Combining spatial and temporal information to explore resting-state networks changes in abstinent heroin-dependent individuals

Majority of previous heroin fMRI studies focused on abnormal brain function in heroin-dependent individuals. However, few fMRI studies focused on the resting-state abnormalities in heroin-dependent individuals and assessed the relationship between the resting-state functional connectivity changes and duration of heroin use. In the present study, discrete cosine transform (DCT) was employed to explore spatial distribution of low frequency BOLD oscillations in heroin-dependent individuals and healthy subjects during resting-state; meanwhile resting-state functional connectivity analysis was used to investigate the temporal signatures of overlapping brain regions obtained in DCT analysis among these two groups. Main finding of the present study is that the default mode network (DMN) and rostral anterior cingulate cortex (rACC) network of heroin-dependent individuals were changed compared with healthy subjects. More importantly, these changes negatively correlated with duration of heroin use. These resting-state functional abnormalites in heroin-dependent individuals provided evidence for abnormal functional organization in heroin-dependent individuals, such as functional impairments in decision-making and inhibitory control.     

Gray matter deficits and resting-state abnormalities in abstinent heroin-dependent individuals

Previous neuroimaging studies have demonstrated both structural and functional damages in heroin-dependent individuals. However, few studies investigated gray matter deficits and abnormal resting-state networks together in heroin-dependent individuals. In the present study, voxel-based morphometry (VBM) was used to identify brain regions with gray matter density reduction. Resting-state fMRI connectivity analysis was employed to assess potential functional abnormalities during resting-state. All clinical significances were investigated by examining their association with duration of heroin use. Compared with healthy subjects, heroin-dependent individuals showed significant reduction in gray matter density in the right dorsolateral prefrontal cortex (DLPFC) and a decrease in resting-state functional connectivity between the right DLPFC and left inferior parietal lobe (IPL). The gray matter density of the right DLPFC and its resting-state functional connectivity with the left IPL both showed significantly negative correlation with duration of heroin use, which were likely to be related to the functional impairments in decision-making and cognitive control exhibited by heroin-dependent individuals. Our findings demonstrated that long heroin dependence impairs the right DLPFC in heroin-dependent individuals, including structural deficits and resting-state functional impairments.     

Dysfunctional connectivity patterns in chronic heroin users: An fMRI study

Recent functional neuroimaging studies have examined cognitive inhibitory control, decision-making and stress regulation in heroin addiction using a cue-reactivity paradigm. Few studies have considered impairments in heroin users from an integrated perspective for evaluation of their brain functions. We hypothesized that the brain regions that are dysregulated in the chronic heroin users during cue-reactivity studies may also show dysfunctional connectivity in memory, inhibition and motivation-related dysfunctions during a resting state free of cues. The present study used resting functional magnetic resonance imaging (fMRI) to compare the interaction of brain regions between 12 chronic heroin users and 12 controls by employing a novel graph theory analysis (GTA) method. As a data-driven approach, GTA has the advantage of evaluating the strength as well as the temporal and spatial patterns of interactions among the brain regions. Abnormal topological properties were explored in the brain of chronic heroin users, such as the dysfunctional connectivity in the prefrontal cortex, ACC, SMA, ventral striatum, insula, amygdala and hippocampus. Our results suggest that GTA is a useful tool in defining dysregulated neural networks even during rest. This dysfunctional brain connectivity may contribute to decrease self-control, impaired inhibitory function as well deficits in stress regulation in chronic heroin users.     

