Sussex Visions

To move efficiently, animals must continuously work out their x,y,z positions with respect to real-world objects, and many animals have a pair of eyes to achieve this. How photoreceptors actively sample the eyes’ optical image disparity is not understood because this fundamental information-limiting step has not been investigated in vivo over the eyes’ whole sampling matrix. This integrative multiscale study will advance our current understanding of stereopsis from static image disparity comparison to a morphodynamic active sampling theory. It shows how photomechanical photoreceptor microsaccades enable Drosophila superresolution three-dimensional vision and proposes neural computations for accurately predicting these flies’ depth-perception dynamics, limits, and visual behaviors.

An object’s colour, brightness and pattern are all influenced by its surroundings, and a number of visual phenomena and “illusions” have been discovered that highlight these often dramatic effects. Explanations for these phenomena range from low-level neural mechanisms to high-level processes that incorporate contextual information or prior knowledge. Importantly, few of these phenomena can currently be accounted for when measuring an object’s perceived colour. Here we ask to what extent colour appearance is predicted by a model based on the principle of coding efficiency. The model assumes that the image is encoded by noisy spatio-chromatic filters at one octave separations, which are either circularly symmetrical or oriented. Each spatial band’s lower threshold is set by the contrast sensitivity function, and the dynamic range of the band is a fixed multiple of this threshold, above which the response saturates. Filter outputs are then reweighted to give equal power in each channel for natural images. We demonstrate that the model fits human behavioural performance in psychophysics experiments, and also primate retinal ganglion responses. Next we systematically test the model’s ability to qualitatively predict over 35 brightness and colour phenomena, with almost complete success. This implies that contrary to high-level processing explanations, much of colour appearance is potentially attributable to simple mechanisms evolved for efficient coding of natural images, and is a basis for modelling the vision of humans and other animals.

A critical function of sensory systems is to reliably extract ethologically relevant features from the complex natural environment. A classic model to study feature detection is the direction-selective circuit of the mammalian retina. In this talk, I will discuss our recent work on how visual contexts dynamically influence the neural processing of motion signals in the direction-selective circuit in the mouse retina.

Fly Escape Behaviors: Flexible and Modular We have identified a set of escape maneuvers performed by a fly when confronted by a looming object. These escape responses can be divided into distinct behavioral modules. Some of the modules are very stereotyped, as when the fly rapidly extends its middle legs to jump off the ground. Other modules are more complex and require the fly to combine information about both the location of the threat and its own body posture. In response to an approaching object, a fly chooses some varying subset of these behaviors to perform. We would like to understand the neural process by which a fly chooses when to perform a given escape behavior. Beyond an appealing set of behaviors, this system has two other distinct advantages for probing neural circuitry. First, the fly will perform escape behaviors even when tethered such that its head is fixed and neural activity can be imaged or monitored using electrophysiology. Second, using Drosophila as an experimental animal makes available a rich suite of genetic tools to activate, silence, or image small numbers of cells potentially involved in the behaviors. Neural Circuits for Escape Until recently, visually induced escape responses have been considered a hardwired reflex in Drosophila. White-eyed flies with deficient visual pigment will perform a stereotyped middle-leg jump in response to a light-off stimulus, and this reflexive response is known to be coordinated by the well-studied giant fiber (GF) pathway. The GFs are a pair of electrically connected, large-diameter interneurons that traverse the cervical connective. A single GF spike results in a stereotyped pattern of muscle potentials on both sides of the body that extends the fly's middle pair of legs and starts the flight motor. Recently, we have found that a fly escaping a looming object displays many more behaviors than just leg extension. Most of these behaviors could not possibly be coordinated by the known anatomy of the GF pathway. Response to a looming threat thus appears to involve activation of numerous different neural pathways, which the fly may decide if and when to employ. Our goal is to identify the descending pathways involved in coordinating these escape behaviors as well as the central brain circuits, if any, that govern their activation. Automated Single-Fly Screening We have developed a new kind of high-throughput genetic screen to automatically capture fly escape sequences and quantify individual behaviors. We use this system to perform a high-throughput genetic silencing screen to identify cell types of interest. Automation permits analysis at the level of individual fly movements, while retaining the capacity to screen through thousands of GAL4 promoter lines. Single-fly behavioral analysis is essential to detect more subtle changes in behavior during the silencing screen, and thus to identify more specific components of the contributing circuits than previously possible when screening populations of flies. Our goal is to identify candidate neurons involved in coordination and choice of escape behaviors. Measuring Neural Activity During Behavior We use whole-cell patch-clamp electrophysiology to determine the functional roles of any identified candidate neurons. Flies perform escape behaviors even when their head and thorax are immobilized for physiological recording. This allows us to link a neuron's responses directly to an action.

