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1.
PLoS One ; 12(7): e0180221, 2017.
Article in English | MEDLINE | ID: mdl-28683115

ABSTRACT

Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy regulation in youth. Recent studies indicate that machine learning techniques can help elucidate the role of neuroimaging measures in classifying individual subjects by specific symptom trajectory. Cortical thickness measures were extracted in sixty-eight anatomical regions covering the entire brain in 115 participants from the Longitudinal Assessment of Manic Symptoms (LAMS) study and 31 healthy comparison youth (12.5 y/o;-Male/Female = 15/16;-IQ = 104;-Right/Left handedness = 24/5). Using a combination of trajectories analyses, surface reconstruction, and machine learning techniques, the present study aims to identify the extent to which measures of cortical thickness can accurately distinguish youth with higher (n = 18) from those with lower (n = 34) trajectories of manic-like behaviors in a large sample of LAMS youth (n = 115; 13.6 y/o; M/F = 68/47, IQ = 100.1, R/L = 108/7). Machine learning analyses revealed that widespread cortical thickening in portions of the left dorsolateral prefrontal cortex, right inferior and middle temporal gyrus, bilateral precuneus, and bilateral paracentral gyri and cortical thinning in portions of the right dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, and right parahippocampal gyrus accurately differentiate (Area Under Curve = 0.89;p = 0.03) youth with different (higher vs lower) trajectories of positive mood and energy dysregulation over a period up to 5years, as measured by the Parent General Behavior Inventory-10 Item Mania Scale. Our findings suggest that specific patterns of cortical thickness may reflect transdiagnostic neural mechanisms associated with different temporal trajectories of positive mood and energy dysregulation in youth. This approach has potential to identify patterns of neural markers of future clinical course.


Subject(s)
Bipolar Disorder/diagnostic imaging , Cerebral Cortex/diagnostic imaging , Image Interpretation, Computer-Assisted , Machine Learning , Prefrontal Cortex/diagnostic imaging , Temporal Lobe/diagnostic imaging , Adolescent , Affect , Bipolar Disorder/pathology , Bipolar Disorder/physiopathology , Case-Control Studies , Cerebral Cortex/pathology , Cerebral Cortex/physiopathology , Child , Female , Humans , Longitudinal Studies , Magnetic Resonance Imaging/statistics & numerical data , Male , Neuroimaging/statistics & numerical data , Parahippocampal Gyrus/diagnostic imaging , Parahippocampal Gyrus/pathology , Parahippocampal Gyrus/physiopathology , Parietal Lobe/diagnostic imaging , Parietal Lobe/pathology , Parietal Lobe/physiopathology , Prefrontal Cortex/pathology , Prefrontal Cortex/physiopathology , Temporal Lobe/pathology , Temporal Lobe/physiopathology
2.
Article in English | MEDLINE | ID: mdl-28480336

ABSTRACT

BACKGROUND: Changes in neural circuitry function may be associated with longitudinal changes in psychiatric symptom severity. Identification of these relationships may aid in elucidating the neural basis of psychiatric symptom evolution over time. We aimed to distinguish these relationships using data from the Longitudinal Assessment of Manic Symptoms (LAMS) cohort. METHODS: Forty-one youth completed two study visits (mean=21.3 months). Elastic-net regression (Multiple response Gaussian family) identified emotional regulation neural circuitry that changed in association with changes in depression, mania, anxiety, affect lability, and positive mood and energy dysregulation, accounting for clinical and demographic variables. RESULTS: Non-zero coefficients between change in the above symptom measures and change in activity over the inter-scan interval were identified in right amygdala and left ventrolateral prefrontal cortex. Differing patterns of neural activity change were associated with changes in each of the above symptoms over time. Specifically, from Scan1 to Scan2, worsening affective lability and depression severity were associated with increased right amygdala and left ventrolateral prefrontal cortical activity. Worsening anxiety and positive mood and energy dysregulation were associated with decreased right amygdala and increased left ventrolateral prefrontal cortical activity. Worsening mania was associated with increased right amygdala and decreased left ventrolateral prefrontal cortical activity. These changes in neural activity between scans accounted for 13.6% of the variance; that is 25% of the total explained variance (39.6%) in these measures. CONCLUSIONS: Distinct neural mechanisms underlie changes in different mood and anxiety symptoms overtime.

