p = 0.01) but not with other cognitive domains. In regional analyses, T2D was associated with lower accumbens volume (β= -44, p = 0.0004) which was in turn associated with poorer attention.

CONCLUSION

T2D-related brain dysfunction in mid-life manifests as attentional loss accompanied by evidence of subtle neurodegeneration and global reduction in cerebral metabolism, in the absence of overt cerebrovascular disease.

Connectome-wide structure-function coupling models implicate polysynaptic alterations in autism

Autism spectrum disorder (ASD) is one of the most common neurodevelopmental diagnoses. Although incompletely understood, structural and functional network alterations are increasingly recognized to be at the core of the condition. We utilized multimodal imaging and connectivity modeling to study structure-function coupling in ASD and probed mono- and polysynaptic mechanisms on structurally-governed network function. We examined multimodal magnetic resonance imaging data in 80 ASD and 61 neurotypical controls from the Autism Brain Imaging Data Exchange (ABIDE) II initiative. We predicted intrinsic functional connectivity from structural connectivity data in each participant using a Riemannian optimization procedure that varies the times that simulated signals can unfold along tractography-derived personalized connectomes. In both ASD and neurotypical controls, we observed improved structure-function prediction at longer diffusion time scales, indicating better modeling of brain function when polysynaptic mechanisms are accounted for. Prediction accuracy differences (∆prediction accuracy) were marked in transmodal association systems, such as the default mode network, in both neurotypical controls and ASD. Differences were, however, lower in ASD in a polysynaptic regime at higher simulated diffusion times. We compared regional differences in ∆prediction accuracy between both groups to assess the impact of polysynaptic communication on structure-function coupling. This analysis revealed that between-group differences in ∆prediction accuracy followed a sensory-to-transmodal cortical hierarchy, with an increased gap between controls and ASD in transmodal compared to sensory/motor systems. Multivariate associative techniques revealed that structure-function differences reflected inter-individual differences in autistic symptoms and verbal as well as non-verbal intelligence. Our network modeling approach sheds light on atypical structure-function coupling in autism, and suggests that polysynaptic network mechanisms are implicated in the condition and that these can help explain its wide range of associated symptoms.

Using Generative Artificial Intelligence to Classify Primary Progressive Aphasia from Connected Speech

Neurodegenerative dementia syndromes, such as Primary Progressive Aphasias (PPA), have traditionally been diagnosed based in part on verbal and nonverbal cognitive profiles. Debate continues about whether PPA is best subdivided into three variants and also regarding the most distinctive linguistic features for classifying PPA variants. In this study, we harnessed the capabilities of artificial intelligence (AI) and natural language processing (NLP) to first perform unsupervised classification of concise, connected speech samples from 78 PPA patients. Large Language Models discerned three distinct PPA clusters, with 88.5% agreement with independent clinical diagnoses. Patterns of cortical atrophy of three data-driven clusters corresponded to the localization in the clinical diagnostic criteria. We then used NLP to identify linguistic features that best dissociate the three PPA variants. Seventeen features emerged as most valuable for this purpose, including the observation that separating verbs into high and low-frequency types significantly improves classification accuracy. Using these linguistic features derived from the analysis of brief connected speech samples, we developed a classifier that achieved 97.9% accuracy in predicting PPA subtypes and healthy controls. Our findings provide pivotal insights for refining early-stage dementia diagnosis, deepening our understanding of the characteristics of these neurodegenerative phenotypes and the neurobiology of language processing, and enhancing diagnostic evaluation accuracy.

Higher Levels of C-reactive Protein Are Associated With Higher Cortical Surface Area and Lower Cortical Thickness in Youth With Bipolar Disorder

BACKGROUND

Inflammation is implicated in the neuropathology of bipolar disorder (BD). The association of C-reactive protein (CRP) with brain structure has been examined in relation to BD among adults but not youth.

METHODS

Participants included 101 youth (BD, n = 55; control group [CG], n = 46; aged 13-20 years). Blood samples were assayed for levels of CRP. T1-weighted brain images were acquired to obtain cortical surface area (SA), volume, and thickness for 3 regions of interest (ROI; whole-brain cortical gray matter, prefrontal cortex, orbitofrontal cortex [OFC]) and for vertex-wise analyses. Analyses included CRP main effects and interaction effects controlling for age, sex, and intracranial volume.

RESULTS

In ROI analyses, higher CRP was associated with higher whole-brain SA (β = 0.16; P = .03) and lower whole-brain (β = -0.31; P = .03) and OFC cortical thickness (β = -0.29; P = .04) within the BD group and was associated with higher OFC SA (β = 0.17; P = .03) within the CG. In vertex-wise analyses, higher CRP was associated with higher SA and lower cortical thickness in frontal and parietal regions within BD. A significant CRP-by-diagnosis interaction was found in frontal and temporal regions, whereby higher CRP was associated with lower neurostructural metrics in the BD group but higher neurostructural metrics in CG.

CONCLUSIONS

This study found that higher CRP among youth with BD is associated with higher SA but lower cortical thickness in ROI and vertex-wise analyses. The study identified 2 regions in which the association of CRP with brain structure differs between youth with BD and the CG. Future longitudinal, repeated-measures studies incorporating additional inflammatory markers are warranted.

CBLL1 is hypomethylated and correlates with cortical thickness in transgender men before gender affirming hormone treatment

Gender identity refers to the consciousness of being a man, a woman or other condition. Although it is generally congruent with the sex assigned at birth, for some people it is not. If the incongruity is distressing, it is defined as gender dysphoria (GD). Here, we measured whole-genome DNA methylation by the Illumina © Infinium Human Methylation 850k array and reported its correlation with cortical thickness (CTh) in 22 transgender men (TM) experiencing GD versus 25 cisgender men (CM) and 28 cisgender women (CW). With respect to the methylation analysis, TM vs. CW showed significant differences in 35 CpGs, while 2155 CpGs were found when TM vs. CM were compared. With respect to correlation analysis, TM showed differences in methylation of CBLL1 and DLG1 genes that correlated with global and left hemisphere CTh. Both genes were hypomethylated in TM compared to the cisgender groups. Early onset TM showed a positive correlation between CBLL1 and several cortical regions in the frontal (left caudal middle frontal), temporal (right inferior temporal, left fusiform) and parietal cortices (left supramarginal and right paracentral). This is the first study relating CBLL1 methylation with CTh in transgender persons and supports a neurodevelopmental hypothesis of gender identity.

Early emotional caregiving environment and associations with memory performance and hippocampal volume in adolescents with prenatal drug exposure

Early adversities, including prenatal drug exposure (PDE) and a negative postnatal emotional caregiving environment, impact children's long-term development. The protracted developmental course of memory and its underlying neural systems offer a valuable framework for understanding the longitudinal associations of pre- and postnatal factors on children with PDE. This study longitudinally examines memory and hippocampal development in 69 parent-child dyads to investigate how the early caregiving emotional environment affects children with PDE's neural and cognitive systems. Measures of physical health, drug exposure, caregiver stress, depression, and distress were collected between 0 and 24 months At age 14 years, adolescents completed multiple measures of episodic memory, and at ages 14 and 18 years, adolescents underwent magnetic resonance imaging (MRI) scans. Latent constructs of episodic memory and the caregiving environment were created using Confirmatory Factor Analysis. Multiple regressions revealed a negative emotional caregiving environment during infancy was associated with poor memory performance and smaller left hippocampal volumes at 14 years. Better memory performance at 14 years predicted larger right hippocampal volume at 18 years. At 18 years, the association between the emotional caregiving environment and hippocampal volume was moderated by sex, such that a negative emotional caregiving environment was associated with larger left hippocampal volumes in males but not females. Findings suggest that the postnatal caregiving environment may modulate the effects of PDE across development, influencing neurocognitive development.

