@inproceedings{18121, abstract = {It is known that sparsity can improve interpretability for deep neural networks. However, existing methods in the area either require networks that are pre-trained with sparsity constraints, or impose sparsity after the fact, altering the network’s general behavior. In this paper, we demonstrate, for the first time, that sparsity can instead be incorporated into the interpretation process itself, as a sample-specific preprocessing step. Unlike previous work, this approach, which we call SPADE, does not place constraints on the trained model and does not affect its behavior during inference on the sample. Given a trained model and a target sample, SPADE uses sample-targeted pruning to provide a "trace" of the network’s execution on the sample, reducing the network to the most important connections prior to computing an interpretation. We demonstrate that preprocessing with SPADE significantly increases the accuracy of image saliency maps across several interpretability methods. Additionally, SPADE improves the usefulness of neuron visualizations, aiding humans in reasoning about network behavior. Our code is available at https://github.com/IST-DASLab/SPADE.}, author = {Moakhar, Arshia Soltani and Iofinova, Eugenia B and Frantar, Elias and Alistarh, Dan-Adrian}, booktitle = {Proceedings of the 41st International Conference on Machine Learning}, issn = {2640-3498}, location = {Vienna, Austria}, pages = {45955--45987}, publisher = {ML Research Press}, title = {{SPADE: Sparsity-guided debugging for deep neural networks}}, volume = {235}, year = {2024}, } @phdthesis{17206, abstract = {Males and females exhibit numerous differences, from the initial stages of sex determination to the development of secondary sexual characteristics. In Drosophila, these differences have been thoroughly studied. Extensive research has been performed to understand the role and molecular mode of action of central sex in determining switch genes, such as transformer (tra) and Sex-lethal (Sxl). Furthermore, studies have highlighted differential gene expression as an essential mechanism to create sexual dimorphism. An alternative path to sexual dimorphism that has been less explored is alternative splicing, the mechanism through which genes can produce multiple transcripts with distinct properties and functions. The primary switch sex-determining gene Sxl is a good example of the role of alternative splicing for sex-specific functions: the inclusion of a specific exon determines the male or female form of the protein, which in turn switches on either the male or female developmental pathway. The genes that act upstream of Sxl and determine which form is expressed - the counter genes - have received less attention. This thesis addresses two critical questions about the molecular encoding of sexes in the Drosophila melanogaster genome: First, the use of splice forms in male and female tissues in D. melanogaster is examined, inferring the molecular and evolutionary parameters shaping the diversity of the splicing landscape. Second, the behaviour of counter genes in Drosophila-related species is investigated, shedding light on potential changes leading to their incorporation into the sex-determination pathway. For the alternative splicing analyses, long-read RNA sequencing of testes, ovaries, female and male midguts, heads, and whole bodies was performed. A novel pipeline was developed to assign unique transcript identifiers for each sequence of exons and introns in the read, enabling detailed comparisons of splicing variants in each tissue/sex. Alternative splicing was found to be more pervasive in females than males (22,201 exclusive splice forms in females versus 12,631 in males), especially when comparing ovaries to other tissues. The ovaries alone displayed 15,299 exclusive splice forms, suggesting most female exclusive splice forms originate there. Genome location and gene age were also correlated with the number of splice forms per gene. In particular, the X and 4th chromosomes (Muller elements A and F) showed more splice forms per gene than other chromosomes. Additionally, genes older than 63 million years exhibited more splice forms per gene than younger genes. Our results suggest that alternative splicing is more prevalent than previously believed, with numerous female-exclusive forms, age, and location playing significant roles in shaping its prevalence. For the counter genes analyses, we combined published gene expression, genomic, and gene interaction data from various clades (Bactrocera jarvisi, B. oleae, Ceratitis capitata, Mus musculus, Caenorhabditis elegans, Homo sapiens, and D. melanogaster). The counter genes scute (sc), extra macrochaetae (emc), groucho (gro), deadpan (dpn), daughterless (da), runt (run), Sxl, hermaphrodite (her), and tra maintain conserved Muller element locations between C. capitata and D. melanogaster, which are most of the counter genes identified in the C. capitata genome. Their expression patterns during early embryogenesis in B. jarvisi and D. melanogaster are also similar for counter genes dpn, gro, da, and emc. However, Sxl and sc are also found to have more extreme expression ratios between the species. Lastly, gene interactions within the counter genes are conserved, with da-sc and gro-dpn interactions occurring