Gray Matter Reduction Research Articles

Abnormal changes of brain function and structure in patients with T2DM-related cognitive impairment: a neuroimaging meta-analysis and an independent validation.

Type 2 diabetes mellitus (T2DM) seriously threatens human health and the quality of life, cognitive impairment is considered as a common complication of T2DM. Neuroimaging meta-analysis found brain functional and structural abnormality in patients with T2DM. Therefore, the purpose of the meta-analysis was to identify brain regions of patients with T2DM-related cognitive impairment (T2DM-CI) where functional and structural indicators changed together or could not synchronize. A literature screening of neuroimaging studies on cognitive impairment in T2DM was conducted from 1 January 2007 to 26 May 2023 in PubMed, Web of Science, Cochrane Library, and Medline databases. The functional indicators we studied were amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and degree centrality (DC), while the structural indicator was gray matter (GM), which included gray matter volume (GMV) and cerebral cortical thickness. Studies reporting ALFF, ReHo, DC and GM abnormalities between T2DM-CI and healthy controls (HCs) were selected and their significant peak coordinates (x, y, z) and effect size (t-value) were extracted to perform a meta-analysis using anisotropic effect size sign differential mapping (AES-SDM) 5.15 software. Moreover, the brain regions with significant differences obtained from meta-analysis were saved as masks and then validated in our data. Total 19 studies and 20 datasets were involved in this study. Compared to HCs, combining ALFF, ReHo, and DC measurements, the brain activity of the left anterior cingulate/paracingulate gyri (ACC.L, BA24) in T2DM-CI patients increased significantly, while the brain activity of the left lingual gyrus (LING.L, BA18) in T2DM-CI patients decreased significantly. The GM indicator of the right superior temporal gyrus (STG.R, BA42) and left inferior occipital gyrus (IOG.L, BA19) in T2DM-CI patients decreased significantly. Meta-regression analysis showed the negative relationship between the brain activity reduction in LING.L and the percentage of female patients, as well as the negative relationship between GM reduction in IOG.L and T2DM duration. Furthermore, we validated a decrease in brain activity in the LING.L of T2DM-CI patients in our independent dataset. The decrease of brain activity in LING.L and the decrease of GM in IOG.L were closely related to visual impairment in T2DM-CI patients. These abnormal brain regions may be the main targets for future research, early intervention can delay the further development of cognitive impairment in T2DM patients and improve their quality of life, which also provided early biomarkers for clarifying the mechanism of cognitive impairment in T2DM.

Temporal Lobe Epilepsy Focus Detection Based on the Correlation Between Brain MR Images and EEG Recordings with a Decision Tree

Background/Objectives: In this study, a medical decision support system is presented to assist physicians in epileptic focus detection by correlating MRI and EEG data of temporal lobe epilepsy patients. Methods: By exploiting the asymmetry in the hippocampus in MRI images and using voxel-based morphometry analysis, gray matter reduction in the temporal and limbic lobes is detected, and epileptic focus prediction is realized. In addition, an epileptic focus is also determined by calculating the asymmetry score from EEG channels. Finally, epileptic focus detection was performed by associating MRI and EEG data with a decision tree. Results: The results obtained from the proposed algorithm provide 100% overlap with the physician’s finding on the EEG data. Conclusions: MRI and EEG correlation in epileptic focus detection was improved compared with physicians. The proposed algorithm can be used as a medical decision support system for epilepsy diagnosis, treatment, and surgery planning.

Mapping computational cognitive profiles of aging to dissociable brain and sociodemographic factors

Aging is associated with declines in cognition and brain structural integrity. However, there is equivocality over (1) the specificity of affected domains in different people, (2) the location of associated patterns of brain structural deterioration, and (3) the sociodemographic factors contributing to ‘unhealthy’ cognition. We aimed to identify cognitive profiles displayed by older adults and determine brain and sociodemographic features potentially shaping these profiles. A sample of Southeast-Asian older adults (N = 386) participated in a multi-session study comprising cognitive testing, neuroimaging, and a structured interview. We used computational models to extract latent mechanisms underlying cognitive flexibility and response inhibition. Data-driven methods were used to construct cognitive profiles based on standard performance measures and model parameters. We also investigated grey matter volume and machine-learning derived ‘brain-ages’. A profile associated with poor set-shifting and rigid focusing was associated with widespread grey matter reduction in cognitive control regions. A slow responding profile was associated with advanced brain-age. Both profiles were correlated with poor socioeconomic standing and cognitive reserve. We found that the impact of sociodemographic factors on cognitive profiles was partially mediated by total grey and white matter, and dorsolateral prefrontal and cerebellar volumes. This study furthers understanding of how distinct aging profiles of cognitive impairment uniquely correspond to specific vs. global brain deterioration and the significance of socioeconomic factors in informing cognitive performance in older age.

