Approaches For Capturing Time-Varying Functional Network Connectivity With Application to Normative Development and Mental Illness

Since the beginning of medical science, the human brain has remained an unsolved puzzle; an illusive organ that controls everything- from breathing to heartbeats, from emotion to anger, and more. With the power of advanced neuroimaging techniques, scientists have now started to solve this nearly impossible puzzle, piece by piece. Over the past decade, various in vivo techniques, including functional magnetic resonance imaging (fMRI), have been increasingly used to understand brain functions. fMRI is extensively being used to facilitate the identification of various neuropsychological disorders such as schizophrenia (SZ), bipolar disorder (BP) and autism spectrum disorder (ASD). These disorders are currently diagnosed based on patients’ self-reported experiences, and observed symptoms and behaviors over the course of the illnesses. Therefore, efficient identification of biological-based markers (biomarkers) can lead to early diagnosis of these mental disorders, and provide a trajectory for disease progression. By applying advanced machine learning techniques on fMRI data, significant differences in brain function among patients with mental disorders and healthy controls can be identified. Moreover, by jointly estimating information from multiple modalities, such as, functional brain data and genetic factors, we can now investigate the relationship between brain function and genes. Functional connectivity (FC) has become a very common measure to characterize brain functions, where FC is defined as the temporal covariance of neural signals between multiple spatially distinct brain regions. Recently, researchers are studying the FC among functionally specialized brain networks which can be defined as a higher level of FC, and is termed as functional network connectivity (FNC, defined as the correlation value that summarizes the overall connection between brain ‘networks’ over time). Most functional connectivity studies have made the limiting assumption that connectivity is stationary over multiple minutes, and ignore to identify the time-varying and reoccurring patterns of FNC among brain regions (known as time-varying FNC). In this dissertation, we demonstrate the use of time-varying FNC features as potential biomarkers to differentiate between patients with mental disorders and healthy subjects. The developmental characteristics of time-varying FNC in children with typically developing brain and ASD have been extensively studies in a cross-sectional framework, and age-, sex- and disease-related FNC profiles have been proposed. Also, time-varying FNC is characterized in healthy adults and patients with severe mental disorders (SZ and BP). Moreover, an efficient classification algorithm is designed to identify patients and controls at individual level. Finally, a new framework is proposed to jointly utilize information from brain’s functional network connectivity and genetic features to find the associations between them. The frameworks that we presented here can help us understand the important role played by time-varying FNC to identify potential biomarkers for the diagnosis of severe mental disorders

Summaries of plenary, symposia, and oral sessions at the XXII World Congress of Psychiatric Genetics, Copenhagen, Denmark, 12-16 October 2014

The XXII World Congress of Psychiatric Genetics, sponsored by the International Society of Psychiatric Genetics, took place in Copenhagen, Denmark, on 12-16 October 2014. A total of 883 participants gathered to discuss the latest findings in the field. The following report was written by student and postdoctoral attendees. Each was assigned one or more sessions as a rapporteur. This manuscript represents topics covered in most, but not all of the oral presentations during the conference, and contains some of the major notable new findings reported

Spontaneous thought and vulnerability to mood disorders : the dark side of the wandering mind

There is increasing interest in spontaneous thought, namely task-unrelated or rest-related mental activity. Spontaneous thought is an umbrella term for processes like mind-wandering, involuntary autobiographical memory, and daydreaming, with evidence elucidating adaptive and maladaptive consequences. In this theoretical framework, we propose that, apart from its positive functions, spontaneous thought is a precursor for cognitive vulnerability in individuals who are at risk for mood disorders. It is important that spontaneous thought mostly focuses on unattained goals and evaluates the discrepancy between current and desired status. In individuals who stably (i.e., trait negative affectivity) or transitorily (i.e., stress) experience negative emotions in reaction to goal-discrepancy, spontaneous thought fosters major cognitive vulnerabilities (e.g., rumination, hopelessness, low self-esteem, and cognitive reactivity), which, in turn, enhance depression. Furthermore, we also highlight preliminary links between spontaneous thought and bipolar disorder. The evidence for this framework is reviewed, and we discuss theoretical and clinical implications of our proposal

EEG Source Imaging Indices of Cognitive Control Show Associations with Dopamine System Genes.

