Preliminary Efficacy of a Digital Intervention for Adolescent Depression: Randomized Controlled Trial.

BACKGROUND: Adolescent depression is a significant public health concern; however, access to effective mental health care is limited. Digital therapeutics (DTx) can improve access to evidence-based interventions; however, their efficacy in adolescents is sparsely documented. OBJECTIVE: This study aims to examine the efficacy of a mobile app DTx versus an active control as an adjunct treatment for adolescent depression symptoms. METHODS: An internet-based open-label randomized control trial was conducted nationwide with a partial crossover design, and 168 adolescents aged 13 to 21 years with symptoms of depression were recruited between November 2020 and September 2021. Participants were randomized (1:1) to the cognitive behavioral therapy-based treatment app (Spark) or to a psychoeducational control app (control), which they would use for a duration of 5 weeks. The primary outcome was a between-group (Spark vs control) difference in the change in depression symptoms from baseline to postintervention, as measured by the Patient Health Questionnaire-8 (PHQ-8) using a linear mixed-effects analysis. The PHQ-8 ranges from 0 to 24, with scores of 5 to 9 indicating mild depression symptoms, scores of 10 to 14 indicating moderate symptoms, scores of 15 to 19 indicating moderately severe symptoms, and scores of 20 to 24 indicating severe symptoms. A minimal clinically important difference (5-point reduction between baseline and postintervention) in the Spark arm and group differences in remission and treatment response rates based on the PHQ-8 at postintervention were also investigated. RESULTS: A total of 160 participants were randomized, 80 in the Spark arm (mean age 16.89, SD 2.5 y) and 80 in the control arm (mean age 16.79, SD 2.59 y). Data from 121 participants (Spark: n=63; control: n=58) with moderate to severe (PHQ-8≥10) symptoms at baseline were included in the primary analyses following a modified intention-to-treat principle. A linear mixed-effect analysis revealed a nonsignificant difference between the study arms in depression symptom change over the intervention period. The Spark arm met a minimal clinically important difference threshold (mean -5.08, 95% CI -6.72 to -3.42). The remission rate in the Spark arm was significantly higher than that in the control arm (11/63, 17% vs 2/58, 3%; χ21=6.2; P=.01; false discovery rate-adjusted P=.03). The treatment response rates were not significantly different between the study arms (P=.07; false discovery rate-adjusted P=.16). Post hoc analyses including participants with mild to severe (PHQ-8 score ≥5) symptoms at baseline revealed promising evidence that Spark is effective in those with mild to severe symptoms. CONCLUSIONS: There is initial evidence that a self-guided, cognitive behavioral therapy-based DTx intervention may effectively treat mild to severe depression symptoms in adolescents. DTx may improve access to mental health care for adolescents or serve as an important adjunct to the standard of care. TRIAL REGISTRATION: ClinicalTrials.gov NCT04524598; https://clinicaltrials.gov/study/NCT04524598.

Self-Guided Digital Intervention for Depression in Adolescents: Feasibility and Preliminary Efficacy Study.