The effect of alemtuzumab on neurodegeneration in relapsing-remitting multiple sclerosis: A five-year prospective mono-center study

BackgroundRelapsing-remitting multiple sclerosis (RRMS) is an inflammatory and neurodegenerative disease. After two or more short courses of alemtuzumab (ALZ), an immune reconstitution is achieved, which long-term results in reduced disease activity. We aimed to investigate the effect of ALZ on measures of neurodegeneration (i.e., brain atrophy, and retinal layer thinning). MethodsWe designed an observational prospective mono-center study in RRMS patients initiating ALZ treatment. Patients were assessed at baseline (month 0) and thereafter annually for five years with clinical measures, synthetic magnetic resonance imaging (SyMRI) and optical coherence tomography (OCT), with a re-baseline SyMRI scan and an OCT exam 24 months after initiating ALZ. Persons with neurological symptoms but without evidence of neurological disease served as symptomatic controls (SCs, n = 27). ResultsForty-nine RRMS patients were included. Baseline median expanded disability status scale [2.0 (IQR 1.5)] was unchanged during follow-up, 71 % were progression-free, 33 % achieved no evidence of disease activity-3 (NEDA-3). Between baseline and month 60, SyMRI showed a reduction of brain parenchymal fraction (BPF) and grey matter (GM) volume in patients. The BPF reduction was greater in RRMS patients than in SCs (p < 0.05), and more pronounced in patients with high pre-baseline disease activity than in those without (p < 0.01). OCT showed significant thinning of macular ganglion cell and inner plexiform layers (mGCIPL) and in peripapillary retinal nerve fiber layer (pRNFL) in patients. In contrast, absolute values of white matter (WM) volume and myelin content (MyC) quantified by SyMRI, were stable or increased after re-baseline (month 24) and up to month 60, and this increase appeared limited to patients without high pre-baseline disease activity and to patients with NEDA-3 or disability worsening during follow-up. A strong positive correlation between WM volume and GM volume at baseline was lost after ALZ intervention for their delta values, i.e., change from re-baseline (month 24) to month 60. While the positive baseline correlation between WM volume and MyC increased for their delta values, the positive baseline correlation between GM volume and MyC changed to negative for their delta values. ConclusionWe showed that neurodegeneration continued in RRMS patients under ALZ treatment, but it appeared to be limited to BPF and GM, and more pronounced in patients with disease activity. Our data suggest that patients who respond to ALZ treatment show signs of remyelination. OCT and SyMRI have potential to quantify measures of neurodegeneration that is affected by treatment intervention in RRMS.

Progressive gray matter atrophy in parkinsonian variant of multiple system atrophy assessed by using causal structural covariance network.

Multiple system atrophy (MSA), a rare neurodegenerative disease, is usually accompanied by brain morphological alterations. However, the causal relationships between progressive gray matter atrophy in MSA parkinsonian (MSA-P) subtype remain unknown. In total, thirty-five MSA-P patients and thirty-five healthy controls (HC) underwent three-dimensional high-resolution T1-weighted structural imaging and voxel-based morphometry analysis. The causal structural covariance network (CaSCN) of gray matter was assessed to explore the causal relationships in MSA-P. With greater illness duration, the reduction of gray matter was originated from right cerebellum and progressed to bilateral cerebellum, fusiform gyrus, insula, putamen, caudate nucleus, frontal lobe, right angular gyrus, right precuneus, left middle occipital lobe and left inferior temporal lobe, then expanded to midbrain, bilateral para-hippocampus, thalamus, temporal lobe, inferior parietal lobule (IPL), precentral gyrus, postcentral gyrus and middle cingulate cortex. The right cerebellum was revealed to be the core node of the directional network and projected positive causal effects to bilateral cerebellum, caudate nucleus and left IPL. MSA-P patients showed progression of gray matter atrophy over time, with the right cerebellum probably as a primary hub. Furthermore, the early structural vulnerability of cerebellum in MSA-P may play a pivotal role in the modulation of motor and non-motor circuits at the structural level.

