Structural Neuroimaging Research Articles

Changes in thalamic functional connectivity in post-Covid patients with and without fatigue

BackgroundFunctional brain alterations in post-Covid-19 condition have been minimally explored to date. Here, we investigate differences in resting-state thalamic functional connectivity among post-Covid patients with and without fatigue, alongside structural brain changes and cognition. MethodsThirty-nine post-Covid patients (n=15 fatigued, n=24 non-fatigued) participated in our study, undergoing comprehensive cognitive assessments, as well as functional and structural neuroimaging. We conducted a seed-based functional connectivity analysis using the thalamus as a seed region, exploring its connectivity with the entire brain. To further elucidate our findings, correlation analyses were performed using the functional coupling between the thalamus and regions showing different connectivity between the two patient groups. ResultsOur results reveal that patients experiencing fatigue exhibit anti-correlated functional coupling between the thalamus and motor-associated regions, including the motor cortex (M1), supplementary motor area (SMA), and anterior cingulate cortex (ACC), compared to non-fatigued patients, who are showing positive functional coupling. Furthermore, this observed coupling was found to correlate with both the fatigue scores obtained from a fatigue questionnaire and performance on the Trail Making Test, Part A, which represents a measure of processing speed. ConclusionsOur study highlights significant differences in resting-state functional connectivity between post-Covid patients with and without fatigue, particularly within motor-associated brain regions. These findings suggest a potential neural mechanism underlying post-Covid fatigue and underscore the importance of considering both functional and structural brain changes in understanding the symptomatic sequelae of post-Covid-19 condition. Further research is warranted to provide insight into the longitudinal trajectories of these neural alterations.

Neuroimaging correlates of cognitive disorders secondary to electroconvulsive therapy: A systematic review

ObjectivesElectroconvulsive therapy is known as an efficient therapy, which is sometimes recommended for the management of severe and resistant depression. However, ECT is associated with cognitive adverse effects. The study of the neurobiological correlates of the cognitive adverse effects of ECT has been covered in few published reviews. However, these mechanisms have been investigated in an increasing number of studies in recent years, particularly in neuroimaging. This systematic review of the literature focuses on correlates between changes in structural or functional neuroimaging and impairment of cognitive functions during the ECT treatment. MethodsWe conducted a systematic review of the literature using PRISMA methodology. Searches were performed on the Medline and Web of Science databases using the following equation: “electroconvulsive therapy AND (MRI OR fMRI OR DTI OR neuroimaging) AND depression AND cogniti*”. ResultsThis article highlights the significant heterogeneity of the results. In structural imaging, approximately 50% of the studies did not report any correlation between volumetric changes and neuropsychological changes. In studies that did highlight a correlation, the latter was mainly reported with changes in the hippocampus. From a functional perspective, we highlighted a correlation between changes in the connectivity of the hippocampal region and cognition. ConclusionThese results demonstrate a growing interest in understanding the neurobiological mechanisms underlying cognitive disorders secondary to ECT treatment. The ultimate aim behind this understanding is to adopt a more effective prevention strategy vis-à-vis these adverse effects.

Beyond Birth Control: The Neuroscience of Hormonal Contraceptives.

Hormonal contraceptives (HCs) are one of the most highly prescribed classes of drugs in the world used for both contraceptive and noncontraceptive purposes. Despite their prevalent use, the impact of HCs on the brain remains inadequately explored. This review synthesizes recent findings on the neuroscience of HCs, with a focus on human structural neuroimaging as well as translational, nonhuman animal studies investigating the cellular, molecular, and behavioral effects of HCs. Additionally, we consider data linking HCs to mood disorders and dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis and stress response as a potential mediator. The review also addresses the unique sensitivity of the adolescent brain to HCs, noting significant changes in brain structure and function when HCs are used during this developmental period. Finally, we discuss potential effects of HCs in combination with smoking-derived nicotine on outcomes of ischemic brain damage. Methodological challenges, such as the variability in HC formulations and user-specific factors, are acknowledged, emphasizing the need for precise and individualized research approaches. Overall, this review underscores the necessity for continued interdisciplinary research to elucidate the neurobiological mechanisms of HCs, aiming to optimize their use and improve women's health.

