Anisotropic retinal circuits for processing of colour and space in nature

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In vision, a constant stream of light patterns that vary in space, time and colour drive electrical activity in millions of photoreceptor neurons in our retinas. Depending on the colour and shape of this light, different sets of photoreceptors are activated to form a camera-like image. However, to send this information to the brain, it needs to be transmitted by the optic nerve. Much like a regular video cable, the amount of information that can be transmitted by this nerve is limited. In humans, the optic nerve has about the same information rate capacity as required to drive a pixel-by-pixel UHD TV picture at video rates. However, across its entire visual field the human retina is 100x more finely resolved still, meaning that only 1% of all pixels could be send to the brain. This is why we need a retina. Instead of wiring each photoreceptor directly to the brain, the retina compares the signals across groups of neighbouring photoreceptors in a series of pre-processing steps to compress the transmitted image. For example, if 1000s of neighbouring photoreceptors signal an image part of a clear-blue sky, there is no need to send 1000 versions of this information to the brain - 1 will do. How the retina achieves this, and many other types of computations is an area of active research that can potentially benefit a wide range of applications, ranging from medicine to computer vision and the design of "intelligent" camera systems. Like in humans, the eyes of all vertebrates such as mice, birds or fish have an optic nerve with a retina as its input. However, depending on the animal, and depending on the position in visual space, the types of information that needs to be sent to the brain varies dramatically. For example, a mouse needs to excel at spotting dark spots in the sky such as the silhouette of a predatory bird. As predatory birds never attack from below, this special computation is only required in half of the eye. In contrast, for a deep-sea fish it may be essential so detect faint luminescence signals emanating from other animals on the backdrop of the pitch-black ocean in any direction. The need for different types of retinal computations has driven specialisations in the way that the retinas of different animals are organised. Together, these present a vast resource for driving our understanding of how our senses work, how brains evolve, and how important information in images can be efficiently detected. We will use the highly visual zebrafish to study how retinal circuits that are positioned in different parts of this animal's eye differ from one another to best extract key information in the zebrafish's visual world. Zebrafish inhabit shallow freshwaters of the Indian subcontinent. In this underwater world, the visual field in front of and below the animal tends to contain a lot of colour, and we recently found that zebrafish invest more neurons for circuits computing colour to survey their lower visual field. In contrast, the upper visual field is dominated by light-dark contrasts, and so zebrafish invest more neurons into detecting bright and dark edges. However, not only colour, but also spatial detail available for vision to detect shapes varies between the upper and lower visual field. In shallow water, you are never far from the ground, and this is where most spatial detail is to be explored using vision. Accordingly, we will now study if like for colour, retinal circuits computing spatial detail are also predominately set-up to survey the ground - and if so, how they overlap with circuits computing colour. After all, there is only so much space for neurons in the tiny zebrafish's eye, and some functions may have to give way to allow the space for others. Studying which colour- and space-computations are implemented in different positions of the zebrafish's eye will shed new light onto how sensory systems can be optimised to preferentially transmit information that matters to the user.