The effect of resting condition on resting-state fMRI reliability and consistency: a comparison between resting with eyes open, closed, and fixated

Mesolimbic Dopamine Function Is Related to Salience Network Connectivity: An Integrative Positron Emission Tomography and Magnetic Resonance Study

BACKGROUND

A wide range of neuropsychiatric disorders, from schizophrenia to drug addiction, involve abnormalities in both the mesolimbic dopamine system and the cortical salience network. Both systems play a key role in the detection of behaviorally relevant environmental stimuli. Although anatomical overlap exists, the functional relationship between these systems remains unknown. Preclinical research has suggested that the firing of mesolimbic dopamine neurons may activate nodes of the salience network, but in vivo human research is required given the species-specific nature of this network.

METHODS

We employed positron emission tomography to measure both dopamine release capacity (using the D2/3 receptor ligand 11C-PHNO, n = 23) and dopamine synthesis capacity (using 18F-DOPA, n = 21) within the ventral striatum. Resting-state functional magnetic resonance imaging was also undertaken in the same individuals to investigate salience network functional connectivity. A graph theoretical approach was used to characterize the relationship between dopamine measures and network connectivity.

RESULTS

Dopamine synthesis capacity was associated with greater salience network connectivity, and this relationship was particularly apparent for brain regions that act as information-processing hubs. In contrast, dopamine release capacity was associated with weaker salience network connectivity. There was no relationship between dopamine measures and visual and sensorimotor networks, indicating specificity of the findings.

CONCLUSIONS

Our findings demonstrate a close relationship between the salience network and mesolimbic dopamine system, and they are relevant to neuropsychiatric illnesses in which aberrant functioning of both systems has been observed.

The right thalamic glutamate level correlates with functional connectivity with right dorsal anterior cingulate cortex/middle occipital gyrus in unmedicated obsessive-compulsive disorder: A combined fMRI and 1H-MRS study

OBJECTIVE

The imbalance in neurotransmitter and neuronal metabolite concentration within cortico-striato-thalamo-cortical (CSTC) circuit contributes to obsessive-compulsive disorder's (OCD) onset. Previous studies showed that glutamate mediated upregulation of resting-state activity in healthy people. However, there have been few studies investigating the correlational features between functional and neurochemical alterations in OCD.

METHODS

We utilize a combined resting-state functional magnetic resonance imaging (rs-fMRI) and proton magnetic resonance spectroscopy (¹H-MRS) approach to investigate the altered functional connectivity (FC) in association with glutamatergic dysfunction in OCD pathophysiology. Three regions of interest are investigated, i.e., medial prefrontal cortex and bilateral thalamus, for seed-based whole-brain FC analysis as well as MRS data acquisition. There are 23 unmedicated adult OCD patients and 23 healthy controls recruited for brain FC analysis. Among them, 12 OCD and 8 controls are performed MRS data acquisition.

RESULTS

Besides abnormal FC within CSTC circuit, we also find altered FCs in large-scale networks outside CSTC circuit, including occipital area and limbic and motor systems. The decreased FC between right thalamus and right middle occipital gyrus (MOG) is correlated with glutamatergic signal within right thalamus in OCD patients. Moreover, the FC between right thalamus and right dorsal anterior cingulate cortex (dACC) is associated with glutamate level in right thalamus, specifically in patient's group. Finally, the FC between right thalamus and right MOG is correlated with patient's Yale-Brown Obsessive Compulsive Scale (YBOCS) compulsion and total scores, while the right thalamic glutamatergic signal is associated with YBOCS-compulsion score.

CONCLUSION

Our findings showed that the coupled intrinsic functional-biochemical alterations existed both within CSTC circuit and from CSTC to occipital lobe in OCD pathophysiology.

Primary biliary cholangitis patients exhibit MRI changes in structure and function of interoceptive brain regions

Background

Many patients with primary biliary cholangitis (PBC) experience non-hepatic symptoms that are possibly linked to altered interoception, the sense of the body’s internal state. We used magnetic resonance imaging (MRI) to determine if PBC patients exhibit structural and functional changes of the thalamus and insula, brain regions that process signals related to interoception.

Methods

Fifteen PBC patients with mild disease and 17 controls underwent 3 Tesla T₁-weighted MRI, resting-state functional MRI, and quantitative susceptibility mapping (QSM), to measure thalamic and insular volume, neuronal activity and iron deposition, respectively. Group differences were assessed using analysis of covariance, and stepwise linear regression was used to determine the predictive power of clinical indicators of disease.

Results

PBC patients exhibited reduced thalamic volume (p < 0.01), and ursodeoxycholic acid (UDCA) non-responders exhibited lower left thalamus activity (p = 0.05). PBC patients also exhibited reduced anterior insula activity (p = 0.012), and liver stiffness positively correlated with MRI indicators of anterior insula iron deposition (p < 0.02).

Conclusions

PBC affects structure and function of brain regions critically important to interoception. Moreover, these brain changes occur in patients with early, milder disease and thus may potentially be reversible.

A study of within-subject reliability of the brain's default-mode network

Objective

Resting-state functional magnetic resonance imaging (fMRI) is promising for Alzheimer’s disease (AD). This study aimed to examine short-term reliability of the default-mode network (DMN), one of the main haemodynamic patterns of the brain.

Materials and methods

Using a 1.5 T Philips Achieva scanner, two consecutive resting-state fMRI runs were acquired on 69 healthy adults, 62 patients with mild cognitive impairment (MCI) due to AD, and 28 patients with AD dementia. The anterior and posterior DMN and, as control, the visual-processing network (VPN) were computed using two different methodologies: connectivity of predetermined seeds (theory-driven) and dual regression (data-driven). Divergence and convergence in network strength and topography were calculated with paired t tests, global correlation coefficients, voxel-based correlation maps, and indices of reliability.

Results

No topographical differences were found in any of the networks. High correlations and reliability were found in the posterior DMN of healthy adults and MCI patients. Lower reliability was found in the anterior DMN and in the VPN, and in the posterior DMN of dementia patients.

Discussion

Strength and topography of the posterior DMN appear relatively stable and reliable over a short-term period of acquisition but with some degree of variability across clinical samples.

Resting state connectivity differences in eyes open versus eyes closed conditions

Functional magnetic resonance imaging data are commonly collected during the resting state. Resting state functional magnetic resonance imaging (rs-fMRI) is very practical and applicable for a wide range of study populations. Rs-fMRI is usually collected in at least one of three different conditions/tasks, eyes closed (EC), eyes open (EO), or eyes fixated on an object (EO-F). Several studies have shown that there are significant condition-related differences in the acquired data. In this study, we compared the functional network connectivity (FNC) differences assessed via group independent component analysis on a large rs-fMRI dataset collected in both EC and EO-F conditions, and also investigated the effect of covariates (e.g., age, gender, and social status score). Our results indicated that task condition significantly affected a wide range of networks; connectivity of visual networks to themselves and other networks was increased during EO-F, while EC was associated with increased connectivity of auditory and sensorimotor networks to other networks. In addition, the association of FNC with age, gender, and social status was observed to be significant only in the EO-F condition (though limited as well). However, statistical analysis did not reveal any significant effect of interaction between eyes status and covariates. These results indicate that resting-state condition is an important variable that may limit the generalizability of clinical findings using rs-fMRI.