Neuroimaging in Clinical Practice: An Overview

Neuroimaging is a specialization of imaging technique that produce images of the brain or other parts of the Central Nervous System (CNS) in a noninvasive manner that directly or indirectly assess the structural or functional activity of the nervous system. Computed tomography (CT) and magnetic resonance imaging (MRI) are the most widely used modalities in routine clinical practice. Neuroimaging can be divided into two broad categories, namely, structural and functional neuroimaging. This article discusses the basics and applications of various traditional, as well as emerging neuroimaging techniques, considering their strengths and limitations with this rapidly expanding field. Bangladesh J Medicine 2024; 35: 147-155

Associations between structural neuroimaging markers of Alzheimer's risk and scam susceptibility.

Older adults with greater scam susceptibility are at greater risk for mild cognitive impairment and incident Alzheimer's dementia, regardless of baseline cognition. This, combined with documented associations between scam susceptibility and beta amyloid at death suggests that scam susceptibility may be an earlier indicator of pathological aging than cognition. Little, however, is known about whether in vivo neuroimaging markers of early-stage risk for Alzheimer's dementia are also related to scam susceptibility; such knowledge will inform upon the associations of neurodegenerative processes with scam susceptibility and may help identify vulnerable individuals. Participants were 472 community-based adults without dementia (age ~ 81y; 75% women) from the Rush Memory and Aging Project. Baseline 3T MRI T1-weighted structural and T2-weighted FLAIR data were used to assess the cortical thickness 'signature' of Alzheimer's disease (AD-CT) and white matter hyperintensity (WMH) burden, respectively. Scam susceptibility was measured using a questionnaire that assessed behaviors associated with vulnerability to fraud and scams. Demographically-adjusted linear effects regression models determined the relationship of each neuroimaging measure, first separately and then combined, with scam susceptibility. Reduced AD-CT was associated with higher levels of scam susceptibility (estimate=-0.10, standard error = 0.03, p = 0.002). WMH burden was not associated with scam susceptibility either alone or when combined in the same model as AD-CT (p-values ≥ 0.14). Results for AD-CT persisted after the inclusion of WMH burden. AD-CT was associated with scam susceptibility in older adults without dementia possibly signaling an in vivo profile of this behavior.

Neural correlates of harm avoidance: a multimodal meta-analysis of brain structural and resting-state functional neuroimaging studies

Harm avoidance (HA) is a Cloninger personality trait that describes behavioural inhibition to avoid aversive stimuli. It serves as a predisposing factor that contributes to the development of mental disorders such as anxiety and major depressive disorder. Neuroimaging research has identified some brain anatomical and functional correlates of HA, but reported findings are inconsistent. We therefore conducted a multimodal meta-analysis of whole-brain structural and resting-state functional neuroimaging studies to identify the most stable neural substrate of HA. Included were a total of 10 structural voxel-based morphometry studies (11 datasets) and 13 functional positron emission tomography or single photon emission computed tomography studies (16 datasets) involving 3053 healthy participants without any psychiatric or neurological disorders evaluated for HA using the Three-Dimensional Personality Questionnaire (TPQ) or the Temperament and Character Inventory (TCI). The meta-analysis revealed brain volumetric correlates of HA in parietal and temporal cortices, and resting-state functional correlates in prefrontal, temporal and parietal gray matter. Volumetric and functional correlates co-occurred in the left superior frontal gyrus and left middle frontal gyrus, and were dissociated in the left rectus gyrus. Our meta-analysis is the first study to give a comprehensive picture of the structural and functional correlates of HA, a contribution that may help bridge the grievous gap between the neurobiology of HA and the pathogenesis, prevention and treatment of HA-related mental disorders.

Understanding Depression in Autism: The Role of Subjective Perception and Anterior Cingulate Cortex Volume.

