Model System
model system
Investigating the Neurobiology and Neurophysiology of Psilocybin Using Drosophila melanogaster as a Model System
Why age-related macular degeneration is a mathematically tractable disease
Among all prevalent diseases with a central neurodegeneration, AMD can be considered the most promising in terms of prevention and early intervention, due to several factors surrounding the neural geometry of the foveal singularity. • Steep gradients of cell density, deployed in a radially symmetric fashion, can be modeled with a difference of Gaussian curves. • These steep gradients give rise to huge, spatially aligned biologic effects, summarized as the Center of Cone Resilience, Surround of Rod Vulnerability. • Widely used clinical imaging technology provides cellular and subcellular level information. • Data are now available at all timelines: clinical, lifespan, evolutionary • Snapshots are available from tissues (histology, analytic chemistry, gene expression) • A viable biogenesis model exists for drusen, the largest population-level intraocular risk factor for progression. • The biogenesis model shares molecular commonality with atherosclerotic cardiovascular disease, for which there has been decades of public health success. • Animal and cell model systems are emerging to test these ideas.
Gut/Body interactions in health and disease
The adult intestine is a major barrier epithelium and coordinator of multi-organ functions. Stem cells constantly repair the intestinal epithelium by adjusting their proliferation and differentiation to tissue intrinsic as well as micro- and macro-environmental signals. How these signals integrate to control intestinal and whole-body homeostasis is largely unknown. Addressing this gap in knowledge is central to an improved understanding of intestinal pathophysiology and its systemic consequences. Combining Drosophila and mammalian model systems my laboratory has discovered fundamental mechanisms driving intestinal regeneration and tumourigenesis and outlined complex inter-organ signaling regulating health and disease. During my talk, I will discuss inter-related areas of research from my lab, including:1- Interactions between the intestine and its microenvironment influencing intestinal regeneration and tumourigenesis. 2- Long-range signals from the intestine impacting whole-body in health and disease.
Spatially-embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings
Brain networks exist within the confines of resource limitations. As a result, a brain network must overcome metabolic costs of growing and sustaining the network within its physical space, while simultaneously implementing its required information processing. To observe the effect of these processes, we introduce the spatially-embedded recurrent neural network (seRNN). seRNNs learn basic task-related inferences while existing within a 3D Euclidean space, where the communication of constituent neurons is constrained by a sparse connectome. We find that seRNNs, similar to primate cerebral cortices, naturally converge on solving inferences using modular small-world networks, in which functionally similar units spatially configure themselves to utilize an energetically-efficient mixed-selective code. As all these features emerge in unison, seRNNs reveal how many common structural and functional brain motifs are strongly intertwined and can be attributed to basic biological optimization processes. seRNNs can serve as model systems to bridge between structural and functional research communities to move neuroscientific understanding forward.
Integrating theory-guided and data-driven approaches for measuring consciousness
Clinical assessment of consciousness is a significant issue, with recent research suggesting some brain-damaged patients who are assessed as unconscious are in fact conscious. Misdiagnosis of consciousness can also be detrimental when it comes to general anaesthesia, causing numerous psychological problems, including post-traumatic stress disorder. Avoiding awareness with overdose of anaesthetics, however, can also lead to cognitive impairment. Currently available objective assessment of consciousness is limited in accuracy or requires expensive equipment with major barriers to translation. In this talk, we will outline our recent theory-guided and data-driven approaches to develop new, optimized consciousness measures that will be robustly evaluated on an unprecedented breadth of high-quality neural data, recorded from the fly model system. We will overcome the subjective-choice problem in data-driven and theory-guided approaches with a comprehensive data analytic framework, which has never been applied to consciousness detection, integrating previously disconnected streams of research in consciousness detection to accelerate the translation of objective consciousness measures into clinical settings.
Active mechanics of sea star oocytes
The cytoskeleton has the remarkable ability to self-organize into active materials which underlie diverse cellular processes ranging from motility to cell division. Actomyosin is a canonical example of an active material, which generates cellularscale contractility in part through the forces exerted by myosin motors on actin filaments. While the molecular players underlying actomyosin contractility have been well characterized, how cellular-scale deformation in disordered actomyosin networks emerges from filament-scale interactions is not well understood. In this talk, I’ll present work done in collaboration with Sebastian Fürthauer and Nikta Fakhri addressing this question in vivo using the meiotic surface contraction wave seen in oocytes of the bat star Patiria miniata as a model system. By perturbing actin polymerization, we find that the cellular deformation rate is a nonmonotonic function of cortical actin density peaked near the wild type density. To understand this, we develop an active fluid model coarse-grained from filament-scale interactions and find quantitative agreement with the measured data. The model makes further predictions, including the surprising prediction that deformation rate decreases with increasing motor concentration. We test these predictions through protein overexpression and find quantitative agreement. Taken together, this work is an important step for bridging the molecular and cellular length scales for cytoskeletal networks in vivo.