Long-Range Temporal Correlations in Resting State Beta Oscillations are Reduced in Schizophrenia

Symptoms of schizophrenia (SCZ) are likely to be generated by genetically mediated synaptic dysfunction, which contribute to large-scale functional neural dysconnectivity. Recent electrophysiological studies suggest that this dysconnectivity is present not only at a spatial level but also at a temporal level, operationalized as long-range temporal correlations (LRTCs). Previous research suggests that alpha and beta frequency bands have weaker temporal stability in people with SCZ. This study sought to replicate these findings with high-density electroencephalography (EEG), enabling a spatially more accurate analysis of LRTC differences, and to test associations with characteristic SCZ symptoms and cognitive deficits. A 128-channel EEG was used to record eyes-open resting state brain activity of 23 people with SCZ and 24 matched healthy controls (HCs). LRTCs were derived for alpha (8-12 Hz) and beta (13-25 Hz) frequency bands. As an exploratory analysis, LRTC was source projected using sLoreta. People with SCZ showed an area of significantly reduced beta-band LRTC compared with HCs over bilateral posterior regions. There were no between-group differences in alpha-band activity. Individual symptoms of SCZ were not related to LRTC values nor were cognitive deficits. The study confirms that people with SCZ have reduced temporal stability in the beta frequency band. The absence of group differences in the alpha band may be attributed to the fact that people had, in contrast to previous studies, their eyes open in the current study. Taken together, our study confirms the utility of LRTC as a marker of network instability in people with SCZ and provides a novel empirical perspective for future examinations of network dysfunction salience in SCZ research.

A longitudinal human phantom reliability study of multi-center T1-weighted, DTI, and resting state fMRI data

Multi-center MRI studies can enhance power, generalizability, and discovery for clinical neuroimaging research in brain disorders. Here, we sought to establish the utility of a clustering algorithm as an alternative to more traditional intra-class correlation coefficient approaches in a longitudinal multi-center human phantom study. We completed annual reliability scans on 'travelling human phantoms'. Acquisitions across sites were harmonized prospectively. Twenty-seven MRI sessions were available across four participants, scanned on five scanners, across three years. For each scan, three metrics were extracted: cortical thickness (CT), white matter fractional anisotropy (FA), and resting state functional connectivity (FC). For each metric, hierarchical clustering (Ward's method) was performed. The cluster solutions were compared to participant and scanner using the adjusted Rand index (ARI). For all metrics, data clustered by participant rather than by scanner (ARI > 0.8 comparing clusters to participants, ARI < 0.2 comparing clusters to scanners). These results demonstrate that hierarchical clustering can reliably identify structural and functional scans from different participants imaged on different scanners across time. With increasing interest in data-driven approaches in psychiatric and neurologic brain imaging studies, our findings provide a framework for multi-center analytic approaches aiming to identify subgroups of participants based on brain structure or function.

Altered Functional Connectivity of the Primary Visual Cortex in Adult Comitant Strabismus: A Resting-State Functional MRI Study

PURPOSE

The aim of this study was to examine the functional connectivity between the primary visual cortex and other cortical areas during rest in normal subjects and patients with comitant strabismus using functional magnetic resonance imaging (fMRI).

METHODS

A prospective, observational study was conducted. Ten patients with comitant exotropia and eleven matched healthy subjects underwent resting-state fMRI with their eyes closed. Resting-state fMRI was performed using a 3.0 T MR scanner. The primary visual cortex was subdivided into anterior and posterior subdivisions. The resting-state functional connectivities within the primary visual cortex and between the primary visual cortex and other cortical areas were calculated for each group and compared between the strabismic and normal control groups. fMRI data were analyzed using Statistical Parametric Mapping software and Analysis of Functional NeuroImages software.

RESULTS

Compared with the normal controls, patients with comitant strabismus had increased functional connectivity between the posterior primary visual cortex and other cortical areas, especially the visual cortex [Brodmann area 19 (BA19)] and other oculomotor regions, such as the frontal eye field (BA6).

CONCLUSIONS

The fMRI results suggest that ongoing and permanent cortical changes occur in patients with comitant strabismus. Disrupted brain functional connectivities are associated with abnormal eye movement and loss of stereopsis. Our study provides a neurological basis for understanding the pathophysiology of comitant strabismus, which may prompt new areas of research to more precisely define this basis and extend these findings to enhance diagnosis and treatment.

Network abnormalities in generalized anxiety pervade beyond the amygdala-pre-frontal cortex circuit: Insights from graph theory

Generalized anxiety disorder (GAD) has excessive anxiety and uncontrollable worry as core symptoms. Abnormal cerebral functioning underpins the expression and perhaps pathogenesis of GAD:. Studies implicate impaired communication between the amygdala and the pre-frontal cortex (PFC). Our aim was to longitudinally investigate whether such network abnormalities are spatially restricted to this circuit or if the integrity of functional brain networks is globally disrupted in GAD. We acquired resting-state functional magnetic resonance imaging data from 16 GAD patients and 16 matched controls at baseline and after 1 year. Using network modeling and graph-theory, whole-brain connectivity was characterized from local and global perspectives. Overall lower global efficiency, indicating sub-optimal brain-wide organization and integration, was present in patients with GAD compared to controls. The amygdala and midline cortices showed higher betweenness centrality, reflecting functional dominance of these brain structures. Third, lower betweenness centrality and lower degree emerged for PFC, suggesting weakened inhibitory control. Overall, network organization showed impairments consistent with neurobiological models of GAD (involving amygdala, PFC, and cingulate cortex) and further pointed to an involvement of temporal regions. Such impairments tended to progress over time and predict anxiety symptoms. A graph-analytic approach represents a powerful approach to deepen our understanding of GAD.

fMRI BOLD Correlates of EEG Independent Components: Spatial Correspondence With the Default Mode Network

Goal: We aimed to identify electroencephalographic (EEG) signal fluctuations within independent components (ICs) that correlate to spontaneous blood oxygenation level dependent (BOLD) activity in regions of the default mode network (DMN) during eyes-closed resting state. Methods: We analyzed simultaneously acquired EEG and functional magnetic resonance imaging (fMRI) eyes-closed resting state data in a convenience sample of 30 participants. IC analysis (ICA) was used to decompose the EEG time-series and common ICs were identified using data-driven IC clustering across subjects. The IC time courses were filtered into seven frequency bands, convolved with a hemeodynamic response function (HRF) and used to model spontaneous fMRI signal fluctuations across the brain. In parallel, group ICA analysis was used to decompose the fMRI signal into ICs from which the DMN was identified. Frequency and IC cluster associated hemeodynamic correlation maps obtained from the regression analysis were spatially correlated with the DMN. To investigate the reliability of our findings, the analyses were repeated with data collected from the same subjects 1 year later. Results: Our results indicate a relationship between power fluctuations in the delta, theta, beta and gamma frequency range and the DMN in different EEG ICs in our sample as shown by small to moderate spatial correlations at the first measurement (0.234 < |r| < 0.346, p < 0.0001). Furthermore, activity within an EEG component commonly identified as eye movements correlates with BOLD activity within regions of the DMN. In addition, we demonstrate that correlations between EEG ICs and the BOLD signal during rest are in part stable across time. Discussion: We show that ICA source separated EEG signals can be used to investigate electrophysiological correlates of the DMN. The relationship between the eye movement component and the DMN points to a behavioral association between DMN activity and the level of eye movement or the presence of neuronal activity in this component. Previous findings of an association between frontal midline theta activity and the DMN were replicated.

Novel Imaging Biomarkers for Huntington's Disease and Other Hereditary Choreas

PURPOSE OF THE REVIEW

Imaging biomarkers for neurodegenerative disorders are primarily developed with the goal to aid diagnosis, to monitor disease progression, and to assess the efficacy of disease-modifying therapies in support to clinical outcomes that may either show limited sensitivity or need extended time for their evaluation. This article will review the most recent concepts and findings in the field of neuroimaging applied to Huntington's disease and Huntington-like syndromes. Emphasis will be given to the discussion of potential pharmacodynamic biomarkers for clinical trials in Huntington's disease (HD) and of neuroimaging tools that can be used as diagnostic biomarkers in HD-like syndromes.