The prevalence of depression is elevated in individuals with autism spectrum disorder (ASD) compared to the general population, yet the reasons for this disparity remain unclear. While social deficits central to ASD may contribute to depression, it is uncertain whether social interaction behavior themselves or individuals' introspection about their social behaviors are more impactful. Although the anterior cingulate cortex (ACC) and amygdala are frequently implicated in ASD, depression, and social functioning, it is unknown if these regions explain differences between ASD adults with and without co-occurring depression. The present study contrasted observed vs. subjective perception of autism symptoms and social performances assessed with both standardized measures and a lab task, in 65 sex-balanced (52.24% male) autistic young adults. We also quantified ACC and amygdala volume with 7-Tesla structural neuroimaging to examine correlations with depression and social functioning. We found that ASD individuals with depression exhibited differences in subjective evaluations including heightened self-awareness of ASD symptoms, lower subjective satisfaction with social relations, and less perceived affiliation during the social interaction task, yet no differences in corresponding observed measures, compared to those without depression. Larger ACC volume was related to depression, greater self-awareness of ASD symptoms, and worse subjective satisfaction with social interactions. In contrast, amygdala volume, despite its association with clinician-rated ASD symptoms, was not related to depression. Due to the cross-sectional nature of our study, we cannot determine the directionality of the observed relationships. Additionally, we included only individuals with an IQ over 60 to ensure participants could complete the social task, which excluded many on the autism spectrum. We also utilized self-reported depression indices instead of clinically diagnosed depression, which may limit the comprehensiveness of the findings. Our approach highlights the unique role of subjective perception of autism symptoms and social interactions, beyond the observable manifestation of social interaction in ASD, in contributing to depression, with the ACC playing a crucial role. These findings imply possible heterogeneity of ASD concerning co-occurring depression. Using neuroimaging, we were able to demarcate depressive phenotypes co-occurring alongside autistic phenotypes.

Children’s exposure to chemical contaminants: Demographic disparities and associations with the developing basal ganglia

Children are regularly exposed to chemical contaminants that may influence brain development. However, relatively little is known about how these contaminants impact the developing human brain. Here, we combined silicone wristband exposure assessments with neuroimaging for the first time to examine how chemical contaminant mixtures are associated with the developing basal ganglia—a brain region key for the healthy development of emotion, reward, and motor processing, and which may be particularly susceptible to contaminant harm. Further, we examined demographic disparities in exposures to clarify which children were at highest risk for any contaminant-associated neurobiological changes. Participants included 62 community children (average age 7.00 years, 53% female, 66% White) who underwent structural neuroimaging to provide data on their basal ganglia structure and wore a silicone wristband for seven days to track their chemical contaminant exposure. 45 chemical contaminants—including phthalates and their alternatives, brominated flame retardants, organophosphate esters, pesticides, polycyclic aromatic hydrocarbons, and polychlorinated biphenyls—were detected in over 75% of wristbands. Notable demographic disparities in exposure were present, such that Non-White and lower-income children were more exposed to several contaminants. Exposure to chemical contaminant mixtures was not associated with overall basal ganglia volume; however, two organophosphate esters (2IPPDPP and 4IPPDPP) were both associated with a larger globus pallidus, a basal ganglia sub-region. Results highlight demographic disparities in exposure and suggest possible risks to a brain region key for healthy emotional development.

Free-water: A promising structural biomarker for cognitive decline in aging and mild cognitive impairment.

Diffusion MRI derived free-water (FW) metrics show promise in predicting cognitive impairment and decline in aging and Alzheimer's disease (AD). FW is sensitive to subtle changes in brain microstructure, so it is possible these measures may be more sensitive than traditional structural neuroimaging biomarkers. In this study, we examined the associations among FW metrics (measured in the hippocampus and two AD signature meta-ROIs) with cognitive performance, and compared FW findings to those from more traditional neuroimaging biomarkers of AD. We leveraged data from a longitudinal cohort (nparticipants = 296, nobservations = 870, age at baseline: 73 ± 7 years, 40% mild cognitive impairment [MCI]) of older adults who underwent serial neuropsychological assessment (episodic memory, information processing speed, executive function, language, and visuospatial skills) and brain MRI over a maximum of four time points, including baseline (n = 284), 18-month (n = 246), 3-year (n = 215), and 5-year (n = 125) visits. The mean follow-up period was 2.8 ± 1.3 years. Structural MRI was used to quantify hippocampal volume, in addition to Schwarz and McEvoy AD Signatures. FW and FW-corrected fractional anisotropy (FAFWcorr) were quantified in the hippocampus (hippocampal FW) and the AD signature areas (SchwarzFW, McEvoyFW) from diffusion-weighted (dMRI) images using bi-tensor modeling (FW elimination and mapping method). Linear regression assessed the association of each biomarker with baseline cognitive performance. Additionally, linear mixed-effects regression assessed the association between baseline biomarker values and longitudinal cognitive performance. A subsequent competitive model analysis was conducted on both baseline and longitudinal data to determine how much additional variance in cognitive performance was explained by each biomarker compared to the covariate only model, which included age, sex, race/ethnicity, apolipoprotein-ε4 status, cognitive status, and modified Framingham Stroke Risk Profile scores. All analyses were corrected for multiple comparisons using an FDR procedure. Cross-sectional results indicate that hippocampal volume, hippocampal FW, Schwarz and McEvoy AD Signatures, and the SchwarzFW and McEvoyFW metrics are all significantly associated with memory performance. Baseline competitive model analyses showed that the McEvoy AD Signature and SchwarzFW explain the most unique variance beyond covariates for memory (ΔRadj 2 = 3.47 ± 1.65%) and executive function (ΔRadj 2 = 2.43 ± 1.63%), respectively. Longitudinal models revealed that hippocampal FW explained substantial unique variance for memory performance (ΔRadj 2 = 8.13 ± 1.25%), and outperformed all other biomarkers examined in predicting memory decline (pFDR = 1.95 x 10-11). This study shows that hippocampal FW is a sensitive biomarker for cognitive impairment and decline, and provides strong evidence for further exploration of this measure in aging and AD.

