Dynamic Spatial Discrimination Maps of Discriminative Activation between Different Tasks Based on Support Vector Machines

As a set of supervised pattern recognition methods, support vector machines (SVMs) have been successfully applied to functional magnetic resonance imaging (fMRI) field, but few studies have focused on visualizing discriminative regions of whole brain between different cognitive tasks dynamically. This paper presents a SVM-based method for visualizing dynamically discriminative activation of whole-brain voxels between two kinds of tasks without any contrast. Our method provides a series of dynamic spatial discrimination maps (DSDMs), representing the temporal evolution of discriminative brain activation during a duty cycle and describing how the discriminating information changes over the duty cycle. The proposed method was applied to investigate discriminative brain functional activations of whole brain voxels dynamically based on a hand-motor task experiment. A set of DSDMs between left hand movement and right hand movement were reached. Our results demonstrated not only where but also when the discriminative activations of whole brain voxels occurred between left hand movement and right hand movement during one duty cycle.

Altered relationship between thickness and intrinsic activity amplitude in generalized tonic–clonic seizures

A thinner cortex has higher potential for binding GABA receptor A which is associated with larger amplitudes of intrinsic brain activity(i BA). However, the relationship between cortical thickness and i BA is unknown in intact and epileptic brains. To this end, we investigated the relationship between cortical thickness measured by highresolution MRI and surface-based i BA derived from resting-state functional MRI in normal controls(n = 82) andpatients with generalized tonic–clonic seizures(GTCS)only(n = 82). We demonstrated that the spatial distribution of cortical thickness negatively correlated with surface-based i BA amplitude at both whole-brain and within independent brain functional networks. In GTCS patients,spatial coupling between thickness and i BA amplitude decreased in the default mode, dorsal attention, and somatomotor networks. In addition, the vertex-wise acrosssubject thickness–i BA amplitude correspondence altered in the frontal and temporal lobes as well as in the precuneus in GTCS patients. The relationship between these two modalities can serve as a brain-based marker for detecting epileptogenic changes.

A Longitudinal Functional Magnetic Resonance Imaging Study of Working Memory in Patients Following a Transient Ischemic Attack: A Preliminary Study

In this study, we used functional magnetic resonance imaging(fMRI) to investigate longitudinal changes in brain activation during a verbal working memory(VWM) task performed by patients who had experienced a transient ischemic attack(TIA). Twenty-five first-ever TIA patients without visible lesions in conventional MRI and 25 healthy volunteers were enrolled. VWM task-related fMRI was conducted 1 week and 3 months post-TIA. The brain activity evoked by the task and changes over time were assessed. We found that, compared with controls, patients exhibited an increased activation in the bilateral inferior frontal gyrus(IFG), right dorsolateral prefrontal cortex(DLPFC), insula, inferior parietal lobe(IPL), and cerebellum during the task performed 1 week post-TIA. But only the right IFG still exhibited an increased activation at 3 months post-TIA. A direct comparison of fMRI data between 1 week and 3 months post-TIA showed greater activation in the bilateral middle temporal gyrus, right DLPFC, IPL, cerebellum, and left IFG in patients at 1 week post-TIA. We conclude that brain activity patterns induced by a VWM task remain dynamic for a period of time after a TIA, despite the cessation of clinical symptoms. Normalization of the VWM activation pattern may be progressively achieved after transient episodes of ischemia in TIA patients.

The ER membrane protein complex subunit Emc3 controls angiogenesis via the FZD4/WNT signaling axis

The endoplasmic reticulum(ER) membrane protein complex(EMC) regulates the synthesis and quality control of membrane proteins with multiple transmembrane domains. One of the membrane spanning subunits, EMC3, is a core member of the EMC complex that provides essential hydrophilic vestibule for substrate insertion. Here, we show that the EMC subunit Emc3 plays critical roles in the retinal vascular angiogenesis by regulating Norrin/Wnt signaling. Postnatal endothelial cell(EC)-specific deletion of Emc3 led to retarded retinal vascular development with a hyperpruned vascular network, the appearance of bluntended, aneurysm-like tip endothelial cells(ECs) with reduced numbers of filopodia and leakage of erythrocytes at the vascular front. Diminished tube formation and cell proliferation were also observed in EMC3 depleted human retinal endothelial cells(HRECs). We then discovered a critical role for EMC3 in expression of FZD4 receptor of β-catenin signaling using RNA sequencing, real-time quantitative PCR(RT-q PCR) and luciferase reporter assay. Moreover, augmentation of Wnt activity via lithium chloride(Li Cl) treatment remarkably enhanced β-catenin signaling and cell proliferation of HRECs. Additionally, Li Cl partially reversed the angiogenesis defects in Emc3-c KO mice. Our data reveal that Emc3 plays essential roles in angiogenesis through direct control of FZD4 expression and Norrin/β-catenin signaling.