Associations between Parenting and Cognitive and Language Abilities at 2 Years of Age Depend on Prenatal Exposure to Disadvantage

To investigate whether parenting or neonatal brain volumes mediate associations between prenatal social disadvantage (SD) and cognitive/language abilities and whether these mechanisms vary by level of disadvantage. Pregnant women were prospectively recruited from obstetric clinics in St Louis, Missouri. Prenatal SD encompassed access to social (eg, education) and material (eg, income-to-needs, health insurance, area deprivation, and nutrition) resources during pregnancy. Neonates underwent brain magnetic resonance imaging. Mother-child dyads (N=202) returned at age 1-year for parenting observations and at age 2-years for cognition/language assessments (Bayley-III). Generalized additive and mediation models tested hypotheses. Greater prenatal SD associated nonlinearly with poorer cognitive/language scores. Associations between parenting and cognition/language were moderated by disadvantage, such that supportive and non-supportive parenting behaviors related only to cognition/language in children with lesser prenatal SD. Parenting mediation effects differed by level of disadvantage: both supportive and non-supportive parenting mediated prenatal SD-cognition/language associations in children with lesser disadvantage, but not in children with greater disadvantage. Prenatal SD-associated reductions in neonatal subcortical grey matter (β=.19, q=.03), white matter (β=.23, q=.02), and total brain volume (β=.18, q=.03) were associated with lower cognition, but did not mediate associations between prenatal SD and cognition. Parenting moderates and mediates associations between prenatal SD and early cognition and language, but only in families with less social disadvantage. These findings, although correlational, suggest that there may be a critical threshold of disadvantage, below which mediating or moderating factors become less effective, highlighting the importance of reducing disadvantage as primary prevention.

Gray matter volume of the feline cerebral cortex and structural plasticity following perinatal deafness

In response to sensory deprivation, the brain adapts according to contemporary demands to efficiently navigate a modified perceptual environment. This reorganization may result in improved processing of the remaining senses–a phenomenon referred to as compensatory crossmodal plasticity. One approach to explore this neuroplasticity is to consider the macrostructural changes in neural tissue that mirror this functional optimization. The current study is the first of its kind to measure MRI-derived gray matter (GM) volumes of control felines (n=30), while additionally identifying volumetric differences in response to perinatal deafness (30 ototoxically-deafened cats). To accomplish this purpose, regional and morphometric methods were performed in parallel. The regional analysis evaluated volumetric alterations of global GM, as well as the volumes of 146 regions of interest (ROIs) and 12 functional subgroupings of these ROIs. Results revealed whole-brain GM preservation; however, somatosensory and visual cortices exhibited an overall increase in volume. On a smaller scale, this analysis uncovered two auditory ROIs (second auditory cortex, A2, and ventral auditory field, VAF) that decreased in volume alongside two visual regions (anteromedial lateral suprasylvian area, AMLS and splenial visual area, SVA) that increased–all localized within the right hemisphere. Comparatively, the findings of tensor-based morphometry (TBM) generally aligned with those of the ROI-based method, as this voxel-wise approach demonstrated clusters of expansion coincident with visual- and somatosensory-related loci; although, it failed to detect any GM reductions following deafness. As distinct differences were identified in each analysis, the current study highlights the importance of employing multiple methods when exploring MRI volumetry. Overall, this study proposes that volumetric alterations within sensory loci allude to a redistribution of cortical space arising from modified perceptual demands following auditory deprivation.

Cortical lobar volume reductions associated with homocysteine-related subcortical brain atrophy and poorer cognition in healthy aging.

Homocysteine (Hcy) is a cardiovascular risk factor implicated in cognitive impairment and cerebrovascular disease but has also been associated with Alzheimer's disease. In 160 healthy older adults (mean age = 69.66 ± 9.95 years), we sought to investigate the association of cortical brain volume with white matter hyperintensity (WMH) burden and a previously identified Hcy-related multivariate network pattern showing reductions in subcortical gray matter (SGM) volumes of hippocampus and nucleus accumbens with relative preservation of basal ganglia. We additionally evaluated the potential role of these brain imaging markers as a series of mediators in a vascular brain pathway leading to age-related cognitive dysfunction in healthy aging. We found reductions in parietal lobar gray matter associated with the Hcy-SGM pattern, which was further associated with WMH burden. Mediation analyses revealed that slowed processing speed related to aging, but not executive functioning or memory, was mediated sequentially through increased WMH lesion volume, greater Hcy-SGM pattern expression, and then smaller parietal lobe volume. Together, these findings suggest that volume reductions in parietal gray matter associated with a pattern of Hcy-related SGM volume differences may be indicative of slowed processing speed in cognitive aging, potentially linking cardiovascular risk to an important aspect of cognitive dysfunction in healthy aging.

