A somato-cognitive action network alternates with effector regions in motor cortex.

Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representations1,2, despite evidence for concentric functional zones3 and maps of complex actions4. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action5 and physiological control6, arousal7, errors8 and pain9. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions4 and connectivity to internal organs10 such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.

Functional parcellation of the neonatal cortical surface.

The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that existing parcellations, including surface-based parcels derived from older samples as well as volume-based neonatal parcels, are a poor fit for neonatal surface data. We next derive a set of 283 cortical surface parcels from a sample of n = 261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.

Prenatal exposure to maternal social disadvantage and psychosocial stress and neonatal white matter connectivity at birth.

Early life adversity (social disadvantage and psychosocial stressors) is associated with altered microstructure in fronto-limbic pathways important for socioemotional development. Understanding when these associations begin to emerge may inform the timing and design of preventative interventions. In this longitudinal study, 399 mothers were oversampled for low income and completed social background measures during pregnancy. Measures were analyzed with structural equation analysis resulting in two latent factors: social disadvantage (education, insurance status, income-to-needs ratio [INR], neighborhood deprivation, and nutrition) and psychosocial stress (depression, stress, life events, and racial discrimination). At birth, 289 healthy term-born neonates underwent a diffusion MRI (dMRI) scan. Mean diffusivity (MD) and fractional anisotropy (FA) were measured for the dorsal and inferior cingulum bundle (CB), uncinate, and fornix using probabilistic tractography in FSL. Social disadvantage and psychosocial stress were fitted to dMRI parameters using regression models adjusted for infant postmenstrual age at scan and sex. Social disadvantage, but not psychosocial stress, was independently associated with lower MD in the bilateral inferior CB and left uncinate, right fornix, and lower MD and higher FA in the right dorsal CB. Results persisted after accounting for maternal medical morbidities and prenatal drug exposure. In moderation analysis, psychosocial stress was associated with lower MD in the left inferior CB among the lower-to-higher socioeconomic status (SES) (INR ≥ 200%) group, but not the extremely low SES (INR < 200%) group. Increasing access to social welfare programs that reduce the burden of social disadvantage and related psychosocial stressors may be an important target to protect fetal brain development in fronto-limbic pathways.

Brexanolone Treatment in a Real-World Patient Population: A Case Series and Pilot Feasibility Study of Precision Neuroimaging.

PURPOSE/BACKGROUND: Brexanolone is approved for postpartum depression (PPD) by the United States Food and Drug Administration. Brexanolone has outperformed placebo in clinical trials, but less is known about the efficacy in real-world patients with complex social and medical histories. Furthermore, the impact of brexanolone on large-scale brain systems such as changes in functional connectivity (FC) is unknown. METHODS/PROCEDURES: We tracked changes in depressive symptoms across a diverse group of patients who received brexanolone at a large medical center. Edinburgh Postnatal Depression Scale (EPDS) scores were collected through chart review for 17 patients immediately prior to infusion through approximately 1 year postinfusion. In 2 participants, we performed precision functional neuroimaging (pfMRI), including before and after treatment in 1 patient. pfMRI collects many hours of data in individuals for precision medicine applications and was performed to assess the feasibility of investigating changes in FC with brexanolone. FINDINGS/RESULTS: The mean EPDS score immediately postinfusion was significantly lower than the mean preinfusion score (mean change [95% CI]: 10.76 [7.11-14.40], t (15) = 6.29, P < 0.0001). The mean EPDS score stayed significantly lower at 1 week (mean difference [95% CI]: 9.50 [5.23-13.76], t (11) = 4.90, P = 0.0005) and 3 months (mean difference [95% CI]: 9.99 [4.71-15.27], t (6) = 4.63, P = 0.0036) postinfusion. Widespread changes in FC followed infusion, which correlated with EPDS scores. IMPLICATIONS/CONCLUSIONS: Brexanolone is a successful treatment for PPD in the clinical setting. In conjunction with routine clinical care, brexanolone was linked to a reduction in symptoms lasting at least 3 months. pfMRI is feasible in postpartum patients receiving brexanolone and has the potential to elucidate individual-specific mechanisms of action.

Sleep and circadian rhythms during pregnancy, social disadvantage, and alterations in brain development in neonates.