BACKGROUND: Depression in adolescents is a large and growing problem; however, access to effective mental health care continues to be a challenge. Digitally based interventions may serve to bridge this access gap for adolescents in need of care. Digital interventions that deliver components of cognitive behavioral therapy (CBT) have been shown to reduce symptoms of depression, and virtual reality (VR) may be a promising adjunctive component. However, research on these types of treatments in adolescents and young adults is limited. OBJECTIVE: This study aims to evaluate the feasibility, acceptability, and preliminary efficacy of Spark (v1.0), a 5-week, self-guided, CBT-based digital program using a mobile app and VR experiences to target symptoms of depression in adolescents. METHODS: A single-arm, open-label study of the Spark program was conducted with a community sample of 30 adolescents and young adults aged 12 to 21 years with self-reported moderate to severe depression symptoms. Participants completed a weekly depression assessment (Patient Health Questionnaire-8) in the app during the 5-week intervention period as well as web-based baseline, postintervention, and 1-month follow-up self-report assessments. The participants also completed a qualitative postintervention interview. For participants aged <18 years, caregivers completed assessments at baseline and postintervention time points. Feasibility outcomes included recruitment rate (the proportion of participants who enrolled in the study divided by the total number of participants screened for eligibility) and retention rate (the proportion of participants who completed postintervention assessments divided by the total number of participants who received the intervention). Acceptability outcomes included engagement with the program and quantitative and qualitative feedback about the program. Preliminary efficacy was evaluated based on the Patient Health Questionnaire-8. RESULTS: The study recruitment (31/66, 47%) and retention (29/30, 97%) rates were high. Participants provided higher ratings for the ease of use of the Spark program (8.76 out of 10) and their enjoyment of both the mobile app (7.00 out of 10) and VR components (7.48 out of 10) of the program, whereas they provided lower ratings for the program's ability to improve mood (4.38 out of 10) or fit into their daily routines (5.69 out of 10). We observed a clinically and statistically significant reduction in depression scores at postintervention (mean difference 5.36; P<.001) and 1-month follow-up (mean difference 6.44; P<.001) time points. CONCLUSIONS: The Spark program was found to be a feasible and acceptable way to deliver a self-guided CBT-focused intervention to adolescents and young adults with symptoms of depression. Preliminary data also indicated that the Spark program reduced the symptoms of depression in adolescents and young adults. Future studies should evaluate the efficacy of this intervention in an adequately powered randomized controlled trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT04165681; https://classic.clinicaltrials.gov/ct2/show/NCT04165681.

Assessing the Efficacy and Safety of a Digital Therapeutic for Symptoms of Depression in Adolescents: Protocol for a Randomized Controlled Trial.

BACKGROUND: Depression is a serious, prevalent, recurrent, and undertreated disorder in adolescents. Low levels of treatment seeking and treatment adherence in this age group, combined with a growing national crisis in access to mental health care, have increased efforts to identify effective treatment alternatives for this demographic. Digital health interventions for mental illness can provide cost-effective, engaging, and accessible means of delivering psychotherapy to adolescents. OBJECTIVE: This protocol describes a virtual randomized controlled trial designed to evaluate the efficacy and safety of a self-guided, mobile app-based implementation of behavioral activation therapy, SparkRx, for the adjunct treatment of symptoms of depression in adolescents. METHODS: Participants are recruited directly through web-based and print advertisements. Following eligibility screening and consenting, participants are randomly assigned to a treatment arm (SparkRx) or a control arm (assessment-enhanced usual care) for 5 weeks. The primary efficacy outcome, total score on the 8-item Patient Health Questionnaire (PHQ-8), is assessed at the end of the 5-week intervention period. Additional participant-reported outcomes are assessed at baseline, the postintervention time point, and 1-month follow-up. The safety of the intervention is assessed by participant report (and legal guardian report, if the participant is younger than 18 years) and by patterns of symptom deterioration on the PHQ-8, as part of a larger clinical safety monitoring protocol. The primary efficacy outcome, total PHQ-8 score at the postintervention time point, will be compared between SparkRx and enhanced usual care arms using mixed effect modeling, with baseline PHQ-8 and current antidepressant medication status included as covariates. Secondary efficacy outcomes, including the proportion of participants exhibiting treatment response, remission, and minimal clinically significant improvement (all derived from total PHQ-8 scores), will be compared between groups using chi-square tests. Symptom severity at 1-month follow-up will also be compared between arms. Planned subgroup analyses will examine the robustness of treatment effects to differences in baseline symptom severity (PHQ-8 score <15 or ≥ 15) and age (younger than 18 years and older than 18 years). The primary safety outcome, the number of psychiatric serious adverse events, will be compared between trial arms using the Fisher exact test. All other adverse events will be presented descriptively. RESULTS: As of May 2023, enrollment into the study has concluded; 223 participants were randomized. The analysis of the efficacy and safety data is expected to be completed by Fall 2023. CONCLUSIONS: We hypothesize that the results of this trial will support the efficacy and safety of SparkRx in attenuating symptoms of depression in adolescents. Positive results would more broadly support the prospect of using accessible, scientifically validated, digital therapeutics in the adjunct treatment of mental health disorders in this age range. TRIAL REGISTRATION: ClinicalTrials.gov NCT05462652; https://clinicaltrials.gov/study/NCT05462652. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48740.

A CBT-based mobile intervention as an adjunct treatment for adolescents with symptoms of depression: a virtual randomized controlled feasibility trial.