Regional gray matter changes in steatotic liver disease provide a neurobiological link to depression: A cross-sectional UK Biobank cohort study

BackgroundSteatotic liver disease (SLD) is characterized by excessive accumulation of lipids in the liver. It is associated with elevated risk of hepatic and cardiometabolic diseases, as well as mental disorders such as depression. Previous studies revealed global gray matter reduction in SLD. To investigate a possible shared neurobiology with depression, we examined liver fat-related regional gray matter alterations in SLD and its most significant clinical subgroup metabolic dysfunction-associated steatotic liver disease (MASLD). MethodsWe analyzed regional cortical thickness and area obtained from brain MRI in 29,051 participants in UK Biobank. Liver fat amount was computed as proton density fat fraction (PDFF) from liver MRI scans. We examined the relationship between brain structure and PDFF, adjusting for sociodemographic, physical, lifestyle, and environmental factors, as well as alcohol intake and a spectrum of cardiometabolic covariates. Finally, we compared patterns of brain alterations in SLD/MASLD and major depressive disorder (MDD) using previously published results. ResultsPDFF-related gray matter alterations were region-specific, involving both increases and decreases in cortical thickness, and increased cortical area. In several regions, PDFF effects on gray matter could also be attributed to cardiometabolic covariates. However, PDFF was consistently associated with lower cortical thickness in middle and superior temporal regions and higher cortical thickness in pericalcarine and right frontal pole regions. PDFF-related alterations for the SLD and the MASLD group correlated with those observed in MDD (Pearson r = 0.45–0.54, p < 0.01). ConclusionThese findings suggest the presence of shared biological mechanisms linking MDD to SLD and MASLD. They might explain the well-known elevated risk of depression in these groups and support early lifestyle interventions and treatment of metabolic risk factors for the successful management of the interconnected diseases depression and SLD/MASLD.

Brain and Ventricle Volume Alterations in Idiopathic Normal Pressure Hydrocephalus Determined by Artificial Intelligence-Based MRI Volumetry.

The aim of this study was to employ artificial intelligence (AI)-based magnetic resonance imaging (MRI) brain volumetry to potentially distinguish between idiopathic normal pressure hydrocephalus (iNPH), Alzheimer's disease (AD), and age- and sex-matched healthy controls (CG) by evaluating cortical, subcortical, and ventricular volumes. Additionally, correlations between the measured brain and ventricle volumes and two established semi-quantitative radiologic markers for iNPH were examined. An IRB-approved retrospective analysis was conducted on 123 age- and sex-matched subjects (41 iNPH, 41 AD, and 41 controls), with all of the iNPH patients undergoing routine clinical brain MRI prior to ventriculoperitoneal shunt implantation. Automated AI-based determination of different cortical and subcortical brain and ventricular volumes in mL, as well as calculation of population-based normalized percentiles according to an embedded database, was performed; the CE-certified software mdbrain v4.4.1 or above was used with a standardized T1-weighted 3D magnetization-prepared rapid gradient echo (MPRAGE) sequence. Measured brain volumes and percentiles were analyzed for between-group differences and correlated with semi-quantitative measurements of the Evans' index and corpus callosal angle: iNPH patients exhibited ventricular enlargement and changes in gray and white matter compared to AD patients and controls, with the most significant differences observed in total ventricular volume (+67%) and the lateral (+68%), third (+38%), and fourth (+31%) ventricles compared to controls. Global ventriculomegaly and marked white matter reduction with concomitant preservation of gray matter compared to AD and CG were characteristic of iNPH, whereas global and frontoparietally accentuated gray matter reductions were characteristic of AD. Evans' index and corpus callosal angle differed significantly between the three groups and moderately correlated with the lateral ventricular volumes in iNPH patients [Evans' index (r > 0.83, p ≤ 0.001), corpus callosal angle (r < -0.74, p ≤ 0.001)]. AI-based MRI volumetry in iNPH patients revealed global ventricular enlargement and focal brain atrophy, which, in contrast to healthy controls and AD patients, primarily involved the supratentorial white matter and was marked temporomesially and in the midbrain, while largely preserving gray matter. Integrating AI volumetry in conjunction with traditional radiologic measures could enhance iNPH identification and differentiation, potentially improving patient management and therapy response assessment.

