Modulatory Interactions of Resting-State Brain Functional Connectivity

The functional brain connectivity studies are generally based on the synchronization of the resting-state functional magnetic resonance imaging (fMRI) signals. Functional connectivity measures usually assume a stable relationship over time; however, accumulating studies have reported time-varying properties of strength and spatial distribution of functional connectivity. The present study explored the modulation of functional connectivity between two regions by a third region using the physiophysiological interaction (PPI) technique. We first identified eight brain networks and two regions of interest (ROIs) representing each of the networks using a spatial independent component analysis. A voxel-wise analysis was conducted to identify regions that showed modulatory interactions (PPI) with the two ROIs of each network. Mostly, positive modulatory interactions were observed within regions involved in the same system. For example, the two regions of the dorsal attention network revealed modulatory interactions with the regions related to attention, while the two regions of the extrastriate network revealed modulatory interactions with the regions in the visual cortex. In contrast, the two regions of the default mode network (DMN) revealed negative modulatory interactions with the regions in the executive network, and vice versa, suggesting that the activities of one network may be associated with smaller within network connectivity of the competing network. These results validate the use of PPI analysis to study modulation of resting-state functional connectivity by a third region. The modulatory effects may provide a better understanding of complex brain functions.     

Default Mode Network in the Effects of Δ9-Tetrahydrocannabinol (THC) on Human Executive Function

Evidence is increasing for involvement of the endocannabinoid system in cognitive functions including attention and executive function, as well as in psychiatric disorders characterized by cognitive deficits, such as schizophrenia. Executive function appears to be associated with both modulation of active networks and inhibition of activity in the default mode network. In the present study, we examined the role of the endocannabinoid system in executive function, focusing on both the associated brain network and the default mode network. A pharmacological functional magnetic resonance imaging (fMRI) study was conducted with a placebo-controlled, cross-over design, investigating effects of the endocannabinoid agonist Δ9-tetrahydrocannabinol (THC) on executive function in 20 healthy volunteers, using a continuous performance task with identical pairs. Task performance was impaired after THC administration, reflected in both an increase in false alarms and a reduction in detected targets. This was associated with reduced deactivation in a set of brain regions linked to the default mode network, including posterior cingulate cortex and angular gyrus. Less deactivation was significantly correlated with lower performance after THC. Regions that were activated by the continuous performance task, notably bilateral prefrontal and parietal cortex, did not show effects of THC. These findings suggest an important role for the endocannabinoid system in both default mode modulation and executive function. This may be relevant for psychiatric disorders associated with executive function deficits, such as schizophrenia and ADHD.     

Stress Impact on Resting State Brain Networks

Resting state brain networks (RSNs) are spatially distributed large-scale networks, evidenced by resting state functional magnetic resonance imaging (fMRI) studies. Importantly, RSNs are implicated in several relevant brain functions and present abnormal functional patterns in many neuropsychiatric disorders, for which stress exposure is an established risk factor. Yet, so far, little is known about the effect of stress in the architecture of RSNs, both in resting state conditions or during shift to task performance. Herein we assessed the architecture of the RSNs using functional magnetic resonance imaging (fMRI) in a cohort of participants exposed to prolonged stress (participants that had just finished their long period of preparation for the medical residence selection exam), and respective gender- and age-matched controls (medical students under normal academic activities). Analysis focused on the pattern of activity in resting state conditions and after deactivation. A volumetric estimation of the RSNs was also performed. Data shows that stressed participants displayed greater activation of the default mode (DMN), dorsal attention (DAN), ventral attention (VAN), sensorimotor (SMN), and primary visual (VN) networks than controls. Importantly, stressed participants also evidenced impairments in the deactivation of resting state-networks when compared to controls. These functional changes are paralleled by a constriction of the DMN that is in line with the pattern of brain atrophy observed after stress exposure. These results reveal that stress impacts on activation-deactivation pattern of RSNs, a finding that may underlie stress-induced changes in several dimensions of brain activity.     

