The intrinsic connectivity distribution: a novel contrast measure reflecting voxel level functional connectivity

Intrinsic connectivity demonstrates a shared role of the posterior cingulate for cue reactivity in both gambling and cocaine use disorders

Cue reactivity is relevant across addictive disorders as a process relevant to maintenance, relapse, and craving. Understanding the neurobiological foundations of cue reactivity across substance and behavioral addictions has important implications for intervention development. The present study used intrinsic connectivity distribution methods to examine functional connectivity during a cue-exposure fMRI task involving gambling, cocaine and sad videos in 22 subjects with gambling disorder, 24 with cocaine use disorder, and 40 healthy comparison subjects. Intrinsic connectivity distribution implicated the posterior cingulate cortex (PCC) at a stringent whole-brain threshold. Post-hoc analyses investigating the nature of the findings indicated that individuals with gambling disorder and cocaine use disorder exhibited decreased connectivity in the posterior cingulate during gambling and cocaine cues, respectively, as compared to other cues and compared to other groups. Brain-related cue reactivity in substance and behavioral addictions involve PCC connectivity in a content-to-disorder specific fashion. The findings suggesting that PCC-related circuitry underlies cue reactivity across substance and behavioral addictions suggests a potential biomarker for targeting in intervention development.

Low-calorie diet-induced weight loss is associated with altered brain connectivity and food desire in obesity

OBJECTIVE

The main objective of this study is to better understand the effects of diet-induced weight loss on brain connectivity in response to changes in glucose levels in individuals with obesity.

METHODS

A total of 25 individuals with obesity, among whom 9 had a diagnosis of type 2 diabetes, underwent functional magnetic resonance imaging (fMRI) scans before and after an 8-week low-calorie diet. We used a two-step hypereuglycemia clamp approach to mimic the changes in glucose levels observed in the postprandial period in combination with task-mediated fMRI intrinsic connectivity distribution (ICD) analysis.

RESULTS

After the diet, participants lost an average of 3.3% body weight. Diet-induced weight loss led to a decrease in leptin levels, an increase in hunger and food intake, and greater brain connectivity in the parahippocampus, right hippocampus, and temporal cortex (limbic-temporal network). Group differences (with vs. without type 2 diabetes) were noted in several brain networks. Connectivity in the limbic-temporal and frontal-parietal brain clusters inversely correlated with hunger.

CONCLUSIONS

A short-term low-calorie diet led to a multifaceted body response in patients with obesity, with an increase in connectivity in the limbic-temporal network (emotion and memory) and hormone and eating behavior changes that may be important for recovering the weight lost.

Functional connectivity-hemodynamic (un)coupling changes in chronic mild brain injury are associated with mental health and neurocognitive indices: a resting state fMRI study

PURPOSE

To examine hemodynamic and functional connectivity alterations and their association with neurocognitive and mental health indices in patients with chronic mild traumatic brain injury (mTBI).

METHODS

Resting-state functional MRI (rs-fMRI) and neuropsychological assessment of 37 patients with chronic mTBI were performed. Intrinsic connectivity contrast (ICC) and time-shift analysis (TSA) of the rs-fMRI data allowed the assessment of regional hemodynamic and functional connectivity disturbances and their coupling (or uncoupling). Thirty-nine healthy age- and gender-matched participants were also examined.

RESULTS

Patients with chronic mTBI displayed hypoconnectivity in bilateral hippocampi and parahippocampal gyri and increased connectivity in parietal areas (right angular gyrus and left superior parietal lobule (SPL)). Slower perfusion (hemodynamic lag) in the left anterior hippocampus was associated with higher self-reported symptoms of depression (r =  - 0.53, p = .0006) and anxiety (r =  - 0.484, p = .002), while faster perfusion (hemodynamic lead) in the left SPL was associated with lower semantic fluency (r =  - 0.474, p = .002). Finally, functional coupling (high connectivity and hemodynamic lead) in the right anterior cingulate cortex (ACC)) was associated with lower performance on attention and visuomotor coordination (r =  - 0.50, p = .001), while dysfunctional coupling (low connectivity and hemodynamic lag) in the left ventral posterior cingulate cortex (PCC) and right SPL was associated with lower scores on immediate passage memory (r =  - 0.52, p = .001; r =  - 0.53, p = .0006, respectively). Uncoupling in the right extrastriate visual cortex and posterior middle temporal gyrus was negatively associated with cognitive flexibility (r =  - 0.50, p = .001).

CONCLUSION

Hemodynamic and functional connectivity differences, indicating neurovascular (un)coupling, may be linked to mental health and neurocognitive indices in patients with chronic mTBI.

Whole-brain functional connectivity predicts groupwise and sex-specific tau PET in preclincal Alzheimer's disease

Preclinical Alzheimer's disease, characterized by the initial accumulation of amyloid and tau pathologies without symptoms, presents a critical opportunity for early intervention. Yet, the interplay between these pathological markers and the functional connectome during this window remains understudied. We therefore set out to elucidate the relationship between the functional connectome and amyloid and tau, as assessed by PET imaging, in individuals with preclinical AD using connectome-based predictive modeling (CPM). We found that functional connectivity predicts tau PET, outperforming amyloid PET models. These models were predominantly governed by linear relationships between functional connectivity and tau. Tau models demonstrated a stronger correlation to global connectivity than underlying tau PET. Furthermore, we identify sex-based differences in the ability to predict regional tau, without any underlying differences in tau PET or global connectivity. Taken together, these results suggest tau is more closely coupled to functional connectivity than amyloid in preclinical disease, and that multimodal predictive modeling approaches stand to identify unique relationships that any one modality may be insufficient to discern.

Regression and Alignment for Functional Data and Network Topology

In the brain, functional connections form a network whose topological organization can be described by graph-theoretic network diagnostics. These include characterizations of the community structure, such as modularity and participation coefficient, which have been shown to change over the course of childhood and adolescence. To investigate if such changes in the functional network are associated with changes in cognitive performance during development, network studies often rely on an arbitrary choice of pre-processing parameters, in particular the proportional threshold of network edges. Because the choice of parameter can impact the value of the network diagnostic, and therefore downstream conclusions, we propose to circumvent that choice by conceptualizing the network diagnostic as a function of the parameter. As opposed to a single value, a network diagnostic curve describes the connectome topology at multiple scales-from the sparsest group of the strongest edges to the entire edge set. To relate these curves to executive function and other covariates, we use scalar-on-function regression, which is more flexible than previous functional data-based models used in network neuroscience. We then consider how systematic differences between networks can manifest in misalignment of diagnostic curves, and consequently propose a supervised curve alignment method that incorporates auxiliary information from other variables. Our algorithm performs both functional regression and alignment via an iterative, penalized, and nonlinear likelihood optimization. The illustrated method has the potential to improve the interpretability and generalizability of neuroscience studies where the goal is to study heterogeneity among a mixture of function- and scalar-valued measures.

The changes of intrinsic connectivity contrast in young smokers

Previous studies demonstrated that reward circuit plays an important role in smoking. The differences of functional and structural connectivity were found among several brain regions such as thalamus and frontal lobe. However, few studies focused on functional connectivity (FC) in whole-brain voxel level of young smokers. In this study, intrinsic connectivity contrast (ICC) was used to perform voxel-based whole-brain analyses in 55 young smokers and 55 matched non-smokers to identify brain regions with significant group differences. ICC results showed that the connectivity of young smokers in medial frontal cortex (MedFC), supramarginal gyrus anterior division left (L_aSMG), central opercular cortex left (L_CO) and middle frontal gyrus left (L_MidFG) showed a significantly lower trend compared with the non-smokers. The seed-based FC analysis about MedFC indicated that young smokers showed reduced connectivity between the MedFC and left hippocampus, left amygdala compared to non-smokers. Correlation analysis showed that the ICC of MedFC in young smokers was significantly negatively correlated with Fagerstrom test for nicotine dependence (FTND) and Questionnaire on Smoking Urges (QSU). The FC between the MedFC and left hippocampus, left amygdala was significantly negatively correlated with Pack_years. The mediation analysis indicated that ICC of MedFC completely mediated FTND and QSU of young smokers. The results suggest that nicotine accumulation may affect the communication of the frontal lobe with the whole brain to some extent, leading to changes in smoking cravings. The above research also provides in-depth insights into the mechanism of adolescent smoking addiction and related intervention treatment.