Functional brain networks are associated with both sex and gender in children

Sex and gender are associated with human behavior throughout the lifespan and across health and disease, but whether they are associated with similar or distinct neural phenotypes is unknown. Here, we demonstrate that, in children, sex and gender are uniquely reflected in the intrinsic functional connectivity of the brain. Unimodal networks are more strongly associated with sex while heteromodal networks are more strongly associated with gender. These results suggest sex and gender are irreducible to one another not only in society but also in biology.

Anatomical connectivity in children with developmental dyscalculia: A graph theory study

Current theories postulate that numerical processing depends upon a brain circuit formed by regions and their connections; specialized in the representation and manipulation of the numerical properties of stimuli. It has been suggested that the damage of these network may cause Developmental Dyscalculia (DD): a persistent neurodevelopmental disorder that significantly interferes with academic performance and daily life activities that require mastery of mathematical notions and operations. However, most of the studies on the brain foundations of DD have focused on regions of interest associated with numerical processing, and have not addressed numerical cognition as a complex network phenomenon. The present study explored DD using a Graph Theory network approach. We studied the association between topological measures of integration and segregation of information processing in the brain proposed by Graph Theory; and individual variability in numerical performance in a group of 11 school-aged children with DD (5 of which presented with comorbidity with Developmental Dyslexia, the specific learning disorder for reading) and 17 typically developing peers. A statistically significant correlation was found between the Weber fraction (a measure of numerical representations' precision) and the Clustering Index (a measure of segregation of information processing) in the whole sample. The DD group showed significantly lower Characteristic Path Length (average shortest path length among all pairs of regions in the brain network) compared to controls. Also, differences in critical regions for the brain network performance (hubs) were found between groups. The presence of limbic hubs characterized the DD brain network while right Temporal and Frontal hubs found in controls were absent in the DD group. Our results suggest that the DD may be associated with alterations in anatomical brain connectivity that hinder the capacity to integrate and segregate numerical information.

Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach

ABSTRACT

Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging-based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). Cross-validated estimates revealed a statistically significant and clinically relevant predictive performance (Pearson r = 0.36, P < 0.0002, R2 = 0.13). The predictions were found to be specific to physical pain thresholds and not biased towards potential confounding effects (eg, anxiety, stress, depression, centre effects, and pain self-evaluation). Analysis of model coefficients suggests that the most robust cortical thickness predictors of pain sensitivity are the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole. Cortical thickness in these regions was negatively correlated to pain sensitivity. Our results can be considered as a proof-of-concept for the capacity of brain morphology to predict pain sensitivity, paving the way towards future multimodal brain-based biomarkers of pain.

The Sporadic Early-onset Alzheimer's Disease Signature Of Atrophy: Preliminary Findings From The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) Cohort

INTRODUCTION

Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early-onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker.

METHODS

We analyzed MRI scans to define the sporadic EOAD-signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early-onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment.

RESULTS

The EOAD-signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD-signature atrophy was associated with the severity of cognitive impairment.

DISCUSSION

The EOAD-signature atrophy is a reliable and clinically valid biomarker of AD-related neurodegeneration that could be used in clinical trials for EOAD.

HIGHLIGHTS

We developed an early-onset Alzheimer's disease (EOAD)-signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD-signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.

Spatiotemporal dynamics of self-generated imagery reveal a reverse cortical hierarchy from cue-induced imagery

Visual imagery allows for the construction of rich internal experience in our mental world. However, it has remained poorly understood how imagery experience derives volitionally as opposed to being cue driven. Here, using electroencephalography and functional magnetic resonance imaging, we systematically investigate the spatiotemporal dynamics of self-generated imagery by having participants volitionally imagining one of the orientations from a learned pool. We contrast self-generated imagery with cue-induced imagery, where participants imagined line orientations based on associative cues acquired previously. Our results reveal overlapping neural signatures of cue-induced and self-generated imagery. Yet, these neural signatures display substantially differential sensitivities to the two types of imagery: self-generated imagery is supported by an enhanced involvement of the anterior cortex in representing imagery contents. By contrast, cue-induced imagery is supported by enhanced imagery representations in the posterior visual cortex. These results jointly support a reverse cortical hierarchy in generating and maintaining imagery contents in self-generated versus externally cued imagery.

Association of polygenic risk for bipolar disorder with grey matter structure and white matter integrity in youth

There is a gap in knowledge regarding the polygenic underpinnings of brain anomalies observed in youth bipolar disorder (BD). This study examined the association of a polygenic risk score for BD (BD-PRS) with grey matter structure and white matter integrity in youth with and without BD. 113 participants were included in the analyses, including 78 participants with both T1-weighted and diffusion-weighted MRI images, 32 participants with T1-weighted images only, and 3 participants with diffusion-weighted images only. BD-PRS was calculated using PRS-CS-auto and was based on independent adult genome-wide summary statistics. Vertex- and voxel-wise analyses examined the associations of BD-PRS with grey matter metrics (cortical volume [CV], cortical surface area [CSA], cortical thickness [CTh]) and fractional anisotropy [FA] in the combined sample, and separately in BD and HC. In the combined sample of participants with T1-weighted images (n = 110, 66 BD, 44 HC), higher BD-PRS was associated with smaller grey matter metrics in frontal and temporal regions. In within-group analyses, higher BD-PRS was associated with lower CTh of frontal, temporal, and fusiform gyrus in BD, and with lower CV and CSA of superior frontal gyrus in HC. In the combined sample of participants with diffusion-weighted images (n = 81, 49 BD, 32 HC), higher BD-PRS was associated with lower FA in widespread white matter regions. In summary, BD-PRS calculated based on adult genetic data was negatively associated with grey matter structure and FA in youth in regions implicated in BD, which may suggest neuroimaging markers of vulnerability to BD. Future longitudinal studies are needed to examine whether BD-PRS predicts neurodevelopmental changes in BD vs. HC and its interaction with course of illness and long-term medication use.

Peripherally acting anti-CGRP monoclonal antibodies alter cortical gray matter thickness in migraine patients: A prospective cohort study

Migraine is underpinned by central nervous system neuroplastic alterations thought to be caused by the repetitive peripheral afferent barrage the brain receives during the headache phase (cortical hyperexcitability). Calcitonin gene-related peptide monoclonal antibodies (anti-CGRP-mAbs) are highly effective migraine preventative treatments. Their ability to alter brain morphometry in treatment-responders vs. non-responders is not well understood. Our aim was to determine the effects of the anti-CGRP-mAb galcanezumab on cortical thickness after 3-month treatment of patients with high-frequency episodic or chronic migraine. High-resolution magnetic resonance imaging was performed pre- and post-treatment in 36 migraine patients. In this group, 19 patients were classified responders (≥50 % reduction in monthly migraine days) and 17 were considered non-responders (<50 % reduction in monthly migraine days). Following cross-sectional processing to analyze the baseline differences in cortical thickness, two-stage longitudinal processing and symmetrized percent change were conducted to investigate treatment-related brain changes. At baseline, no significant differences were found between the responders and non-responders. After 3-month treatment, decreased cortical thickness (compared to baseline) was observed in the responders in regions of the somatosensory cortex, anterior cingulate cortex, medial frontal cortex, superior frontal gyrus, and supramarginal gyrus. Non-responders demonstrated decreased cortical thickness in the left dorsomedial cortex and superior frontal gyrus. We interpret the cortical thinning seen in the responder group as suggesting that reduction in head pain could lead to changes in neural swelling and dendritic complexity and that such changes reflect the recovery process from maladaptive neural activity. This conclusion is further supported by our recent study showing that 3 months after treatment initiation, the incidence of premonitory symptoms and prodromes that are followed by headache decreases but not the incidence of the premonitory symptoms or prodromes themselves (that is, cortical thinning relates to reductions in the nociceptive signals in the responders). We speculate that a much longer recovery period is required to allow the brain to return to a more 'normal' functioning state whereby prodromes and premonitory symptoms no longer occur.