Pregnant women in poverty may be especially likely to experience sleep and circadian rhythm disturbances, which may have downstream effects on fetal neurodevelopment. However, the associations between sleep and circadian rhythm disturbances, social disadvantage during pregnancy, and neonatal brain structure remains poorly understood. The current study explored the association between maternal sleep and circadian rhythm disturbances during pregnancy and neonatal brain outcomes, examining sleep and circadian rhythm disturbances as a mediator of the effect of social disadvantage during pregnancy on infant structural brain outcomes. The study included 148 mother-infant dyads, recruited during early pregnancy, who had both actigraphy and neuroimaging data. Mothers' sleep was assessed throughout their pregnancy using actigraphy, and neonates underwent brain magnetic resonance imaging in the first weeks of life. Neonatal structural brain outcomes included cortical gray matter, subcortical gray matter, and white matter volumes along with a measure of the total surface area of the cortex. Neonates of mothers who experienced greater inter-daily deviations in sleep duration had smaller total cortical gray and white matter volumes and reduced cortical surface areas. Neonates of mothers who had higher levels of circadian misalignment and later sleep timing during pregnancy showed smaller subcortical gray matter volumes. Inter-daily deviations in sleep duration during pregnancy mediated the association between maternal social disadvantage and neonatal structural brain outcomes. Findings highlight the importance of regularity and rhythmicity in sleep schedules during pregnancy and bring to light the role of chronodisruption as a potential mechanism underlying the deleterious neurodevelopmental effects of prenatal adversity. RESEARCH HIGHLIGHTS: Social disadvantage was associated with sleep and circadian rhythm disturbances during pregnancy, including later sleep schedules, increased variability in sleep duration, circadian misalignment, and a higher proportion of the sleep period spent awake. Maternal sleep and circadian rhythm disturbances during pregnancy were associated with decreased brain volume and reduced cortical surface area in neonates. Maternal inter-daily deviations in sleep duration during pregnancy mediated the association between social disadvantage and neonatal brain volume and cortical surface area.

Network-specific selectivity of functional connections in the neonatal brain.

The adult human brain is organized into functional brain networks, groups of functionally connected segregated brain regions. A key feature of adult functional networks is long-range selectivity, the property that spatially distant regions from the same network have higher functional connectivity than spatially distant regions from different networks. Although it is critical to establish the status of functional networks and long-range selectivity during the neonatal period as a foundation for typical and atypical brain development, prior work in this area has been mixed. Although some studies report distributed adult-like networks, other studies suggest that neonatal networks are immature and consist primarily of spatially isolated regions. Using a large sample of neonates (n = 262), we demonstrate that neonates have long-range selective functional connections for the default mode, fronto-parietal, and dorsal attention networks. An adult-like pattern of functional brain networks is evident in neonates when network-detection algorithms are tuned to these long-range connections, when using surface-based registration (versus volume-based registration), and as per-subject data quantity increases. These results help clarify factors that have led to prior mixed results, establish that key adult-like functional network features are evident in neonates, and provide a foundation for studies of typical and atypical brain development.

Maturation of large-scale brain systems over the first month of life.

The period immediately after birth is a critical developmental window, capturing rapid maturation of brain structure and a child's earliest experiences. Large-scale brain systems are present at delivery, but how these brain systems mature during this narrow window (i.e. first weeks of life) marked by heightened neuroplasticity remains uncharted. Using multivariate pattern classification techniques and functional connectivity magnetic resonance imaging, we detected robust differences in brain systems related to age in newborns (n = 262; R2 = 0.51). Development over the first month of life occurred brain-wide, but differed and was more pronounced in brain systems previously characterized as developing early (i.e. sensorimotor networks) than in those characterized as developing late (i.e. association networks). The cingulo-opercular network was the only exception to this organizing principle, illuminating its early role in brain development. This study represents a step towards a normative brain "growth curve" that could be used to identify atypical brain maturation in infancy.

Less attention to emotional faces is associated with low empathy and prosociality in 12-to 20-month old infants.