Exploring mechanisms of human brain expansion in cerebral organoids
The human brain sets us apart as a species, with its size being one of its most striking features. Brain size is largely determined during development as vast numbers of neurons and supportive glia are generated. In an effort to better understand the events that determine the human brain’s cellular makeup, and its size, we use a human model system in a dish, called cerebral organoids. These 3D tissues are generated from pluripotent stem cells through neural differentiation and a supportive 3D microenvironment to generate organoids with the same tissue architecture as the early human fetal brain. Such organoids are allowing us to tackle questions previously impossible with more traditional approaches. Indeed, our recent findings provide insight into regulation of brain size and neuron number across ape species, identifying key stages of early neural stem cell expansion that set up a larger starting cell number to enable the production of increased numbers of neurons. We are also investigating the role of extrinsic regulators in determining numbers and types of neurons produced in the human cerebral cortex. Overall, our findings are pointing to key, human-specific aspects of brain development and function, that have important implications for neurological disease.
Sensing in Insect Wings
Ali Weber (University of Washington, USA) uses the the hawkmoth as a model system, to investigate how information from a small number of mechanoreceptors on the wings are used in flight control. She employs a combination of experimental and computational techniques to study how these sensors respond during flight and how one might optimally array a set of these sensors to best provide feedback during flight.
Functional Divergence at the Mouse Bipolar Cell Terminal
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.
Retinal neurogenesis and lamination: What to become, where to become it and how to move from there!
The vertebrate retina is an important outpost of the central nervous system, responsible for the perception and transmission of visual information. It consists of five different types of neurons that reproducibly laminate into three layers, a process of crucial importance for the organ’s function. Unsurprisingly, impaired fate decisions as well as impaired neuronal migrations and lamination lead to impaired retinal function. However, how processes are coordinated at the cellular and tissue level and how variable or robust retinal formation is, is currently still underexplored. In my lab, we aim to shed light on these questions from different angles, studying on the one hand differentiation phenomena and their variability and on the other hand the downstream migration and lamination phenomena. We use zebrafish as our main model system due to its excellent possibilities for live imaging and quantitative developmental biology. More recently we also started to use human retinal organoids as a comparative system. We further employ cross disciplinary approaches to address these issues combining work of cell and developmental biology, biomechanics, theory and computer science. Together, this allows us to integrate cell with tissue-wide phenomena and generate an appreciation of the reproducibility and variability of events.
Dynamic spatial processing in insect vision
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.
A biological model system for studying predictive processing
Despite the increasing recognition of predictive processing in circuit neuroscience, little is known about how it may be implemented in cortical circuits. We set out to develop and characterise a biological model system with layer 5 pyramidal cells in the centre. We aim to gain access to prediction and internal model generating processes by controlling, understanding or monitoring everything else: the sensory environment, feed-forward and feed-back inputs, integrative properties, their spiking activity and output. I’ll show recent work from the lab establishing such a model system both in terms of biology as well as tool development.
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).
Functional ultrasound imaging during behavior
The dream of a systems neuroscientist is to be able to unravel neural mechanisms that give rise to behavior. It is increasingly appreciated that behavior involves the concerted distributed activity of multiple brain regions so the focus on single or few brain areas might hinder our understanding. There have been quite a few technological advancements in this domain. Functional ultrasound imaging (fUSi) is an emerging technique that allows us to measure neural activity from medial frontal regions down to subcortical structures up to a depth of 20 mm. It is a method for imaging transient changes in cerebral blood volume (CBV), which are proportional to neural activity changes. It has excellent spatial resolution (~100 μm X 100 μm X 400 μm); its temporal resolution can go down to 100 milliseconds. In this talk, I will present its use in two model systems: marmoset monkeys and rats. In marmoset monkeys, we used it to delineate a social – vocal network involved in vocal communication while in rats, we used it to gain insights into brain wide networks involved in evidence accumulation based decision making. fUSi has the potential to provide an unprecedented access to brain wide dynamics in freely moving animals performing complex behavioral tasks.