in Drosophila, worms, humans, and mice. Interactions such as dpn-sc, dpn-da, da-emc, and gro-run are present in Drosophila, mice, and humans, suggesting these genes were recruited by ancestral characteristics, primarily during embryogenesis. The conserved expression, location, and interactions of counter genes suggest serendipitous recruitment of such genes instead of a change in those characteristics as they were recruited for this function. }, author = {Raices, Julia}, issn = {2663-337X}, pages = {82}, publisher = {Institute of Science and Technology Austria}, title = {{Novel approaches to studying alternative splicing in Drosophila Melanogaster : Insights into sex-specific gene expression and the evolution of sex determination}}, doi = {10.15479/at:ista:17206}, year = {2024}, } @phdthesis{18101, abstract = {The Retroviridae family consists of two sub-families, the Orthoretrovirinae and the Spumaretrovirinae. The Orthoretroviruses contain important human pathogens, such as the human immunodeficiency virus 1 (HIV-1). They also harbor other retrovirus species which are regularly used as model systems to study the retroviral life cycle. The main structural component of the retroviruses, is the Gag protein and its truncation derivatives occurring during viral maturation. Orthoretroviral Gag assemblies have been extensively studied to understand the interactions that confer stability and morphology to viral particles. The Spumaretrovirinae subfamily represent an early diverging branch of the Retroviridae. Its members, the Foamy viruses (FV), share most of the conventional features found in retroviruses. However, they also possess multiple characteristics that make them unique. In particular, FV Gag does not get extensively cleaved as in orthoretroviruses. Hence, the Gag architecture deviates from the canonical domain arrangement in FV. They also exhibit a peculiar particle morphology, having no apparent immature state and a seemingly icosahedral mature particle. Due to this, many fundamental questions on FV structural assembly mechanisms remain open. To answer these questions, was the main focus of this thesis. Mainly, it is not known how FV assemble their core in a virus particle and what are the important assembly interaction sites within said core. What is the minimum assembly competent domain of FV Gag? Is there a morphological change in the assembly type of FVGag lattices? If so, what is defining these morphological shifts? Finally, it would be interesting to know what is the evolutionary relationship between FV and the rest of the retrotranscribing elements, from a structural point of view? To answer these questions, membrane-enveloped mammalian cell-derived FV virus-like particles (VLPs) were produced. Cryo-electron tomography (cryo-ET) analysis suggested these FV VLPs do not form a canonical retroviral Gag lattice structure, which is in line with earlier observations. To further evaluate FV Gag assembly competence and morphology, the first bacterial cell-derived in vitro VLP assembly system was designed and optimized. Using this system with different truncation variants, the minimum assembly competent domain of FV Gag was found to be the putative CA300-477 domain. Varying VLP morphologies were also observed and strongly suggested residues upstream of CA300-477 play a role in morphology determination. Finally, a combined cryo-electron microscopy (cryoEM) and cryo-ET approach was taken to analyze tubular assemblies from the minimal assembly competent domain. This revealed an unexpectedly unique non-canonical assembly architecture. Three novel lattice stabilizing interfaces were described which proved to be as unique as the lattice arrangement. Comparison to a newly published FV CA core structure revealed the CA-CA interactions in the atypical assembly do not recapitulate what is described for the FV core lattice. However, the new in vitro VLP assembly system obtained in this thesis also provides an exciting opportunity to study still unresolved FV assembly features in a potentially facilitated approach compared to conventional methods. In summary, this work provided a deeper understanding of the basic FV Gag assembly unit, as well as presenting the first FV Gag-derived in vitro VLP assembly system. This system reveals a novel and unique assembly architecture among retroviral in vitro assemblies.}, author = {Porley, Dario J}, isbn = {978-3-99078-041-1}, issn = {2663-337X}, pages = {131}, publisher = {Institute of Science and Technology Austria}, title = {{Structural characterization of spumavirus capsid assemblies}}, doi = {10.15479/at:ista:18101}, year = {2024}, } @phdthesis{17465, abstract = {In the modern age of machine learning, artificial neural networks have become an integral part of many practical systems. One of the key ingredients of the success of the deep learning approach is recent computational advances which allowed the training of models with billions of parameters on large-scale data. Such over-parameterized and data-hungry regimes pose a challenge for the theoretical analysis of modern models since “classical” statistical wisdom is no longer applicable. In this view, it is paramount to extend or develop new machinery that will allow tackling the neural network analysis under new challenging asymptotic regimes, which is the focus of this