The science of the retina has reached an interesting stage of completion. There exists now a consensus standard model of this neural system - at least in the minds of many researchers - that serves as a baseline against which to evaluate new claims. The standard model links phenomena from molecular biophysics, cell biology, neuroanatomy, synaptic physiology, circuit function, and visual psychophysics. It is further supported by a normative theory explaining what the purpose is of processing visual information this way. Most new reports of retinal phenomena fit squarely within the standard model, and major revisions seem increasingly unlikely. Given that our understanding of other brain circuits with comparable complexity is much more rudimentary, it is worth considering an example of what success looks like. In this talk I will summarize what I think are the ingredients that led to this mature understanding of the retina. Equally important, a number of practices and concepts that are currently en vogue in neuroscience were not needed or indeed counterproductive. I look forward to debating how these lessons might extend to other areas of brain research.

The visual system of the brain is highly parallel in its architecture. This is clearly evident in the outputs of the retina, which arise from neurons called ganglion cells. Work in our lab has shown that mammalian retinas contain more than a dozen distinct types of ganglion cells. Each type appears to filter the retinal image in a unique way and to relay this processed signal to a specific set of targets in the brain. My students and I are working to understand the meaning of this parallel organization through electrophysiological and anatomical studies. We record from light-responsive ganglion cells in vitro using the whole-cell patch method. This allows us to correlate directly the visual response properties, intrinsic electrical behavior, synaptic pharmacology, dendritic morphology and axonal projections of single neurons. Other methods used in the lab include neuroanatomical tracing techniques, single-unit recording and immunohistochemistry. We seek to specify the total number of ganglion cell types, the distinguishing characteristics of each type, and the intraretinal mechanisms (structural, electrical, and synaptic) that shape their stimulus selectivities. Recent work in the lab has identified a bizarre new ganglion cell type that is also a photoreceptor, capable of responding to light even when it is synaptically uncoupled from conventional (rod and cone) photoreceptors. These ganglion cells appear to play a key role in resetting the biological clock. It is just this sort of link, between a specific cell type and a well-defined behavioral or perceptual function, that we seek to establish for the full range of ganglion cell types. My research concerns the structural and functional organization of retinal ganglion cells, the output cells of the retina whose axons make up the optic nerve. Ganglion cells exhibit great diversity both in their morphology and in their responses to light stimuli. On this basis, they are divisible into a large number of types (>15). Each ganglion-cell type appears to send its outputs to a specific set of central visual nuclei. This suggests that ganglion cell heterogeneity has evolved to provide each visual center in the brain with pre-processed representations of the visual scene tailored to its specific functional requirements. Though the outline of this story has been appreciated for some time, it has received little systematic exploration. My laboratory is addressing in parallel three sets of related questions: 1) How many types of ganglion cells are there in a typical mammalian retina and what are their structural and functional characteristics? 2) What combination of synaptic networks and intrinsic membrane properties are responsible for the characteristic light responses of individual types? 3) What do the functional specializations of individual classes contribute to perceptual function or to visually mediated behavior? To pursue these questions, we label retinal ganglion cells by retrograde transport from the brain; analyze in vitro their light responses, intrinsic membrane properties and synaptic pharmacology using the whole-cell patch clamp method; and reveal their morphology with intracellular dyes. Recently, we have discovered a novel ganglion cell in rat retina that is intrinsically photosensitive. These ganglion cells exhibit robust light responses even when all influences from classical photoreceptors (rods and cones) are blocked, either by applying pharmacological agents or by dissociating the ganglion cell from the retina. These photosensitive ganglion cells seem likely to serve as photoreceptors for the photic synchronization of circadian rhythms, the mechanism that allows us to overcome jet lag. They project to the circadian pacemaker of the brain, the suprachiasmatic nucleus of the hypothalamus. Their temporal kinetics, threshold, dynamic range, and spectral tuning all match known properties of the synchronization or "entrainment" mechanism. These photosensitive ganglion cells innervate various other brain targets, such as the midbrain pupillary control center, and apparently contribute to a host of behavioral responses to ambient lighting conditions. These findings help to explain why circadian and pupillary light responses persist in mammals, including humans, with profound disruption of rod and cone function. Ongoing experiments are designed to elucidate the phototransduction mechanism, including the identity of the photopigment and the nature of downstream signaling pathways. In other studies, we seek to provide a more detailed characterization of the photic responsiveness and both morphological and functional evidence concerning possible interactions with conventional rod- and cone-driven retinal circuits. These studies are of potential value in understanding and designing appropriate therapies for jet lag, the negative consequences of shift work, and seasonal affective disorder.

