The vertebrate retina: a window into the evolution of computation in the brain

Abstract

Animal brains are probably the most complex computational machines on our planet, and like everything in biology, they are the product of evolution. Advances in developmental and palaeobiology have been expanding our general understanding of how nervous systems can change at a molecular and structural level. However, how these changes translate into altered function - that is, into 'computation' - remains comparatively sparsely explored. What, concretely, does it mean for neuronal computation when neurons change their morphology and connectivity, when new neurons appear or old ones disappear, or when transmitter systems are slowly modified over many generations? And how does evolution use these many possible knobs and dials to constantly tune computation to give rise to the amazing diversity in animal behaviours we see today? Addressing these major gaps of understanding benefits from choosing a suitable model system. Here, I present the vertebrate retina as one perhaps unusually promising candidate. The retina is ancient and displays highly conserved core organisational principles across the entire vertebrate lineage, alongside a myriad of adjustments across extant species that were shaped by the history of their visual ecology. Moreover, the computational logic of the retina is readily interrogated experimentally, and our existing understanding of retinal circuits in a handful of species can serve as an anchor when exploring the visual circuit adaptations across the entire vertebrate tree of life, from fish deep in the aphotic zone of the oceans to eagles soaring high up in the sky.

Figure 1

The brain, the eye, and the retinal circuit organisation. (a) The neural computations of central circuits are usually difficult to study and link across large phylogenetic distances. (b) By comparison, deep circuit conservation across all vertebrate retinas helps link circuit elements across large evolutionary distances. (c) Retinal circuits are feedforward across the layers, from the outer to the inner retina and finally, the spiking output of retinal ganglion cells to the brain . Retinal circuit elements are also highly conserved, with neuron types falling along a homology gradient that peaks with photoreceptors and horizontal cells in the outer retina and gradually falls via bipolar cells to the amacrine cells and ganglion cells . This homology gradient antialigns with a complexity gradient, both in terms of neuronal diversity and in terms of the visual signals that neurons at different stages of retinal processing encode. Photoreceptors carry comparatively simple and broad signals, while visual features encoded by ganglion cells can be notably more specific.

Figure 2

Retinal designs have been shaped by the history of an animal’s visual ecology. For example, some birds and primates, or some cetaceans and fish, share a common habitat and visual ecology. However, because of their distinct evolutionary histories, their retinas are built very differently. Vision evolved in the water for some 150 million years before the first vertebrates emerged on land, which probably came in hand with the emergence of a new pair of photoreceptors called the ‘double cone’ (expressing LWS), potentially to support ‘fast’ vision , . Soon after came the split of the early amniote lineage that would ultimately give rise to birds and reptiles on one branch and mammals on the other. Reptiles dominated diurnal niches, while early mammals were mostly nocturnal. During this time, the lineage that would give rise to modern eutherian mammals first lost the green cone (RH2), then blue (SWS2), and finally also the double cone (LWS). Upon the extinction of the dinosaurs, many mammals returned to a diurnal lifestyle, and some of them eventually gave rise to primates and ultimately humans. Very recently, primates duplicated their ancestral red cones (LWS) to evolve a relatively unusual form of de novo trichromacy . By contrast, other mammals returned to the water, became very large, and lost the ancestral UV cone (SWS1). Some of these became small again to ultimately give rise to dolphins. All the while, fish never left the water, and many retain the complete ancestral photoreceptor complement. RH2, Rhodopsin-2; SWS, Short Wavelength Selective.

Figure 3

Phylogeny, photoreceptor types, and retinal complexity. (a) Phylogenetic tree of major vertebrate lineages with key events in the evolution of photoreceptor types and features indicated. (b) The density of vertebrates’ retinal ganglion cells scales with the number of photoreceptor types present. By and large, vertebrates can be divided into two retinal complexity groups: mammals, elasmobranchs (sharks, rays, and skates), and jawless species typically have low photoreceptor type diversity and low-density retinas, while many fish, amphibians, reptiles, and birds have larger numbers of photoreceptor types and high-density retinas.

Figure 4

Evolution of the primate midget and parasol pathways. (a,b) Primate midget and parasol circuits are orthologs, respectively, of murine sustained and transient alpha ganglion cells and their presynaptic bipolar cells. (c) Retinal projections to the brain in mice and primates. (d–h) Murine-sustained alpha cells mirror key properties of primate midget circuits. Unlike transient alpha cells (right), sustained alphas display more sluggish light responses and electrotonically compact dendritic integration. Sustained but not transient alphas are enriched in the ventrotemporal retina to survey the upper-frontal horizon. A subset of these ventronasal-sustained alphas make ipsilateral projections that are probably key for visual prey capture of crickets. During hunting, mice align their heads to bring the target into their binocular zone (f). Ablation of ipsilateral projection greatly deteriorates prey-capture performance (g). On- and Off-sustained alpha cells readily respond to prey-like moving stimuli (h).