RECENT FINDINGS

Several magnetic resonance (MR) and positron emission tomography (PET) molecular imaging tools have been identified as potential pharmacodynamic biomarkers and others are in the pipeline after preclinical validation. MRI and 18F-fluorodeoxyglucose PET can be considered useful supportive diagnostic tools for the differentiation of other HD-like syndromes. New trials in HD have the primary goal to lower mutant huntingtin (mHTT) protein levels in the brain in order to reduce or alter the progression of the disease. MR and PET molecular imaging markers have been developed as tools to monitor disease progression and to evaluate treatment outcomes of disease-modifying trials in HD. These markers could be used alone or in combination for detecting structural and pharmacodynamic changes potentially associated with the lowering of mHTT.

Anhedonia and depression severity dissociated by dmPFC resting-state functional connectivity in adolescents

INTRODUCTION

Given the heterogeneity within depression, in this study we aim to examine how resting-state functional connectivity (RSFC) in adolescents is related to anhedonia and depression severity on a continuum in line with the research domain criteria (RDoC) approach.

METHODS

We examined how RSFC in the dorsal medial prefrontal cortex (dmPFC), nucleus accumbens (NAcc) and pregenual anterior cingulate cortex (pgACC) was related to anhedonia and depression severity in 86 adolescents (13-21 years).

RESULTS

We found both anhedonia and depression severity related to decreased dmPFC RSFC with the precuneus, a part of the default mode network. However we also found that increased dmPFC connectivity with the ACC/paracingulate gyrus related to anhedonia whereas increased RSFC with the frontal pole related to depression severity.

DISCUSSION

This work extends the view that the dmPFC is a potential therapeutic target for depression in two ways: 1. We report dmPFC connectivity in adolescents; and 2. We show different dmPFC RSFC specific to anhedonia and depression severity, providing neural targets for intervention in young people at risk of depression.

Resting state functional connectivity in patients with remitted psychotic depression: A multi-centre STOP-PD study

Background

There is paucity of neurobiological knowledge about major depressive disorder with psychotic features (“psychotic depression”). This study addresses this knowledge gap by using resting state functional magnetic resonance imaging (R-fMRI) to compare functional connectivity in patients with psychotic depression and healthy controls.

Methods

We scanned patients who participated in a randomized controlled trial as well as healthy controls. All patients achieved remission from depressive and psychotic symptoms with sertraline and olanzapine. We employed Independent Component Analysis in independent samples to isolate the default mode network (DMN) and compared patients and controls.

Findings

The Toronto sample included 28 patients (mean [SD], age 56·2 [13·7]) and 39 controls (age 55·1 [13·5]). The Replication sample included 29 patients (age 56·1 [17·7]) and 36 controls (age 48·3 [17·9]). Patients in the Toronto sample demonstrated decreased between-network functional connectivity between the DMN and bilateral insular, somatosensory/motor, and auditory cortices with peak activity in the right planum polare (t = 4·831; p = 0·001, Family Wise Error (FWE) corrected). A similar pattern of between-network functional connectivity was present in our Replication sample with peak activity in the right precentral gyrus (t = 4·144; p = 0·003, FWE corrected).

Interpretation

Remission from psychotic depression is consistently associated with an absence of increased DMN-related functional connectivity and presence of decreased between-network functional connectivity. Future research will evaluate this abnormal DMN-related functional connectivity as a potential biomarker for treatment trajectories.

Funding

National Institute of Mental Health.

Oxytocin differentially modulates specific dorsal and ventral striatal functional connections with frontal and cerebellar regions

Interactions between oxytocin and the basal ganglia are central in current overarching conceptualizations of its broad modulatory effects on behavior. Whereas evidence from animal models emphasizes the critical role of the ventral striatum in the behavioral effects of oxytocin, region-specific contributions of the basal ganglia have not been systematically explored in humans. The present study combined the randomized placebo-controlled administration of oxytocin versus placebo in healthy men (n = 144) with fMRI-based resting-state functional connectivity to determine the modulatory role of oxytocin on the major basal ganglia pathways. Oxytocin specifically increased connectivity between ventral striatal and pallidal nodes with upstream frontal regions, whereas it decreased the strengths of downstream pathways between the dorsal striatum and posterior cerebellum. These pathways have previously been implicated in salience, reward and behavioral flexibility, thus shaping goal-directed behavior. Given the importance of aberrant striatal intrinsic organization in autism, addiction and schizophrenia the present findings may suggest new mechanistic perspectives for the therapeutic potential of oxytocin in these disorders.

Repetitive Transcranial Electrical Stimulation Induces Quantified Changes in Resting Cerebral Perfusion Measured from Arterial Spin Labeling

The use of transcranial electrical stimulation (TES) as a method to augment neural activity has increased in popularity in the last decade and a half. The specific application of TES to the left prefrontal cortex has been shown to produce broad cognitive effects; however, the neural mechanisms underlying these effects remain unknown. In this work, we evaluated the effect of repetitive TES on cerebral perfusion. Stimulation was applied to the left prefrontal cortex on three consecutive days, and resting cerebral perfusion was quantified before and after stimulation using arterial spin labeling. Perfusion was found to decrease significantly more in a matched sham stimulation group than in a group receiving active stimulation across many areas of the brain. These changes were found to originate in the locus coeruleus and were broadly distributed in the neocortex. The changes in the neocortex may be a direct result of the stimulation or an indirect result via the changes in the noradrenergic system produced from the altered activity of the locus coeruleus. These findings indicate that anodal left prefrontal stimulation alters the activity of the locus coeruleus, and this altered activity may excite the noradrenergic system producing the broad behavioral effects that have been reported.

The Relationship Between Resting State Network Connectivity and Individual Differences in Executive Functions

The brain is organized into a number of large networks based on shared function, for example, high-level cognitive functions (frontoparietal network), attentional capabilities (dorsal and ventral attention networks), and internal mentation (default network). The correlations of these networks during resting-state fMRI scans varies across individuals and is an indicator of individual differences in ability. Prior work shows higher cognitive functioning (as measured by working memory and attention tasks) is associated with stronger negative correlations between frontoparietal/attention and default networks, suggesting that increased ability may depend upon the diverging activation of networks with contrasting function. However, these prior studies lack specificity with regard to the higher-level cognitive functions involved, particularly with regards to separable components of executive function (EF). Here we decompose EF into three factors from the unity/diversity model of EFs: Common EF, Shifting-specific EF, and Updating-specific EF, measuring each via factor scores derived from a battery of behavioral tasks completed by 250 adult participants (age 28) at the time of a resting-state scan. We found the hypothesized segregated pattern only for Shifting-specific EF. Specifically, after accounting for one’s general EF ability (Common EF), individuals better able to fluidly switch between task sets have a stronger negative correlation between the ventral attention network and the default network. We also report non-predicted novel findings in that individuals with higher Shifting-specific abilities exhibited more positive connectivity between frontoparietal and visual networks, while those individuals with higher Common EF exhibited increased connectivity between sensory and default networks. Overall, these results reveal a new degree of specificity with regard to connectivity/EF relationships.