Imagine that: elevated sensory strength of mental imagery in individuals with Parkinson's disease and visual hallucinations

Visual hallucinations occur when our conscious experience does not accurately reflect external reality. However, these dissociations also regularly occur when we imagine the world around us in the absence of visual stimulation. We used two novel behavioural paradigms to objectively measure visual hallucinations and voluntary mental imagery in 19 individuals with Parkinson''s disease (ten with visual hallucinations; nine without) and ten healthy, age-matched controls. We then used this behavioural overlap to interrogate the connectivity both within and between the major attentional control networks using resting-state functional magnetic resonance imaging. Patients with visual hallucinations had elevated mental imagery strength compared with patients without hallucinations and controls. Specifically, the sensory strength of imagery predicted the frequency of visual hallucinations. Together, hallucinations and mental imagery predicted multiple abnormalities in functional connectivity both within and between the attentional control networks, as measured with resting-state functional magnetic resonance imaging. However, the two phenomena were also dissociable at the neural level, with both mental imagery and visual misperceptions associated with specific abnormalities in attentional network connectivity. Our results provide the first evidence of both the shared and unique neural correlates of these two similar, yet distinct phenomena.     

Functional Reorganization of the Default Mode Network across Chronic Pain Conditions

Chronic pain is associated with neuronal plasticity. Here we use resting-state functional magnetic resonance imaging to investigate functional changes in patients suffering from chronic back pain (CBP), complex regional pain syndrome (CRPS) and knee osteoarthritis (OA). We isolated five meaningful resting-state networks across the groups, of which only the default mode network (DMN) exhibited deviations from healthy controls. All patient groups showed decreased connectivity of medial prefrontal cortex (MPFC) to the posterior constituents of the DMN, and increased connectivity to the insular cortex in proportion to the intensity of pain. Multiple DMN regions, especially the MPFC, exhibited increased high frequency oscillations, conjoined with decreased phase locking with parietal regions involved in processing attention. Both phase and frequency changes correlated to pain duration in OA and CBP patients. Thus chronic pain seems to reorganize the dynamics of the DMN and as such reflect the maladaptive physiology of different types of chronic pain.     

fMRI Resting Slow Fluctuations Correlate with the Activity of Fast Cortico-Cortical Physiological Connections

Recording of slow spontaneous fluctuations at rest using functional magnetic resonance imaging (fMRI) allows distinct long-range cortical networks to be identified. The neuronal basis of connectivity as assessed by resting-state fMRI still needs to be fully clarified, considering that these signals are an indirect measure of neuronal activity, reflecting slow local variations in de-oxyhaemoglobin concentration. Here, we combined fMRI with multifocal transcranial magnetic stimulation (TMS), a technique that allows the investigation of the causal neurophysiological interactions occurring in specific cortico-cortical connections. We investigated whether the physiological properties of parieto-frontal circuits mapped with short-latency multifocal TMS at rest may have some relationship with the resting-state fMRI measures of specific resting-state functional networks (RSNs). Results showed that the activity of fast cortico-cortical physiological interactions occurring in the millisecond range correlated selectively with the coupling of fMRI slow oscillations within the same cortical areas that form part of the dorsal attention network, i.e., the attention system believed to be involved in reorientation of attention. We conclude that resting-state fMRI ongoing slow fluctuations likely reflect the interaction of underlying physiological cortico-cortical connections.     

Topological fractionation of resting-state networks

Exploring topological properties of human brain network has become an exciting topic in neuroscience research. Large-scale structural and functional brain networks both exhibit a small-world topology, which is evidence for global and local parallel information processing. Meanwhile, resting state networks (RSNs) underlying specific biological functions have provided insights into how intrinsic functional architecture influences cognitive and perceptual information processing. However, topological properties of single RSNs remain poorly understood. Here, we have two hypotheses: i) each RSN also has optimized small-world architecture; ii) topological properties of RSNs related to perceptual and higher cognitive processes are different. To test these hypotheses, we investigated the topological properties of the default-mode, dorsal attention, central-executive, somato-motor, visual and auditory networks derived from resting-state functional magnetic resonance imaging (fMRI). We found small-world topology in each RSN. Furthermore, small-world properties of cognitive networks were higher than those of perceptual networks. Our findings are the first to demonstrate a topological fractionation between perceptual and higher cognitive networks. Our approach may be useful for clinical research, especially for diseases that show selective abnormal connectivity in specific brain networks.     

