Your browser doesn't support javascript.
loading
Exploring neural heterogeneity in inattention and hyperactivity.
Zdorovtsova, Natalia; Jones, Jonathan; Akarca, Danyal; Benhamou, Elia; Astle, Duncan E.
Afiliación
  • Zdorovtsova N; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK. Electronic address: natalia.zdorovtsova@mrc-cbu.cam.ac.uk.
  • Jones J; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
  • Akarca D; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
  • Benhamou E; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
  • The Calm Team; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
  • Astle DE; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK; Department of Psychiatry, University of Cambridge, Cambridge, UK.
Cortex ; 164: 90-111, 2023 07.
Article en En | MEDLINE | ID: mdl-37207412
Inattention and hyperactivity are cardinal symptoms of Attention Deficit Hyperactivity Disorder (ADHD). These characteristics have also been observed across a range of other neurodevelopmental conditions, such as autism and dyspraxia, suggesting that they might best be studied across diagnostic categories. Here, we evaluated the associations between inattention and hyperactivity behaviours and features of the structural brain network (connectome) in a large transdiagnostic sample of children (Centre for Attention, Learning, and Memory; n = 383). In our sample, we found that a single latent factor explains 77.6% of variance in scores across multiple questionnaires measuring inattention and hyperactivity. Partial Least-Squares (PLS) regression revealed that variability in this latent factor could not be explained by a linear component representing nodewise properties of connectomes. We then investigated the type and extent of neural heterogeneity in a subset of our sample with clinically-elevated levels of inattention and hyperactivity. Multidimensional scaling combined with k-means clustering revealed two neural subtypes in children with elevated levels of inattention and hyperactivity (n = 232), differentiated primarily by nodal communicability-a measure which demarcates the extent to which neural signals propagate through specific brain regions. These different clusters had similar behavioural profiles, which included high levels of inattention and hyperactivity. However, one of the clusters scored higher on multiple cognitive assessment measures of executive function. We conclude that inattention and hyperactivity are so common in children with neurodevelopmental difficulties because they emerge through multiple different trajectories of brain development. In our own data, we can identify two of these possible trajectories, which are reflected by measures of structural brain network topology and cognition.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Trastorno por Déficit de Atención con Hiperactividad / Conectoma Tipo de estudio: Prognostic_studies Límite: Child / Humans Idioma: En Revista: Cortex Año: 2023 Tipo del documento: Article Pais de publicación: Italia
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Trastorno por Déficit de Atención con Hiperactividad / Conectoma Tipo de estudio: Prognostic_studies Límite: Child / Humans Idioma: En Revista: Cortex Año: 2023 Tipo del documento: Article Pais de publicación: Italia