3.
Brain ; 138(Pt 9): 2777-90, 2015 Sep.
Article in English | MEDLINE | ID: mdl-26112339

ABSTRACT

This study aimed to identify neuroimaging measures associated with risk for, or protection against, bipolar disorder by comparing youth offspring of parents with bipolar disorder versus youth offspring of non-bipolar parents versus offspring of healthy parents in (i) the magnitude of activation within emotional face processing circuitry; and (ii) functional connectivity between this circuitry and frontal emotion regulation regions. The study was conducted at the University of Pittsburgh Medical Centre. Participants included 29 offspring of parents with bipolar disorder (mean age = 13.8 years; 14 females), 29 offspring of non-bipolar parents (mean age = 13.8 years; 12 females) and 23 healthy controls (mean age = 13.7 years; 11 females). Participants were scanned during implicit processing of emerging happy, sad, fearful and angry faces and shapes. The activation analyses revealed greater right amygdala activation to emotional faces versus shapes in offspring of parents with bipolar disorder and offspring of non-bipolar parents than healthy controls. Given that abnormally increased amygdala activation during emotion processing characterized offspring of both patient groups, and that abnormally increased amygdala activation has often been reported in individuals with already developed bipolar disorder and those with major depressive disorder, these neuroimaging findings may represent markers of increased risk for affective disorders in general. The analysis of psychophysiological interaction revealed that offspring of parents with bipolar disorder showed significantly more negative right amygdala-anterior cingulate cortex functional connectivity to emotional faces versus shapes, but significantly more positive right amygdala-left ventrolateral prefrontal cortex functional connectivity to happy faces (all P-values corrected for multiple tests) than offspring of non-bipolar parents and healthy controls. Taken together with findings of increased amygdala-ventrolateral prefrontal cortex functional connectivity, and decreased amygdala-anterior cingulate cortex functional connectivity previously shown in individuals with bipolar disorder, these connectivity patterns in offspring of parents with bipolar disorder may be risk markers for, rather than markers conferring protection against, bipolar disorder in youth. The patterns of activation and functional connectivity remained unchanged after removing medicated participants and those with current psychopathology from analyses. This is the first study to demonstrate that abnormal functional connectivity patterns within face emotion processing circuitry distinguish offspring of parents with bipolar disorder from those of non-bipolar parents and healthy controls.


Subject(s)
Amygdala/blood supply , Bipolar Disorder/pathology , Child of Impaired Parents , Facial Expression , Neural Pathways/blood supply , Prefrontal Cortex/blood supply , Adolescent , Amygdala/pathology , Brain Mapping , Child , Child of Impaired Parents/psychology , Female , Humans , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Male , Oxygen/blood , Parents , Pattern Recognition, Visual , Photic Stimulation , Prefrontal Cortex/pathology , Psychiatric Status Rating Scales
4.
JAMA Psychiatry ; 72(4): 367-76, 2015 Apr.
Article in English | MEDLINE | ID: mdl-25715064

ABSTRACT

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.


Subject(s)
Affective Symptoms/pathology , Behavioral Symptoms/pathology , Brain/pathology , Gyrus Cinguli/pathology , White Matter/pathology , Adolescent , Affective Symptoms/complications , Anisotropy , Behavioral Symptoms/complications , Case-Control Studies , Diffusion Tensor Imaging , Female , Humans , Male
5.
Psychiatry Res ; 231(1): 77-86, 2015 Jan 30.
Article in English | MEDLINE | ID: mdl-25433424

ABSTRACT

The Research Domain Criteria (RDoC) adopts a dimensional approach for examining pathophysiological processes underlying categorically defined psychiatric diagnoses. We used this framework to examine relationships among symptom dimensions, diagnostic categories, and resting state connectivity in behaviorally and emotionally dysregulated youth selected from the Longitudinal Assessment of Manic Symptoms study (n=42) and healthy control youth (n=18). Region of interest analyses examined relationships among resting state connectivity, symptom dimensions (behavioral and emotional dysregulation measured with the Parent General Behavior Inventory-10 Item Mania Scale [PGBI-10M]; dimensional severity measures of mania, depression, anxiety), and diagnostic categories (Bipolar Spectrum Disorders, Attention Deficit Hyperactivity Disorder, Anxiety Disorders, and Disruptive Behavior Disorders). After adjusting for demographic variables, two dimensional measures showed significant inverse relationships with resting state connectivity, regardless of diagnosis: 1) PGBI-10M with amygdala-left posterior insula/bilateral putamen; and 2) depressive symptoms with amygdala-right posterior insula connectivity. Diagnostic categories showed no significant relationships with resting state connectivity. Resting state connectivity between amygdala and posterior insula decreased with increasing severity of behavioral and emotional dysregulation and depression; this suggests an intrinsic functional uncoupling of key neural regions supporting emotion processing and regulation. These findings support the RDoC dimensional approach for characterizing pathophysiologic processes that cut across different psychiatric disorders.


Subject(s)
Amygdala/physiopathology , Bipolar Disorder/physiopathology , Emotions/physiology , Magnetic Resonance Imaging/methods , Adolescent , Anxiety/physiopathology , Anxiety Disorders/physiopathology , Attention Deficit and Disruptive Behavior Disorders/physiopathology , Case-Control Studies , Depression/physiopathology , Depressive Disorder/physiopathology , Female , Functional Neuroimaging/methods , Humans , Longitudinal Studies , Male , Personality Inventory , Young Adult
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