Color
color
Development of an Optical and Colorimetric Biosensor for the Quantification of Microrna 184 for Late Life Depression
SYNGAP1 Natural History Study/ Multidisciplinary Clinic at Children’s Hospital Colorado
From pecking order to ketamine - neural mechanism of social and emotional behavior
Emotions and social interactions color our lives and shape our behaviors. Using animal models and engineered manipulations, we aim to understand how social and emotional behaviors are encoded in the brain, focusing on the neural circuits underlying dominance hierarchy and depression. This lecture will highlight our recent discoveries on how downward social mobility leads to depression; how ketamine tames depression by blocking burst firing in the brain’s antireward center; and, how glia-neuron interaction plays a surprising role in this process. I will also present our recent work on the mechanism underlying the sustained antidepressant activity of ketamine and its brain region specificity. With these results, we hope to illuminate on a more unified theory on ketamine’s mode of action and inspire new treatment strategies for depression.
From pecking order to ketamine - neural mechanism of social and emotional behavior
Emotions and social interactions color our lives and shape our behaviors. Using animal models and engineered manipulations, we aim to understand how social and emotional behaviors are encoded in the brain, focusing on the neural circuits underlying dominance hierarchy and depression. This lecture will highlight our recent discoveries on how downward social mobility leads to depression; how ketamine tames depression by blocking burst firing in the brain’s antireward center; and, how glia-neuron interaction plays a surprising role in this process. I will also present our recent work on the mechanism underlying the sustained antidepressant activity of ketamine and its brain region specificity. With these results, we hope to illuminate on a more unified theory on ketamine’s mode of action and inspire new treatment strategies for depression.
Metastatic recurrence in colorectal cancer arises from residual EMP1+ cells
Redox and mitochondrial dysregulation in epilepsy
Epileptic seizures render the brain uniquely dependent on energy producing pathways. Studies in our laboratory have been focused on the role of redox processes and mitochondria in the context of abnormal neuronal excitability associated with epilepsy. We have shown that that status epilepticus (SE) alters mitochondrial and cellular redox status, energetics and function and conversely, that reactive oxygen species and resultant dysfunction can lead to chronic epilepsy. Oxidative stress and neuroinflammatory pathways have considerable crosstalk and targeting redox processes has recently been shown to control neuroinflammation and excitability. Understanding the role of metabolic and redox processes can enable the development of novel therapeutics to control epilepsy and/or its comorbidities.
Color vision circuits for primate intrinsically photosensitive retinal ganglion cells
The rising and setting of the sun is accompanied by changes in both the irradiance and the spectral distribution of the sky. Since the discovery of intrinsically photosensitive retinal ganglion cells (ipRGCs) 20 years ago, considerable progress has been made in understanding melanopsin's contributions to encoding irradiance. Much less is known about the cone inputs to ipRGCs and how they could encode changes in the color of the sky. I will summarize our recent connectomic investigation into the cone-opponent inputs to primate ipRGCs and the implications of this work on our understanding of circadian photoentrainment and the evolution of color vision.
How vision succeeds in a hidden world
Seeing colour: is human perception optimised for natural illumination?
Connecting structure and function in early visual circuits
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
Synergy of color and motion vision for detecting approaching objects in Drosophila
I am working on color vision in Drosophila, identifying behaviors that involve color vision and understanding the neural circuits supporting them (Longden 2016). I have a long-term interest in understanding how neural computations operate reliably under changing circumstances, be they external changes in the sensory context, or internal changes of state such as hunger and locomotion. On internal state-modulation of sensory processing, I have shown how hunger alters visual motion processing in blowflies (Longden et al. 2014), and identified a role for octopamine in modulating motion vision during locomotion (Longden and Krapp 2009, 2010). On responses to external cues, I have shown how one kind of uncertainty in the motion of the visual scene is resolved by the fly (Saleem, Longden et al. 2012), and I have identified novel cells for processing translation-induced optic flow (Longden et al. 2017). I like working with colleagues who use different model systems, to get at principles of neural operation that might apply in many species (Ding et al. 2016, Dyakova et al. 2015). I like work motivated by computational principles - my background is computational neuroscience, with a PhD on models of memory formation in the hippocampus (Longden and Willshaw, 2007).
