Читать книгу Bird Senses - Graham R. Martin - Страница 46

It is the retina that starts the process of image analysis. The retina extracts the essential information that the image contains, encodes it neurologically, and sends it via the optic nerve for further analysis by the brain.

When looking into any eye we see the pupil as a black void. We are looking through the optical system and through the thin transparent neurological layers of the retina to the uniformly black surface, the pigmented epithelium, that lies behind it. As outlined above, each retina contains many millions of individual neural cells arranged in distinct layers. The most prominent of these layers contains the photoreceptor cells, the well-known rods and cones, and these are discussed in detail below.

When light photons reach a photoreceptor, a neural signal is generated and relayed to a ganglion cell which in turn relays that information through the optic nerve to the brain. Of crucial importance at this first level of image analysis are the number, density, and distribution of photoreceptor and ganglion cells across a retina. The actual numbers of photoreceptors are very high. For example, in the eyes of eagles (and humans) the total number of cells in the whole retina probably exceeds 100 million. In all retinas, however, the number and density of photoreceptor cells are far from uniform. In some locations photoreceptor cells are packed close together, in others they are more sparse, and large differences in density can occur between locations less than 1 mm apart. In an eagle’s retina density can peak at about 450,000 photoreceptors per square millimetre, and in humans it reaches about 200,000, but less than 1 mm from the site of peak receptor density it drops to 16,000 photoreceptors per square millimetre. However, these changes in receptor density do not occur randomly across the retina; they occur in distinct patterns in the eyes of different species.

The patterns of photoreceptors can be revealed and characterised using isodensity contour maps (Figure 3.5). These link locations across a retina which have the same cell densities. In the same way that contour maps link locations of the same elevation and allow us to quickly appreciate the topography of a landscape, these density maps of retinal cells provide a quick way to compare retinas in different species and hence are a ready means of comparing some basic aspects of vision between species. A number of examples of receptor and ganglion cell maps will be discussed in later chapters.

FIGURE 3.5 Examples of isodensity maps of the ganglion cells in bird retinas. In each diagram the retina has been spread flat, but its orientation is as in the eyes in the intact birds shown above. Flattening the retina causes splits, hence the rather ragged shape. The densities of the ganglion cells (×1000 per square millimetre) have been analysed across the whole of the retina and points with similar density have been joined to give contour maps, much as a topographical map links places of the same height. Clear patterns emerge in these maps showing how the images projected onto the retina by the eye’s optics are analysed to extract different degrees of detail. On the left is the retina of a Manx Shearwater Puffinus puffinus, and the map shows that their retinas have a band running horizontally across the field of view in which details are particularly resolved (receptors are at high density, providing greater detail). On the right, the Rock Dove Columba livia shows a retina with two distinct areas from which detailed information is extracted: one looks out close to the axis of the eye (in this view almost directly out of the page), while the other also projects laterally but downwards and slightly forward within the bird’s field of view. (The diagram of the dove is redrawn from work published by Bingelli and Paul.)

The importance of these density patterns can be appreciated by considering the photoreceptors of a retina to be analogous with the photodiodes of the receptor surface of a digital camera. In a camera we understand that the photodiodes are responsible for pixelating the image, and we expect that the photodiodes are not jumbled but spread at an even density across the whole image-analysing surface. This guarantees that the same amount of detail is available across the whole of the image. However, in retinas the densities of receptors and ganglion cells vary markedly across the image surface. Furthermore, there are consistent and different photoreceptor and ganglion cell patterns in the retinas of every bird species. It is as though we were able to choose between cameras not just on their overall density of photodiodes, but also on how the photodiodes are placed across the image surface. It is as if we could choose between one camera that analysed the image in greater detail at its centre, another that could analyse with greater detail in a band horizontally across the middle of the image, another more to one side, and so on. An endless number of possible arrangements would be possible.

Such patterns are indeed found in bird retinas, and indeed in all retinas, including our own. In human eyes the image is analysed in greatest detail more or less at its centre, and in less detail towards the periphery, but even in our eyes the patterns are not symmetrical. In birds highly complex patterns are found (Figure 3.5). What this means is that across bird species there is a wide range of patterns in the way that information is extracted from the environment surrounding the bird. The eyes of two different species may be imaging the same scene, but because of differences in their retinas the scene is analysed in different ways. These different receptor patterns are the result of natural selection driven by the need for the extraction of key information used in the control of different visually guided tasks in different species.

While knowing about these patterns gives valuable insight into the vision of different species, knowledge of the absolute density of ganglion cells or photoreceptors in a particular eye is also of great value. It allows an estimation to be made of the upper limits of the resolution (acuity) of an eye and can also provide an idea of acuity in different parts of the field of view. To achieve this, data on ganglion cell density must be combined with information on the size of the image. Using this method, estimates of the maximum spatial resolution of eyes have been calculated for a range of species (see Appendix). Furthermore, this method has been validated by determinations of maximum acuity using training techniques (of the kind described in Chapter 2) in the same species, most notably in some birds of prey, including both eagles and falcons.