Cortical mapping of callosal connections in healthy young adults.

The corpus callosum (CC) is the principal white matter bundle supporting communication between the two brain hemispheres. Despite its importance, a comprehensive mapping of callosal connections is still lacking. Here, we constructed the first bidirectional population-based callosal connectional atlas between the midsagittal section of the CC and the cerebral cortex of the human brain by means of diffusion-weighted imaging tractography. The estimated connectional topographic maps within this atlas have the most fine-grained spatial resolution, demonstrate histological validity, and were reproducible in two independent samples. This new resource, a complete and comprehensive atlas, will facilitate the investigation of interhemispheric communication and come with a user-friendly companion online tool (CCmapping) for easy access and visualization of the atlas.

Common and distinct patterns underlying different linguistic tasks: multivariate disconnectome symptom mapping in poststroke patients.

Numerous studies have been devoted to neural mechanisms of a variety of linguistic tasks (e.g. speech comprehension and production). To date, however, whether and how the neural patterns underlying different linguistic tasks are similar or differ remains elusive. In this study, we compared the neural patterns underlying 3 linguistic tasks mainly concerning speech comprehension and production. To address this, multivariate regression approaches with lesion/disconnection symptom mapping were applied to data from 216 stroke patients with damage to the left hemisphere. The results showed that lesion/disconnection patterns could predict both poststroke scores of speech comprehension and production tasks; these patterns exhibited shared regions on the temporal pole of the left hemisphere as well as unique regions contributing to the prediction for each domain. Lower scores in speech comprehension tasks were associated with lesions/abnormalities in the superior temporal gyrus and middle temporal gyrus, while lower scores in speech production tasks were associated with lesions/abnormalities in the left inferior parietal lobe and frontal lobe. These results suggested an important role of the ventral and dorsal stream pathways in speech comprehension and production (i.e. supporting the dual stream model) and highlighted the applicability of the novel multivariate disconnectome-based symptom mapping in cognitive neuroscience research.

Individual variability in functional connectivity of human auditory cortex.

Individual variability in functional connectivity underlies individual differences in cognition and behaviors, yet its association with functional specialization in the auditory cortex remains elusive. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, this study was designed to investigate the spatial distribution of auditory cortex individual variability in its whole-brain functional network architecture. An inherent hierarchical axis of the variability was discerned, which radiates from the medial to lateral orientation, with the left auditory cortex demonstrating more pronounced variations than the right. This variability exhibited a significant correlation with the variations in structural and functional metrics in the auditory cortex. Four auditory cortex subregions, which were identified from a clustering analysis based on this variability, exhibited unique connectional fingerprints and cognitive maps, with certain subregions showing specificity to speech perception functional activation. Moreover, the lateralization of the connectional fingerprint exhibited a U-shaped trajectory across the subregions. These findings emphasize the role of individual variability in functional connectivity in understanding cortical functional organization, as well as in revealing its association with functional specialization from the activation, connectome, and cognition perspectives.

Glymphatic dysfunction in patients with early-stage amyotrophic lateral sclerosis.