慢性失眠患者大脑蓝斑的异常静息态功能连接

目的:利用功能连接方法观察慢性失眠患者静息态下蓝斑的异常功能连接。方法:采集49例慢性失眠患者以及47例性别年龄和受教育程度相匹配的健康对照组的功能磁共振图像,以蓝斑为感兴趣区域,与全脑其他体素进行功能连接分析,得到两组之间功能连接的差异脑区,再对异常连接脑区的功能连接值与临床量表分数做相关分析。结果:与对照组相比,慢性失眠患者蓝斑与右楔前叶皮质、右后扣带回皮质、左颞中回皮质、左距状沟周围皮质、右眶部额上回皮质之间的功能连接增强（P<0.05, FDR校正）,并且蓝斑与左颞中回皮质之间功能连接值与抑郁自评量表呈正相关（P=0.021）。结论:慢性失眠患者蓝斑与多个脑区（主要是默认模式网络）出现的异常功能连接,可能有助于更好地理解慢性失眠的神经生物学机制,可能为失眠的高度唤醒假说提供新的影像学证据。     

Neural mechanisms of oxytocin receptor gene mediating anxiety-related temperament

A common variant (rs53576) of the OXTR gene has been implicated in a number of socio-emotional phenotypes, such as anxiety-related behavior. Previous studies have demonstrated that A-allele carriers have higher levels of physiological and dispositional stress reactivity and depressive symptomatology compared to those with the GG genotype, but the mediating neural mechanisms remain poorly understood. We combined voxel-based morphometry and resting-state functional connectivity analyses in a large cohort of healthy young Chinese Han individuals to test the hypothesis that the OXTR gene polymorphism influences an anxiety-related temperamental trait, as assessed by the harm avoidance subscale from the Tridimensional Personality Questionnaire via modulating the gray matter volume and resting-state functional connectivity of the brain, especially the limbic system. We revealed that female subjects with the AA genotype showed increased harm avoidance scores relative to G-carrier females. We also found that, compared to female individuals with the GG/GA genotype, female individuals with the AA genotype exhibited significantly smaller amygdala volumes bilaterally (especially the centromedial subregion), with a trend of allele-load-dependence. Compared to female individuals with the GG/GA genotype, female subjects with the AA genotype demonstrated reduced resting-state functional coupling between the prefrontal cortex and amygdala bilaterally, also with an allele-load-dependent trend. Furthermore, the magnitude of prefrontal-amygdala coupling in the left hemisphere was positively correlated with harm avoidance scores in female subjects. Our findings highlight a possible neural pathway by which a naturally occurring variation of the OXTR gene may affect an anxiety-related temperamental trait in female subjects by modulating prefrontal-amygdala functional connectivity.     

丁丙诺啡舌下片合并东莨菪碱、异丙嗪药物依赖者脑灰质密度的研究

目的:观察盐酸丁丙诺啡舌下片(sublingual buprenorphine)合并东莨菪碱(scopolamine)、异丙嗪(promet鄄hazine)药物依赖者(简称BSP依赖者)脑灰质密度的变化,并比较其与海洛因依赖者脑结构损害的异同。方法:采用基于像素的形态学测量(voxel-based morphometry,VBM)方法对16例BSP依赖者、20例海洛因依赖者停药第3天、第2个月的脑灰质密度进行了组间以及组内自身前后对比研究,并设立18例正常对照者。结果:与正常对照组相比,BSP滥用可导致成瘾者大脑广泛性脑结构损害,表现为灰质密度下降,涉及额叶、顶叶、颞叶、枕叶、岛叶、纹状体等脑区;与海洛因依赖组相比,停药3天BSP依赖组脑区灰质受损程度重于海洛因依赖组,且随着停药时间的延长,BSP依赖者灰质恢复进程慢于海洛因依赖者。结论:BSP滥用可造成依赖者广泛性、严重的脑皮质结构异常,主要集中在额叶等与成瘾关系密切的脑区。BSP滥用较海洛因更易损伤大脑皮质神经元,且大脑灰质恢复进程慢于海洛因依赖组,这提示BSP滥用对大脑皮质神经元的损害在短时间难以恢复。     

Polymorphisms of brain-derived neurotrophic factor associated with heroin dependence