thesis. Large neural network systems are usually optimized via “local” search algorithms, such as stochastic gradient descent (SGD). However, given the high-dimensional nature of the parameter space, it is a priori not clear why such a crude “local” approach works so remarkably well in practice. We take a step towards demystifying this phenomenon by showing that the landscape of the SGD training dynamics exhibits a few beneficial properties for the optimization. First, we show that along the SGD trajectory an over-parameterized network is dropout stable. The emergence of dropout stability allows to conclude that the minima found by SGD are connected via a continuous path of small loss. This in turn means that the high-dimensional landscape of the neural network optimization problem is provably not so unfavourable to gradient-based training, due to mode connectivity. Next, we show that SGD for an over-parameterized network tends to find solutions that are functionally more “simple”. This in turn means that the SGD minima are more robust, since a less complicated solution will less likely overfit the data. More formally, for a prototypical example of a wide two-layer ReLU network on a 1d regression task we show that the SGD algorithm is implicitly selective in its choice of an interpolating solution. Namely, at convergence the neural network implements a piece-wise linear function with the number of linear regions depending only on the amount of training data. This is in contrast to a “smooth”-like behaviour which one would expect given such a severe over-parameterization of the model. Diverging from the generic supervised setting of classification and regression problems, we analyze an auto-encoder model that is commonly used for representation learning and data compression. Despite the wide applicability of the auto-encoding paradigm, the theoretical understanding of their behaviour is limited even in the simplistic shallow case. The related work is restricted to extreme asymptotic regimes in which the auto-encoder is either severely over-parameterized or under-parameterized. In contrast, we provide a tight characterization for the 1-bit compression of Gaussian signals in the challenging proportional regime, i.e., the input dimension and the size of the compressed representation obey the same asymptotics. We also show that gradient-based methods are able to find a globally optimal solution and that the predictions made for Gaussian data extrapolate beyond - to the case of compression of natural images. Next, we relax the Gaussian assumption and study more structured input sources. We show that the shallow model is sometimes agnostic to the structure of the data vii which results in a Gaussian-like behaviour. We prove that making the decoding component slightly less shallow is already enough to escape the “curse” of Gaussian performance. }, author = {Shevchenko, Aleksandr}, issn = {2663-337X}, pages = {232}, publisher = {Institute of Science and Technology Austria}, title = {{High-dimensional limits in artificial neural networks}}, doi = {10.15479/at:ista:17465}, year = {2024}, } @inproceedings{17469, abstract = {Autoencoders are a prominent model in many empirical branches of machine learning and lossy data compression. However, basic theoretical questions remain unanswered even in a shallow two-layer setting. In particular, to what degree does a shallow autoencoder capture the structure of the underlying data distribution? For the prototypical case of the 1-bit compression of sparse Gaussian data, we prove that gradient descent converges to a solution that completely disregards the sparse structure of the input. Namely, the performance of the algorithm is the same as if it was compressing a Gaussian source - with no sparsity. For general data distributions, we give evidence of a phase transition phenomenon in the shape of the gradient descent minimizer, as a function of the data sparsity: below the critical sparsity level, the minimizer is a rotation taken uniformly at random (just like in the compression of non-sparse data); above the critical sparsity, the minimizer is the identity (up to a permutation). Finally, by exploiting a connection with approximate message passing algorithms, we show how to improve upon Gaussian performance for the compression of sparse data: adding a denoising function to a shallow architecture already reduces the loss provably, and a suitable multi-layer decoder leads to a further improvement. We validate our findings on image datasets, such as CIFAR-10 and MNIST.