@phdthesis{15338, author = {Ernst, Doris}, title = {{The world of Pokemon}}, year = {2026}, } @phdthesis{15346, abstract = {I tried my best!}, author = {Ernst, Doris}, title = {{The science within Pokemon}}, year = {2026}, } @phdthesis{14821, author = {Chiossi, Heloisa}, issn = {2663 - 337X}, pages = {89}, publisher = {Institute of Science and Technology Austria}, title = {{Adaptive hierarchical representations in the hippocampus}}, doi = {10.15479/at:ista:14821}, year = {2024}, } @phdthesis{15020, abstract = {This thesis consists of four distinct pieces of work within theoretical biology, with two themes in common: the concept of optimization in biological systems, and the use of information-theoretic tools to quantify biological stochasticity and statistical uncertainty. Chapter 2 develops a statistical framework for studying biological systems which we believe to be optimized for a particular utility function, such as retinal neurons conveying information about visual stimuli. We formalize such beliefs as maximum-entropy Bayesian priors, constrained by the expected utility. We explore how such priors aid inference of system parameters with limited data and enable optimality hypothesis testing: is the utility higher than by chance? Chapter 3 examines the ultimate biological optimization process: evolution by natural selection. As some individuals survive and reproduce more successfully than others, populations evolve towards fitter genotypes and phenotypes. We formalize this as accumulation of genetic information, and use population genetics theory to study how much such information can be accumulated per generation and maintained in the face of random mutation and genetic drift. We identify the population size and fitness variance as the key quantities that control information accumulation and maintenance. Chapter 4 reuses the concept of genetic information from Chapter 3, but from a different perspective: we ask how much genetic information organisms actually need, in particular in the context of gene regulation. For example, how much information is needed to bind transcription factors at correct locations within the genome? Population genetics provides us with a refined answer: with an increasing population size, populations achieve higher fitness by maintaining more genetic information. Moreover, regulatory parameters experience selection pressure to optimize the fitness-information trade-off, i.e. minimize the information needed for a given fitness. This provides an evolutionary derivation of the optimization priors introduced in Chapter 2. Chapter 5 proves an upper bound on mutual information between a signal and a communication channel output (such as neural activity). Mutual information is an important utility measure for biological systems, but its practical use can be difficult due to the large dimensionality of many biological channels. Sometimes, a lower bound on mutual information is computed by replacing the high-dimensional channel outputs with decodes (signal estimates). Our result provides a corresponding upper bound, provided that the decodes are the maximum posterior estimates of the signal.}, author = {Hledik, Michal}, issn = {2663 - 337X}, keywords = {Theoretical biology, Optimality, Evolution, Information}, pages = {158}, publisher = {Institute of Science and Technology Austria}, title = {{Genetic information and biological optimization}}, doi = {10.15479/at:ista:15020}, year = {2024}, } @phdthesis{14711, abstract = {In nature, different species find their niche in a range of environments, each with its unique characteristics. While some thrive in uniform (homogeneous) landscapes where environmental conditions stay relatively consistent across space, others traverse the complexities of spatially heterogeneous terrains. Comprehending how species are distributed and how they interact within these landscapes holds the key to gaining insights into their evolutionary dynamics while also informing conservation and management strategies. For species inhabiting heterogeneous landscapes, when the rate of dispersal is low compared to spatial fluctuations in selection pressure, localized adaptations may emerge. Such adaptation in response to varying selection strengths plays an important role in the persistence of populations in our rapidly changing world. Hence, species in nature are continuously in a struggle to adapt to local environmental conditions, to ensure their continued survival. Natural populations can often adapt in time scales short enough for evolutionary changes to influence ecological dynamics and vice versa, thereby creating a feedback between evolution and demography. The analysis of this feedback and the relative contributions of gene flow, demography, drift, and natural selection to genetic variation and differentiation has remained a recurring theme in evolutionary biology. Nevertheless, the effective role of these forces in maintaining variation and shaping patterns of diversity is not fully understood. Even in homogeneous environments devoid of local adaptations, such understanding remains elusive. Understanding this feedback is crucial, for example in determining the conditions under which extinction risk can be mitigated in peripheral populations subject to deleterious mutation accumulation at the edges of species’ ranges as well as in highly fragmented populations. In this thesis we explore both uniform and spatially heterogeneous metapopulations, investigating and providing theoretical insights into the dynamics of local adaptation in the latter and examining the dynamics of load and extinction as well as the impact of joint ecological and evolutionary (eco-evolutionary) dynamics in the former. The thesis is divided into 5 chapters. Chapter 1 provides a general introduction into the subject matter, clarifying concepts and ideas used throughout the thesis. In chapter 2, we explore how fast a species distributed across a heterogeneous landscape adapts to changing conditions marked by alterations in carrying capacity, selection pressure, and migration rate. In chapter 3, we investigate how migration selection and drift influences adaptation and the maintenance of variation in a metapopulation with three habitats, an extension of previous models of adaptation in two habitats. We further develop analytical approximations for the critical threshold required for polymorphism to persist. The