Cognitive or executive control is a critical mental ability, an important marker of mental illness, and among the most heritable of neurocognitive traits. Two candidate genes, catechol-O-methyltransferase (COMT) and DRD4, which both have a roles in the regulation of cortical dopamine, have been consistently associated with cognitive control. Here, we predicted that individuals with the COMT Met/Met allele would show improved response execution and inhibition as indexed by event-related potentials in a Go/NoGo task, while individuals with the DRD4 7-repeat allele would show impaired brain activity. We used independent component analysis (ICA) to separate brain source processes contributing to high-density EEG scalp signals recorded during the task. As expected, individuals with the DRD4 7-repeat polymorphism had reduced parietal P3 source and scalp responses to response (Go) compared to those without the 7-repeat. Contrary to our expectation, the COMT homozygous Met allele was associated with a smaller frontal P3 source and scalp response to response-inhibition (NoGo) stimuli, suggesting that while more dopamine in frontal cortical areas has advantages in some tasks, it may also compromise response inhibition function. An interaction effect emerged for P3 source responses to Go stimuli. These were reduced in those with both the 7-repeat DRD4 allele and either the COMT Val/Val or the Met/Met homozygous polymorphisms but not in those with the heterozygous Val/Met polymorphism. This epistatic interaction between DRD4 and COMT replicates findings that too little or too much dopamine impairs cognitive control. The anatomic and functional separated maximally independent cortical EEG sources proved more informative than scalp channel measures for genetic studies of brain function and thus better elucidate the complex mechanisms in psychiatric illness

Autonomic and brain morphological predictors of stress resilience

Stressful life events are an important cause of psychopathology. Humans exposed to aversive or stressful experiences show considerable inter-individual heterogeneity in their responses. However, the majority does not develop stress-related psychiatric disorders. The dynamic processes encompassing positive and functional adaptation in the face of significant adversity have been broadly defined as resilience. Traditionally, the assessment of resilience has been confined to self-report measures, both within the general community and putative high-risk populations. Although this approach has value, it is highly susceptible to subjective bias and may not capture the dynamic nature of resilience, as underlying construct. Recognizing the obvious benefits of more objective measures of resilience, research in the field has just started investigating the predictive value of several potential biological markers. This review provides an overview of theoretical views and empirical evidence suggesting that individual differences in heart rate variability (HRV), a surrogate index of resting cardiac vagal outflow, may underlie different levels of resilience toward the development of stress-related psychiatric disorders. Following this line of thought, recent studies describing associations between regional brain morphometric characteristics and resting state vagally-mediated HRV are summarized. Existing studies suggest that the structural morphology of the anterior cingulated cortex (ACC), particularly its cortical thickness, is implicated in the expression of individual differences in HRV. These findings are discussed in light of emerging structural neuroimaging research, linking morphological characteristics of the ACC to psychological traits ascribed to a high-resilient profile and abnormal structural integrity of the ACC to the psychophysiological expression of stress-related mental health consequences. We conclude that a multidisciplinary approach integrating brain structural imaging with HRV monitoring could offer novel perspectives about brain-body pathways in resilience and adaptation to psychological stres

Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines

The dearth of prescribing guidelines for physicians is one key driver of the current opioid epidemic in the United States. In this work, we analyze medical and pharmaceutical claims data to draw insights on characteristics of patients who are more prone to adverse outcomes after an initial synthetic opioid prescription. Toward this end, we propose a generative model that allows discovery from observational data of subgroups that demonstrate an enhanced or diminished causal effect due to treatment. Our approach models these sub-populations as a mixture distribution, using sparsity to enhance interpretability, while jointly learning nonlinear predictors of the potential outcomes to better adjust for confounding. The approach leads to human-interpretable insights on discovered subgroups, improving the practical utility for decision suppor

Pairing Neutral Cues with Alcohol Intoxication: New Findings in Executive and Attention Networks

Rationale: Alcohol-associated stimuli capture attention, yet drinkers differ in the precise stimuli that become paired with intoxication. Objectives: Extending our prior work to examine the influence of alcoholism risk factors, we paired abstract visual stimuli with intravenous alcohol delivered covertly and examined brain responses to these Pavlovian conditioned stimuli in fMRI when subjects were not intoxicated. Methods: Sixty healthy drinkers performed task-irrelevant alcohol conditioning that presented geometric shapes as conditioned stimuli. Shapes were paired with a rapidly rising alcohol limb (CS+) using intravenous alcohol infusion targeting a final peak breath alcohol concentration of 0.045 g/dL or saline (CS−) infusion at matched rates. On day two, subjects performed monetary delay discounting outside the scanner to assess delay tolerance and then underwent event-related fMRI while performing the same task with CS+, CS−, and an irrelevant symbol. Results: CS+ elicited stronger activation than CS− in frontoparietal executive/attention and orbitofrontal reward-associated networks. Risk factors including family history, recent drinking, sex, and age of drinking onset did not relate to the [CS+ > CS−] activation. Delay-tolerant choice and [CS+ > CS−] activation in right inferior parietal cortex were positively related. Conclusions: Networks governing executive attention and reward showed enhanced responses to stimuli experimentally paired with intoxication, with the right parietal cortex implicated in both alcohol cue pairing and intertemporal choice. While different from our previous study results in 14 men, we believe this paradigm in a large sample of male and female drinkers offers novel insights into Pavlovian processes less affected by idiosyncratic drug associations