Local resting state functional connectivity in autism: site and cohort variability and the effect of eye status

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with prominent impairments in sociocommunicative abilities, which have been linked to anomalous brain network organization. Despite ample evidence of atypical long-distance connectivity, the literature on local connectivity remains small and divergent. We used resting-state functional MRI regional homogeneity (ReHo) as a local connectivity measure in comparative analyses across several well-matched low-motion subsamples from the Autism Brain Imaging Data Exchange and in-house data, with a grand total of 147 ASD and 184 typically developing (TD) participants, ages 7-18 years. We tested for group differences in each subsample, with additional focus on the difference between eyes-open and eyes-closed resting states. Despite selection of highest quality data and tight demographic and motion matching between groups and across samples, few effects in exactly identical loci (voxels) were found across samples. However, there was gross consistency across all eyes-open samples of local overconnectivity (ASD > TD) in posterior, visual regions. There was also gross consistency of local underconnectivity (ASD < TD) in cingulate gyrus, although exact loci varied between mid/posterior and anterior sections. While all eyes-open datasets showed the described gross similarities, the pattern of group differences for participants scanned with eyes closed was different, with local overconnectivity in ASD in posterior cingulate gyrus, but underconnectivity in some visual regions. Our findings suggest that fMRI local connectivity measures may be relatively susceptible to site and cohort variability and that some previous inconsistencies in the ASD ReHo literature may be reconciled by more careful consideration of eye status.

Intra- and Inter-Scanner Reliability of Voxel-Wise Whole-Brain Analytic Metrics for Resting State fMRI

As the multi-center studies with resting-state functional magnetic resonance imaging (RS-fMRI) have been more and more applied to neuropsychiatric studies, both intra- and inter-scanner reliability of RS-fMRI are becoming increasingly important. The amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) are 3 main RS-fMRI metrics in a way of voxel-wise whole-brain (VWWB) analysis. Although the intra-scanner reliability (i.e., test-retest reliability) of these metrics has been widely investigated, few studies has investigated their inter-scanner reliability. In the current study, 21 healthy young subjects were enrolled and scanned with blood oxygenation level dependent (BOLD) RS-fMRI in 3 visits (V1 - V3), with V1 and V2 scanned on a GE MR750 scanner and V3 on a Siemens Prisma. RS-fMRI data were collected under two conditions, eyes open (EO) and eyes closed (EC), each lasting 8 minutes. We firstly evaluated the intra- and inter-scanner reliability of ALFF, ReHo, and DC. Secondly, we measured systematic difference between two scanning visits of the same scanner as well as between two scanners. Thirdly, to account for the potential difference of intra- and inter-scanner local magnetic field inhomogeneity, we measured the difference of relative BOLD signal intensity to the mean BOLD signal intensity of the whole brain between each pair of visits. Last, we used percent amplitude of fluctuation (PerAF) to correct the difference induced by relative BOLD signal intensity. The inter-scanner reliability was much worse than intra-scanner reliability; Among the VWWB metrics, DC showed the worst (both for intra-scanner and inter-scanner comparisons). PerAF showed similar intra-scanner reliability with ALFF and the best reliability among all the 4 metrics. PerAF reduced the influence of BOLD signal intensity and hence increase the inter-scanner reliability of ALFF. For multi-center studies, inter-scanner reliability should be taken into account.

Functional Connectivity Alterations Reveal Complex Mechanisms Based on Clinical and Radiological Status in Mild Relapsing Remitting Multiple Sclerosis

Resting state functional MRI (rs-fMRI) has provided important insights into functional reorganization in subjects with Multiple Sclerosis (MS) at different stage of disease. In this cross-sectional study we first assessed, by means of rs-fMRI, the impact of overall T2 lesion load (T2LL) and MS severity score (MSSS) on resting state networks (RSNs) in 62 relapsing remitting MS (RRMS) patients with mild disability (MSSS < 3). Independent Component Analysis (ICA) followed by dual regression analysis confirmed functional connectivity (FC) alterations of many RSNs in RRMS subjects compared to healthy controls. The anterior default mode network (DMNa) and the superior precuneus network (PNsup) showed the largest areas of decreased FC, while the sensory motor networks area M1 (SMNm1) and the medial visual network (MVN) showed the largest areas of increased FC. In order to better understand the nature of these alterations as well as the mechanisms of functional alterations in MS we proposed a method, based on linear regression, that takes into account FC changes and their correlation with T2LL and MSSS. Depending on the sign of the correlation between FC and T2LL, and furthermore the sign of the correlation with MSSS, we suggested the following possible underlying mechanisms to interpret altered FC: (1) FC reduction driven by MS lesions, (2) "true" functional compensatory mechanism, (3a) functional compensation attempt, (3b) "false" functional compensation, (4a) neurodegeneration, (4b) pre-symptomatic condition (damage precedes MS clinical manifestation). Our data shows areas satisfying 4 of these 6 conditions (i.e., 1,2,3b,4b), supporting the suggestion that increased FC has a complex nature that may exceed the simplistic assumption of an underlying compensatory mechanism attempting to limit the brain damage caused by MS progression. Exploring differences between RRMS subjects with short disease duration (MS_short) and RRMS with similar disability but longer disease duration (MS_long), we found that MS_short and MS_long were characterized by clearly distinct pattern of FC, involving predominantly sensory and cognitive networks respectively. Overall, these results suggest that the analysis of FC alterations in multiple large-scale networks in relation to radiological (T2LL) and clinical (MSSS, disease duration) status may provide new insights into the pathophysiology of relapse onset MS evolution.

Test-retest reliability of dynamic functional connectivity in resting state fMRI

While static functional connectivity (sFC) of resting state fMRI (rfMRI) measures the average functional connectivity (FC) over the entire rfMRI scan, dynamic FC (dFC) captures the temporal variations of FC at shorter time windows. Although numerous studies have implemented dFC analyses, only a few studies have investigated the reliability of dFC and this limits the biological interpretation of dFC. Here, we used a large cohort (N = 820) of subjects and four rfMRI scans from the Human Connectome Project to systematically explore the relationship between sFC, dFC and their test-retest reliabilities through intra-class correlation (ICC). dFC ICC was explored through the sliding window approach with three dFC statistics (standard deviation, ALFF, and excursion). Excursion demonstrated the highest dFC ICC and the highest age prediction accuracy. dFC ICC was generally higher at window sizes less than 40 s. sFC and dFC were negatively correlated. Compared to sFC, dFC was less reliable. While sFC and sFC ICC were positively correlated, dFC and dFC ICC were negatively correlated, indicating that FC that was more dynamic was less reliable. Intra-network FCs in the frontal-parietal, default mode, sensorimotor and visual networks demonstrated high sFC and low dFC. Moreover, ICCs of both sFC and dFC in these regions were higher. The above results were consistent across two brain atlases and independent component analysis-based networks, multiple window sizes and all three dFC statistics. In summary, dFC is less reliable than sFC and additional experiments are required to better understand the neurophysiological relevance of dFC.

Attenuated resting-state functional connectivity in patients with childhood- and adult-onset schizophrenia

BACKGROUND

Childhood-onset schizophrenia (COS) is a rare, severe form of the adult-onset disorder (AOS). Our previous resting-state fMRI study identified attenuated functional connectivity in COS compared with controls. Here, we ask whether COS and AOS patients and their siblings exhibit similar abnormalities of functional connectivity.

METHODS

A whole-brain, data-driven approach was used to assess resting-state functional connectivity differences in COS (patients/siblings/controls, n: 26/28/33) and AOS (n: 19/28/30). There were no significant differences in age, sex, or head motion across groups in each dataset and as designed, the COS dataset has a significantly lower age than the AOS.

RESULTS

Both COS and AOS patients showed decreased functional connectivity relative to controls among a wide set of brain regions (P<0.05, corrected), but their siblings did not. Decreased connectivity in COS and AOS patients showed no amplitude differences and was not modulated by age-at-onset or medication doses. Cluster analysis revealed that these regions fell into two large-scale networks: one sensorimotor network and one centered on default-mode network regions, but including higher-order cognitive areas only in COS. Decreased connectivity between these two networks was notable (P<0.05, corrected) for both patient groups.