focus of chapter 4 of the thesis is on understanding the interplay between ecology and evolution as coupled processes. We investigate how eco-evolutionary feedback between migration, selection, drift, and demography influences eco-evolutionary outcomes in marginal populations subject to deleterious mutation accumulation. Using simulations as well as theoretical approximations of the coupled dynamics of population size and allele frequency, we analyze how gene flow from a large mainland source influences genetic load and population size on an island (i.e., in a marginal population) under genetically realistic assumptions. Analyses of this sort are important because small isolated populations, are repeatedly affected by complex interactions between ecological and evolutionary processes, which can lead to their death. Understanding these interactions can therefore provide an insight into the conditions under which extinction risk can be mitigated in peripheral populations thus, contributing to conservation and restoration efforts. Chapter 5 extends the analysis in chapter 4 to consider the dynamics of load (due to deleterious mutation accumulation) and extinction risk in a metapopulation. We explore the role of gene flow, selection, and dominance on load and extinction risk and further pinpoint critical thresholds required for metapopulation persistence. Overall this research contributes to our understanding of ecological and evolutionary mechanisms that shape species’ persistence in fragmented landscapes, a crucial foundation for successful conservation efforts and biodiversity management.}, author = {Olusanya, Oluwafunmilola O}, issn = {2663 - 337X}, pages = {183}, publisher = {Institute of Science and Technology Austria}, title = {{Local adaptation, genetic load and extinction in metapopulations}}, doi = {10.15479/at:ista:14711}, year = {2024}, } @phdthesis{12470, abstract = {The brain is an exceptionally sophisticated organ consisting of billions of cells and trillions of connections that orchestrate our cognition and behavior. To decode its complex connectivity, it is pivotal to disentangle its intricate architecture spanning from cm-sized circuits down to tens of nm-small synapses. To achieve this goal, I developed CATS – Comprehensive Analysis of nervous Tissue across Scales, a versatile toolbox for obtaining a holistic view of nervous tissue context with (superresolution) fluorescence microscopy. CATS combines comprehensive labeling of the extracellular space, that is compatible with chemical fixation, with information on molecular markers, superresolved data acquisition and machine-learning based data analysis for segmentation and synapse identification. I used CATS to analyze key features of nervous tissue connectivity, ranging from whole tissue architecture, neuronal in- and output-fields, down to synapse morphology. Focusing on the hippocampal circuitry, I quantified synaptic transmission properties of mossy fiber boutons and analyzed the connectivity pattern of dentate gyrus granule cells with CA3 pyramidal neurons. This shows that CATS is a viable tool to study hallmarks of neuronal connectivity with light microscopy.}, author = {Michalska, Julia M}, isbn = { 978-3-99078-026-8}, issn = {2663-337X}, pages = {201}, publisher = {Institute of Science and Technology Austria}, title = {{A versatile toolbox for the comprehensive analysis of nervous tissue organization with light microscopy}}, doi = {10.15479/at:ista:12470}, year = {2023}, } @phdthesis{12491, abstract = {The extracellular matrix (ECM) is a hydrated and complex three-dimensional network consisting of proteins, polysaccharides, and water. It provides structural scaffolding for the cells embedded within it and is essential in regulating numerous physiological processes, including cell migration and proliferation, wound healing, and stem cell fate. Despite extensive study, detailed structural knowledge of ECM components in physiologically relevant conditions is still rudimentary. This is due to methodological limitations in specimen preparation protocols which are incompatible with keeping large samples, such as the ECM, in their native state for subsequent imaging. Conventional electron microscopy (EM) techniques rely on fixation, dehydration, contrasting, and sectioning. This results in the alteration of a highly hydrated environment and the potential introduction of artifacts. Other structural biology techniques, such as nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography, allow high-resolution analysis of protein structures but only work on homogenous and purified samples, hence lacking contextual information. Currently, no approach exists for the ultrastructural and structural study of extracellular components under native conditions in a physiological, 3D environment. In this thesis, I have developed a workflow that allows for the ultrastructural analysis of the ECM in near-native conditions at molecular resolution. The developments I introduced include implementing a novel specimen preparation workflow for cell-derived matrices (CDMs) to render them compatible with ion-beam milling and subsequent high-resolution cryo-electron tomography (ET). To this end, I have established protocols to generate CDMs grown over several weeks on EM grids that are compatible with downstream cryo-EM sample preparation and imaging techniques. Characterization of these ECMs confirmed that they contain essential ECM components such as collagen I, collagen VI, and fibronectin I in high abundance and hence represent a bona fide biologically-relevant sample. I successfully optimized vitrification of these specimens by testing various vitrification techniques and cryoprotectants. In order to obtain high-resolution molecular insights into the ultrastructure and organization of CDMs, I established cryo-focused ion beam scanning electron microscopy (FIBSEM) on these challenging and complex specimens. I explored different approaches for the creation of thin cryo-lamellae by FIB milling and succeeded in optimizing the cryo-lift-out technique, resulting in high-quality lamellae of approximately 200 nm thickness. High-resolution Cryo-ET of these lamellae revealed for the first time the architecture of native CDM in the context of matrix-secreting cells. This allowed for the in situ visualization of fibrillar matrix proteins such as collagen, laying the foundation for future structural and ultrastructural characterization of these proteins in their near-native environment. In summary, in this thesis, I present a novel workflow that combines state-of-the-art cryo-EM specimen preparation and imaging technologies to permit characterization of the ECM, an important tissue component in higher organisms. This innovative and highly versatile workflow will enable addressing far-reaching questions on ECM architecture, composition, and reciprocal ECM-cell interactions.