Regional brain volumes and their relationship to neurocognitive outcomes in children with severe hemophilia A

AbstractThe effect of factor VIII (FVIII) deficiency on neurocognitive outcomes in children with hemophilia A (HA) is not well characterized. This study aimed to examine differences in brain volume and neurocognition between children with severe HA and healthy controls.This single-center study included 32 males aged 6 to 16 years, 9 with severe FVIII deficiency and 23 healthy controls. Volumetric data from magnetic resonance imaging and neurocognitive testing were compared using linear models including age to evaluate the association between regional brain volume and function. Cerebellar gray matter volume was significantly smaller in the HA cohort than in healthy controls (estimate, –0.375; 95% confidence interval [CI], –0.732 to –0.019; t(26) = 2.07; P = .049). A reduction in cerebellar gray matter was associated with neurocognitive executive dysfunction as noted by abnormal scores on 2 executive function assessments: the Delis-Kaplan Executive Function System, total switching accuracy (estimate, 0.549; 95% CI, –0.876 to 0.221; t(25) = –3.28; P = .003) and total correct category switching (estimate, 0.538; 95% CI, –0.868 to 0.207; t(25) = –3.19; P = .004), and the Behavior Rating Inventory of Executive Function, behavioral regulation index score (estimate, 0.531; 95% CI, 0.228-0.835; t(25) = 3.44; P = .002). Our study provides key insights into the lower brain volumes found in patients with HA and the corresponding executive dysfunction. Quantitative brain volume assessment in patients with HA may provide an integrated measure and with further research could be a useful clinical tool when assessing risk for neurocognitive dysfunction.

PATHOPHYSIOLOGICAL, NEUROCHEMICAL AND BRAIN IMAGING ANALYSIS AS PARAMETERS FOR THE EARLY DIAGNOSIS OF BIPOLAR DISORDER

Introduction: Bipolar affective disorder is a complex psychiatric disorder. Its most striking feature is the alternation, sometimes sudden, of episodes of depression with those of euphoria (mania and hypomania) and asymptomatic periods in between. The crises can vary in intensity (mild, moderate and severe), frequency and duration. Objectives: The aim of this study was to identify the pathophysiology and neurochemistry of bipolar disorder, from diagnosis to treatment. Material and Methods: The methodology used was a literature review. The research was carried out through an electronic search for scientific articles published on the Scielo (Scientific Electronic Library Online) and Lilacs (Latin American Health Sciences Literature) and Pubmed websites. The health terminologies consulted in the Health Sciences descriptors (DeCS/BIREME) were used; the pathophysiology and neurochemistry of bipolar disorder, from diagnosis to treatment. Results: Structural neuroimaging studies have shown significant changes in brain volume, suggesting atrophy and/or neuronal loss, at least in a proportion of individuals with BD. Several studies have reported a significant decrease in gray matter in the prefrontal and temporal cortex, as well as an increase in the lateral ventricles. Bipolar patients tend to show reductions in gray matter in the frontal regions of the brain involved in self-control, while sensory and visual regions are normal. Conclusion: When struggling with a mental health disorder, the road to improvement usually begins with the long process of trying various treatments and approaches to find the one that best suits the patient.

Repeated caffeine intake suppresses cerebral grey matter responses to chronic sleep restriction in an A1 adenosine receptor-dependent manner: a double-blind randomized controlled study with PET-MRI