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.
Theory of activity-powered interface
Interfaces and membranes are ubiquitous in cellular systems across various scales. From lipid membranes to the interfaces of biomolecular condensates inside the cell, these borders not only protect and segregate the inner components from the outside world, but also are actively participating in mechanical regulation and biochemical reaction of the cell. Being part of a living system, these interfaces (membranes) are usually active and away from equilibrium. Yet, it's still not clear how activity can tweak their equilibrium dynamics. Here, I will introduce a model system to tackle this problem. We put together a passive fluid and an active nematics, and study the behavior of this liquid-liquid interface. Whereas thermal fluctuation of such an interface is too weak to be observed, active stress can easily force the interface to fluctuate, overhang, and even break up. In the presence of a wall, the active phase exhibits superfluid-like behavior: it can climb up walls -- a phenomenon we call activity-induced wetting. I will show how to formulate theories to capture these phenomena, highlighting the nontrivial effects of active stress. Our work not only demonstrates that activity can introduce interesting features to an interface, but also sheds light on controlling interfacial properties using activity.
Bacterial rheotaxis in bulk and at surfaces
Individual bacteria transported in viscous flows, show complex interactions with flows and bounding surfaces resulting from their complex shape as well as their activity. Understanding these transport dynamics is crucial, as they impact soil contamination, transport in biological conducts or catheters, and constitute thus a serious health threat. Here we investigate the trajectories of individual E-coli bacteria in confined geometries under flow, using microfluidic model systems in bulk flows as well as close to surfaces using a novel Langrangian 3D tracking method. Combining experimental observations and modelling we elucidate the origin of upstream swimming, lateral drift or persistent transport along corners. [1] Junot et al, EPL, 126 (2019) 44003 [2] Mathijssen et al. 10:3 (2019) Nature Comm. [3] Figueroa-Morales et al., Soft Matter, 2015,11, 6284-6293 [4] Darnige et al. Review of Scientific Instruments 88, 055106 (2017) [5] Jing et al, Science Advances, 2020; 6 : eabb2012 [6] Figueroa-Morales et al, Sci. Adv. 2020; 6 : eaay0155, 2020, 10.1126/sciadv.aay0155
Flocking through complex environments
The spontaneous collective motion of self-propelled agents is ubiquitous in the natural world, and it often occurs in complex environments, be it bacteria and cells migrating through polymeric extracellular matrix or animal herds and human crowds navigating structured terrains. Much is known about flocking dynamics in pristine backgrounds, but how do spatio-temporal heterogeneities in the environment impact such collective self-organization? I will present two model systems, a colloidal active fluid negotiating disordered obstacles and a confined dense bacterial suspension in a viscoelastic medium, as controllable platforms to explore this question and highlight general mechanisms for active self-organization in complex environments. By combining theory and experiment, I will show how flocks on disordered substrates organize into a novel dynamic vortex glass phase, akin to vortex glasses in dirty superconductors, while the presence of viscoelasticity can calm the otherwise turbulent swarming of bacteria, allowing the emergence of a large scale coherent and even oscillatory vortex when confined on the millimetre scale.
Learning to perceive with new sensory signals
I will begin by describing recent research taking a new, model-based approach to perceptual development. This approach uncovers fundamental changes in information processing underlying the protracted development of perception, action, and decision-making in childhood. For example, integration of multiple sensory estimates via reliability-weighted averaging – widely used by adults to improve perception – is often not seen until surprisingly late into childhood, as assessed by both behaviour and neural representations. This approach forms the basis for a newer question: the scope for the nervous system to deploy useful computations (e.g. reliability-weighted averaging) to optimise perception and action using newly-learned sensory signals provided by technology. Our initial model system is augmenting visual depth perception with devices translating distance into auditory or vibro-tactile signals. This problem has immediate applications to people with partial vision loss, but the broader question concerns our scope to use technology to tune in to any signal not available to our native biological receptors. I will describe initial progress on this problem, and our approach to operationalising what it might mean to adopt a new signal comparably to a native sense. This will include testing for its integration (weighted averaging) alongside the native senses, assessing the level at which this integration happens in the brain, and measuring the degree of ‘automaticity’ with which new signals are used, compared with native perception.