Background: High rates of adolescent depression demand for more effective, accessible treatment options. A virtual randomized controlled trial was used to assess the feasibility and acceptability of a 5-week, self-guided, cognitive behavioral therapy (CBT)-based mobile application, Spark, compared to a psychoeducational mobile application (Active Control) as an adjunct treatment for adolescents with depression during the COVID-19 pandemic. Methods: A community sample aged 13-21, with self-reported symptoms of depression, was recruited nationwide. Participants were randomly assigned to use either Spark or Active Control (NSpark = 35; NActive Control = 25). Questionnaires, including the PHQ-8 measuring depression symptoms, completed before, during, and immediately following completion of the intervention, evaluated depressive symptoms, usability, engagement, and participant safety. App engagement data were also analyzed. Results: 60 eligible adolescents (female = 47) were enrolled in 2 months. 35.6% of those expressing interest were consented and all enrolled. Study retention was high (85%). Spark users rated the app as usable (System Usability Scalemean = 80.67) and engaging (User Engagement Scale-Short Formmean = 3.62). Median daily use was 29%, and 23% completed all levels. There was a significant negative relationship between behavioral activations completed and change in PHQ-8. Efficacy analyses revealed a significant main effect of time, F = 40.60, p < .001, associated with decreased PHQ-8 scores over time. There was no significant Group × Time interaction (F = 0.13, p = .72) though the numeric decrease in PHQ-8 was greater for Spark (4.69 vs. 3.56). No serious adverse events or adverse device effects were reported for Spark users. Two serious adverse events reported in the Active Control group were addressed per our safety protocol. Conclusion: Recruitment, enrollment, and retention rates demonstrated study feasibility by being comparable or better than other mental health apps. Spark was highly acceptable relative to published norms. The study's novel safety protocol efficiently detected and managed adverse events. The lack of significant difference in depression symptom reduction between Spark and Active Control may be explained by study design and study design factors. Procedures established during this feasibility study will be leveraged for subsequent powered clinical trials evaluating app efficacy and safety. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT04524598.

A Neurodevelopmental Shift in Reward Circuitry from Mother's to Nonfamilial Voices in Adolescence.

The social worlds of young children primarily revolve around parents and caregivers, who play a key role in guiding children's social and cognitive development. However, a hallmark of adolescence is a shift in orientation toward nonfamilial social targets, an adaptive process that prepares adolescents for their independence. Little is known regarding neurobiological signatures underlying changes in adolescents' social orientation. Using functional brain imaging of human voice processing in children and adolescents (ages 7-16), we demonstrate distinct neural signatures for mother's voice and nonfamilial voices across child and adolescent development in reward and social valuation systems, instantiated in nucleus accumbens and ventromedial prefrontal cortex. While younger children showed greater activity in these brain systems for mother's voice compared with nonfamilial voices, older adolescents showed the opposite effect with increased activity for nonfamilial compared with mother's voice. Findings uncover a critical role for reward and social valuative brain systems in the pronounced changes in adolescents' orientation toward nonfamilial social targets. Our approach provides a template for examining developmental shifts in social reward and motivation in individuals with pronounced social impairments, including adolescents with autism.SIGNIFICANCE STATEMENT Children's social worlds undergo a transformation during adolescence. While socialization in young children revolves around parents and caregivers, adolescence is characterized by a shift in social orientation toward nonfamilial social partners. Here we show that this shift is reflected in neural activity measured from reward processing regions in response to brief vocal samples. When younger children hear their mother's voice, reward processing regions show greater activity compared with when they hear nonfamilial, unfamiliar voices. Strikingly, older adolescents show the opposite effect, with increased activity for nonfamilial compared with mother's voice. Findings identify the brain basis of adolescents' switch in social orientation toward nonfamilial social partners and provides a template for understanding neurodevelopment in clinical populations with social and communication difficulties.

Developmental maturation of causal signaling hubs in voluntary control of saccades and their functional controllability.