}, author = {Kögler, Kevin and Shevchenko, Aleksandr and Hassani, Hamed and Mondelli, Marco}, booktitle = {Proceedings of the 41st International Conference on Machine Learning}, location = {Vienna, Austria}, pages = {24964--25015}, publisher = {ML Research Press}, title = {{Compression of structured data with autoencoders: Provable benefit of nonlinearities and depth}}, volume = {235}, year = {2024}, } @phdthesis{17119, abstract = {Genomes are shaped by natural selection at the level of the organism, as genomic variants that have a beneficial effect on the viability or fecundity of their carriers are on average expected to be passed on to more offspring than less beneficial alleles. However, selection also favors genomic variants that drive their own transmission to the next generation above the mendelian expectation of 50 percent in heterozygotes, even if these self-promoting variants are less beneficial to the organism than other variants at the same locus. Such variants, called meiotic drivers, are found in diverse taxa, and often impose fitness costs on their host organisms. As meiotic drivers often require multiple genes and sequences for transmission ratio distortion, they are often found in regions of low recombination, such as inversions, which prevent their recombination with the non-driving homologous regions. Reduced recombination rates are expected to lead to the accumulation of deleterious mutations, which may affect hundreds of genes trapped in the inversions of meiotic drivers. Although the observed fitness costs of self-promoting haplotypes are thought to possibly reflect sequence degeneration, no study has systematically investigated the level of degeneration on a meiotic driver. Further, the low rates of recombination between driving and non-driving haplotypes have limited the power of traditional genetic studies in uncovering the gene content of meiotic drivers, and made the the identification of the genes causing transmission ratio distortion difficult. After an introduction to meiotic drivers in Chapter 1, this thesis presents three studies that make use of next generation sequencing data to characterize the sequence and expression evolution of genes on the t-haplotype, a large and ancient meiotic driver in house mice that is transmitted to up to 100% of the offspring in males heterozygous for it. Chapter 2 presents a comprehensive assessment of the t-haplotype’s sequence evolution, which shows signs of sequence degeneration counteracted by occasional recombination with the non-driving homolog over large parts of the meiotic driver, proposing an explanation for its long-term survival. Chapter 3 investigates the sequence and expression evolution of genes on the t-haplotype, and finds widespread expression and copy number changes and signs of less efficient purifying selection compared to the genes on the non-driving homolog. Further, this chapter finds candidates for involvment in drive: two positively selected genes on the t-haplotype, and the discovery of a t-specific gene duplicate, which was gained from another chromosome, and which acquired novel sequence and testis-specific expression on the t-haplotype. Finally, Chapter 4 provides unprecedented insights into the gene expression landscape in testes of t-carrier mice, using single nucleus sequencing. Cell-resolved RNA-sequencing allows the comparison of expression in spermatids carrying or not carrying the t-haplotype as well as the timing of t-haplotype-induced expression changes along spermatogenesis. This study shows the timing of previously found drive-associated genes, and uncovers novel candidate genes and biological processes that may underlie the complex biology of transmission ratio distortion of the t-haplotype. Chapter 5 synthesizes the findings of the three studies, and discusses them in the context of the current state of meiotic drive research.}, author = {Kelemen, Réka K}, isbn = {978-3-99078-039-8}, issn = {2663-337X}, keywords = {meiotic driver, neofunctionalization, single nucleus sequencing}, pages = {105}, publisher = {Institute of Science and Technology Austria}, title = {{Characterizing the sequence and expression evolution of the t-haplotype, a model meiotic driver}}, doi = {10.15479/at:ista:17119}, year = {2024}, } @phdthesis{18477, abstract = {ADAR1 is broadly expressed across various tissues and is vital in regulating pathways associated with innate immune responses. ADAR1 marks double-stranded RNA as "self" through its A-to-I editing activity, effectively repressing autoimmunity and maintaining immune tolerance. This editing process has been detected at millions of sites across the human genome. However, the mechanism underlying ADAR1's substrate selectivity properties remains largely unclear, with much of the current knowledge derived from comparisons to its more extensively studied homolog, ADAR2. By studying ADAR1 in complex with its RNA substrates and applying a combination of biochemical techniques and structural studies using CryoEM, we aim to gain a more comprehensive understanding of the substrate selectivity characteristics of ADAR1. In this thesis, the purification protocol for ADAR1 was successfully optimized, resulting in the first report in the literature to achieve high protein purity and activity. This advancement enabled the investigation of complex formation between ADAR1 and various RNA substrates, leading to the identification of optimal conditions for preparing the cryoEM sample. However, despite comprehensive optimization of the cryo-EM conditions, the resulting data lacked the desired quality, highlighting the need for similar rigorous optimization of the RNA substrates to facilitate structural studies of the ADAR1-RNA complex. The study was complemented by AlphaFold predictions, which provided some insights into this mechanism. Moreover, during this project I established a collaboration with a research group focused on studying ADAR homologs. Notably ADAR homologs were identified in bivalve species, and it was further demonstrated that ADAR and its A-to-I editing activity are upregulated in Pacific oysters