CONCLUSIONS

A shared pattern of attenuated functional connectivity was found in COS and AOS, supporting the continuity of childhood-onset and adult-onset schizophrenia. Connections were altered between sensorimotor areas and default-mode areas in both COS and AOS, suggesting potential abnormalities in processes of self-monitoring and sensory prediction. The absence of substantial dysconnectivity in siblings indicates that attenuation is state-related.

Limitations of Resting-State Functional MR Imaging in the Setting of Focal Brain Lesions

Methods of image acquisition and analysis for resting-state functional MR imaging (rsfMR imaging) are still evolving. Neurovascular uncoupling and susceptibility artifact are important confounds of rsfMR imaging in the setting of focal brain lesions such as brain tumors. This article reviews the detection of these confounds using rsfMR imaging metrics in the setting of focal brain lesions. In the near future, with the wide range of ongoing research in rsfMR imaging, these issues likely will be overcome and will open new windows into brain function and connectivity.

Effects of Tissue-Specific Functional Magnetic Resonance Imaging Signal Regression on Resting-State Functional Connectivity

Neuroimaging studies typically consider white matter as unchanging in different neural and metabolic states. However, a recent study demonstrated that white matter signal regression (WMSR) produced a similar loss of neurometabolic information to global (whole-brain) signal regression (GSR) in resting-state functional magnetic resonance imaging (R-fMRI) data. This was unexpected as the loss of information would normally be attributed to neural activity within gray matter correlating with the global R-fMRI signal. Indeed, WMSR has been suggested as an alternative to avoid such pitfalls in GSR. To address these concerns about tissue-specific regression in R-fMRI data analysis, we performed GSR, WMSR, and gray matter signal regression (GMSR) on R-fMRI data from the 1000 Functional Connectomes Project. We describe several regional and motion-related differences between different types of regressions. However, the overall effects of concern, particularly network-specific alteration of correlation coefficients, are present for all regressions. This suggests that tissue-specific regression is not an adequate strategy to counter pitfalls of GSR. Conversely, if GSR is desired, but the studied disease state excludes either gray matter or white matter from analysis (e.g., due to tissue atrophy), our results indicate that WMSR or GMSR may reproduce the gross effects of GSR.

Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker?

Biomarkers in whichever modality are tremendously important in diagnosing of disease, tracking disease progression and clinical trials. This applies in particular for disorders with a long disease course including pre-symptomatic stages, in which only subtle signs of clinical progression can be observed. Magnetic resonance imaging (MRI) biomarkers hold particular promise due to their relative ease of use, cost-effectiveness and non-invasivity. Studies measuring resting-state functional MR connectivity have become increasingly common during recent years and are well established in neuroscience and related fields. Its increasing application does of course also include clinical settings and therein neurodegenerative diseases. In the present review, we critically summarise the state of the literature on resting-state functional connectivity as measured with functional MRI in neurodegenerative disorders. In addition to an overview of the results, we briefly outline the methods applied to the concept of resting-state functional connectivity. While there are many different neurodegenerative disorders cumulatively affecting a substantial number of patients, for most of them studies on resting-state fMRI are lacking. Plentiful amounts of papers are available for Alzheimer's disease (AD) and Parkinson's disease (PD), but only few works being available for the less common neurodegenerative diseases. This allows some conclusions on the potential of resting-state fMRI acting as a biomarker for the aforementioned two diseases, but only tentative statements for the others. For AD, the literature contains a relatively strong consensus regarding an impairment of the connectivity of the default mode network compared to healthy individuals. However, for AD there is no considerable documentation on how that alteration develops longitudinally with the progression of the disease. For PD, the available research points towards alterations of connectivity mainly in limbic and motor related regions and networks, but drawing conclusions for PD has to be done with caution due to a relative heterogeneity of the disease. For rare neurodegenerative diseases, no clear conclusions can be drawn due to the few published results. Nevertheless, summarising available data points towards characteristic connectivity alterations in Huntington's disease, frontotemporal dementia, dementia with Lewy bodies, multiple systems atrophy and the spinocerebellar ataxias. Overall at this point in time, the data on AD are most promising towards the eventual use of resting-state fMRI as an imaging biomarker, although there remain issues such as reproducibility of results and a lack of data demonstrating longitudinal changes. Improved methods providing more precise classifications as well as resting-state network changes that are sensitive to disease progression or therapeutic intervention are highly desirable, before routine clinical use could eventually become a reality.

Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI

Resting state fMRI (rs-fMRI) provides imaging biomarkers of task-independent brain function that can be associated with clinical variables or modulated by interventions such as behavioral training or pharmacological manipulations. These biomarkers include time-averaged regional brain function as manifested by regional cerebral blood flow (CBF) measured using arterial spin labeled (ASL) perfusion MRI and correlated temporal fluctuations of function across brain networks with either ASL or blood oxygenation level dependent (BOLD) fMRI. Resting-state studies are typically carried out using just one of several prescribed state conditions such as eyes closed (EC), eyes open (EO), or visual fixation on a cross-hair (FIX), which may affect the reliability and specificity of rs-fMRI. In this study, we collected test-retest ASL MRI data during 4 resting-state task conditions: EC, EO, FIX and PVT (low-frequency psychomotor vigilance task), and examined the effects of these task conditions on reliability and reproducibility as well as trait specificity of regional brain function. We also acquired resting-state BOLD fMRI under FIX and compared the network connectivity reliabilities between the four ASL conditions and the BOLD FIX condition. For resting-state ASL data, EC provided the highest CBF reliability, reproducibility, trait specificity, and network connectivity reliability, followed by EO, while FIX was lowest on all of these measures. PVT demonstrated lower CBF reliability, reproducibility and trait specificity than EO and EC. Overall network connectivity reliability was comparable between ASL and BOLD. Our findings confirm ASL CBF as a reliable, stable, and consistent measure of resting-state regional brain function and support the use of EC or EO over FIX and PVT as the resting-state condition.

Gray matter deficits and altered resting-state connectivity in the superior temporal gyrus among individuals with problematic hypersexual behavior

Neuroimaging studies on the characteristics of hypersexual disorder have been accumulating, yet alternations in brain structures and functional connectivity in individuals with problematic hypersexual behavior (PHB) has only recently been studied. This study aimed to investigate gray matter deficits and resting-state abnormalities in individuals with PHB using voxel-based morphometry and resting-state connectivity analysis. Seventeen individuals with PHB and 19 age-matched healthy controls participated in this study. Gray matter volume of the brain and resting-state connectivity were measured using 3T magnetic resonance imaging. Compared to healthy subjects, individuals with PHB had significant reductions in gray matter volume in the left superior temporal gyrus (STG) and right middle temporal gyrus. Individuals with PHB also exhibited a decrease in resting-state functional connectivity between the left STG and left precuneus and between the left STG and right caudate. The gray matter volume of the left STG and its resting-state functional connectivity with the right caudate both showed significant negative correlations with the severity of PHB. The findings suggest that structural deficits and resting-state functional impairments in the left STG might be linked to PHB and provide new insights into the underlying neural mechanisms of PHB.

Selective functional dysconnectivity of the dorsal-anterior subregion of the precuneus in drug-naive major depressive disorder

BACKGROUND

Patients with major depressive disorder (MDD) have shown altered resting-state functional connectivity (rsFC) of the precuneus; however, it is unknown whether rsFC of the precuneus subregions is differentially affected in this disorder.

METHODS

In this study, we aimed to clarify this issue by comparing rsFC of each precuneus subregion between patients with MDD and healthy controls. Forty-seven drug-naive patients with MDD and 47 sex-, age- and education-matched healthy controls underwent resting-state functional magnetic resonance imaging (fMRI). The precuneus was divided into PCun-1 (dorsal-central portion; medial area 7), PCun-2 (dorsal-anterior portion; medial area 5), PCun-3 (dorsal-posterior portion; dorsomedial parietooccipital sulcus) and PCun-4 (ventral portion; area 31). The rsFC of each precuneus subregion was compared between the two groups.