Application of Airy beam light sheet microscopy to examine early neurodevelopmental structures in 3D hiPSC-derived human cortical spheroids
The inability to observe relevant biological processes in vivo significantly restricts human neurodevelopmental research. Advances in appropriate in vitro model systems, including patient-specific human brain organoids and human cortical spheroids (hCSs), offer a pragmatic solution to this issue. In particular, hCSs are an accessible method for generating homogenous organoids of dorsal telencephalic fate, which recapitulate key aspects of human corticogenesis, including the formation of neural rosettes—in vitro correlates of the neural tube. These neurogenic niches give rise to neural progenitors that subsequently differentiate into neurons. Studies differentiating induced pluripotent stem cells (hiPSCs) in 2D have linked atypical formation of neural rosettes with neurodevelopmental disorders such as autism spectrum conditions. Thus far, however, conventional methods of tissue preparation in this field limit the ability to image these structures in three-dimensions within intact hCS or other 3D preparations. To overcome this limitation, we have sought to optimise a methodological approach to process hCSs to maximise the utility of a novel Airy-beam light sheet microscope (ALSM) to acquire high resolution volumetric images of internal structures within hCS representative of early developmental time points.
The collective behavior of the clonal raider ant: computations, patterns, and naturalistic behavior
Colonies of ants and other eusocial insects are superorganisms, which perform sophisticated cognitive-like functions at the level of the group. In my talk I will review our efforts to establish the clonal raider ant Ooceraea biroi as a lab model system for the systematic study of the principles underlying collective information processing in ant colonies. I will use results from two separate projects to demonstrate the potential of this model system: In the first, we analyze the foraging behavior of the species, known as group raiding: a swift offensive response of a colony to the detection of a potential prey by a scout. By using automated behavioral tracking and detailed analysis we show that this behavior is closely related to the army ant mass raid, an iconic collective behavior in which hundreds of thousands of ants spontaneously leave the nest to go hunting, and that the evolutionary transition between the two can be explained by a change in colony size alone. In the second project, we study the emergence of a collective sensory response threshold in a colony. The sensory threshold is a fundamental computational primitive, observed across many biological systems. By carefully controlling the sensory environment and the social structure of the colonies we were able to show that it also appear in a collective context, and that it emerges out of a balance between excitatory and inhibitory interactions between ants. Furthermore, by using a mathematical model we predict that these two interactions can be mapped into known mechanisms of communication in ants. Finally, I will discuss the opportunities for understanding collective behavior that are opening up by the development of methods for neuroimaging and neurocontrol of our ants.
Liquid-liquid phase separation out of equilibrium
Living cells contain millions of enzymes and proteins, which carry out multiple reactions simultaneously. To optimize these processes, cells compartmentalize reactions in membraneless liquid condensates. Certain features of cellular condensates can be explained by principles of liquid-liquid phase separation studied in material science. However, biological condensates exist in the inherently out of equilibrium environment of a living cell, being driven by force-generating microscopic processes. These cellular conditions are fundamentally different than the equilibrium conditions of liquid-liquid phase separation studied in materials science and physics. How condensates function in the active riotous environment of a cell is essential for understanding of cellular functions, as well as to the onset of neurodegenerative diseases. Currently, we lack model systems that enable rigorous studies of these processes. Living cells are too complex for quantitative analysis, while reconstituted equilibrium condensates fail to capture the non-equilibrium environment of biological cells. To bridge this gap, we reconstituted a DNA based membraneless condensates in an active environment that mimics the conditions of a living cell. We combine condensates with a reconstituted network of cytoskeletal filaments and molecular motors, and study how the mechanical interactions change the phase behavior and dynamics of membraneless structures. Studying these composite materials elucidates the fundamental physics rules that govern the behavior of liquid-liquid phase separation away from equilibrium while providing insight into the mechanism of condensate phase separation in cellular environments.
Variability, maintenance and learning in birdsong
The songbird zebra finch is an exemplary model system in which to study trial-and-error learning, as the bird learns its single song gradually through the production of many noisy renditions. It is also a good system in which to study the maintenance of motor skills, as the adult bird actively maintains its song and retains some residual plasticity. Motor learning occurs through the association of timing within the song, represented by sparse firing in nucleus HVC, with motor output, driven by nucleus RA. Here we show through modeling that the small level of observed variability in HVC can result in a network which is more easily able to adapt to change, and is most robust to cell damage or death, than an unperturbed network. In collaboration with Carlos Lois’ lab, we also consider the effect of directly perturbing HVC through viral injection of toxins that affect the firing of projection neurons. Following these perturbations, the song is profoundly affected but is able to almost perfectly recover. We characterize the changes in song acoustics and syntax, and propose models for HVC architecture and plasticity that can account for some of the observed effects. Finally, we suggest a potential role for inputs from nucleus Uva in helping to control timing precision in HVC.
