Daniel Hillier, leader of the IOB non-human primate platform, just won a Horizon NEURON grant totalling 1.2 million Euro for an amblyopia project.
Congratulations!
The project with the acronym: UnscrAMBLY (stands for Understanding brain circuit dysfunction in amblyopia using large-scale multimodal recordings in a new visuomotor task applied to animal models and patients) aims to exploit the capacity of the brain to predict expected changes in the visual scene caused by a subject’s own motion. The new method they will explore and further develop may also be applicable to other neurodevelopmental disorders, providing a widely useful tool for clinical diagnosis and basic research.
The unmet medical need
Amblyopia (also known as “lazy eye”) is one of the most studied neurodevelopmental vision disorders. The lack of proper treatment can lead to permanently decreased performance in everyday tasks, such as reading, driving or walking. Amblyopia must be diagnosed early and treated promptly because current treatments cannot efficiently recover lost vision beyond the age of 8 years. “Only a small fraction of about 200 million affected patients worldwide, mostly those living in locations with high-quality healthcare and education structures in place, have access to timely and precise diagnosis and long-term support. Elucidating why it is so hard to fully restore vision of amblyopic patients is very challenging,” explains Daniel. “This is motivating us to develop a new, efficient and widely accessible test for diagnosis and treatment monitoring”, he adds.
The project plan
The study - to be carried out in a consortium under leadership of Daniel Hillier with international project partners (see below) - aims to exploit the capacity of the brain to predict expected changes in the visual scene, especially those caused by a subject’s own motion.
“Study participants will pedal forward in a virtual reality corridor, while we non-invasively record their brain activity on the brain surface, plus their eye- and limb motion. We will briefly halt the visual motion at small regions of the scene, and analyze the data. Using machine learning we will determine differences between healthy and amblyopic patients”, says Daniel.
Magnetic resonance imaging could also record deep brain activity, but it requires a fixed body and head for prolonged times and therefore is not applicable to the study. To collect high-resolution data also from deep regions of the brain, the team will use cats and mice as amblyopia models. “Visual function of the cat is very similar to humans. We use functional ultrasound imaging in behaving cats to link activity of deep brain areas to amblyopia. Genetic tools available in mice allow us to test the functional role of brain regions involved in amblyopia in even more detail. This combined method will help us to provide a very robust network view of the origins of amblyopia and serve as a first step to set new and better directions for therapy”, Daniel explains.
The international project partners
The project will be driven forward in Daniel’s labs at IOB, in the Research Centre for Natural Sciences, Institute of Cognitive Neuroscience and Psychology, Hungary, and at the Faculty of Information Technology and Bionics, Pazmany Peter Catholic University, Hungary, in a consortium with project partners from the Babes-Bolyai University, Physics Department, Romania; the Department of Neuroscience KU Leuven, imec and VIB, Belgium; the Institute of Basic Medical Sciences, University of Oslo, Norway, and the Department of Ophthalmology at the Semmelweis University in Hungary.