慢性疼痛患者静息态脑功能磁共振的默认网络研究

运用静息态功能磁共振成像技术(resting-state fMRI)研究慢性疼痛患者脑默认网络结构.通过选择双侧膝骨性关节炎(knee osteoarthritis,KOA)患者20例和正常志愿者20名,以后扣带回(posterior cingulated cortex,PCC)为种子点,分别进行fMRI扫描,分析配对两组受试者的脑功能连接情况.结果显示相对正常受试者,KOA患者存在异常脑功能连接,主要表现为PCC呈负激活,边缘叶、脑岛呈正激活.     

Changes of Functional Brain Networks in Major Depressive Disorder: A Graph Theoretical Analysis of Resting-State fMRI

Recent developments in graph theory have heightened the need for investigating the disruptions in the topological structure of functional brain network in major depressive disorder (MDD). In this study, we employed resting-state functional magnetic resonance imaging (fMRI) and graph theory to examine the whole-brain functional networks among 42 MDD patients and 42 healthy controls. Our results showed that compared with healthy controls, MDD patients showed higher local efficiency and modularity. Furthermore, MDD patients showed altered nodal centralities of many brain regions, including hippocampus, temporal cortex, anterior cingulate gyrus and dorsolateral prefrontal gyrus, mainly located in default mode network and cognitive control network. Together, our results suggested that MDD was associated with disruptions in the topological structure of functional brain networks, and provided new insights concerning the pathophysiological mechanisms of MDD.     

Selective Vulnerability Related to Aging in Large-Scale Resting Brain Networks

Normal aging is associated with cognitive decline. Evidence indicates that large-scale brain networks are affected by aging; however, it has not been established whether aging has equivalent effects on specific large-scale networks. In the present study, 40 healthy subjects including 22 older (aged 60–80 years) and 18 younger (aged 22–33 years) adults underwent resting-state functional MRI scanning. Four canonical resting-state networks, including the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN) and salience network, were extracted, and the functional connectivities in these canonical networks were compared between the younger and older groups. We found distinct, disruptive alterations present in the large-scale aging-related resting brain networks: the ECN was affected the most, followed by the DAN. However, the DMN and salience networks showed limited functional connectivity disruption. The visual network served as a control and was similarly preserved in both groups. Our findings suggest that the aged brain is characterized by selective vulnerability in large-scale brain networks. These results could help improve our understanding of the mechanism of degeneration in the aging brain. Additional work is warranted to determine whether selective alterations in the intrinsic networks are related to impairments in behavioral performance.     

Identifying Individuals with Antisocial Personality Disorder Using Resting-State fMRI

Antisocial personality disorder (ASPD) is closely connected to criminal behavior. A better understanding of functional connectivity in the brains of ASPD patients will help to explain abnormal behavioral syndromes and to perform objective diagnoses of ASPD. In this study we designed an exploratory data-driven classifier based on machine learning to investigate changes in functional connectivity in the brains of patients with ASPD using resting state functional magnetic resonance imaging (fMRI) data in 32 subjects with ASPD and 35 controls. The results showed that the classifier achieved satisfactory performance (86.57% accuracy, 77.14% sensitivity and 96.88% specificity) and could extract stabile information regarding functional connectivity that could be used to discriminate ASPD individuals from normal controls. More importantly, we found that the greatest change in the ASPD subjects was uncoupling between the default mode network and the attention network. Moreover, the precuneus, superior parietal gyrus and cerebellum exhibited high discriminative power in classification. A voxel-based morphometry analysis was performed and showed that the gray matter volumes in the parietal lobule and white matter volumes in the precuneus were abnormal in ASPD compared to controls. To our knowledge, this study was the first to use resting-state fMRI to identify abnormal functional connectivity in ASPD patients. These results not only demonstrated good performance of the proposed classifier, which can be used to improve the diagnosis of ASPD, but also elucidate the pathological mechanism of ASPD from a resting-state functional integration viewpoint.     