Association between Neural Plasticity and Pain-Related Fear in Chronic Ankle Instability: A Structural Neuroimaging Study.

Pain-related movement fear is a contributing factor to residual pain and functional deficits in chronic ankle instability (CAI), but its underlying neural mechanisms remain unclear. We aimed to (1) delineate whether participants with CAI exhibit discernible differences in specific emotion and pain-related brain regions, compared to a healthy control (HC) cohort and (2) explore potential neural mechanisms underlying pain and fear in participants with CAI, with an emphasis on investigating possible associations with pain-related neural plasticity. Cross-sectional study. University research laboratory. 28 participants with CAI (17males and 11 females; age: 31.28±6.31 years) and 28 HCs (16 males and 12 females; age: 30.18±7.59 years). We analyzed T1 structural imaging data from participants and assessed their fear of movement and pain intensity using the Tampa Scale for Kinesiophobia (TSK) and the Visual Analog Scale (VAS) for pain, respectively. We compared the mean gray matter (GM) density of pain-related area between the two groups and their correlations with the TSK and VAS scores. In comparison with the HC group, participants with CAI showed a significant decrease in the mean GM density in the prefrontal cortex (Cohen's d = -0.808) and periaqueductal gray (Cohen's d = -0.934). In participants with CAI, the mean GM density of the prefrontal cortex (PFC) was negatively correlated with the TSK scores (r = -0.531). During intense exercise, the mean GM density of the periaqueductal gray (PAG) was negatively correlated with the VAS scores (r = -0.484). Additionally, TSK scores were positively correlated with VAS scores (r = 0.455). Our exploratory findings suggest that, in participants with CAI, the atrophy of the PFC and PAG may be associated with pain-related fear. Future clinical diagnosis and treatment for CAI should consider the impact of psychological barriers on functional recovery.

Frontotemporal lobar degeneration targets brain regions linked to expression of recently evolved genes.

In frontotemporal lobar degeneration (FTLD), pathological protein aggregation in specific brain regions is associated with declines in human-specialized social-emotional and language functions. In most patients, disease protein aggregates contain either TDP-43 (FTLD-TDP) or tau (FTLD-tau). Here, we explored whether FTLD-associated regional degeneration patterns relate to regional gene expression of human accelerated regions (HARs), conserved sequences that have undergone positive selection during recent human evolution. To this end, we used structural neuroimaging from patients with FTLD and human brain regional transcriptomic data from controls to identify genes expressed in FTLD-targeted brain regions. We then integrated primate comparative genomic data to test our hypothesis that FTLD targets brain regions linked to expression levels of recently evolved genes. In addition, we asked whether genes whose expression correlates with FTLD atrophy are enriched for genes that undergo cryptic splicing when TDP-43 function is impaired. We found that FTLD-TDP and FTLD-tau subtypes target brain regions with overlapping and distinct gene expression correlates, highlighting many genes linked to neuromodulatory functions. FTLD atrophy-correlated genes were strongly enriched for HARs. Atrophy-correlated genes in FTLD-TDP showed greater overlap with TDP-43 cryptic splicing genes and genes with more numerous TDP-43 binding sites compared with atrophy-correlated genes in FTLD-tau. Cryptic splicing genes were enriched for HAR genes, and vice versa, but this effect was due to the confounding influence of gene length. Analyses performed at the individual-patient level revealed that the expression of HAR genes and cryptically spliced genes within putative regions of disease onset differed across FTLD-TDP subtypes. Overall, our findings suggest that FTLD targets brain regions that have undergone recent evolutionary specialization and provide intriguing potential leads regarding the transcriptomic basis for selective vulnerability in distinct FTLD molecular-anatomical subtypes.

