University of Birmingham > Talks@bham > Applied Mathematics Seminar Series > Elastic jumps on networks - towards a mathematical framework for predicting retinal haemorrhage

## Elastic jumps on networks - towards a mathematical framework for predicting retinal haemorrhageAdd to your list(s) Download to your calendar using vCal - Peter Stewart, University of Glasgow
- Thursday 21 February 2019, 12:00-13:00
- PHYW-LT (117).
If you have a question about this talk, please contact Fabian Spill. The optic nerve is a collection of nerve fibres which connect the photoreceptors in the retina to the brain. This nerve is surrounded by a sheath, which contains a thin layer of cerebrospinal fluid (CSF) at the intracranial pressure. The central retinal artery and vein, which supply the retinal circulation, pass through the centre of the optic nerve as they enter the eye, but about half way back from the globe they deviate and pass through the nerve sheath into the surrounding fatty tissue. Hence, these blood vessels form an interesting point of coupling between the eye and the brain. In this talk I will show how modelling of the flow of CSF along the nerve sheath and the flow of blood in the central retinal artery and vein can provide a route to abrupt pressure changes in the retinal circulation. In particular, I will demonstrate how a large increase in CSF pressure is transmitted into the retinal artery and vein, leading to a spreading shock wave through the retinal circulation and the possible rupture of retinal blood vessels (ie retinal haemorrhages). This talk is part of the Applied Mathematics Seminar Series series. ## This talk is included in these lists:Note that ex-directory lists are not shown. |
## Other listsCond. Mat. seminar Theoretical Physics Journal Club Filling in the blank – I will be ….... in 2050’## Other talksTBC Sylow branching coefficients for symmetric groups Quantum simulations using ultra cold ytterbium Provably Convergent Plug-and-Play Quasi-Newton Methods for Imaging Inverse Problems TBC Modelling uncertainty in image analysis. |