Atypical Associations between Functional Connectivity during Pragmatic and Semantic Language Processing and Cognitive Abilities in Children with Autism

Autism Spectrum Disorder (ASD) is characterized by both atypical functional brain connectivity and cognitive challenges across multiple cognitive domains. The relationship between task-dependent brain connectivity and cognitive abilities, however, remains poorly understood. In this study, children with ASD and their typically developing (TD) peers engaged in semantic and pragmatic language tasks while their task-dependent brain connectivity was mapped and compared. A multivariate statistical approach revealed associations between connectivity and psychometric assessments of relevant cognitive abilities. While both groups exhibited brain-behavior correlations, the nature of these associations diverged, particularly in the directionality of overall correlations across various psychometric categories. Specifically, greater disparities in functional connectivity between the groups were linked to larger differences in Autism Questionnaire, BRIEF, MSCS, and SRS-2 scores but smaller differences in WASI, pragmatic language, and Theory of Mind scores. Our findings suggest that children with ASD utilize distinct neural communication patterns for language processing. Although networks recruited by children with ASD may appear less efficient than those typically engaged, they could serve as compensatory mechanisms for potential disruptions in conventional brain networks.

Associations between parental depression and anxiety symptom severity and their Offspring's cortical thickness and subcortical volume

Depression and anxiety are associated with grey matter changes in subcortical regions in adults and adolescents. Parent psychopathology is associated with offspring brain structure, but it's unclear whether altered brain structure in children is associated with severity of parental depression and anxiety symptoms. We examined 123 youth (Mean age = 13.64; 62% female) with no clinically significant history of depression or anxiety and one parent diagnosed with current or past depressive or anxiety disorders. Parents completed the Mini International Neuropsychiatric Interview to assess diagnostic status and the Beck Depression Inventory-II, and the Generalized Anxiety Disorder-7 to assess current symptom severity. Youth underwent T1 weighted structural Magnetic Resonance Imaging scans. Bivariate analyses revealed higher parental depressive severity was not significantly associated with offspring grey matter. Parental anxiety severity was significantly associated with less left global surface area. When controlling for offspring age, sex and intracranial volume (ICV), offspring right surface area was negatively associated with parental depressive severity at a trend level. In previously depressed parents, greater parental depressive severity was significantly associated with offspring decreased left and right surface area. There were no significant associations between parental anxiety severity in previously depressed parents and offspring subcortical or cortical brain regions. These results highlight associations between parental depressive symptom severity and offspring brain structure and suggest that even within an already high-risk group of adolescents, there may be altered cortical surface area depending on parent symptom severity. This may help identify youth most at risk for developing a mood disorder and could help further early intervention and identification efforts.

FreeSurfer 7 quality control: Key problem areas and importance of manual corrections

We have studied the effects of manual quality control of brain Magnetic Resonance Imaging (MRI) images processed with Freesurfer. T1 images of first episode psychosis patients (N = 60) and healthy controls (N = 41) were inspected for gray matter boundary errors. The errors were fixed, and the effects of error correction on brain volume, thickness, and surface area were measured. It is commonplace to apply quality control to Freesurfer MRI recordings to ensure that the edges of gray and white matter are detected properly, as incorrect edge detection leads to changes in variables such as volume, cortical thickness, and cortical surface area. We find that while Freesurfer v7.1.1. does regularly make mistakes in identifying the edges of cortical gray matter, correcting these errors yields limited changes in the commonly measured variables listed above. We further find that the software makes fewer gray matter boundary errors when processing female brains. The results suggest that manually correcting gray matter boundary errors may not be worthwhile due to its small effect on the measurements, with potential exceptions for studies that focus on the areas that are more commonly affected by errors: the areas around the cerebellar tentorium, paracentral lobule, and the optic nerves, specifically the horizontal segment of the middle cerebral artery.

Can diffusion tensor imaging have a diagnostic utility to differentiate early-onset forms of bipolar disorder and schizophrenia: A neuroimaging study with explainable machine learning algorithms

BACKGROUND/AIM

Accurate diagnosis of early-onset psychotic disorders is crucial to improve clinical outcomes. This study aimed to differentiate patients with early-onset schizophrenia (EOS) from early-onset bipolar disorder (EBD) with machine learning (ML) algorithms using white matter tracts (WMT).

METHOD

Diffusion tensor imaging was obtained from adolescents with either EOS (n = 43) or EBD (n = 32). Global probabilistic tractography using an automated tract-based TRACULA software was performed to analyze the fractional anisotropy (FA) of forty-two WMT. The nested cross-validation was performed in feature selection and model construction. EXtreme Gradient Boosting (XGBoost) was applied to select the features that can give the best performance in the ML model. The interpretability of the model was explored with the SHApley Additive exPlanations (SHAP).

FINDINGS

The XGBoost algorithm identified nine out of the 42 major WMTs with significant predictive power. Among ML models, Support Vector Machine-Linear showed the best performance. Higher SHAP values of left acoustic radiation, bilateral anterior thalamic radiation, and the corpus callosum were associated with a higher likelihood of EOS.

CONCLUSIONS

Our findings suggested that ML models based on the FA values of major WMT reconstructed by global probabilistic tractography can unveil hidden microstructural aberrations to distinguish EOS from EBD.

A prospective 5-year longitudinal study detects neurocognitive and imaging correlates of seizure remission in self-limiting Rolandic epilepsy

OBJECTIVE

Self-limiting Rolandic epilepsy (RE) is the most common epilepsy in school-age children. Seizures are generally infrequent, but cognitive, language, and motor coordination problems can significantly impact the child's life. To better understand brain structure and function changes in RE, we longitudinally assessed neurocognition, cortical thickness, and subcortical volumes.

METHODS

At baseline, we recruited 30 participants diagnosed with RE and 24-healthy controls and followed up for 4.94 ± 0.8 years when the participants with RE were in seizure remission. Measures included were as follows: T1-weighted magnetic resonance brain imaging (MRI) with FreeSurfer analysis and detailed neuropsychological assessments. MRI and neuropsychological data were compared between baseline and follow-up in seizure remission.

RESULTS

Longitudinal MRI revealed excess cortical thinning in the left-orbitofrontal (p = 0.0001) and pre-central gyrus (p = 0.044). There is a significant association (p = 0.003) between a reduction in cortical thickness in the left-orbitofrontal cluster and improved processing of filtered words. Longitudinal neuropsychology revealed significant improvements in the symptoms of developmental coordination disorder (DCD, p = 0.005) in seizure remission.

CONCLUSIONS

There is evidence for altered development of neocortical regions between active seizure state and seizure remission in RE within two clusters maximal in the left-orbitofrontal and pre-central gyrus. There is significant evidence for improvement in motor coordination between active seizures and seizure remission and suggestive evidence for a decline in fluid intelligence and gains in auditory processing.