Recently, an astrocytic aquaporin 4-dependent drainage system, that is, the glymphatic system, has been identified in the live murine and human brain. Growing evidence suggests that glymphatic function is impaired in patients with several neurodegenerative diseases, including Alzheimer's and Parkinson's disease. As the third most common neurodegenerative disease, although animal studies have indicated that early glymphatic dysfunction is likely an important pathological mechanism underpinning amyotrophic lateral sclerosis (ALS), no available study has been conducted to thoroughly assess glymphatic function in vivo in ALS patients to date, particularly in patients with early-stage ALS. Thus, using diffusion tensor imaging analysis along the perivascular space (ALPS) index, an approximate measure of glymphatic function in vivo, we aimed to explore whether glymphatic function is impaired in patients with patients with early-stage ALS, and the diagnostic performance of the ALPS index in distinguishing between patients with early-stage ALS and healthy subjects. We also aimed to identify the relationships between glymphatic dysfunction and clinical disabilities and sleep problems in patients with early-stage ALS. In this retrospective study, King's Stage 1 ALS patients were defined as patients with early-stage ALS. We enrolled 56 patients with early-stage ALS and 32 age- and sex-matched healthy control subjects. All participants completed clinical screening, sleep assessment and ALPS index analysis. For the sleep assessment, the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and polysomnography were used. Compared with healthy control subjects, patients with early-stage ALS had a significantly lower ALPS index after family-wise error correction (P < 0.05). Moreover, receiver operating characteristic analysis showed that the area under the curve for the ALPS index was 0.792 (95% confidence interval 0.700-0.884). Partial correlation analyses showed that the ALPS index was significantly correlated with clinical disability and sleep disturbances in patients with early-stage ALS. Multivariate analysis showed that sleep efficiency (r = 0.419, P = 0.002) and periodic limb movements in sleep index (r = -0.294, P = 0.017) were significant predictive factors of the ALPS index in patients with early-stage ALS. In conclusion, our study continues to support an important role for glymphatic dysfunction in ALS pathology, and we provide additional insights into the early diagnostic value of glymphatic dysfunction and its correlation with sleep disturbances in vivo in patients with early-stage ALS. Moreover, we suggest that early improvement of glymphatic function may be a promising strategy for slowing the neurodegenerative process in ALS. Future studies are needed to explore the diagnostic and therapeutic value of glymphatic dysfunction in individuals with presymptomatic-stage neurodegenerative diseases.

Brain white matter alterations in young adult male patients with childhood-onset growth hormone deficiency: a diffusion tensor imaging study.

PURPOSE: This study aimed to detect white matter changes and different effects of thyroid hormone on the white matter integrity in young adult male patients with childhood-onset growth hormone deficiency (CO-GHD), compared with healthy people. METHODS: Magnetic resonance imaging (structural imaging and diffusion tensor imaging) was performed in 17 young adult male patients with CO-GHD and 17 healthy male controls. The white matter volume, mean diffusivity (MD) values and fractional anisotropy (FA) values were quantified and compared between two groups (CO-GHD group vs. control group). We assessed the interaction effects between thyroid hormone and groups (CO-GHD group vs. control group) on white matter integrity. RESULTS: Patients with CO-GHD exhibited similar white matter volumes compared with controls. However, compared with the controls, patients with CO-GHD showed a significant reduction in FA values in six clusters and a substantial increase in MD values in four clusters, mainly involving the corticospinal tracts, corpus callosum and so on. Moreover, after correcting for insulin-like growth factor-1 levels, the significant interaction effects between groups (CO-GHD group vs. control group) and serum free thyroxine levels on MD values were noted in three clusters, mainly involving in superior longitudinal fasciculus and sagittal stratum. CONCLUSION: In conclusion, young males with CO-GHD showed white matter changes in multiple brain regions and different effects of thyroid hormone on the white matter integrity.

Functional connectome through the human life span.

The functional connectome of the human brain represents the fundamental network architecture of functional interdependence in brain activity, but its normative growth trajectory across the life course remains unknown. Here, we aggregate the largest, quality-controlled multimodal neuroimaging dataset from 119 global sites, including 33,809 task-free fMRI and structural MRI scans from 32,328 individuals ranging in age from 32 postmenstrual weeks to 80 years. Lifespan growth charts of the connectome are quantified at the whole cortex, system, and regional levels using generalized additive models for location, scale, and shape. We report critical inflection points in the non-linear growth trajectories of the whole-brain functional connectome, particularly peaking in the fourth decade of life. Having established the first fine-grained, lifespan-spanning suite of system-level brain atlases, we generate person-specific parcellation maps and further show distinct maturation timelines for functional segregation within different subsystems. We identify a spatiotemporal gradient axis that governs the life-course growth of regional connectivity, transitioning from primary sensory cortices to higher-order association regions. Using the connectome-based normative model, we demonstrate substantial individual heterogeneities at the network level in patients with autism spectrum disorder and patients with major depressive disorder. Our findings shed light on the life-course evolution of the functional connectome and serve as a normative reference for quantifying individual variation in patients with neurological and psychiatric disorders.

