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Functional magnetic resonance imaging (fMRI) has been widely used in studying the neural mechanisms of pain in the human brain, primarily focusing on where in the brain pain‐elicited neural activities occur (i.e., the spatial distribution of pain‐related brain activities). However, the temporal dynamics of pain‐elicited hemodynamic responses (HDRs) measured by fMRI may also contain information specific to pain processing but have been largely neglected. Using high temporal resolution fMRI (TR = 0.8 s) data acquired from 62 healthy participants, in the present study we aimed to test whether pain‐distinguishing information could be decoded from the spatial pattern of the temporal dynamics (i.e., the spatiotemporal pattern) of HDRs elicited by painful stimuli. Specifically, the peak latency and the response duration were used to characterize the temporal dynamics of HDRs to painful laser stimuli and non‐painful electric stimuli, and then were compared between the two conditions (i.e., pain and no‐pain) using a voxel‐wise univariate analysis and a multivariate pattern analysis. Furthermore, we also tested whether the two temporal characteristics of pain‐elicited HDRs and their spatial patterns were associated with pain‐related behaviors. We found that the spatial patterns of HDR peak latency and response duration could successfully discriminate pain from no‐pain. Interestingly, we also observed that the Pain Vigilance and Awareness Questionnaire (PVAQ) scores were correlated with the average response duration in bilateral insula and secondary somatosensory cortex (S2) and could also be predicted from the across‐voxel spatial patterns of response durations in the middle cingulate cortex and middle frontal gyrus only during painful condition but not during non‐painful condition. These findings indicate that the spatiotemporal pattern of pain‐elicited HDRs may contain pain‐specific information and highlight the importance of studying the neural mechanisms of pain by taking advantage of the high sensitivity of fMRI to both spatial and temporal information of brain responses. [ABSTRACT FROM AUTHOR]

Subcortical ischemic stroke can lead to persistent structural changes in the cerebral cortex. The evolution of cortical structural changes after subcortical stroke is largely unknown, as are their relations with motor recovery, lesion location, and early impairment of specific subsets of fibers in the corticospinal tract (CST). In this observational study, cortical structural changes were compared between 181 chronic patients with subcortical stroke involving the motor pathway and 113 healthy controls. The impacts of acute lesion location and early impairments of specific CSTs on cortical structural changes were investigated in the patients by combining voxel‐based correlation analysis with an association study that compared CST damage and cortical structural changes. Longitudinal patterns of cortical structural change were explored in a group of 81 patients with subcortical stroke using a linear mixed‐effects model. In the cross‐sectional analyses, patients with partial recovery showed more significant reductions in cortical thickness, surface area, or gray matter volume in the sensorimotor cortex, cingulate gyrus, and gyrus rectus than did patients with complete recovery; however, patients with complete recovery demonstrated more significant increases in the cortical structural measures in frontal, temporal, and occipital regions than did patients with partial recovery. Voxel‐based correlation analysis in these patients showed that acute stroke lesions involving the CST fibers originating from the primary motor cortex were associated with cortical thickness reductions in the ipsilesional motor cortex in the chronic stage. Acute stroke lesions in the putamen were correlated with increased surface area in the temporal pole in the chronic stage. The early impairment of the CST fibers originating from the primary sensory area was associated with increased cortical thickness in the occipital cortex. In the longitudinal analyses, patients with partial recovery showed gradually reduced cortical thickness, surface area, and gray matter volume in brain regions with significant structural damage in the chronic stage. Patients with complete recovery demonstrated gradually increasing cortical thickness, surface area, and gray‐matter volume in the frontal, temporal, and occipital regions. The directions of slow structural changes in the frontal, occipital, and cingulate cortices were completely different between patients with partial and complete recovery. Complex cortical structural changes and their dynamic evolution patterns were different, even contrasting, in patients with partial and complete recovery, and were associated with lesion location and with impairment of specific CST fiber subsets. [ABSTRACT FROM AUTHOR]