Correlation between immune-related genes and depression-like features in an animal model and in humans

A growing body of evidence suggests that immune-related genes play pivotal roles in the pathophysiology of depression. In the present study, we investigated a plausible connection between gene expression, DNA methylation, and brain structural changes in the pathophysiology of depression using a combined approach of murine and human studies. We ranked the immobility behaviors of 30 outbred Crl:CD1 (ICR) mice in the forced swim test (FST) and harvested their prefrontal cortices for RNA sequencing. Of the 24,532 analyzed genes, 141 showed significant correlations with FST immobility time, as determined through linear regression analysis with p ≤ 0.01. The identified genes were mostly involved in immune responses, especially interferon signaling pathways. Moreover, induction of virus-like neuroinflammation in the brains of two separate mouse cohorts (n = 30 each) using intracerebroventricular polyinosinic:polycytidylic acid injection resulted in increased immobility during FST and similar expression of top immobility-correlated genes. In human blood samples, candidate gene (top 5%) expression profiling using DNA methylation analysis found the interferon-related USP18 (cg25484698, p = 7.04 × 10-11, Δβ = 1.57 × 10-2; cg02518889, p = 2.92 × 10-3, Δβ =  - 8.20 × 10-3) and IFI44 (cg07107453, p = 3.76 × 10-3, Δβ =  - 4.94 × 10-3) genes to be differentially methylated between patients with major depressive disorder (n = 350) and healthy controls (n = 161). Furthermore, cortical thickness analyses using T1-weighted images revealed that the DNA methylation scores for USP18 were negatively correlated with the thicknesses of several cortical regions, including the prefrontal cortex. Our results reveal the important role of the interferon pathway in depression and suggest USP18 as a potential candidate target. The results of the correlation analysis between transcriptomic data and animal behavior carried out in this study provide insights that could enhance our understanding of depression in humans.

Frequency and imaging correlates of neuropsychiatric symptoms in Progressive Supranuclear Palsy

Neuropsychiatric symptoms are intrinsic to Progressive Supranuclear Palsy (PSP) and a spoonful of studies investigated their imaging correlates. Describe (I) the frequency and severity of neuropsychiatric symptoms in PSP and (II) their structural imaging correlates. Twenty-six PSP patients underwent Neuropsychiatric Inventory (NPI) and brain 3D T1-weighted MRI. Spearman's rho with Bonferroni correction was used to investigate correlations between NPI scores and volumes of gray matter regions. More than 80% of patients presented at least one behavioral symptom of any severity. The most frequent and severe were depression/dysphoria, apathy, and irritability/lability. Significant relationships were found between the severity of irritability and right pars opercularis volume (p < 0.001) as well as between the frequency of agitation/aggression and left lateral occipital volume (p < 0.001). Depression, apathy, and irritability are the most common neuropsychiatric symptoms in PSP. Moreover, we found a relationship between specific positive symptoms as irritability and agitation/aggression and greater volume of the right pars opercularis cortex and lower volume of the left occipital cortex, respectively, which deserve further investigations.

Predicting 'Brainage' in late childhood to adolescence (6-17yrs) using structural MRI, morphometric similarity, and machine learning

Brain development is regularly studied using structural MRI. Recently, studies have used a combination of statistical learning and large-scale imaging databases of healthy children to predict an individual's age from structural MRI. This data-driven, predicted 'Brainage' typically differs from the subjects chronological age, with this difference a potential measure of individual difference. Few studies have leveraged higher-order or connectomic representations of structural MRI data for this Brainage approach. We leveraged morphometric similarity as a network-level approach to structural MRI to generate predictive models of age. We benchmarked these novel Brainage approaches using morphometric similarity against more typical, single feature (i.e., cortical thickness) approaches. We showed that these novel methods did not outperform cortical thickness or cortical volume measures. All models were significantly biased by age, but robust to motion confounds. The main results show that, whilst morphometric similarity mapping may be a novel way to leverage additional information from a T1-weighted structural MRI beyond individual features, in the context of a Brainage framework, morphometric similarity does not provide more accurate predictions of age. Morphometric similarity as a network-level approach to structural MRI may be poorly positioned to study individual differences in brain development in healthy participants in this way.

Genetic risks of Alzheimer's by APOE and MAPT on cortical morphology in young healthy adults

Genetic risk factors such as APOE ε4 and MAPT (rs242557) A allele are associated with amyloid and tau pathways and grey matter changes at both early and established stages of Alzheimer's disease, but their effects on cortical morphology in young healthy adults remain unclear. A total of 144 participants aged from 18 to 24 underwent 3T MRI and genotyping for APOE and MAPT to investigate unique impacts of these genetic risk factors in a cohort without significant comorbid conditions such as metabolic and cardiovascular diseases. We segmented the cerebral cortex into 68 regions and calculated the cortical area, thickness, curvature and folding index for each region. Then, we trained machine learning models to classify APOE and MAPT genotypes using these morphological features. In addition, we applied a growing hierarchical self-organizing maps algorithm, which clustered the 68 regions into 4 subgroups representing different morphological patterns. Then, we performed general linear model analyses to estimate the interaction between APOE and MAPT on cortical patterns. We found that the classifiers using all cortical features could accurately classify individuals carrying genetic risks of dementia outperforming each individual feature alone. APOE ε4 carriers had a more convoluted and thinner cortex across the cerebral cortex. A similar pattern was found in MAPT A allele carriers only in the regions that are vulnerable for early tau pathology. With the clustering analysis, we found a synergetic effect between APOE ε4 and MAPT A allele, i.e. carriers of both risk factors showed the most deviation of cortical pattern from the typical pattern of that cluster. Genetic risk factors of dementia by APOE ε4 and MAPT (rs242557) A allele were associated with variations of cortical morphology, which can be observed in young healthy adults more than 30 years before Alzheimer's pathology is likely to occur and 50 years before dementia symptoms may begin.

The association between white matter tract structural connectivity and information processing speed in relapsing-remitting multiple sclerosis

BACKGROUND

Information processing speed (IPS) deterioration is common in relapsing-remitting multiple sclerosis (RRMS) patients [1] and might severely affect quality of life and occupational activity. However, understanding of its neural substrate is not fully elucidated. We aimed to investigate the associations between MRI-derived metrics of neuroanatomical structures, including the tracts, and IPS.

METHODS

Symbol Digit Modalities Test (SDMT), Paced Auditory Serial Addition Test (PASAT), and Color Trails Test (CTT) were used to evaluate IPS in 73 RRMS consecutive patients, all undergoing only interferon beta (IFN-β) therapy during the study. At the same time, 1.5T MRI including diffusion tensor imaging (DTI) data was acquired for each recruited subject. We analyzed volumetric and diffusion MRI measures (FreeSurfer 6.0) including normalized brain volume (NBV), cortical thickness (thk), white matter hypointensities (WMH), volume (vol), diffusion parameters: mean (MD), radial (RD), axial (AD) diffusivities, and fractional anisotropy (FA) of 18 major white-matter (WM) tracts. Multiple linear regression model with interaction resulted in distinguishing the neural substrate of IPS deficit in the IPS impaired subgroup of patients.

RESULTS

The most significant tract abnormalities contributing to IPS deficit were right inferior longitudinal fasciculus (R ILF) FA, forceps major (FMAJ) FA, forceps minor (FMIN) FA, R uncinate fasciculus (UNC) AD, R corticospinal tract (CST) FA, and left superior longitudinal fasciculus FA (L SLFT). Among volumetric MRI metrics, IPS deficit was associated with L and R thalamic vol. and cortical thickness of insular regions.

CONCLUSION

In this study, we showed that disconnection of the selected WM tracts, in addition to cortical and deep gray matter (GM) atrophy, might underlie IPS deficit in RRMS patients but more extensive studies are needed for precise associations.

