Vision, Evolution, Computation
How do synapses, neurons and networks enable ‘function’, and how can they rearrange to meet new sensory and behavioural demands on evolutionary timescales? To address these questions, we link state-of-the-art approaches in systems and computational neuroscience with behavioural and sensory ecology, while also drawing on connectomics, transcriptomics and genetic manipulation. Our model systems include zebrafish and mice, as well as birds, frogs, and sharks.
Evolution of Vision
All vertebrate retinas follow a common circuit blueprint, yet different species show striking specialisations that reflect their visual ecology. Many retinal circuits appear deeply conserved, while key properties are tuned to the sensory demands of each species. Understanding how lifestyle and evolutionary history shape these networks requires comparisons across animals, including non-model species. Alongside our core work on zebrafish vision, we therefore regularly explore the visual systems of other animals.
"Rethinking" colour vision
During the age of the dinosaurs, early mammals adopted a largely nocturnal lifestyle and lost several ancestral cone photoreceptor types. As a result, most mammals today have only two cone classes, whereas many other vertebrates, including fish, birds, reptiles and amphibians, retain four or more. These extra cones are often described as enabling animals to see more colours. However, growing evidence suggests a different view: cone types act as parallel feature channels that sample different parts of the visual spectrum and support specialised visual computations.
Synaptic computation
The computational power of retinal networks is deeply rooted in their synaptic architecture. The highly specialised ribbon-type synapses of photoreceptors and bipolar cells receive a myriad of feedback and feed-forward signals through the network, making them probably the most important computational locus of the circuit. Using 2-photon imaging of voltage, calcium and synaptic release signals in vivo we aim to probe the visual response properties of retinal synapses towards a better understanding of locally visual signal transformations.
The natural visual world of animals
All sensory systems are specialised to best serve an animal’s sensory-ecological niche, and vision is no exception. Here, specialisations range from basic anatomy all the way down to the tuning individual synapses and microcircuits. To understand what natural sensory demands and pressures shape requires measurements of natural visual worlds, including systematic variations in space, time and wavelength composition. We use custom camera and hyperspectral scan-systems to survey visual information available to animals in nature.
Retinal coding
The retina breaks light patterns into increasingly specific internal representations of the visual world. Spike trains of retinal gamglion cells (RGCs), the retina’s only output neurons, retain only a tiny fraction of original visual input to form a sparse but information rich retinal code. Within the retina, interactions between five principal neuron classes, each comprised of several types, fundamentally shape the response properties of individual pathway elements. We study the gradual evolution of feature extraction as visual information trickles through the retinal network.
Technology development
To probe neuronal function in the living nervous system requires state of the art imaging equipment such as our heavily customised 2-photon microscopes and visual stimulators. Here, we aim to drive current possibilities in optical imaging technology, for example by light-path optimisations or the implementation of custom scan strategies that acknowledge the 3D curvature of biological samples. In parallel, we invest heavily in open hardware approaches to optimise research-grade lab equipment for a fraction of commerical costs.
Why retina?
The retina is probably the most accessible part of the central nervous system. Its entire computational logic can be interrogated in a dish, from patterns of lights as the natural input, to spike trains on the optic nerve as the natural output. Consequently, retinal circuits include some of the best understood computational networks in neuroscience.
The retina is also ancient, and central to the emergence of neurally complex life on our planet. Alongside new locomotor strategies, the parallel evolution of image forming vision in vertebrate and invertebrate lineages is thought to have driven speciation during the Cambrian. This early investment in sophisticated vision is evident in the fossil record and from comparing the retina’s structural make up in extant species. Animals as diverse as eagles and lampreys share the same retinal make up of five classes of neurons, arranged into three nuclear layers flanking two synaptic layers. In fact, some retinal neuron types can be linked across the entire vertebrate tree of life. For example, the photoreceptors in our own eyes can be directly linked to those in eagles and lampreys. And yet, the functions that these photoreceptors serve in each species, and the circuits that they innervate to do so, are almost certainly distinct to acknowledge the vast differences in species-specific visuo-behavioural demands.