Neuroimaging anomalies in asymptomatic middle cerebral artery steno-occlusive disease with normal-appearing white matter.

Background: Asymptomatic chronic cerebrovascular steno-occlusive disease is common, but the cognitive function and alterations in the brain's structural and functional profiles have not been well studied. This study aimed to reveal whether and how patients with asymptomatic middle cerebral artery (MCA) steno-occlusive disease and normal-appearing white matter differ in brain structural and functional profiles from normal controls and their correlations with cognitive function. Methods: In all, 26 patients with asymptomatic MCA steno-occlusive disease and 22 healthy controls were compared for neurobehavioral assessments, brain volume, cortical thickness, fiber connectivity density (FiCD) value, and resting-state functional connectivity (FC) using multimodal MRI. We also investigated the associations between abnormal cortical thicknesses, FiCD values, and functional connectivities with the neurobehavioral assessments. Results: Patients performed worse on memory tasks (Auditory Verbal Learning Test-Huashan version) compared with healthy controls. Patients were divided into two groups: the right group (patients with right MCA steno-occlusive disease) and the left group (patients with left MCA steno-occlusive disease). The left group showed significant cortical thinning in the left superior parietal lobule, while the right group showed significant cortical thinning in the right superior parietal lobule and caudal portion of the right middle frontal gyrus. Increased FiCD values in the superior frontal region of the left hemisphere were observed in the left group. In addition, a set of interhemispheric and intrahemispheric FC showed a significant decrease or increase in both the left and right groups. Many functional connectivity profiles were positively correlated with cognitive scores. No correlation was found between cortical thickness, FiCD values, and cognitive scores. Conclusion: Even if the patients with MCA steno-occlusive disease were asymptomatic and had normal-appearing white matter, their cognitive function and structural and functional profiles had changed, especially the FC. Alterations in FC may be an important mechanism underlying the neurodegenerative process in patients with asymptomatic MCA steno-occlusive disease before structural changes occur, so FC assessment may promote the detection of network alterations, which may be used as a biomarker of disease progression and therapeutic efficacy evaluation in these patients.

Altered resting-state functional connectivity in the prefrontal cortex is related to the development of dyscalculia in patients with Turner syndrome.

AIM: Patients with Turner syndrome have a high rate of developmental dyscalculia, but the underlying neurocognitive mechanisms are not well-understood. Some studies have implicated visuospatial impairments in patients with Turner syndrome, but others have focused on poor procedural skills in patients with Turner syndrome. This study used brain imaging data to test these two alternative views. METHODS: This study recruited 44 girls with Turner syndrome (mean age, 12.91 years; SD, 2.02), with 13 (29.5%) of them meeting the criterion for developmental dyscalculia, and 14 normally developing girls (mean age, 14.26 years; SD, 2.18) as a comparison group. All participants were given basic mathematical ability tests and an intelligence test and were scanned using magnetic resonance imaging. We compared patients with Turner syndrome who had dyscalculia, patients with Turner syndrome who did not have dyscalculia, and the normal controls in terms of brain structures and resting-state functional activity. RESULTS: Compared with normal controls, both groups of patients with Turner syndrome (with or without dyscalculia) showed similarly altered functional connectivity in the occipitoparietal dorsal stream. Importantly, compared with patients with Turner syndrome without dyscalculia and normal controls, patients with Turner syndrome with dyscalculia showed decreased functional connectivity between the prefrontal and the lateral occipital cortex. CONCLUSION: We concluded that both groups of patients with Turner syndrome shared visual deficits, and patients with Turner syndrome with dyscalculia had a deficit in frontal cortex-based higher cognitive processing. It is not their visuospatial deficits but rather their deficits in higher cognitive processing that are responsible for the development of dyscalculia in patients with Turner syndrome.

Improving Multi-Site Autism Classification via Site-Dependence Minimization and Second-Order Functional Connectivity.

