Dataset Information

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

ABSTRACT:

Introduction

High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points.

Methods

A sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels.

Results

Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model included cerebellum, sensory-motor and fronto-limbic areas.

Conclusions

The combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.

SUBMITTER: Portugal LC

PROVIDER: S-EPMC4701457 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

Portugal Liana C L LC Rosa Maria João MJ Rao Anil A Bebko Genna G Bertocci Michele A MA Hinze Amanda K AK Bonar Lisa L Almeida Jorge R C JR Perlman Susan B SB Versace Amelia A Schirda Claudiu C Travis Michael M Gill Mary Kay MK Demeter Christine C Diwadkar Vaibhav A VA Ciuffetelli Gary G Rodriguez Eric E Forbes Erika E EE Sunshine Jeffrey L JL Holland Scott K SK Kowatch Robert A RA Birmaher Boris B Axelson David D Horwitz Sarah M SM Arnold Eugene L EL Fristad Mary A MA Youngstrom Eric A EA Findling Robert L RL Pereira Mirtes M Oliveira Leticia L Phillips Mary L ML Mourao-Miranda Janaina J

PloS one 20160105 1

<h4>Introduction</h4>High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine w ...[more]

PMID: 26731403

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Project description:IMPORTANCE:Psychiatric disorders in youth characterized by behavioral and emotional dysregulation are often comorbid and difficult to distinguish. An alternative approach to conceptualizing these disorders is to move toward a diagnostic system based on underlying pathophysiologic processes that may cut across conventionally defined diagnoses. Neuroimaging techniques have potentials for the identification of these processes. OBJECTIVE:To determine whether diffusion imaging, a neuroimaging technique examining white matter (WM) structure, can identify neural correlates of emotional dysregulation in a sample of youth with different psychiatric disorders characterized by behavioral and emotional dysregulation. DESIGN, SETTING, AND PARTICIPANTS:Using global probabilistic tractography, we examined relationships between WM structure in key tracts in emotional regulation circuitry (ie, cingulum, uncinate fasciculus, and forceps minor) and (1) broader diagnostic categories of behavioral and emotional dysregulation disorders (DDs) and (2) symptom dimensions cutting across conventional diagnoses in 120 youth with behavioral and/or emotional DDs, a referred sample of the Longitudinal Assessment of Manic Symptoms (LAM) study. Thirty age- and sex-matched typically developing youth (control participants) were included. Multivariate multiple regression models were used. The study was conducted from July 1, 2010, to February 28, 2014. MAIN OUTCOMES AND MEASURES:Fractional anisotropy as well as axial and radial diffusivity were estimated and imported into a well-established statistical package. We hypothesized that (1) youth with emotional DDs and those with both behavioral and emotional DDs would show significantly lower fractional anisotropy compared with youth with behavioral DDs in these WM tracts and (2) that there would be significant inverse relationships between dimensional measures of affective symptom severity and fractional anisotropy in these tracts across all participants. RESULTS:Multivariate multiple regression analyses revealed decreased fractional anisotropy and decreased axial diffusivity within the uncinate fasciculus in youth with emotional DDs vs those with behavioral DDs, those with both DDs, and the controls (F6,160?=?2.4; P?=?.032; all pairwise comparisons, P?<?.002). In the same model, greater severity of manic symptoms was positively associated with higher fractional anisotropy across all affected youth (F3,85?=?2.8; P?=?.044). CONCLUSIONS AND RELEVANCE:These findings suggest that abnormal uncinate fasciculus and cingulum WM structure may underlie emotional, but not behavioral, dysregulation in pediatric psychiatric disorders and that a different neural mechanism may exist for comorbid emotional and behavioral DDs.