Individual Variability and Test-Retest Reliability Revealed by Ten Repeated Resting-State Brain Scans over One Month

Individual differences in mind and behavior are believed to reflect the functional variability of the human brain. Due to the lack of a large-scale longitudinal dataset, the full landscape of variability within and between individual functional connectomes is largely unknown. We collected 300 resting-state functional magnetic resonance imaging (rfMRI) datasets from 30 healthy participants who were scanned every three days for one month. With these data, both intra- and inter-individual variability of six common rfMRI metrics, as well as their test-retest reliability, were estimated across multiple spatial scales. Global metrics were more dynamic than local regional metrics. Cognitive components involving working memory, inhibition, attention, language and related neural networks exhibited high intra-individual variability. In contrast, inter-individual variability demonstrated a more complex picture across the multiple scales of metrics. Limbic, default, frontoparietal and visual networks and their related cognitive components were more differentiable than somatomotor and attention networks across the participants. Analyzing both intra- and inter-individual variability revealed a set of high-resolution maps on test-retest reliability of the multi-scale connectomic metrics. These findings represent the first collection of individual differences in multi-scale and multi-metric characterization of the human functional connectomes in-vivo, serving as normal references for the field to guide the use of common functional metrics in rfMRI-based applications.     

The Neural Mechanisms Underlying the Acute Effect of Cigarette Smoking on Chronic Smokers

Although previous research had related structural changes and impaired cognition to chronic cigarette smoking, recent neuroimaging studies have associated nicotine, which is a main chemical substance in cigarettes, with improvements in cognitive functions (e.g. improved attention performance). However, information about the alterations of whole-brain functional connectivity after acute cigarette smoking is limited. In this study, 22 smokers underwent resting-state functional magnetic resonance imaging (rs-fMRI) after abstaining from smoking for 12 hours (state of abstinence, SOA). Subsequently, the smokers were allowed to smoke two cigarettes (state of satisfaction, SOS) before they underwent a second rs-fMRI. Twenty non-smokers were also recruited to undergo rs-fMRI. In addition, high-resolution 3D T1-weighted images were acquired using the same magnetic resonance imaging(fMRI)scanner for all participants. The results showed that smokers had structural changes in insula, thalamus, medial frontal cortex and several regions of the default mode network (DMN) compared with non-smokers. Voxel-wise group comparisons of newly developed global brain connectivity (GBC) showed that smokers in the SOA condition had higher GBC in the insula and superior frontal gyrus compared with non-smokers. However, smokers in the SOS condition demonstrated significantly lower GBC in several regions of the DMN, as compared with smokers in the SOA condition. These results suggest that structural integrity combined with dysfunction of the DMN might be involved in relapses after a short period of time among smokers.     

Default Mode,Dorsal Attention and Auditory Resting State Networks Exhibit Differential Functional Connectivity in Tinnitus and Hearing Loss

We investigated auditory, dorsal attention, and default mode networks in adults with tinnitus and hearing loss in a resting state functional connectivity study. Data were obtained using continuous functional magnetic resonance imaging (fMRI) while the participants were at “rest” and were not performing any task. Participants belonged to one of three groups: middle-aged adults with tinnitus and mild-to-moderate high frequency hearing loss (TIN), age-matched controls with normal hearing and no tinnitus (NH), and a second control group with mild-to-moderate high frequency hearing loss without tinnitus (HL). After standard preprocessing, (a) a group independent component analysis (ICA) using 30 components and (b) a seeding-based connectivity analysis were conducted. In the group ICA, the default mode network was the only network to display visual differences between subject groups. In the seeding analysis, we found increased connectivity between the left parahippocampus and the auditory resting state network in the TIN group when compared to NH controls. Similarly, there was also an increased correlation between the right parahippocampus and the dorsal attention network when compared to HL controls. Other group differences in this attention network included decreased correlations between the seed regions and the right supramarginal gyrus in TIN patients when compared to HL controls. In the default mode network, there was a strong decrease in correlation between the seed regions and the precuneus when compared to both control groups. The findings of this study identify specific alterations in the connectivity of the default mode, dorsal attention, and auditory resting state networks due to tinnitus. The results suggest that therapies for tinnitus that mitigate the increased connectivity of limbic regions with auditory and attention resting state networks and the decreased coherence of the default mode network could be effective at reducing tinnitus-related distress.     