A multidimensional characterization of the neurocognitive architecture underlying age-related temporal speech processing

Healthy aging is often associated with speech comprehension difficulties in everyday life situations despite a pure-tone hearing threshold in the normative range. Drawing on this background, we used a multidimensional approach to assess the functional and structural neural correlates underlying age-related temporal speech processing while controlling for pure-tone hearing acuity. Accordingly, we combined structural magnetic resonance imaging and electroencephalography, and collected behavioral data while younger and older adults completed a phonetic categorization and discrimination task with consonant-vowel syllables varying along a voice-onset time continuum. The behavioral results confirmed age-related temporal speech processing singularities which were reflected in a shift of the boundary of the psychometric categorization function, with older adults perceiving more syllable characterized by a short voice-onset time as /ta/ compared to younger adults. Furthermore, despite the absence of any between-group differences in phonetic discrimination abilities, older adults demonstrated longer N100/P200 latencies as well as increased P200 amplitudes while processing the consonant-vowel syllables varying in voice-onset time. Finally, older adults also exhibited a divergent anatomical gray matter infrastructure in bilateral auditory-related and frontal brain regions, as manifested in reduced cortical thickness and surface area. Notably, in the younger adults but not in the older adult cohort, cortical surface area in these two gross anatomical clusters correlated with the categorization of consonant-vowel syllables characterized by a short voice-onset time, suggesting the existence of a critical gray matter threshold that is crucial for consistent mapping of phonetic categories varying along the temporal dimension. Taken together, our results highlight the multifaceted dimensions of age-related temporal speech processing characteristics, and pave the way toward a better understanding of the relationships between hearing, speech and the brain in older age.

Cerebral cortical thinning in brain regions involved in emotional regulation relates to persistent symptoms in subjects with posttraumatic stress disorder

A considerable proportion of individuals exposed to trauma experience chronic and persistent posttraumatic stress disorder (PTSD). However, the specific brain and clinical features that render trauma-exposed individuals more susceptible to enduring symptoms remain elusive. This study investigated 112 trauma-exposed participants who had been diagnosed with PTSD and 112 demographically-matched healthy controls. Trauma-exposed participants were classified into those with current PTSD (persistent PTSD, n = 78) and those without (remitted PTSD, n = 34). Cortical thickness analysis was performed to discern group-specific brain structural characteristics. Coping strategies and resilience levels, assessed as clinical attributes, were compared across the groups. The persistent PTSD group displayed cortical thinning in the superior frontal cortex (SFC), insula, superior temporal cortex, dorsolateral prefrontal cortex, superior parietal cortex, and precuneus, relative to the remitted PTSD and control groups. Cortical thinning in the SFC was associated with increased utilization of maladaptive coping strategies, while diminished thickness in the insula correlated with lower resilience levels among trauma-exposed individuals. These findings imply that cortical thinning in brain regions related to coping strategy and resilience plays a vital role in the persistence of PTSD symptoms.

Functional and structural connectivity in the Papez circuit in different stages of Alzheimer's disease

OBJECTIVE

Alzheimer's disease (AD) is a progressive neurodegenerative continuum with memory impairment. We aimed to examine the detailed functional (FC) and structural connectivity (SC) pattern of the Papez circuit, known as the memory circuit, along the AD.

METHODS

MRI data of 15 patients diagnosed with AD dementia (ADD), 15 patients with the amnestic mild cognitive impairment (MCI), and 15 patients with subjective cognitive impairment were analyzed. The FC analyses were performed between main nodes of the Papez circuit, and the SC was quantified as fractional anisotropy (FA) of the main white matter pathways of the Papez circuit.

RESULTS

The FC between the retrosplenial (RSC) and parahippocampal cortices (PHC) was the earliest affected FC, while a manifest SC change in the ventral cingulum and fornix was observed in the later ADD stage. The RSC-PHC FC and the ventral cingulum FA efficiently predicted the memory performance of the non-demented participants.

CONCLUSIONS

Our findings revealed the importance of the Papez circuit as target regions along the AD.

SIGNIFICANCE

The ventral cingulum connecting the RSC and PHC, a critical overlap area between the Papez circuit and the default mode network, seems to be a target region associated with the earliest objective memory findings in AD.

Comparative neuroimaging of sex differences in human and mouse brain anatomy

In vivo neuroimaging studies have established several reproducible volumetric sex differences in the human brain, but the causes of such differences are hard to parse. While mouse models are useful for understanding the cellular and mechanistic bases of sex-biased brain development in mammals, there have been no attempts to formally compare mouse and human sex differences across the whole brain to ascertain how well they translate. Addressing this question would shed critical light on use of the mouse as a translational model for sex differences in the human brain and provide insights into the degree to which sex differences in brain volume are conserved across mammals. Here, we use cross-species structural magnetic resonance imaging to carry out the first comparative neuroimaging study of sex-biased neuroanatomical organization of the human and mouse brain. In line with previous findings, we observe that in humans, males have significantly larger and more variable total brain volume; these sex differences are not mirrored in mice. After controlling for total brain volume, we observe modest cross-species congruence in the volumetric effect size of sex across 60 homologous brain regions (r=0.30; e.g.: M>F amygdala, hippocampus, bed nucleus of the stria terminalis, and hypothalamus and F>M anterior cingulate, somatosensory, and primary auditory cortices). This cross-species congruence is greater in the cortex (r=0.33) than non-cortex (r=0.16). By incorporating regional measures of gene expression in both species, we reveal that cortical regions with greater cross-species congruence in volumetric sex differences also show greater cross-species congruence in the expression profile of 2835 homologous genes. This phenomenon differentiates primary sensory regions with high congruence of sex effects and gene expression from limbic cortices where congruence in both these features was weaker between species. These findings help identify aspects of sex-biased brain anatomy present in mice that are retained, lost, or inverted in humans. More broadly, our work provides an empirical basis for targeting mechanistic studies of sex-biased brain development in mice to brain regions that best echo sex-biased brain development in humans.

Bright light therapy and early morning attention, mathematical performance, electroencephalography and brain connectivity in adolescents with morning sleepiness

Adolescents typically sleep too little and feel drowsy during morning classes. We assessed whether morning use of an LED bright light device could increase alertness in school students. Twenty-six (8M/18F) healthy, unmedicated participants, ages 13-18 years, (mean 17.1±1.4) were recruited following screenings to exclude psychopathology. Baseline assessments were made of actigraph-assessed sleep, attention, math solving ability, electroencephalography and structural and functional MRI (N = 10-11, pre-post). Participants nonrandomly received 3-4 weeks of bright light therapy (BLT) for 30 minutes each morning and used blue light blocking glasses for 2 hours before bedtime. BLT devices were modified to surreptitiously record degree of use so that the hypothesis tested was whether there was a significant relationship between degree of use and outcome. They were used 57±18% (range 23%-90%) of recommended time. There was a significant association between degree of use and: (1) increased beta spectral power in frontal EEG leads (primary measure); (2) greater post-test improvement in math performance and reduction in errors of omission on attention test; (3) reduced day-to-day variability in bed times, sleep onset, and sleep duration during school days; (4) increased dentate gyrus volume and (5) enhanced frontal connectivity with temporal, occipital and cerebellar regions during Go/No-Go task performance. BLT was associated with improvement in sleep cycle consistency, arousal, attention and functional connectivity, but not sleep onset or duration (primary measures). Although this was an open study, it suggests that use of bright morning light and blue light blocking glasses before bed may benefit adolescents experiencing daytime sleepiness. Clinical trial registration: Clinicaltrials.gov ID-NCT05383690.

Decreased GABA levels of the anterior and posterior cingulate cortex are associated with executive dysfunction in mild cognitive impairment

Background and purpose

Executive function impairment, a slight but noticeable cognitive deficit in mild cognitive impairment (MCI) patients, is influenced by gamma-aminobutyric acid (GABA) levels. Reduced cognitive function is accompanied by thinning of the cerebral cortex, which has higher GABA levels than white matter. However, the relationships among GABA levels, cortical thickness, and executive function in MCI patients have not yet been elucidated. We investigated the relationships among GABA levels, cortical thickness, and executive function in MCI patients.

