Future Directions for Examination of Brain Networks in Neurodevelopmental Disorders

Exploring electroencephalography with a model inspired by quantum mechanics

An outstanding issue in cognitive neuroscience concerns how the brain is organized across different conditions. For instance, during the resting-state condition, the brain can be clustered into reliable and reproducible networks (e.g., sensory, default, executive networks). Interestingly, the same networks emerge during active conditions in response to various tasks. If similar patterns of neural activity have been found across diverse conditions, and therefore, different underlying processes and experiences of the environment, is the brain organized by a fundamental organizational principle? To test this, we applied mathematical formalisms borrowed from quantum mechanisms to model electroencephalogram (EEG) data. We uncovered a tendency for EEG signals to be localized in anterior regions of the brain during “rest”, and more uniformly distributed while engaged in a task (i.e., watching a movie). Moreover, we found analogous values to the Heisenberg uncertainty principle, suggesting a common underlying architecture of human brain activity in resting and task conditions. This underlying architecture manifests itself in the novel constant K_Brain, which is extracted from the brain state with the least uncertainty. We would like to state that we are using the mathematics of quantum mechanics, but not claiming that the brain behaves as a quantum object.

Early or Late Gestational Exposure to Maternal Immune Activation Alters Neurodevelopmental Trajectories in Mice: An Integrated Neuroimaging, Behavioral, and Transcriptional Study

BACKGROUND

Exposure to maternal immune activation (MIA) in utero is a risk factor for neurodevelopmental disorders later in life. The impact of the gestational timing of MIA exposure on downstream development remains unclear.

METHODS

We characterized neurodevelopmental trajectories of mice exposed to the viral mimetic poly I:C (polyinosinic:polycytidylic acid) either on gestational day 9 (early) or on day 17 (late) using longitudinal structural magnetic resonance imaging from weaning to adulthood. Using multivariate methods, we related neuroimaging and behavioral variables for the time of greatest alteration (adolescence/early adulthood) and identified regions for further investigation using RNA sequencing.

RESULTS

Early MIA exposure was associated with accelerated brain volume increases in adolescence/early adulthood that normalized in later adulthood in the striatum, hippocampus, and cingulate cortex. Similarly, alterations in anxiety-like, stereotypic, and sensorimotor gating behaviors observed in adolescence normalized in adulthood. MIA exposure in late gestation had less impact on anatomical and behavioral profiles. Multivariate maps associated anxiety-like, social, and sensorimotor gating deficits with volume of the dorsal and ventral hippocampus and anterior cingulate cortex, among others. The most transcriptional changes were observed in the dorsal hippocampus, with genes enriched for fibroblast growth factor regulation, autistic behaviors, inflammatory pathways, and microRNA regulation.

CONCLUSIONS

Leveraging an integrated hypothesis- and data-driven approach linking brain-behavior alterations to the transcriptome, we found that MIA timing differentially affects offspring development. Exposure in late gestation leads to subthreshold deficits, whereas exposure in early gestation perturbs brain development mechanisms implicated in neurodevelopmental disorders.

What have we really learned from functional connectivity in clinical populations?

Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.

Altered patterns of brain dynamics linked with body mass index in youth with autism