Regression models for partially localized fMRI connectivity analyses

Background

Brain functional connectivity analysis of resting-state functional magnetic resonance imaging (fMRI) data is typically performed in a standardized template space assuming consistency of connections across subjects. Analysis methods can come in the form of one-edge-at-a-time analyses or dimension reduction/decomposition methods. Common to these approaches is an assumption that brain regions are functionally aligned across subjects; however, it is known that this functional alignment assumption is often violated.

Methods

In this paper, we use subject-level regression models to explain intra-subject variability in connectivity. Covariates can include factors such as geographic distance between two pairs of brain regions, whether the two regions are symmetrically opposite (homotopic), and whether the two regions are members of the same functional network. Additionally, a covariate for each brain region can be included, to account for the possibility that some regions have consistently higher or lower connectivity. This style of analysis allows us to characterize the fraction of variation explained by each type of covariate. Additionally, comparisons across subjects can then be made using the fitted connectivity regression models, offering a more parsimonious alternative to edge-at-a-time approaches.

Results

We apply our approach to Human Connectome Project data on 268 regions of interest (ROIs), grouped into eight functional networks. We find that a high proportion of variation is explained by region covariates and network membership covariates, while geographic distance and homotopy have high relative importance after adjusting for the number of predictors. We also find that the degree of data repeatability using our connectivity regression model-which uses only partial location information about pairs of ROI's-is comparably as high as the repeatability obtained using full location information.

Discussion

While our analysis uses data that have been transformed into a common template-space, we also envision the method being useful in multi-atlas registration settings, where subject data remains in its own geometry and templates are warped instead. These results suggest the tantalizing possibility that fMRI connectivity analysis can be performed in subject-space, using less aggressive registration, such as simple affine transformations, multi-atlas subject-space registration, or perhaps even no registration whatsoever.

Preliminary findings on long-term effects of fMRI neurofeedback training on functional networks involved in sustained attention

INTRODUCTION

Neurofeedback based on functional magnetic resonance imaging allows for learning voluntary control over one's own brain activity, aiming to enhance cognition and clinical symptoms. We previously reported improved sustained attention temporarily by training healthy participants to up-regulate the differential activity of the sustained attention network minus the default mode network (DMN). However, the long-term brain and behavioral effects of this training have not yet been studied. In general, despite their relevance, long-term learning effects of neurofeedback training remain under-explored.

METHODS

Here, we complement our previously reported results by evaluating the neurofeedback training effects on functional networks involved in sustained attention and by assessing behavioral and brain measures before, after, and 2 months after training. The behavioral measures include task as well as questionnaire scores, and the brain measures include activity and connectivity during self-regulation runs without feedback (i.e., transfer runs) and during resting-state runs from 15 healthy individuals.

RESULTS

Neurally, we found that participants maintained their ability to control the differential activity during follow-up sessions. Further, exploratory analyses showed that the training increased the functional connectivity between the DMN and the occipital gyrus, which was maintained during follow-up transfer runs but not during follow-up resting-state runs. Behaviorally, we found that enhanced sustained attention right after training returned to baseline level during follow-up.

CONCLUSION

The discrepancy between lasting regulation-related brain changes but transient behavioral and resting-state effects raises the question of how neural changes induced by neurofeedback training translate to potential behavioral improvements. Since neurofeedback directly targets brain measures to indirectly improve behavior in the long term, a better understanding of the brain-behavior associations during and after neurofeedback training is needed to develop its full potential as a promising scientific and clinical tool.

Diagnostic group differences and exploratory sex differences in intrinsic connectivity during fMRI Stroop in individuals with and without cocaine use disorder

BACKGROUND

Sex-/gender-related differences in cognitive control and how they relate to addictions may inform novel treatment options. Cognitive control, including Stroop performance, has been linked to addictions and treatment outcomes. The extent to which women and men with cocaine use disorder (CUD) show brain and behavioral differences relating to Stroop performance has not been previously studied. We examined sex-related differences in Stroop-related brain connectivity in female and male CUD and healthy-comparison (HC) subjects.

METHODS

40 individuals with CUD (20 female) and 40 HC (20 female) subjects matched on age, race, and ethnicity completed an fMRI Stroop task. Intrinsic connectivity distribution (ICD) and mean-adjusted ICD analyses were conducted to identify differences related to sex and diagnostic group. Stroop task performance was also considered.

RESULTS

Behavioral results confirmed a Stroop effect. A main effect of diagnostic group indicated that the CUD versus HC group showed lower connectivity in the prefrontal cortex, frontal gyrus, cingulate gyrus, precuneus, cerebellum, and somatosensory, visual, and auditory areas. An exploratory main effect of sex suggested that males may show relatively lower connectivity than females in the cerebellum and brainstem, although connectivity was largely similar across sexes.

CONCLUSIONS

Intrinsic connectivity during cognitive control varied by diagnostic group and possibly by sex. The findings suggest that interventions targeting cognitive control in CUD should consider sex.

Sex differences in default mode network connectivity in healthy aging adults

Women show an increased lifetime risk of Alzheimer's disease (AD) compared with men. Characteristic brain connectivity changes, particularly within the default mode network (DMN), have been associated with both symptomatic and preclinical AD, but the impact of sex on DMN function throughout aging is poorly understood. We investigated sex differences in DMN connectivity over the lifespan in 595 cognitively healthy participants from the Human Connectome Project-Aging cohort. We used the intrinsic connectivity distribution (a robust voxel-based metric of functional connectivity) and a seed connectivity approach to determine sex differences within the DMN and between the DMN and whole brain. Compared with men, women demonstrated higher connectivity with age in posterior DMN nodes and lower connectivity in the medial prefrontal cortex. Differences were most prominent in the decades surrounding menopause. Seed-based analysis revealed higher connectivity in women from the posterior cingulate to angular gyrus, which correlated with neuropsychological measures of declarative memory, and hippocampus. Taken together, we show significant sex differences in DMN subnetworks over the lifespan, including patterns in aging women that resemble changes previously seen in preclinical AD. These findings highlight the importance of considering sex in neuroimaging studies of aging and neurodegeneration.

Regression models for partially localized fMRI connectivity analyses

Brain functional connectivity analysis of resting-state functional magnetic resonance imaging (fMRI) data is typically performed in a standardized template space assuming consistency of connections across subjects. This can come in the form of one-edge-at-a-time analyses or dimension reduction/decomposition methods. Common to these approaches is the assumption of complete localization (or spatial alignment) of brain regions across subjects. Alternative approaches completely eschew localization assumptions by treating connections as statistically exchangeable (for example, using the density of connectivity between nodes). Yet other approaches, such as hyperalignment, attempt to align subjects on function as well as structure, thereby achieving a different sort of template-based localization. In this paper, we propose the use of simple regression models to characterize connectivity. To that end, we build regression models on subject-level Fisher transformed regional connection matrices using geographic distance, homotopic distance, network labels, and region indicators as covariates to explain variation in connections. While we perform our analysis in template-space in this paper, we envision the method being useful in multi-atlas registration settings, where subject data remains in its own geometry and templates are warped instead. A byproduct of this style of analysis is the ability to characterize the fraction of variation in subject-level connections explained by each type of covariate. Using Human Connectome Project data, we found that network labels and regional characteristics contribute far more than geographic or homotopic relationships (considered non-parametrically). In addition, visual regions had the highest explanatory power (i.e., largest regression coefficients). We also considered subject repeatability and found that the degree of repeatability seen in fully localized models is largely recovered using our proposed subject-level regression models. Further, even fully exchangeable models retain a sizeable amount of repeatability information, despite discarding all localization information. These results suggest the tantalizing possibility that fMRI connectivity analysis can be performed in subject-space, using less aggressive registration, such as simple affine transformations, multi-atlas subject-space registration, or perhaps even no registration whatsoever.

A graph theory neuroimaging approach to distinguish the depression of bipolar disorder from major depressive disorder in adolescents and young adults

BACKGROUND

Markers to differentiate depressions of bipolar disorder (BD-Dep) from depressions of major depressive disorder (MDD-Dep), and for more targeted treatments, are critically needed to decrease current high rates of misdiagnosis that can lead to ineffective or potentially deleterious treatments. Distinguishing, and specifically treating the depressions, during the adolescent/young adult epoch is especially important to decrease illness progression and improve prognosis, and suicide, as it is the epoch when suicide thoughts and behaviors often emerge. With differences in functional connectivity patterns reported when BD-Dep and MDD-Dep have been studied separately, this study used a graph theory approach aimed to identify functional connectivity differences in their direct comparison.

METHODS

Functional magnetic resonance imaging whole-brain functional connectivity (Intrinsic Connectivity Distribution, ICD) measures were compared across adolescents/young adults with BD-Dep (n = 28), MDD-Dep (n = 20) and HC (n = 111). Follow-up seed-based connectivity was conducted on regions of significant ICD differences. Relationships with demographic and clinical measures were assessed.