}, author = {Zens, Bettina}, isbn = {978-3-99078-027-5}, issn = {2663-337X}, keywords = {cryo-EM, cryo-ET, FIB milling, method development, FIBSEM, extracellular matrix, ECM, cell-derived matrices, CDMs, cell culture, high pressure freezing, HPF, structural biology, tomography, collagen}, pages = {187}, publisher = {Institute of Science and Technology Austria}, title = {{Ultrastructural characterization of natively preserved extracellular matrix by cryo-electron tomography}}, doi = {10.15479/at:ista:12491}, year = {2023}, } @phdthesis{12531, abstract = {All visual experiences of the vertebrates begin with light being converted into electrical signals by the eye retina. Retinal ganglion cells (RGCs) are the neurons of the innermost layer of the mammal retina, and they transmit visual information to the rest of the brain. It has been shown that RGCs vary in their morphology and genetic profiles, moreover they can be unambiguously grouped into subtypes that share the same morphological and/or molecular properties. However, in terms of RGCs function, it remains unclear how many distinct types there are and what response properties their typology relies on. Even given the recent studies that successfully classified RGCs in a patch of the retina [1] and in scotopic conditions [2], the question remains whether the found subtypes persist across the entire retina. In this work, using a novel imaging method, we show that, when sampled from a large portion of the retina, RGCs can not be clearly divided into functional subtypes. We found that in photopic conditions, which implies more prominent natural scene statistic differences across the visual field, response properties can be exhibited by cells differently depending on their location in the retina, which leads to formation of a gradient of features rather than distinct classes. This finding suggests that RGCs follow a global organization across the visual field of the animal, adapting each RGC subtype to the requirements imposed by the natural scene statistics.}, author = {Kirillova, Kseniia}, issn = {2791-4585}, pages = {46}, publisher = {Institute of Science and Technology Austria}, title = {{Panoramic functional gradients across the mouse retina}}, doi = {10.15479/at:ista:12531}, year = {2023}, } @phdthesis{12716, abstract = {The process of detecting and evaluating sensory information to guide behaviour is termed perceptual decision-making (PDM), and is critical for the ability of an organism to interact with its external world. Individuals with autism, a neurodevelopmental condition primarily characterised by social and communication difficulties, frequently exhibit altered sensory processing and PDM difficulties are widely reported. Recent technological advancements have pushed forward our understanding of the genetic changes accompanying this condition, however our understanding of how these mutations affect the function of specific neuronal circuits and bring about the corresponding behavioural changes remains limited. Here, we use an innate PDM task, the looming avoidance response (LAR) paradigm, to identify a convergent behavioural abnormality across three molecularly distinct genetic mouse models of autism (Cul3, Setd5 and Ptchd1). Although mutant mice can rapidly detect threatening visual stimuli, their responses are consistently delayed, requiring longer to initiate an appropriate response than their wild-type siblings. Mutant animals show abnormal adaptation in both their stimulus- evoked escape responses and exploratory dynamics following repeated stimulus presentations. Similarly delayed behavioural responses are observed in wild-type animals when faced with more ambiguous threats, suggesting the mutant phenotype could arise from a dysfunction in the flexible control of this PDM process. Our knowledge of the core neuronal circuitry mediating the LAR facilitated a detailed dissection of the neuronal mechanisms underlying the behavioural impairment. In vivo extracellular recording revealed that visual responses were unaffected within a key brain region for the rapid processing of visual threats, the superior colliculus (SC), indicating that the behavioural delay was unlikely to originate from sensory impairments. Delayed behavioural responses were recapitulated in the Setd5 model following optogenetic stimulation of the excitatory output neurons of the SC, which are known to mediate escape initiation through the activation of cells in the underlying dorsal periaqueductal grey (dPAG). In vitro patch-clamp recordings of dPAG cells uncovered a stark hypoexcitability phenotype in two out of the three genetic models investigated (Setd5 and Ptchd1), that in Setd5, is mediated by the misregulation of voltage-gated potassium channels. Overall, our results show that the ability to use visual information to drive efficient escape responses is impaired in three diverse genetic mouse models of autism and that, in one of the models studied, this behavioural delay likely originates from differences in the intrinsic excitability of a key subcortical node, the dPAG. Furthermore, this work showcases the use of an innate behavioural paradigm to mechanistically dissect PDM processes in autism.