Influence of Anodal Transcranial Direct Current Stimulation (tDCS) over the Right Angular Gyrus on Brain Activity during Rest

Although numerous studies examined resting-state networks (RSN) in the human brain, so far little is known about how activity within RSN might be modulated by non-invasive brain stimulation applied over parietal cortex. Investigating changes in RSN in response to parietal cortex stimulation might tell us more about how non-invasive techniques such as transcranial direct current stimulation (tDCS) modulate intrinsic brain activity, and further elaborate our understanding of how the resting brain responds to external stimulation. Here we examined how activity within the canonical RSN changed in response to anodal tDCS applied over the right angular gyrus (AG). We hypothesized that changes in resting-state activity can be induced by a single tDCS session and detected with functional magnetic resonance imaging (fMRI). Significant differences between two fMRI sessions (pre-tDCS and post-tDCS) were found in several RSN, including the cerebellar, medial visual, sensorimotor, right frontoparietal, and executive control RSN as well as the default mode and the task positive network. The present results revealed decreased and increased RSN activity following tDCS. Decreased RSN activity following tDCS was found in bilateral primary and secondary visual areas, and in the right putamen. Increased RSN activity following tDCS was widely distributed across the brain, covering thalamic, frontal, parietal and occipital regions. From these exploratory results we conclude that a single session of anodal tDCS over the right AG is sufficient to induce large-scale changes in resting-state activity. These changes were localized in sensory and cognitive areas, covering regions close to and distant from the stimulation site.     

Comparing structural and functional graph theory features in the human brain using multimodal MRI

Recent advances in magnetic resonance imaging (MRI) are allowing neuroscientists to gain critical insights into the neural networks mediating a variety of cognitive processes. This work investigates structural and functional connectivity in the human brain under different experimental conditions through multimodal MRI acquisitions. To define the nodes of a full-brain network, a set of regions was identified from resting-state functional MRI (fMRI) data using spatial independent component analysis (sICA) and a hierarchical clustering technique. Diffusion-weighted imaging (DWI) data were acquired from the same subjects and a probabilistic fiber tracking method was used to estimate the structure of this network. Using features originating from graph theory, such as small-world properties and network efficiency, we characterized the structural and functional connectivities of the full-brain network and we compared them quantitatively. We showed that structural and functional networks shared some properties in terms of topology as measured by the distribution of the node degrees, hence supporting the existence of an underlying anatomical substrate for functional networks.     

Functional Connectivity Estimated from Resting-State fMRI Reveals Selective Alterations in Male Adolescents with Pure Conduct Disorder

Conduct disorder (CD) is characterized by a persistent pattern of antisocial behavior and aggression in childhood and adolescence. Previous task-based and resting-state functional magnetic resonance imaging (fMRI) studies have revealed widespread brain regional abnormalities in adolescents with CD. However, whether the resting-state networks (RSNs) are altered in adolescents with CD remains unknown. In this study, resting-state fMRI data were first acquired from eighteen male adolescents with pure CD and eighteen age- and gender-matched typically developing (TD) individuals. Independent component analysis (ICA) was implemented to extract nine representative RSNs, and the generated RSNs were then compared to show the differences between the CD and TD groups. Interestingly, it was observed from the brain mapping results that compared with the TD group, the CD group manifested decreased functional connectivity in four representative RSNs: the anterior default mode network (left middle frontal gyrus), which is considered to be correlated with impaired social cognition, the somatosensory network (bilateral supplementary motor area and right postcentral gyrus), the lateral visual network (left superior occipital gyrus), and the medial visual network (right fusiform, left lingual gyrus and right calcarine), which are expected to be relevant to the perceptual systems responsible for perceptual dysfunction in male adolescents with CD. Importantly, the novel findings suggested that male adolescents with pure CD were identified to have dysfunctions in both low-level perceptual networks (the somatosensory network and visual network) and a high-order cognitive network (the default mode network). Revealing the changes in the functional connectivity of these RSNs enhances our understanding of the neural mechanisms underlying the modulation of emotion and social cognition and the regulation of perception in adolescents with CD.     

