Altered small-world brain functional networks and duration of heroin use in male abstinent heroin-dependent individuals

Although previous studies reported addiction-related alteration in resting-state brain connectivity, it is unclear whether these resting-state connectivity alterations were associated with chronic heroin use. In the current study, graph theory analysis (GTA) was applied to detect abnormal topological properties in heroin-dependent individuals. Several statistical parameters, such as degree (D), clustering coefficient (C) and shortest absolute path length (L), were included to test whether or not there was significant correlation between these parameters and the duration of heroin use. Our results demonstrated abnormal topological properties in several brain regions among our heroin-dependent subjects. Some of these regions are key areas of drug addiction-related circuits (control, reward, motivation/drive and memory), while others are involved in stress regulation. In addition, the duration of heroin use was positively correlated with the parameter D in the right parahippocampal gyrus, left putamen and bilateral cerebellum, but negatively correlated with the parameter L in the same regions. Our findings suggested that there is abnormal functional organization in heroin-dependent individuals and that the duration of heroin use is a critical factor leading to the altered brain connectivity.     

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.     

Neural changes after Emotional Freedom Techniques treatment for chronic pain sufferers

This clinical trial investigated the effect of an Emotional Freedom Techniques (EFT) intervention on brain activation in chronic pain sufferers using functional magnetic resonance imaging (fMRI). EFT is a brief stress reduction technique which combines stating a cognitive statement with somatic tapping on acupressure points. Twenty-four adults were allocated to a six-week online group EFT treatment and underwent resting-state fMRI pre and post the intervention. A repeated measures MANOVA indicated significant differences in the levels of pain severity (−21%), pain interference (−26%), quality of life (+7%), somatic symptoms (−28%), depression (−13.5%), anxiety (−37.1%), happiness (+17%), and satisfaction with life (+8.8%) from pre-to post-test. Cohen's effect sizes ranged from small (0.2) to large (0.75) values suggesting significance for the intervention. fMRI analysis showed post-EFT treatment significantly decreased connectivity between the medial prefrontal cortex (a pain modulating area) and bilateral grey matter areas in the posterior cingulate cortex and thalamus, both areas being related to modulating and catastrophizing of pain. There were no brain areas that showed significantly increased connectivity post-EFT treatment. Coupled with the psychological measures the findings support the effects of the EFT intervention in reducing chronic pain and its impacts. Recommendations for future research are discussed.     

The influence of head motion on intrinsic functional connectivity MRI

Functional connectivity MRI (fcMRI) has been widely applied to explore group and individual differences. A confounding factor is head motion. Children move more than adults, older adults more than younger adults, and patients more than controls. Head motion varies considerably among individuals within the same population. Here we explored the influence of head motion on fcMRI estimates. Mean head displacement, maximum head displacement, the number of micro movements (> 0.1 mm), and head rotation were estimated in 1000 healthy, young adult subjects each scanned for two resting-state runs on matched 3T scanners. The majority of fcMRI variation across subjects was not linked to head motion. However, head motion had significant, systematic effects on fcMRI network measures. Head motion was associated with decreased functional coupling in the default and frontoparietal control networks — two networks characterized by coupling among distributed regions of association cortex. Other network measures increased with motion including estimates of local functional coupling and coupling between left and right motor regions — a region pair sometimes used as a control in studies to establish specificity. Comparisons between groups of individuals with subtly different levels of head motion yielded difference maps that could be mistaken for neuronal effects in other contexts. These effects are important to consider when interpreting variation between groups and across individuals.     

The influence of spontaneous activity on stimulus processing in primary visual cortex

Spontaneous activity in the resting human brain has been studied extensively; however, how such activity affects the local processing of a sensory stimulus is relatively unknown. Here, we examined the impact of spontaneous activity in primary visual cortex on neuronal and behavioural responses to a simple visual stimulus, using functional MRI. Stimulus-evoked responses remained essentially unchanged by spontaneous fluctuations, combining with them in a largely linear fashion (i.e., with little evidence for an interaction). However, interactions between spontaneous fluctuations and stimulus-evoked responses were evident behaviourally; high levels of spontaneous activity tended to be associated with increased stimulus detection at perceptual threshold. Our results extend those found in studies of spontaneous fluctuations in motor cortex and higher order visual areas, and suggest a fundamental role for spontaneous activity in stimulus processing.     

Caffeine increases the temporal variability of resting-state BOLD connectivity in the motor cortex

Correlations between spontaneous fluctuations in the blood oxygenation level dependent (BOLD) signal measured with functional MRI are finding increasing use as measures of functional connectivity in the brain, where differences can potentially predict cognitive performance and diagnose disease. Caffeine, which is a widely consumed neural stimulant and vasoactive agent, has been found to decrease the amplitude and correlation of resting-state BOLD fluctuations, and hence is an important factor to consider in functional connectivity studies. However, because the BOLD signal is sensitive to neural and vascular factors, the physiological mechanisms by which caffeine alters spontaneous BOLD fluctuations remain unclear. Resting-state functional connectivity has traditionally been assessed using stationary measures, such as the correlation coefficient between BOLD signals measured across the length of a scan. However, recent work has shown that the correlation of resting-state networks can vary considerably over time, with periods as short as 10 s. In this study, we used a sliding window correlation analysis to assess temporal variations in resting-state functional connectivity of the motor cortex before and after caffeine ingestion. We found that the temporal variability of BOLD correlation was significantly higher following a caffeine dose, with transient periods of strong correlation alternating with periods of low or negative correlation. This phenomenon was primarily due to increased variability in the phase difference between BOLD time courses in the left and right motor cortices. These results indicate that caffeine may cause underlying spontaneous neural fluctuations to go in and out of coherence more frequently, and emphasizes the need to consider non-stationary measures when studying changes in functional connectivity.     