RESULTS

Compared to the HC group, both the BD-Dep and MDD-Dep groups exhibited left-sided frontal, insular, and medial temporal ICD increases. The BD-Dep group had additional right-sided ICD increases in frontal, basal ganglia, and fusiform areas. In seed-based analyses, the BD-Dep group exhibited increased interhemispheric functional connectivity between frontal areas not seen in the MDD-Dep group.

LIMITATIONS

Modest sample size; medications not studied systematically.

CONCLUSIONS

This study supports bilateral and interhemispheric functional dysconnectivity as features of BD-Dep that may differentiate it from MDD-Dep in adolescents/young adults and serve as a target for early diagnosis and treatment strategies.

Differences in functional connectivity distribution after transcranial direct-current stimulation: A connectivity density point of view

In this manuscript, we consider the problem of relating functional connectivity measurements viewed as statistical distributions to outcomes. We demonstrate the utility of using the distribution of connectivity on a study of resting-state functional magnetic resonance imaging association with an intervention. The method uses the estimated density of connectivity between nodes of interest as a functional covariate. Moreover, we demonstrate the utility of the procedure in an instance where connectivity is naturally considered an outcome by reversing the predictor/response relationship using case/control methodology. The method utilizes the density quantile, the density evaluated at empirical quantiles, instead of the empirical density directly. This improved the performance of the method by highlighting tail behavior, though we emphasize that by being flexible and non-parametric, the technique can detect effects related to the central portion of the density. To demonstrate the method in an application, we consider 47 primary progressive aphasia patients with various levels of language abilities. These patients were randomly assigned to two treatment arms, transcranial direct-current stimulation and language therapy versus sham (language therapy only), in a clinical trial. We use the method to analyze the effect of direct stimulation on functional connectivity. As such, we estimate the density of correlations among the regions of interest and study the difference in the density post-intervention between treatment arms. We discover that it is the tail of the density, rather than the mean or lower order moments of the distribution, that demonstrates a significant impact in the classification. The new approach has several benefits. Among them, it drastically reduces the number of multiple comparisons compared with edge-wise analysis. In addition, it allows for the investigation of the impact of functional connectivity on the outcomes where the connectivity is not geometrically localized.

Effects of Smoking Status and State on Intrinsic Connectivity

BACKGROUND

Smoking behavior during the first 24 hours of a quit attempt is a significant predictor of longer-term abstinence, yet little is known about the neurobiology of early tobacco abstinence. Specifically, the effects of acute tobacco deprivation and reinstatement on brain function-particularly at the level of large-scale network dynamics and assessed across the entire brain-remain incompletely understood. To address this gap, this study used a mixed within- and between-subjects design to assess the effects of smoking status (yes/no smoker) and state (deprived vs. satiated) on whole-brain patterns of intrinsic connectivity.

METHODS

Participants included 42 tobacco smokers who underwent resting-state functional magnetic resonance imaging following overnight abstinence (deprived state) and following smoking reinstatement (satiated state, randomized order across participants). Sixty healthy control nonsmokers underwent a single resting-state scan using the same acquisition parameters. Functional connectivity data were analyzed using both a canonical network-of-interest approach and a whole-brain, data-driven approach, i.e., intrinsic connectivity distribution.

RESULTS

Network-of-interest-based analyses indicated decreased functional connectivity within frontoparietal and salience networks among smokers relative to nonsmokers as well as effects of smoking state on default mode connectivity. In addition, intrinsic connectivity distribution analyses identified novel between-group differences in subcortical-cerebellar and corticocerebellar networks that were largely smoking state dependent.

CONCLUSIONS

These data demonstrate the importance of considering smoking state and the utility of using both theory- and data-driven analysis approaches. These data provide much-needed insight into the functional neurobiology of early abstinence, which may be used in the development of novel treatments.

A graph theory-based whole brain approach to assess mood state differences in adolescents and young adults with bipolar disorder

OBJECTIVES

Identifying hubs of brain dysfunction in adolescents and young adults with Bipolar I Disorder (BD_AYA ) could provide targets for early detection, prevention, and treatment. Previous neuroimaging studies across mood states of BD_AYA are scarce and often examined limited brain regions potentially prohibiting detection of other important regions. We used a data-driven whole-brain Intrinsic Connectivity Distribution (ICD) approach to investigate dysconnectivity hubs across mood states in BD_AYA .

METHODS

Functional magnetic resonance imaging whole-brain ICD data were investigated for differences across four groups: BD_AYA -depressed (n = 22), BD_AYA -euthymic (n = 45), BD_AYA -elevated (n = 24), and healthy controls (HC, n = 111). Clusters of ICD differences were assessed for regional dysconnectivity and mood symptom relationships. Analyses were also performed for BD_AYA overall (vs. HC) ICD differences persisting across mood states.

RESULTS

ICD was higher in the BD_AYA- depressed group than other groups in bilateral ventral/rostral/dorsal prefrontal cortex (PFC) and right lenticular nucleus (LN) (p_corrected  <0.05). In BD_AYA -depressed, functional connectivity (FC) was increased between these regions with their contralateral homologues and PFC-medial temporal FC was more negative (p < 0.005). PFC-related findings correlated with depression scores (p < 0.05). The overall BD_AYA group showed ICD increases in more ventral left PFC and right cerebellum, present across euthymia and acute mood states.

CONCLUSIONS

This ICD approach supports a PFC hub of inter- and intra-hemispheric frontotemporal dysconnectivity in BD_AYA with potential trait features and disturbances of higher magnitude during depression. Hubs were also revealed in LN and cerebellum, less common foci of BD research. The hubs are potential targets for early interventions to detect, prevent, and treat BD.

Multimodal neuroimaging of metabotropic glutamate 5 receptors and functional connectivity in alcohol use disorder

BACKGROUND

People recovering from alcohol use disorder (AUD) show altered resting brain connectivity. The metabotropic glutamate 5 (mGlu5) receptor is an important regulator of synaptic plasticity potentially linked with synchronized brain activity and a target of interest in treating AUD. The goal of this work was to assess potential relationships of brain connectivity at rest with mGlu5 receptor availability in people with AUD at two time points early in abstinence.

METHODS

Forty-eight image data sets were acquired with a multimodal neuroimaging battery that included resting-state functional magnetic resonance imaging (fMRI) and mGlu5 receptor positron emission tomography (PET) with the radiotracer [¹⁸ F]FPEB. Participants with AUD (n = 14) were scanned twice, at approximately 1 and 4 weeks after beginning supervised abstinence. [¹⁸ F]FPEB PET results were published previously. Primary comparisons of fMRI outcomes were performed between the AUD group and healthy controls (HCs; n = 23) and assessed changes over time within the AUD group. Relationships between resting-state connectivity measures and mGlu5 receptor availability were explored within groups.

RESULTS

Compared to HCs, global functional connectivity of the orbitofrontal cortex was higher in the AUD group at 4 weeks of abstinence (p = 0.003), while network-level functional connectivity within the default mode network (DMN) was lower (p < 0.04). Exploratory multimodal analyses showed that mGlu5 receptor availability was correlated with global connectivity across all brain regions (HCs, r = 0.41; AUD group at 1 week of abstinence, r = 0.50 and at 4 weeks, r = 0.46; all p < 0.0001). Furthermore, a component of cortical and striatal mGlu5 availability was correlated with connectivity between the DMN and salience networks in HCs (r = 0.60, p = 0.003) but not in the AUD group (p > 0.3).

CONCLUSIONS

These preliminary findings of altered global and network connectivity during the first month of abstinence from drinking may reflect the loss of efficient network function, while exploratory relationships with mGlu5 receptor availability suggest a potential glutamatergic relationship with network coherence.

