This study will perform a meta-analysis of brain imaging studies (e.g., fMRI, PET, MEG) in individuals with the BAP. The methodology will follow the protocol outlined by Papadatou-Pastou et al. (2023), which adheres to the PRISMA guidelines (Page et al., 2021). Relevant studies will be identified through systematic searches in PubMed, Scopus, and PsycInfo using pre-registered keywords, and selected based on predefined inclusion and exclusion criteria. Analyses will be conducted in R using random-effects models, with activation likelihood estimation used to examine gray matter laterality in BAP participants compared to controls, following Minkova et al. (2017). The study will also assess publication and small-study bias and conduct risk-of-bias evaluations.
This study will investigate cerebral laterality for language as a potential biomarker for the Broad Autism Phenotype (BAP), utilising transcranial Doppler ultrasonography to compare probands, siblings, and controls. Neurophysiological and behavioural tools will be employed. Results will inform improved understanding and potentially early screening for autism and BAP.
This study will assess, for the first time, the external validity of a computerised behavioural laterality battery against fTCD. The battery, developed and validated for reliability by Parker and collaborators at the University of Oxford (Parker et al., 2021), represents state-of-the-art methodology in the field. Its computerised format allows it to be used in clinical settings, with individuals unable to undergo neuroimaging or neurophysiological assessments (due to young age, claustrophobia, or neurodevelopmental challenges), and at scale, either offline (e.g., for large groups such as army recruits) or online for research and screening purposes.
This study will, for the first time, investigate whether computer-based laterality scores (derived from the computerised behavioural laterality battery, developed by Parker et al., [2021]) are associated with autism spectrum quotient (AQ) scores--the gold-standard behavioural measure of ASD traits.
This study will conduct an exome sequencing analysis, led by Prof Silvia Paracchini (one of our collaborators), as part of the “StAndrews_WES_language_laterality” project, which investigates language laterality in neurodevelopmental disorders.