The development of empathy and prosocial behavior begins in infancy and is likely supported by emotion processing skills. The current study explored whether early emerging deficits in emotion processing are associated with disruptions in the development of empathy and prosociality. We investigated this question in a large, diverse sample of 147, 11- to 20-month-old infants (42% female; 61% Black; 67% low socioeconomic status). Infants completed two observational tasks assessing prosocial helping and one task assessing empathy and prosocial comforting behavior. Infants also completed an eye-tracking task assessing engagement and disengagement with negative emotional faces. Infants who attended less to angry, sad, and fearful faces (i.e., by being slower to look at and/or quicker to look away from negative compared to neutral faces) engaged in fewer helping behaviors, and effect sizes were larger when examining infants' attention toward the eye regions of faces. Additionally, infants who were quicker to look away from the eye regions of angry faces, but not the whole face, displayed less empathy and comforting behaviors. Results suggest that as early as 12 months of age, infants' decreased attention toward negative emotional faces, particularly the eye regions, is associated with less empathy and prosociality during a developmental period in which these abilities are rapidly maturing.

Socioeconomic disadvantage and parental mood/affective problems links negative parenting and executive dysfunction in children born very preterm.

Poverty increases the risk of poorer executive function (EF) in children born full-term (FT). Stressors associated with poverty, including variability in parenting behavior, may explain links between poverty and poorer EF, but this remains unclear for children born very preterm (VPT). We examine socioeconomic and parental psychosocial adversity on parenting behavior, and whether these factors independently or jointly influence EF in children born VPT. At age five years, 154 children (VPT = 88, FT = 66) completed parent-child interaction and EF tasks. Parental sensitivity, intrusiveness, cognitive stimulation, and positive and negative regard were coded with the Parent-Child Interaction Rating Scale. Socioeconomic adversity spanned maternal demographic stressors, Income-to-Needs ratio, and Area Deprivation Index. Parents completed measures of depression, anxiety, inattention/hyperactivity, parenting stress, and social-communication interaction (SCI) problems. Parental SCI problems were associated with parenting behavior in parents of children born VPT, whereas socioeconomic adversity was significant in parents of FT children. Negative parenting behaviors, but not positive parenting behaviors, were related to child EF. This association was explained by parental depression/anxiety symptoms and socioeconomic adversity. Results persisted after adjustment for parent and child IQ. Findings may inform research on dyadic interventions that embed treatment for parental mood/affective symptoms and SCI problems to improve childhood EF.

Predictive Utility of Irritability "In Context": Proof-of-Principle for an Early Childhood Mental Health Risk Calculator.

OBJECTIVE: We provide proof-of-principle for a mental health risk calculator advancing clinical utility of the irritability construct for identification of young children at high risk for common, early onsetting syndromes. METHOD: Data were harmonized from two longitudinal early childhood subsamples (total N = 403; 50.1% Male; 66.7% Nonwhite; Mage = 4.3 years). The independent subsamples were clinically enriched via disruptive behavior and violence (Subsample 1) and depression (Subsample 2). In longitudinal models, epidemiologic risk prediction methods for risk calculators were applied to test the utility of the transdiagnostic indicator, early childhood irritability, in the context of other developmental and social-ecological indicators to predict risk of internalizing/externalizing disorders at preadolescence (Mage = 9.9 years). Predictors were retained when they improved model discrimination (area under the receiver operating characteristic curve [AUC] and integrated discrimination index [IDI]) beyond the base demographic model. RESULTS: Compared to the base model, the addition of early childhood irritability and adverse childhood experiences significantly improved the AUC (0.765) and IDI slope (0.192). Overall, 23% of preschoolers went on to develop a preadolescent internalizing/externalizing disorder. For preschoolers with both elevated irritability and adverse childhood experiences, the likelihood of an internalizing/externalizing disorder was 39-66%. CONCLUSIONS: Predictive analytic tools enable personalized prediction of psychopathological risk for irritable young children, holding transformative potential for clinical translation.

Individual-specific functional connectivity of the amygdala: A substrate for precision psychiatry.

The amygdala is central to the pathophysiology of many psychiatric illnesses. An imprecise understanding of how the amygdala fits into the larger network organization of the human brain, however, limits our ability to create models of dysfunction in individual patients to guide personalized treatment. Therefore, we investigated the position of the amygdala and its functional subdivisions within the network organization of the brain in 10 highly sampled individuals (5 h of fMRI data per person). We characterized three functional subdivisions within the amygdala of each individual. We discovered that one subdivision is preferentially correlated with the default mode network; a second is preferentially correlated with the dorsal attention and fronto-parietal networks; and third subdivision does not have any networks to which it is preferentially correlated relative to the other two subdivisions. All three subdivisions are positively correlated with ventral attention and somatomotor networks and negatively correlated with salience and cingulo-opercular networks. These observations were replicated in an independent group dataset of 120 individuals. We also found substantial across-subject variation in the distribution and magnitude of amygdala functional connectivity with the cerebral cortex that related to individual differences in the stereotactic locations both of amygdala subdivisions and of cortical functional brain networks. Finally, using lag analyses, we found consistent temporal ordering of fMRI signals in the cortex relative to amygdala subdivisions. Altogether, this work provides a detailed framework of amygdala-cortical interactions that can be used as a foundation for models relating aberrations in amygdala connectivity to psychiatric symptoms in individual patients.