Graph theory analysis of whole brain functional connectivity to assess disturbances associated with suicide attempts in bipolar disorder

Brain targets to lower the high risk of suicide in Bipolar Disorder (BD) are needed. Neuroimaging studies employing analyses dependent on regional assumptions could miss hubs of dysfunction critical to the pathophysiology of suicide behaviors and their prevention. This study applied intrinsic connectivity distribution (ICD), a whole brain graph-theoretical approach, to identify hubs of functional connectivity (FC) disturbances associated with suicide attempts in BD. ICD, from functional magnetic resonance imaging data acquired while performing a task involving implicit emotion regulation processes important in BD and suicide behaviors, was compared across 40 adults with BD with prior suicide attempts (SAs), 49 with BD with no prior attempts (NSAs) and 51 healthy volunteers (HVs). Areas of significant group differences were used as seeds to identify regional FC differences and explore associations with suicide risk-related measures. ICD was significantly lower in SAs than in NSAs and HVs in bilateral ventromedial prefrontal cortex (vmPFC) and right anterior insula (RaIns). Seed connectivity revealed altered FC from vmPFC to bilateral anteromedial orbitofrontal cortex, left ventrolateral PFC (vlPFC) and cerebellum, and from RaIns to right vlPFC and temporopolar cortices. VmPFC and RaIns ICD were negatively associated with suicidal ideation severity, and vmPFC ICD with hopelessness and attempt lethality severity. The findings suggest that SAs with BD have vmPFC and RaIns hubs of dysfunction associated with altered FC to other ventral frontal, temporopolar and cerebellar cortices, and with suicidal ideation, hopelessness, and attempt lethality. These hubs may be targets for novel therapeutics to reduce suicide risk in BD.

Sex-specific associations between traumatic experiences and resting-state functional connectivity in the Philadelphia Neurodevelopmental Cohort

Background

Traumatic experiences during childhood or adolescence are a significant risk factor for multiple psychiatric disorders and adversely affect multiple cognitive functions. Resting-state functional magnetic resonance imaging has been used to investigate the effects of traumatic experiences on functional connectivity, but the impact of sex differences has not been well documented. This study investigated sex-specific associations between resting-state functional connectivity (rsFC) and traumatic experiences in typically developing youth.

Methods

The sample comprised 1395 participants, aged 8-21 years, from the Philadelphia Neurodevelopmental Cohort. Traumatic experiences were assessed based on the structured psychiatric evaluation. Sex, the number of traumatic events, and their interaction were regressed onto voxel-wise intrinsic connectivity distribution parameter values derived from resting-state functional magnetic resonance imaging. Brain regions that passed cluster correction were used as seeds to define resting-state networks.

Results

After quality control, the final sample had 914 participants with mean (SD) age 14.6 (3.3) years; 529 (57.8%) females; 437 (47.8%) experienced at least one kind of traumatic event. Four discrete anatomical clusters showed decreased functional connectivity as the number of traumatic events increased. The resting-state networks defined by using these four clusters as seeds corresponded with the somatomotor network. Sex-specific associations were identified in another three clusters for which males showed increased connectivity, and females showed decreased connectivity as the number of traumatic events increased. The resting-state networks defined by the three sex-specific clusters corresponded with the default mode network (DMN).

Conclusions

In youth without psychiatric diagnoses, traumatic experiences are associated with an alteration of rsFC in brain regions corresponding with the somatomotor network. Associations differ in direction between males and females in brain regions corresponding with the DMN, suggesting sex-specific responses to early exposure to trauma.

Inside information: Systematic within-node functional connectivity changes observed across tasks or groups

Mapping the human connectome and understanding its relationship to brain function holds tremendous clinical potential. The connectome has two fundamental components: the nodes and the sconnections between them. While much attention has been given to deriving atlases and measuring the connections between nodes, there have been no studies examining the networks within nodes. Here we demonstrate that each node contains significant connectivity information, that varies systematically across task-induced states and subjects, such that measures based on these variations can be used to classify tasks and identify subjects. The results are not specific for any particular atlas but hold across different atlas resolutions. To date, studies examining changes in connectivity have focused on edge changes and assumed there is no useful information within nodes. Our findings illustrate that for typical atlases, within-node changes can be significant and may account for a substantial fraction of the variance currently attributed to edge changes .

Increased amygdala and decreased frontolimbic r esting- s tate functional connectivity in children with aggressive behavior

Childhood maladaptive aggression is associated with disrupted functional connectivity within amygdala-prefrontal circuitry. In this study, neural correlates of childhood aggression were probed using the intrinsic connectivity distribution, a voxel-wise metric of global resting-state brain connectivity. This sample included 38 children with aggressive behavior (26 boys, 12 girls) ages 8-16 years and 21 healthy controls (14 boys, 6 girls) matched for age and IQ. Functional MRI data were acquired during resting state, and differential patterns of intrinsic functional connectivity were tested in a priori regions of interest implicated in the pathophysiology of aggressive behavior. Next, correlational analyses tested for associations between functional connectivity and severity of aggression measured by the Reactive-Proactive Aggression Questionnaire in children with aggression. Children with aggressive behavior showed increased global connectivity in the bilateral amygdala relative to controls. Greater severity of aggressive behavior was associated with decreasing global connectivity in the dorsal anterior cingulate and ventromedial prefrontal cortex. Follow-up seed analysis revealed that aggression was also positively correlated with left amygdala connectivity with the dorsal anterior cingulate, ventromedial and dorsolateral prefrontal cortical regions. These results highlight the potential role of connectivity of the amygdala and medial prefrontal and anterior cingulate cortices in modulating the severity of aggressive behavior in treatment-seeking children.

Selective increase of correlated activity in Arc-positive neurons after chemically induced long-term potentiation in cultured hippocampal neurons

The activity-dependent expression of immediate-early genes (IEGs) has been utilised to label memory traces. However, their roles in engram specification are incompletely understood. Outstanding questions remain as to whether expression of IEGs can interplay with network properties such as functional connectivity and also if neurons expressing different IEGs are functionally distinct. In order to connect IEG expression at the cellular level with changes in functional-connectivity, we investigated the expression of 2 IEGs, Arc and c-Fos, in cultured hippocampal neurons. Primary neuronal cultures were treated with a chemical cocktail (4-aminopyridine, bicuculline, and forskolin) to increase neuronal activity, IEG expression, and induce chemical long-term potentiation. Neuronal firing is assayed by intracellular calcium imaging using GCaMP6m and expression of IEGs is assessed by immunofluorescence staining. We noted an emergent network property of refinement in network activity, characterized by a global downregulation of correlated activity, together with an increase in correlated activity between subsets of specific neurons. Subsequently, we show that Arc expression correlates with the effects of refinement, as the increase in correlated activity occurs specifically between Arc-positive neurons. The expression patterns of the IEGs c-Fos and Arc strongly overlap, but Arc was more selectively expressed than c-Fos. A subpopulation of neurons positive for both Arc and c-Fos shows increased correlated activity, while correlated firing between Arc+/cFos- neurons is reduced. Our results relate neuronal activity-dependent expression of the IEGs Arc and c-Fos on the individual cellular level to changes in correlated activity of the neuronal network.SIGNIFICANCEEstablishing a stable long-lasting memory requires neuronal network-level changes in connection strengths in a subset of neurons, which together constitute a memory trace or engram. Two genes, c-Fos and Arc, have been implicated to play critical roles in the formation of the engram. They have been studied extensively at the cellular/molecular level, and have been used as markers of memory traces in mice. We have correlated Arc and c-Fos cellular expression with refinement of correlated neuronal activity following pharmacological activation of networks formed by cultured hippocampal neurons. Whereas there is a global loss of correlated activity, Arc-positive neurons show selectively increased correlated activity. Arc is more selectively expressed than c-Fos, but the two genes act together in encoding information about changes in correlated firing.

rTMS Induces Brain Functional and Structural Alternations in Schizophrenia Patient With Auditory Verbal Hallucination

BACKGROUND

Low-frequency transcranial magnetic stimulation (rTMS) over the left temporoparietal cortex reduces the auditory verbal hallucination (AVH) in schizophrenia. However, the underlying neural basis of the rTMS treatment effect for schizophrenia remains not well understood. This study investigates the rTMS induced brain functional and structural alternations and their associations with clinical as well as neurocognitive profiles in schizophrenia patients with AVH.

METHODS

Thirty schizophrenia patients with AVH and thirty-three matched healthy controls were enrolled. The patients were administered by 15 days of 1 Hz rTMS delivering to the left temporoparietal junction (TPJ) area. Clinical symptoms and neurocognitive measurements were assessed at pre- and post-rTMS treatment. The functional (amplitude of low-frequency fluctuation, ALFF) and structural (gray matter volume, GMV) alternations were compared, and they were then used to related to the clinical and neurocognitive measurements after rTMS treatment.

RESULTS

The results showed that the positive symptoms, including AVH, were relieved, and certain neurocognitive measurements, including visual learning (VisLearn) and verbal learning (VerbLearn), were improved after the rTMS treatment in the patient group. Furthermore, the rTMS treatment induced brain functional and structural alternations in patients, such as enhanced ALFF in the left superior frontal gyrus and larger GMV in the right inferior temporal cortex. The baseline ALFF and GMV values in certain brain areas (e.g., the inferior parietal lobule and superior temporal gyrus) could be associated with the clinical symptoms (e.g., positive symptoms) and neurocognitive performances (e.g., VerbLearn and VisLearn) after rTMS treatment in patients.