}, author = {Burnett, Laura}, issn = {2663-337X}, pages = {178}, publisher = {Institute of Science and Technology Austria}, title = {{To flee, or not to flee? Using innate defensive behaviours to investigate rapid perceptual decision-making through subcortical circuits in mouse models of autism}}, doi = {10.15479/at:ista:12716}, year = {2023}, } @phdthesis{12726, abstract = {Most motions of many-body systems at any scale in nature with sufficient degrees of freedom tend to be chaotic; reaching from the orbital motion of planets, the air currents in our atmosphere, down to the water flowing through our pipelines or the movement of a population of bacteria. To the observer it is therefore intriguing when a moving collective exhibits order. Collective motion of flocks of birds, schools of fish or swarms of self-propelled particles or robots have been studied extensively over the past decades but the mechanisms involved in the transition from chaos to order remain unclear. Here, the interactions, that in most systems give rise to chaos, sustain order. In this thesis we investigate mechanisms that preserve, destabilize or lead to the ordered state. We show that endothelial cells migrating in circular confinements transition to a collective rotating state and concomitantly synchronize the frequencies of nucleating actin waves within individual cells. Consequently, the frequency dependent cell migration speed uniformizes across the population. Complementary to the WAVE dependent nucleation of traveling actin waves, we show that in leukocytes the actin polymerization depending on WASp generates pushing forces locally at stationary patches. Next, in pipe flows, we study methods to disrupt the self–sustaining cycle of turbulence and therefore relaminarize the flow. While we find in pulsating flow conditions that turbulence emerges through a helical instability during the decelerating phase. Finally, we show quantitatively in brain slices of mice that wild-type control neurons can compensate the migratory deficits of a genetically modified neuronal sub–population in the developing cortex.}, author = {Riedl, Michael}, issn = {2663-337X}, pages = {260}, publisher = {Institute of Science and Technology Austria}, title = {{Synchronization in collectively moving active matter}}, doi = {10.15479/at:ista:12726}, year = {2023}, } @phdthesis{12732, abstract = {Nonergodic systems, whose out-of-equilibrium dynamics fail to thermalize, provide a fascinating research direction both for fundamental reasons and for application in state of the art quantum devices. Going beyond the description of statistical mechanics, ergodicity breaking yields a new paradigm in quantum many-body physics, introducing novel phases of matter with no counterpart at equilibrium. In this Thesis, we address different open questions in the field, focusing on disorder-induced many-body localization (MBL) and on weak ergodicity breaking in kinetically constrained models. In particular, we contribute to the debate about transport in kinetically constrained models, studying the effect of $U(1)$ conservation and inversion-symmetry breaking in a family of quantum East models. Using tensor network techniques, we analyze the dynamics of large MBL systems beyond the limit of exact numerical methods. In this setting, we approach the debated topic of the coexistence of localized and thermal eigenstates separated by energy thresholds known as many-body mobility edges. Inspired by recent experiments, our work further investigates the localization of a small bath induced by the coupling to a large localized chain, the so-called MBL proximity effect. In the first Chapter, we introduce a family of particle-conserving kinetically constrained models, inspired by the quantum East model. The system we study features strong inversion-symmetry breaking, due to the nature of the correlated hopping. We show that these models host so-called quantum Hilbert space fragmentation, consisting of disconnected subsectors in an entangled basis, and further provide an analytical description of this phenomenon. We further probe its effect on dynamics of simple product states, showing revivals in fidelity and local observalbes. The study of dynamics within the largest subsector reveals an anomalous transient superdiffusive behavior crossing over to slow logarithmic dynamics at later times. This work suggests that particle conserving constrained models with inversion-symmetry breaking realize new universality classes of dynamics and invite their further theoretical and experimental studies. Next, we use kinetic constraints and disorder to design a model with many-body mobility edges in particle density. This feature allows to study the dynamics of localized and thermal states in large systems beyond the limitations of previous studies. The time-evolution shows typical signatures of localization at small densities, replaced by thermal behavior at larger densities. Our results provide evidence in favor of the stability of many-body mobility edges, which was recently challenged by a theoretical argument. To support our findings, we probe the mechanism proposed as a cause of delocalization in many-body localized systems with mobility edges suggesting its ineffectiveness in the model studied. In the last Chapter of this Thesis, we address the topic of many-body localization proximity effect. We study a model inspired by recent experiments, featuring Anderson localized coupled to a small bath of free hard-core bosons. The interaction among the two particle species results in non-trivial dynamics, which we probe using tensor network techniques. Our simulations show convincing evidence of many-body localization proximity effect when the bath is composed by a single free particle and interactions are strong. We furthter observe an anomalous entanglement dynamics, which we explain through a phenomenological theory. Finally, we extract highly excited eigenstates of large systems, providing supplementary evidence in favor of our findings.}, author = {Brighi, Pietro}, issn = {2663-337X}, pages = {158}, publisher = {Institute of Science and Technology Austria}, title = {{Ergodicity breaking in disordered and kinetically constrained quantum many-body systems}}, doi = {10.15479/at:ista:12732}, year = {2023}, } @phdthesis{12781, abstract = {Most energy in humans is produced in form of ATP by the mitochondrial respiratory chain consisting of several protein assemblies embedded into lipid membrane (complexes I-V). Complex I is the first and the largest enzyme of the respiratory chain which is essential for energy production. It couples the transfer of two electrons from NADH to ubiquinone with proton translocation across bacterial or inner mitochondrial membrane. The coupling mechanism between electron transfer and proton translocation is one of the biggest enigma in bioenergetics and structural biology. Even though the enzyme has been studied for decades, only recent technological advances in cryo-EM allowed its extensive structural investigation. Complex I from E.coli appears to be of special importance because it is a perfect