Maternal emotional intelligence and negative parenting affect are independently associated with callous-unemotional traits in preschoolers.

Deficits in emotion intelligence (EI) are a key component of early-childhood callous-unemotional (CU) traits. Children's EI may be influenced by their mother's EI through both familial genetic and environmental mechanisms; however, no study has directly tested the role of maternal EI in the development of CU traits. This study investigated whether maternal EI had a direct relationship with children's CU traits when controlling for the potential influence of parenting affect and other psychiatric diagnoses. Mothers and their 3- to 5-year-old preschoolers (N = 200) were recruited as part of a parent-child interaction-emotion development therapy treatment trial for preschool clinical depression and comorbid psychopathology. Using data collected prior to treatment, regression models tested whether maternal EI was related to children's CU traits, which specific aspects of maternal EI were most strongly associated with CU traits, and whether associations held after accounting for observed parenting affect. Maternal EI (p < 0.005), specifically the ability to understand others' emotions (p < 0.01), was significantly associated with children's CU traits. This relationship was specific, as maternal EI did not predict depression or oppositional defiant disorder. Both maternal EI and observed negative parenting affect were independently and significantly related to CU traits (p < 0.05) in a combined model. Given that maternal EI and observed negative parenting affect were independent predictors of CU traits in preschoolers with comorbid depression, findings suggest that current treatments for CU traits that focus solely on improving parenting could be made more effective by targeting maternal EI and helping mothers better model emotional competence.

Associations Between Preterm Birth, Inhibitory Control-Implicated Brain Regions and Tracts, and Inhibitory Control Task Performance in Children: Consideration of Socioeconomic Context.

Preterm birth (PTB) is associated with increased risk for unfavorable outcomes such as deficits in attentional control and related brain structure alterations. Crucially, PTB is more likely to occur within the context of poverty. The current study examined associations between PTB and inhibitory control (IC) implicated brain regions/tracts and task performance, as well as the moderating role of early life poverty on the relation between PTB and IC-implicated regions/tracts/task performance. 2,899 children from the ABCD study were sampled for this study. Mixed effects models examined the relation between PTB and subsequent IC performance as well as prefrontal gray matter volume, white matter fractional anisotropy (FA), and mean diffusivity (MD). Household income was examined as a moderator. PTB was significantly associated with less improvement in IC task performance over time and decreased FA in left uncinate fasciculus (UF) and cingulum bundle (CB). Early life poverty moderated the relation between PTB and both CB FA and UF MD.

New Directions in Child Psychiatry: Shaping Neurodevelopmental Trajectories.

Historically, the field of child psychiatry has lagged behind the field of general psychiatry in terms of research innovations and the availability of empirically supported treatment modalities. However, over the last two decades there has been increasing interest in and research focused on the developmental origins of mental disorders examining both neurobiological and psychosocial etiologies.1 This has catalyzed the field leading to advances in understanding the developmental psychopathology of mental disorders and the generation of novel early interventions that have shown significant promise.2-4 Further, catalyzing this effort is new data demonstrating the powerful impact of psychosocial forces on neurodevelopment. New methodologies and discoveries in the basic areas of early childhood developmental psychology have led to a greater appreciation for the emotional and cognitive sophistication of children in the first three years of life. Advances in methods to understand preverbal children's emotional and attentional responses (through measures of eye gaze and suck for example) as well as observational methods to glean a variety of mental health relevant behaviors early in life (e.g. behavioral inhibition, pro-social behaviors and social motivation) have further elucidated and validated these capacities. In addition, measures of neural function using electroencephalogram and evoked response potentials (EEG/ERP) and functional magnetic resonance imaging (fMRI) as early as the neonatal period, with many analysis methods developed at WUSTL, have further informed this domain providing new insight into early brain and behavioral relationships as well as how intervention impact brain function.5-7.

Synthesizing pseudo-T2w images to recapture missing data in neonatal neuroimaging with applications in rs-fMRI.