The ability to adaptively respond to behaviorally relevant cues in the environment, including voluntary control of automatic but inappropriate responses and deployment of a goal-relevant alternative response, undergoes significant maturation from childhood to adulthood. Importantly, the maturation of voluntary control processes influences the developmental trajectories of several key cognitive domains, including executive function and emotion regulation. Understanding the maturation of voluntary control is therefore of fundamental importance, but little is known about the underlying causal functional circuit mechanisms. Here, we use state-space and control-theoretic modeling to investigate the maturation of causal signaling mechanisms underlying voluntary control over saccades. We demonstrate that directed causal interactions in a canonical saccade network undergo significant maturation between childhood and adulthood. Crucially, we show that the frontal eye field (FEF) is an immature causal signaling hub in children during control over saccades. Using control-theoretic analysis, we then demonstrate that the saccade network is less controllable in children and that greater energy is required to drive FEF dynamics in children compared to adults. Our findings provide novel evidence that strengthening of causal signaling hubs and controllability of FEF are key mechanisms underlying age-related improvements in the ability to plan and execute voluntary control over saccades.

Influences of affective context on amygdala functional connectivity during cognitive control from adolescence through adulthood.

Emotion processing is believed to dominate over other brain functions during adolescence, including inhibitory control. However, few studies have examined the neural underpinnings of affective states during cognitive control. Here, we characterized the brain in an affective state by cross-sectionally assessing age-related changes in amygdala background connectivity during an affective inhibitory control task. Participants completed an antisaccade (AS) fMRI task while affective auditory stimuli were presented, and a 5-minute resting state scan. Results showed that while adolescents reported similar arousal levels across emotional conditions, adults perceived negative sounds to be more "arousing" and performed better than adolescents in negative trials. Amygdala background connectivity showed age-related increases with brain regions related to attention and executive control, which were not evident during resting state. Together, results suggest that amygdala connectivity within an affective context is fairly low in mid-adolescence but much stronger in adulthood, supporting age-related improvements in inhibitory control within an affective state. These findings suggest limitations during adolescence in differentiating between the arousing effects of various emotions, potentially undermining the ability to optimally engage inhibitory control. Furthermore, the age-related fMRI findings suggest that low amygdala connectivity to brain areas involved in executive control may underlie these limited abilities during adolescence.

Anxiety and Stress Alter Decision-Making Dynamics and Causal Amygdala-Dorsolateral Prefrontal Cortex Circuits During Emotion Regulation in Children.

BACKGROUND: Anxiety and stress reactivity are risk factors for the development of affective disorders. However, the behavioral and neurocircuit mechanisms that potentiate maladaptive emotion regulation are poorly understood. Neuroimaging studies have implicated the amygdala and dorsolateral prefrontal cortex (DLPFC) in emotion regulation, but how anxiety and stress alter their context-specific causal circuit interactions is not known. Here, we use computational modeling to inform affective pathophysiology, etiology, and neurocircuit targets for early intervention. METHODS: Forty-five children (10-11 years of age; 25 boys) reappraised aversive stimuli during functional magnetic resonance imaging scanning. Clinical measures of anxiety and stress were acquired for each child. Drift-diffusion modeling of behavioral data and causal circuit analysis of functional magnetic resonance imaging data, with a National Institute of Mental Health Research Domain Criteria approach, were used to characterize latent behavioral and neurocircuit decision-making dynamics driving emotion regulation. RESULTS: Children successfully reappraised negative responses to aversive stimuli. Drift-diffusion modeling revealed that emotion regulation was characterized by increased initial bias toward positive reactivity during viewing of aversive stimuli and increased drift rate, which captured evidence accumulation during emotion evaluation. Crucially, anxiety and stress reactivity impaired latent behavioral dynamics associated with reappraisal and decision making. Anxiety and stress increased dynamic casual influences from the right amygdala to DLPFC. In contrast, DLPFC, but not amygdala, reactivity was correlated with evidence accumulation and decision making during emotion reappraisal. CONCLUSIONS: Our findings provide new insights into how anxiety and stress in children impact decision making and amygdala-DLPFC signaling during emotion regulation, and uncover latent behavioral and neurocircuit mechanisms of early risk for psychopathology.

Hyperdirect insula-basal-ganglia pathway and adult-like maturity of global brain responses predict inhibitory control in children.

