Developmental Cognitive Neuroscience最新文献

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. Wearable and remote sensing technologies have advanced data collection outside of laboratory settings to enable exploring, in more detail, the associations of early experiences with brain development and social and health outcomes. In the HBCD Study, the Novel Technology/Wearable Sensors Working Group (WG-NTW) identified two primary data types to be collected: infant activity (by measuring leg movements) and sleep (by measuring heart rate and leg movements). These wearable technologies allow for remote collection in the natural environment. This paper illustrates the collection of such data via wearable technologies and describes the decision-making framework, which led to the currently deployed study design, data collection protocol, and derivatives, which will be made publicly available. Moreover, considerations regarding actual and potential challenges to adoption and use, data management, privacy, and participant burden were examined. Lastly, the present limitations in the field of wearable sensor data collection and analysis will be discussed in terms of extant validation studies, the difficulties in comparing performance across different devices, and the impact of evolving hardware/software/firmware.

Purpose

Methods

Results

Conclusion

The fundamental organization of the human brain is established before birth, with rapid growth continuing over the first postnatal years. Children exposed before or after birth to various biological (e.g., substance exposure) or psychosocial hazards (e.g., maltreatment) are at elevated likelihood of deviating from a typical developmental trajectory, which in turn can be associated with psychological, behavioral, and physical health sequelae. In the HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, brain, physical, biological, cognitive, behavioral, social, and emotional development is being examined starting in pregnancy and planned through age 10 (data are sampled at varying degrees of granularity depending on age, with more dense sampling earlier in life). HBCD aims to determine the short- and long-term impacts of a variety of both harmful and protective factors, including prenatal substance use, on developmental trajectories through early childhood. Organized as a nationwide consortium across 27 sites, the HBCD Study will collect multimodal data that will be made publicly available on a yearly basis, through a data use application and approval process. Here we provide an overview of the HBCD Study design, sampling, protocol development, and data management. Data collected through HBCD will be fundamental to informing future prenatal and early childhood interventions and policies to promote wellbeing and resilience in all children.

Adolescence is a developmental period characterized by increasingly complex and influential peer contexts. Concurrently, developmental changes in neural circuits, particularly those related to social cognition, affective salience, and cognitive control, contribute to individuals’ social interactions and behaviors. However, while adolescents’ behaviors and overall outcomes are influenced by the entirety of their social environments, insights from developmental and social neuroscience often come from studies of individual relationships or specific social actors. By capturing information about both adolescents’ individual relations and their larger social contexts, social network analysis offers a powerful opportunity to enhance our understanding of how social factors interact with adolescent development. In this review, we highlight the relevant features of adolescent social and neural development that should be considered when integrating social network analysis and neuroimaging methods. We focus on broad themes of adolescent development, including identity formation, peer sensitivity, and the pursuit of social goals, that serve as potential mechanisms for the relations between neural processes and social network features. With these factors in mind, we review the current research and propose future applications of these methods and theories.

Previously institutionalized adolescents show increased risk for psychopathology, though placement into high-quality foster care can partially mitigate this risk. White matter (WM) structure is associated with early institutional rearing and psychopathology in youth. Here we investigate associations between WM structure and psychopathology in previously institutionalized youth. Adolescent psychopathology data were collected using the MacArthur Health and Behavior Questionnaire. Participants underwent diffusion MRI, and data were processed using fixel-based analyses. General linear models investigated interactions between institutionalization groups and psychopathology on fixel metrics. Supplementary analyses also examined the main effects of psychopathology and institutionalization group on fixel metrics. Ever–Institutionalized children included 41 randomized to foster care (Mage=16.6), and 40 to care-as-usual (Mage=16.7)). In addition, 33 participants without a history of institutionalization were included as a reference group (Mage=16.9). Ever–Institutionalized adolescents displayed altered general psychopathology–fixel associations within the cerebellar peduncles, inferior longitudinal fasciculi, corticospinal tract, and corpus callosum, and altered externalizing–fixel associations within the cingulum and fornix. Our findings indicate brain–behavior associations reported in the literature may not be generalizable to all populations. Previously institutionalized youth may develop differential brain development, which in turn leads to altered neural correlates of psychopathology that are still apparent in adolescence.

Addressing the tremendous burden of early-life adversity requires constructive dialogues between scientists and policy makers to improve population health. Whereas dialogues focused on several aspects of early-life adversity have been initiated, discussion of an underrecognized form of adversity that has been observed across multiple contexts and cultures is only now emerging. Here we provide evidence for “why unpredictability?”, including: 1. Evidence that exposures to unpredictability affect child neurodevelopment, with influences that persist into adulthood. 2. The existence of a translational non-human animal model of exposure to early life unpredictability that can be capitalized upon to causally probe neurobiological mechanisms. 3. Evidence that patterns of signals in the early environment promote brain maturation across species. 4. The uneven distribution of unpredictability across demographic populations that illuminates a possible focal point for enhancing health equity. We then outline the potential of unpredictability in terms of the “what”; that is, how might the concept of unpredictability be leveraged to inform policy? We emphasize the importance of interdisciplinary and community partnerships to the success of this work and describe our community-engaged research project. Finally, we highlight opportunities for the science of unpredictability to inform policies in areas such as screening, immigration, criminal justice, education, childcare, child welfare, employment, healthcare and housing.

Neuroscientific evidence documenting continued neural development throughout adolescence has been leveraged in advocacy for more lenient treatment of adolescents in the criminal justice system. In recent years, developmental science, including neuroscience, has progressed and enabled more nuanced interpretations of what continuing neural development in adolescence likely means functionally for adolescents’ capabilities. However, oversimplified interpretations equating continuing neural development to overall “immaturity” are frequently used to make the case that adolescents should have fewer legal rights to make decisions on their own behalf, including regarding reproductive and voting rights. Here we address ongoing debates about adolescents’ autonomy rights and whether such rights should be expanded or restricted. We review extant neuroscientific and developmental research that can inform these debates. We call for: (1) a more nuanced application of developmental neuroscience to specific rights issues in specific contexts; (2) additional research designed to inform our understanding of the developmental benefits or harms of rights-based policies on young people over time; and (3) the grounding of developmental neuroscientific research on adolescents within a human rights framework. We offer suggestions to developmental and neuroscience scholars on how to discuss the science of adolescent development with those seeking guidance in their design of law and policy.

Youth diagnosed with Attention-Deficit/Hyperactivity Disorder (ADHD) often show deficits in various measures of higher-level cognition, such as, executive functioning. Poorer cognitive functioning in children with ADHD has been associated with differences in functional connectivity across the brain. However, little is known about the developmental changes to the brain’s functional properties linked to different cognitive abilities in this cohort. To characterize these changes, we analyzed fMRI data (ADHD = 373, NT = 106) collected while youth between the ages of 6 and 16 watched a short movie-clip. We applied machine learning models to identify patterns of network connectivity in response to movie-watching that differentially predict cognitive abilities in our cohort. Using out-of-sample cross validation, our models successfully predicted IQ, visual spatial, verbal comprehension, and fluid reasoning in children (ages 6 – 11), but not in adolescents with ADHD (ages 12–16). Connections with the default mode, memory retrieval, and dorsal attention were driving prediction during early and middle childhood, but connections with the somatomotor, cingulo-opercular, and frontoparietal networks were more important in middle childhood. This work demonstrated that machine learning approaches can identify distinct functional connectivity profiles associated with cognitive abilities at different developmental stages in children and adolescents with ADHD.