Children with autism spectrum disorder (ASD) have higher rates of overweight and obesity (OWOB) compared with typically developing (TD) children. Brain functional connectivity differences have been shown in both ASD and OWOB. However, only one study to date has examined ASD and OWOB concurrently, so little is known regarding the neural mechanisms associated with the higher prevalence of OWOB and its behavioral impacts in ASD. We investigated co-activation patterns (CAPs) of brain regions identified by independent component analysis in 129 children and adolescents between 6 and 18 years of age (n = 68 ASD). We examined the interaction between body mass index (BMI) and diagnosis in predicting dynamic brain metrics (dwell time, DT; frequency of occurrence, and transitions between states) as well as dimensional brain-behavior relationships. The relationship between BMI and brain dynamics was moderated by diagnosis (ASD, TD), particularly among the frequency of CAP 4, characterized by co-activation of lateral frontoparietal, temporal, and frontal networks. This pattern was negatively associated with parent-reported inhibition skills. Children with ASD had shorter CAP 1, characterized by co-activation of the subcortical, temporal, sensorimotor, and frontal networks, and CAP 4 DTs compared with TD children. CAP 1 DT was negatively associated with cognitive flexibility, inhibition, social functioning, and BMI. Cognitive flexibility moderated the relationship between BMI and brain dynamics in the visual network. Our findings provide novel evidence of neural mechanisms associated with OWOB in children with ASD. Further, poorer cognitive flexibility may result in increased vulnerability for children with ASD and co-occurring OWOB. LAY SUMMARY: Obesity is a societal epidemic and is common in autism, however, little is known about the neural mechanisms associated with the higher rates of obesity in autism. Here, we find unique patterns of brain dynamics associated with obesity in autism that were not observed in typically developing children. Further, the relationship between body mass index and brain dynamics depended on cognitive flexibility. These findings suggest that individuals with autism may be more vulnerable to the effects of obesity on brain function. Autism Res 2021, 14: 873-886. © 2021 International Society for Autism Research, Wiley Periodicals LLC.

Brain Mechanisms Supporting Flexible Cognition and Behavior in Adolescents With Autism Spectrum Disorder

Cognitive flexibility enables appropriate responses to a changing environment and is associated with positive life outcomes. Adolescence, with its increased focus on transitioning to independent living, presents particular challenges for youths with autism spectrum disorder (ASD) who often struggle to behave in a flexible way when faced with challenges. This review focuses on brain mechanisms underlying the development of flexible cognition during adolescence and how these neural systems are affected in ASD. Neuroimaging studies of task switching and set-shifting provide evidence for atypical lateral frontoparietal and midcingulo-insular network activation during cognitive flexibility task performance in individuals with ASD. Recent work also examines how intrinsic brain network dynamics support flexible cognition. These dynamic functional connectivity studies provide evidence for alterations in the number of transitions between brain states, as well as hypervariability of functional connections in adolescents with ASD. Future directions for the field include addressing issues related to measurement of cognitive flexibility using a combination of metrics with ecological and construct validity. Heterogeneity of executive function ability in ASD must also be parsed to determine which individuals will benefit most from targeted training to improve flexibility. The influence of pubertal hormones on brain network development and cognitive maturation in adolescents with ASD is another area requiring further exploration. Finally, the intriguing possibility that bilingualism might be associated with preserved cognitive flexibility in ASD should be further examined. Addressing these open questions will be critical for future translational neuroscience investigations of cognitive and behavioral flexibility in adolescents with ASD.

Coactivation pattern analysis reveals altered salience network dynamics in children with autism spectrum disorder

Brain connectivity studies of autism spectrum disorder (ASD) have historically relied on static measures of functional connectivity. Recent work has focused on identifying transient configurations of brain activity, yet several open questions remain regarding the nature of specific brain network dynamics in ASD. We used a dynamic coactivation pattern (CAP) approach to investigate the salience/midcingulo-insular (M-CIN) network, a locus of dysfunction in ASD, in a large multisite resting-state fMRI dataset collected from 172 children (ages 6–13 years; n = 75 ASD; n = 138 male). Following brain parcellation by using independent component analysis, dynamic CAP analyses were conducted and k-means clustering was used to determine transient activation patterns of the M-CIN. The frequency of occurrence of different dynamic CAP brain states was then compared between children with ASD and typically developing (TD) children. Dynamic brain configurations characterized by coactivation of the M-CIN with central executive/lateral fronto-parietal and default mode/medial fronto-parietal networks appeared less frequently in children with ASD compared with TD children. This study highlights the utility of time-varying approaches for studying altered M-CIN function in prevalent neurodevelopmental disorders. We speculate that altered M-CIN dynamics in ASD may underlie the inflexible behaviors commonly observed in children with the disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with altered patterns of functional brain connectivity. Little is currently known about how moment-to-moment brain dynamics differ in children with ASD and typically developing (TD) children. Altered functional integrity of the midcingulo-insular network (M-CIN) has been implicated in the neurobiology of ASD. Here we use a novel coactivation analysis approach applied to a large sample of resting-state fMRI data collected from children with ASD and TD children to demonstrate altered patterns of M-CIN dynamics in children with the disorder. We speculate that these atypical patterns of brain dynamics may underlie behavioral inflexibility in ASD.