Inhibitory control is fundamental to children's self-regulation and cognitive development. Here we investigate cortical-basal ganglia pathways underlying inhibitory control in children and their adult-like maturity. We first conduct a comprehensive meta-analysis of extant neurodevelopmental studies of inhibitory control and highlight important gaps in the literature. Second, we examine cortical-basal ganglia activation during inhibitory control in children ages 9-12 and demonstrate the formation of an adult-like inhibitory control network by late childhood. Third, we develop a neural maturation index (NMI), which assesses the similarity of brain activation patterns between children and adults, and demonstrate that higher NMI in children predicts better inhibitory control. Fourth, we show that activity in the subthalamic nucleus and its effective connectivity with the right anterior insula predicts children's inhibitory control. Fifth, we replicate our findings across multiple cohorts. Our findings provide insights into cortical-basal ganglia circuits and global brain organization underlying the development of inhibitory control.

Development of Human Emotion Circuits Investigated Using a Big-Data Analytic Approach: Stability, Reliability, and Robustness.

Emotion perception is fundamental to affective and cognitive development and is thought to involve distributed brain circuits. Efforts to chart neurodevelopmental changes in emotion have been severely hampered by narrowly focused approaches centered on activation of individual brain regions and small sample sizes. Here we investigate the maturation of human functional brain circuits associated with identification of fearful, angry, sad, happy, and neutral faces using a large sample of 759 children, adolescents, and adults (ages 8-23; female/male = 419/340). Network analysis of emotion-related brain circuits revealed three functional modules, encompassing lateral frontoparietal, medial prefrontal-posterior cingulate, and subcortical-posterior insular cortices, with hubs in medial prefrontal, but not posterior cingulate, cortex. This overall network architecture was stable by age 8, and it anchored maturation of circuits important for salience detection and cognitive control, as well as dissociable circuit patterns across distinct emotion categories. Our findings point to similarities and differences in functional circuits associated with identification of fearful, angry, sad, happy, and neutral faces, and reveal aspects of brain circuit organization underlying emotion perception that are stable over development as well as features that change with age. Reliability analyses demonstrated the robustness of our findings and highlighted the importance of large samples for probing functional brain circuit development. Our study emphasizes a need to focus beyond amygdala circuits and provides a robust neurodevelopmental template for investigating emotion perception and identification in psychopathology.SIGNIFICANCE STATEMENT Emotion perception is fundamental to cognitive and affective development. However, efforts to chart neurodevelopmental changes in emotion perception have been hampered by narrowly focused approaches centered on the amygdala and prefrontal cortex and small sample sizes. Using a large sample of 759 children, adolescents, and adults and a multipronged analytical strategy, we investigated the development of brain network organization underlying identification and categorization of fearful, happy, angry, sad, and neutral facial expressions. Results revealed a developmentally stable modular architecture that anchored robust age-related and emotion category-related changes in brain connectivity across multiple brain systems that extend far beyond amygdala circuits and provide a new template for investigation of emotion processing in the developing brain.

Impaired voice processing in reward and salience circuits predicts social communication in children with autism.

Engaging with vocal sounds is critical for children's social-emotional learning, and children with autism spectrum disorder (ASD) often 'tune out' voices in their environment. Little is known regarding the neurobiological basis of voice processing and its link to social impairments in ASD. Here, we perform the first comprehensive brain network analysis of voice processing in children with ASD. We examined neural responses elicited by unfamiliar voices and mother's voice, a biologically salient voice for social learning, and identified a striking relationship between social communication abilities in children with ASD and activation in key structures of reward and salience processing regions. Functional connectivity between voice-selective and reward regions during voice processing predicted social communication in children with ASD and distinguished them from typically developing children. Results support the Social Motivation Theory of ASD by showing reward system deficits associated with the processing of a critical social stimulus, mother's voice, in children with ASD. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that minor issues remain unresolved (see decision letter).

Deficits in mesolimbic reward pathway underlie social interaction impairments in children with autism.