Dysregulated daily rhythmicity of neuronal resting-state networks in MCI patients

In young healthy participants, the degree of daily rhythmicity largely varies across different neuronal resting-state networks (RSNs), while it is to date unknown whether this temporal pattern of activity is conserved in healthy and pathological aging. Twelve healthy elderly (mean age?=?65.1?±?5.7 years) and 12 patients with amnestic mild cognitive impairment (aMCI; mean age?=?69.6?±?6.2 years) underwent four resting-state functional magnetic resonance imaging scans at fixed 2.5?h intervals throughout a day. Time courses of a RSN were extracted by a connectivity strength and a spatial extent approach performed individually for each participant. Highly rhythmic RSNs included a sensorimotor, a cerebellar and a visual network in healthy elderly; the least rhythmic RSNs in this group included a network associated with executive control and an orbitofrontal network. The degree of daily rhythmicity in aMCI patients was reduced and dysregulated. For healthy elderly, the findings are in accordance with results reported for young healthy participants suggesting a comparable distribution of daily rhythmicity across RSNs during healthy aging. In contrast, the reduction and dysregulation of daily rhythmicity observed in aMCI patients is presumably indicative of underlying neurodegenerative processes in this group.     

Connectivity Features for Identifying Cognitive Impairment in Presymptomatic Carotid Stenosis

Severe asymptomatic stenosis of the internal carotid artery (ICA) leads to increased incidence of mild cognitive impairment (MCI) likely through silent embolic infarcts and/or chronic hypoperfusion, but the brain dysfunction is poorly understood and difficult to diagnose. Thirty cognitively intact subjects with asymptomatic, severe (≧70%), unilateral stenosis of the ICA were compared with 30 healthy controls, matched for age, sex, cardiovascular risk factors and education level, on a battery of neuropsychiatric tests, voxel-based morphometry of magnetic resonance imaging (MRI), diffusion tensor imaging and brain-wise, seed-based analysis of resting-state functional MRI. Multivariate regression models and multivariate pattern classification (support vector machines) were computed to assess the relationship between connectivity measures and neurocognitive performance. The patients had worse dizziness scores and poorer verbal memory, executive function and complex visuo-spatial performance than controls. Twelve out of the 30 patients (40%) were considered to have MCI. Nonetheless, the leukoaraiosis Sheltens scores, hippocampal and brain volumes were not different between groups. Their whole-brain mean fractional anisotropy (FA) was significantly reduced and regional functional connectivity (Fc) was significantly impaired in the dorsal attention network (DAN), frontoparietal network, sensorimotor network and default mode network. In particular, the Fc strength at the insula of the DAN and the mean FA were linearly related with attention performance and dizziness severity, respectively. The multivariate pattern classification gave over 90% predictive accuracy of individuals with MCI or severe dizziness. Cognitive decline in stroke-free individuals with severe carotid stenosis may arise from nonselective widespread disconnections of long-range, predominantly interhemispheric non-hippocampal pathways. Connectivity measures may serve as both predictors for cases at risk and therapeutic targets for mitigating vascular cognitive impairment.     

Evaluating the effective connectivity of resting state networks using conditional Granger causality

The human brain has been documented to be spatially organized in a finite set of specific coherent patterns, namely resting state networks (RSNs). The interactions among RSNs, being potentially dynamic and directional, may not be adequately captured by simple correlation or anticorrelation. In order to evaluate the possible effective connectivity within those RSNs, we applied a conditional Granger causality analysis (CGCA) to the RSNs retrieved by independent component analysis (ICA) from resting state functional magnetic resonance imaging (fMRI) data. Our analysis provided evidence for specific causal influences among the detected RSNs: default-mode, dorsal attention, core, central-executive, self-referential, somatosensory, visual, and auditory networks. In particular, we identified that self-referential and default-mode networks (DMNs) play distinct and crucial roles in the human brain functional architecture. Specifically, the former RSN exerted the strongest causal influence over the other RSNs, revealing a top-down modulation of self-referential mental activity (SRN) over sensory and cognitive processing. In quite contrast, the latter RSN was profoundly affected by the other RSNs, which may underlie an integration of information from primary function and higher level cognition networks, consistent with previous task-related studies. Overall, our results revealed the causal influences among these RSNs at different processing levels, and supplied information for a deeper understanding of the brain network dynamics.