retinal biomarkers group
We are looking into the eye to understand the brain in conditions affecting cognitive and emotional functioning from ASD, ADHD, anxiety, depression, cerebral visual impairment and vasculopathies.
The group has developed from collaborations in London where we explored visual function in autism spectrum disorder (ASD). These early studies replicated early work of Ed Ritvo, who in 1988 first identified that the retinal responses to light were different in ASD. With the support of Ed, we were able to extend this work and in 2020 we published the first large study that supported using the retina as a biomarker for ASD.
From that original study we also noticed that children with attention deficit hyperactivity disorder (ADHD) also have different responses to light that could help to differentiate between ASD and ADHD.
Now with the power of machine learning and different methods for analyzing the retinal signals from light - we are beginning to develop models that could help classify neurodevelopmental conditions with a retinal biomarker.
We are also exploring retinal changes using structural and functional biomarkers for cerebral ischaemia, cortical visual impairment and peripheral arterial disease.
Group Members
Paul Constable PhD
Visual Electrophysiology
Based at Flinders University, Adelaide, I have supported the research projects with recording electroretinograms (ERGs) in children with and without a neurodevelopmental condition. I have expertise in retinal physiology and working with children on the spectrum
Hugo Posada-Quintero PhD
Visual Electrophysiology
Hugo is based at the University of Connecticut Department of Biomedical Engineering, and is a member of the Biosignal Processing and Wearable Device Lab where he co-ordinates the development of new medical devices for the classification of neurodevelopmental conditions.
Denis Delisle Rodriguez PhD
PhD in Electrical Engineering from the Federal University of Espírito Santo (UFES), Master in Biomedical Engineering from Universidad del Oriente Cuba and graduated in Engineering in Telecommunications and Electronics from Universidad del Oriente Cuba. Acts in development of systems that include biomedical signal processing and pattern recognition through Machine Learning and Deep Learning, especially with brain and myoelectric signals. He also works on the development and construction of signal acquisition prototypes, mobile robotic devices, brain-computer interfaces and human-machine interfaces, cognitive attention training, and increasing verbal and communication skills.
Dorothy Thompson PhD
Senior Bio-Engineer
Consultant Clinical Electrophysiologist. Co-Director, Service provision & Clinical Audit at
the Tony Kriss Visual Electrophysiology Unit,
Great Ormond Street Hospital for Children NHS Foundation Trust. Dr Thompson is a leading expert in paediatric visual electrophysiology and co-ordinated the retinal biomarkers group based in London.
Lynne Loh PhD
Research Assistant
Based at Flinders University, Lynne is an experienced visual electrophysiologist and has a long history of working with paediatric populations. Lynne helps co-ordinate and run the group's studies.
Fernando Marmolejo-Ramos PhD
Statistical Modelling
Fernando Marmolejo-Ramos is a research fellow in human and artificial cognition at the Centre for Change and Complexity in Learning (C3L) at the University of South Australia. Fernando has research interests in embodied cognition (e.g. embodiment of language and emotions) and applied statistics/methodology. Fernando contributes to modelling features for classification of neurodevelopmental disorders.
Marek Brabec PhD
Statistical Modelling
Mikhail Kulyabin PhD
Machine Learning and Signal Analysis
Mikhail is based at the Friedrich-Alexander-UniversitätErlangen-Nürnberg within the Pattern Recognition Laboratory of the Computer Science Division. Mikhail specialises in the application of machine learning to recognise differences in the signal patterns that help with classification of neurodevelopmental disorders.
Aleksei Zhdanov PhD
Machine Learning and Signal Analysis
Prof Nadja Klein PhD
Statistical and Machine Learning, Uncertainty Quantification
Nadja is Professor of Uncertainty Quantification and Statistical Learning at Research Center “Trustworthy Data Science and Security” (University Alliance Ruhr) and Universität Dortmund. Nadja's work is interdisciplinary and has been published in leading outlets in statistics. Methodologically, her interests are in: Bayesian Computational Methods. Bayesian Deep Learning, Machine Learning, Smoothing, Regularization and Shrinkage, Distributional Regression, Network Analysis and Spatial Statistics which in this project she applies and extends towards understanding and modelling of retinal biomarker datasets.
Natalie Mills MBBS, PhD
Academic and Clinical Psychiatrist
Natalie is a child and adolescent Psychiatrist at the University of Adelaide, Discipline of Psychiatry. Her PhD investigated the role of cytokines and inflammatory markers in depression in adolescents. Natalie contributes clinical expertise in developmental disorders and the role of inflammatory pathways in depression and anxiety
Physicist
Nicolas is based at the University National of Colombia in the department of physics where they are working on a prototype ERG device for applications in retinal and neurological disorders.
Physicist
Sam is based at the University National of Colombia in the department of physics where they are working on a prototype ERG device for applications in retinal and neurological disorders.