Volume of the right supramarginal gyrus is associated with a maintenance of emotion recognition ability

Emotion recognition is known to change with age, but associations between the change and brain atrophy are not well understood. In the current study atrophied brain regions associated with emotion recognition were investigated in elderly and younger participants. Group comparison showed no difference in emotion recognition score, while the score was associated with years of education, not age. We measured the gray matter volume of 18 regions of interest including the bilateral precuneus, supramarginal gyrus, orbital gyrus, straight gyrus, superior temporal sulcus, inferior frontal gyrus, insular cortex, amygdala, and hippocampus, which have been associated with social function and emotion recognition. Brain reductions were observed in elderly group except left inferior frontal gyrus, left straight gyrus, right orbital gyrus, right inferior frontal gyrus, and right supramarginal gyrus. Path analysis was performed using the following variables: age, years of education, emotion recognition score, and the 5 regions that were not different between the groups. The analysis revealed that years of education were associated with volumes of the right orbital gyrus, right inferior frontal gyrus, and right supramarginal gyrus. Furthermore, the right supramarginal gyrus volume was associated with the emotion recognition score. These results suggest that the amount of education received contributes to maintain the right supramarginal gyrus volume, and indirectly affects emotion recognition ability.

Alterations of Regional Homogeneity in the Mild and Moderate Stages of Parkinson’s Disease

Objectives: This study aimed to investigate alterations in regional homogeneity (ReHo) in early Parkinson’s disease (PD) at different Hoehn and Yahr (HY) stages and to demonstrate the relationships between altered brain regions and clinical scale scores.Methods: We recruited 75 PD patients, including 43 with mild PD (PD-mild; HY stage: 1.0–1.5) and 32 with moderate PD (PD-moderate; HY stage: 2.0–2.5). We also recruited 37 age- and sex-matched healthy subjects as healthy controls (HC). All subjects underwent neuropsychological assessments and a 3.0 Tesla magnetic resonance scanning. Regional homogeneity of blood oxygen level-dependent (BOLD) signals was used to characterize regional cerebral function. Correlative relationships between mean ReHo values and clinical data were then explored.Results: Compared to the HC group, the PD-mild group exhibited increased ReHo values in the right cerebellum, while the PD-moderate group exhibited increased ReHo values in the bilateral cerebellum, and decreased ReHo values in the right superior temporal gyrus, the right Rolandic operculum, the right postcentral gyrus, and the right precentral gyrus. Reho value of right Pre/Postcentral was negatively correlated with HY stage. Compared to the PD-moderate group, the PD-mild group showed reduced ReHo values in the right superior orbital gyrus and the right rectus, in which the ReHo value was negatively correlated with cognition.Conclusion: The right superior orbital gyrus and right rectus may serve as a differential indicator for mild and moderate PD. Subjects with moderate PD had a greater scope for ReHo alterations in the cortex and compensation in the cerebellum than those with mild PD. PD at HY stages of 2.0–2.5 may already be classified as Braak stages 5 and 6 in terms of pathology. Our study revealed the different patterns of brain function in a resting state in PD at different HY stages and may help to elucidate the neural function and early diagnosis of patients with PD.

Abnormal Degree Centrality in White Matter Hyperintensities: A Resting-State Functional Magnetic Resonance Imaging Study

Background: White matter hyperintensities (WMHs) are a common occurrence with aging and are associated with cognitive impairment. However, the neurobiological mechanisms of WMHs remain poorly understood. Functional magnetic resonance imaging (fMRI) is a prominent tool that helps in non-invasive examinations and is increasingly used to diagnose neuropsychiatric diseases. Degree centrality (DC) is a common and reliable index in fMRI, which counts the number of direct connections for a given voxel in a network and reflects the functional connectivity within brain networks. We explored the underlying mechanism of cognitive impairment in WMHs from the perspective of DC.Methods: A total of 104 patients with WMHs and 37 matched healthy controls (HCs) were enrolled in the current study. All participants underwent individual and overall cognitive function tests and resting-state fMRI (rs-fMRI). WMHs were divided into three groups (39 mild WMHs, 37 moderate WMHs, and 28 severe WMHs) according to their Fazekas scores, and the abnormal DC values in the WMHs and HCs groups were analyzed.Results: There was a significant difference in the right inferior frontal orbital gyrus and left superior parietal gyrus between the WMHs and HCs groups. The functional connectivity between the right inferior frontal orbital gyrus and left inferior temporal gyrus, left superior parietal gyrus, and left parietal inferior gyrus was also different in the WMHs group.Conclusion: The change in DC value may be one of the underlying mechanisms of cognitive impairment in individuals with WMHs, which provides us with a new approach to delaying cognitive impairment in WMHs.

