Improving access to first-line treatment for pediatric obesity: Lessons from the dissemination of SmartMoves.

Objective: The increasing prevalence of and inequities in childhood obesity demand improved access to effective treatment. The SmartMoves curriculum used in Bright Bodies, a proven-effective, intensive health behavior and lifestyle treatment (IHBLT), was disseminated to ≥30 US sites from 2003 to 2018. We aimed to identify barriers to and facilitators of IHBLT implementation/sustainment.

User-Centered Framework for Implementation of Technology (UFIT): Development of an Integrated Framework for Designing Clinical Decision Support Tools Packaged With Tailored Implementation Strategies.

Background: Electronic health record-based clinical decision support (CDS) tools can facilitate the adoption of evidence into practice. Yet, the impact of CDS beyond single-site implementation is often limited by dissemination and implementation barriers related to site- and user-specific variation in workflows and behaviors. The translation of evidence-based CDS from initial development to implementation in heterogeneous environments requires a framework that assures careful balancing of fidelity to core functional elements with adaptations to ensure compatibility with new contexts.

High Blood Pressure in Children Aged 3 to 12 Years Old With Overweight or Obesity.

(1) To describe the prevalence of high blood pressure (BP) and the association with BMI in young children with overweight/obesity; (2) to evaluate the accuracy of a single high BP to diagnose sustained hypertension over three visits. We used pre-intervention data from the Improving Pediatric Obesity Practice Using Prompts (iPOP-UP) trial. We included children aged 3-12 years with BMI ≥85th percentile at well-visits in 2019-2021 at 84 primary care practices in 3 US health systems in the Northeast, Midwest, and South.

Brain decoding of spontaneous thought: Predictive modeling of self-relevance and valence using personal narratives.

The contents and dynamics of spontaneous thought are important factors for personality traits and mental health. However, assessing spontaneous thoughts is challenging due to their unconstrained nature, and directing participants' attention to report their thoughts may fundamentally alter them. Here, we aimed to decode two key content dimensions of spontaneous thought-self-relevance and valence-directly from brain activity.

Brain Functional Connectivity and Anatomical Features as Predictors of Cognitive Behavioral Therapy Outcome for Anxiety in Youths.

Background: Because pediatric anxiety disorders precede the onset of many other problems, successful prediction of response to the first-line treatment, cognitive-behavioral therapy (CBT), could have major impact. However, existing clinical models are weakly predictive. The current study evaluates whether structural and resting-state functional magnetic resonance imaging can predict post-CBT anxiety symptoms.

Individuals who see the good in the bad engage distinctive default network coordination during post-encoding rest.

Focusing on the upside of negative events often promotes resilience. Yet, the underlying mechanisms that allow some people to spontaneously see the good in the bad remain unclear. The broaden-and-build theory of positive emotion has long suggested that positive affect, including positivity in the face of negative events, is linked to idiosyncratic thought patterns (i.

Will you read how I will read? Naturalistic fMRI predictors of emergent reading.

Despite reading being an essential and almost universal skill in the developed world, reading proficiency varies substantially from person to person. To study why, the fMRI field is beginning to turn from single-word or nonword reading tasks to naturalistic stimuli like connected text and listening to stories. To study reading development in children just beginning to read, listening to stories is an appropriate paradigm because speech perception and phonological processing are important for, and are predictors of, reading proficiency.

Functional neuroimaging as a catalyst for integrated neuroscience.

Functional magnetic resonance imaging (fMRI) enables non-invasive access to the awake, behaving human brain. By tracking whole-brain signals across a diverse range of cognitive and behavioural states or mapping differences associated with specific traits or clinical conditions, fMRI has advanced our understanding of brain function and its links to both normal and atypical behaviour. Despite this headway, progress in human cognitive neuroscience that uses fMRI has been relatively isolated from rapid advances in other subdomains of neuroscience, which themselves are also somewhat siloed from one another.

Inter-subject correlation during long narratives reveals widespread neural correlates of reading ability.

Recent work using fMRI inter-subject correlation analysis has provided new information about the brain's response to video and audio narratives, particularly in frontal regions not typically activated by single words. This approach is very well suited to the study of reading, where narrative is central to natural experience. But since past reading paradigms have primarily presented single words or phrases, the influence of narrative on semantic processing in the brain - and how that influence might change with reading ability - remains largely unexplored.

The default network dominates neural responses to evolving movie stories.