CONCLUSION

The low-frequency rTMS over the left TPJ area is an efficacious treatment for schizophrenia patients with AVH and could selectively modulate the neural basis underlying psychiatric symptoms and neurocognitive domains in schizophrenia.

Within node connectivity changes, not simply edge changes, influence graph theory measures in functional connectivity studies of the brain

Interest in understanding the organization of the brain has led to the application of graph theory methods across a wide array of functional connectivity studies. The fundamental basis of a graph is the node. Recent work has shown that functional nodes reconfigure with brain state. To date, all graph theory studies of functional connectivity in the brain have used fixed nodes. Here, using fixed-, group-, state-specific, and individualized- parcellations for defining nodes, we demonstrate that functional connectivity changes within the nodes significantly influence the findings at the network level. In some cases, state- or group-dependent changes of the sort typically reported do not persist, while in others, changes are only observed when node reconfigurations are considered. The findings suggest that graph theory investigations into connectivity contrasts between brain states and/or groups should consider the influence of voxel-level changes that lead to node reconfigurations; the fundamental building block of a graph.

Altered intrinsic connectivity distribution in internet gaming disorder and its associations with psychotherapy treatment outcomes

Alterations in brain connectivity have been implicated in internet gaming disorder (IGD). However, little is known about alterations in whole-brain connectivity and their associations with long-term treatment outcomes. Here, we used a relatively new analytic approach, intrinsic connectivity distribution (ICD) analysis, to examine brain connectivity in 74 IGD participants and 41 matched healthy controls (HCs) and conducted post hoc seed-based resting-state functional connectivity (rsFC) analyses based on the ICD findings. We also examined how these findings related to outcomes involving a craving behavioral intervention (CBI) for IGD. IGD participants showed less whole-brain connectivity in the left angular gyrus and ventromedial prefrontal cortex (vmPFC) compared with HC participants. Seed-based rsFC analyses revealed that the left angular gyrus in the IGD group showed less connectivity with areas involved in the default-mode network and greater connectivity with areas in the salience and executive control networks. CBI was associated with improved connectivity within regions in the default-mode network and regions across the default-mode and salience networks. ICD-identified connectivity differences in the left angular gyrus and vmPFC were related to changes in craving and severity of addiction 6 months after the intervention. The findings suggest that IGD is associated with alterations in brain connectivity that may be sensitive to interventions. Thus, the findings have implications for understanding mechanisms underlying CBI effects and for further treatment development.

Intrinsic connectivity of the prefrontal cortex and striato-limbic system respectively differentiate major depressive from generalized anxiety disorder

Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are highly prevalent and debilitating disorders. The high overlap on the symptomatic and neurobiological level led to ongoing debates about their diagnostic and neurobiological uniqueness. The present study aims to identify common and disorder-specific neuropathological mechanisms and treatment targets in MDD and GAD. To this end we combined categorical and dimensional disorder models with a fully data-driven intrinsic network-level analysis (intrinsic connectivity contrast, ICC) to resting-state fMRI data acquired in 108 individuals (n = 35 and n = 38 unmedicated patients with first-episode GAD, MDD, respectively, and n = 35 healthy controls). Convergent evidence from categorical and dimensional analyses revealed MDD-specific decreased whole-brain connectivity profiles of the medial prefrontal and dorsolateral prefrontal cortex while GAD was specifically characterized by decreased whole-brain connectivity profiles of the putamen and decreased communication of this region with the amygdala. Together, findings from the present data-driven analysis suggest that intrinsic communication of frontal regions engaged in executive functions and emotion regulation represent depression-specific neurofunctional markers and treatment targets whereas dysregulated intrinsic communication of the striato-amygdala system engaged in reinforcement-based and emotional learning processes represent GAD-specific markers.

Neurological Functional Connectivity in Unilateral Coronal Synostosis: A Side-Based Comparison

PURPOSE

Unicoronal synostosis (UCS) has been associated with reading, language, and social dysfunction. Limited brain function connectivity studies exist for UCS with none devoted to comparing outcomes by side of synostosis (left versus right-sided UCS).

METHODS

Twelve patients with surgically treated UCS, 7 right-sided and 5 left-sided, were age matched to healthy controls. Resting state functional MRI was acquired in a 3T Siemens TIM Trio scanner (Erlangen, Germany). Data was collected with intrinsic connectivity distribution and seed-connectivity analysis using BioImage Suite (Yale School of Medicine). Region of interest analysis was performed based on Brodmann areas related to emotional, executive, language, motor, and visuo-spatial function. Significance was set at P < 0.05.

RESULTS

Compared to controls, all UCS patients demonstrated decreased connectivity in areas of the parietal and temporal cortices responsible for visuo-motor coordination and language function. Right UCS patients demonstrated decreased intrinsic connectivity in regions related to complex motor movement and proprioception relative to control subjects. Left UCS patients demonstrated decreased seed connectivity between regions of the parietal lobe and occipital lobe related to motor coordination, visual function, and language compared to right UCS patients.

CONCLUSION

Unicoronal synostosis had decreased functional connectivity in regions associated with memory, visual information processing, and motor function. Moreover, left-sided UCS had decreased connectivity in circuits for motor coordination and language when compared to right-sided UCS. This study provides data suggestive of long-term sequelae of UCS that varies by sidedness, which may be responsible for neurocognitive impairments found in previous cognitive analyses.

Association of Maternal Prepregnancy Body Mass Index With Fetal Growth and Neonatal Thalamic Brain Connectivity Among Adolescent and Young Women

Importance

Higher maternal prepregnancy body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is associated with adverse long-term outcomes for offspring, including obesity, poorer cognitive and social abilities, and increased risk of psychiatric disorders. Less clear is whether higher maternal BMI disrupts fetal growth and brain development.

Objective

To investigate the association of maternal prepregnancy BMI with fetal growth and neonatal functional connectivity.

Design, Setting, and Participants

This prospective longitudinal cohort study was conducted from 2012 to 2017. Participants included nulliparous pregnant adolescent and young adult women, aged 14 to 19 years who were recruited in the second trimester through Columbia University Irving Medical Center and Weill Cornell Medical College. Women received routine prenatal care and had no major health problems at the time of recruitment. Data were analyzed from January 2018 to March 2020.

Exposures

Maternal prepregnancy BMI.

Main Outcomes and Measures

The main outcomes were fetal growth, measured as estimated fetal weight, and neonatal functional connectivity, measured using magnetic resonance imaging. Prepregnancy BMI and fetal ultrasonographic measurements were obtained from electronic health record review. Resting-state brain imaging data were acquired in infants within the first month of postnatal life. Functional connectivity was measured using intrinsic functional distribution and seed-based methods.

Results

Among 129 women recruited, 105 had ultrasonographic data from at least 2 points and were included in analyses. The mean (SD) age at delivery was 17.82 (1.31) years. Maternal prepregnancy BMI was positively associated with the slope of estimated fetal weight (β = 0.668; 95% CI, 0.163 to 1.175; P = .01) but not with fetal head circumference (β = -0.004; 95% CI, -0.024 to 0.016; P = .70). In a subsample of 45 infants with magnetic resonance imaging data, maternal prepregnancy BMI was positively correlated with global connectivity in the left thalamus. Using this thalamic region as a seed, higher maternal BMI was associated with greater local thalamic (both hemispheres) and lower frontothalamic connectivity.

Conclusions and Relevance

These results suggest that maternal prepregnancy BMI was associated with the development of regulation of body weight and thalamic functional brain connectivity in offspring even during fetal development.

Differential Resting State Connectivity Responses to Glycemic State in Type 1 Diabetes

CONTEXT

Individuals with type 1 diabetes mellitus (T1DM) have alterations in brain activity that have been postulated to contribute to the adverse neurocognitive consequences of T1DM; however, the impact of T1DM and hypoglycemic unawareness on the brain's resting state activity remains unclear.

OBJECTIVE

To determine whether individuals with T1DM and hypoglycemia unawareness (T1DM-Unaware) had changes in the brain resting state functional connectivity compared to healthy controls (HC) and those with T1DM and hypoglycemia awareness (T1DM-Aware).

DESIGN

Observational study.

SETTING

Academic medical center.

PARTICIPANTS

27 individuals with T1DM and 12 HC volunteers participated in the study.

