Tu banner alternativo

Retinal mosaic

In today's world, Retinal mosaic has gained great relevance in various areas of society. Its impact has been reflected in politics, the economy, culture, and even in people's daily lives. Throughout history, Retinal mosaic has been the subject of various debates and analyses, arousing the interest of academics, specialists, and the general public. In this article, we will explore the many facets of Retinal mosaic, examining its influence in the current context and projecting its importance in the future. From its origin to its implications in contemporary life, Retinal mosaic invites us to reflect and better understand the world around us.

Tu banner alternativo
Illustration of the distribution of cone cells in the fovea of an individual with normal color vision (left), and a color blind (protanopic) retina. Note that the center of the fovea holds very few blue-sensitive cones.

Retinal mosaic is the name given to the distribution of any particular type of neuron across any particular layer in the retina. Typically such distributions are somewhat regular; it is thought that this is so that each part of the retina is served by each type of neuron in processing visual information.[1]

The regularity of retinal mosaics can be quantitatively studied by modelling the mosaic as a spatial point pattern. This is done by treating each cell as a single point and using spatial statistics such as the Effective Radius, Packing Factor and Regularity Index.[2][3]

Using adaptive optics, it is nowadays possible to image the photoreceptor mosaic (i.e. the distribution of rods and cones) in living humans, enabling the detailed study of photoreceptor density and arrangement across the retina.[4]

In the fovea (where photoreceptor density is highest) the spacing between adjacent receptors is about 6-8 micrometer. This corresponds to an angular resolution of approximately 0.5 arc minute, effectively the upper limit of human visual acuity.

References

  1. ^ Reese, Benjamin (2012). "Retinal Mosaics: Pattern Formation Driven by Local Interactions between Homotypic Neighbors". Frontiers in Neural Circuits. 6: 24. doi:10.3389/fncir.2012.00024. PMC 3343307. PMID 22586373.
  2. ^ Rodiek, R.W. (2003). "The density recovery profile: A method for the analysis of points in the plane applicable to retinal studies". Visual Neuroscience. 20 (3): 349. doi:10.1017/S0952523803203138. S2CID 233366586.
  3. ^ Eglen, Stephen J. "Cellular spacing: analysis and modelling of retinal mosaics" (PDF). Springer.
  4. ^ PLoS One. 2018 Jan 16;13(1):e0191141. doi: 10.1371/journal.pone.0191141. eCollection 2018.


Stub icon

This neuroscience article is a stub. You can help Wikipedia by expanding it.

Wikious
Boobota
Sagapedia