Neurocognitive and fMRI Correlates of ADHD in Autism
Research type
Research Study
Full title
Neurocognitive and Functional MRI Correlates of Attention Deficit Hyperactivity Symptoms in Autism Spectrum Disorders
IRAS ID
119190
Contact name
Steve Lukito
Contact email
Sponsor organisation
King's College London
Research summary
Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are two different childhood-onset disorders that have life-long consequences. The two disorders co-occur at a rate substantially higher than chance. The reasons for this are unknown although twin studies suggest that the two disorders share common genetic influences, as well as disorder-specific ones. This study is conducted as a part of a longitudinal investigation on a cohort (Special Needs and Autism Project - SNAP) that has been followed since the age of 12 years and now in their early 20s, a significant proportion of whom had co-occurring diagnosis of ADHD. From this cohort two groups of participants (ASD only and ASD+ADHD) are formed. This application is written concerning the recruitment of three further participant groups: participants with ADHD, healthy control participants, and participants with ASD from the UK-based EU-AIMS community cohort to enable simultaneous comparisons of all four groups. We employ several neurocognitive tasks in- and out-of Magnetic Resonance Imaging (MRI) scanner to study the behavioural performance and neural activation of the participants during neurocognitive tasks. Performance on such tasks are indicators for the participants capacity for understanding others’ mind (i.e., “Theory of Mind“) and for regulating their thought processes (i.e., “Executive Function“). We will also conduct non-functional MRI scans to investigate brain structure and connectivity. Our goal is, firstly, to compare the neurocognitive tasks performance, structural, and functional images of the brain between groups. Secondly, we will classify the structural and functional MRI data into the diagnostic groups using a multivariate machine-learning approach that has been shown to distinguish ADHD, ASD, and healthy control with reasonable accuracy. We will investigate whether this method can set apart the ADHD+ASD from the pure ADHD and ASD groups in a similar manner.
REC name
London - Camberwell St Giles Research Ethics Committee
REC reference
13/LO/0373
Date of REC Opinion
11 Jun 2013
REC opinion
Further Information Favourable Opinion