INTERVENTION

All participants underwent blood oxygenation level dependent (BOLD) resting state functional magnetic brain imaging during a 2-step hyperinsulinemic euglycemic (90 mg/dL)-hypoglycemic (60 mg/dL) clamp.

OUTCOME

Changes in resting state functional connectivity.

RESULTS

Using 2 separate methods of functional connectivity analysis, we identified distinct differences in the resting state brain responses to mild hypoglycemia between HC, T1DM-Aware, and T1DM-Unaware participants, particularly in the angular gyrus, an integral component of the default mode network (DMN). Furthermore, changes in angular gyrus connectivity also correlated with greater symptoms of hypoglycemia (r = 0.461, P = 0.003) as well as higher scores of perceived stress (r = 0.531, P = 0.016).

CONCLUSION

These findings provide evidence that individuals with T1DM have changes in the brain's resting state connectivity patterns, which may be further associated with differences in awareness to hypoglycemia. These changes in connectivity may be associated with alterations in functional outcomes among individuals with T1DM.

Dynamic-flip-angle ECG-gating with nuisance signal regression improves resting-state BOLD functional connectivity mapping by reducing cardiogenic noise

PURPOSE

To investigate an ECG-gated dynamic-flip-angle BOLD sequence with improved robustness against cardiogenic noise in resting-state fMRI.

METHODS

ECG-gating minimizes the cardiogenic noise but introduces T₁ -dependent signal variation, which is minimized by combination of a dynamic-flip-angle technique and retrospective nuisance signal regression (NSR) using signals of white matter, CSF, and global average. The technique was studied with simulations in a wide range of T₁ and B₁ fields and phantom imaging with pre-programmed TR variations. Resting-state fMRI of 20 healthy subjects was acquired with non-gated BOLD (NG), ECG-gated constant-flip-angle BOLD (GCFA), ECG-gated BOLD with retrospective T₁ -correction (GRC), and ECG-gated dynamic-flip-angle BOLD (GDFA), all processed by the same NSR method. GDFA was compared to alternative methods over temporal SNR (tSNR), seed-based connectivity, and whole-brain voxelwise connectivity based on intrinsic connectivity distribution (ICD). A previous large-cohort data set (N = 100) was used as a connectivity gold standard.

RESULTS

Simulations and phantom imaging show substantial reduction of the T₁ -dependent signal variation with GDFA alone, and further reduction with NSR. The resting-state study shows improved tSNR in the basal brain, comparing GDFA to NG, after both processed with NSR. Furthermore, GDFA significantly improved subcortical-subcortical and cortical-subcortical connectivity for several representative seeds and significantly improved ICD in the brainstem, thalamus, striatum, and prefrontal cortex, compared to the other 3 approaches.

CONCLUSION

GDFA with NSR improves mapping of the resting-state functional connectivity of the basal-brain regions by reducing cardiogenic noise.

Lower synaptic density is associated with depression severity and network alterations

Synaptic loss and deficits in functional connectivity are hypothesized to contribute to symptoms associated with major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). The synaptic vesicle glycoprotein 2A (SV2A) can be used to index the number of nerve terminals, an indirect estimate of synaptic density. Here, we used positron emission tomography (PET) with the SV2A radioligand [11C]UCB-J to examine synaptic density in n = 26 unmedicated individuals with MDD, PTSD, or comorbid MDD/PTSD. The severity of depressive symptoms was inversely correlated with SV2A density, and individuals with high levels of depression showing lower SV2A density compared to healthy controls (n = 21). SV2A density was also associated with aberrant network function, as measured by magnetic resonance imaging (MRI) functional connectivity. This is the first in vivo evidence linking lower synaptic density to network alterations and symptoms of depression. Our findings provide further incentive to evaluate interventions that restore synaptic connections to treat depression.

Data-Driven Analysis of Functional Connectivity Reveals a Potential Auditory Verbal Hallucination Network

Schizophrenia is a severe global health problem, with over half of such patients experiencing auditory verbal hallucinations (AVHs). A better understanding of the neural correlates differentiating patients experiencing AVHs from patients not experiencing AVHs and healthy controls may identify targets that lead to better treatment strategies for AVHs. Employing 2 data-driven, voxel-based measure of functional connectivity, we studied 46 patients with schizophrenia or schizoaffective disorder (28 experiencing AVHs and 18 not experiencing AVHs). Twenty healthy controls matched for age, gender, ethnicity, education level, handedness, and estimated verbal intelligence were included for comparison. The intrinsic connectivity distribution (ICD) was used to model each voxel's connectivity to the rest of the brain using a Weibull distribution. To investigate lateralization of connectivity, we used cross-hemisphere ICD, a method that separates the contribution of each hemisphere to interrogate connectivity laterality. Patients with AVHs compared with patients without AVHs exhibited significantly decreased whole-brain connectivity in the medial prefrontal cortex and posterior cingulate cortex, less lateralized connectivity in left putamen, and more lateralized connectivity in left interior frontal gyrus. Correlations with Auditory Hallucination Rating Scale (AHRS) and post hoc seed connectivity analyses revealed significantly altered network connectivity. Using the results from all analyses comparing the patient groups and correlations with AHRS, we identified a potential AVH network, consisting of 25 nodes, showing substantial overlap with the default mode network and language processing networks. This network as a whole, instead of individual nodes, may represent actionable targets for interventions.

Language Network Function in Young Children Born Very Preterm

Language deficits are reported in preterm born children across development. Recent neuroimaging studies have found functional alterations in large-scale brain networks underlying these language deficits, but the early childhood development of the language network has not been investigated. Here, we compared intrinsic language network connectivity in 4-year-old children born VPT and term-born controls, using defined language regions (Broca's area, Wernicke's areas, and their homologues in the right hemisphere). Resting-state functional magnetic resonance imaging (fMRI) was obtained, and the group differences in whole-brain connectivity were examined from each seed as well as correlations with language outcomes. We found significantly decreased functional connectivity in almost all language regions in children born VPT compared to their term controls. Notably, Broca's area homologue in the right hemisphere emerged as a functional hub of decreased connectivity in VPT group, specifically to bilateral inferior frontal and supramarginal gyri; connectivity strength between Broca's area homologue with the right supramarginal and the left inferior frontal gyri was associated with better language outcomes at 4 years of age. Wernicke's area and its homologue also showed decreased inter-hemispheric connections to bilateral supramarginal gyri in the VPT group. Decreased intra- and inter-hemispheric connectivity among primary language regions suggests immature and altered function in the language network in children born VPT.

Aberrant structural and functional connectivity and neurodevelopmental impairment in preterm children

Background

Despite advances in antenatal and neonatal care, preterm birth remains a leading cause of neurological disabilities in children. Infants born prematurely, particularly those delivered at the earliest gestational ages, commonly demonstrate increased rates of impairment across multiple neurodevelopmental domains. Indeed, the current literature establishes that preterm birth is a leading risk factor for cerebral palsy, is associated with executive function deficits, increases risk for impaired receptive and expressive language skills, and is linked with higher rates of co-occurring attention deficit hyperactivity disorder, anxiety, and autism spectrum disorders. These same infants also demonstrate elevated rates of aberrant cerebral structural and functional connectivity, with persistent changes evident across advanced magnetic resonance imaging modalities as early as the neonatal period. Emerging findings from cross-sectional and longitudinal investigations increasingly suggest that aberrant connectivity within key functional networks and white matter tracts may underlie the neurodevelopmental impairments common in this population.

Main body

This review begins by highlighting the elevated rates of neurodevelopmental disorders across domains in this clinical population, describes the patterns of aberrant structural and functional connectivity common in prematurely-born infants and children, and then reviews the increasingly established body of literature delineating the relationship between these brain abnormalities and adverse neurodevelopmental outcomes. We also detail important, typically understudied, clinical, and social variables that may influence these relationships among preterm children, including heritability and psychosocial risks.

Conclusion

Future work in this domain should continue to leverage longitudinal evaluations of preterm infants which include both neuroimaging and detailed serial neurodevelopmental assessments to further characterize relationships between imaging measures and impairment, information necessary for advancing our understanding of modifiable risk factors underlying these disorders and best practices for improving neurodevelopmental trajectories in this high-risk clinical population.

