Spectral graph model for fMRI: a biophysical, connectivity-based generative model for the analysis of frequency-resolved resting state fMRI.

Resting state functional MRI (rs-fMRI) is a popular and widely used technique to explore the brain's functional organization and to examine if it is altered in neurological or mental disorders. The most common approach for its analysis targets the measurement of the synchronized fluctuations between brain regions, characterized as functional connectivity (FC), typically relying on pairwise correlations in activity across different brain regions. While hugely successful in exploring state- and disease-dependent network alterations, these statistical graph theory tools suffer from two key limitations. First, they discard useful information about the rich frequency content of the fMRI signal. The rich spectral information now achievable from advances in fast multiband acquisitions is consequently being under-utilized. Second, the analyzed FCs are phenomenological without a direct neurobiological underpinning in the underlying structures and processes in the brain. There does not currently exist a complete generative model framework for whole brain resting fMRI that is informed by its underlying biological basis in the structural connectome. Here we propose that a different approach can solve both challenges at once: the use of an appropriately realistic yet parsimonious biophysical signal generation model followed by graph spectral (i.e. eigen) decomposition. We call this model a Spectral Graph Model (SGM) for fMRI, using which we can not only quantify the structure-function relationship in individual subjects, but also condense the variable and individual-specific repertoire of fMRI signal's spectral and spatial features into a small number of biophysically-interpretable parameters. We expect this model-based inference of rs-fMRI that seamlessly integrates with structure can be used to examine state and trait characteristics of structure-function relations in a variety of brain disorders.

Resting state brain subnetwork relates to prosociality and compassion in adolescents.

Adolescence is a crucial time for social development, especially for helping (prosocial) and compassionate behaviors; yet brain networks involved in adolescent prosociality and compassion currently remain underexplored. Here, we sought to evaluate a recently proposed domain-general developmental (Do-GooD) network model of prosocial cognition by relating adolescent functional and structural brain networks with prosocial and compassionate disposition. We acquired resting state fMRI and diffusion MRI from 95 adolescents (ages 14-19 years; 46 males; 49 females) along with self-report questionnaires assessing prosociality and compassion. We then applied the Network-Based Statistic (NBS) to inductively investigate whether there is a significant subnetwork related to prosociality and compassion while controlling for age and sex. Based on the Do-GooD model, we expected that this subnetwork would involve connectivity to the ventromedial prefrontal cortex (VMPFC) from three domain-general networks, the default mode network (DMN), the salience network, and the control network, as well as from the DMN to the mirror neuron systems. NBS revealed a significant functional (but not structural) subnetwork related to prosociality and compassion connecting 31 regions (p = 0.02), showing DMN and DLPFC connectivity to the VMPFC; DMN connectivity to mirror neuron systems; and connectivity between the DMN and cerebellum. These findings largely support and extend the Do-GooD model of prosocial cognition in adolescents by further illuminating network-based relationships that have the potential to advance our understanding of brain mechanisms of prosociality.

A Feasibility Study of a Remotely-Delivered Mindfulness-Based Training for Adolescents During the COVID-19 Pandemic.