model system with a rich mutant library, however the structure of the entire complex was unknown. In this thesis I have resolved structures of the minimal complex I version from E. coli in different states including reduced, inhibited, under reaction turnover and several others. Extensive structural analyses of these structures and comparison to structures from other species allowed to derive general features of conformational dynamics and propose a universal coupling mechanism. The mechanism is straightforward, robust and consistent with decades of experimental data available for complex I from different species. Cyanobacterial NDH (cyanobacterial complex I) is a part of broad complex I superfamily and was studied as well in this thesis. It plays an important role in cyclic electron transfer (CET), during which electrons are cycled within PSI through ferredoxin and plastoquinone to generate proton gradient without NADPH production. Here, I solved structure of NDH and revealed additional state, which was not observed before. The novel “resting” state allowed to propose the mechanism of CET regulation. Moreover, conformational dynamics of NDH resembles one in complex I which suggest more broad universality of the proposed coupling mechanism. In summary, results presented here helped to interpret decades of experimental data for complex I and contributed to fundamental mechanistic understanding of protein function. }, author = {Kravchuk, Vladyslav}, isbn = {978-3-99078-029-9}, issn = {2663-337X}, pages = {127}, publisher = {Institute of Science and Technology Austria}, title = {{Structural and mechanistic study of bacterial complex I and its cyanobacterial ortholog}}, doi = {10.15479/at:ista:12781}, year = {2023}, } @phdthesis{12800, abstract = {The evolutionary processes that brought about today’s plethora of living species and the many billions more ancient ones all underlie biology. Evolutionary pathways are neither directed nor deterministic, but rather an interplay between selection, migration, mutation, genetic drift and other environmental factors. Hybrid zones, as natural crossing experiments, offer a great opportunity to use cline analysis to deduce different evolutionary processes - for example, selection strength. Theoretical cline models, largely assuming uniform distribution of individuals, often lack the capability of incorporating population structure. Since in reality organisms mostly live in patchy distributions and their dispersal is hardly ever Gaussian, it is necessary to unravel the effect of these different elements of population structure on cline parameters and shape. In this thesis, I develop a simulation inspired by the A. majus hybrid zone of a single selected locus under frequency dependent selection. This simulation enables us to untangle the effects of different elements of population structure as for example a low-density center and long-range dispersal. This thesis is therefore a first step towards theoretically untangling the effects of different elements of population structure on cline parameters and shape. }, author = {Julseth, Mara}, issn = {2791-4585}, pages = {21}, publisher = {Institute of Science and Technology Austria}, title = {{The effect of local population structure on genetic variation at selected loci in the A. majus hybrid zone}}, doi = {10.15479/at:ista:12800}, year = {2023}, } @phdthesis{12809, abstract = {Understanding the mechanisms of learning and memory formation has always been one of the main goals in neuroscience. Already Pavlov (1927) in his early days has used his classic conditioning experiments to study the neural mechanisms governing behavioral adaptation. What was not known back then was that the part of the brain that is largely responsible for this type of associative learning is the cerebellum. Since then, plenty of theories on cerebellar learning have emerged. Despite their differences, one thing they all have in common is that learning relies on synaptic and intrinsic plasticity. The goal of my PhD project was to unravel the molecular mechanisms underlying synaptic plasticity in two synapses that have been shown to be implicated in motor learning, in an effort to understand how learning and memory formation are processed in the cerebellum. One of the earliest and most well-known cerebellar theories postulates that motor learning largely depends on long-term depression at the parallel fiber-Purkinje cell (PC-PC) synapse. However, the discovery of other types of plasticity in the cerebellar circuitry, like long-term potentiation (LTP) at the PC-PC synapse, potentiation of molecular layer interneurons (MLIs), and plasticity transfer from the cortex to the cerebellar/ vestibular nuclei has increased the popularity of the idea that multiple sites of plasticity might be involved in learning. Still a lot remains unknown about the molecular mechanisms responsible for these types of plasticity and whether they occur during physiological learning. In the first part of this thesis we have analyzed the variation and nanodistribution of voltagegated calcium channels (VGCCs) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid type glutamate receptors (AMPARs) on the parallel fiber-Purkinje cell synapse after vestibuloocular reflex phase reversal adaptation, a behavior that has been suggested to rely on PF-PC LTP. We have found that on the last day of adaptation there is no learning trace in form of VGCCs nor AMPARs variation at the PF-PC synapse, but instead a decrease in the number of PF-PC synapses. These data seem to support the view that learning is only stored in the cerebellar cortex in an initial learning phase, being transferred later to the vestibular nuclei. Next, we have studied the role of MLIs in motor learning using a relatively simple and well characterized behavioral paradigm – horizontal optokinetic reflex (HOKR) adaptation. We have found behavior-induced MLI potentiation in form of release probability increase that could be explained by the increase of VGCCs at the presynaptic side. Our results strengthen the idea of distributed cerebellar plasticity contributing to learning and provide a novel mechanism for release probability increase. }, author = {Alcarva, Catarina}, issn = {2663 - 337X}, pages = {115}, publisher = {Institute of Science and Technology Austria}, title = {{Plasticity in the cerebellum: What molecular mechanisms are behind