during infections with Ostreid herpesvirus-1—a highly infectious virus that leads to significant losses in oyster populations globally. I successfully purified oyster ADAR and prepared in vitro edited RNA for nanopore sequencing—a direct sequencing technology capable of detecting modified nucleotides without the need for reverse transcription. The collaborators initiated optimization of this nanopore-based approach. However, current technological limitations still constrain the reliable detection of modified nucleotides. The project also examined the impact of RNA editing on RNA binding and filament formation by MDA5, a key cytosolic dsRNA sensor that triggers an interferon response. A primary target of ADAR1's editing activity is RNA derived from repetitive elements present in the genome, particularly Alu elements forming double-stranded RNA. When unedited, these RNA sequences are recognized by MDA5. However, the mechanisms by which MDA5 interacts with Alu RNAs, as well as the role of A-to-I editing in influencing this binding, are still not well understood. The interaction between MDA5 and Alu elements, was successfully established. This was achieved through the testing of different RNA variants and the evaluation of filament formation using binding techniques and electron microscopy imaging. This groundwork has set the conditions for further evaluation using CryoEM. Furthermore, the effects of A-to-I editing on the binding properties of MDA5 with Alu RNA were investigated. Given the recent research that has provided new insights into MDA5's interaction with dsRNA, it is essential to revise the experimental setup to integrate these findings before moving forward with the CryoEM sample analysis.}, author = {Kaczmarek, Beata M}, isbn = {978-3-99078-045-9}, issn = {2663-337X}, pages = {124}, publisher = {Institute of Science and Technology Austria}, title = {{Biochemical and structural insights into ADAR1 RNA editing}}, doi = {10.15479/at:ista:18477}, year = {2024}, } @phdthesis{17319, abstract = {This thesis comprises two distinct projects, each offering unique insights into fundamental cellular processes. While distinct in their focus, these different perspectives have a common theme: chemiosmotic theory and utilisation of the proton gradient for driving the essential processes like auxin efflux and ATP synthesis, effectively bridging the membrane protein structure and function from the realms of plant biology and cellular bioenergetics. The first project of this thesis centres on the characterisation of PIN proteins, a class of transmembrane transporters pivotal in the regulation of auxin transport and distribution in plants. PINs form a conserved and phylogenetically abundant group of transporters present in land plants and certain algae. Despite their great importance, they were one of the few elusive proteins essential for plant development not to be structurally and mechanistically characterised since their discovery almost 30 years ago. This work aimed to uncover the structural and functional dynamics of the PIN protein-mediated auxin transport using an array of experimental techniques, including protein purification, biochemical assays and structural analysis. Through an exhaustive screening process that took several years and included testing different PIN homologues, expression systems, constructs, and purification conditions, we developed a robust protocol for isolating the pure, stable, and monodisperse PIN8 protein. Moreover, utilising biophysical methods and buffer screening, we demonstrated that PIN8 exhibits detergent and pH-dependent stability, with mild detergents and lower pH (5.0 and 6.0) being optimal for the stability of the protein. Using SEC-MALS and crosslinking, we determined that PIN8 forms dimers, which was confirmed by our structural studies. We obtained a cryo-EM map of PIN8 at pH 6.0, and, compared to recently published structures, our map implies major pH-dependent conformational changes and possibly utilisation of the proton gradient in the transport mechanism. The subject of the second project was F1Fo-ATP synthase, an enzyme complex fundamental to cellular energy metabolism. Through an approach integrating biochemical assays and structural analysis, this research aimed to unveil the molecular mechanism of inhibition of ATP synthase by yaku´amide, a bioactive compound with potential therapeutic implications. Using submitochondrial particles and purified F1Fo-ATP synthase, we demonstrated that, contrary to published data, yaku´amide inhibits both ATP hydrolysis and ATP synthesis reactions. Moreover, we found that yaku´amide inhibitory activity is proton motive force (pmf) dependent, with lower inhibition in a more coupled system. Utilising cryo-EM, we obtained maps and models for the three main rotational states of murine ATP synthase (State 1 at 3.0 Å, 8 State 2 at 3.1 Å, and State 3 at 3.2 Å, overall). We observed several new features in our maps; however, we cannot definitively determine the exact mechanism of yaku amide’s inhibition on the protein due to either resolution limits or suboptimal binding of the inhibitor.