Machine learning has been widely used to develop classification models for autism spectrum disorder (ASD) using neuroimaging data. Recently, studies have shifted towards using large multi-site neuroimaging datasets to boost the clinical applicability and statistical power of results. However, the classification performance is hindered by the heterogeneous nature of agglomerative datasets. In this paper, we propose new methods for multi-site autism classification using the Autism Brain Imaging Data Exchange (ABIDE) dataset. We firstly propose a new second-order measure of functional connectivity (FC) named as Tangent Pearson embedding to extract better features for classification. Then we assess the statistical dependence between acquisition sites and FC features, and take a domain adaptation approach to minimize the site dependence of FC features to improve classification. Our analysis shows that 1) statistical dependence between site and FC features is statistically significant at the 5% level, and 2) extracting second-order features from neuroimaging data and minimizing their site dependence can improve over state-of-the-art (SOTA) classification results, achieving a classification accuracy of 73%. The code is available at https://github.com/kundaMwiza/fMRI-site-adaptation.

Development of functional connectome gradients during childhood and adolescence.

Connectome mapping studies have documented a principal primary-to-transmodal gradient in the adult brain network, capturing a functional spectrum that ranges from perception and action to abstract cognition. However, how this gradient pattern develops and whether its development is linked to cognitive growth, topological reorganization, and gene expression profiles remain largely unknown. Using longitudinal resting-state functional magnetic resonance imaging data from 305 children (aged 6-14 years), we describe substantial changes in the primary-to-transmodal gradient between childhood and adolescence, including emergence as the principal gradient, expansion of global topography, and focal tuning in primary and default-mode regions. These gradient changes are mediated by developmental changes in network integration and segregation, and are associated with abstract processing functions such as working memory and expression levels of calcium ion regulated exocytosis and synaptic transmission-related genes. Our findings have implications for understanding connectome maturation principles in normal development and developmental disorders.

Activation network mapping for integration of heterogeneous fMRI findings.

Functional neuroimaging techniques have been widely used to probe the neural substrates of facial emotion processing in healthy people. However, findings are largely inconsistent across studies. Here, we introduce a new technique termed activation network mapping to examine whether heterogeneous functional magnetic resonance imaging findings localize to a common network for emotion processing. First, using the existing method of activation likelihood estimation meta-analysis, we showed that individual-brain-based reproducibility was low across studies. Second, using activation network mapping, we found that network-based reproducibility across these same studies was higher. Validation analysis indicated that the activation network mapping-localized network aligned with stimulation sites, structural abnormalities and brain lesions that disrupt facial emotion processing. Finally, we verified the generality of the activation network mapping technique by applying it to another cognitive process, that is, rumination. Activation network mapping may potentially be broadly applicable to localize brain networks of cognitive functions.

Callosal Fiber Length Scales with Brain Size According to Functional Lateralization, Evolution, and Development.

Brain size significantly impacts the organization of white matter fibers. Fiber length scaling, the degree to which fiber length varies according to brain size, was overlooked. We investigated how fiber lengths within the corpus callosum, the most prominent white matter tract, vary according to brain size. The results showed substantial variation in length scaling among callosal fibers, replicated in two large healthy cohorts (∼2000 human subjects, including both sexes). The underscaled callosal fibers mainly connected the precentral gyrus and parietal cortices, whereas the overscaled callosal fibers mainly connected the prefrontal cortices. The variation in such length scaling was biologically meaningful: larger scaling corresponded to larger neurite density index but smaller fractional anisotropy values; cortical regions connected by the callosal fibers with larger scaling were more lateralized functionally as well as phylogenetically and ontogenetically more recent than their counterparts. These findings highlight an interaction between interhemispheric communication and organizational and adaptive principles underlying brain development and evolution.SIGNIFICANCE STATEMENT Brain size varies across evolution, development, and individuals. Relative to small brains, the neural fiber length in large brains is inevitably increased, but the degree of such increase may differ between fiber tracts. Such a difference, if it exists, is valuable for understanding adaptive neural principles in large versus small brains during evolution and development. The present study showed a substantial difference in the length increase between the callosal fibers that connect the two hemispheres, replicated in two large healthy cohorts. Together, our study demonstrates that reorganization of interhemispheric fibers length according to brain size is intrinsically related to fiber composition, functional lateralization, cortical myelin content, and evolutionary and developmental expansion.