Brain-derived neurotrophic factor (BDNF) promotes synaptic remodeling and modulates the function of other neurotransmitters. It also plays a role in the reward response to many drugs, including heroin. To identify genetic variants associated with heroin dependence, we compared four single nucleotide polymorphisms (SNPs, rs13306221, rs6265, rs56164415, and rs16917204) of the BDNF gene in 487 subjects with heroin dependence and 492 healthy individuals. The analysis revealed the G allele of rs6265 was significantly more common in heroin-dependent subjects than in the healthy controls (P=0.001 after Bonferroni correction). Among heroin-dependent individuals, the onset of dependence was significantly earlier in individuals with GG or GA genotypes compared to AA individuals (P<0.01). Additionally, we found that the G allele of rs13306221 was significantly more frequent in heroin-dependent subjects than in controls (P=0.005 after Bonferroni correction). These findings support a role of BDNF rs6265 and rs13306221 polymorphisms in heroin dependence and may guide future studies to identify other genetic risk factors for heroin dependence.     

Resting-State Functional Connectivity Within Medial Prefrontal Cortex Mediates Age Differences in Risk Taking

To investigate the association between age-related changes in risk taking and resting-state functional activity, we recorded resting-state scans from both young (n = 26) and older adults (n = 27). In addition, all participants completed two decision-making tasks: the Cambridge Gambling Task and the Balloon Analogue Risk Task. We found that older adults showed decreased functional connectivity within the medial prefrontal cortex, particularly between the ventromedial prefrontal cortex and the dorsal medial prefrontal cortex. Moreover, these changes in resting-state functional connectivity were associated with the individuals’ risk-taking behavior, and mediated the influence of age on risk taking.     

Detecting Functional Connectivity in fMRI Using PCA and Regression Analysis

A fMRI connectivity analysis approach combining principal component analysis (PCA) and regression analysis is proposed to detect functional connectivity between the brain regions. By first using PCA to identify clusters within the vectors of fMRI time series, more energy and information features in the signal can be maintained than using averaged values from brain regions of interest. Then, regression analysis can be applied to the extracted principal components in order to further investigate functional connectivity. Finally, t-test is applied and the patterns with t-values lager than a threshold are considered as functional connectivity mappings. The validity and reliability of the presented method were demonstrated with both simulated data and human fMRI data obtained during behavioral task and resting state. Compared to the conventional functional connectivity methods such as average signal based correlation analysis, independent component analysis (ICA) and PCA, the proposed method achieves competitive performance with greater accuracy and true positive rate (TPR). Furthermore, the ‘default mode’ and motor network results of resting-state fMRI data indicate that using PCA may improve upon application of existing regression analysis methods in study of human brain functional connectivity.     

Insights into TREM2 biology by network analysis of human brain gene expression data

Rare variants in TREM2 cause susceptibility to late-onset Alzheimer's disease. Here we use microarray-based expression data generated from 101 neuropathologically normal individuals and covering 10 brain regions, including the hippocampus, to understand TREM2 biology in human brain. Using network analysis, we detect a highly preserved TREM2-containing module in human brain, show that it relates to microglia, and demonstrate that TREM2 is a hub gene in 5 brain regions, including the hippocampus, suggesting that it can drive module function. Using enrichment analysis we show significant overrepresentation of genes implicated in the adaptive and innate immune system. Inspection of genes with the highest connectivity to TREM2 suggests that it plays a key role in mediating changes in the microglial cytoskeleton necessary not only for phagocytosis, but also migration. Most importantly, we show that the TREM2-containing module is significantly enriched for genes genetically implicated in Alzheimer's disease, multiple sclerosis, and motor neuron disease, implying that these diseases share common pathways centered on microglia and that among the genes identified are possible new disease-relevant genes.     