JAK/STAT regulation of the transcriptomic response during epileptogenesis
Temporal lobe epilepsy (TLE) is a progressive disorder mediated by pathological changes in molecular cascades and neural circuit remodeling in the hippocampus resulting in increased susceptibility to spontaneous seizures and cognitive dysfunction. Targeting these cascades could prevent or reverse symptom progression and has the potential to provide viable disease-modifying treatments that could reduce the portion of TLE patients (>30%) not responsive to current medical therapies. Changes in GABA(A) receptor subunit expression have been implicated in the pathogenesis of TLE, and the Janus Kinase/Signal Transducer and Activator of Transcription (JAK/STAT) pathway has been shown to be a key regulator of these changes. The JAK/STAT pathway is known to be involved in inflammation and immunity, and to be critical for neuronal functions such as synaptic plasticity and synaptogenesis. Our laboratories have shown that a STAT3 inhibitor, WP1066, could greatly reduce the number of spontaneous recurrent seizures (SRS) in an animal model of pilocarpine-induced status epilepticus (SE). This suggests promise for JAK/STAT inhibitors as disease-modifying therapies, however, the potential adverse effects of systemic or global CNS pathway inhibition limits their use. Development of more targeted therapeutics will require a detailed understanding of JAK/STAT-induced epileptogenic responses in different cell types. To this end, we have developed a new transgenic line where dimer-dependent STAT3 signaling is functionally knocked out (fKO) by tamoxifen-induced Cre expression specifically in forebrain excitatory neurons (eNs) via the Calcium/Calmodulin Dependent Protein Kinase II alpha (CamK2a) promoter. Most recently, we have demonstrated that STAT3 KO in excitatory neurons (eNSTAT3fKO) markedly reduces the progression of epilepsy (SRS frequency) in the intrahippocampal kainate (IHKA) TLE model and protects mice from kainic acid (KA)-induced memory deficits as assessed by Contextual Fear Conditioning. Using data from bulk hippocampal tissue RNA-sequencing, we further discovered a transcriptomic signature for the IHKA model that contains a substantial number of genes, particularly in synaptic plasticity and inflammatory gene networks, that are down-regulated after KA-induced SE in wild-type but not eNSTAT3fKO mice. Finally, we will review data from other models of brain injury that lead to epilepsy, such as TBI, that implicate activation of the JAK/STAT pathway that may contribute to epilepsy development.
Opponent processing in the expanded retinal mosaic of Nymphalid butterflies
In many butterflies, the ancestral trichromatic insect colour vision, based on UV-, blue- and green-sensitive photoreceptors, is extended with red-sensitive cells. Physiological evidence for red receptors has been missing in nymphalid butterflies, although some species can discriminate red hues well. In eight species from genera Archaeoprepona, Argynnis, Charaxes, Danaus, Melitaea, Morpho, Heliconius and Speyeria, we found a novel class of green-sensitive photoreceptors that have hyperpolarizing responses to stimulation with red light. These green-positive, red-negative (G+R–) cells are allocated to positions R1/2, normally occupied by UV and blue-sensitive cells. Spectral sensitivity, polarization sensitivity and temporal dynamics suggest that the red opponent units (R–) are the basal photoreceptors R9, interacting with R1/2 in the same ommatidia via direct inhibitory synapses. We found the G+R– cells exclusively in butterflies with red-shining ommatidia, which contain longitudinal screening pigments. The implementation of the red colour channel with R9 is different from pierid and papilionid butterflies, where cells R5–8 are the red receptors. The nymphalid red-green opponent channel and the potential for tetrachromacy seem to have been switched on several times during evolution, balancing between the cost of neural processing and the value of extended colour information.
NMC4 Short Talk: Transient neuronal suppression for exploitation of new sensory evidence
Decision-making in noisy environments with constant sensory evidence involves integrating sequentially-sampled evidence, a strategy formalized by diffusion models which is supported by decades behavioral and neural findings. By contrast, it is unknown whether this strategy is also used during decision-making when the underlying sensory evidence is expected to change. Here, we trained monkeys to identify the dominant color of a dynamically refreshed checkerboard pattern that doesn't become informative until after a variable delay. Animals' behavioral responses were briefly suppressed after an abrupt change in evidence, and many neurons in the frontal eye field displayed a corresponding dip in activity at this time, similar to the dip frequently observed after stimulus onset. Generalized drift-diffusion models revealed that behavior and neural activity were consistent with a brief suppression of motor output without a change in evidence accumulation itself, in contrast to the popular belief that evidence accumulation is paused or reset. These results suggest that a brief interruption in motor preparation is an important strategy for dealing with changing evidence during perceptual decision making.