physiological learning}}, doi = {10.15479/at:ista:12809}, year = {2023}, } @phdthesis{12826, abstract = {During navigation, animals can infer the structure of the environment by computing the optic flow cues elicited by their own movements, and subsequently use this information to instruct proper locomotor actions. These computations require a panoramic assessment of the visual environment in order to disambiguate similar sensory experiences that may require distinct behavioral responses. The estimation of the global motion patterns is therefore essential for successful navigation. Yet, our understanding of the algorithms and implementations that enable coherent panoramic visual perception remains scarce. Here I pursue this problem by dissecting the functional aspects of interneuronal communication in the lobula plate tangential cell network in Drosophila melanogaster. The results presented in the thesis demonstrate that the basis for effective interpretation of the optic flow in this circuit are stereotyped synaptic connections that mediate the formation of distinct subnetworks, each extracting a particular pattern of global motion. Firstly, I show that gap junctions are essential for a correct interpretation of binocular motion cues by horizontal motion-sensitive cells. HS cells form electrical synapses with contralateral H2 neurons that are involved in detecting yaw rotation and translation. I developed an FlpStop-mediated mutant of a gap junction protein ShakB that disrupts these electrical synapses. While the loss of electrical synapses does not affect the tuning of the direction selectivity in HS neurons, it severely alters their sensitivity to horizontal motion in the contralateral side. These physiological changes result in an inappropriate integration of binocular motion cues in walking animals. While wild-type flies form a binocular perception of visual motion by non-linear integration of monocular optic flow cues, the mutant flies sum the monocular inputs linearly. These results indicate that rather than averaging signals in neighboring neurons, gap-junctions operate in conjunction with chemical synapses to mediate complex non-linear optic flow computations. Secondly, I show that stochastic manipulation of neuronal activity in the lobula plate tangential cell network is a powerful approach to study the neuronal implementation of optic flow-based navigation in flies. Tangential neurons form multiple subnetworks, each mediating course-stabilizing response to a particular global pattern of visual motion. Application of genetic mosaic techniques can provide sparse optogenetic activation of HS cells in numerous combinations. These distinct combinations of activated neurons drive an array of distinct behavioral responses, providing important insights into how visuomotor transformation is performed in the lobula plate tangential cell network. This approach can be complemented by stochastic silencing of tangential neurons, enabling direct assessment of the functional role of individual tangential neurons in the processing of specific visual motion patterns. Taken together, the findings presented in this thesis suggest that establishing specific activity patterns of tangential cells via stereotyped synaptic connectivity is a key to efficient optic flow-based navigation in Drosophila melanogaster.}, author = {Pokusaeva, Victoria}, issn = {2663 - 337X}, pages = {106}, publisher = {Institute of Science and Technology Austria}, title = {{Neural control of optic flow-based navigation in Drosophila melanogaster}}, doi = {10.15479/at:ista:12826}, year = {2023}, } @phdthesis{12885, abstract = {High-performance semiconductors rely upon precise control of heat and charge transport. This can be achieved by precisely engineering defects in polycrystalline solids. There are multiple approaches to preparing such polycrystalline semiconductors, and the transformation of solution-processed colloidal nanoparticles is appealing because colloidal nanoparticles combine low cost with structural and compositional tunability along with rich surface chemistry. However, the multiple processes from nanoparticle synthesis to the final bulk nanocomposites are very complex. They involve nanoparticle purification, post-synthetic modifications, and finally consolidation (thermal treatments and densification). All these properties dictate the final material’s composition and microstructure, ultimately affecting its functional properties. This thesis explores the synthesis, surface chemistry and consolidation of colloidal semiconductor nanoparticles into dense solids. In particular, the transformations that take place during these processes, and their effect on the material’s transport properties are evaluated. }, author = {Calcabrini, Mariano}, isbn = {978-3-99078-028-2}, issn = {2663-337X}, pages = {82}, publisher = {Institute of Science and Technology Austria}, title = {{Nanoparticle-based semiconductor solids: From synthesis to consolidation}}, doi = {10.15479/at:ista:12885}, year = {2023}, } @phdthesis{12891, abstract = {The tight spatiotemporal coordination of signaling activity determining embryo patterning and the physical processes driving embryo morphogenesis renders embryonic development robust, such that key developmental processes can unfold relatively normally even outside of the full embryonic context. For instance, embryonic stem cell cultures can recapitulate the hallmarks of gastrulation, i.e. break symmetry leading to germ layer formation and morphogenesis, in a very reduced environment. This leads to questions on specific contributions of embryo-specific features, such as the presence of extraembryonic tissues, which are inherently involved in gastrulation in the full embryonic context. To address this, we established zebrafish embryonic explants without the extraembryonic yolk cell, an important player as a signaling source and for morphogenesis during gastrulation, as a model of ex vivo development. We found that dorsal-marginal determinants are required and sufficient in these explants to form and pattern all three germ layers. However, formation of tissues, which require the highest Nodal-signaling levels, is variable, demonstrating a contribution of extraembryonic tissues for reaching peak Nodal signaling levels. Blastoderm explants also undergo gastrulation-like axis elongation. We found that this elongation movement shows hallmarks of oriented mesendoderm cell intercalations typically associated with dorsal tissues in the intact embryo. These are disrupted by uniform upregulation of BMP signaling activity and concomitant explant ventralization, suggesting that tight spatial control of BMP signaling is a prerequisite for explant morphogenesis. This control is achieved by Nodal signaling, which is critical for effectively downregulating BMP signaling in the mesendoderm, highlighting that Nodal signaling is not only directly required for mesendoderm cell fate specification and morphogenesis, but also by maintaining low levels of BMP signaling at the dorsal side. Collectively, we provide insights into the capacity and organization of signaling and morphogenetic domains to recapitulate features of zebrafish gastrulation outside of the full embryonic context.