Disrupted brain connectome in semantic variant of primary progressive aphasia

Using resting-state functional magnetic resonance imaging and graph analysis, the topological organization of the functional brain network connectivity was explored in patients with left-sided onset semantic variant (SV) of primary progressive aphasia relative to healthy controls. Functional brain networks in SV patients were characterized by a significantly lower mean network degree, clustering coefficient, and global efficiency, longer characteristic path length and higher assortativity compared with controls. SV patients showed also a strongly left-lateralized loss of hubs, and reduced nodal degree in the inferior and ventral temporal regions and occipital cortices. In SV, the decreased nodal degree extended into the medial and ventral frontal cortex bilaterally, left amygdala and/or hippocampus, and left caudate nucleus. These findings provide evidence that the focal structural degeneration of the inferior temporal, and perysilvian language regions in SV patients ultimately results in a distributed pattern of functional connectivity abnormalities. The local network analysis shows that SV is associated with a functional degradation in the “pan-modal” inferior and/or ventral temporal regions, and the “modality-specific” visual cortical origin of the ventral processing pathway.     

Abnormal Functional Connectivity Density in Post-traumatic Stress Disorder

Post-traumatic stress disorder (PTSD) is a psychiatric disorder that occurs in individuals who have experienced life-threatening mental traumas. Previous neuroimaging studies have indicated that the pathology of PTSD may be associated with the abnormal functional integration among brain regions. In the current study, we used functional connectivity density (FCD) mapping, a novel voxel-wise data-driven approach based on graph theory, to explore aberrant FC through the resting-state functional magnetic resonance imaging of the PTSD. We calculated both short- and long-range FCD in PTSD patients and healthy controls (HCs). Compared with HCs, PTSD patients showed significantly increased long-range FCD in the left dorsolateral prefrontal cortex (DLPFC), but no abnormal short-range FCD was found in PTSD. Furthermore, seed-based FC analysis of the left DLPFC showed increased connectivity in the left superior parietal lobe and visual cortex of PTSD patients. The results suggested that PTSD patients experienced a disruption of intrinsic long-range functional connections in the fronto-parietal network and visual cortex, which are associated with attention control and visual information processing.     

Resting state functional connectivity of five neural networks in bipolar disorder and schizophrenia

Background

Bipolar disorder (BPD) and schizophrenia (SCZ) share clinical characteristics and genetic contributions. Functional dysconnectivity across various brain networks has been reported to contribute to the pathophysiology of both SCZ and BPD. However, research examining resting-state neural network dysfunction across multiple networks to understand the relationship between these two disorders is lacking.

Methods

We conducted a resting-state functional connectivity fMRI study of 35 BPD and 25 SCZ patients, and 33 controls. Using previously defined regions-of-interest, we computed the mean connectivity within and between five neural networks: default mode (DM), fronto-parietal (FP), cingulo-opercular (CO), cerebellar (CER), and salience (SAL). Repeated measures ANOVAs were used to compare groups, adjusting false discovery rate to control for multiple comparisons. The relationship of connectivity with the SANS/SAPS, vocabulary and matrix reasoning was investigated using hierarchical linear regression analyses.

Results

Decreased within-network connectivity was only found for the CO network in BPD. Across groups, connectivity was decreased between CO-CER (p<0.001), to a larger degree in SCZ than in BPD. In SCZ, there was also decreased connectivity in CO-SAL, FP-CO, and FP-CER, while BPD showed decreased CER-SAL connectivity. Disorganization symptoms were predicted by connectivity between CO-CER and CER-SAL.

Discussion

Our findings indicate dysfunction in the connections between networks involved in cognitive and emotional processing in the pathophysiology of BPD and SCZ. Both similarities and differences in connectivity were observed across disorders. Further studies are required to investigate relationships of neural networks to more diverse clinical and cognitive domains underlying psychiatric disorders.     