Suboptimal human inference inverts the bias-variance trade-off for decisions with asymmetric evidence
Solutions to challenging inference problems are often subject to a fundamental trade-off between bias (being systematically wrong) that is minimized with complex inference strategies and variance (being oversensitive to uncertain observations) that is minimized with simple inference strategies. However, this trade-off is based on the assumption that the strategies being considered are optimal for their given complexity and thus has unclear relevance to the frequently suboptimal inference strategies used by humans. We examined inference problems involving rare, asymmetrically available evidence, which a large population of human subjects solved using a diverse set of strategies that were suboptimal relative to the Bayesian ideal observer. These suboptimal strategies reflected an inversion of the classic bias-variance trade-off: subjects who used more complex, but imperfect, Bayesian-like strategies tended to have lower variance but high bias because of incorrect tuning to latent task features, whereas subjects who used simpler heuristic strategies tended to have higher variance because they operated more directly on the observed samples but displayed weaker, near-normative bias. Our results yield new insights into the principles that govern individual differences in behavior that depends on rare-event inference, and, more generally, about the information-processing trade-offs that are sensitive to not just the complexity, but also the optimality of the inference process.
Using non-invasive brain measurement to predict social, cognitive, and affective states in real-time
Physical Computation in Insect Swarms
Our world is full of living creatures that must share information to survive and reproduce. As humans, we easily forget how hard it is to communicate within natural environments. So how do organisms solve this challenge, using only natural resources? Ideas from computer science, physics and mathematics, such as energetic cost, compression, and detectability, define universal criteria that almost all communication systems must meet. We use insect swarms as a model system for identifying how organisms harness the dynamics of communication signals, perform spatiotemporal integration of these signals, and propagate those signals to neighboring organisms. In this talk I will focus on two types of communication in insect swarms: visual communication, in which fireflies communicate over long distances using light signals, and chemical communication, in which bees serve as signal amplifiers to propagate pheromone-based information about the queen’s location.
What Art can tell us about the Brain
Artists have been doing experiments on vision longer than neurobiologists. Some major works of art have provided insights as to how we see; some of these insights are so undamental that they can be understood in terms of the underlying neurobiology. For example, artists have long realized that color and luminance can play independent roles in visual perception. Picasso said, "Colors are only symbols. Reality is to be found in luminance alone." This observation has a parallel in the functional subdivision of our visual systems, where color and luminance are processed by the evolutionarily newer, primate-specific What system, and the older, colorblind, Where (or How) system. Many techniques developed over the centuries by artists can be understood in terms of the parallel organization of our visual systems. I will explore how the segregation of color and luminance processing are the basis for why some Impressionist paintings seem to shimmer, why some op art paintings seem to move, some principles of Matisse's use of color, and how the Impressionists painted "air". Central and peripheral vision are distinct, and I will show how the differences in resolution across our visual field make the Mona Lisa's smile elusive, and produce a dynamic illusion in Pointillist paintings, Chuck Close paintings, and photomosaics. I will explore how artists have figured out important features about how our brains extract relevant information about faces and objects, and I will discuss why learning disabilities may be associated with artistic talent.
Gap Junction Coupling between Photoreceptors
Simply put, the goal of my research is to describe the neuronal circuitry of the retina. The organization of the mammalian retina is certainly complex but it is not chaotic. Although there are many cell types, most adhere to a relatively constant morphology and they are distributed in non-random mosaics. Furthermore, each cell type ramifies at a characteristic depth in the retina and makes a stereotyped set of synaptic connections. In other words, these neurons form a series of local circuits across the retina. The next step is to identify the simplest and commonest of these repeating neural circuits. They are the building blocks of retinal function. If we think of it in this way, the retina is a fabulous model for the rest of the CNS. We are interested in identifying specific circuits and cell types that support the different functions of the retina. For example, there appear to be specific pathways for rod and cone mediated vision. Rods are used under low light conditions and rod circuitry is specialized for high sensitivity when photons are scarce (when you’re out camping, starlight). The hallmark of the rod-mediated system is monochromatic vision. In contrast, the cone circuits are specialized for high acuity and color vision under relatively bright or daylight conditions. Individual neurons may be filled with fluorescent dyes under visual control. This is achieved by impaling the cell with a glass microelectrode using a 3D micromanipulator. We are also interested in the diffusion of dye through coupled neuronal networks in the retina. The dye filled cells are also combined with antibody labeling to reveal neuronal connections and circuits. This triple-labeled material may be viewed and reconstructed in 3 dimensions by multi-channel confocal microscopy. We have our own confocal microscope facility in the department and timeslots are available to students in my lab.