Probing connections between social connectedness, mortality risk, and brain age: A preregistered study.

Many lifestyle and psychosocial factors are associated with a longer lifespan; central among these is social connectedness, or the feeling of belongingness, identification, and bond as part of meaningful human relationships. Decades of research have established that social connectedness is related not only to better mental health (e.g., less loneliness and depression) but also to improved physical health (e.g., decreased inflammatory markers, reduced cortisol activity). Recent methodological advances allow for the investigation of a novel marker of biological health by deriving a predicted "age of the brain" from a structural neuroimaging scan. Discrepancies between a person's algorithm-predicted brain-age and chronological age (i.e., the brain-age gap) have been found to predict mortality and psychopathology risk with accuracy rivaling other known measures of aging. This preregistered investigation uses the Midlife in the United States (MIDUS) study to examine connections between the quality of social connections, the brain-age gap, and markers of mortality risk to understand the longevity-promoting associations of social connectedness from a novel biological vantage point. While social connectedness was associated with markers of mortality risk (number of chronic conditions and ability to perform activities of daily living), our models did not find significant links between social connectedness and the brain-age gap, or the brain-age gap and mortality risk. Supplemental and sensitivity analyses suggest alternate approaches to investigating these associations and overcoming limitations. While plentiful evidence underscores that being socially connected is good for the mind, future research should continue to consider whether it impacts neural markers of aging and longevity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Connectivity of the Piriform Cortex and its Implications in Temporal Lobe Epilepsy.

The piriform cortex has been implicated in the initiation, spread and termination of epileptic seizures. This understanding has extended to surgical management of epilepsy, where it has been shown that resection or ablation of the piriform cortex can result in better outcomes. How and why the piriform cortex may play such a crucial role in seizure networks is not well understood. To answer these questions, we investigated the functional and structural connectivity of the piriform cortex in both healthy controls and temporal lobe epilepsy (TLE) patients. We studied a retrospective cohort of 55 drug-resistant unilateral TLE patients and 26 healthy controls who received structural and functional neuroimaging. Using seed-to-voxel connectivity we compared the normative whole-brain connectivity of the piriform to that of the hippocampus, a region commonly involved in epilepsy, to understand the differential contribution of the piriform to the epileptogenic network. We subsequently measured the inter-piriform coupling (IPC) to quantify similarities in the inter-hemispheric cortical functional connectivity profile between the two piriform cortices. We related differences in IPC in TLE back to aberrations in normative piriform connectivity, whole brain functional properties, and structural connectivity. We find that relative to the hippocampus, the piriform is functionally connected to the anterior insula and the rest of the salience ventral attention network (SAN). We also find that low IPC is a sensitive metric of poor surgical outcome (sensitivity: 85.71%, 95% CI: [19.12%, 99.64%]); and differences in IPC within TLE were related to disconnectivity and hyperconnectivity to the anterior insula and the SAN. More globally, we find that low IPC is associated with whole-brain functional and structural segregation, marked by decreased functional small-worldness and fractional anisotropy. Our study presents novel insights into the functional and structural neural network alterations associated with this structure, laying the foundation for future work to carefully consider its connectivity during the presurgical management of epilepsy.

Unraveling the Potential Underlying Mechanisms of Mild Behavioral Impairment: Focusing on Amyloid and Tau Pathology.