Methods

In this study, a total of 36 MCI patients and 36 sex-, age-, and education-matched healthy controls (HC) were recruited. But 33 MCI patients and 35 HC were included because of head motion or poor data quality for three MCI patients and one HC. The levels of gamma-aminobutyric acid plus relative to creatine (GABA+/Cr) and glutamate-glutamine relative to creatine (Glx/Cr) in the anterior cingulate cortex (ACC) and posterior cingulate cortex (PCC) were measured using the Meshcher-Garwood point resolved spectroscopy (MEGA-PRESS) sequence. Metabolite ratios, cortical thickness, and executive function and their interrelationships were determined in the MCI and HC groups.

Results

Patients with MCI showed lower GABA+/Cr levels in the ACC and PCC. Combined levels of GABA+ and Glx in the ACC and GABA+ in the PCC showed good diagnostic efficacy for MCI (AUC: 0.82). But no differences in cortical thickness were found between the two groups. In the MCI group, lower GABA+/Cr level was correlated to worse performance on the digit span test backward, and the shape trail test-B. The cortical thickness was not associated with GABA+ levels and executive function in patients.

Conclusion

These results implied that decreased GABA levels in the ACC and PCC had a critical role in the early diagnosis of impaired executive function of MCI. Therefore, GABA in the ACC and PCC could be a potential diagnostic marker of the executive function decline of MCI.

Self-supervised learning with application for infant cerebellum segmentation and analysis

Accurate tissue segmentation is critical to characterize early cerebellar development in the first two postnatal years. However, challenges in tissue segmentation arising from tightly-folded cortex, low and dynamic tissue contrast, and large inter-site data heterogeneity have limited our understanding of early cerebellar development. In this paper, we propose an accurate self-supervised learning framework for infant cerebellum segmentation. We validate its accuracy using 358 subjects from three datasets. Our results suggest the first six months exhibit the most rapid and dynamic changes, with gray matter (GM) playing a dominant role in cerebellar growth over white matter (WM). We also find both GM and WM volumes are larger in males than females, and GM and WM volumes are larger in autistic males than neurotypical males. Application of our method to a larger population will fuel more cerebellar studies, ultimately advancing our comprehension of its structure and function in neurotypical and disordered development.

Gray matter volume and pain tolerance in a general population: the Tromsø study

ABSTRACT

As pain is processed by an extensive network of brain regions, the structural status of the brain may affect pain perception. We aimed to study the association between gray matter volume (GMV) and pain sensitivity in a general population. We used data from 1522 participants in the seventh wave of the Tromsø study, who had completed the cold pressor test (3°C, maximum time 120 seconds), undergone magnetic resonance imaging (MRI) of the brain, and had complete information on covariates. Cox proportional hazards regression models were fitted with time to hand withdrawal from cold exposure as outcome. Gray matter volume was the independent variable, and analyses were adjusted for intracranial volume, age, sex, education level, and cardiovascular risk factors. Additional adjustment was made for chronic pain and depression in subsamples with available information on the respective item. FreeSurfer was used to estimate vertexwise cortical and subcortical gray matter volumes from the T1-weighted MR image. Post hoc analyses were performed on cortical and subcortical volume estimates. Standardized total GMV was associated with risk of hand withdrawal (hazard ratio [HR] 0.81, 95% confidence interval [CI] 0.71-0.93). The effect remained significant after additional adjustment for chronic pain (HR 0.84, 95% CI 0.72-0.97) or depression (HR 0.82, 95% CI 0.71-0.94). In post hoc analyses, positive associations between standardized GMV and pain tolerance were seen in most brain regions, with larger effect sizes in regions previously shown to be associated with pain. In conclusion, our findings indicate that larger GMV is associated with longer pain tolerance in the general population.

Vascular Endothelial Growth Factor Polymorphism rs699947 Is Associated with Neurostructural Phenotypes in Youth with Bipolar Disorder

Background: Vascular endothelial growth factor (VEGF) may be relevant to bipolar disorder (BD) and brain structure. We evaluated VEGF rs699947 single-nucleotide polymorphism in relation to structural neuroimaging phenotypes in youth BD. Methods: We collected 3 T anatomical magnetic resonance images from 154 youth (79 BD and 75 healthy control [HC]) genotyped for VEGF rs699947. The participants were age (BD = 17.28 ± 1.40 and HC = 17.01 ± 1.83, t = -1.02, p = 0.31) and sex (BD = 63.3% females and HC = 52.0% females, χ2 = 2.01, p = 0.16) matched. Cortical thickness, surface area (SA), and volume were examined by region-of-interest (ROI) and vertex-wise analyses using general linear models (GLMs). ROI investigations selected for the prefrontal cortex (PFC), amygdala, and hippocampus. Vertex-wise analyses controlled for age, sex, and intracranial volume. Results: ROI results found lower PFC SA (p = 0.003, ηp2 = 0.06) and volume (p = 0.04, ηp2 = 0.03) in BD and a main effect of rs699947 on hippocampal volume (p = 0.03, ηp2 = 0.05). The latter two findings did not survive multiple comparisons. Vertex-wise analyses found rs699947 main effects on left postcentral gyrus volume (p < 0.001), right rostral anterior cingulate SA (p = 0.004), and right superior temporal gyrus thickness (p = 0.004). There were significant diagnosis-by-genotype interactions in the left superior temporal, left caudal middle frontal, left superior frontal, right fusiform, and right lingual gyri, and the left insular cortex. Posthoc analyses revealed the AA allele was associated with larger brain structures among HC, but smaller brain structures in BD for most clusters. Conclusions: Overall, we found preliminary evidence of divergent associations between BD and HC youth in terms of neurostructural correlates of VEGF rs699947 encompassing highly relevant frontotemporal regions.

Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes

Implantation of electrodes in the brain has been used as a clinical tool for decades to stimulate and record brain activity. As this method increasingly becomes the standard of care for several disorders and diseases, there is a growing need to quickly and accurately localize the electrodes once they are placed within the brain. We share here a protocol pipeline for localizing electrodes implanted in the brain, which we have applied to more than 260 patients, that is accessible to multiple skill levels and modular in execution. This pipeline uses multiple software packages to prioritize flexibility by permitting multiple different parallel outputs while minimizing the number of steps for each output. These outputs include co-registered imaging, electrode coordinates, 2D and 3D visualizations of the implants, automatic surface and volumetric localizations of the brain regions per electrode, and anonymization and data sharing tools. We demonstrate here some of the pipeline's visualizations and automatic localization algorithms which we have applied to determine appropriate stimulation targets, to conduct seizure dynamics analysis, and to localize neural activity from cognitive tasks in previous studies. Further, the output facilitates the extraction of information such as the probability of grey matter intersection or the nearest anatomic structure per electrode contact across all data sets that go through the pipeline. We expect that this pipeline will be a useful framework for researchers and clinicians alike to localize implanted electrodes in the human brain.