Rule learning representation in the fronto-parietal network
We must constantly adapt the rules we use to guide our attention. To understand how the brain learns these rules, we designed a novel task that required monkeys to learn which color is the most rewarded at a given time (the current rule). However, just as in real life, the monkey was never explicitly told the rule. Instead, they had to learn it through trial and error by choosing a color, receiving feedback (amount of reward), and then updating their internal rule. After the monkeys reached a behavioral criterion, the rule changed. This change was not cued but could be inferred based on reward feedback. Behavioral modeling found monkeys used rewards to learn the rules. After the rule changed, animals adopted one of two strategies. If the change was small, reflected in a small reward prediction error, the animals continuously updated their rule. However, for large changes, monkeys ‘reset’ their belief about the rule and re-learned the rule from scratch. To understand the neural correlates of learning new rules, we recorded neurons simultaneously from the prefrontal and parietal cortex. We found that the strength of the rule representation increased with the certainty about the current rule, and that the certainty about the rule was represented both implicitly and explicitly in the population.
Using opsin genes to see through the eyes of a fish
Many animals are highly visual. They view their world through photoreceptors sensitive to different wavelengths of light. Animal survival and optimal behavioral performance may select for varying photoreceptor sensitivities depending on animal habitat or visual tasks. Our goal is to understand what drives visual diversity from both an evolutionary and molecular perspective. The group of more than 2000 cichlid fish species are an ideal system for examining such diversity. Cichlid are a colorful group of fresh water fishes. They have undergone adaptive radiation throughout Africa and the new world and occur in rivers and lakes that vary in water clarity. They are also behaviorally complex, having diverse behaviors for foraging, mate choice and even parental care. As a result, cichlids have highly diverse visual systems with cone sensitivities shifting by 30-90 nm between species. Although this group has seven cone opsin genes, individual species differ in which subset of the cone opsins they express. Some species show developmental shifts in opsin expression, switching from shorter to longer wavelength opsins through ontogeny. Other species modify that developmental program to express just one of the sets, causing the large sensitivity differences. Cichlids are therefore natural mutants for opsin expression. We have used cichlid diversity to explore the relationship between visual sensitivities and ecology. We have also exploited the genomic power of the cichlid system to identify genes and mutations that cause opsin expression shifts. Ultimately, our goal is to learn how different cichlid species see the world and whether differences matter. Behavioral experiments suggest they do indeed use color vision to survive and thrive. Cichlids therefore are a unique model for exploring how visual systems evolve in a changing world.
Internal structure of honey bee swarms for mechanical stability and division of labor
The western honey bee (Apis mellifera) is a domesticated pollinator famous for living in highly social colonies. In the spring, thousands of worker bees and a queen fly from their hive in search of a new home. They self-assemble into a swarm that hangs from a tree branch for several days. We reconstruct the non-isotropic arrangement of worker bees inside swarms made up of 3000 - 8000 bees using x-ray computed tomography. Some bees are stationary and hang from the attachment board or link their bodies into hanging chains to support the swarm structure. The remaining bees use the chains as pathways to walk around the swarm, potentially to feed the queen or communicate with one another. The top layers of bees bear more weight per bee than the remainder of the swarm, suggesting that bees are optimizing for additional factors besides weight distribution. Despite not having a clear leader, honey bees are able to organize into a swarm that protects the queen and remains stable until scout bees locate a new hive.