Neuroscientific studies exploring real-world dynamic perception often overlook the influence of continuous changes in narrative content. In our research, we utilize machine learning tools for natural language processing to examine the relationship between movie narratives and neural responses. By analyzing over 50,000 brain images of participants watching Forrest Gump from the studyforrest dataset, we find distinct brain states that capture unique semantic aspects of the unfolding story.

Negative affect homogenizes and positive affect diversifies social memory consolidation across people.

We are often surprised when an interaction we remember positively is recalled by a peer negatively. What colors social memories with positive versus negative hues? We show that when resting after a social experience, individuals showing similar default network responding subsequently remember more negative information, while individuals showing idiosyncratic default network responding remember more positive information. Results were specific to rest after the social experience (as opposed to before or during the social experience, or rest after a nonsocial experience).

Neural unscrambling of temporal information during a nonlinear narrative.

Although we must experience our lives chronologically, storytellers often manipulate the order in which they relay events. How the brain processes temporal information while encoding a nonlinear narrative remains unclear. Here, we use functional magnetic resonance imaging during movie watching to investigate which brain regions are sensitive to information about time in a narrative and test whether the representation of temporal context across a narrative is more influenced by the order in which events are presented or their underlying chronological sequence.

Seeing Social: A Neural Signature for Conscious Perception of Social Interactions.

Social information is some of the most ambiguous content we encounter in our daily lives, yet in experimental contexts, percepts of social interactions-that is, whether an interaction is present and if so, the nature of that interaction-are often dichotomized as correct or incorrect based on experimenter-assigned labels. Here, we investigated the behavioral and neural correlates of subjective (or conscious) social perception using data from the Human Connectome Project in which participants ( = 1049; 486 men, 562 women) viewed animations of geometric shapes during fMRI and indicated whether they perceived a social interaction or random motion. Critically, rather than experimenter-assigned labels, we used observers' own reports of "Social" or "Non-social" to classify percepts and characterize brain activity, including leveraging a particularly ambiguous animation perceived as "Social" by some but "Non-social" by others to control for visual input.

Leveraging the power of media to drive cognition: a media-informed approach to naturalistic neuroscience.

So-called 'naturalistic' stimuli have risen in popularity in cognitive, social and affective neuroscience over the last 15 years. However, a critical property of these stimuli is frequently overlooked: Media-like film, television, books and podcasts-are 'fundamentally not natural'. They are deliberately crafted products meant to elicit particular human thought, emotion and behavior.

In-degree centrality in a social network is linked to coordinated neural activity.

Convergent processing of the world may be a factor that contributes to social connectedness. We use neuroimaging and network analysis to investigate the association between the social-network position (as measured by in-degree centrality) of first-year university students and their neural similarity while watching naturalistic audio-visual stimuli (specifically, videos). There were 119 students in the social-network study; 63 of them participated in the neuroimaging study.

The positive-negative mode link between brain connectivity, demographics and behaviour: a pre-registered replication of Smith . (2015).

In mental health research, it has proven difficult to find measures of brain function that provide reliable indicators of mental health and well-being, including susceptibility to mental health disorders. Recently, a family of data-driven analyses have provided such reliable measures when applied to large, population-level datasets. In the current pre-registered replication study, we show that the canonical correlation analysis (CCA) methods previously developed using resting-state magnetic resonance imaging functional connectivity and subject measures (SMs) of cognition and behaviour from healthy adults are also effective in measuring well-being (a 'positive-negative axis') in an independent developmental dataset.

Is it time to put rest to rest?

The so-called resting state, in which participants lie quietly with no particular inputs or outputs, represented a paradigm shift from conventional task-based studies in human neuroimaging. Our foray into rest was fruitful from both a scientific and methodological perspective, but at this point, how much more can we learn from rest on its own? While rest still dominates in many subfields, data from tasks have empirically demonstrated benefits, as well as the potential to provide insights about the mind in addition to the brain. I argue that we can accelerate progress in human neuroscience by de-emphasizing rest in favor of more grounded experiments, including promising integrated designs that respect the prominence of self-generated activity while offering enhanced control and interpretability.

Neural signatures of attentional engagement during narratives and its consequences for event memory.

As we comprehend narratives, our attentional engagement fluctuates over time. Despite theoretical conceptions of narrative engagement as emotion-laden attention, little empirical work has characterized the cognitive and neural processes that comprise subjective engagement in naturalistic contexts or its consequences for memory. Here, we relate fluctuations in narrative engagement to patterns of brain coactivation and test whether neural signatures of engagement predict subsequent memory.