PTSD and its dissociative subtype through the lens of the insula: Anterior and posterior insula resting-state functional connectivity and its predictive validity using machine learning

Individuals with post-traumatic stress disorder (PTSD) typically experience states of reliving and hypervigilance; however, the dissociative subtype of PTSD (PTSD+DS) presents with additional symptoms of depersonalization and derealization. Although the insula is critical to emotion processing, its association with these contrasting symptom profiles is yet to be fully delineated. Accordingly, we investigated insula subregion resting-state functional connectivity patterns among individuals with PTSD, PTSD+DS, and healthy controls. Using SPM12 and PRONTO software, we implemented a seed-based resting-state functional connectivity approach, along with multiclass Gaussian process classification machine learning, respectively, in order to evaluate unique patterns and the predictive validity of insula subregion connectivity among individuals with PTSD (n = 84), PTSD+DS (n = 49), and age-matched healthy controls (n = 51). As compared to PTSD and PTSD+DS, healthy controls showed increased right anterior and posterior insula connectivity with frontal lobe structures. By contrast, PTSD showed increased bilateral posterior insula connectivity with subcortical structures, including the periaqueductal gray. Strikingly, as compared to PTSD and controls, PTSD+DS showed increased bilateral anterior and posterior insula connectivity with posterior cortices, including the left lingual gyrus and the left precuneus. Moreover, machine learning analyses were able to classify PTSD, PTSD+DS, and controls using insula subregion connectivity patterns with 80.4% balanced accuracy (p < .01). These findings suggest a neurobiological distinction between PTSD and its dissociative subtype with regard to insula subregion functional connectivity patterns. Furthermore, machine learning algorithms were able to utilize insula resting-state connectivity patterns to discriminate between participant groups with high predictive accuracy.     

Endophenotypes in a Dynamically Connected Brain

We examined the longitudinal genetic architecture of three parameters of functional brain connectivity. One parameter described overall connectivity (synchronization likelihood, SL). The two others were derived from graph theory and described local (clustering coefficient, CC) and global (average path length, L) aspects of connectivity. We measured resting state EEG in 1,438 subjects from four age groups of about 16, 18, 25 and 50 years. Developmental curves for SL and L indicate that connectivity is more random at adolescence and old age, and more structured in middle-aged adulthood. Individual variation in SL and L were moderately to highly heritable at each age (SL: 40–82%; L: 29–63%). Genetic factors underlying these phenotypes overlapped. CC was also heritable (25–49%) but showed no systematic overlap with SL and L. SL, CC, and L in the alpha band showed high phenotypic and genetic stability from 16 to 25 years. Heritability for parameters in the beta band was lower, and less stable across ages, but genetic stability was high. We conclude that the connectivity parameters SL, CC, and L in the alpha band show the hallmarks of a good endophenotype for behavior and developmental disorders.     

Greater than the sum of its parts: a review of studies combining structural connectivity and resting-state functional connectivity

It is commonly assumed that functional brain connectivity reflects structural brain connectivity. The exact relationship between structure and function, however, might not be straightforward. In this review we aim to examine how our understanding of the relationship between structure and function in the ‘resting’ brain has advanced over the last several years. We discuss eight articles that directly compare resting-state functional connectivity with structural connectivity and three clinical case studies of patients with limited white matter connections between the cerebral hemispheres. All studies examined show largely convergent results: the strength of resting-state functional connectivity is positively correlated with structural connectivity strength. However, functional connectivity is also observed between regions where there is little or no structural connectivity, which most likely indicates functional correlations mediated by indirect structural connections (i.e. via a third region). As the methodologies for measuring structural and functional connectivity continue to improve and their complementary strengths are applied in parallel, we can expect important advances in our diagnostic and prognostic capacities in diseases like Alzheimer’s, multiple sclerosis, and stroke.     