Correlation of [18F]florbetaben textural features and age of onset of Alzheimer’s disease: a principal components analysis approach

Background When Alzheimer’s disease (AD) is occurring at an early onset before 65 years old, its clinical course is generally more aggressive than in the case of a late onset. We aim at identifying [$$^{18}$$ 18 F]florbetaben PET biomarkers sensitive to differences between early-onset Alzheimer’s disease (EOAD) and late-onset Alzheimer’s disease (LOAD). We conducted [$$^{18}$$ 18 F]florbetaben PET/CT scans of 43 newly diagnosed AD subjects. We calculated 93 textural parameters for each of the 83 Hammers areas. We identified 41 independent principal components for each brain region, and we studied their Spearman correlation with the age of AD onset, by taking into account multiple comparison corrections. Finally, we calculated the probability that EOAD and LOAD patients have different amyloid-$$\beta$$ β ($$A\beta$$ A β ) deposition by comparing the mean and the variance of the significant principal components obtained in the two groups with a 2-tailed Student’s t-test. Results We found that four principal components exhibit a significant correlation at a 95% confidence level with the age of onset in the left lateral part of the anterior temporal lobe, the right anterior orbital gyrus of the frontal lobe, the right lateral orbital gyrus of the frontal lobe and the left anterior part of the superior temporal gyrus. The data are consistent with the hypothesis that EOAD patients have a significantly different [$$^{18}$$ 18 F]florbetaben uptake than LOAD patients in those four brain regions. Conclusions Early-onset AD implies a very irregular pattern of $$A\beta$$ A β deposition. The authors suggest that the identified textural features can be used as quantitative biomarkers for the diagnosis and characterization of EOAD patients.

Resting-State Functional Connectivity in Mathematical Expertise

To what extent are different levels of expertise reflected in the functional connectivity of the brain? We addressed this question by using resting-state functional magnetic resonance imaging (fMRI) in mathematicians versus non-mathematicians. To this end, we investigated how the two groups of participants differ in the correlation of their spontaneous blood oxygen level-dependent fluctuations across the whole brain regions during resting state. Moreover, by using the classification algorithm in machine learning, we investigated whether the resting-state fMRI networks between mathematicians and non-mathematicians were distinguished depending on features of functional connectivity. We showed diverging involvement of the frontal–thalamic–temporal connections for mathematicians and the medial–frontal areas to precuneus and the lateral orbital gyrus to thalamus connections for non-mathematicians. Moreover, mathematicians who had higher scores in mathematical knowledge showed a weaker connection strength between the left and right caudate nucleus, demonstrating the connections’ characteristics related to mathematical expertise. Separate functional networks between the two groups were validated with a maximum classification accuracy of 91.19% using the distinct resting-state fMRI-based functional connectivity features. We suggest the advantageous role of preconfigured resting-state functional connectivity, as well as the neural efficiency for experts’ successful performance.

Altered asymmetries of the structural networks comprising the fronto-limbic brain circuitry of preterm infants

This study aimed to elaborate upon prior findings suggestive of the altered lateralization of structural connectivity in the developing preterm brain by using diffusion tensor imaging tractography to explore how network topological asymmetries in fronto-limbic neural circuitry are altered at 36–41 weeks, postmenstrual age in 64 preterm infants without severe brain injury and 33 term-born infants. We compared the pattern of structural connectivity and network lateralization of the betweenness centrality in the medial fronto-orbital gyrus, superior temporal gyrus, amygdala, and hippocampus—the structures comprising the fronto-limbic brain circuit—between preterm and term infants. Global efficiency, local efficiency, and small-world characteristics did not differ significantly between the two hemispheres in term-born infants, suggesting that integration and segregation are balanced between the left and right hemispheres. However, the preterm brain showed significantly greater leftward lateralization of small-worldness (P = 0.033); the lateralization index of the betweenness centrality revealed that the medial fronto-orbital gyrus (P = 0.008), superior temporal gyrus (P = 0.031), and hippocampus (P = 0.028) showed significantly increased leftward asymmetry in preterm infants relative to term-infants independent of sex, age at imaging, and bronchopulmonary dysplasia. The altered lateralization of fronto-limbic brain circuitry might be involved in the early development of social–emotional disorders in preterm infants.

Dynamical Role of Pivotal Brain Regions in Parkinson Symptomatology Uncovered with Deep Learning

Background: The release of a broad, longitudinal anatomical dataset by the Parkinson’s Progression Markers Initiative promoted a surge of machine-learning studies aimed at predicting disease onset and progression. However, the excessive number of features used in these models often conceals their relationship to the Parkinsonian symptomatology. Objectives: The aim of this study is two-fold: (i) to predict future motor and cognitive impairments up to four years from brain features acquired at baseline; and (ii) to interpret the role of pivotal brain regions responsible for different symptoms from a neurological viewpoint. Methods: We test several deep-learning neural network configurations, and report our best results obtained with an autoencoder deep-learning model, run on a 5-fold cross-validation set. Comparison with Existing Methods: Our approach improves upon results from standard regression and others. It also includes neuroimaging biomarkers as features. Results: The relative contributions of pivotal brain regions to each impairment change over time, suggesting a dynamical reordering of culprits as the disease progresses. Specifically, the Putamen is initially the most critical region accounting for the overall cognitive state, only being surpassed by the Substantia Nigra in later years. The Pallidum is the first region to influence motor scores, followed by the parahippocampal and ambient gyri, and the anterior orbital gyrus. Conclusions: While the causal link between regional brain atrophy and Parkinson symptomatology is poorly understood, our methods demonstrate that the contributions of pivotal regions to cognitive and motor impairments are more dynamical than generally appreciated.