The evolution of vision revolutionised animal biology, and eyes have evolved in a stunning array of diverse forms over the past half a billion years. Among these are curious duplicated visual systems, where eyes can be spread across the body and specialised for different tasks. Although it sounds radical, duplicated vision is found in most major groups across the animal kingdom, but remains poorly understood. We will explore how and why animals collect information about their environment in this unusual way, looking at examples from tropical forests to the sea floor, and from ancient arthropods to living jellyfish. Have we been short-changed with just two eyes? Dr Lauren Sumner-Rooney is a Research Fellow at the OUMNH studying the function and evolution of animal visual systems. Lauren completed her undergraduate degree at Oxford in 2012, and her PhD at Queen’s University Belfast in 2015. She worked as a research technician and science communicator at the Royal Veterinary College (2015-2016) and held a postdoctoral research fellowship at the Museum für Naturkunde, Berlin (2016-2017) before arriving at the Museum in 2017.

Bioluminescence, which is rare on land, is extremely common in the deep sea, being found in 80% of the animals living between 200 and 1000 m. These animals rely on bioluminescence for communication, feeding, and/or defense, so the generation and detection of light is essential to their survival. Our present knowledge of this phenomenon has been limited due to the difficulty in bringing up live deep-sea animals to the surface, and the lack of proper techniques needed to study this complex system. However, new genomic techniques are now available, and a team with extensive experience in deep-sea biology, vision, and genomics has been assembled to lead this project. This project is aimed to study three questions 1) What are the evolutionary patterns of different types of bioluminescence in deep-sea shrimp? 2) How are deep-sea organisms’ eyes adapted to detect bioluminescence? 3) Can bioluminescent organs (called photophores) detect light in addition to emitting light? Findings from this study will provide valuable insight into a complex system vital to communication, defense, camouflage, and species recognition. This study will bring monumental contributions to the fields of deep sea and evolutionary biology, and immediately improve our understanding of bioluminescence and light detection in the marine environment. In addition to scientific advancement, this project will reach K-college aged students through the development and dissemination of educational tools, a series of molecular and organismal-based workshops, museum exhibits, public seminars, and biodiversity initiatives.

The research in my lab focuses on sensory signal processing, particularly in cases where sensory systems perform at or near the limits imposed by physics. Photon counting in the visual system is a beautiful example. At its peak sensitivity, the performance of the visual system is limited largely by the division of light into discrete photons. This observation has several implications for phototransduction and signal processing in the retina: rod photoreceptors must transduce single photon absorptions with high fidelity, single photon signals in photoreceptors, which are only 0.03 – 0.1 mV, must be reliably transmitted to second-order cells in the retina, and absorption of a single photon by a single rod must produce a noticeable change in the pattern of action potentials sent from the eye to the brain. My approach is to combine quantitative physiological experiments and theory to understand photon counting in terms of basic biophysical mechanisms. Fortunately there is more to visual perception than counting photons. The visual system is very adept at operating over a wide range of light intensities (about 12 orders of magnitude). Over most of this range, vision is mediated by cone photoreceptors. Thus adaptation is paramount to cone vision. Again one would like to understand quantitatively how the biophysical mechanisms involved in phototransduction, synaptic transmission, and neural coding contribute to adaptation.