Hypothalamic subregion abnormalities are related to body mass index in patients with sporadic amyotrophic lateral sclerosis.

OBJECTIVE: To investigate atrophy patterns in hypothalamic subunits at different stages of ALS and examine correlations between hypothalamic subunit volume and clinical information. METHODS: We used the King's clinical staging system to divide 91 consecutive ALS patients into the different disease stages. We investigated patterns of hypothalamic atrophy using a recently published automated segmentation method in ALS patients and in 97 healthy controls. We recorded all subjects' demographic and clinical information. RESULTS: Compared with healthy controls, we found significant atrophy in the bilateral anterior-superior subunit and the superior tubular subunit, as well as a reduction in global hypothalamic volume in ALS patients. When we used the King's clinical staging system to divide patients into the different disease stages, we found neither global nor specific subunit atrophy until King's stage 3 in the hypothalamus. Moreover, specific subunit volumes were significantly associated with body mass index. CONCLUSIONS: In a relatively large sample of Chinese patients with ALS, using a recently published automated segmentation method for the hypothalamus, we found the pattern of hypothalamic atrophy in ALS patients differed greatly across King's clinical disease stages. Moreover, specific hypothalamic subunit atrophy may play an important role in energy metabolism in ALS patients. Thus, our findings suggest that hypothalamic atrophy may have potential phenotypic associations, and improved energy metabolism may become an important component of individualised therapy for ALS.

Identify aberrant white matter microstructure in ASD, ADHD and other neurodevelopmental disorders: A meta-analysis of diffusion tensor imaging studies.

BACKGROUND: Neurodevelopmental disorders (NDDs) usually present overlapping symptoms. Abnormal white matter (WM) microstructure has been found in these disorders. Identification of common and unique neural abnormalities across NDDs could provide further insight into the underlying pathophysiological mechanisms. METHODS: We performed a voxel-based meta-analysis of whole-brain diffusion tensor imaging (DTI) studies in autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) and other NDDs. A systematic literature search was conducted through March 2020 to identify studies that compared measures of WM microstructure between patients with NDDs and neurotypical controls. Peak voxel coordinates were meta-analyzed via anisotropic effect size-signed differential mapping (AES-SDM) as well as activation likelihood estimation (ALE). RESULTS: Our final sample included a total of 4137 subjects from 66 studies across five NDDs. Fractional anisotropy (FA) reductions were found in the splenium of the CC in ADHD, and the genu and splenium of CC in ASD. And mean diffusivity (MD) increases were shown in posterior thalamic radiation in ASD. No consistent abnormalities were detected in specific learning disorder, motor disorder or communication disorder. Significant differences between child/adolescent and adult patients were found within the CC across NDDs, reflective of aberrant neurodevelopmental processes in NDDs. CONCLUSIONS: The current study demonstrated atypical WM patterns in ASD, ADHD and other NDDs. Microstructural abnormalities in the splenium of the CC were possibly shared among ASD and ADHD.

Alterations in brain structure and function associated with pediatric growth hormone deficiency: A multi-modal magnetic resonance imaging study.

Introduction: Pediatric growth hormone deficiency (GHD) is a disease resulting from impaired growth hormone/insulin-like growth factor-1 (IGF-1) axis but the effects of GHD on children's cognitive function, brain structure and brain function were not yet fully illustrated. Methods: Full Wechsler Intelligence Scales for Children, structural imaging, diffusion tensor imaging, and resting-state functional magnetic resonance imaging were assessed in 11 children with GHD and 10 matched healthy controls. Results: (1) The GHD group showed moderate cognitive impairment, and a positive correlation existed between IGF-1 levels and cognitive indices. (2) Mean diffusivity was significantly increased in both corticospinal tracts in GHD group. (3) There were significant positive correlations between IGF-1 levels and volume metrics of left thalamus, left pallidum and right putamen but a negative correlation between IGF-1 levels and cortical thickness of the occipital lobe. And IGF-1 levels negatively correlated with fractional anisotropy in the superior longitudinal fasciculus and right corticospinal tract. (4) Regional homogeneity (ReHo) in the left hippocampus/parahippocampal gyrus was negatively correlated with IGF-1 levels; the amplitude of low-frequency fluctuation (ALFF) and ReHo in the paracentral lobe, postcentral gyrus and precentral gyrus were also negatively correlated with IGF-1 levels, in which region ALFF fully mediates the effect of IGF-1 on working memory index. Conclusion: Multiple subcortical, cortical structures, and regional neural activities might be influenced by serum IGF-1 levels. Thereinto, ALFF in the paracentral lobe, postcentral gyrus and precentral gyrus fully mediates the effect of IGF-1 on the working memory index.

