Faculty Bibliography

Research in developmental psychology requires sampling at different time points. Accurate depictions of developmental change provide a foundation for further empirical studies and theories about developmental mechanisms. However, overreliance on widely spaced sampling intervals in cross-sectional and longitudinal designs threatens the validity of the enterprise. This article discusses how to sample development in order to accurately discern the shape of developmental change. The ideal solution is daunting: to summarize behavior over 24-hour intervals and collect daily samples over the critical periods of change. We discuss the magnitude of errors due to undersampling, and the risks associated with oversampling. When daily sampling is not feasible, we offer suggestions for sampling methods that can provide preliminary reference points and provisional sketches of the general shape of a developmental trajectory. Denser sampling then can be applied strategically during periods of enhanced variability, inflections in the rate of developmental change, or in relation to key events or processes that may affect the course of change. Despite the challenges of dense repeated sampling, researchers must take seriously the problem of sampling on a developmental time scale if we are to know the true shape of developmental change.

BACKGROUND: Although numerous studies have examined the role of latent predispositions to internalizing and externalizing disorders in the structure of comorbidity among common mental disorders, none examined latent predispositions in predicting development of comorbidity. METHODS: A novel method was used to study the role of latent variables in the development of comorbidity among lifetime DSM-IV disorders in the National Comorbidity Surveys. Broad preliminary findings are briefly presented to describe the method. The method used survival analysis to estimate time-lagged associations among 18 lifetime DSM-IV anxiety, mood, behavior, and substance disorders. A novel estimation approach examined the extent to which these predictive associations could be explained by latent canonical variables representing internalizing and externalizing disorders. RESULTS: Consistently significant positive associations were found between temporally primary and secondary disorders. Within-domain time-lagged associations were generally stronger than between-domain associations. The vast majority of associations were explained by a model that assumed mediating effects of latent internalizing and externalizing variables, although the complexity of this model differed across samples. A number of intriguing residual associations emerged that warrant further investigation. CONCLUSIONS: The good fit of the canonical model suggests that common causal pathways account for most comorbidity among the disorders considered. These common pathways should be the focus of future research on the development of comorbidity. However, the existence of several important residual associations shows that more is involved than simple mediation. The method developed to carry out these analyses provides a unique way to pinpoint these significant residual associations for subsequent focused study.

BACKGROUND: Obsessive-compulsive disorder (OCD) is a common neuropsychiatric disorder that is characterized by recurrent intrusive thoughts, ideas or images and repetitive ritualistic behaviours. Although focal structural and functional abnormalities in specific brain regions have been widely studied in populations with OCD, changes in the functional relations among them remain poorly understood. This study examined OCD-related alterations in functional connectivity patterns in the brain's top-down control network. METHODS: We applied resting-state functional magnetic resonance imaging to investigate the correlation patterns of intrinsic or spontaneous blood oxygen level-dependent signal fluctuations in 18 patients with OCD and 16 healthy controls. The brain control networks were first constructed by thresholding temporal correlation matrices of 39 brain regions associated with top-down control and then analyzed using graph theory-based approaches. RESULTS: Compared with healthy controls, the patients with OCD showed decreased functional connectivity in the posterior temporal regions and increased connectivity in various control regions such as the cingulate, precuneus, thalamus and cerebellum. Furthermore, the brain's control networks in the healthy controls showed small-world architecture (high clustering coefficients and short path lengths), suggesting an optimal balance between modularized and distributed information processing. In contrast, the patients with OCD showed significantly higher local clustering, implying abnormal functional organization in the control network. Further analysis revealed that the changes in network properties occurred in regions of increased functional connectivity strength in patients with OCD. Limitations: The patient group in the present study was heterogeneous in terms of symptom clusters, and most of the patients with OCD were medicated. CONCLUSION: Our preliminary results suggest that the organizational patterns of intrinsic brain activity in the control networks are altered in patients with OCD and thus provide empirical evidence for aberrant functional connectivity in the large-scale brain systems in people with this disorder.

The study's objectives were to assess diagnostic stability of initial autism spectrum disorder (ASD) diagnoses in community settings and identify factors associated with diagnostic instability using data from a national Web-based autism registry. A Cox proportional hazards model was used to assess the relative risk of change in initial ASD diagnosis as a function of demographic characteristics, diagnostic subtype, environmental factors and natural history. Autistic disorder was the most stable initial diagnosis; pervasive developmental disorder-not otherwise specified was the least stable. Additional factors such as diagnosing clinician, region, when in time a child was initially diagnosed, and history of autistic regression also were significantly associated with diagnostic stability in community settings. Findings suggest that the present classification system and other secular factors may be contributing to increasing instability of community-assigned labels of ASD

This study examines the rates of depressive symptoms and service use among caregivers whose children receive treatment for disruptive behavior disorders. Descriptive analyses examined preliminary baseline data from the Family Groups for Urban Youth with Disruptive Behaviors study for 212 caregivers to determine rates of caregiver depressive symptoms and lifetime mental health service use. Findings indicate that caregivers manifest substantially higher rates of depressive symptoms compared to national norms. Of those caregivers with clinically significant depressive symptoms, less than half reported ever receiving mental health services. Findings suggest that greater attention should be paid to identifying and treating caregiver depression among children receiving treatment for disruptive behavior disorders.

In the rat olfactory bulb (OB), fast oscillations of the local field potential (LFP) are observed during the respiratory cycle. Gamma-range oscillations (40-90 Hz) occur at the end of inspiration, followed by beta-range oscillations (15-30 Hz) during exhalation. These oscillations are highly stereotypical, and their frequencies are stable under various conditions. In this study, we investigate the effect of stimulus intensity on activity in the OB. Using a double-cannulation protocol, we showed that although the frequency of the LFP oscillation does depend on the respiratory cycle phase, it is relatively independent of the intensity of odorant stimulation. In contrast, we found that the individual firing rate of mitral OB cells dramatically changed with the intensity of the stimulation. This suggests that OB fast oscillation parameters, particularly frequency, are fully determined by intrinsic OB network parameters. To test this hypothesis, we explored a model of the OB where fast oscillations are generated by the interplay between excitatory mitral/tufted cells and inhibitory granule cells with graded inhibition. We found that our model has two distinct activity regimes depending on the amount of noise. In a low-noise regime, the model displays oscillation in the beta range with a stable frequency across a wide range of excitatory inputs. In a high-noise regime, the model displays oscillatory dynamics with irregular cell discharges and fast oscillations, similar to what is observed during gamma oscillations but without stability of the oscillation frequency with respect to the network external input. Simulations of the full model and theoretical studies of the network's linear response show that the characteristics of the low-noise regime are induced by non-linearities in the model, notably, the saturation of graded inhibition. Finally, we discuss how this model can account for the experimentally observed stability of the oscillatory regimes.