T1- and T2-weighted (T1w and T2w) images are essential for tissue classification and anatomical localization in Magnetic Resonance Imaging (MRI) analyses. However, these anatomical data can be challenging to acquire in non-sedated neonatal cohorts, which are prone to high amplitude movement and display lower tissue contrast than adults. As a result, one of these modalities may be missing or of such poor quality that they cannot be used for accurate image processing, resulting in subject loss. While recent literature attempts to overcome these issues in adult populations using synthetic imaging approaches, evaluation of the efficacy of these methods in pediatric populations and the impact of these techniques in conventional MR analyses has not been performed. In this work, we present two novel methods to generate pseudo-T2w images: the first is based in deep learning and expands upon previous models to 3D imaging without the requirement of paired data, the second is based in nonlinear multi-atlas registration providing a computationally lightweight alternative. We demonstrate the anatomical accuracy of pseudo-T2w images and their efficacy in existing MR processing pipelines in two independent neonatal cohorts. Critically, we show that implementing these pseudo-T2w methods in resting-state functional MRI analyses produces virtually identical functional connectivity results when compared to those resulting from T2w images, confirming their utility in infant MRI studies for salvaging otherwise lost subject data.

Filtering respiratory motion artifact from resting state fMRI data in infant and toddler populations.

The importance of motion correction when processing resting state functional magnetic resonance imaging (rs-fMRI) data is well-established in adult cohorts. This includes adjustments based on self-limited, large amplitude subject head motion, as well as factitious rhythmic motion induced by respiration. In adults, such respiration artifact can be effectively removed by applying a notch filter to the motion trace, resulting in higher amounts of data retained after frame censoring (e.g., "scrubbing") and more reliable correlation values. Due to the unique physiological and behavioral characteristics of infants and toddlers, rs-fMRI processing pipelines, including methods to identify and remove colored noise due to subject motion, must be appropriately modified to accurately reflect true neuronal signal. These younger cohorts are characterized by higher respiration rates and lower-amplitude head movements than adults; thus, the presence and significance of comparable respiratory artifact and the subsequent necessity of applying similar techniques remain unknown. Herein, we identify and characterize the consistent presence of respiratory artifact in rs-fMRI data collected during natural sleep in infants and toddlers across two independent cohorts (aged 8-24 months) analyzed using different pipelines. We further demonstrate how removing this artifact using an age-specific notch filter allows for both improved data quality and data retention in measured results. Importantly, this work reveals the critical need to identify and address respiratory-driven head motion in fMRI data acquired in young populations through the use of age-specific motion filters as a mechanism to optimize the accuracy of measured results in this population.

Neonatal Intensive Care Unit Network Neurobehavioral Scale Profiles in Full-Term Infants: Associations with Maternal Adversity, Medical Risk, and Neonatal Outcomes.

OBJECTIVES: To examine healthy, full-term neonatal behavior using the Neonatal Intensive Care Unit Network Neurobehavioral Scale (NNNS) in relation to measures of maternal adversity, maternal medical risk, and infant brain volumes. STUDY DESIGN: This was a prospective, longitudinal, observational cohort study of pregnant mothers followed from the first trimester and their healthy, full-term infants. Infants underwent an NNNS assessment and high-quality magnetic resonance imaging 2-5 weeks after birth. A latent profile analysis of NNNS scores categorized infants into neurobehavioral profiles. Univariate and multivariate analyses compared differences in maternal factors (social advantage, psychosocial stress, and medical risk) and neonatal characteristics between profiles. RESULTS: The latent profile analysis of NNNS summary scales of 296 infants generated 3 profiles: regulated (46.6%), hypotonic (16.6%), and fussy (36.8%). Infants with a hypotonic profile were more likely to be male (χ2 = 8.601; P = .014). Fussy infants had smaller head circumferences (F = 3.871; P = .022) and smaller total brain (F = 3.522; P = .031) and cerebral white matter (F = 3.986; P = .020) volumes compared with infants with a hypotonic profile. There were no differences between profiles in prenatal maternal health, social advantage, or psychosocial stress. CONCLUSIONS: Three distinct neurobehavioral profiles were identified in healthy, full-term infants with hypotonic and fussy neurobehavioral features related to neonatal brain volumes and head circumference, but not prenatal exposure to socioeconomic or psychosocial adversity. Follow-up beyond the neonatal period will determine if identified profiles at birth are associated with subsequent clinical or developmental outcomes.