Lack of interest in social interaction is a hallmark of autism spectrum disorder. Animal studies have implicated the mesolimbic reward pathway in driving and reinforcing social behaviour, but little is known about the integrity of this pathway and its behavioural consequences in children with autism spectrum disorder. Here we test the hypothesis that the structural and functional integrity of the mesolimbic reward pathway is aberrant in children with autism spectrum disorder, and these aberrancies contribute to the social interaction impairments. We examine structural and functional connectivity of the mesolimbic reward pathway in two independent cohorts totalling 82 children aged 7-13 years with autism spectrum disorder and age-, gender-, and intelligence quotient-matched typically developing children (primary cohort: children with autism spectrum disorder n = 24, typically developing children n = 24; replication cohort: children with autism spectrum disorder n = 17, typically developing children n = 17), using high angular resolution diffusion-weighted imaging and functional MRI data. We reliably identify white matter tracts linking-the nucleus accumbens and the ventral tegmental area-key subcortical nodes of the mesolimbic reward pathway, and provide reproducible evidence for structural aberrations in these tracts in children with autism spectrum disorder. Further, we show that structural aberrations are accompanied by aberrant functional interactions between nucleus accumbens and ventral tegmental area in response to social stimuli. Crucially, we demonstrate that both structural and functional circuit aberrations in the mesolimbic reward pathway are related to parent-report measures of social interaction impairments in affected children. Our findings, replicated across two independent cohorts, reveal that deficits in the mesolimbic reward pathway contribute to impaired social skills in childhood autism, and provide fundamental insights into neurobiological mechanisms underlying reduced social interest in humans.

Functional connectivity differences in autism during face and car recognition: underconnectivity and atypical age-related changes.

Face recognition abilities improve between adolescence and adulthood over typical development (TD), but plateau in autism, leading to increasing face recognition deficits in autism later in life. Developmental differences between autism and TD may reflect changes between neural systems involved in the development of face encoding and recognition. Here, we focused on whole-brain connectivity with the fusiform face area (FFA), a well-established face-preferential brain region. Older children, adolescents, and adults with and without autism completed the Cambridge Face Memory Test, and a matched car memory test, during fMRI scanning. We then examined task-based functional connectivity between the FFA and the rest of the brain, comparing autism and TD groups during encoding and recognition of face and car stimuli. The autism group exhibited underconnectivity, relative to the TD group, between the FFA and frontal and primary visual cortices, independent of age. Underconnectivity with the medial and rostral lateral prefrontal cortex was face-specific during encoding and recognition, respectively. Conversely, underconnectivity with the L orbitofrontal cortex was evident for both face and car encoding. Atypical age-related changes in connectivity emerged between the FFA and the R temporoparietal junction, and R dorsal striatum for face stimuli only. Similar differences in age-related changes in autism emerged for FFA connectivity with the amygdala across both face and car recognition. Thus, underconnectivity and atypical development of functional connectivity may lead to a less optimal face-processing network in the context of increasing general and social cognitive deficits in autism.

The Default Mode Network in Autism.

Autism spectrum disorder (ASD) is characterized by deficits in social communication and interaction. Since its discovery as a major functional brain system, the default mode network (DMN) has been implicated in a number of psychiatric disorders, including ASD. Here we review converging multimodal evidence for DMN dysfunction in the context of specific components of social cognitive dysfunction in ASD: 'self-referential processing' - the ability to process social information relative to oneself and 'theory of mind' or 'mentalizing' - the ability to infer the mental states such as beliefs, intentions, and emotions of others. We show that altered functional and structural organization of the DMN, and its atypical developmental trajectory, are prominent neurobiological features of ASD. We integrate findings on atypical cytoarchitectonic organization and imbalance in excitatory-inhibitory circuits, which alter local and global brain signaling, to scrutinize putative mechanisms underlying DMN dysfunction in ASD. Our synthesis of the extant literature suggests that aberrancies in key nodes of the DMN and their dynamic functional interactions contribute to atypical integration of information about the self in relation to 'other', as well as impairments in the ability to flexibly attend to socially relevant stimuli. We conclude by highlighting open questions for future research.

Temporal Dynamics and Developmental Maturation of Salience, Default and Central-Executive Network Interactions Revealed by Variational Bayes Hidden Markov Modeling.

Little is currently known about dynamic brain networks involved in high-level cognition and their ontological basis. Here we develop a novel Variational Bayesian Hidden Markov Model (VB-HMM) to investigate dynamic temporal properties of interactions between salience (SN), default mode (DMN), and central executive (CEN) networks-three brain systems that play a critical role in human cognition. In contrast to conventional models, VB-HMM revealed multiple short-lived states characterized by rapid switching and transient connectivity between SN, CEN, and DMN. Furthermore, the three "static" networks occurred in a segregated state only intermittently. Findings were replicated in two adult cohorts from the Human Connectome Project. VB-HMM further revealed immature dynamic interactions between SN, CEN, and DMN in children, characterized by higher mean lifetimes in individual states, reduced switching probability between states and less differentiated connectivity across states. Our computational techniques provide new insights into human brain network dynamics and its maturation with development.

