Ben Fulcher
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Lecturer in Brain Dynamics
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About
Ben Fulcher is a Lecturer in Brain Dynamics at the University of Sydney, Australia. His research focuses on brain connectomics, dynamical patterns in fMRI, and analyzing brain responses to stimulation. Recent publications include investigations into community detection methods, the effects of wakefulness versus anesthesia, and the stability of brain dynamics related to meditation.
Recent Grants
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Integrating theory-guided and data-driven approaches for measuring consciousness
Open Date: 2019-12-07
Close Date:
Grant: Close
A dimensional approach to mapping the risk mechanisms of mental illness
Open Date: 2018-01-01
Close Date: 2022-12-31
Grant: Close
From brain maps to mechanisms: modeling the pathophysiology of schizophrenia
Open Date: 2015-01-01
Close Date: 2018-01-01
Articles (23)
The distribution of parent‐reported attention‐deficit/hyperactivity disorder and subclinical autistic traits in children with and without an ADHD diagnosis
Background Autistic traits are often reported to be elevated in children diagnosed with attention‐deficit/hyperactivity disorder (ADHD). However, the distribution of subclinical autistic traits in children with ADHD has not yet been established; knowing this may have important implications for diagnostic and intervention processes. The present study proposes a preliminary model of the distribution of parent‐reported ADHD and subclinical autistic traits in two independent samples of Australian children with and without an ADHD diagnosis. Methods Factor mixture modelling was applied to Autism Quotient and Conners' Parent Rating Scale – Revised responses from parents of Australian children aged 6–15 years who participated in one of two independent studies. Results A 2‐factor, 2‐class factor mixture model with class varying factor variances and intercepts demonstrated the best fit to the data in both discovery and replication samples. The factors corresponded to the latent constructs of ‘autism’ and ‘ADHD’, respectively. Class 1 was characterised by low levels of both ADHD and autistic traits. Class 2 was characterised by high levels of ADHD traits and low‐to‐moderate levels of autistic traits. The classes were largely separated along diagnostic boundaries. The largest effect size for differences between classes on the Autism Quotient was on the Social Communication subscale. Conclusions Our findings support the conceptualisation of ADHD as a continuum, whilst confirming the utility of current categorical diagnostic criteria. Results suggest that subclinical autistic traits, particularly in the social communication domain, are unevenly distributed across children with clinically significant levels of ADHD traits. These traits might be profitably screened for in assessments of children with high ADHD symptoms and may also represent useful targets for intervention.
Year:
2024
Collaborators (14)
Mark A. Bellgrove
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Naotsugu Tsuchiya
MONASH UNIVERSITY
Johannes Bohacek
Assistant Professor
ETH Zürich
Sylvain Baillet
Professor
McGill University
Stuart Oldham
Murdoch Childrens Research Institute
Thomas Andrillon
MONASH UNIVERSITY
Joseph T Lizier
University of Sydney
Bernadette Fitzgibbon
The Australian National University
Leonardo Gollo
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Theodore Satterthwaite
Associate Professor
University of Pennsylvania
Neil Bailey
MONASH UNIVERSITY
Kevin Aquino
MONASH UNIVERSITY
Bradley Voytek
Professor
University of California, San Diego
Natasha Matthews
Lecturer
University of Queensland

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