Faculty Bibliography

OBJECTIVE: We examined the perceived impact of child anxiety disorders on family functioning, because such impact is a key predictor of mental health service receipt. In addition, we examined the relative impact of preschool anxiety compared to that of other early childhood disorders, and whether this impact persisted after accounting for the effects of comorbidity, or varied by child age and sex. METHOD: Drawing from a pediatric primary-care clinic and oversampling for children at risk for anxiety, 917 parents of preschoolers (aged 2-5 years) completed a diagnostic interview and reported on child psychiatric symptom impact on family finances, relationships, activities, and well-being. RESULTS: After accounting for comorbid disorders, families of children with anxiety were 3.5 times more likely to report a negative impact of their child's behavior on the family relative to nondisordered children. Generalized and separation anxiety had an impact on family functioning similar to that of attention-deficit/hyperactivity disorder and disruptive disorders. There was a significant family impact for girls with social phobia, whereas there was no impact for boys. CONCLUSIONS: Preschool anxiety has a significant, unique impact on family functioning, particularly parental adjustment, highlighting the family impairment linked with early anxiety, and the need for further research on barriers to care for these disorders.

OBJECTIVE: As initial episode type can predict later morbidity in bipolar disorder, we tested the hypothesis that clinical antecedents might predict initial episode types. METHOD: We studied 263 first-episode, adult, DSM-IV-TR type I bipolar disorder (BD-I) subjects within the McLean-Harvard-International First-Episode Project. Based on blinded assessments of antecedents from SCID examinations and clinical records, we compared first lifetime manic vs. other (mixed, depressive, or non-affective) major psychotic episodes. RESULTS: We identified 32 antecedents arising at early, intermediate or later times, starting 12.3 +/- 10.7 years prior to first lifetime major psychotic episodes. Based on multivariate modeling, antecedents associated significantly and independently with other (n = 113) more than manic (n = 150) first lifetime major psychotic episodes ranked by odds ratio: more early attentional disturbances, more late depression, more early perplexity, more detoxification, more early unstable mixed affects, more antidepressants, more early dysphoria, more intermediate depression, more early impulsivity, more late anhedonia, longer early-to-intermediate intervals, more intermediate substance abuse, more family history of major depression, and younger at earliest antecedents. Antecedents selectively preceding manic more than other first psychotic episodes included more late behavioral problems and more risk of familial BD-I. CONCLUSION: Clinical antecedents in adult, BD-I patients, beginning a decade before first major episodes and progressing through sequential stages were dissimilar in manic vs. other first psychotic episodes.

The target article argues that developmental processes are key to understanding the mirror neuron system, yet neglects several bodies of developmental research that are informative for doing so. Infants' actions and action understanding are structured by goals, and the former lends structure to the latter. Evaluating the origins and functions of mirror neurons depends on integrating investigations of neural, social-cognitive and motor development.

Medical imaging studies increasingly use longitudinal images of individual subjects in order to follow-up changes due to development, degeneration, disease progression or efficacy of therapeutic intervention. Repeated image data of individuals are highly correlated, and the strong causality of information over time lead to the development of procedures for joint segmentation of the series of scans, called 4D segmentation. A main aim was improved consistency of quantitative analysis, most often solved via patient-specific atlases. Challenging open problems are contrast changes and occurance of subclasses within tissue as observed in multimodal MRI of infant development, neurodegeneration and disease. This paper proposes a new 4D segmentation framework that enforces continuous dynamic changes of tissue contrast patterns over time as observed in such data. Moreover, our model includes the capability to segment different contrast patterns within a specific tissue class, for example as seen in myelinated and unmyelinated white matter regions in early brain development. Proof of concept is shown with validation on synthetic image data and with 4D segmentation of longitudinal, multimodal pediatric MRI taken at 6, 12 and 24 months of age, but the methodology is generic w.r.t. different application domains using serial imaging.

