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Andreotti, C.

Publications and source records attributed to Andreotti, C..

2 recordsLinked to original sources

Associations between Processing Speed and Psychopathology in a Transdiagnostic, Pediatric Sample

ObjectiveThe present study sought to examine the relationships between processing speed (PS), mental health disorders, and learning disorders. Prior work has tended to explore relationships between PS deficits and individual diagnoses (i.e., anxiety, autism, ADHD, depressive) in isolation of one another, often relying on relatively modest sample sizes. In contrast, the present work simultaneously investigated associations between PS deficits and these diagnoses, along with specific learning disabilities (i.e., reading, math), in a large-scale, transdiagnostic, community self-referred sample.\n\nMethodA total of 843 children, ages 8-16 were included from the Healthy Brain Network (HBN) Biobank. Given the presence of four PS tasks in HBN, principal component analysis (PCA) was employed to create a composite measure that represented the shared variance of the four PS tasks, referred to as PC1. Intraclass correlation coefficient (ICC) between the four PS measures, as well as PC1, were calculated to assess reliability. We then used multiple linear regression models to assess specific relationships between PS deficits and psychiatric diagnoses.\n\nResultsICCs were moderate between WISC-V tasks (0.663), and relatively modest between NIH Toolbox Pattern Comparison and other PS scales (0.14-0.27). Regression analyses revealed specific significant relationships between PS and reading and math disabilities, ADHD-inattentive type (ADHD-I), and ADHD-combined type (ADHD-C). Secondary analyses accounting for inattention dimensionally diminished associations with ADHD-C, but not ADHD-I or specific learning disability subtypes. The present study did not find a significant relationship with Autism Spectrum Disorder after accounting for inattentive symptoms. Consistent with prior work, demographic variables, including sex, socioeconomic status, and motor control exhibited independent relationships with PC1 as well.\n\nDiscussionThis study provided a comprehensive examination of PS, mental health disorders, and learning disabilities through a transdiagnostic approach. Implications for understanding how PS interacts with a highly heterogeneous childhood sample, as well as the need for increased focus on detection of affected populations are discussed.

developmental biology↗

The Healthy Brain Network Biobank: An open resource for transdiagnostic research in pediatric mental health and learning disorders

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics, and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n = 664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

neuroscience↗