A brain circuit for curiosity
Motivational drives are internal states that can be different even in similar interactions with external stimuli. Curiosity as the motivational drive for novelty-seeking and investigating the surrounding environment is for survival as essential and intrinsic as hunger. Curiosity, hunger, and appetitive aggression drive three different goal-directed behaviors—novelty seeking, food eating, and hunting— but these behaviors are composed of similar actions in animals. This similarity of actions has made it challenging to study novelty seeking and distinguish it from eating and hunting in nonarticulating animals. The brain mechanisms underlying this basic survival drive, curiosity, and novelty-seeking behavior have remained unclear. In spite of having well-developed techniques to study mouse brain circuits, there are many controversial and different results in the field of motivational behavior. This has left the functions of motivational brain regions such as the zona incerta (ZI) still uncertain. Not having a transparent, nonreinforced, and easily replicable paradigm is one of the main causes of this uncertainty. Therefore, we chose a simple solution to conduct our research: giving the mouse freedom to choose what it wants—double freeaccess choice. By examining mice in an experimental battery of object free-access double-choice (FADC) and social interaction tests—using optogenetics, chemogenetics, calcium fiber photometry, multichannel recording electrophysiology, and multicolor mRNA in situ hybridization—we uncovered a cell type–specific cortico-subcortical brain circuit of the curiosity and novelty-seeking behavior. We found in mice that inhibitory neurons in the medial ZI (ZIm) are essential for the decision to investigate an object or a conspecific. These neurons receive excitatory input from the prelimbic cortex to signal the initiation of exploration. This signal is modulated in the ZIm by the level of investigatory motivation. Increased activity in the ZIm instigates deep investigative action by inhibiting the periaqueductal gray region. A subpopulation of inhibitory ZIm neurons expressing tachykinin 1 (TAC1) modulates the investigatory behavior.
Novel Object Detection and Multiplexed Motion Representation in Retinal Bipolar Cells
Detection of motion is essential for survival, but how the visual system processes moving stimuli is not fully understood. Here, based on a detailed analysis of glutamate release from bipolar cells, we outline the rules that govern the representation of object motion in the early processing stages. Our main findings are as follows: (1) Motion processing begins already at the first retinal synapse. (2) The shape and the amplitude of motion responses cannot be reliably predicted from bipolar cell responses to stationary objects. (3) Enhanced representation of novel objects - particularly in bipolar cells with transient dynamics. (4) Response amplitude in bipolar cells matches visual salience reported in humans: suddenly appearing objects > novel motion > existing motion. These findings can be explained by antagonistic interactions in the center-surround receptive field, demonstrate that despite their simple operational concepts, classical center-surround receptive fields enable sophisticated visual computations.
Memory for Latent Representations: An Account of Working Memory that Builds on Visual Knowledge for Efficient and Detailed Visual Representations
Visual knowledge obtained from our lifelong experience of the world plays a critical role in our ability to build short-term memories. We propose a mechanistic explanation of how working memory (WM) representations are built from the latent representations of visual knowledge and can then be reconstructed. The proposed model, Memory for Latent Representations (MLR), features a variational autoencoder with an architecture that corresponds broadly to the human visual system and an activation-based binding pool of neurons that binds items’ attributes to tokenized representations. The simulation results revealed that shape information for stimuli that the model was trained on, can be encoded and retrieved efficiently from latents in higher levels of the visual hierarchy. On the other hand, novel patterns that are completely outside the training set can be stored from a single exposure using only latents from early layers of the visual system. Moreover, the representation of a given stimulus can have multiple codes, representing specific visual features such as shape or color, in addition to categorical information. Finally, we validated our model by testing a series of predictions against behavioral results acquired from WM tasks. The model provides a compelling demonstration of visual knowledge yielding the formation of compact visual representation for efficient memory encoding.
A role for cognitive maps in metaphors and analogy?
In human and non-human animals, conceptual knowledge is partially organized according to low-dimensional geometries that rely on brain structures and computations involved in spatial representations. Recently, two separate lines of research have investigated cognitive maps, that are associated with the hippocampal formation and are similar to world-centered representations of the environment, and image spaces, that are associated with the parietal cortex and are similar to self-centered spatial relationships. I will suggest that cognitive maps and image spaces may be two manifestations of a more general propensity of the mind to create low-dimensional internal models, and may play a role in analogical reasoning and metaphorical thinking. Finally, I will show some data suggesting that the metaphorical relationship between colors and emotions can be accounted for by the structural alignment of low-dimensional conceptual spaces.