The emergence of sustained neuropsychiatric symptoms (NPS) among non-demented individuals in later life, defined as mild behavioral impairment (MBI), is linked to a higher risk of cognitive decline. However, the underlying pathophysiological mechanisms remain largely unexplored. A growing body of evidence has shown that MBI is associated with alterations in structural and functional neuroimaging studies, higher genetic predisposition to clinical diagnosis of Alzheimer's disease (AD), as well as amyloid and tau pathology assessed in the blood, cerebrospinal fluid, positron-emission tomography (PET) imaging and neuropathological examination. These findings shed more light on the MBI-related potential neurobiological mechanisms, paving the way for the development of targeted pharmacological approaches. In this review, we aim to discuss the available clinical evidence on the role of amyloid and tau pathology in MBI and the potential underlying pathophysiological mechanisms. Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, disruption of neurotrophic factors, such as the brain-derived neurotrophic factor (BDNF), abnormal neuroinflammatory responses including the kynurenine pathway, dysregulation of transforming growth factor beta (TGF-β1), epigenetic alterations including micro-RNA (miR)-451a and miR-455-3p, synaptic dysfunction, imbalance in neurotransmitters including acetylcholine, dopamine, serotonin, gamma-aminobutyric acid (GABA) and norepinephrine, as well as altered locus coeruleus (LC) integrity are some of the potential mechanisms connecting MBI with amyloid and tau pathology. The elucidation of the underlying neurobiology of MBI would facilitate the design and efficacy of relative clinical trials, especially towards amyloid- or tau-related pathways. In addition, we provide insights for future research into our deeper understanding of its underlying pathophysiology of MBI, and discuss relative therapeutic implications.

The Future of Neurodiagnosis: Deep Learning for Earlier Intervention

This study presents an innovative deep learning framework for improved early detection of a debilitating neurodegenerative condition marked by cognitive decline and memory impairment. Timely diagnosis is crucial for effective interventions and improved patient outcomes. Our framework integrates diverse data sources, including structural and functional neuroimaging (MRI and PET) alongside clinical information, to enhance detection precision. Convolutional Neural Networks (CNNs) analyze structural MRI scans, extracting subtle changes in brain structure indicative of early disease progression. Functional insights are gleaned from PET scans, contributing to increased sensitivity. Additionally, longitudinal data is incorporated through Recurrent Neural Networks (RNNs) to capture the disease's temporal evolution. Training on a diverse dataset utilizes transfer learning, optimizing performance even with limited labeled data. Rigorous validation consistently demonstrates the model's effectiveness, achieving a 92% accuracy rate.

Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery

Background The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight. Objective To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual’s early post-stroke. Methods Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined. Results Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively. Conclusions This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.

Structural Brain Differences in the Alzheimer’s Disease Continuum: Insights Into the Heterogeneity From a Large Multisite Neuroimaging Consortium

BackgroundNeurodegenerative diseases require collaborative, multisite research to comprehensively grasp their complex and diverse pathological progression; however, there is caution in aggregating global data due to data heterogeneity. In the current study, we investigated brain structure across stages of Alzheimer’s disease (AD) and how relationships vary across sources of heterogeneity. MethodsUsing 6 international datasets (n > 27,000), associations of structural neuroimaging markers were investigated in relation to the AD continuum via meta-analysis. We investigated whether associations varied across elements of magnetic resonance imagingacquisition, study design, and populations. ResultsModest differences in associations were found depending on how data were acquired; however, patterns were similar. Preliminary results suggested that neuroimaging marker–AD relationships differ across ethnic groups. ConclusionsDiversity in data offers unique insights into the neural substrate of AD; however, harmonized processing and transparency of data collection are needed. Global collaborations should embrace the inherent heterogeneity that exists in the data and quantify its contribution to research findings at the meta-analytical stage.

Association of Metabolic Syndrome With Neuroimaging and Cognitive Outcomes in the UK Biobank.