Generalizing theories of cerebellum-like learning
Since the theories of Marr, Ito, and Albus, the cerebellum has provided an attractive well-characterized model system to investigate biological mechanisms of learning. In recent years, theories have been developed that provide a normative account for many features of the anatomy and function of cerebellar cortex and cerebellum-like systems, including the distribution of parallel fiber-Purkinje cell synaptic weights, the expansion in neuron number of the granule cell layer and their synaptic in-degree, and sparse coding by granule cells. Typically, these theories focus on the learning of random mappings between uncorrelated inputs and binary outputs, an assumption that may be reasonable for certain forms of associative conditioning but is also quite far from accounting for the important role the cerebellum plays in the control of smooth movements. I will discuss in-progress work with Marjorie Xie, Samuel Muscinelli, and Kameron Decker Harris generalizing these learning theories to correlated inputs and general classes of smooth input-output mappings. Our studies build on earlier work in theoretical neuroscience as well as recent advances in the kernel theory of wide neural networks. They illuminate the role of pre-expansion structures in processing input stimuli and the significance of sparse granule cell activity. If there is time, I will also discuss preliminary work with Jack Lindsey extending these theories beyond cerebellum-like structures to recurrent networks.
Synaesthesia as a Model System for Understanding Variation in the Human Mind and Brain
During this talk, I will seek to reposition synaesthesia as model system for understanding variation in the construction of the human mind and brain. People with synaesthesia inhabit a remarkable mental world in which numbers can be coloured, words can have tastes, and music is a visual spectacle. Synaesthesia has now been documented for over two hundred years but key questions remain unanswered about why it exists, and what such conditions might mean for theories of the human mind. I will argue that we need to rethink synaesthesia as not just representing exceptional experiences, but as a product of an unusual neurodevelopmental cascade from genes to brain to cognition of which synaesthesia is only one outcome. Rather than synaesthesia being a kind of 'dangling qualia' (atypical experiences attached to a typical mind/brain) it should be thought of as unusual experiences that accompany an unusual mind/brain. Specifically, differences in the brains of synaesthetes support a distinctive way of thinking (enhanced memory, imagery etc.) and may also predispose towards particular clinical vulnerabilities. It is this neurodiverse phenotype that is an important object of study in its own right and may explain any adaptive value for having synaesthesia.
Neuroendocrine control of female germline stem cell increase in the fruit fly Drosophila melanogaster
The development and maintenance of many tissues are fueled by stem cells. Many studies have addressed how intrinsic factors and local signals from neighboring niche cells maintain stem cell identity and proliferative potential. In contrast, it is poorly understood how stem cell activity is controlled by systemic, tissue-extrinsic signals in response to environmental cues and changes in physiological status. Our laboratory has been focusing on female germline stem cells (fGSCs) in the fruit fly Drosophila melanogaster as a model system and studying neuroendocrine control of fGSC increase. The increase of fGSCs is induced by mating stimuli. We have previously reported that mating-induced fGSC increase is regulated by the ovarian steroid hormone and the enteroendocrine peptide hormone [Ameku & Niwa, PLOS Genetics 2016; Ameku et al. PLOS Biology 2018]. In this presentation, we report our recent finding showing a neuronal mechanism of mating-induced fGSC increase. We first found that the ovarian somatic cell-specific RNAi for Oamb, a G protein-coupled receptor for the neurotransmitter octopamine, failed to induce fGSC proliferation after mating. Both ex vivo and in vivo experiments revealed that octopamine and Oamb positively regulated mating-induced fGSC increase via intracellular Ca 2+ signaling. We also found that a small subset of octopaminergic neurons directly projected to the ovary, and neuronal activity of these neurons was required for mating-induced fGSC increase. This study provides a mechanism describing how the neuronal system controls stem cell behavior through stem cell niche signaling [Yoshinari et al. eLife 2020]. Here I will also present our recent data showing how the neuroendocrine system couples fGSC behavior to multiple environmental cues, such as mating and nutrition.