Evidence has shown that both sleep loss and daily caffeine intake can induce changes in grey matter (GM). Caffeine is frequently used to combat sleepiness and impaired performance caused by insufficient sleep. It is unclear (1) whether daily use of caffeine could prevent or exacerbate the GM alterations induced by 5-day sleep restriction (i.e. chronic sleep restriction, CSR), and (2) whether the potential impact on GM plasticity depends on individual differences in the availability of adenosine receptors, which are involved in mediating effects of caffeine on sleep and waking function. Thirty-six healthy adults participated in this double-blind, randomized, controlled study (age = 28.9 ± 5.2 y/; F:M = 15:21; habitual level of caffeine intake < 450 mg; 29 homozygous C/C allele carriers of rs5751876 of ADORA2A, an A2A adenosine receptor gene variant). Each participant underwent a 9-day laboratory visit consisting of one adaptation day, 2 baseline days (BL), 5-day sleep restriction (5 h time-in-bed), and a recovery day (REC) after an 8-h sleep opportunity. Nineteen participants received 300 mg caffeine in coffee through the 5 days of CSR (CAFF group), while 17 matched participants received decaffeinated coffee (DECAF group). We examined GM changes on the 2nd BL Day, 5th CSR Day, and REC Day using magnetic resonance imaging and voxel-based morphometry. Moreover, we used positron emission tomography with [18F]-CPFPX to quantify the baseline availability of A1 adenosine receptors (A1R) and its relation to the GM plasticity. The results from the voxel-wise multimodal whole-brain analysis on the Jacobian-modulated T1-weighted images controlled for variances of cerebral blood flow indicated a significant interaction effect between caffeine and CSR in four brain regions: (a) right temporal-occipital region, (b) right dorsomedial prefrontal cortex (DmPFC), (c) left dorsolateral prefrontal cortex (DLPFC), and (d) right thalamus. The post-hoc analyses on the signal intensity of these GM clusters indicated that, compared to BL, GM on the CSR day was increased in the DECAF group in all clusters but decreased in the thalamus, DmPFC, and DLPFC in the CAFF group. Furthermore, lower baseline subcortical A1R availability predicted a larger GM reduction in the CAFF group after CSR of all brain regions except for the thalamus. In conclusion, our data suggest an adaptive GM upregulation after 5-day CSR, while concomitant use of caffeine instead leads to a GM reduction. The lack of consistent association with individual A1R availability may suggest that CSR and caffeine affect thalamic GM plasticity predominantly by a different mechanism. Future studies on the role of adenosine A2A receptors in CSR-induced GM plasticity are warranted.

The Association Between Chronic Tobacco Smoking and Brain Alterations in Schizophrenia: A Systematic Review of Magnetic Resonance Imaging Studies.

The high co-occurrence of tobacco smoking in patients with schizophrenia spectrum disorders (SSD) poses a serious health concern, linked to increased mortality and worse clinical outcomes. The mechanisms underlying this co-occurrence are not fully understood. Addressing the need for a comprehensive overview of the impact of tobacco use on SSD neurobiology, we conducted a systematic review of neuroimaging studies (including structural, functional, and neurochemical magnetic resonance imaging studies) that investigate the association between chronic tobacco smoking and brain alterations in patients with SSD. Eight structural and fourteen functional studies were included. Structural studies show widespread independent and additive reductions in gray matter in relation to smoking and SSD. The majority of functional studies suggest that smoking might be associated with improvements in connectivity deficits linked to SSD. However, the limited number of and high amount of cross-sectional studies, and high between-studies sample overlap prevent a conclusive determination of the nature and extent of the impact of smoking on brain functioning in patients with SSD. Overall, functional results imply a distinct neurobiological mechanism for tobacco addiction in patients with SSD, possibly attributed to differences at the nicotinic acetylcholine receptor level. Our findings highlight the need for more longitudinal and exposure-dependent studies to differentiate between inherent neurobiological differences and the (long-term) effects of smoking in SSD, and to unravel the complex interaction between smoking and schizophrenia at various disease stages. This could inform more effective strategies addressing smoking susceptibility in SSD, potentially improving clinical outcomes.

The thalamic covariance network is associated with cognitive deficits in patients with cerebral small vascular disease.