RESULTS

Compared with healthy controls, patients with MDD exhibited increased rsFC between the left PCun-2 and the right fusiform gyrus, lateral prefrontal cortex, sensorimotor cortex and supramarginal gyrus. No significant inter-group difference was observed in the rsFC of other precuneus subregions. In addition, there was no difference in gray matter volume of all the precuneus subregions between patients with MDD and healthy controls.

LIMITATIONS

Some of the patients had chronic MDD and relevant neuropsychological data were not collected.

CONCLUSIONS

These findings suggest a selective functional dysconnectivity of the precuneus subregions in drug-naive MDD, characterized by the hyperconnnectivity between the dorsal-anterior subregion and regions involved in visual, executive control, sensorimotor and bottom-up attention functions.

Impact of Total Knee Arthroplasty with General Anesthesia on Brain Networks: Cognitive Efficiency and Ventricular Volume Predict Functional Connectivity Decline in Older Adults

Using resting state functional magnetic resonance imaging (RS-fMRI), we explored: 1) pre- to post-operative changes in functional connectivity in default mode, salience, and central executive networks after total knee arthroplasty (TKA) with general anesthesia, and 2) the contribution of cognitive/brain reserve metrics these resting state functional declines. Individuals age 60 and older electing unilateral total knee arthroplasty (TKA; n = 48) and non-surgery peers with osteoarthritis (n = 45) completed baseline cognitive testing and baseline and post-surgery (post-baseline, 48-h post-surgery) brain MRI. We acquired cognitive and brain estimates for premorbid (vocabulary, reading, education, intracranial volume) and current (working memory, processing speed, declarative memory, ventricular volume) reserve. Functional network analyses corrected for pain severity and pain medication. The surgery group declined in every functional network of interest (p < 0.001). Relative to non-surgery peers, 23% of surgery participants declined in at least one network and 15% of the total TKA sample declined across all networks. Larger preoperative ventricular volume and lower scores on preoperative metrics of processing speed and working memory predicted default mode network connectivity decline. Premorbid cognitive and premorbid brain reserve did not predict decline. Within 48 hours after surgery, at least one fourth of the older adult sample showed significant functional network decline. Metrics of current brain status (ventricular volume), working memory, and processing speed predicted the severity of default mode network connectivity decline. These findings demonstrate the relevance of preoperative cognition and brain integrity on acute postoperative functional network change.

Different pre-scanning instructions induce distinct psychological and resting brain states during functional magnetic resonance imaging

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to investigate functional brain network connectivity during rest or when the subject is not performing an explicit task. In the standard procedure, subjects are instructed to 'let your mind wander' or 'think of nothing'. While these instructions appear appropriate to induce a 'resting-state', they could induce distinct psychological and physiological states during the scan. In this study, we investigated whether different instructions affect mental state and functional connectivity (FC) (i.e. induce distinct 'resting states') during rs-fMRI scanning. Thirty healthy subjects were subjected to two rs-fMRI scans differing only in pre-scan instructions: think of nothing (TN) and mind-wandering (MW) conditions. Self-reports confirmed that subjects spent the majority of the scanning time in the appropriate mental state. Independent component analysis extracted 19 independent components (ICs) of interest and functional network connectivity analyses indicated several conditional differences in FCs among those ICs, especially characterised by stronger FC in the MW condition than in the TN condition, between default mode network and salience/visual/frontal network. Complementary correlation analysis indicated that some of the network FCs were significantly correlated with their self-reported data on how often they had the TN condition during the scans. The present results provide evidence that the pre-scan instruction has a significant influence on resting-state FC and its relationship with mental activities.

Exploring the alpha desynchronization hypothesis in resting state networks with intracranial electroencephalography and wiring cost estimates

This paper addresses a fundamental question, are eyes closed and eyes open resting states equivalent baseline conditions, or do they have consistently different electrophysiological signatures? We compare the functional connectivity patterns in an eyes closed resting state with an eyes open resting state to investigate the alpha desynchronization hypothesis. The change in functional connectivity from eyes closed to eyes open, is here, for the first time, studied with intracranial recordings. We perform network connectivity analysis in iEEG and we find that phase-based connectivity is sensitive to the transition from eyes closed to eyes open only in interhemispheral and frontal electrodes. Power based connectivity, on the other hand, consistently discriminates between the two conditions in temporal and interhemispheral electrodes. Additionally, we provide a calculation for the wiring cost, defined in terms of the connectivity between electrodes weighted by distance. We find that the wiring cost variation from eyes closed to eyes open is sensitive to the eyes closed and eyes open conditions. We extend the standard network-based approach using the filtration method from algebraic topology which does not rely on the threshold selection problem. Both the wiring cost measure defined here and this novel methodology provide a new avenue for understanding the electrophysiology of resting state.

Negative mood influences default mode network functional connectivity in patients with chronic low back pain: implications for functional neuroimaging biomarkers

The default mode network (DMN) has been proposed as a biomarker for several chronic pain conditions. Default mode network functional connectivity (FC) is typically examined during resting-state functional neuroimaging, in which participants are instructed to let thoughts wander. However, factors at the time of data collection (eg, negative mood) that might systematically impact pain perception and its brain activity, influencing the application of the DMN as a pain biomarker, are rarely reported. This study measured whether positive and negative moods altered DMN FC patterns in patients with chronic low back pain (CLBP), specifically focusing on negative mood because of its clinical relevance. Thirty-three participants (CLBP = 17) underwent resting-state functional magnetic resonance imaging scanning before and after sad and happy mood inductions, and rated levels of mood and pain intensity at the time of scanning. Two-way repeated-measures analysis of variances were conducted on resting-state functional connectivity data. Significant group (CLBP > healthy controls) × condition (sadness > baseline) interaction effects were identified in clusters spanning parietal operculum/postcentral gyrus, insular cortices, anterior cingulate cortex, frontal pole, and a portion of the cerebellum (PFDR < 0.05). However, only 1 significant cluster covering a portion of the cerebellum was identified examining a two-way repeated-measures analysis of variance for happiness > baseline (PFDR < 0.05). Overall, these findings suggest that DMN FC is affected by negative mood in individuals with and without CLBP. It is possible that DMN FC seen in patients with chronic pain is related to an affective dimension of pain, which is important to consider in future neuroimaging biomarker development and implementation.

Implication of the Slow-5 Oscillations in the Disruption of the Default-Mode Network in Healthy Aging and Stroke

The processes of normal aging and aging-related pathologies subject the brain to an active re-organization of its brain networks. Among these, the default-mode network (DMN) is consistently implicated with a demonstrated reduction in functional connectivity within the network. However, no clear stipulation on the underlying mechanisms of the de-synchronization has yet been provided. In this study, we examined the spectral distribution of the intrinsic low-frequency oscillations (LFOs) of the DMN sub-networks in populations of young normals, older subjects, and acute and subacute ischemic stroke patients. The DMN sub-networks were derived using a mid-order group independent component analysis with 117 eyes-closed resting-state functional magnetic resonance imaging (rs-fMRI) sessions from volunteers in those population groups, isolating three robust components of the DMN among other resting-state networks. The posterior component of the DMN presented noticeable differences. Measures of amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) of the network component demonstrated a decrease in resting-state cortical oscillation power in the elderly (normal and patient), specifically in the slow-5 (0.01-0.027 Hz) range of oscillations. Furthermore, the contribution of the slow-5 oscillations during the resting state was diminished for a greater influence of the slow-4 (0.027-0.073 Hz) oscillations in the subacute stroke group, not only suggesting a vulnerability of the slow-5 oscillations to disruption but also indicating a change in the distribution of the oscillations within the resting-state frequencies. The reduction of network slow-5 fALFF in the posterior DMN component was found to present a potential association with behavioral measures, suggesting a brain-behavior relationship to those oscillations, with this change in behavior potentially resulting from an altered network integrity induced by a weakening of the slow-5 oscillations during the resting state. The repeated identification of those frequencies in the disruption of DMN stresses a critical role of the slow-5 oscillations in network disruption, and it accentuates the importance of managing those oscillations in the health of the DMN.