Evoked and intrinsic brain network dynamics in children with autism spectrum disorder

OBJECTIVE

Brain dynamics underlie flexible cognition and behavior, yet little is known regarding this relationship in autism spectrum disorder (ASD). We examined time-varying changes in functional co-activation patterns (CAPs) across rest and task-evoked brain states to characterize differences between children with ASD and typically developing (TD) children and identify relationships with severity of social behaviors and restricted and repetitive behaviors.

METHOD

17 children with ASD and 27 TD children ages 7-12 completed a resting-state fMRI scan and four runs of a non-cued attention switching task. Metrics indexing brain dynamics were generated from dynamic CAPs computed across three major large-scale brain networks: midcingulo-insular (M-CIN), medial frontoparietal (M-FPN), and lateral frontoparietal (L-FPN).

RESULTS

Five time-varying CAPs representing dynamic co-activations among network nodes were identified across rest and task fMRI datasets. Significant Diagnosis × Condition interactions were observed for the dwell time of CAP 3, representing co-activation between nodes of the M-CIN and L-FPN, and the frequency of CAP 1, representing co-activation between nodes of the L-FPN. A significant brain-behavior association between dwell time of CAP 5, representing co-activation between nodes of the M-FPN, and social abilities was also observed across both groups of children.

CONCLUSION

Analysis of brain co-activation patterns reveals altered dynamics among three core networks in children with ASD, particularly evident during later stages of an attention task. Dimensional analyses demonstrating relationships between M-FPN dwell time and social abilities suggest that metrics of brain dynamics may index individual differences in social cognition and behavior.

The Roles of Physical Activity, Exercise, and Fitness in Promoting Resilience During Adolescence: Effects on Mental Well-Being and Brain Development

Adolescence is a critical yet vulnerable period for developing behaviors important for mental well-being. The existing literature suggests that physical activity (PA), exercise, and aerobic fitness promote well-being and reduce risk of mental health problems. In this review, we focus on PA, exercise, and fitness as modifiable resilience factors that may help promote self-regulation via strengthening of top-down control of bottom-up processes in the brain, thereby acting as a buffer against mental health problems during this period of vulnerability. First, we briefly review the link between PA, exercise, and aerobic fitness with mental well-being and reduced mental health problems in adolescence. Then we present how impairments in self-regulation, which involves top-down control to modulate bottom-up processes, are common across a wide range of mental health disorders. Finally, we use the extant neuroimaging literature to highlight how neural systems underlying top-down control continue to develop across adolescence, and propose that PA, exercise, and aerobic fitness may facilitate resilience through strengthening individual brain regions as well as large-scale neural circuits to improve emotional and behavioral regulation. Future neuroimaging studies assessing the effects of PA, exercise, and aerobic fitness at various developmental stages in each sex and studies considering the characteristics (e.g., frequency, intensity, type) and social context of PA and exercise are vital to better understand both macro- and microscale mechanisms by which these behaviors and attributes may facilitate mental health resilience during adolescent development.

Hyperconnectivity of social brain networks in autism during action-intention judgment

Deficits in social communication in autism spectrum disorder (ASD) have been documented using neuroimaging techniques such as functional MRI over the past decade. More recently, functional connectivity MRI has revealed altered connectivity in face processing, mentalizing, and mirroring brain networks, networks involved in the social brain in ASD. However, to our knowledge, previous studies have not examined these three networks concurrently. The purpose of the current study was to investigate the functional connectivity of the face processing, mentalizing, and mirroring networks (within each network and across networks) in ASD during an action-intention task in which participants were asked to determine the means and intention of a model's actions. We examined: a) within-network connectivity of each network using an ROI-to-ROI analysis; b) connectivity of each network hub to the rest of the brain using a seed-to-voxel analysis; c) the between-network connectivity of each network hub using ROI-to-ROI analysis; and d) brain-behavior relationships by correlating autism symptoms with brain connectivity. Task-fMRI data were used from 21 participants with ASD and 20 typically developing participants. The ASD group consistently showed significantly greater connectivity between networks and between hub regions to the rest of the brain. Hyperconnectivity in ASD may entail more and widespread resource utilization for accomplishing action-intention judgment.

