Validation of the structured interview section of the penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT GOASSESS).

Large-scale studies and burdened clinical settings require precise, efficient measures that assess multiple domains of psychopathology. Computerized adaptive tests (CATs) can reduce administration time without compromising data quality. We examined feasibility and validity of an adaptive psychopathology measure, GOASSESS, in a clinical community-based sample (N = 315; ages 18-35) comprising three groups: healthy controls, psychosis, mood/anxiety disorders. Assessment duration was compared between the Full and CAT GOASSESS. External validity was tested by comparing how the CAT and Full versions related to demographic variables, study group, and socioeconomic status. The relationships between scale scores and criteria were statistically compared within a mixed-model framework to account for dependency between relationships. Convergent validity was assessed by comparing scores of the CAT and the Full GOASSESS using Pearson correlations. The CAT GOASSESS reduced interview duration by more than 90 % across study groups and preserved relationships to external criteria and demographic variables as the Full GOASSESS. All CAT GOASSESS scales could replace those of the Full instrument. Overall, the CAT GOASSESS showed acceptable psychometric properties and demonstrated feasibility by markedly reducing assessment time compared to the Full GOASSESS. The adaptive version could be used in large-scale studies or clinical settings for intake screening.

Validation of the cognitive section of the Penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT-CCNB).

BACKGROUND: The Penn Computerized Neurocognitive Battery is an efficient tool for assessing brain-behavior domains, and its efficiency was augmented via computerized adaptive testing (CAT). This battery requires validation in a separate sample to establish psychometric properties. METHODS: In a mixed community/clinical sample of N = 307 18-to-35-year-olds, we tested the relationships of the CAT tests with the full-form tests. We compared discriminability among recruitment groups (psychosis, mood, control) and examined how their scores relate to demographics. CAT-Full relationships were evaluated based on a minimum inter-test correlation of 0.70 or an inter-test correlation within at least 0.10 of the full-form correlation with a previous administration of the full battery. Differences in criterion relationships were tested via mixed models. RESULTS: Most tests (15/17) met the minimum criteria for replacing the full-form with the updated CAT version (mean r = 0.67; range = 0.53-0.80) when compared to relationships of the full-forms with previous administrations of the full-forms (mean r = 0.68; range = 0.50-0.85). Most (16/17) CAT-based relationships with diagnostics and other validity criteria were indistinguishable (interaction p > 0.05) from their full-form counterparts. CONCLUSIONS: The updated CNB shows psychometric properties acceptable for research. The full-forms of some tests should be retained due to insufficient time savings to justify the loss in precision.

Construction of a computerized adaptive test (CAT-CCNB) for efficient neurocognitive and clinical psychopathology assessment.

BACKGROUND: Traditional paper-and-pencil neurocognitive evaluations and semi-structured mental health interviews can take hours to administer and score. Computerized assessment has decreased that burden substantially, and contemporary psychometric tools such as item response theory and computerized adaptive testing (CAT) allow even further abbreviation. NEW METHOD: The goal of this paper was to describe the application of CAT and related methods to the Penn Computerized Neurocognitive Battery (CNB) and a well-validated clinical assessment in order to increase efficiency in assessment and relevant domain coverage. To calibrate item banks for CAT, N = 5053 participants (63% female; mean age 45 years, range 18-80) were collected from across the United States via crowdsourcing, providing item parameters that were then linked to larger item banks and used in individual test construction. Tests not amenable to CAT were abbreviated using complementary short-form methods. RESULTS: The final "CAT-CCNB" battery comprised 21 cognitive tests (compared to 14 in the original) and five adaptive clinical scales (compared to 16 in the original). COMPARISON WITH EXISTING METHODS: This new battery, derived with contemporary psychometric approaches, provides further improvements over existing assessments that use collections of fixed-length tests developed for stand-alone administration. The CAT-CCNB provides an improved version of the CNB that shows promise as a maximally efficient tool for neuropsychiatric assessment. CONCLUSIONS: We anticipate CAT-CCNB will help satisfy the clear need for broad yet efficient measurement of cognitive and clinical domains, facilitating implementation of large-scale, "big science" approaches to data collection, and potential widespread clinical implementation.

Diminished reward responsiveness is associated with lower reward network GluCEST: an ultra-high field glutamate imaging study.

Low reward responsiveness (RR) is associated with poor psychological well-being, psychiatric disorder risk, and psychotropic treatment resistance. Functional MRI studies have reported decreased activity within the brain's reward network in individuals with RR deficits, however the neurochemistry underlying network hypofunction in those with low RR remains unclear. This study employed ultra-high field glutamate chemical exchange saturation transfer (GluCEST) imaging to investigate the hypothesis that glutamatergic deficits within the reward network contribute to low RR. GluCEST images were acquired at 7.0 T from 45 participants (ages 15-29, 30 females) including 15 healthy individuals, 11 with depression, and 19 with psychosis spectrum symptoms. The GluCEST contrast, a measure sensitive to local glutamate concentration, was quantified in a meta-analytically defined reward network comprised of cortical, subcortical, and brainstem regions. Associations between brain GluCEST contrast and Behavioral Activation System Scale RR scores were assessed using multiple linear regressions. Analyses revealed that reward network GluCEST contrast was positively and selectively associated with RR, but not other clinical features. Follow-up investigations identified that this association was driven by the subcortical reward network and network areas that encode the salience of valenced stimuli. We observed no association between RR and the GluCEST contrast within non-reward cortex. This study thus provides new evidence that reward network glutamate levels contribute to individual differences in RR. Decreased reward network excitatory neurotransmission or metabolism may be mechanisms driving reward network hypofunction and RR deficits. These findings provide a framework for understanding the efficacy of glutamate-modulating psychotropics such as ketamine for treating anhedonia.