Post-acquisition motion correction is widely performed in diffusion-weighted imaging (DWI) to guarantee voxel-wise correspondence between DWIs. Whereas this is primarily motivated to save as many scans as possible if corrupted by motion, users do not fully understand the consequences of different types of interpolation schemes on the final analysis. Nonetheless, interpolation might increase the partial volume effect while not preserving the volume of the diffusion profile, whereas excluding poor DWIs may affect the ability to resolve crossing fibers especially with small separation angles. In this paper, we investigate the effect of interpolating diffusion measurements as well as the elimination of bad directions on the reconstructed fiber orientation diffusion functions and on the estimated fiber orientations. We demonstrate such an effect on synthetic and real HARDI datasets. Our experiments demonstrate that the effect of interpolation is more significant with small fibers separation angles where the exclusion of motion-corrupted directions decreases the ability to resolve such crossing fibers.

Temporal modeling frameworks often operate on scalar variables by summarizing data at initial stages as statistical summaries of the underlying distributions. For instance, DTI analysis often employs summary statistics, like mean, for regions of interest and properties along fiber tracts for population studies and hypothesis testing. This reduction via discarding of variability information may introduce significant errors which propagate through the procedures. We propose a novel framework which uses distribution-valued variables to retain and utilize the local variability information. Classic linear regression is adapted to employ these variables for model estimation. The increased stability and reliability of our proposed method when compared with regression using single-valued statistical summaries, is demonstrated in a validation experiment with synthetic data. Our driving application is the modeling of age-related changes along DTI white matter tracts. Results are shown for the spatiotemporal population trajectory of genu tract estimated from 45 healthy infants and compared with a Krabbe's patient.

4D pathological anatomy modeling is key to understanding complex pathological brain images. It is a challenging problem due to the difficulties in detecting multiple appearing and disappearing lesions across time points and estimating dynamic changes and deformations between them. We propose a novel semi-supervised method, called 4D active cut, for lesion recognition and deformation estimation. Existing interactive segmentation methods passively wait for user to refine the segmentations which is a difficult task in 3D images that change over time. 4D active cut instead actively selects candidate regions for querying the user, and obtains the most informative user feedback. A user simply answers 'yes' or 'no' to a candidate object without having to refine the segmentation slice by slice. Compared to single-object detection of the existing methods, our method also detects multiple lesions with spatial coherence using Markov random fields constraints. Results show improvement on the lesion detection, which subsequently improves deformation estimation.

A variety of regression schemes have been proposed on images or shapes, although available methods do not handle them jointly. In this paper, we present a framework for joint image and shape regression which incorporates images as well as anatomical shape information in a consistent manner. Evolution is described by a generative model that is the analog of linear regression, which is fully characterized by baseline images and shapes (intercept) and initial momenta vectors (slope). Further, our framework adopts a control point parameterization of deformations, where the dimensionality of the deformation is determined by the complexity of anatomical changes in time rather than the sampling of the image and/or the geometric data. We derive a gradient descent algorithm which simultaneously estimates baseline images and shapes, location of control points, and momenta. Experiments on real medical data demonstrate that our framework effectively combines image and shape information, resulting in improved modeling of 4D (3D space + time) trajectories.

Behavioral inhibition (BI), a temperament characterized by vigilance to novelty, sensitivity to approach-withdrawal cues and social reticence in childhood, is associated with risk for anxiety in adolescence. Independent studies link reward hyper-responsivity to BI, adolescent anxiety and dopamine gene variants. This exploratory study extends these observations by examining the impact of DRD4 genotype and reward hyper-responsivity on the BI-anxiety link. Adolescents (N = 78) completed a monetary incentive delay task in the fMRI environment. Participants were characterized based on a continuous score of BI and the 7-repeat allele (7R+) of the DRD4 functional polymorphism. Parent-report and self-report measures of anxiety were also collected. Across the entire sample, striatal activation increased systematically with increases in the magnitude of anticipated monetary gains and losses. DRD4 status moderated the relation between BI and activation in the caudate nucleus. Childhood BI was associated with parent report of adolescent anxiety among 7R+ participants with elevated levels of striatal response to incentive cues. DRD4 genotype influenced the relations among neural response to incentives, early childhood BI and anxiety. The findings help refine our understanding of the role reward-related brain systems play in the emergence of anxiety in temperamentally at-risk individuals, building a foundation for future larger scale studies.