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Mapping cell density in the human eye

14.12.2020

In a nutshell: A new map of cell density in the human retina will help researchers better understand visual perception.

View Paper Abstract

Mapping cell density in the human eye

Visual processing starts in the retina where photoreceptor cells – the rods and cones – capture light and convert it into electrical signals. Depending on the type of visual information contained in these signals, they are transmitted to the brain along different pathways.

The midget-parvocellular (P) pathway is involved in red-green colour vision. The parasol-magnocellular (M) pathway is involved primarily in detecting motion. But how the two pathways contribute to spatial vision – which we use to recognise objects and see fine details in the world around us – was not well understood.

To better understand spatial vision, Brain Function CoE researchers Rania Masri, Ulrike Grünert and Paul Martin from the University of Sydney tracked different cell types involved in the P and M pathways. They tagged the cell networks in these pathways using newly developed molecular markers, then used high-resolution microscopy to take images of the whole retina.

Their goal was to analyse cell density, which underpins the ability of each pathway to detect fine details. A high-density cell network is like a fine-grain sieve that can catch small details. By contrast, a low-density cell network lets fine details slip through undetected.

By analysing the retinal images, the researchers found that the density of the cell network in the M pathway is too low to support detailed spatial vision. However, the density in the P pathway precisely matches the level that people typically need to observe fine detail.

Next steps:
The team plans to look at how cell density in P and M networks is affected in sight-destroying diseases such as macular degeneration and glaucoma.


Reference:
Masri, R. A., Grünert, U., & Martin, P. R. (2020). Analysis of parvocellular and magnocellular visual pathways in human retina. Journal of Neuroscience, 40(42), 8132-8148. doi: 10.1523/JNeurosci.1671-20.2020


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