Leveraging multi-shell diffusion for studies of brain development in youth and young adulthood.

Diffusion weighted imaging (DWI) has advanced our understanding of brain microstructure evolution over development. Recently, the use of multi-shell diffusion imaging sequences has coincided with advances in modeling the diffusion signal, such as Neurite Orientation Dispersion and Density Imaging (NODDI) and Laplacian-regularized Mean Apparent Propagator MRI (MAPL). However, the relative utility of recently-developed diffusion models for understanding brain maturation remains sparsely investigated. Additionally, despite evidence that motion artifact is a major confound for studies of development, the vulnerability of metrics derived from contemporary models to in-scanner motion has not been described. Accordingly, in a sample of 120 youth and young adults (ages 12-30) we evaluated metrics derived from diffusion tensor imaging (DTI), NODDI, and MAPL for associations with age and in-scanner head motion at multiple scales. Specifically, we examined mean white matter values, white matter tracts, white matter voxels, and connections in structural brain networks. Our results revealed that multi-shell diffusion imaging data can be leveraged to robustly characterize neurodevelopment, and demonstrate stronger age effects than equivalent single-shell data. Additionally, MAPL-derived metrics were less sensitive to the confounding effects of head motion. Our findings suggest that multi-shell imaging data and contemporary modeling techniques confer important advantages for studies of neurodevelopment.

Accelerated cortical thinning within structural brain networks is associated with irritability in youth.

Irritability is an important dimension of psychopathology that spans multiple clinical diagnostic categories, yet its relationship to patterns of brain development remains sparsely explored. Here, we examined how transdiagnostic symptoms of irritability relate to the development of structural brain networks. All participants (n = 137, 83 females) completed structural brain imaging with 3 Tesla MRI at two timepoints (mean age at follow-up: 21.1 years, mean inter-scan interval: 5.2 years). Irritability at follow-up was assessed using the Affective Reactivity Index, and cortical thickness was quantified using Advanced Normalization Tools software. Structural covariance networks were delineated using non-negative matrix factorization, a multivariate analysis technique. Both cross-sectional and longitudinal associations with irritability at follow-up were evaluated using generalized additive models with penalized splines. The False Discovery Rate (q < 0.05) was used to correct for multiple comparisons. Cross-sectional analysis of follow-up data revealed that 11 of the 24 covariance networks were associated with irritability, with higher levels of irritability being associated with thinner cortex. Longitudinal analyses further revealed that accelerated cortical thinning within nine networks was related to irritability at follow-up. Effects were particularly prominent in brain regions implicated in emotion regulation, including the orbitofrontal, lateral temporal, and medial temporal cortex. Collectively, these findings suggest that irritability is associated with widespread reductions in cortical thickness and accelerated cortical thinning, particularly within the frontal and temporal cortex. Aberrant structural maturation of regions important for emotional regulation may in part underlie symptoms of irritability.

Using Pharmacological Manipulation and High-precision Radio Telemetry to Study the Spatial Cognition in Free-ranging Animals.

An animal's ability to perceive and learn about its environment plays a key role in many behavioral processes, including navigation, migration, dispersal and foraging. However, the understanding of the role of cognition in the development of navigation strategies and the mechanisms underlying these strategies is limited by the methodological difficulties involved in monitoring, manipulating the cognition of, and tracking wild animals. This study describes a protocol for addressing the role of cognition in navigation that combines pharmacological manipulation of behavior with high-precision radio telemetry. The approach uses scopolamine, a muscarinic acetylcholine receptor antagonist, to manipulate cognitive spatial abilities. Treated animals are then monitored with high frequency and high spatial resolution via remote triangulation. This protocol was applied within a population of Eastern painted turtles (Chrysemys picta) that has inhabited seasonally ephemeral water sources for ~100 years, moving between far-off sources using precise (± 3.5 m), complex (i.e., non-linear with high tortuosity that traverse multiple habitats), and predictable routes learned before 4 years of age. This study showed that the processes used by these turtles are consistent with spatial memory formation and recall. Together, these results are consistent with a role of spatial cognition in complex navigation and highlight the integration of ecological and pharmacological techniques in the study of cognition and navigation.

Turtles outsmart rapid environmental change: The role of cognition in navigation.

Animals inhabiting changing environments show high levels of cognitive plasticity. Cognition may be a means by which animals buffer the impact of environmental change. However, studies examining the evolution of cognition seldom compare populations where change is rapid and selection pressures are strong. We investigated this phenomenon by radiotracking experienced and naïve Eastern painted turtles (Chrysemys picta) as they sought new habitats when their pond was drained. Resident adults repeatedly used specific routes to permanent water sources with exceptional precision, while adults translocated to the site did not. Naïve 1-3 y olds from both populations used the paths taken by resident adults, an ability lost by age 4. Experience did not, however, influence the timing of movement or the latency to begin navigation. This suggests that learning during a critical period may be important for how animals respond to changing environments, highlighting the importance of incorporating cognition into conservation.