The pattern of cortical thickness underlying disruptive behaviors in Alzheimer's disease.

Background: Disruptive behaviors, including agitation, disinhibition, irritability, and aberrant motor behaviors, are commonly observed in patients with Alzheimer's disease (AD). However, the neuroanatomical basis of these disruptive behaviors is not fully understood. Objective: To confirm the differences in cortical thickness and surface area between AD patients and healthy controls and to further investigate the features of cortical thickness and surface area associated with disruptive behaviors in patients with AD. Methods: One hundred seventy-four participants (125 AD patients and 49 healthy controls) were recruited from memory clinics at the Peking University Institute of Sixth Hospital. Disruptive behaviors, including agitation/aggression, disinhibition, irritability/lability, and aberrant motor activity subdomain scores, were evaluated using the Neuropsychiatry Inventory. Both whole-brain vertex-based and region-of-interest-based cortical thickness and surface area analyses were automatically conducted with the CIVET pipeline based on structural magnetic resonance images. Both group-based statistical comparisons and brain-behavior association analyses were performed using general linear models, with age, sex, and education level as covariables. Results: Compared with healthy controls, the AD patients exhibited widespread reduced cortical thickness, with the most significant thinning located in the medial and lateral temporal and parietal cortex, and smaller surface areas in the left fusiform and left inferior temporal gyrus. High total scores of disruptive behaviors were significantly associated with cortical thinning in several regions that are involved in sensorimotor processing, language, and expression functions. The total score of disruptive behaviors did not show significant associations with surface areas. Conclusion: We highlight that disruptive behaviors in patients with AD are selectively associated with cortical thickness abnormalities in sensory, motor, and language regions, which provides insights into neuroanatomical substrates underlying disruptive behaviors. These findings could lead to sensory, motor, and communication interventions for alleviating disruptive behaviors in patients with AD.

Hippocampal subfield and anterior-posterior segment volumes in patients with sporadic amyotrophic lateral sclerosis.

Neuroimaging studies of hippocampal volumes in patients with amyotrophic lateral sclerosis (ALS) have reported inconsistent results. Our aims were to demonstrate that such discrepancies are largely due to atrophy of different regions of the hippocampus that emerge in different disease stages of ALS and to explore the existence of co-pathology in ALS patients. We used the well-validated King's clinical staging system for ALS to classify patients into different disease stages. We investigated in vivo hippocampal atrophy patterns across subfields and anterior-posterior segments in different King's stages using structural MRI in 76 ALS patients and 94 health controls (HCs). The thalamus, corticostriatal tract and perforant path were used as structural controls to compare the sequence of alterations between these structures and the hippocampal subfields. Compared with HCs, ALS patients at King's stage 1 had lower volumes in the bilateral posterior subiculum and presubiculum; ALS patients at King's stage 2 exhibited lower volumes in the bilateral posterior subiculum, left anterior presubiculum and left global hippocampus; ALS patients at King's stage 3 showed significantly lower volumes in the bilateral posterior subiculum, dentate gyrus and global hippocampus. Thalamic atrophy emerged at King's stage 3. White matter tracts remained normal in a subset of ALS patients. Our study demonstrated that the pattern of hippocampal atrophy in ALS patients varies greatly across King's stages. Future studies in ALS patients that focus on the hippocampus may help to further clarify possible co-pathologies in ALS.

Neuroimaging Anomalies in Community-Dwelling Asymptomatic Adults With Very Early-Stage White Matter Hyperintensity.