Project description:The continuum view of the psychosis spectrum (PS) implies that, in population-based samples, PS symptoms should be associated with neural abnormalities similar to those found in help-seeking clinical risk individuals and in schizophrenia. To our knowledge, functional neuroimaging has not previously been applied in large population-based PS samples and can help us understand the neural architecture of psychosis more broadly and identify brain phenotypes beyond symptoms that are associated with the extended psychosis phenotype.To examine the categorical and dimensional relationships of PS symptoms to prefrontal hypoactivation during working memory and to amygdala hyperactivation during threat emotion processing.The Philadelphia Neurodevelopmental Cohort is a genotyped, prospectively accrued, population-based sample of almost 10,000 youths who received a structured psychiatric evaluation and a computerized neurocognitive battery. The study was conducted at an academic and children's hospital health care network, between November 1, 2009 to November 30, 2011. A subsample of 1445 youths underwent neuroimaging, including functional magnetic resonance imaging tasks examined herein. Participants were youth aged 11 to 22 years old identified through structured interview as having PS features (PS group) (n = 260) and typically developing (TD) comparison youth without significant psychopathology (TD group) (n = 220).Two functional magnetic resonance imaging paradigms were used: a fractal n-back working memory task probing executive system function and an emotion identification task probing amygdala responses to threatening faces.In the n-back task, working memory evoked lower activation in the PS group than the TD group throughout the executive control circuitry, including dorsolateral prefrontal cortex (cluster-corrected P <?.05). Within the PS group, dorsolateral prefrontal cortex activation correlated with cognitive deficits (r =?.32, P <?.001), but no correlation was found with positive symptom severity. During emotion identification, PS demonstrated elevated responses to threatening facial expressions in amygdala, as well as left fusiform cortex and right middle frontal gyrus (cluster-corrected P <?.05). The response in the amygdala correlated with positive symptom severity (r =?.16, P =?.01) but not with cognitive deficits.The pattern of functional abnormalities observed in the PS group is similar to that previously found in schizophrenia and help-seeking risk samples. Specific circuit dysfunction during cognitive and emotion-processing tasks is present early in the development of psychopathology and herein could not be attributed to chronic illness or medication confounds. Hypoactivation in executive circuitry and limbic hyperactivation to threat could reflect partly independent risk factors for PS symptoms, with the former relating to cognitive deficits that increase the risk for developing psychotic symptoms and the latter contributing directly to positive psychotic symptoms.

Project description:BackgroundTo investigate ethnic differences in the protective effects of family income against youth social, emotional, and behavioral problems in the US. As proposed by the Marginalization-related Diminished Returns (MDRs), family income may generate fewer tangible outcomes for ethnic minority compared to NHW families. Our existing knowledge is minimal about diminished returns of family income on parental reports of youth social, emotional, and behavioral outcomes.AimTo compare ethnic groups for the effects of family income on parental reports of youth social, emotional, and behavioral problems.Materials and methodsIn this cross-sectional study, data from wave 1 of the Adolescent Brain Cognitive Development (ABCD) study were included. The ABCD, an ongoing national cohort of American youth brain development, included 10,762 American youth between ages 8 and 11 years old. The independent variable was family income. The primary outcomes were 1) anxious and depressed mood, 2) withdrawn and depressed affect, 3) somatic complaints, 4) social and interpersonal problems, 5) thought problems, 6) rule-breaking behaviors, 7) attention problems, and 8) violent and aggressive behaviors. These outcomes were generated based on parent-reported behavioral problems measured using the Child Behavior Checklist (CBCL).ResultsOverall, high family income was associated with lower levels of parental reports of youth social, emotional, and behavioral problems across all domains (p <0.05 for all beta coefficients across multivariable regression models). Ethnicity showed statistically significant interactions with family income on youth fewer social, emotional, and behavioral problems (all domains), net of all confounders (p <0.05 for all beta coefficients that reflected interaction terms across multivariable regression models), indicating smaller tangible gains from their family income for NHB and HW compared to NHW youth.ConclusionThe protective effects of family income against behavioral problems are systematically diminished for HW and NHB youth compared to NHW youth. To minimize the ethnic gap in youth social, behavioral, and emotional problems, diminished returns of family income should be addressed. There is a need for programs and interventions that equalize not only SES but also the marginal returns of SES for ethnic groups. Such efforts require addressing structural and societal barriers that hinder HW and NHB families from translating their SES resources into tangible outcomes. There is a need for studies that can minimize MDRs for NHB and HW families. Thus, SES can similarly secure tangible outcomes in the presence of SES resources.

Dataset Information

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

Introduction

Methods

Results

Conclusions

Publications

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

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