Surgery requiring general anesthesia in preterm infants is associated with altered brain volumes at term equivalent age and neurodevelopmental impairment.

BACKGROUND: The aim of the study was to describe and contrast the brain development and outcome among very preterm infants that were and were not exposed to surgery requiring general anesthesia prior to term equivalent age (TEA). METHODS: Preterm infants born ≤30 weeks' gestation who did (n = 25) and did not (n = 59) have surgery requiring general anesthesia during the preterm period were studied. At TEA, infants had MRI scans performed with measures of brain tissue volumes, cortical surface area, Gyrification Index, and white matter microstructure. Neurodevelopmental follow-up with the Bayley Scales of Infant and Toddler Development, Third Edition was undertaken at 2 years of corrected age. Multivariate models, adjusted for clinical and social risk factors, were used to compare the groups. RESULTS: After controlling for clinical and social variables, preterm infants exposed to surgical anesthesia demonstrated decreased relative white matter volumes at TEA and lower cognitive and motor composite scores at 2-year follow-up. Those with longer surgical exposure demonstrated the greatest decrease in white matter volumes and lower cognitive and motor outcomes at age 2 years. CONCLUSIONS: Very preterm infants who required surgery during the preterm period had lower white mater volumes at TEA and worse neurodevelopmental outcome at age 2 years. IMPACT: In very preterm infants, there is an association between surgery requiring general anesthesia during the preterm period and reduced white mater volume on MRI at TEA and lower cognitive and motor composite scores at age 2 years. It is known that the very preterm infant's brain undergoes rapid growth during the period corresponding to the third trimester. The current study suggests an association between surgery requiring general anesthesia during this period and worse outcomes.

Translating RDoC to Real-World Impact in Developmental Psychopathology: A Neurodevelopmental Framework for Application of Mental Health Risk Calculators.

The National Institute of Mental Health Research Domain Criteria's (RDoC) has prompted a paradigm shift from categorical psychiatric disorders to considering multiple levels of vulnerability for probabilistic risk of disorder. However, the lack of neurodevelopmentally-based tools for clinical decision-making has limited RDoC's real-world impact. Integration with developmental psychopathology principles and statistical methods actualize the clinical implementation of RDoC to inform neurodevelopmental risk. In this conceptual paper, we introduce the probabilistic mental health risk calculator as an innovation for such translation and lay out a research agenda for generating an RDoC- and developmentally-informed paradigm that could be applied to predict a range of developmental psychopathologies from early childhood to young adulthood. We discuss methods that weigh the incremental utility for prediction based on intensity and burden of assessment, the addition of developmental change patterns, considerations for assessing outcomes, and integrative data approaches. Throughout, we illustrate the risk calculator approach with different neurodevelopmental pathways and phenotypes. Finally, we discuss real-world implementation of these methods for improving early identification and prevention of developmental psychopathology. We propose that mental health risk calculators can build a needed bridge between RDoC's multiple units of analysis and developmental science.

Dynamic patterns of cortical expansion during folding of the preterm human brain.

During the third trimester of human brain development, the cerebral cortex undergoes dramatic surface expansion and folding. Physical models suggest that relatively rapid growth of the cortical gray matter helps drive this folding, and structural data suggest that growth may vary in both space (by region on the cortical surface) and time. In this study, we propose a unique method to estimate local growth from sequential cortical reconstructions. Using anatomically constrained multimodal surface matching (aMSM), we obtain accurate, physically guided point correspondence between younger and older cortical reconstructions of the same individual. From each pair of surfaces, we calculate continuous, smooth maps of cortical expansion with unprecedented precision. By considering 30 preterm infants scanned two to four times during the period of rapid cortical expansion (28-38 wk postmenstrual age), we observe significant regional differences in growth across the cortical surface that are consistent with the emergence of new folds. Furthermore, these growth patterns shift over the course of development, with noninjured subjects following a highly consistent trajectory. This information provides a detailed picture of dynamic changes in cortical growth, connecting what is known about patterns of development at the microscopic (cellular) and macroscopic (folding) scales. Since our method provides specific growth maps for individual brains, we are also able to detect alterations due to injury. This fully automated surface analysis, based on tools freely available to the brain-mapping community, may also serve as a useful approach for future studies of abnormal growth due to genetic disorders, injury, or other environmental variables.