Neural circuits underlying mother's voice perception predict social communication abilities in children.

The human voice is a critical social cue, and listeners are extremely sensitive to the voices in their environment. One of the most salient voices in a child's life is mother's voice: Infants discriminate their mother's voice from the first days of life, and this stimulus is associated with guiding emotional and social function during development. Little is known regarding the functional circuits that are selectively engaged in children by biologically salient voices such as mother's voice or whether this brain activity is related to children's social communication abilities. We used functional MRI to measure brain activity in 24 healthy children (mean age, 10.2 y) while they attended to brief (<1 s) nonsense words produced by their biological mother and two female control voices and explored relationships between speech-evoked neural activity and social function. Compared to female control voices, mother's voice elicited greater activity in primary auditory regions in the midbrain and cortex; voice-selective superior temporal sulcus (STS); the amygdala, which is crucial for processing of affect; nucleus accumbens and orbitofrontal cortex of the reward circuit; anterior insula and cingulate of the salience network; and a subregion of fusiform gyrus associated with face perception. The strength of brain connectivity between voice-selective STS and reward, affective, salience, memory, and face-processing regions during mother's voice perception predicted social communication skills. Our findings provide a novel neurobiological template for investigation of typical social development as well as clinical disorders, such as autism, in which perception of biologically and socially salient voices may be impaired.

Heterogeneous and nonlinear development of human posterior parietal cortex function.

Human cognitive problem solving skills undergo complex experience-dependent changes from childhood to adulthood, yet most neurodevelopmental research has focused on linear changes with age. Here we challenge this limited view, and investigate spatially heterogeneous and nonlinear neurodevelopmental profiles between childhood, adolescence, and young adulthood, focusing on three cytoarchitectonically distinct posterior parietal cortex (PPC) regions implicated in numerical problem solving: intraparietal sulcus (IPS), angular gyrus (AG), and supramarginal gyrus (SMG). Adolescents demonstrated better behavioral performance relative to children, but their performance was equivalent to that of adults. However, all three groups differed significantly in their profile of activation and connectivity across the PPC subdivisions. Activation in bilateral ventral IPS subdivision IPS-hIP1, along with adjoining anterior AG subdivision, AG-PGa, and the posterior SMG subdivision, SMG-PFm, increased linearly with age, whereas the posterior AG subdivision, AG-PGp, was equally deactivated in all three groups. In contrast, the left anterior SMG subdivision, SMG-PF, showed an inverted U-shaped profile across age groups such that adolescents exhibited greater activation than both children and young adults. Critically, greater SMG-PF activation was correlated with task performance only in adolescents. Furthermore, adolescents showed greater task-related functional connectivity of the SMG-PF with ventro-temporal, anterior temporal and prefrontal cortices, relative to both children and adults. These results suggest that nonlinear up-regulation of SMG-PF and its interconnected functional circuits facilitate adult-level performance in adolescents. Our study provides novel insights into heterogeneous age-related maturation of the PPC underlying cognitive skill acquisition, and further demonstrates how anatomically precise analysis of both linear and nonlinear neurofunctional changes with age is necessary for more fully characterizing cognitive development.

Sex differences in cortical volume and gyrification in autism.