Neuron-glia interactions in synapse degeneration in Alzheimer's disease
Tara Spires-Jones’ research focuses on the mechanisms and reversibility of neurodegeneration in Alzheimer’s disease, other degenerative brain diseases, and ageing. The objective of her research group is to understand why synapses and neurons become dysfunctional and die in these diseases in order to develop effective therapeutic strategies. Her work has shown that soluble forms of the pathological proteins amyloid beta and tau contribute to synapse degeneration, and that lowering levels of these proteins can prevent and reverse phenotypes in model systems. Further, she has pioneered high-resolution imaging techniques in human post-mortem brain and found evidence that these proteins accumulate in synapses in human disease.
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.
Circuit mechanisms underlying the dynamic control of cortical processing by subcortical neuromodulators
Behavioral states such as arousal and attention can have profound effects on sensory processing, determining how – sometimes whether – a stimulus is processed. This state-dependence is believed to arise, at least in part, as a result of inputs to cortex from subcortical structures that release neuromodulators such as acetylcholine, noradrenaline, and serotonin, often non-synaptically. The mechanisms that underlie the interaction between these “wireless” non-synaptic signals and the “wired” cortical circuit are not well understood. Furthermore, neuromodulatory signaling is traditionally considered broad in its impact across cortex (within a species) and consistent in its form and function across species (at least in mammals). The work I will present approaches the challenge of understanding neuromodulatory action in the cortex from a number of angles: anatomy, physiology, pharmacology, and chemistry. The overarching goal of our effort is to elucidate the mechanisms behind local neuromodulation in the cortex of non-human primates, and to reveal differences in structure and function across cortical model systems.
Shaping colloidal bananas to reveal biaxial, splay-bend nematic, and smectic phases
Colloidal dispersions of rod-like particles are widely accepted as convenient model systems to study the phase behavior of liquid-crystal forming systems, commonly found in LCDs. This is due to the fact that colloidal rods exhibit analogous phase behavior to that of elongated molecules, while they can be directly observed by optical microscopy. Recently, there has been a surge of interest in the liquid crystalline behaviour of so-called bent-core, or banana-shaped, molecules. This is due to their ability to form exotic biaxial nematic phases such as the twist-bend and splay-bend nematic phase, which may be of particular interest inherent to their fast switching response in LCDs. Here, we develop model “banana-shaped” colloidal particles with tunable dimensions and curvature, whose structure and dynamics are accessible at the particle level. By heating initially straight rods made of SU-8 photoresist, we induce a controllable shape deformation that causes the rods to buckle into banana-shaped particles. We elucidate the phase behavior of differently curved colloidal bananas using confocal microscopy. Although highly curved bananas only form isotropic phases, less curved bananas exhibit very rich phase behavior, including biaxial nematic phases, polar and antipolar smectic-like phases, and even the long-predicted, elusive splay-bend nematic phase.
Glia neuron metabolic interactions in Drosophila
To function properly, the nervous system consumes vast amounts of energy, which is mostly provided by carbohydrate metabolism. Neurons are very sensitive to changes in the extracellular fluid surrounding them, which necessitated shielding of the nervous system from fluctuating solute concentrations in circulation. This is achieved by the blood-brain barrier (BBB) that prevents paracellular diffusion of solutes into the nervous system. This in turn also means that all nutrients that are needed e.g. for sufficient energy supply need to be transported over the BBB. We use Drosophila as a model system to better understand the metabolic homeostasis in the central nervous system. Glial cells play essential roles in both nutrient uptake and neural energy metabolism. Carbohydrate transport over the glial BBB is well-regulated and can be adapted to changes in carbohydrate availability. Furthermore, Drosophila glial cell are highly glycolytic cells that support the rather oxidative metabolism of neurons. Upon perturbations of carbohydrate metabolism, the glial cells prove to be metabolically very flexible and able to adapt to changing circumstances. I will summarize what we know about carbohydrate transport at the Drosophila BBB and about the metabolic coupling between neurons and glial cells. Our data shows that many basic features of neural metabolism are well conserved between the fly and mammals.
Design Principles of Living Matter
In this talk, I will describe my lab’s recent efforts to understand the design principles of the active, soft materials that drive cell morphogenesis. In particular, we are interested in how collections of myosin II motors and actin polymers generate, relax, sense and adapt to mechanical force. I will discuss how motor-filament interactions lead to either distributed extensile or contractile stresses as the mechanics of the system changes from fluid to solid. Using optical control of motors, we are now exploring how spatially structured stress can be used to drive local flows and motion. If time, I will also describe how feedbacks between local geometry and activity can be harnessed to drive morphogenetic changes in model systems.