A molecular-genetic and imaging-genetic approach to specific comprehension difficulties in children

Children with poor reading comprehension despite typical word reading skills were examined using neuropsychological, genetic, and neuroimaging data collected from the Genes, Reading and Dyslexia Study of 1432 Hispanic American and African American children. This unexpected poor comprehension was associated with profound deficits in vocabulary, when compared to children with comprehension skills consistent with their word reading. Those with specific comprehension difficulties were also more likely to have RU2Short alleles of READ1 regulatory variants of DCDC2, strongly associated with reading and language difficulties. Subjects with RU2Short alleles showed stronger resting state functional connectivity between the right insula/inferior frontal gyrus and the right supramarginal gyrus, even after controlling for potentially confounding variables including genetic ancestry and socioeconomic status. This multi-disciplinary approach advances the current understanding of specific reading comprehension difficulties, and suggests the need for interventions that are more appropriately tailored to the specific comprehension deficits of this group of children.

A Heartbeat Away From Consciousness: Heart Rate Variability Entropy Can Discriminate Disorders of Consciousness and Is Correlated With Resting-State fMRI Brain Connectivity of the Central Autonomic Network

Background: Disorders of consciousness are challenging to diagnose, with inconsistent behavioral responses, motor and cognitive disabilities, leading to approximately 40% misdiagnoses. Heart rate variability (HRV) reflects the complexity of the heart-brain two-way dynamic interactions. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals. We here investigate the complexity index (CI), a score of HRV complexity by aggregating the non-linear multi-scale entropies over a range of time scales, and its discriminative power in chronic patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), and its relation to brain functional connectivity. Methods: We investigated the CI in short (CIs) and long (CIl) time scales in 14 UWS and 16 MCS sedated. CI for MCS and UWS groups were compared using a Mann-Whitney exact test. Spearman's correlation tests were conducted between the Coma Recovery Scale-revised (CRS-R) and both CI. Discriminative power of both CI was assessed with One-R machine learning model. Correlation between CI and brain connectivity (detected with functional magnetic resonance imagery using seed-based and hypothesis-free intrinsic connectivity) was investigated using a linear regression in a subgroup of 10 UWS and 11 MCS patients with sufficient image quality. Results: Higher CIs and CIl values were observed in MCS compared to UWS. Positive correlations were found between CRS-R and both CI. The One-R classifier selected CIl as the best discriminator between UWS and MCS with 90% accuracy, 7% false positive and 13% false negative rates after a 10-fold cross-validation test. Positive correlations were observed between both CI and the recovery of functional connectivity of brain areas belonging to the central autonomic networks (CAN). Conclusion: CI of MCS compared to UWS patients has high discriminative power and low false negative rate at one third of the estimated human assessors' misdiagnosis, providing an easy, inexpensive and non-invasive diagnostic tool. CI reflects functional connectivity changes in the CAN, suggesting that CI can provide an indirect way to screen and monitor connectivity changes in this neural system. Future studies should assess the extent of CI's predictive power in a larger cohort of patients and prognostic power in acute patients.

Application of Research Domain Criteria to childhood and adolescent impulsive and addictive disorders: Implications for treatment

The Research Domain Criteria (RDoC) initiative provides a large-scale, dimensional framework for the integration of research findings across traditional diagnoses, with the long-term aim of improving existing psychiatric treatments. A neurodevelopmental perspective is essential to this endeavor. However, few papers synthesizing research findings across childhood and adolescent disorders exist. Here, we discuss how the RDoC framework may be applied to the study of childhood and adolescent impulsive and addictive disorders in order to improve neurodevelopmental understanding and to enhance treatment development. Given the large scope of RDoC, we focus on a single construct highly relevant to addictive and impulsive disorders - initial responsiveness to reward attainment. Findings from genetic, molecular, neuroimaging and other translational research methodologies are highlighted.

Altered functional network connectivity in preterm infants: antecedents of cognitive and motor impairments?

Very preterm infants (≤ 31 weeks gestational age) are at high risk for brain injury and delayed development. Applying functional connectivity and graph theory methods to resting state MRI data (fcMRI), we tested the hypothesis that preterm infants would demonstrate alterations in connectivity measures both globally and in specific networks related to motor, language and cognitive function, even when there is no anatomical imaging evidence of injury. Fifty-one healthy full-term controls and 24 very preterm infants without significant neonatal brain injury, were evaluated at term-equivalent age with fcMRI. Preterm subjects showed lower functional connectivity from regions associated with motor, cognitive, language and executive function, than term controls. Examining brain networks using graph theory measures of functional connectivity, very preterm infants also exhibited lower rich-club coefficient and assortativity but higher small-worldness and no significant difference in modularity when compared to term infants. The findings provide evidence that functional connectivity exhibits deficits soon after birth in very preterm infants in key brain networks responsible for motor, language and executive functions, even in the absence of anatomical lesions. These functional network measures could serve as prognostic biomarkers for later developmental disabilities and guide decisions about early interventions.

Fine-Grained Parcellation of Brain Connectivity Improves Differentiation of States of Consciousness During Graded Propofol Sedation

Conscious perception relies on interactions between spatially and functionally distinct modules of the brain at various spatiotemporal scales. These interactions are altered by anesthesia, an intervention that leads to fading consciousness. Relatively little is known about brain functional connectivity and its anesthetic modulation at a fine spatial scale. Here, we used functional imaging to examine propofol-induced changes in functional connectivity in brain networks defined at a fine-grained parcellation based on a combination of anatomical and functional features. Fifteen healthy volunteers underwent resting-state functional imaging in wakeful baseline, mild sedation, deep sedation, and recovery of consciousness. Compared with wakeful baseline, propofol produced widespread, dose-dependent functional connectivity changes that scaled with the extent to which consciousness was altered. The dominant changes in connectivity were associated with the frontal lobes. By examining node pairs that demonstrated a trend of functional connectivity change between wakefulness and deep sedation, quadratic discriminant analysis differentiated the states of consciousness in individual participants more accurately at a fine-grained parcellation (e.g., 2000 nodes) than at a coarse-grained parcellation (e.g., 116 anatomical nodes). Our study suggests that defining brain networks at a high granularity may provide a superior imaging-based distinction of the graded effect of anesthesia on consciousness.

Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC-vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder.

Alterations in Anatomical Covariance in the Prematurely Born

Preterm (PT) birth results in long-term alterations in functional and structural connectivity, but the related changes in anatomical covariance are just beginning to be explored. To test the hypothesis that PT birth alters patterns of anatomical covariance, we investigated brain volumes of 25 PTs and 22 terms at young adulthood using magnetic resonance imaging. Using regional volumetrics, seed-based analyses, and whole brain graphs, we show that PT birth is associated with reduced volume in bilateral temporal and inferior frontal lobes, left caudate, left fusiform, and posterior cingulate for prematurely born subjects at young adulthood. Seed-based analyses demonstrate altered patterns of anatomical covariance for PTs compared with terms. PTs exhibit reduced covariance with R Brodmann area (BA) 47, Broca's area, and L BA 21, Wernicke's area, and white matter volume in the left prefrontal lobe, but increased covariance with R BA 47 and left cerebellum. Graph theory analyses demonstrate that measures of network complexity are significantly less robust in PTs compared with term controls. Volumes in regions showing group differences are significantly correlated with phonological awareness, the fundamental basis for reading acquisition, for the PTs. These data suggest both long-lasting and clinically significant alterations in the covariance in the PTs at young adulthood.

Cerebellar and prefrontal cortical alterations in PTSD: structural and functional evidence

BACKGROUND

Neuroimaging studies have revealed that disturbances in network organization of key brain regions may underlie cognitive and emotional dysfunction in posttraumatic stress disorder (PTSD). Examining both brain structure and function in the same population may further our understanding of network alterations in PTSD.

METHODS

We used tensor-based morphometry (TBM) and intrinsic connectivity distribution (ICD) to identify regions of altered volume and functional connectivity in unmedicated individuals with PTSD (n=21) and healthy comparison (HC) participants (n=18). These regions were then used as seeds for follow-up anatomical covariance and functional connectivity analyses.

RESULTS

Smaller volume in the cerebellum and weaker structural covariance between the cerebellum seed and middle temporal gyrus were observed in the PTSD group. Individuals with PTSD also exhibited lower whole-brain connectivity in the cerebellum, dorsolateral prefrontal cortex (dlPFC) and medial prefrontal cortex (mPFC). Functional connectivity in the cerebellum and grey matter volume in the dlPFC were negatively correlated with PTSD severity as measured by the DSM-5 PTSD checklist (PCL-5; r= -.0.77, r=-0.79). Finally, seed connectivity revealed weaker connectivity within nodes of the central executive network (right and left dlPFC), and between nodes of the default mode network (mPFC and cerebellum) and the supramarginal gyrus, in the PTSD group.