Frequency-dependent functional connectivity within resting-state networks: an atlas-based MEG beamformer solution

The brain consists of functional units with more-or-less specific information processing capabilities, yet cognitive functions require the co-ordinated activity of these spatially separated units. Magnetoencephalography (MEG) has the temporal resolution to capture these frequency-dependent interactions, although, due to volume conduction and field spread, spurious estimates may be obtained when functional connectivity is estimated on the basis of the extra-cranial recordings directly. Connectivity estimates on the basis of reconstructed sources may similarly be affected by biases introduced by the source reconstruction approach.Here we propose an analysis framework to reliably determine functional connectivity that is based around two main ideas: (i) functional connectivity is computed for a set of atlas-based ROIs in anatomical space that covers almost the entire brain, aiding the interpretation of MEG functional connectivity/network studies, as well as the comparison with other modalities; (ii) volume conduction and similar bias effects are removed by using a functional connectivity estimator that is insensitive to these effects, namely the Phase Lag Index (PLI).Our analysis approach was applied to eyes-closed resting-state MEG data for thirteen healthy participants. We first demonstrate that functional connectivity estimates based on phase coherence, even at the source-level, are biased due to the effects of volume conduction and field spread. In contrast, functional connectivity estimates based on PLI are not affected by these biases. We then looked at mean PLI, or weighted degree, over areas and subjects and found significant mean connectivity in three (alpha, beta, gamma) of the five (including theta and delta) classical frequency bands tested. These frequency-band dependent patterns of resting-state functional connectivity were distinctive; with the alpha and beta band connectivity confined to posterior and sensorimotor areas respectively, and with a generally more dispersed pattern for the gamma band. Generally, these patterns corresponded closely to patterns of relative source power, suggesting that the most active brain regions are also the ones that are most-densely connected.Our results reveal for the first time, using an analysis framework that enables the reliable characterisation of resting-state dynamics in the human brain, how resting-state networks of functionally connected regions vary in a frequency-dependent manner across the cortex.     

The discovery of population differences in network community structure: new methods and applications to brain functional networks in schizophrenia

The modular organization of the brain network can vary in two fundamental ways. The amount of inter- versus intra-modular connections between network nodes can be altered, or the community structure itself can be perturbed, in terms of which nodes belong to which modules (or communities). Alterations have previously been reported in modularity, which is a function of the proportion of intra-modular edges over all modules in the network. For example, we have reported that modularity is decreased in functional brain networks in schizophrenia: There are proportionally more inter-modular edges and fewer intra-modular edges. However, despite numerous and increasing studies of brain modular organization, it is not known how to test for differences in the community structure, i.e., the assignment of regional nodes to specific modules. Here, we introduce a method based on the normalized mutual information between pairs of modular networks to show that the community structure of the brain network is significantly altered in schizophrenia, using resting-state fMRI in 19 participants with childhood-onset schizophrenia and 20 healthy participants. We also develop tools to show which specific nodes (or brain regions) have significantly different modular communities between groups, a subset that includes right insular and perisylvian cortical regions. The methods that we propose are broadly applicable to other experimental contexts, both in neuroimaging and other areas of network science.     

Abnormal regions in functional connectivity of chronic schizophrenia

Abstract

Objectives：Schizophrenia is a predominant product of pathological alterations distributed throughout interconnected neural systems. Functional connections (FCs) methodology is an effective lever to investigate macroscopic neural activity patterns underlying critical aspects of cognition and behaviour. However, region properties of brain architecture have been less investigated by special markers of dynamical graph in general mental disorders.

Methods：Embracing the eigenvector centrality in holism significance, our important process is to uncover noticeable edges and regions with antagonistic stance between morbid and normal FCs of 67 healthy controls (HCs) and 53 chronic schizophrenia patients (SZs).

Results: Results suggest that, there are 12 abnormal edges with significant p value of FCs weight, such as lingual gyrus L versus cuneus L, thalamus L versus middle frontal gyrus R, superior temporal gyrus R versus thalamus R. Importantly, SZs’ superior temporal gyrus R, parahippocampal gyrus L and parahippocampal gyrus R are endowed with different eigenvector centrality scores.

Conclusion: Consistent with SZs’ positive symptoms of hallucinations, and negative symptoms of thinking impairment, it can be infer that the functional separation and integration are destroyed in schizophrenia. Thought the strict contrastive study, it is worth stressing that eigenvector centrality is a meaningful biological marker to excavating schizophrenic psychopathology.     

功能磁共振在精神障碍性疾病中的研究进展

功能磁共振成像(resting-state functional magnetic resonance imaging,fMR)l为探索脑工作机制和规律提供了一新思路和方法.其中联合应用静息态功能磁共振成像(fMR)I与弥散张量成像技术(DT)I,在探讨研究精神障碍性患者静息态功能连接与解剖连接的关系方面有一定临床价值.本文就功能磁共振在常见精神障碍性疾病方面的研究进行综述.