The neuroanatomical hallmarks of chronic tinnitus in comorbidity with pure-tone hearing loss

Tinnitus is one of the main hearing impairments often associated with pure-tone hearing loss, and typically manifested in the perception of phantom sounds. Nevertheless, tinnitus has traditionally been studied in isolation without necessarily considering auditory ghosting and hearing loss as part of the same syndrome. Hence, in the present neuroanatomical study, we attempted to pave the way toward a better understanding of the tinnitus syndrome, and compared two groups of almost perfectly matched individuals with (TIHL) and without (NTHL) pure-tone tinnitus, but both characterized by pure-tone hearing loss. The two groups were homogenized in terms of sample size, age, gender, handedness, education, and hearing loss. Furthermore, since the assessment of pure-tone hearing thresholds alone is not sufficient to describe the full spectrum of hearing abilities, the two groups were also harmonized for supra-threshold hearing estimates which were collected using temporal compression, frequency selectivity und speech-in-noise tasks. Regions-of-interest (ROI) analyses based on key brain structures identified in previous neuroimaging studies showed that the TIHL group exhibited increased cortical volume (CV) and surface area (CSA) of the right supramarginal gyrus and posterior planum temporale (PT) as well as CSA of the left middle-anterior part of the superior temporal sulcus (STS). The TIHL group also demonstrated larger volumes of the left amygdala and of the left head and body of the hippocampus. Notably, vertex-wise multiple linear regression analyses additionally brought to light that CSA of a specific cluster, which was located in the left middle-anterior part of the STS and overlapped with the one found to be significant in the between-group analyses, was positively associated with tinnitus distress level. Furthermore, distress also positively correlated with CSA of gray matter vertices in the right dorsal prefrontal cortex and the right posterior STS, whereas tinnitus duration was positively associated with CSA and CV of the right angular gyrus (AG) and posterior part of the STS. These results provide new insights into the critical gray matter architecture of the tinnitus syndrome matrix responsible for the emergence, maintenance and distress of auditory phantom sensations.

Harmonizing Healthy Cohorts to Support Multicenter Studies on Migraine Classification using Brain MRI Data

Multicenter and multi-scanner imaging studies might be needed to provide sample sizes large enough for developing accurate predictive models. However, multicenter studies, which likely include confounding factors due to subtle differences in research participant characteristics, MRI scanners, and imaging acquisition protocols, might not yield generalizable machine learning models, that is, models developed using one dataset may not be applicable to a different dataset. The generalizability of classification models is key for multi-scanner and multicenter studies, and for providing reproducible results. This study developed a data harmonization strategy to identify healthy controls with similar (homogenous) characteristics from multicenter studies to validate the generalization of machine-learning techniques for classifying individual migraine patients and healthy controls using brain MRI data. The Maximum Mean Discrepancy (MMD) was used to compare the two datasets represented in Geodesic Flow Kernel (GFK) space, capturing the data variabilities for identifying a "healthy core". A set of homogeneous healthy controls can assist in overcoming some of the unwanted heterogeneity and allow for the development of classification models that have high accuracy when applied to new datasets. Extensive experimental results show the utilization of a healthy core. One dataset consists of 120 individuals (66 with migraine and 54 healthy controls) and another dataset consists of 76 (34 with migraine and 42 healthy controls) individuals. A homogeneous dataset derived from a cohort of healthy controls improves the performance of classification models by about 25% accuracy improvements for both episodic and chronic migraineurs.

Preliminary validation of a structural magnetic resonance imaging metric for tracking dementia-related neurodegeneration and future decline

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by cognitive decline and atrophy in the medial temporal lobe (MTL) and subsequent brain regions. Structural magnetic resonance imaging (sMRI) has been widely used in research and clinical care for diagnosis and monitoring AD progression. However, atrophy patterns are complex and vary by patient. To address this issue, researchers have made efforts to develop more concise metrics that can summarize AD-specific atrophy. Many of these methods can be difficult to interpret clinically, hampering adoption. In this study, we introduce a novel index which we call an "AD-NeuroScore," that uses a modified Euclidean-inspired distance function to calculate differences between regional brain volumes associated with cognitive decline. The index is adjusted for intracranial volume (ICV), age, sex, and scanner model. We validated AD-NeuroScore using 929 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, with a mean age of 72.7 years (SD = 6.3; 55.1-91.5) and cognitively normal (CN), mild cognitive impairment (MCI), or AD diagnoses. Our validation results showed that AD-NeuroScore was significantly associated with diagnosis and disease severity scores (measured by MMSE, CDR-SB, and ADAS-11) at baseline. Furthermore, baseline AD-NeuroScore was associated with both changes in diagnosis and disease severity scores at all time points with available data. The performance of AD-NeuroScore was equivalent or superior to adjusted hippocampal volume (AHV), a widely used metric in AD research. Further, AD-NeuroScore typically performed as well as or sometimes better when compared to other existing sMRI-based metrics. In conclusion, we have introduced a new metric, AD-NeuroScore, which shows promising results in detecting AD, benchmarking disease severity, and predicting disease progression. AD-NeuroScore differentiates itself from other metrics by being clinically practical and interpretable.

Distinct brain network features predict internalizing and externalizing traits in children and adults

Internalizing and externalizing traits are two distinct classes of behaviors in psychiatry. However, whether shared or unique brain network features predict internalizing and externalizing behaviors in children and adults remain poorly understood. Using a sample of 2262 children from the Adolescent Brain Cognitive Development (ABCD) study and 752 adults from the Human Connectome Project (HCP), we show that network features predicting internalizing and externalizing behavior are, at least in part, dissociable in children, but not in adults. In ABCD children, traits within internalizing and externalizing behavioral categories are predicted by more similar network features concatenated across task and resting states than those between different categories. We did not observe this pattern in HCP adults. Distinct network features predict internalizing and externalizing behaviors in ABCD children and HCP adults. These data reveal shared and unique brain network features accounting for individual variation within broad internalizing and externalizing categories across developmental stages.

White matter hyperintensities and smaller cortical thickness are associated with neuropsychiatric symptoms in neurodegenerative and cerebrovascular diseases

BACKGROUND

Neuropsychiatric symptoms (NPS) are a core feature of most neurodegenerative and cerebrovascular diseases. White matter hyperintensities and brain atrophy have been implicated in NPS. We aimed to investigate the relative contribution of white matter hyperintensities and cortical thickness to NPS in participants across neurodegenerative and cerebrovascular diseases.

METHODS

Five hundred thirteen participants with one of these conditions, i.e. Alzheimer's Disease/Mild Cognitive Impairment, Amyotrophic Lateral Sclerosis, Frontotemporal Dementia, Parkinson's Disease, or Cerebrovascular Disease, were included in the study. NPS were assessed using the Neuropsychiatric Inventory - Questionnaire and grouped into hyperactivity, psychotic, affective, and apathy subsyndromes. White matter hyperintensities were quantified using a semi-automatic segmentation technique and FreeSurfer cortical thickness was used to measure regional grey matter loss.

RESULTS

Although NPS were frequent across the five disease groups, participants with frontotemporal dementia had the highest frequency of hyperactivity, apathy, and affective subsyndromes compared to other groups, whilst psychotic subsyndrome was high in both frontotemporal dementia and Parkinson's disease. Results from univariate and multivariate results showed that various predictors were associated with neuropsychiatric subsyndromes, especially cortical thickness in the inferior frontal, cingulate, and insula regions, sex(female), global cognition, and basal ganglia-thalamus white matter hyperintensities.

CONCLUSIONS

In participants with neurodegenerative and cerebrovascular diseases, our results suggest that smaller cortical thickness and white matter hyperintensity burden in several cortical-subcortical structures may contribute to the development of NPS. Further studies investigating the mechanisms that determine the progression of NPS in various neurodegenerative and cerebrovascular diseases are needed.

Subcortical volume analysis in non-suicidal self-injury adolescents: A pilot study

Given the high prevalence of non-suicidal self-injury (NSSI) among teenagers worldwide, the underlying mechanisms promoting such behavior must be urgently investigated. This study aimed to investigate neurobiological changes in the regional brain in adolescents with NSSI by comparing the volumes of the subcortical structures of 23 female adolescents with NSSI and 23 healthy controls with no history of psychiatric diagnosis or treatment. The NSSI group comprised those who underwent inpatient treatment for non-suicidal self-harm behavior at the Department of Psychiatry at Daegu Catholic University Hospital from July 1, 2018, to December 31, 2018. The control group comprised healthy adolescents from the community. We compared differences in the volume of the bilateral thalamus, caudate, putamen, hippocampus, and amygdala. All statistical analyses were conducted using SPSS Statistics Version 25. The NSSI group exhibited decreased subcortical volume in the left amygdala and marginally decreased subcortical volume in the left thalamus. Our results provide important clues about adolescent NSSI's underlying biology. Analysis of subcortical volumes between the NSSI and normal groups revealed subcortical volume differences in the left amygdala and thalamus, part of the core cerebral regions responsible for emotional processing and regulation, which may help explain the neurobiological mechanism of NSSI.