Metabolic syndrome (MetS) has been linked to dementia. In this study, we examined the association of MetS with neuroimaging and cognition in dementia-free adults, offering insight into the impact of MetS on brain health prior to dementia onset. We included 37,395 dementia-free adults from the UK Biobank database. MetS was defined as having at least three of the following components: larger waist circumference; elevated levels of triglycerides, blood pressure, HbA1c; or reduced HDL cholesterol levels. Multivariable-adjusted linear regression was used to assess associations of MetS with structural neuroimaging and cognitive domains. MetS was associated with lower total brain (standardized β: -0.06; 95% CI -0.08, -0.04), gray matter (β: -0.10; 95% CI -0.12, -0.08) and hippocampal (for left side, β: -0.03, 95% CI -0.05, -0.01; for right side, β: -0.04, 95% CI -0.07, -0.02) volumes, and greater white matter hyperintensity (WMH) volume (β: 0.08; 95% CI 0.06, 0.11). Study participants with MetS performed poorer on cognitive tests of working memory (β: -0.10; 95% CI -0.13, -0.07), verbal declarative memory (β: -0.08; 95% CI -0.11, -0.05), processing speed (β: -0.06; 95% CI -0.09, -0.04), verbal and numerical reasoning (β: -0.07; 95% CI -0.09, -0.04), nonverbal reasoning (β: -0.03; 95% CI -0.05, -0.01), and on tests of executive function, where higher scores indicated poorer performance (β: 0.05; 95% CI 0.03, 0.08). More MetS components were also associated with less brain volume, greater WMH, and poorer cognition across all domains. MetS was associated poorer brain health in dementia-free adults, characterized by less brain volume, greater vascular pathology, and poorer cognition. Further research is necessary to understand whether reversal or improvement of MetS can improve brain health.

Analyzing fractal dimension in electroconvulsive therapy: Unraveling complexity in structural and functional neuroimaging

BackgroundNumerous studies show that electroconvulsive therapy (ECT) induces hippocampal neuroplasticity, but findings are inconsistent regarding its clinical relevance. This study aims to investigate ECT-induced plasticity of anterior and posterior hippocampi using mathematical complexity measures in neuroimaging, namely Higuchi's fractal dimension (HFD) for fMRI time series and the fractal dimension of cortical morphology (FD-CM). Furthermore, we explore the potential of these complexity measures to predict ECT treatment response. MethodsTwenty patients with a current depressive episode (16 with major depressive disorder and 4 with bipolar disorder) underwent MRI-scans before and after an ECT-series. Twenty healthy controls matched for age and sex were also scanned twice for comparison purposes. Resting-state fMRI data were processed, and HFD was computed for anterior and posterior hippocampi. Group-by-time effects for HFD in anterior and posterior hippocampi were calculated and correlations between HFD changes and improvement in depression severity were examined. For FD-CM analyses, we preprocessed structural MRI with CAT12′s surface-based methods. We explored group-by-time effects for FD-CM and the predictive value of baseline HFD and FD-CM for treatment outcome. ResultsPatients exhibited a significant increase in bilateral hippocampal HFD from baseline to follow-up scans. Right anterior hippocampal HFD increase was associated with reductions in depression severity. We found no group differences and group-by-time effects in FD-CM. After applying a whole-brain regression analysis, we found that baseline FD-CM in the left temporal pole predicted reduction of overall depression severity after ECT. Baseline hippocampal HFD did not predict treatment outcome. ConclusionThis study suggests that HFD and FD-CM are promising imaging markers to investigate ECT-induced neuroplasticity associated with treatment response.

Integrative molecular and structural neuroimaging analyses of the interaction between depression and age of onset: A multimodal magnetic resonance imaging study

Depression is a neurodevelopmental disorder that exhibits progressive gray matter volume (GMV) atrophy. Research indicates that brain development is influential in depression-induced GMV alterations. However, the interaction between depression and age of onset is not well understood by the underlying molecular and neuropathological mechanisms. Thus, 152 first-episode depression individuals and matched 130 healthy controls (HCs) were recruited to undergo T1-weighted high-resolution magnetic resonance imaging for this study. By two-way ANOVA, age and diagnosis were used as factors when analyzing the interaction of GMV in the participants. Then, spatial correlations between neurotransmitter maps and factor-related volume maps are established. Results illustrate a pronounced antagonistic interaction between depression and age of onset in the right insula, superior temporal gyrus, anterior cingulate gyrus, and orbitofrontal gyrus. Depression-caused reductions in GMV are mainly distributed in thalamic-limbic-cortical regions, regardless of age. For the main effect of age, adults exhibit brain atrophy in frontal, cerebellum, parietal, and temporal lobe structures. Cross-modal correlations showed that GMV changes in the interactive regions were linked with the serotonergic system and dopaminergic systems. Summarily, our results reveal the interaction between depression and age of onset in neurobiological mechanisms, which provide hints for future treatment of different ages of depression.