Visual restoration is certainly the greatest challenge for brain-machine interfaces with the high pixel number and high refreshing rate. In the recent year, we brought retinal prostheses and optogenetic therapy up to successful clinical trials. Concerning visual restoration at the cortical level, prostheses have shown efficacy for limited periods of time and limited pixel numbers. We are investigating the potential of sonogenetics to develop a non-contact brain machine interface allowing long-lasting activation of the visual cortex. The presentation will introduce our genetic-based brain machine interfaces for visual restoration at the retinal and cortical levels.

Research in our lab focuses on the circuit mechanisms underlying sensory computation. We use the mouse retina as a model system because it allows us to stimulate the circuit precisely with its natural input, patterns of light, and record its natural output, the spike trains of retinal ganglion cells. We harness the power of genetic manipulations and detailed information about cell types to uncover new circuits and discover their role in visual processing. Our methods include electrophysiology, computational modeling, and circuit tracing using a variety of imaging techniques.

My research uses electrophysiological techniques to evaluate normal retinal function, dysfunction caused by blinding retinal diseases and the restoration of function using a variety of therapeutic strategies. We can use our understanding or normal retinal function and disease-related changes to construct optimal therapeutic strategies and evaluate how they ameliorate the effects of disease. Retinitis pigmentosa (RP) is a family of blinding eye diseases caused by photoreceptor degeneration. The absence of the cells that for this primary signal leads to blindness. My interest in RP involves the evaluation of therapies to restore vision: replacing degenerated photoreceptors either with: (1) new stem or other embryonic cells, manipulated to become photoreceptors or (2) prosthetics devices that replace the photoreceptor signal with an electronic signal to light. Glaucoma is caused by increased intraocular pressure and leads to ganglion cell death, which eliminates the link between the retinal output and central visual processing. We are parsing out of the effects of increased intraocular pressure and aging on ganglion cells. Congenital Stationary Night Blindness (CSNB) is a family of diseases in which signaling is eliminated between rod photoreceptors and their postsynaptic targets, rod bipolar cells. This deafferents the retinal circuit that is responsible for vision under dim lighting. My interest in CSNB involves understanding the basic interplay between excitation and inhibition in the retinal circuit and its normal development. Because of the targeted nature of this disease, we are hopeful that a gene therapy approach can be developed to restore night vision. My work utilizes rodent disease models whose mutations mimic those found in human patients. While molecular manipulation of rodents is a fairly common approach, we have recently developed a mutant NIH miniature swine model of a common form of autosomal dominant RP (Pro23His rhodopsin mutation) in collaboration with the National Swine Resource Research Center at University of Missouri. More genetically modified mini-swine models are in the pipeline to examine other retinal diseases.

How does the visual system of insects function in vastly different light intensities, process separate parts of the visual field in parallel, and cope with eye sizes that differ between individuals? This talk will give you the answers we receive from our unique(ly adorable) model system: hawkmoths.

How does the brain interpret signals from the outside world? Walking through a park, you might take for granted the ease with which you can understand what you see. Rather than seeing a series of still snapshots, you are able to see simple, fluid movement — of dogs running, squirrels foraging, or kids playing basketball. You can track their paths and know where they are headed without much thought. “How does this process take place?” asks Rudy Behnia, PhD, a principal investigator at Columbia’s Mortimer B. Zuckerman Mind Brain Behavior Institute. “For most of us, it’s hard to imagine a world where we can’t see motion, shapes, and color; where we can’t have a representation of the physical world in our head.” And yet this representation does not happen automatically — our brain has no direct connection with the outside world. Instead, it interprets information taken in by our senses. Dr. Behnia is studying how the brain builds these representations. As a starting point, she focuses on how we see motion

Statistics of natural scenes are not uniform - their structure varies dramatically from ground to sky. It remains unknown whether these non-uniformities are reflected in the large-scale organization of the early visual system and what benefits such adaptations would confer. By deploying an efficient coding argument, we predict that changes in the structure of receptive fields across visual space increase the efficiency of sensory coding. To test this experimentally, developed a simple, novel imaging system that is indispensable for studies at this scale. In agreement with our predictions, we could show that receptive fields of retinal ganglion cells change their shape along the dorsoventral axis, with a marked surround asymmetry at the visual horizon. Our work demonstrates that, according to principles of efficient coding, the panoramic structure of natural scenes is exploited by the retina across space and cell-types.