Abnormalities in the gray matter structure of cerebral small vessel disease (CSVD) have been observed throughout the brain. However, whether cortico-cortical connections exist between regions of gray matter atrophy in patients with CSVD has not been fully elucidated. This question was tested by comparing the gray matter covariance networks in CSVD patients with and without cognitive impairment (CI). We performed multivariate modeling of the gray matter volume measurements of 61 patients with CI (CSVD-CI), 85 patients without CI (CSVD-NC), and 108 healthy controls using source-based morphological analysis (SBM) to obtain gray matter structural covariance networks at the population level. Then, correlations between structural covariance networks and cognitive functions were analyzed in CSVD patients. Finally, a support vector machine (SVM) classifier was used with the gray matter covariance network as a classification feature to identify CI among the CSVD population. The results of the analysis of all the subjects showed that compared with healthy controls, the expression of the thalamic covariance network, cerebellum covariance network, and calcarine cortex covariance network was reduced in patients with CSVD. Moreover, CSVD-CI patients showed a significant reduction in the expression of the thalamic covariance network, encompassing the thalamus and the parahippocampal gyrus, relative to CSVD-NC patients, which persisted after excluding CSVD patients with thalamic lacunes. In patients with CSVD, cognitive functions were positively correlated with measures of the thalamic covariance network. More than 80% of CSVD patients with CI were correctly identified by the SVM classifier. Our findings provide new evidence to explain the distribution state of gray matter reduction in CSVD patients, and the thalamic covariance network is the core region for early gray matter reduction during the development of CSVD disease, which is related to cognitive deficits. Reduced expression of thalamic covariance networks may provide a neuroimaging biomarker for the early identification of cognitive impairment in CSVD patients.

Where alcohol use disorder meets interoception: A meta-analytic view on structural and functional neuroimaging data.

Alcohol use disorder (AUD) has been associated with changes in the processing of internal body signals, known as interoception. Changes in brain structure, particularly in the insula, are thought to underlie impaired interoception. As studies specifically investigating this association are largely lacking, this analysis takes an approach that compares meta-analytic results on interoception with recently published meta-analytic results on gray matter reduction in AUD. A systematic literature search identified 25 eligible interoception studies. Activation likelihood estimation (ALE) was used to test for spatial convergence of study results. Overlap between interoception and AUD clusters was tested using conjunction analysis. Meta-analytic connectivity modeling (MACM) and resting-state functional connectivity were used to identify the functional network of interoception and to test where this network overlapped with AUD meta-analytic clusters. The results were characterized using behavioral domain analysis. The interoception ALE identified a cluster in the left middle insula. There was no overlap with clusters of reduced gray matter in AUD. MACM analysis of the interoception cluster revealed a large network located in the insulae, thalami, basal nuclei, cingulate and medial frontal cortices, and pre- and postcentral gyri. Resting state analysis confirmed this result, showing the strongest connections to nodes of the salience- and somatomotor network. Five of the eight clusters that showed a structural reduction in AUD were located within these networks. The behavioral profiles of these clusters were suggestive of higher-level processes such as salience control, somatomotor functions, and skin sensations. The results suggest an altered salience mapping of interoceptive signals in AUD, consistent with current models. Connections to the somatomotor network may be related to action control and integration of skin sensations. Mindfulness-based interventions, pleasurable touch, and (deep) transcranial magnetic stimulation may be targeted interventions that reduce interoceptive deficits in AUD and thus contribute to drug use reduction and relapse prevention.

Effect of serum concentrations of IL-6 and TNF-α on brain structure in anorexia nervosa: a combined cross-sectional and longitudinal study

Previous studies of brain structure in anorexia nervosa (AN) have reported reduced gray matter in underweight patients, which largely normalizes upon weight gain. One underlying biological mechanism may be glial cell alterations related to low-grade inflammation. Here, we investigated relationships between brain structure as measured by magnetic resonance imaging and serum concentrations of two pro-inflammatory cytokines (interleukin-6 and tumor necrosis factor alpha) cross-sectionally in 82 underweight adolescent and young adult female patients (mean age 16.8 years; 59 of whom were observed longitudinally after short-term weight restoration; mean duration 2.8 months), 20 individuals long-term weight-recovered from AN (mean age 22.7 years) and 105 healthy control (HC) participants (mean age 17.2 years). We measured cortical thickness, subcortical volumes and local gyrification index, a measure of cortical folding. In contrast to most previous studies of cytokine concentrations in AN, we found no cross-sectional group differences (interleukin-6: p = 0.193, tumor necrosis factor alpha: p = 0.057) or longitudinal changes following weight restoration (interleukin-6: p = 0.201, tumor necrosis factor alpha: p = 0.772). As expected, widespread gray matter reductions (cortical thickness, subcortical volumes, cortical folding) were observed in underweight patients with AN compared to HC. However, we found no evidence of associations between cytokine concentrations and structural brain measures in any participant group. Furthermore, longitudinal changes in cytokine concentrations were unrelated to changes in gray matter. In conclusion, we did not identify any association between (sub-)inflammatory processes and structural brain changes in AN. Future studies are needed to elucidate which other factors besides nutritional status may contribute to brain morphological alterations.