Visual working memory representations are distorted by their use in perceptual comparisons
Visual working memory (VWM) allows us to maintain a small amount of task-relevant information in mind so that we can use them to guide our behavior. Although past studies have successfully characterized its capacity limit and representational quality during maintenance, the consequence of its usage for task-relevant behaviors has been largely unknown. In this talk, I will demonstrate that VWM representations get distorted when they are used for perceptual comparisons with new visual inputs, especially when the inputs are subjectively similar to the VWM representations. Furthermore, I will show that this similarity-induced memory bias (SIMB) occurs for both simple (e.g. , color, shape) and complex stimuli (e.g., real world objects, faces) that are perceptually encoded and retrieved from long-term memory. Given the observed versatility of the SIMB, its implication for other memory distortion phenomena (e.g., distractor-induced distortion, misinformation effect) will be discussed.
The neuroscience of color and what makes primates special
Among mammals, excellent color vision has evolved only in certain non-human primates. And yet, color is often assumed to be just a low-level stimulus feature with a modest role in encoding and recognizing objects. The rationale for this dogma is compelling: object recognition is excellent in grayscale images (consider black-and-white movies, where faces, places, objects, and story are readily apparent). In my talk I will discuss experiments in which we used color as a tool to uncover an organizational plan in inferior temporal cortex (parallel, multistage processing for places, faces, colors, and objects) and a visual-stimulus functional representation in prefrontal cortex (PFC). The discovery of an extensive network of color-biased domains within IT and PFC, regions implicated in high-level object vision and executive functions, compels a re-evaluation of the role of color in behavior. I will discuss behavioral studies prompted by the neurobiology that uncover a universal principle for color categorization across languages, the first systematic study of the color statistics of objects and a chromatic mechanism by which the brain may compute animacy, and a surprising paradoxical impact of memory on face color. Taken together, my talk will put forward the argument that color is not primarily for object recognition, but rather for the assessment of the likely behavioral relevance, or meaning, of the stuff we see.
Mechanisms underlying detection and temporal sensitivity of single-photon responses in the mammalian retina
We have long known that rod and cone signals interact within the retina and can even contribute to color vision, but the extent of these influences has remained unclear. New results with more powerful methods of RNA expression profiling, specific cell labeling, and single-cell recording have provided greater clarity and are showing that rod and cone signals can mix at virtually every level of signal processing. These interactions influence the integration of retinal signals and make an important contribution to visual perception.
The Evolution of Looking and Seeing: New Insights from Colorful Jumping Spiders
During communication, alignment between signals and sensors can be critical. Signals are often best perceived from specific angles, and sensory systems can also exhibit strong directional biases. However, we know little about how animals establish and maintain such signaling alignment during communication. To investigate this, we characterized the spatial dynamics of visual courtship signal- ing in the jumping spider Habronattus pyrrithrix. The male performs forward-facing displays involving complex color and movement patterns, with distinct long- and short-range phases. The female views displays with 2 distinct eye types and can only perceive colors and fine patterns of male displays when they are presented in her frontal field of view. Whether and how courtship interactions pro- duce such alignment between male display and female field of view is unknown. We recorded relative positions and orientations of both actors throughout courtship and established the role of each sex in maintaining signaling alignment. Males always oriented their displays toward the female. However, when females were free to move, male displays were consistently aligned with female princi- pal eyes only during short-range courtship. When female position was fixed, signaling alignment consistently occurred during both phases, suggesting that female movement reduces communication efficacy. When female models were experimentally rotated to face away during courtship, males rarely repositioned themselves to re-align their display. However, males were more likely to present cer- tain display elements after females turned to face them. Thus, although signaling alignment is a function of both sexes, males appear to rely on female behavior for effective communication
The Blurry Beginnings: What nature’s strangest eyes tell us about the evolution of vision
Our study reveals the most elaborate opsin expression patterns ever described in any animal eye. In mantis shrimp, a pugnacious crustacean renowned for its visual sophistication, we found unexpected retinal expression patterns highlighting the potential for cryptic photoreceptor functional diversity, including single photoreceptors that coexpress opsins from different spectral clades and a single opsin with a putative nonvisual function important in color vision. This study demonstrates the evolutionary potential for increasing visual system functional diversity through opsin gene duplication and diversification, as well as changes in patterns of gene coexpression among photoreceptors and retinula cells. These results have significant implications for the function of other visual systems, particularly in arthropods where large numbers of retinally expressed opsins have been documented.