Deep Natural Image Reconstruction from Human Brain Activity Based on Conditional Progressively Growing Generative Adversarial Networks

Brain decoding based on functional magnetic resonance imaging has recently enabled the identification of visual perception and mental states.However,due to the limitations of sample size and the lack of an effective reconstruction model,accurate reconstruction of natural images is still a major challenge.The current,rapid development of deep learning models provides the possibility of overcoming these obstacles.Here,we propose a deep learning-based framework that includes a latent feature extractor,a latent feature decoder,and a natural image generator,to achieve the accurate reconstruction of natural images from brain activity.The latent feature extractor is used to extract the latent features of natural images.The latent feature decoder predicts the latent features of natural images based on the response signals from the higher visual cortex.The natural image generatoris applied to generate reconstructed images from the predicted latent features of natural images and the response signals from the visual cortex.Quantitative and qualitative evaluations were conducted with test images.The results showed that the reconstructed image achieved comparable,accurate reproduction of the presented image in both highlevel semantic category information and low-level pixel information.The framework we propose shows promise for decoding the brain activity.

Dynamic alterations of amplitude of low-frequency fluctuations in patients with chronic neck pain

Background:The pathogenesis of neck pain in the brain,which is the fourth most common cause of disability,remains unclear.Furthermore,little is known about the characteristics of dynamic local functional brain activity in cervical pain.Objective:The present study aimed to investigate the changes of local brain activity caused by chronic neck pain and the factors leading to neck pain.Methods:Using the amplitude of low-frequency fluctuations(ALFF)method combined with sliding window approach,we compared local brain activity that was measured by the functional magnetic resonance imaging(fMRI)of 107 patients with chronic neck pain(CNP)with that of 57 healthy control participants.Five pathogenic factors were selected for correlation analysis.Results:The group comparison results of dynamic amplitude of low-frequency fluctuation(dALFF)variability showed that patients with CNP exhibited decreased dALFF variability in the left inferior temporal gyrus,the middle temporal gyrus,the angular gyrus,the inferior parietal marginal angular gyrus,and the middle occipital gyrus.The abnormal dALFF variability of the left inferior temporal gyrus was negatively correlated with the average daily working hours of patients with neck pain.Conclusions:The findings indicated that the brain regions of patients with CNP responsible for audition,vision,memory,and emotion were subjected to temporal variability of abnormal regional brain activity.Moreover,the dALFF variability in the left inferior temporal gyrus might be a risk factor for neck pain.This study revealed the brain dysfunction of patients with CNP from the perspective of dynamic local brain activity,and highlighted the important role of dALFF variability in understanding the neural mechanism of CNP.

Mapping brain functional and structural abnormities in autism spectrum disorder:moving toward precision treatment

Autism spectrum disorder(ASD)is a formidable challenge for psychiatry and neuroscience because of its high prevalence,lifelong nature,complexity,and substantial heterogeneity.A major goal of neuroimaging studies of ASD is to understand the neurobiological underpinnings of this disorder from multi-dimensional and multi-level perspectives,by investigating how brain anatomy,function,and connectivity are altered in ASD,and how they vary across the population.However,ongoing debate exists within those studies,and neuroimaging findings in ASD are often contradictory.Over the past decade,we have dedicated to delineate a comprehensive and consistent mapping of the abnormal structure and function of the autistic brain,and this review synthesizes the findings across our studies reaching a consensus that the“social brain”are the most affected regions in the autistic brain at different levels and modalities.We suggest that the social brain network can serve as a plausible biomarker and potential target for effective intervention in individuals with ASD.