Swimming in the third domain: archaeal extremophiles
Archaea have evolved to survive in some of the most extreme environments on earth. Life in extreme, nutrient-poor conditions gives the opportunity to probe fundamental energy limitations on movement and response to stimuli, two essential markers of living systems. Here we use three-dimensional holographic microscopy and computer simulations to show that halophilic archaea achieve chemotaxis with power requirements one hundred-fold lower than common eubacterial model systems. Their swimming direction is stabilised by their flagella (archaella), enhancing directional persistence in a manner similar to that displayed by eubacteria, albeit with a different motility apparatus. Our experiments and simulations reveal that the cells are capable of slow but deterministic chemotaxis up a chemical gradient, in a biased random walk at the thermodynamic limit.
Mechanisms of pathogenesis in the tauopathies
The distribution of pathological tau in the brain of patients with AD is highly predicable, and as disease worsens, it spreads transynaptically from initial regions of vulnerability. The reason why only some neurons are vulnerable to the accumulation and propagation of pathological forms of tau, and the mechanisms by which tauopathy spreads through the brain are not well understood. Using a combination of immunohistochemistry and computational analysis we have examined pathway differences between vulnerable and resistant neurons. How tau spreads across a synapse has been examined in vitro using different model systems. Our data show that dysregulation of tau homeostasis determines the cellular and regional vulnerability of specific neurons to tau pathology (H. Fu et al. 2019. Nat. Neuro. 22 (1):47-56) and that deficits in tau homeostasis can exacerbate tau accumulation and propagation. Aging appears to impact similar neuronal populations. Mechanisms and consequences of abnormal tau accumulation within neurons, its transfer between cells, pathology propagation and therapeutic opportunities will be discussed.
How the brain comes to balance: Development of postural stability and its neural architecture in larval zebrafish
Maintaining posture is a vital challenge for all freely-moving organisms. As animals grow, their relationship to destabilizing physical forces changes. How does the nervous system deal with this ongoing challenge? Vertebrates use highly conserved vestibular reflexes to stabilize the body. We established the larval zebrafish as a new model system to understand the development of the vestibular reflexes responsible for balance. In this talk, I will begin with the biophysical challenges facing baby fish as they learn to swim. I’ll briefly review published work by David Ehrlich, Ph.D., establishing a fundamental relationship between postural stability and locomotion. The bulk of the talk will highlight unpublished work by Kyla Hamling. She discovered that a small (~50) population of molecularly-defined brainstem neurons called vestibulo-spinal cells act as a nexus for postural development. Her loss-of-function experiments show that these neurons contribute more to postural stability as animals grow older. I’ll end with brief highlights from her ongoing work examining tilt-evoked responses of these neurons using 2-photon imaging and the consequences of downstream activity in the spinal cord using single-objective light-sheet (SCAPE) microscopy
Developmental origin of individuality in brain and behaviour
The “Nature versus Nurture” debate on the origin of behaviour has long been dominated by a genome versus experience dichotomy. However, evidence that genetically identical individuals kept under identical conditions are behaviourally different is incontrovertible. Where might such individuality come from? Neither genes nor the environment directly encode behaviour. They encode or influence processes, notably the development of neuronal circuits, that in turn control behaviour. An understanding of how neuronal circuits develop and function at the individual organism level is therefore essential for understanding the origin of individuals. I will discuss our efforts to address this issue over the past decade using the Drosophila fruit fly as a model system.
Diverse synaptic mechanisms underlie visual signaling in the retina
Our laboratory seeks to understand how neural circuits receive, compute, encode and transmit information. More specifically, we’d like to learn what biophysical and morphological features equip synapses, neurons and networks to perform these tasks. The retina is a model system for the study of neuronal information processing: We can deliver precisely defined physiological stimuli and record responses from many different cell types at various points within the network; in addition, retinal circuitry is particularly well understood, enabling us to interpret more directly the impact of synaptic and cellular mechanisms on circuit function. I will present recent experiments in the lab that exploit these advantages to examine how synapses and neurons within retinal amacrine cell circuits perform specific visual computations.
Targeting norepinephrine neurons of the locus coeruleus: A comparison of model systems and strategies
FENS Forum 2024