}, author = {Lukic, Kristina}, issn = {2663-337X}, pages = {224}, publisher = {Institute of Science and Technology Austria}, title = {{Membrane proteins in plant physiology and bioenergetics : Investigating auxin efflux transporter PIN8 and ATP synthase inhibition by the novel inhibitor Yaku'amide B}}, doi = {10.15479/at:ista:17319}, year = {2024}, } @article{15323, abstract = {Supercomplexes of the respiratory chain are established constituents of the oxidative phosphorylation system, but their role in mammalian metabolism has been hotly debated. Although recent studies have shown that different tissues/organs are equipped with specific sets of supercomplexes, depending on their metabolic needs, the notion that supercomplexes have a role in the regulation of metabolism has been challenged. However, irrespective of the mechanistic conclusions, the composition of various high molecular weight supercomplexes remains uncertain. Here, using cryogenic electron microscopy, we demonstrate that mammalian (mouse) tissues contain three defined types of ‘respirasome’, supercomplexes made of CI, CIII2 and CIV. The stoichiometry and position of CIV differs in the three respirasomes, of which only one contains the supercomplex-associated factor SCAF1, whose involvement in respirasome formation has long been contended. Our structures confirm that the ‘canonical’ respirasome (the C-respirasome, CICIII2CIV) does not contain SCAF1, which is instead associated to a different respirasome (the CS-respirasome), containing a second copy of CIV. We also identify an alternative respirasome (A-respirasome), with CIV bound to the ‘back’ of CI, instead of the ‘toe’. This structural characterization of mouse mitochondrial supercomplexes allows us to hypothesize a mechanistic basis for their specific role in different metabolic conditions.}, author = {Vercellino, Irene and Sazanov, Leonid A}, issn = {1545-9985}, journal = {Nature Structural and Molecular Biology}, pages = {1061--1071}, publisher = {Springer Nature}, title = {{SCAF1 drives the compositional diversity of mammalian respirasomes}}, doi = {10.1038/s41594-024-01255-0}, volume = {31}, year = {2024}, } @phdthesis{17346, abstract = {Acquiring, retaining, and retrieving information over a wide range of timescales are crucial functions of the brain. The successful processing of memories affects many aspects of our lives and enables us and many other organisms to operate in a complex environment and to interact with it. In this context, the hippocampus and functionally connected brain areas, such as the prefrontal cortex, are central and have been subject to intensive research in the past decades. Storage of memories is believed to rely on distributed neural activity within these neural circuits. Additionally, neural memory traces of recent experience are reinstated during periods of rest or sleep. These reactivations are thought to play an outstanding role in the consolidation of memories and potentially facilitate the transfer of information from the hippocampus to cortical areas for long-term storage and integration into existing knowledge. However, there is growing evidence that memory-related neural representations in the hippocampus are not as stable as initially thought and that they change even in the absence of learning. It has been suggested that these changes reflect the accumulation of experience, but the influence of interspersed consolidation periods has not been considered. Previous studies have analyzed consolidation periods by detecting activity that strongly resembled neural activity during the acquisition of memory. Besides being often limited to only non-rapid eye movement (NREM) sleep, the used approaches were not capable of tracking changes in neural representations over extended temporal periods. More fluid representations do not only challenge our understanding of how information is stored, but they also affect the transfer of information between brain areas during the consolidation process. For this thesis, I investigated the evolution of memory-related activity during sleep periods expected to be involved in consolidation in the hippocampus and between the hippocampus and prefrontal cortex. I found that reactivated activity in the hippocampus gradually transformed during prolonged periods of sleep and inactivity. In the beginning, neural activity strongly resembled acquisition activity, whereas, with the progression of time, it became more similar to the subsequent recall activity. NREM periods drove this process, while rapid-eye movement (REM) periods showed a resetting effect. This reactivation drift was due to firing rate changes of a subset of cells and mirrored the representational changes from the acquisition to the recall. A stable subset of cells withstood the drift and maintained their activity. Therefore, my results indicate that memory-related representations undergo spontaneous modifications during consolidation periods and that these changes are predictive of representational drift. Furthermore, I found that the amount of change in the neural activity during subsequent sleep periods was biased by prior behavioral performance. Observed changes in the hippocampus and the prefrontal cortex were synchronized and increased after poor performance, highlighting a potential role in the exchange of information. Low-variance vii periods with distinct, more stable activity from a subset of cells significantly contributed to the heightened synchrony between both areas. Hence, interleaved phases of more stable neural activity could facilitate the information transfer between brain areas. In conclusion, my investigations underline the fluidity of memory-related representations and assign a prominent role to sleep reactivation periods in their evolution. In addition, I identified a potential mechanism of stable activity phases that might facilitate the synchronization across hippocampal-prefrontal activity despite ongoing changes. Reconciling and integrating findings from both spontaneous and behaviorally-related representational changes in functionally related brain areas will help to broaden our understanding of how knowledge is stored, maintained, updated, and transferred between brain areas.