Pushing the Boundaries of Psychiatric Neuroimaging to Ground Diagnosis in Biology

To accurately detect, track progression of, and develop novel treatments for mental illnesses, a diagnostic framework is needed that is grounded in biological features. Here, we present the case for utilizing personalized neuroimaging, computational modeling, standardized computing, and ecologically valid neuroimaging to anchor psychiatric nosology in biology.

The brain's functional connectome in young children with prenatal alcohol exposure

Prenatal alcohol exposure (PAE) can lead to altered brain function and structure, as well as lifelong cognitive, behavioral, and mental health difficulties. Previous research has shown reduced brain network efficiency in older children and adolescents with PAE, but no imaging studies have examined brain differences in young children with PAE, at an age when cognitive and behavioral problems often first become apparent. The present study aimed to investigate the brain's functional connectome in young children with PAE using passive viewing fMRI. We analyzed 34 datasets from 26 children with PAE aged 2-7 years and 215 datasets from 87 unexposed typically-developing children in the same age range. The whole brain functional connectome was constructed using functional connectivity analysis across 90 regions for each dataset. We examined intra- and inter-participant stability of the functional connectome, graph theoretical measurements, and their correlations with age. Children with PAE had similar inter- and intra-participant stability to controls. However, children with PAE, but not controls, showed increasing intra-participant stability with age, suggesting a lack of variability of intrinsic brain activity over time. Inter-participant stability increased with age in controls but not in children with PAE, indicating more variability of brain function across the PAE population. Global graph metrics were similar between children with PAE and controls, in line with previous studies in older children. This study characterizes the functional connectome in young children with PAE for the first time, suggesting that the increased brain variability seen in older children develops early in childhood, when participants with PAE fail to show the expected age-related increases in inter-individual stability.

Future Directions for Early Childhood Prevention of Mental Disorders: A Road Map to Mental Health, Earlier

Mental disorders are the predominant chronic diseases of youth, with substantial life span morbidity and mortality. A wealth of evidence demonstrates that the neurodevelopmental roots of common mental health problems are present in early childhood. Unfortunately, this has not been translated to systematic strategies for improving population-level mental health at this most malleable neurodevelopmental period. We lay out a translational Mental Health, Earlier road map as a key future direction for prevention of mental disorder. This paradigm shift aims to reduce population attributable risk of mental disorder emanating from early life, by preventing, attenuating, or delaying onset/course of chronic psychopathology via the promotion of self-regulation in early childhood within large-scale health care delivery systems. The Earlier Pillar rests on a "science of when to worry" that (a) optimizes clinical assessment methods for characterizing probabilistic clinical risk beginning in infancy via deliberate incorporation of neurodevelopmental heterogeneity, and (b) universal primary-care-based screening targeting patterns of dysregulated irritability as a robust transdiagnostic marker of vulnerability to life span mental health problems. The core of the Healthier Pillar is provision of low-intensity selective intervention promoting self-regulation for young children with developmentally atypical patterns of irritability within an implementation science framework in pediatric primary care to ensure highest population impact and sustainability. These Mental Health, Earlier strategies hold much promise for transforming clinical outlooks and ensuring young children's mental health and well-being in a manner that reverberates throughout the life span.

The emotional brain: Fundamental questions and strategies for future research

Emotions play a central role in human experience. Over time, methods for manipulating emotion have become increasingly refined and techniques for making sense of the underlying neurobiology have become ever more powerful and precise, enabling new insights into the organization of emotions in the brain. Yet recent years have witnessed a remarkably vigorous debate about the nature and origins of emotion, with leading scientists raising compelling concerns about the canon of facts and principles that has inspired and guided the field for the past quarter century. Here, we consider ways in which recent neuroimaging research informs this dialogue. By focusing attention on the most important outstanding questions about the nature of emotion and the architecture of the emotional brain, we hope to stimulate the kinds of work that will be required to move the field forward. Addressing these questions is critical, not just for understanding the mind, but also for elucidating the root causes of many of its disorders.