Distinguishing Patients with MRI-Negative Temporal Lobe Epilepsy from Normal Controls Based on Individual Morphological Brain Network

Temporal Lobe Epilepsy (TLE) is the most common subtype of focal epilepsy and the most refractory to drug treatment. Roughly 30% of patients do not have easily identifiable structural abnormalities. In other words, MRI-negative TLE has normal MRI scans on visual inspection. Thus, MRI-negative TLE is a diagnostic and therapeutic challenge. In this study, we investigate the cortical morphological brain network to identify MRI-negative TLE. The 210 cortical ROIs based on the Brainnetome atlas were used to define the network nodes. The least absolute shrinkage and selection operator (LASSO) algorithm and Pearson correlation methods were used to calculate the inter-regional morphometric features vector correlation respectively. As a result, two types of networks were constructed. The topological characteristics of networks were calculated by graph theory. Then after, a two-stage feature selection strategy, including a two-sample t-test and support vector machine-based recursive feature elimination (SVM-RFE), was performed in feature selection. Finally, classification with support vector machine (SVM) and leave-one-out cross-validation (LOOCV) was employed for the training and evaluation of the classifiers. The performance of two constructed brain networks was compared in MRI-negative TLE classification. The results indicated that the LASSO algorithm achieved better performance than the Pearson pairwise correlation method. The LASSO algorithm provides a robust method of individual morphological network construction for distinguishing patients with MRI-negative TLE from normal controls.

Altered thalamic volume in patients with mild autonomous cortisol secretion: a structural brain MRI study

PURPOSE

To compare thalamic volume and cognitive functions of patients with mild autonomous cortisol secretion (MACS) with control subjects and patients with overt Cushing's syndrome (CS).

METHODS

In this cross-sectional study, volumes of regions of interest were assessed using 3 T magnetic resonance imaging and a voxel-based morphometry approach in 23 patients with MACS, 21 patients with active CS, 27 patients with CS in remission, and 21 control subjects. Cognitive functions were assessed using validated questionnaires.

RESULTS

Patients with MACS had smaller left thalamic (F = 3.8, p = 0.023), left posterior thalamic (F = 4.9, p = 0.01), left medial thalamic (F = 4.7, p = 0.028), and right lateral thalamic (F = 4.1, p = 0.025) volumes than control subjects. Patients with active CS also had smaller left thalamic (F = 3.8, p = 0.044), left posterior thalamic (F = 4.9, p = 0.007), left medial thalamic (F = 4.7, p = 0.006), and right lateral thalamic (F = 4.1, p = 0.042) volumes compared to controls. Patients with CS in remission had smaller left medial (F = 4.7, p = 0.030) and right lateral thalamic (F = 4.1, p = 0.028) volumes than controls. Neuropsychological tests showed no difference between the groups.

CONCLUSION

MACS may decrease thalamic volume.

Relationship Between Prediction Accuracy and Feature Importance Reliability: an Empirical and Theoretical Study

There is significant interest in using neuroimaging data to predict behavior. The predictive models are often interpreted by the computation of feature importance, which quantifies the predictive relevance of an imaging feature. Tian and Zalesky (2021) suggest that feature importance estimates exhibit low split-half reliability, as well as a trade-off between prediction accuracy and feature importance reliability across parcellation resolutions. However, it is unclear whether the trade-off between prediction accuracy and feature importance reliability is universal. Here, we demonstrate that, with a sufficient sample size, feature importance (operationalized as Haufe-transformed weights) can achieve fair to excellent split-half reliability. With a sample size of 2600 participants, Haufe-transformed weights achieve average intra-class correlation coefficients of 0.75, 0.57 and 0.53 for cognitive, personality and mental health measures respectively. Haufe-transformed weights are much more reliable than original regression weights and univariate FC-behavior correlations. Original regression weights are not reliable even with 2600 participants. Intriguingly, feature importance reliability is strongly positively correlated with prediction accuracy across phenotypes. Within a particular behavioral domain, there is no clear relationship between prediction performance and feature importance reliability across regression models. Furthermore, we show mathematically that feature importance reliability is necessary, but not sufficient, for low feature importance error. In the case of linear models, lower feature importance error is mathematically related to lower prediction error. Therefore, higher feature importance reliability might yield lower feature importance error and higher prediction accuracy. Finally, we discuss how our theoretical results relate with the reliability of imaging features and behavioral measures. Overall, the current study provides empirical and theoretical insights into the relationship between prediction accuracy and feature importance reliability.

Correspondence of functional connectivity gradients across human isocortex, cerebellum, and hippocampus

Gradient mapping is an important technique to summarize high dimensional biological features as low dimensional manifold representations in exploring brain structure-function relationships at various levels of the cerebral cortex. While recent studies have characterized the major gradients of functional connectivity in several brain structures using this technique, very few have systematically examined the correspondence of such gradients across structures under a common systems-level framework. Using resting-state functional magnetic resonance imaging, here we show that the organizing principles of the isocortex, and those of the cerebellum and hippocampus in relation to the isocortex, can be described using two common functional gradients. We suggest that the similarity in functional connectivity gradients across these structures can be meaningfully interpreted within a common computational framework based on the principles of predictive processing. The present results, and the specific hypotheses that they suggest, represent an important step toward an integrative account of brain function.

Differential association of endothelial function with brain structure in youth with versus without bipolar disorder

BACKGROUND

Mood symptoms and disorders are associated with impaired endothelial function, a marker of early atherosclerosis. Given the increased vascular burden and neurostructural differences among individuals with mood disorders, we investigated the endothelial function and brain structure interface in relation to youth bipolar disorder (BD).

METHODS

This cross-sectional case-controlled study included 115 youth, ages 13-20 years (n = 66 BD; n = 49 controls [CG]). Cortical thickness and volume for regions of interest (ROI; insular cortex, ventrolateral prefrontal cortex [vlPFC], temporal lobe) were acquired from FreeSurfer processed T1-weighted MRI images. Endothelial function was assessed using pulse amplitude tonometry, yielding a reactive hyperemia index (RHI). ROI and vertex-wise analyses controlling for age, sex, obesity, and intracranial volume investigated for RHI-neurostructural associations, and RHI-by-diagnosis interactions.

RESULTS

In ROI analyses, higher RHI (i.e., better endothelial function) was associated with lower thickness in the insular cortex (β = -0.19, p_FDR = 0.03), vlPFC (β = -0.30, p_FDR = 0.003), and temporal lobe (β = -0.22, p_FDR = 0.01); and lower temporal lobe volume (β = -0.16, p_FDR = 0.01) in the overall sample. In vertex-wise analyses, higher RHI was associated with lower cortical thickness and volume in the insular cortex, prefrontal cortex (e.g., vlPFC), and temporal lobe. Additionally, higher RHI was associated with lower vlPFC and temporal lobe volume to a greater extent in youth with BD vs. CG.

CONCLUSIONS

Better endothelial function was associated with lower regional brain thickness and volume, contrasting the hypothesized associations. Additionally, we found evidence that this pattern was exaggerated in youth with BD. Future studies examining the direction of the observed associations and underlying mechanisms are warranted.