}, author = {Bollmann, Lars}, issn = {2663-337X}, keywords = {Memory, Hippocampus, Consolidation}, pages = {103}, publisher = {Institute of Science and Technology Austria}, title = {{Stability and change in the memory system during rest}}, doi = {10.15479/at:ista:17346}, year = {2024}, } @phdthesis{15352, abstract = {Epilepsy affects about 50 to 65 million people globally. It summarizes a spectrum of neurological disorders that have in common a hyperactivity of the neuronal network resulting in seizures. A common assumption is that an imbalance between neuronal excitation and inhibition is a key mechanism in seizure generation and epileptogeneisis. In at least one-third of the patients, current therapies have proven unsuccessful in treating seizure progression. One potential reason could be that the therapies only focus on neurons. Recent studies suggest that neuronal hyperactivity causes a microglial response, which reinstates brain homeostasis. Additionally, interactions between microglia and neurons have been shown to inhibit neuronal firing and dampen seizure activity. However, the exact relationship between microglia and seizure progression in epilepsy is yet to be elucidated. A main bottleneck is that several studies investigate microglia dynamics in ex vivo slice models, which can severely affect the microglia dynamics due to their rapid response to environmental changes. On the other hand, in vivo studies focus mostly on behavior characterization of the epileptic seizure phenotype and their long-term consequences on microglia activity leaving out the direct consequences of acute seizure activity on microglia dynamics. Here, we perform a pilot study to combine electroencephalography (EEG) and in vivo live imaging to directly monitor and correlate the onset of seizure activity with microglia response. To induce seizures, we take advantage of the kainic acid (KA) model, which represents similar neuropathological and electroencephalographic features seen in human patients with temporal lobe epilepsy (TLE). After confirmation of induction of the seizure and microglia activity in the hippocampus as a focal point, we investigated whether these changes also reached the primary visual cortex (V1) as a secondary generalized seizure activity. Indeed, we found that microglia changed their morphology at high doses of KA in the V1. Next, we optimized each of the two methodological components: for the EEG recording, our initial attempts under the microscope suffered from extensive electrical noise, which overlaid the actual signal. Thus, we built a customized Faraday-cage and confirmed that the signal-to-noise ratio was sufficiently reduced to be able to record brain oscillatory activity. For the in vivo live imaging of microglia, we had to optimize the imaging parameters, so that we would be able to detect microglial processes in a sufficient resolution to track their process changes. Finally, we combined both methodologies with the KA model. We confirmed that KA induced seizure activity and found first indication that those correlate with microglia volume changes. Overall, we have developed a first methodological approach, which allows the analysis of the acute effects of seizure onset on microglia. Future studies will have to continue to optimize the drift during imaging recording and the post-image analysis. }, author = {Murmann, Julie Stefanie}, issn = {2791-4585}, pages = {54}, publisher = {Institute of Science and Technology Austria}, title = {{Investigating acute microglia response to seizure activity in vivo: Combining 2-Photon imaging and EEG recording}}, doi = {10.15479/at:ista:15352}, year = {2024}, } @phdthesis{14821, abstract = {The hippocampus is central to memory formation, storage and retrieval over many timescales. Neurons in this brain area are highly selective to spatial position as well as to many other variables of the environment. It is believed that the selectivity patterns of hippocampal neurons reflect the structure of tasks an animal performs. However, especially at timescales longer than a few minutes or hours it is not fully known how these representations evolve, nor how they map to behaviour in the process. In this thesis, I monitored the evolution of hippocampal representations in a novel spatial-associative memory task for rats. Reward locations were associated with global sensory cues (i.e. context); animals had to remember the associations and dig for food in those locations only. I used in vivo electrophysiology to record the activity of the hippocampus dorsal CA1 neurons during the learning period of a few days. I report here a novel and simple method