How our biases may influence our study of visual modalities: Two tales from the sea
It has long been appreciated (and celebrated) that certain species have sensory capabilities that humans do not share, for example polarization, ultraviolet, and infrared vision. What is less appreciated however, is that our position as terrestrial human scientists can significantly affect our study of animal senses and signals, even within modalities that we do share. For example, our acute vision can lead us to over-interpret the relevance of fine patterns in animals with coarser vision, and our Cartesian heritage as scientists can lead us to divide sensory modalities into orthogonal parameters (e.g. hue and brightness for color vision), even though this division may not exist within the animal itself. This talk examines two cases from marine visual ecology where a reconsideration of our biases as sharp-eyed Cartesian land mammals can help address questions in visual ecology. The first case examines the enormous variation in visual acuity among animals with image-forming eyes, and focuses on how acknowledging the typically poorer resolving power of animals can help us interpret the function of color patterns in cleaner shrimp and their client fish. The second case examines the how the typical human division of polarized light stimuli into angle and degree of polarization is problematic, and how a physiologically relevant interpretation is both closer to the truth and resolves a number of issues, particularly when considering the propagation of polarized light
The When, Where and What of visual memory formation
The eyes send a continuous stream of about two million nerve fibers to the brain, but only a fraction of this information is stored as visual memories. This talk will detail three neurocomputational models that attempt an understanding how the visual system makes on-the-fly decisions about how to encode that information. First, the STST family of models (Bowman & Wyble 2007; Wyble, Potter, Bowman & Nieuwenstein 2011) proposes mechanisms for temporal segmentation of continuous input. The conclusion of this work is that the visual system has mechanisms for rapidly creating brief episodes of attention that highlight important moments in time, and also separates each episode from temporally adjacent neighbors to benefit learning. Next, the RAGNAROC model (Wyble et al. 2019) describes a decision process for determining the spatial focus (or foci) of attention in a spatiotopic field and the neural mechanisms that provide enhancement of targets and suppression of highly distracting information. This work highlights the importance of integrating behavioral and electrophysiological data to provide empirical constraints on a neurally plausible model of spatial attention. The model also highlights how a neural circuit can make decisions in a continuous space, rather than among discrete alternatives. Finally, the binding pool (Swan & Wyble 2014; Hedayati, O’Donnell, Wyble in Prep) provides a mechanism for selectively encoding specific attributes (i.e. color, shape, category) of a visual object to be stored in a consolidated memory representation. The binding pool is akin to a holographic memory system that layers representations of select latent representations corresponding to different attributes of a given object. Moreover, it can bind features into distinct objects by linking them to token placeholders. Future work looks toward combining these models into a coherent framework for understanding the full measure of on-the-fly attentional mechanisms and how they improve learning.
Human color perception and double-opponent cells in V1 cortex
Beyond energy - an unconventional role of mitochondria in cone photoreceptors
The long-term goal of my research is to study the mammalian retina as a model for the central nervous system (CNS) -- to understand how it functions in physiological conditions, how it is formed, how it breaks down in pathological conditions, and how it can be repaired. I have focused on two research themes: 1) Photoreceptor structure, synapse, circuits, and development, 2) Hibernation and metabolic adaptations in the retina and beyond. As the first neuron of the visual system, photoreceptors are vital for photoreception and transmission of visual signals. I am particularly interested in cone photoreceptors, as they mediate our daylight vision with high resolution color information. Diseases affecting cone photoreceptors compromise visual functions in the central macular area of the human retina and are thus most detrimental to our vision. However, because cones are much less abundant compared to rods in most mammals, they are less well studied. We have used the ground squirrel (GS) as a model system to study cone vision, taking advantage of their unique cone-dominant retina. In particular, we have focused on short-wavelength sensitive cones (S-cones), which are not only essential for color vision, but are also an important origin of signals for biological rhythm, mood and cognitive functions, and the growth of the eye during development. We are studying critical cone synaptic structures – synaptic ribbons, the synaptic connections of S-cones, and the development of S-cones with regard to their specific connections. These works will provide knowledge of normal retinal development and function, which can also be extended to the rest of CNS; for example, the mechanisms of synaptic targeting during development. In addition, such knowledge will benefit the development of optimal therapeutic strategies for regeneration and repair in cases of retinal degenerative disease. Many neurodegenerative diseases, including retinal diseases, are rooted in metabolic stress in neurons and/or glial cells. Using the same GS model, we aim to learn from this hibernating mammal, which possesses an amazing capability to adapt to the extreme metabolic conditions during hibernation. By exploring the mechanisms of such adaptation, we hope to discover novel therapeutic tactics for neurodegenerative diseases.