Can brain state be manipulated to emphasize individual differences in functional connectivity?

While neuroimaging studies typically collapse data from many subjects, brain functional organization varies between individuals, and characterizing this variability is crucial for relating brain activity to behavioral phenotypes. Rest has become the default state for probing individual differences, chiefly because it is easy to acquire and a supposed neutral backdrop. However, the assumption that rest is the optimal condition for individual differences research is largely untested. In fact, other brain states may afford a better ratio of within- to between-subject variability, facilitating biomarker discovery. Depending on the trait or behavior under study, certain tasks may bring out meaningful idiosyncrasies across subjects, essentially enhancing the individual signal in networks of interest beyond what can be measured at rest. Here, we review theoretical considerations and existing work on how brain state influences individual differences in functional connectivity, present some preliminary analyses of within- and between-subject variability across conditions using data from the Human Connectome Project, and outline questions for future study.

The Effect of Low-Frequency Physiological Correction on the Reproducibility and Specificity of Resting-State fMRI Metrics: Functional Connectivity, ALFF, and ReHo

The resting-state fMRI (rs-fMRI) signal is affected by a variety of low-frequency physiological phenomena, including variations in cardiac-rate (CRV), respiratory-volume (RVT), and end-tidal CO₂ (PETCO₂). While these effects have become better understood in recent years, the impact that their correction has on the quality of rs-fMRI measurements has yet to be clarified. The objective of this paper is to investigate the effect of correcting for CRV, RVT and PETCO₂ on the rs-fMRI measurements. Nine healthy subjects underwent a test-retest rs-fMRI acquisition using repetition times (TRs) of 2 s (long-TR) and 0.323 s (short-TR), and the data were processed using eight different physiological correction strategies. Subsequently, regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and resting-state connectivity of the motor and default-mode networks are calculated for each strategy. Reproducibility is calculated using intra-class correlation and the Dice Coefficient, while the accuracy of functional-connectivity measures is assessed through network separability, sensitivity and specificity. We found that: (1) the reproducibility of the rs-fMRI measures improved significantly after correction for PETCO₂; (2) separability of functional networks increased after PETCO₂ correction but was not affected by RVT and CRV correction; (3) the effect of physiological correction does not depend on the data sampling-rate; (4) the effect of physiological processes and correction strategies is network-specific. Our findings highlight limitations in our understanding of rs-fMRI quality measures, and underscore the importance of using multiple quality measures to determine the optimal physiological correction strategy.

Unique Neural Characteristics of Atypical Lateralization of Language in Healthy Individuals

Using functional magnetic resonance imaging (fMRI) in 63 healthy participants, including left-handed and ambidextrous individuals, we tested how atypical lateralization of language—i. e., bilateral or right hemispheric language representation—differs from the typical left-hemisphere dominance. Although regardless of their handedness, all 11 participants from the atypical group engaged classical language centers, i.e., Broca's and Wernicke's areas, the right-hemisphere components of the default mode network (DMN), including the angular gyrus and middle temporal gyrus, were also critically involved during the verbal fluency task. Importantly, activity in these regions could not be explained in terms of mirroring the typical language pattern because left-hemisphere dominant individuals did not exhibit similar significant signal modulations. Moreover, when spatial extent of language-related activity across whole brain was considered, the bilateral language organization entailed more diffuse functional processing. Finally, we detected significant differences between the typical and atypical group in the resting-state connectivity at the global and local level. These findings suggest that the atypical lateralization of language has unique features, and is not a simple mirror image of the typical left hemispheric language representation.

Genome-wide imaging association study implicates functional activity and glial homeostasis of the caudate in smoking addiction

Background

Nearly 6 million deaths and over a half trillion dollars in healthcare costs worldwide are attributed to tobacco smoking each year. Extensive research efforts have been pursued to elucidate the molecular underpinnings of smoking addiction and facilitate cessation. In this study, we genotyped and obtained both resting state and task-based functional magnetic resonance imaging from 64 non-smokers and 42 smokers. Smokers were imaged after having smoked normally (“sated”) and after having not smoked for at least 12 h (“abstinent”).

Results

While abstinent smokers did not differ from non-smokers with respect to pairwise resting state functional connectivities (RSFCs) between 12 brain regions of interest, RSFCs involving the caudate and putamen of sated smokers significantly differed from those of non-smokers (P < 0.01). Further analyses of caudate and putamen activity during elicited experiences of reward and disappointment show that caudate activity during reward (CR) correlated with smoking status (P = 0.015). Moreover, abstinent smokers with lower CR experienced greater withdrawal symptoms (P = 0.024), which suggests CR may be related to smoking urges. Associations between genetic variants and CR, adjusted for smoking status, were identified by genome-wide association study (GWAS). Genes containing or exhibiting caudate-specific expression regulation by these variants were enriched within Gene Ontology terms that describe cytoskeleton functions, synaptic organization, and injury response (P < 0.001, FDR < 0.05).

Conclusions

By integrating genomic and imaging data, novel insights into potential mechanisms of caudate activation and homeostasis are revealed that may guide new directions of research toward improving our understanding of addiction pathology.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4124-5) contains supplementary material, which is available to authorized users.

Graph Theoretic Analysis of Resting State Functional MR Imaging

Graph theoretic analyses applied to examine the brain at rest have played a critical role in clarifying the foundations of the brain's intrinsic and task-related activity. There are many opportunities for clinical scientists to describe and predict dysfunction using a network perspective. This primer describes the theoretic basis and practical application of graph theoretic analysis to resting state functional MR imaging data. Major practices, concepts, and findings are concisely reviewed. The theoretic and practical frontiers of resting state functional MR imaging are highlighted with observations about major avenues for conceptual advances and clinical translation.

Primary Biliary Cholangitis Alters Functional Connections of the Brain's Deep Gray Matter

OBJECTIVES

Fatigue, itch, depressed mood, and cognitive impairment significantly impact the quality of life of many patients with primary biliary cholangitis (PBC). Previous neuroimaging studies of non-hepatic diseases suggest that these symptoms are often associated with dysfunction of deep gray matter brain regions. We used resting-state functional magnetic resonance imaging (rsfMRI) to determine whether PBC patients exhibit altered functional connections of deep gray matter.

METHODS

Twenty female non-cirrhotic PBC patients and 21 age/gender-matched controls underwent rsfMRI. Resting-state functional connectivity (rsFC) of deep gray matter brain structures (putamen, thalamus, amygdala, hippocampus) was compared between groups. Fatigue, itch, mood, cognitive performance, and clinical response to ursodeoxycholic acid (UDCA) were assessed, and their association with rsFC was determined.

RESULTS

Relative to controls, PBC patients exhibited significantly increased rsFC between the putamen, thalamus, amygdala, and hippocampus, as well as with frontal and parietal regions. Reduced rsFC of the putamen and hippocampus with motor and sensory regions of the brain were also observed. Fatigue, itch, complete response to UDCA, and verbal working memory performance were also associated with altered rsFC of deep gray matter. These rsFC changes were independent of biochemical disease severity.