}, author = {Schauer, Alexandra}, issn = {2663 - 337X}, pages = {190}, publisher = {Institute of Science and Technology Austria}, title = {{Mesendoderm formation in zebrafish gastrulation: The role of extraembryonic tissues}}, doi = {10.15479/at:ista:12891}, year = {2023}, } @phdthesis{12897, abstract = {Inverse design problems in fabrication-aware shape optimization are typically solved on discrete representations such as polygonal meshes. This thesis argues that there are benefits to treating these problems in the same domain as human designers, namely, the parametric one. One reason is that discretizing a parametric model usually removes the capability of making further manual changes to the design, because the human intent is captured by the shape parameters. Beyond this, knowledge about a design problem can sometimes reveal a structure that is present in a smooth representation, but is fundamentally altered by discretizing. In this case, working in the parametric domain may even simplify the optimization task. We present two lines of research that explore both of these aspects of fabrication-aware shape optimization on parametric representations. The first project studies the design of plane elastic curves and Kirchhoff rods, which are common mathematical models for describing the deformation of thin elastic rods such as beams, ribbons, cables, and hair. Our main contribution is a characterization of all curved shapes that can be attained by bending and twisting elastic rods having a stiffness that is allowed to vary across the length. Elements like these can be manufactured using digital fabrication devices such as 3d printers and digital cutters, and have applications in free-form architecture and soft robotics. We show that the family of curved shapes that can be produced this way admits geometric description that is concise and computationally convenient. In the case of plane curves, the geometric description is intuitive enough to allow a designer to determine whether a curved shape is physically achievable by visual inspection alone. We also present shape optimization algorithms that convert a user-defined curve in the plane or in three dimensions into the geometry of an elastic rod that will naturally deform to follow this curve when its endpoints are attached to a support structure. Implemented in an interactive software design tool, the rod geometry is generated in real time as the user edits a curve and enables fast prototyping. The second project tackles the problem of general-purpose shape optimization on CAD models using a novel variant of the extended finite element method (XFEM). Our goal is the decoupling between the simulation mesh and the CAD model, so no geometry-dependent meshing or remeshing needs to be performed when the CAD parameters change during optimization. This is achieved by discretizing the embedding space of the CAD model, and using a new high-accuracy numerical integration method to enable XFEM on free-form elements bounded by the parametric surface patches of the model. Our simulation is differentiable from the CAD parameters to the simulation output, which enables us to use off-the-shelf gradient-based optimization procedures. The result is a method that fits seamlessly into the CAD workflow because it works on the same representation as the designer, enabling the alternation of manual editing and fabrication-aware optimization at will.}, author = {Hafner, Christian}, isbn = {978-3-99078-031-2}, issn = {2663-337X}, pages = {180}, publisher = {Institute of Science and Technology Austria}, title = {{Inverse shape design with parametric representations: Kirchhoff Rods and parametric surface models}}, doi = {10.15479/at:ista:12897}, year = {2023}, } @phdthesis{12900, abstract = {About a 100 years ago, we discovered that our universe is inherently noisy, that is, measuring any physical quantity with a precision beyond a certain point is not possible because of an omnipresent inherent noise. We call this - the quantum noise. Certain physical processes allow this quantum noise to get correlated in conjugate physical variables. These quantum correlations can be used to go beyond the potential of our inherently noisy universe and obtain a quantum advantage over the classical applications. Quantum noise being inherent also means that, at the fundamental level, the physical quantities are not well defined and therefore, objects can stay in multiple states at the same time. For example, the position of a particle not being well defined means that the particle is in multiple positions at the same time. About 4 decades ago, we started exploring the possibility of using objects which can be in multiple states at the same time to increase the dimensionality in computation. Thus, the field of quantum computing was born. We discovered that using quantum entanglement, a property closely related to quantum correlations, can be used to speed up computation of certain problems, such as factorisation of large numbers, faster than any known classical algorithm. Thus began the pursuit to make quantum computers a reality. Till date, we have explored quantum control over many physical systems including photons, spins, atoms, ions and even simple circuits made up of superconducting material. However, there persists one ubiquitous theme. The more readily a system interacts with an external field or matter, the more easily we can control it. But this also means that such a system can easily interact with a noisy environment and quickly lose its coherence. Consequently, such systems like