BACKGROUND: Male predominance is a prominent feature of autism spectrum disorders (ASD), with a reported male to female ratio of 4:1. Because of the overwhelming focus on males, little is known about the neuroanatomical basis of sex differences in ASD. Investigations of sex differences with adequate sample sizes are critical for improving our understanding of the biological mechanisms underlying ASD in females. METHODS: We leveraged the open-access autism brain imaging data exchange (ABIDE) dataset to obtain structural brain imaging data from 53 females with ASD, who were matched with equivalent samples of males with ASD, and their typically developing (TD) male and female peers. Brain images were processed with FreeSurfer to assess three key features of local cortical morphometry: volume, thickness, and gyrification. A whole-brain approach was used to identify significant effects of sex, diagnosis, and sex-by-diagnosis interaction, using a stringent threshold of p < 0.01 to control for false positives. Stability and power analyses were conducted to guide future research on sex differences in ASD. RESULTS: We detected a main effect of sex in the bilateral superior temporal cortex, driven by greater cortical volume in females compared to males in both the ASD and TD groups. Sex-by-diagnosis interaction was detected in the gyrification of the ventromedial/orbitofrontal prefrontal cortex (vmPFC/OFC). Post-hoc analyses revealed that sex-by-diagnosis interaction was driven by reduced vmPFC/OFC gyrification in males with ASD, compared to females with ASD as well as TD males and females. Finally, stability analyses demonstrated a dramatic drop in the likelihood of observing significant clusters as the sample size decreased, suggesting that previous studies have been largely underpowered. For instance, with a sample of 30 females with ASD (total n = 120), a significant sex-by-diagnosis interaction was only detected in 50 % of the simulated subsamples. CONCLUSIONS: Our results demonstrate that some features of typical sex differences are preserved in the brain of individuals with ASD, while others are not. Sex differences in ASD are associated with cortical regions involved in language and social function, two domains of deficits in the disorder. Stability analyses provide novel quantitative insights into why smaller samples may have previously failed to detect sex differences.

Development and validation of consensus clustering-based framework for brain segmentation using resting fMRI.

BACKGROUND: Clustering methods are increasingly employed to segment brain regions into functional subdivisions using resting-state functional magnetic resonance imaging (rs-fMRI). However, these methods are highly sensitive to the (i) precise algorithms employed, (ii) their initializations, and (iii) metrics used for uncovering the optimal number of clusters from the data. NEW METHOD: To address these issues, we develop a novel consensus clustering evidence accumulation (CC-EAC) framework, which effectively combines multiple clustering methods for segmenting brain regions using rs-fMRI data. Using extensive computer simulations, we examine the performance of widely used clustering algorithms including K-means, hierarchical, and spectral clustering as well as their combinations. We also examine the accuracy and validity of five objective criteria for determining the optimal number of clusters: mutual information, variation of information, modified silhouette, Rand index, and probabilistic Rand index. RESULTS: A CC-EAC framework with a combination of base K-means clustering (KC) and hierarchical clustering (HC) with probabilistic Rand index as the criterion for choosing the optimal number of clusters, accurately uncovered the correct number of clusters from simulated datasets. In experimental rs-fMRI data, these methods reliably detected functional subdivisions of the supplementary motor area, insula, intraparietal sulcus, angular gyrus, and striatum. COMPARISON WITH EXISTING METHODS: Unlike conventional approaches, CC-EAC can accurately determine the optimal number of stable clusters in rs-fMRI data, and is robust to initialization and choice of free parameters. CONCLUSIONS: A novel CC-EAC framework is proposed for segmenting brain regions, by effectively combining multiple clustering methods and identifying optimal stable functional clusters in rs-fMRI data.

Developmental changes in brain function underlying inhibitory control in autism spectrum disorders.

The development of inhibitory control-the ability to suppress inappropriate actions in order to make goal-directed responses-is often impaired in autism spectrum disorders (ASD). In the present study, we examined whether the impairments in inhibitory control evident in ASD reflect-in part-differences in the development of the neural substrates of inhibitory control from adolescence into adulthood. We conducted a functional magnetic resonance imaging (fMRI) study on the anti-saccade task, a probe of inhibitory control, in high-functioning adolescents and adults with ASD compared to a matched group of typically developing (TD) individuals. The ASD group did not show the age-related improvements in behavioral performance from adolescence to adulthood evident in the typical group, consistent with previous behavioral work. The fMRI results indicated that much of the circuitry recruited by the ASD group was similar to the TD group. However, the ASD group demonstrated some unique patterns, including: (a) a failure to recruit the frontal eye field during response preparation in adolescence but comparable recruitment in adulthood; (b) greater recruitment of putamen in adolescence and precuneus in adolescence and adulthood than the TD group; and (c) decreased recruitment in the inferior parietal lobule relative to TD groups. Taken together, these results suggest that brain circuitry underlying inhibitory control develops differently from adolescence to adulthood in ASD. Specifically, there may be relative underdevelopment of brain processes underlying inhibitory control in ASD, which may lead to engagement of subcortical compensatory processes.