CONCLUSIONS

PBC patients have objective evidence of altered rsFC of the brain's deep gray matter that is in part linked to fatigue severity, itch, response to UDCA therapy, and cognitive performance. These results may guide future approaches to define how PBC leads to altered brain connectivity and provide insight into novel targets for treating PBC-associated brain dysfunction and behavioral symptoms.

[18F]Fludeoxyglucose-Positron Emission Tomography Evidence for Cerebral Hypermetabolism in the Awake State in Narcolepsy and Idiopathic Hypersomnia

Background

Changes in structural and functional central nervous system have been reported in narcolepsy, with large discrepancies between studies. No study has investigated yet spontaneous brain activity at wake in idiopathic hypersomnia (IH). We compared relative changes in regional brain metabolism in two central hypersomnia conditions with different clinical features, namely narcolepsy type 1 (NT1) and IH, and in healthy controls.

Methods

Sixteen patients [12 males, median age 30 years (17–78)] with NT1, nine patients [2 males, median age 27 years (20–60)] with IH and 19 healthy controls [16 males, median age 36 years (17–78)] were included. ¹⁸F-fludeoxyglucose positron emission tomography (PET) was performed in all drug-free subjects under similar conditions and instructions to stay in a wake resting state.

Results

We found increased metabolism in the anterior and middle cingulate and the insula in the two pathological conditions as compared to healthy controls. The reverse contrast failed to evidence hypometabolism in patients vs. controls. Comparisons between patient groups were non-significant. At sub-statistical threshold, we found higher right superior occipital gyrus glucose metabolism in narcolepsy and higher middle orbital cortex and supplementary motor area metabolism in IH, findings that require further confirmation.

Conclusion

There is significant hypermetabolism in narcolepsy and IH in the wake resting state in a set of brain regions constitutive of the salience cortical network that may reflect a compensatory neurocircuitry activity secondary to sleepiness. Metabolic differences between the two disorders within the executive-control network may be a signature of abnormally functioning neural system leading to persistent drowsiness typical of IH.

Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks

Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the “immune system” of mental health recently developed in relation to flexible hub theory.

The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions

Background

Although typically measured during the resting state, a growing literature is illustrating the ability to map intrinsic connectivity with functional MRI during task and naturalistic viewing conditions. These paradigms are drawing excitement due to their greater tolerability in clinical and developing populations and because they enable a wider range of analyses (e.g., inter-subject correlations). To be clinically useful, the test-retest reliability of connectivity measured during these paradigms needs to be established. This resource provides data for evaluating test-retest reliability for full-brain connectivity patterns detected during each of four scan conditions that differ with respect to level of engagement (rest, abstract animations, movie clips, flanker task). Data are provided for 13 participants, each scanned in 12 sessions with 10 minutes for each scan of the four conditions. Diffusion kurtosis imaging data was also obtained at each session.

Findings

Technical validation and demonstrative reliability analyses were carried out at the connection-level using the Intraclass Correlation Coefficient and at network-level representations of the data using the Image Intraclass Correlation Coefficient. Variation in intrinsic functional connectivity across sessions was generally found to be greater than that attributable to scan condition. Between-condition reliability was generally high, particularly for the frontoparietal and default networks. Between-session reliabilities obtained separately for the different scan conditions were comparable, though notably lower than between-condition reliabilities.

Conclusions

This resource provides a test-bed for quantifying the reliability of connectivity indices across subjects, conditions and time. The resource can be used to compare and optimize different frameworks for measuring connectivity and data collection parameters such as scan length. Additionally, investigators can explore the unique perspectives of the brain's functional architecture offered by each of the scan conditions.

Nicotinic modulation of salience network connectivity and centrality in schizophrenia

Although functional abnormalities of the salience network are associated with schizophrenia, the acute effects of nicotine on its function and network dynamics during the resting state in patients are poorly understood. In this study, the effects of a 7 mg nicotine patch (vs. placebo) on salience network connectivity were examined in 17 patients with schizophrenia and 19 healthy subjects. We hypothesized abnormal connectivity between the salience network and other major networks (e.g. executive network) in patients under placebo administration and amelioration of this difference after nicotine. We also examined effects of nicotine on betweenness centrality (a measure of the influence of a region on information transfer throughout the brain) and local efficiency (a measure of local information transfer) of the network. A hybrid independent component analysis (ICA)/seed-based connectivity approach was implemented in which the salience network was extracted by ICA and cortical network peaks (anterior cingulate cortex (ACC), left and right insula) were used as seeds for whole-brain seed-to-voxel connectivity analysis. Significant drug X diagnosis interactions were observed between the ACC seed and superior parietal lobule and ventrolateral prefrontal cortex. A significant interaction effect was also observed between the left insula seed and middle cingulate cortex. During placebo conditions, abnormal connectivity predicted negative symptom severity and lower global functioning in patients. A significant drug X diagnosis interaction was also observed for betweenness centrality of the ACC. These results suggest that nicotine may target abnormalities in functional connectivity between salience and executive network areas in schizophrenia as well as affect the ability of the salience network to act as an integrator of global signaling in the disorder.

Bupropion Administration Increases Resting-State Functional Connectivity in Dorso-Medial Prefrontal Cortex

Background

Patients on the selective serotonergic reuptake inhibitors like citalopram report emotional blunting. We showed previously that citalopram reduces resting-state functional connectivity in healthy volunteers in a number of brain regions, including the dorso-medial prefrontal cortex, which may be related to its clinical effects. Bupropion is a dopaminergic and noradrenergic reuptake inhibitor and is not reported to cause emotional blunting. However, how bupropion affects resting-state functional connectivity in healthy controls remains unknown.

Methods

Using a within-subjects, repeated-measures, double-blind, crossover design, we examined 17 healthy volunteers (9 female, 8 male). Volunteers received 7 days of bupropion (150 mg/d) and 7 days of placebo treatment and underwent resting-state functional Magnetic Resonance Imaging. We selected seed regions in the salience network (amygdala and pregenual anterior cingulate cortex) and the central executive network (dorsal medial prefrontal cortex). Mood and anhedonia measures were also recorded and examined in relation to resting-state functional connectivity.

Results

Relative to placebo, bupropion increased resting-state functional connectivity in healthy volunteers between the dorsal medial prefrontal cortex seed region and the posterior cingulate cortex and the precuneus cortex, key parts of the default mode network.

Conclusions

These results are opposite to that which we found with 7 days treatment of citalopram in healthy volunteers. These results reflect a different mechanism of action of bupropion compared with selective serotonergic reuptake inhibitors. These results help explain the apparent lack of emotional blunting caused by bupropion in depressed patients.

Improving the Test-Retest Reliability of Resting State fMRI by Removing the Impact of Sleep

Resting state functional magnetic resonance imaging (rs-fMRI) provides a powerful tool to examine large-scale neural networks in the human brain and their disturbances in neuropsychiatric disorders. Thanks to its low demand and high tolerance, resting state paradigms can be easily acquired from clinical population. However, due to the unconstrained nature, resting state paradigm is associated with excessive head movement and proneness to sleep. Consequently, the test-retest reliability of rs-fMRI measures is moderate at best, falling short of widespread use in the clinic. Here, we characterized the effect of sleep on the test-retest reliability of rs-fMRI. Using measures of heart rate variability (HRV) derived from simultaneous electrocardiogram (ECG) recording, we identified portions of fMRI data when subjects were more alert or sleepy, and examined their effects on the test-retest reliability of functional connectivity measures. When volumes of sleep were excluded, the reliability of rs-fMRI is significantly improved, and the improvement appears to be general across brain networks. The amount of improvement is robust with the removal of as much as 60% volumes of sleepiness. Therefore, test-retest reliability of rs-fMRI is affected by sleep and could be improved by excluding volumes of sleepiness as indexed by HRV. Our results suggest a novel and practical method to improve test-retest reliability of rs-fMRI measures.