Social distancing, home confinement, economic challenges, and COVID-19-related illness and deaths during the COVID-19 pandemic can significantly affect mental health in youth. One promising approach to reduce anxiety and depression in adolescents is the neuroscience-based mindfulness intervention Training for Awareness, Resilience, and Action (TARA). The objective of this individually randomized waitlist-controlled trial (RCT) was (1) to test the feasibility of TARA, delivered partially over Zoom, and (2) to assess changes in the emotional wellbeing in healthy adolescents between the ages of 14-18 years old during the COVID-19 pandemic. METHODS: Twenty-one healthy adolescents were randomized to the TARA intervention or to the waitlist control group in February 2020, just before the start of the pandemic. The TARA group intervention was delivered in person for the first five sessions and remotely over Zoom for the remaining seven sessions due to the pandemic. The participants' acceptability of TARA was assessed weekly using the Child Session Rating Scale (CSRS). The primary outcome was the emotional wellbeing measured using emotional symptoms subscale of the Strengths and Difficulties Questionnaire (SDQ) pre/post-TARA. We also explored weekly changes in TARA participants' wellbeing using the Child Outcome Rating Scale (CORS). RESULTS: The overall session rating in TARA participants improved after the switch to Zoom (Cohen's d = 1.2, p = 0.008). The results of the two-way ANOVA showed no statistically significant difference in the change of the SDQ emotional symptoms during the 12 weeks between the TARA group and waitlist-control group (timepoint × group interaction: F = 0.77, p = 0.38). The exploratory analysis using the CORS in the TARA participants showed a significant improvement in their functioning over the weeks of training. CONCLUSION: Our results support the feasibility of TARA delivered over Zoom. While our primary outcome did not provide support for the improvement of the emotional wellbeing with TARA compared to a passive control group, our exploratory analysis in the intervention group indicated an improved functioning over the weeks of TARA training. The important general positive impact of this study lies in the possibility of offering a neuroscience-based mindfulness intervention remotely to youth living in remote areas and for all youth during pandemic times.

A Domain-General Developmental "Do-GooD" Network Model of Prosocial Cognition in Adolescence: A Systematic Review.

Adolescence is a period of substantial neural and social development, and prosocial decisions are beneficial to personal well-being, the well-being of others, and the functioning of society. Advances in network neuroscience call for a systematic synthesis and reappraisal of prosocial neural correlates during adolescent development. In this systematic review, we aim to outline the progress made in this field, identify the similarities between study results, and propose a model for prosocial cognition in adolescents to young adults. A total of 25 articles were included in this review. After reviewing and synthesizing the literature, we propose a DOmain-General Developmental "Do-GooD" network model of prosocial cognition that aligns with the reviewed literature, accounts for development, and combines elements of the value-based decision-making model with distinct value contributions from the default mode network, salience network, and control network. We offer predictions to test the "Do-GooD" model and propose new future directions for studying prosocial behavior and its development during adolescence, which in turn may lead to improving education and the development of better health interventions for adolescents.

Reduced anxiety and changes in amygdala network properties in adolescents with training for awareness, resilience, and action (TARA).

Mindfulness-based approaches show promise to improve emotional health in youth and may help treat and prevent adolescent depression and anxiety. However, there is a fundamental gap in understanding the neural reorganization that takes place as a result of such interventions. The Training for Awareness, Resilience, and Action (TARA) program, initially developed for depressed adolescents, uses a framework drawn from neuroscience, mindfulness, yoga, and modern psychotherapeutic techniques to promote emotional health. The goal of this study was to assess the effects of the TARA training on emotional health and structural white matter brain networks in healthy youth. We analyzed data from 23 adolescents who underwent the 12-week TARA training in a controlled within-subject study design and whose brain networks were assessed using diffusion MRI connectomics. Compared to the control time period, adolescents showed a significant decrease in anxiety symptoms with TARA (Cohen's d = -0.961, p = 0.006); moreover, the node strength of the Right Amygdala decreased significantly after TARA (Cohen's d = -1.026, p = 0.004). Post-hoc analyses indicated that anxiety at baseline before TARA was positively correlated with Right Amygdala node strength (r = 0.672, p = 0.001). While change in Right Amygdala node strength with TARA was not correlated with change in anxiety (r = 0.146, p = 0.51), it was associated with change in depression subscale of Anhedonia / Negative Affect (r = 0.575, p = 0.004, exploratory analysis), possibly due to overlapping constructs captured in our anxiety and depression scales. Our results suggest that increased structural connectivity of Right Amygdala may underlie increased anxiety in adolescents and be lowered through anxiety-reducing training such as TARA. The results of this study contribute to our understanding of the neural mechanisms of TARA and may facilitate neuroscience-based prevention and treatment of adolescent anxiety and depression.