Functional connectivity (FC) disruption is a remarkable characteristic of schizophrenia. However, heterogeneous patterns reported across sites severely hindered its clinical generalization. Based on qualified nodal‐based FC of 340 schizophrenia patients (SZ) and 348 normal controls (NC) acquired from seven different scanners, this study compared four commonly used site‐effect correction methods in removing the site‐related heterogeneities, and then tried to cluster the abnormal FCs into several replicable and independent disrupted subnets across sites, related them to clinical symptoms, and evaluated their potentials in schizophrenia classification. Among the four site‐related heterogeneity correction methods, ComBat harmonization (F1 score: 0.806 ± 0.145) achieved the overall best balance between sensitivity and false discovery rate in unraveling the aberrant FCs of schizophrenia in the local and public data sets. Hierarchical clustering analysis identified three replicable FC disruption subnets across the local and public data sets: hypo‐connectivity within sensory areas (Net1), hypo‐connectivity within thalamus, striatum, and ventral attention network (Net2), and hyper‐connectivity between thalamus and sensory processing system (Net3). Notably, the derived composite FC within Net1 was negatively correlated with hostility and disorientation in the public validation set (p <.05). Finally, the three subnet‐specific composite FCs (Best area under the receiver operating characteristic curve [AUC] = 0.728) can robustly and meaningfully discriminate the SZ from NC with comparable performance with the full identified FCs features (best AUC = 0.765) in the out‐of‐sample public data set (Z = −1.583, p =.114). In conclusion, ComBat harmonization was most robust in detecting aberrant connectivity for schizophrenia. Besides, the three subnet‐specific composite FC measures might be replicable neuroimaging markers for schizophrenia. [ABSTRACT FROM AUTHOR]

Microsatellite variants in the arginine vasopressin receptor 1A gene ( AVPR1A) RS3 have been associated with normal social behaviors variation and autism spectrum disorders (ASDs) in a sex-specific manner. However, neural mechanisms underlying these associations remain largely unknown. We hypothesized that AVPR1A RS3 variants affect altruistic behavior by modulating the gray matter volume (GMV) of specific brain regions in a sex-specific manner. We investigated 278 young healthy adults using the Dictator Game to assess altruistic behavior. All subjects were genotyped and main effect of AVPR1A RS3 repeat polymorphisms and interaction of genotype-by-sex on the GMV were assessed in a voxel-wise manner. We observed that male subjects with relatively short repeats allocated less money to others and exhibited a significantly smaller GMV in the right fusiform face area (FFA) compared with male long homozygotes. In male subjects, the GMV of the right FFA exhibited a significant positive correlation with altruistic behavior. A mixed mediation and moderation analysis further revealed both a significant mediation effect of the GMV of the right FFA on the association between AVPR1A RS3 repeat polymorphisms and allocation sums and a significant moderation effect of sex (only in males) on the mediation effect. Post hoc analysis showed that the GMV of the right FFA was significantly smaller in male subjects carrying allele 426 than in non-426 carriers. These results suggest that the GMV of the right FFA may be a potential mediator whereby the genetic variants in AVPR1A RS3 affect altruistic behavior in healthy male subjects. Hum Brain Mapp 37:2700-2709, 2016. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a common neurodegeneration disease associated with substantial disruptions in the brain network. However, most studies investigated static resting-state functional connections, while the alteration of dynamic functional connectivity in AD remains largely unknown. This study used group independent component analysis and the sliding-window method to estimate the subject-specific dynamic connectivity states in 1704 individuals from three data sets. Informative inherent states were identified by the multivariate pattern classification method, and classifiers were built to distinguish ADs from normal controls (NCs) and to classify mild cognitive impairment (MCI) patients with informative inherent states similar to ADs or not. In addition, MCI subgroups with heterogeneous functional states were examined in the context of different cognition decline trajectories. Five informative states were identified by feature selection, mainly involving functional connectivity belonging to the default mode network and working memory network. The classifiers discriminating AD and NC achieved the mean area under the receiver operating characteristic curve of 0.87 with leave-one-site-out cross-validation. Alterations in connectivity strength, fluctuation, and inter-synchronization were found in AD and MCIs. Moreover, individuals with MCI were clustered into two subgroups, which had different degrees of atrophy and different trajectories of cognition decline progression. The present study uncovered the alteration of dynamic functional connectivity in AD and highlighted that the dynamic states could be powerful features to discriminate patients from NCs. Furthermore, it demonstrated that these states help to identify MCIs with faster cognition decline and might contribute to the early prevention of AD., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)