to classify behaviour performance to account for individual variability in learning speed and spurious performance unrelated to true task rule learning. Using this classification I was then able to investigate neural responses on different stages of learning matched across animals. On the first day of learning, I observed a fast formation of single-cell selectivity to task variables which remained stable over days. I also observed that reward tuning was not a single process but dependent on task-related cognitive load. At the population level, a linear decoding approach revealed a hierarchy in the representation of task variables that changed with learning. In the high-dimensional space of population activity, the representation of contexts was specific to each position in the maze, and could thus be better decoded if the position was known. The decoding of position did not improve with knowledge of other variables. As learning progressed, the hippocampal code underwent a reorganisation of high-variance directions in population activity, identified by principal component analysis. I found that dominant dimensions started carrying increasing amounts of information about task context specifically at those positions where it mattered for task performance. When I contrasted this with variables less relevant to task performance (e.g. movement direction), I did not observe differences in decoding quality over positions nor a reduction of dimensionality with learning. Overall, the largest changes in CA1 neural response with task learning happened in a matter of a few trials; over days, changes undetectable in single-cell statistics were responsible for re-structuring the hierarchy of neural representations at the population level; these changes were task-specific and reflected different stages of learning. This indicates that complex task learning may involve different magnitudes of response modulation in CA1, which happen at specific time scales linked to behaviour.}, 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}, } @article{18706, abstract = {We prove discrete-to-continuum convergence for dynamical optimal transport on Zd -periodic graphs with cost functional having linear growth at infinity. This result provides an answer to a problem left open by Gladbach, Kopfer, Maas, and Portinale (Calc Var Partial Differential Equations 62(5), 2023), where the convergence behaviour of discrete boundary-value dynamical transport problems is proved under the stronger assumption of superlinear growth. Our result extends the known literature to some important classes of examples, such as scaling limits of 1 -Wasserstein transport problems. Similarly to what happens in the quadratic case, the geometry of the graph plays a crucial role in the structure of the limit cost function, as we discuss in the final part of this work, which includes some visual representations.}, author = {Portinale, Lorenzo and Quattrocchi, Filippo}, issn = {1469-4425}, journal = {European Journal of Applied Mathematics}, pages = {1--29}, publisher = {Cambridge University Press}, title = {{Discrete-to-continuum limits of optimal transport with linear growth on periodic graphs}}, doi = {10.1017/s0956792524000810}, year = {2024}, } @unpublished{20571, abstract = {We prove the convergence of a modified Jordan--Kinderlehrer--Otto scheme to a solution to the Fokker--Planck equation in $\Omega \Subset \mathbb{R}^d$ with general, positive and temporally constant, Dirichlet boundary conditions. We work under mild assumptions on the domain, the drift, and the initial datum. In the special case where $\Omega$ is an interval in $\mathbb{R}^1$, we prove that such a solution is a gradient flow -- curve of maximal slope -- within a suitable space of measures, endowed with a modified Wasserstein distance. Our discrete scheme and modified distance draw inspiration from contributions by A. Figalli and N. Gigli [J. Math. Pures Appl. 94, (2010), pp. 107--130], and J. Morales [J. Math. Pures Appl. 112, (2018), pp. 41--88] on an optimal-transport approach to evolution equations with Dirichlet boundary conditions. Similarly to these works, we allow the mass to flow from/to the boundary $\partial \Omega$ throughout the evolution. However, our leading idea is to also keep track of the mass at the boundary by working with measures defined on the whole closure $\overline \Omega$. The driving functional is a modification of the classical relative entropy that also makes use of the information at the boundary. As an intermediate result, when $\Omega$ is an interval in $\mathbb{R}^1$, we find a formula for the descending slope of this geodesically nonconvex functional. }, author = {Quattrocchi, Filippo}, booktitle = {arXiv}, keywords = {gradient flows, Jordan–Kinderlehrer–Otto scheme, curves of maximal slope, optimal transport, Dirichlet boundary conditions, Fokker–Planck equation}, title = {{Variational structures for the Fokker-Planck equation with general Dirichlet boundary conditions}}, doi = {10.48550/arXiv.2403.07803}, year = {2024}, } @unpublished{20570, abstract = {We investigate the minimal error in approximating a general probability measure $\mu$ on $\mathbb{R}^d$ by the uniform measure on a finite set with prescribed cardinality $n$. The error is measured in the $p$-Wasserstein distance. In particular, when $1\le p