White matter hyperintensity (WMH) is common in healthy adults in their 60s and can be seen as early as in their 30s and 40s. Alterations in the brain structural and functional profiles in adults with WMH have been repeatedly studied but with a focus on late-stage WMH. To date, structural and functional MRI profiles during the very early stage of WMH remain largely unexplored. To address this, we investigated multimodal MRI (structural, diffusion, and resting-state functional MRI) profiles of community-dwelling asymptomatic adults with very early-stage WMH relative to age-, sex-, and education-matched non-WMH controls. The comparative results showed significant age-related and age-independent changes in structural MRI-based morphometric measures and resting-state fMRI-based measures in a set of specific gray matter (GM) regions but no global white matter changes. The observed structural and functional anomalies in specific GM regions in community-dwelling asymptomatic adults with very early-stage WMH provide novel data regarding very early-stage WMH and enhance understanding of the pathogenesis of WMH.

Characterizing the hyper- and hypometabolism in temporal lobe epilepsy using multivariate machine learning.

Mesial temporal lobe epilepsy (MTLE) is the most common type of focal epilepsy, presenting both structural and metabolic abnormalities in the ipsilateral mesial temporal lobe. While it has been demonstrated that the metabolic abnormalities in MTLE actually extend beyond the epileptogenic zone, how such multidimensional information is associated with the diagnosis of MTLE remains to be tested. Here, we explore the whole-brain metabolic patterns in 23 patients with MTLE and 24 healthy controls using [18 F]fluorodeoxyglucose PET imaging. Based on a multivariate machine learning approach, we demonstrate that the brain metabolic patterns can discriminate patients with MTLE from controls with a superior accuracy (>95%). Importantly, voxels showing the most extreme contributing weights to the classification (i.e., the most important regional predictors) distribute across both hemispheres, involving both ipsilateral negative weights over the anterior part of lateral and medial temporal lobe, posterior insula, and lateral orbital frontal gyrus, and contralateral positive weights over the anterior frontal lobe, temporal lobe, and lingual gyrus. Through region-of-interest analyses, we verify that in patients with MTLE, the negatively weighted regions are hypometabolic, and the positively weighted regions are hypermetabolic, compared to controls. Interestingly, despite that both hypo- and hypermetabolism have mutually contributed to our model, they may reflect different pathological and/or compensative responses. For instance, patients with earlier age at epilepsy onset present greater hypometabolism in the ipsilateral inferior temporal gyrus, while we find no evidence of such association with hypermetabolism. In summary, quantitative models utilizing multidimensional brain metabolic information may provide additional assistance to presurgical workups in TLE.

White Matter but not Gray Matter Volumes Are Associated with Cognition in Community-Dwelling Chinese Populations.

BACKGROUND: Few studies have investigated the association between cognition and brain volume associated with cerebral small vessel disease (CSVD). OBJECTIVE: We investigated the association between cognition and brain volume and neuroimaging markers of CSVD in a community-dwelling population. METHODS: Participants (n = 993, age≥35 years) from the community-based Shunyi Study were included to investigate the association between neuroimaging markers and cognition cross-sectionally. Magnetic resonance imaging markers included brain volume measurements of the total cerebrum, white matter, gray matter, and CSVD imaging markers. Cognitive performance was assessed using neuropsychological tests of the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Fuld Object Memory, digit span, Trail Making Test (TMT)-A, and TMT-B. RESULTS: For brain volume measurement, subcortical white matter fraction was positively associated with MMSE score (ß= 0.034, p = 0.0062) and MoCA score (ß= 0.034, p = 0.0174), and negatively associated with TMT-A and TMT-B completion time (ß= -2.319, p = 0.0002; ß= -2.827, p = 0.0073, respectively). For evaluation of CSVD imaging markers, the presence of lacunes was positively associated with TMT-B completion time (ß= 17.241, p = 0.0028). CONCLUSION: In community-dwelling populations, reduced white matter volumes, as a consequence of aging and vascular damage, are associated with worse global cognition and executive function. Our findings provide potential insights into the correlation between cognition and CSVD-associated subcortical white matter injury.