CONCLUSION

We demonstrate structural and functional alterations in PTSD converging on the PFC and cerebellum. Whilst PFC alterations are relatively well established in PTSD, the cerebellum has not generally been considered a key region in PTSD. Our findings add to a growing evidence base implicating cerebellar involvement in the pathophysiology of PTSD.

Task-related changes in degree centrality and local coherence of the posterior cingulate cortex after major cardiac surgery in older adults

OBJECTIVES

Older adults often display postoperative cognitive decline (POCD) after surgery, yet it is unclear to what extent functional connectivity (FC) alterations may underlie these deficits. We examined for postoperative voxel-wise FC changes in response to increased working memory load demands in cardiac surgery patients and nonsurgical controls.

EXPERIMENTAL DESIGN

Older cardiac surgery patients (n = 25) completed a verbal N-back working memory task during MRI scanning and cognitive testing before and 6 weeks after surgery; nonsurgical controls with cardiac disease (n = 26) underwent these assessments at identical time intervals. We measured postoperative changes in degree centrality, the number of edges attached to a brain node, and local coherence, the temporal homogeneity of regional functional correlations, using voxel-wise graph theory-based FC metrics. Group × time differences were evaluated in these FC metrics associated with increased N-back working memory load (2-back > 1-back), using a two-stage partitioned variance, mixed ANCOVA.

PRINCIPAL OBSERVATIONS

Cardiac surgery patients demonstrated postoperative working memory load-related degree centrality increases in the left dorsal posterior cingulate cortex (dPCC; p < .001, cluster p-FWE < .05). The dPCC also showed a postoperative increase in working memory load-associated local coherence (p < .001, cluster p-FWE < .05). dPCC degree centrality and local coherence increases were inversely associated with global cognitive change in surgery patients (p < .01), but not in controls.

CONCLUSIONS

Cardiac surgery patients showed postoperative increases in working memory load-associated degree centrality and local coherence of the dPCC that were inversely associated with postoperative global cognitive outcomes and independent of perioperative cerebrovascular damage.

Altered functional connectivity to stressful stimuli in prenatally cocaine-exposed adolescents

BACKGROUND

Prenatal cocaine exposure (PCE) is linked to addiction and obesity vulnerability. Neural responses to stressful and appetitive cues in adolescents with PCE versus those without have been differentially linked to substance-use initiation. However, no prior studies have assessed cue-reactivity responses among PCE adolescents using a connectivity-based approach.

METHODS

Twenty-two PCE and 22 non-prenatally drug-exposed (NDE) age-, sex-, IQ- and BMI-matched adolescents participated in individualized guided imagery with appetitive (favorite-food), stressful and neutral-relaxing cue scripts during functional magnetic resonance imaging. Subjective favorite-food craving scores were collected before and after script exposure. A data-driven voxel-wise intrinsic connectivity distribution analysis was used to identify between-group differences and examine relationships with craving scores.

RESULTS

A group-by-cue interaction effect identified a parietal lobe cluster where PCE versus NDE adolescents showed less connectivity during stressful and more connectivity during neutral-relaxing conditions. Follow-up seed-based connectivity analyses revealed that, among PCE adolescents, the parietal seed was positively connected to inferior parietal and sensory areas and negatively connected to corticolimbic during both stress and neutral-relaxing conditions. For NDE, greater parietal connectivity to parietal, cingulate and sensory areas and lesser parietal connectivity to medial prefrontal areas were found during stress compared to neutral-relaxing cueing. Craving scores inversely correlated with corticolimbic connectivity in PCE, but not NDE adolescents, during the favorite-food condition.

CONCLUSIONS

Findings from this first data-driven intrinsic connectivity analysis of PCE influences on adolescent brain function indicate differences relating to PCE status and craving. These findings provide insight into the developmental impact of in utero drug exposure.

Altered Insula Connectivity under MDMA

Recent work with noninvasive human brain imaging has started to investigate the effects of 3,4-methylenedioxymethamphetamine (MDMA) on large-scale patterns of brain activity. MDMA, a potent monoamine-releaser with particularly pronounced serotonin- releasing properties, has unique subjective effects that include: marked positive mood, pleasant/unusual bodily sensations and pro-social, empathic feelings. However, the neurobiological basis for these effects is not properly understood, and the present analysis sought to address this knowledge gap. To do this, we administered MDMA-HCl (100 mg p.o.) and, separately, placebo (ascorbic acid) in a randomized, double-blind, repeated-measures design with twenty-five healthy volunteers undergoing fMRI scanning. We then employed a measure of global resting-state functional brain connectivity and follow-up seed-to-voxel analysis to the fMRI data we acquired. Results revealed decreased right insula/salience network functional connectivity under MDMA. Furthermore, these decreases in right insula/salience network connectivity correlated with baseline trait anxiety and acute experiences of altered bodily sensations under MDMA. The present findings highlight insular disintegration (ie, compromised salience network membership) as a neurobiological signature of the MDMA experience, and relate this brain effect to trait anxiety and acutely altered bodily sensations-both of which are known to be associated with insular functioning.

Multi-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks

Anesthesia-induced changes in functional connectivity and cerebral blow flow (CBF) in large-scale brain networks have emerged as key markers of reduced consciousness. However, studies of functional connectivity disagree on which large-scale networks are altered or preserved during anesthesia, making it difficult to find a consensus amount studies. Additionally, pharmacological alterations in CBF could amplify or occlude changes in connectivity due to the shared variance between CBF and connectivity. Here, we used data-driven connectivity methods and multi-modal imaging to investigate shared and unique neural correlates of reduced consciousness for connectivity in large-scale brain networks. Rs-fMRI and CBF data were collected from the same subjects during an awake and deep sedation condition induced by propofol. We measured whole-brain connectivity using the intrinsic connectivity distribution (ICD), a method not reliant on pre-defined seed regions, networks of interest, or connectivity thresholds. The shared and unique variance between connectivity and CBF were investigated. Finally, to account for shared variance, we present a novel extension to ICD that incorporates cerebral blood flow (CBF) as a scaling factor in the calculation of global connectivity, labeled CBF-adjusted ICD). We observed altered connectivity in multiple large-scale brain networks including the default mode (DMN), salience, visual, and motor networks and reduced CBF in the DMN, frontoparietal network, and thalamus. Regional connectivity and CBF were significantly correlated during both the awake and propofol condition. Nevertheless changes in connectivity and CBF between the awake and deep sedation condition were only significantly correlated in a subsystem of the DMN, suggesting that, while there is significant shared variance between the modalities, changes due to propofol are relatively unique. Similar, but less significant, results were observed in the CBF-adjusted ICD analysis, providing additional evidence that connectivity differences were not fully explained by CBF. In conclusion, these results provide further evidence of alterations in large-scale brain networks are associated with reduced consciousness and suggest that different modalities capture unique aspects of these large scale changes.

Weak functional connectivity in the human fetal brain prior to preterm birth

It has been suggested that neurological problems more frequent in those born preterm are expressed prior to birth, but owing to technical limitations, this has been difficult to test in humans. We applied novel fetal resting-state functional MRI to measure brain function in 32 human fetuses in utero and found that systems-level neural functional connectivity was diminished in fetuses that would subsequently be born preterm. Neural connectivity was reduced in a left-hemisphere pre-language region, and the degree to which connectivity of this left language region extended to right-hemisphere homologs was positively associated with the time elapsed between fMRI assessment and delivery. These results provide the first evidence that altered functional connectivity in the preterm brain is identifiable before birth. They suggest that neurodevelopmental disorders associated with preterm birth may result from neurological insults that begin in utero.

Biological Relevance of Network Architecture

Mathematical representations of brain networks in neuroscience through the use of graph theory may be very useful for the understanding of neurological diseases and disorders and such an explanatory power is currently under intense investigation. Graph metrics are expected to vary across subjects and are likely to reflect behavioural and cognitive performances. The challenge is to set up a framework that can explain how behaviour, cognition, memory, and other brain properties can emerge through the combined interactions of neurons, ensembles of neurons, and larger-scale brain regions that make information transfer possible. "Hidden" graph theoretic properties in the construction of brain networks may limit or enhance brain functionality and may be representative of aspects of human psychology. As theorems emerge from simple mathematical properties of graphs, similarly, cognition and behaviour may emerge from the molecular, cellular and brain region substrate interactions. In this review report, we identify some studies in the current literature that have used graph theoretical metrics to extract neurobiological conclusions, we briefly discuss the link with the human connectome project as an effort to integrate human data that may aid the study of emergent patterns and we suggest a way to start categorizing diseases according to their brain network pathologies as these are measured by graph theory.

Memory-Efficient Analysis of Dense Functional Connectomes

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download.