Disruption of prefrontal function and connectivity in individuals with phenylketonuria

Phenylketonuria (PKU) is a genetic disorder associated with disruption of prefrontal cortex (PFC) development and executive dysfunction. To date, however, there is little evidence directly linking these two sequelae of PKU. We utilized functional magnetic resonance imaging (fMRI) to evaluate prefrontal functioning in six individuals with early-treated PKU (ETPKU) during performance of an n-back working memory task and compared results with those of six age- and gender-matched neurologically intact individuals. In addition, we evaluated the possible presence of PKU-related disruptions in functional connectivity, as might be hypothesized based on prior reports of white matter injury in individuals with ETPKU. A number of brain regions, nearly half of which were located in the PFC, were found to show atypical neural activity in individuals with ETPKU during working memory performance. We also found decreased connectivity both within the PFC as well as between the PFC and other brain regions in individuals with ETPKU compared with controls. Results from this preliminary study suggest that both prefrontal dysfunction and disruptions in functional connectivity may contribute to PKU-related executive impairment. In addition to advancing our understanding of PKU, the current findings have a broader impact in that PKU is regularly used as a model of early prefrontal dysfunction in the study of other neurodevelopmental disorders (e.g., autism).     

Fast computation of voxel-level brain connectivity maps from resting-state functional MRI using l1-norm as approximation of Pearson's temporal correlation: Proof-of-concept and example vector hardware implementation

An outstanding issue in graph-based analysis of resting-state functional MRI is choice of network nodes. Individual consideration of entire brain voxels may represent a less biased approach than parcellating the cortex according to pre-determined atlases, but entails establishing connectedness for 1⁹–1¹¹ links, with often prohibitive computational cost. Using a representative Human Connectome Project dataset, we show that, following appropriate time-series normalization, it may be possible to accelerate connectivity determination replacing Pearson correlation with l₁-norm. Even though the adjacency matrices derived from correlation coefficients and l₁-norms are not identical, their similarity is high. Further, we describe and provide in full an example vector hardware implementation of l₁-norm on an array of 4096 zero instruction-set processors. Calculation times <1000 s are attainable, removing the major deterrent to voxel-based resting-sate network mapping and revealing fine-grained node degree heterogeneity. L₁-norm should be given consideration as a substitute for correlation in very high-density resting-state functional connectivity analyses.     

海洛因成瘾者静息状态下脑功能连接研究

目的:探讨海洛因成瘾者在静息状态下脑功能连接与正常对照的区别。方法:对16例海洛因成瘾者和16例匹配的正常对照进行静息状态下的脑功能扫描。选择杏仁核为种子区,比较两组之间脑功能连接的区别。结果:同正常对照相比,海洛因成瘾者杏仁核与左右扣带回、左右扣带回前部以及右侧Brodmann 24脑区功能连接下降。结论:这种功能连接的下降可能反映出海洛因成瘾者的杏仁核功能处于脱抑制状态,造成海洛因成瘾者犒赏、动机、记忆功能异常,从而参与了海洛因成瘾行为产生和维持。     

Study on Functional Connectivity Density in Patients with Frontal Lobe Tumor at Resting-State

At present, the neuropathological mechanisms and the plastic changes of brain cognitive function in patents with front lobe tumor remain unclear, most studies just focused on global measures of brain functional connectivity without considering the time correlation in the different regions of the brain. This study aims to investigate brain cognitive alterations and functional plasticity in patients with front lobe tumor at resting-state by conducting functional connectivity density(FCD) mapping and granger causality analysis(GCA). Firstly, FCD mapping was used to extract abnormal functional connectivity(FC) of patients with frontal lobe tumor, and analyzed altered brain FC in both short-and long-range FCD. Then, the voxel-wise GCA method was used to analyze the causal relationship between altered FC regions and other regions in order to detect the time correlation between regions of interest(ROI) and reveal the direction of information flow between brain ROIs. It was found that patients had increased short-range FCD in motor and space attention function areas, had increased short-and long-range FCDs both in Temporal and Insula, and the causal coefficients were changed obviously in Temporal and Frontal. The results show that there is a functional plasticity in space attention function areas. Temporal and Insula are affected by tumor in frontal lobe, and functional reorganization appears inside Temporal.