Decentralized Mixed Effects Modeling in COINSTAC.

Performing group analysis on magnetic resonance imaging (MRI) data with linear mixed-effects (LME) models is challenging due to its large dimensionality and inherent multi-level covariance structure. In addition, as large-scale collaborative projects become commonplace in neuroimaging, data must increasingly be stored and analyzed from different locations. In such settings, substantial overhead can occur in terms of data transfer and coordination between participating research groups. In some cases, data cannot be pooled together due to privacy or regulatory concerns. In this work, we propose a decentralized LME model to perform a large-scale analysis of data from different collaborations without data pooling. This method is efficient as it overcomes the hurdles of data sharing and has lower bandwidth and memory requirements for analysis than the centralized modeling approach. We evaluate our model using features extracted from structural magnetic resonance imaging (sMRI) data. Results highlight gray matter reductions in the temporal lobe/insula and medial frontal regions in schizophrenia, consistent with prior studies. Our analysis also demonstrates that decentralized LME models achieve similar performance compared to the models trained with all the data in one location. We also implement the decentralized LME approach in COINSTAC, an open source, decentralized platform for federating neuroimaging analysis, providing an easy to use tool for dissemination to the neuroimaging community.

Anatomical correlates of apathy and impulsivity co-occurrence in early Parkinson’s disease

BackgroundAlthough apathy and impulse control disorders (ICDs) are considered to represent opposite extremes of a continuum of motivated behavior (i.e., hypo- and hyperdopaminergic behaviors), they may also co-occur in Parkinson’s disease (PD).ObjectivesWe aimed to explore the co-occurrence of ICDs and apathy and its neural correlates analyzing gray matter (GM) changes in early untreated PD patients. Moreover, we aimed to investigate the possible longitudinal relationship between ICDs and apathy and their putative impact on cognition during the first five years of PD.MethodsWe used the Parkinson’s Progression Markers Initiative (PPMI) database to identify the co-occurrence of apathy and ICDs in 423 early drug-naïve PD patients at baseline and at 5-year follow-up. Baseline MRI volumes and gray matter changes were analyzed between groups using voxel-based morphometry. Multi-level models assessed the longitudinal relationship (across five years) between apathy and ICDs and cognitive functioning.ResultsAt baseline, co-occurrence of apathy and ICDs was observed in 23 patients (5.4%). This finding was related to anatomical GM reduction along the cortical regions involved in the limbic circuit and cognitive control systems. Longitudinal analyses indicated that apathy and ICDs were related to each other as well as to the combined use of levodopa and dopamine agonists. Worse apathetic and ICDs states were associated with poorer executive functions.ConclusionsApathy and ICDs are joint non-exclusive neuropsychiatric disorders also in the early stages of PD and their co-occurrence was associated with GM decrease in several cortical regions of the limbic circuit and cognitive control systems.

Widespread reductions in cortical thickness following ketamine abuse.

Esketamine is a version of ketamine that has been approved for treatment-resistant depression, but our previous studies showed a link between non-medical use of ketamine and brain structural and functional alterations, including dorsal prefrontal grey matter reduction among chronic ketamine users. In this study, we sought to determine cortical thickness abnormalities following long-term, non-medical use of ketamine. We acquired structural brain images for patients with ketamine use disorder and drug-free healthy controls. We used FreeSurfer software to measure cortical thickness for 68 brain regions. We compared cortical thickness between the 2 groups using analysis of covariance with covariates of age, gender, educational level, smoking, drinking, and whole-brain mean cortical thickness. We included images from 95 patients with ketamine use disorder and 169 controls. Compared with healthy controls, patients with ketamine use disorder had widespread decreased cortical thickness, with the most extensive reductions in the frontal (including the dorsolateral prefrontal cortex) and parietal (including the precuneus) lobes. Increased cortical thickness was not observed among ketamine users relative to comparison participants. Estimated total lifetime ketamine consumption was correlated with reductions in the right inferior parietal and the right rostral middle frontal cortical thickness. We conducted a retrospective cross-sectional study, but longitudinal studies are needed to further validate decreased cortical thickness after nonmedical use of ketamine. This study provided evidence that, compared with healthy controls, chronic ketamine users have widespread reductions in cortical thickness. Our study underscores the importance of the long-term effects of ketamine on brain structure and serves as a reference for the antidepressant use of ketamine.