Simons-Emory Workshop on Neural Dynamics: What could neural dynamics have to say about neural computation, and do we know how to listen?
Speakers will deliver focused 10-minute talks, with periods reserved for broader discussion on topics at the intersection of neural dynamics and computation. Organizer & Moderator: Chethan Pandarinath - Emory University and Georgia Tech Speakers & Discussants: Adrienne Fairhall - U Washington Mehrdad Jazayeri - MIT John Krakauer - John Hopkins Francesca Mastrogiuseppe - Gatsby / UCL Abigail Person - U Colorado Abigail Russo - Princeton Krishna Shenoy - Stanford Saurabh Vyas - Columbia
Colors and objects
Predicting the future from the past: Motion processing in the primate retina
The Manookin lab is investigating the structure and function of neural circuits within the retina and developing techniques for treating blindness. Many blinding diseases, such as retinitis pigmentosa, cause death of the rods and cones, but spare other cell types within the retina. Thus, many techniques for restoring visual function following blindness are based on the premise that other cells within the retina remain viable and capable of performing their various roles in visual processing. There are more than 80 different neuronal types in the human retina and these form the components of the specialized circuits that transform the signals from photoreceptors into a neural code responsible for our perception of color, form, and motion, and thus visual experience. The Manookin laboratory is investigating the function and connectivity of neural circuits in the retina using a variety of techniques including electrophysiology, calcium imaging, and electron microscopy. This knowledge is being used to develop more effective techniques for restoring visual function following blindness.
Mechanism(s) of negative feedback from horizontal cells to cones and its consequence for (color) vision
Vision starts in the retina where images are transformed and coded into neuronal activity relevant for the brain. These coding steps function optimally over a wide range of conditions: from bright day on the beach to a moonless night. Under these very different conditions, specific retinal mechanisms continue to select relevant aspects of the visual world and send this information to the brain. We are studying the neuronal processing involved in these selection and adaptation processes. This knowledge is essential for understanding how the visual system works and forms the basis for research dedicated to restoring vision in blind people.
Cooperative binding of transcription factors is a hallmark of active enhancers
What the eye tells the brain: Visual feature extraction in the mouse retina
Visual processing begins in the retina: within only two synaptic layers, multiple parallel feature channels emerge, which relay highly processed visual information to different parts of the brain. To functionally characterize these feature channels we perform calcium and glutamate population activity recordings at different levels of the mouse retina. This allows following the complete visual signal across consecutive processing stages in a systematic way. In my talk, I will summarize our recent findings on the functional diversity of retinal output channels and how they arise within the retinal network. Specifically, I will talk about the role of inhibition and cell-type specific dendritic processing in generating diverse visual channels. Then, I will focus on how color – a single visual feature – emerges across all retinal processing layers and link our results to behavioral output and the statistics of mouse natural scenes. With our approach, we hope to identify general computational principles of retinal signaling, thereby increasing our understanding of what the eye tells the brain.
Exploiting color space geometry for visual stimulus design across animals
COSYNE 2022
Neural representation of color in the pigeon visual Wulst
COSYNE 2025
Cell-specific simultaneous optogenetic stimulation and inhibition utilizing dual-color striped organic LEDs
FENS Forum 2024
A new family of multicolor genetically encoded indicators for fast, sensitive, and selective in vivo imaging of norepinephrine
FENS Forum 2024
Fused Fiber Photometry 2.0: A flexible and versatile system for multi-color fiber photometry and optogenetic manipulation
FENS Forum 2024
Improved dual-color GRAB sensors for monitoring dopaminergic activity in vivo
FENS Forum 2024
Neural representation of color in the pigeon brain
FENS Forum 2024