electron spins need to be protected from the environment to ensure the longevity of their coherence. Other systems like nuclear spins are naturally protected as they do not interact easily with the environment. But, due to the same reason, it is harder to interact with such systems. After decades of experimentation with various systems, we are convinced that no one type of quantum system would be the best for all the quantum applications. We would need hybrid systems which are all interconnected - much like the current internet where all sorts of devices can all talk to each other - but now for quantum devices. A quantum internet. Optical photons are the best contenders to carry information for the quantum internet. They can carry quantum information cheaply and without much loss - the same reasons which has made them the backbone of our current internet. Following this direction, many systems, like trapped ions, have already demonstrated successful quantum links over a large distances using optical photons. However, some of the most promising contenders for quantum computing which are based on microwave frequencies have been left behind. This is because high energy optical photons can adversely affect fragile low-energy microwave systems. In this thesis, we present substantial progress on this missing quantum link between microwave and optics using electrooptical nonlinearities in lithium niobate. The nonlinearities are enhanced by using resonant cavities for all the involved modes leading to observation of strong direct coupling between optical and microwave frequencies. With this strong coupling we are not only able to achieve almost 100\% internal conversion efficiency with low added noise, thus presenting a quantum-enabled transducer, but also we are able to observe novel effects such as cooling of a microwave mode using optics. The strong coupling regime also leads to direct observation of dynamical backaction effect between microwave and optical frequencies which are studied in detail here. Finally, we also report first observation of microwave-optics entanglement in form of two-mode squeezed vacuum squeezed 0.7dB below vacuum level. With this new bridge between microwave and optics, the microwave-based quantum technologies can finally be a part of a quantum network which is based on optical photons - putting us one step closer to a future with quantum internet. }, author = {Sahu, Rishabh}, isbn = {978-3-99078-030-5}, issn = {2663 - 337X}, keywords = {quantum optics, electrooptics, quantum networks, quantum communication, transduction}, pages = {190}, publisher = {Institute of Science and Technology Austria}, title = {{Cavity quantum electrooptics}}, doi = {10.15479/at:ista:12900}, year = {2023}, } @phdthesis{12964, abstract = {Pattern formation is of great importance for its contribution across different biological behaviours. During developmental processes for example, patterns of chemical gradients are established to determine cell fate and complex tissue patterns emerge to define structures such as limbs and vascular networks. Patterns are also seen in collectively migrating groups, for instance traveling waves of density emerging in moving animal flocks as well as collectively migrating cells and tissues. To what extent these biological patterns arise spontaneously through the local interaction of individual constituents or are dictated by higher level instructions is still an open question however there is evidence for the involvement of both types of process. Where patterns arise spontaneously there is a long standing interest in how far the interplay of mechanics, e.g. force generation and deformation, and chemistry, e.g. gene regulation and signaling, contributes to the behaviour. This is because many systems are able to both chemically regulate mechanical force production and chemically sense mechanical deformation, forming mechano-chemical feedback loops which can potentially become unstable towards spatio and/or temporal patterning. We work with experimental collaborators to investigate the possibility that this type of interaction drives pattern formation in biological systems at different scales. We focus first on tissue-level ERK-density waves observed during the wound healing response across different systems where many previous studies have proposed that patterns depend on polarized cell migration and arise from a mechanical flocking-like mechanism. By combining theory with mechanical and optogenetic perturbation experiments on in vitro monolayers we instead find evidence for mechanochemical pattern formation involving only scalar bilateral feedbacks between ERK signaling and cell contraction. We perform further modeling and experiment to study how this instability couples with polar cell migration in order to produce a robust and efficient wound healing response. In a following chapter we implement ERK-density coupling and cell migration in a 2D active vertex model to investigate the interaction of ERK-density patterning with different tissue rheologies and find that the spatio-temporal dynamics are able to both locally and globally fluidize a tissue across the solid-fluid glass transition. In a last chapter we move towards lower spatial scales in the context of subcellular patterning of the cell cytoskeleton where we investigate the transition between phases of spatially homogeneous temporal oscillations and chaotic spatio-temporal patterning in the dynamics of myosin and ROCK activities (a motor component of the actomyosin cytoskeleton and its activator). Experimental evidence supports an intrinsic chemical oscillator which we encode in a reaction model and couple to a contractile active gel description of the cell cortex. The model exhibits phases of chemical oscillations and contractile spatial patterning which reproduce many features of the dynamics seen in Drosophila oocyte epithelia in vivo. However, additional pharmacological perturbations to inhibit myosin contractility leaves the role of contractile instability unclear. We discuss alternative hypotheses and investigate the possibility of reaction-diffusion instability.}, author = {Boocock, Daniel R}, isbn = {978-3-99078-032-9}, issn = {2663-337X}, pages = {146}, publisher = {Institute of Science and Technology Austria}, title = {{Mechanochemical pattern formation across biological scales}}, doi = {10.15479/at:ista:12964}, year = {2023}, }