Coupled Intrinsic Connectivity Distribution analysis: a method for exploratory connectivity analysis of paired FMRI data

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.

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.

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.

Cingulate cortex functional connectivity predicts future relapse in alcohol dependent individuals

Alcohol dependence is a chronic relapsing illness. Alcohol and stress cues have consistently been shown to increase craving and relapse risk in recovering alcohol dependent (AUD) patients. However, differences in functional connectivity in response to these cues have not been studied using data-driven approaches. Here, voxel-wise connectivity is used in a whole-brain investigation of functional connectivity differences associated with alcohol and stress cues and to examine whether these differences are related to subsequent relapse. In Study 1, 45, 4- to 8-week abstinent, recovering AUD patients underwent functional magnetic resonance imaging during individualized imagery of alcohol, stress, and neutral cues. Relapse measures were collected prospectively for 90 days post-discharge from inpatient treatment. AUD patients showed blunted anterior (ACC), mid (MCC) and posterior cingulate cortex (PCC), voxel-wise connectivity responses to stress compared to neutral cues and blunted PCC response to alcohol compared to neutral cues. Using Cox proportional hazard regression, weaker connectivity in ACC and MCC during neutral exposure was associated with longer time to relapse (better recovery outcome). Similarly, greater connectivity in PCC during alcohol-cue compared to stress cue was associated with longer time to relapse. In Study 2, a sub-group of 30 AUD patients were demographically-matched to 30 healthy control (HC) participants for group comparisons. AUD compared to HC participants showed reduced cingulate connectivity during alcohol and stress cues. Using novel data-driven approaches, the cingulate cortex emerged as a key region in the disruption of functional connectivity during alcohol and stress-cue processing in AUD patients and as a marker of subsequent alcohol relapse.

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AUD patients showed blunted cingulate connectivity to alcohol and stress cues.

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Cingulate connectivity predicted time to relapse in AUD patients.

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Greater PCC connectivity during alcohol cues predicted longer time to relapse.

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AUD vs. HC subjects showed less cingulate connectivity to alcohol and stress cues.

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The cingulate cortex emerged as a marker of subsequent alcohol relapse.

Multisite reliability of MR-based functional connectivity

Recent years have witnessed an increasing number of multisite MRI functional connectivity (fcMRI) studies. While multisite studies provide an efficient way to accelerate data collection and increase sample sizes, especially for rare clinical populations, any effects of site or MRI scanner could ultimately limit power and weaken results. Little data exists on the stability of functional connectivity measurements across sites and sessions. In this study, we assess the influence of site and session on resting state functional connectivity measurements in a healthy cohort of traveling subjects (8 subjects scanned twice at each of 8 sites) scanned as part of the North American Prodrome Longitudinal Study (NAPLS). Reliability was investigated in three types of connectivity analyses: (1) seed-based connectivity with posterior cingulate cortex (PCC), right motor cortex (RMC), and left thalamus (LT) as seeds; (2) the intrinsic connectivity distribution (ICD), a voxel-wise connectivity measure; and (3) matrix connectivity, a whole-brain, atlas-based approach to assessing connectivity between nodes. Contributions to variability in connectivity due to subject, site, and day-of-scan were quantified and used to assess between-session (test-retest) reliability in accordance with Generalizability Theory. Overall, no major site, scanner manufacturer, or day-of-scan effects were found for the univariate connectivity analyses; instead, subject effects dominated relative to the other measured factors. However, summaries of voxel-wise connectivity were found to be sensitive to site and scanner manufacturer effects. For all connectivity measures, although subject variance was three times the site variance, the residual represented 60-80% of the variance, indicating that connectivity differed greatly from scan to scan independent of any of the measured factors (i.e., subject, site, and day-of-scan). Thus, for a single 5min scan, reliability across connectivity measures was poor (ICC=0.07-0.17), but increased with increasing scan duration (ICC=0.21-0.36 at 25min). The limited effects of site and scanner manufacturer support the use of multisite studies, such as NAPLS, as a viable means of collecting data on rare populations and increasing power in univariate functional connectivity studies. However, the results indicate that aggregation of fcMRI data across longer scan durations is necessary to increase the reliability of connectivity estimates at the single-subject level.

Sex differences in normal age trajectories of functional brain networks

Resting-state functional magnetic resonance image (rs-fMRI) is increasingly used to study functional brain networks. Nevertheless, variability in these networks due to factors such as sex and aging is not fully understood. This study explored sex differences in normal age trajectories of resting-state networks (RSNs) using a novel voxel-wise measure of functional connectivity, the intrinsic connectivity distribution (ICD). Males and females showed differential patterns of changing connectivity in large-scale RSNs during normal aging from early adulthood to late middle-age. In some networks, such as the default-mode network, males and females both showed decreases in connectivity with age, albeit at different rates. In other networks, such as the fronto-parietal network, males and females showed divergent connectivity trajectories with age. Main effects of sex and age were found in many of the same regions showing sex-related differences in aging. Finally, these sex differences in aging trajectories were robust to choice of preprocessing strategy, such as global signal regression. Our findings resolve some discrepancies in the literature, especially with respect to the trajectory of connectivity in the default mode, which can be explained by our observed interactions between sex and aging. Overall, results indicate that RSNs show different aging trajectories for males and females. Characterizing effects of sex and age on RSNs are critical first steps in understanding the functional organization of the human brain.