Spatial expression pattern of ZNF391 gene in the brains of patients with schizophrenia, bipolar disorders or major depressive disorder identifies new cross-disorder biotypes: A trans-diagnostic, top-down approach

SummaryBackgroundGiven the struggle in the field of psychiatry to realize the precise diagnosis and treatment, it is in an urgent need to redefine psychiatric disorders based on objective biomarkers. The results generated from large psychiatric genomic consortia show us some new vantage points to understand the pathophysiology of psychiatric disorders. Nevertheless, how to relate these captured signals to the more refined disease dimensions has yet to be established.MethodsWe chose a top-down, cross-disorder approach by using the summary statistics of GWAS from large psychiatric genomic consortia to build a genomic structural equation model (SEM) for SCZ, BD and MDD to detect their common factor (CF), and to map a potential causal core gene for the CF, followed by the transcriptional prediction of the identified causal gene in our sample and the discovery of new biotypes based on the prediction pattern of the causal gene in the brain. We then characterized the biotypes in the context of their demographic features, cognitive functions and neuroimaging traits.OutcomesA common factor emerged from a well-fitting genomic SEM of SCZ, BD and MDD (loading 0.42, 0.35 and 0.09 for SCZ, BD and MDD, respectively). One genomic region in chromosome 6 was implicated in the genetic make-up of the common factor, with fine-mapping analysis marking ZNF391 as a potential causal core gene (posterior possibility = 0.96). Gene expression inference analysis identified eight brain regions showing different expression levels of ZNF391 between patients and controls, with three biotypes arising from clustering patients based on their expression pattern of ZNF391 in the brain. The three biotypes performed significantly differently in working memory (PDMS_TC = 0.015, PDMS_TC_A = 0.0318, PDMS_t0D = 0.015) and demonstrated different gray matter volumes in right inferior frontal orbital gyrus (RIFOG) in the same order as working memory (biotype 3 > biotype 2 > biotype 1, PRIFOG = 0.0027). Using ZNF391 as instrumental variable (IV), a partial casual path could be linked from RIFOG to working memory (βRIFOG->DMS_TC0D = 4.95, P = 0.0056; βRIFOG->DMS_TC = 2.53, P = 0.059; βRIFOG->DMS_TC_A = 2.57, P = 0.056).InterpretationThe general predisposition to several psychiatric disorders may be influenced by variations of ZNF391, through its effects on right inferior frontal orbital gyrus and working memory. This illustrates the potential of a trans-diagnostic, top-down approach in understanding the commonality of psychiatric disorders.Evidence before this studyThe results from recent cross-disorder genome-wide association studies (GWAS)using large samples indicate that there is notable genetic overlapping between psychiatric disorders. However, the structural relationship of these disorders at the genomic level and the details of refined disease dimensions affected by the associated loci in a cross-disorder pattern remains unknown. We searched the published studies (up to Sep 7, 2019) in PubMed using the combination of the following keywords “((cross disorder) OR (schizophrenia AND bipolar disorder AND major depressive disorder) AND (genome AND structural equation) AND (cognition OR imaging))”, no published study was found. We then removed the term “structural equation”, 23 original studies were found. To the best of our knowledge, none of these studies explored the organized structure between three disorders. Further, of 23 articles we found, the majority of them took an approach of either polygenic risk score (PRS) or candidate gene to test the association with either psychological traits such as loneliness or neuroimaging measures in one (schizophrenia) or two (schizophrenia and bipolar) disorders. Hitherto, no study has been conducted to redefine three disorders based on the biological markers generated from the cross-disorder genomic studies.Added value of this studyAdopting a novel approach of genomic structural equation modelling, we used the latest results of GWAS of three major psychiatric disorders to detect their common factor, further, to identify the loci associated with such as a common factor, and the loci’s transcription consequences in the brain. Propelled by the phenomenon “genes do not read DSM”, we used a cutting-edge clustering algorithm to redefine three disorders based on the cerebral spatial expression pattern of associated core gene. Our study provides another piece of evidence as to the potentials of utilizing the signals arising from large population-scale GWAS to dissect and redefine psychiatric disorders.Implications of all the available evidenceConsistent with previous case-control cross-disorder GWAS, our study suggests that a common factor exists in three major psychiatric disorders and the biological information of core gene associated with the common factor could be used as an objective marker to explain three disorders and their pathophysiology.