@article{14826,
  abstract     = {The plant-signaling molecule auxin triggers fast and slow cellular responses across land plants and algae. The nuclear auxin pathway mediates gene expression and controls growth and development in land plants, but this pathway is absent from algal sister groups. Several components of rapid responses have been identified in Arabidopsis, but it is unknown if these are part of a conserved mechanism. We recently identified a fast, proteome-wide phosphorylation response to auxin. Here, we show that this response occurs across 5 land plant and algal species and converges on a core group of shared targets. We found conserved rapid physiological responses to auxin in the same species and identified rapidly accelerated fibrosarcoma (RAF)-like protein kinases as central mediators of auxin-triggered phosphorylation across species. Genetic analysis connects this kinase to both auxin-triggered protein phosphorylation and rapid cellular response, thus identifying an ancient mechanism for fast auxin responses in the green lineage.},
  author       = {Kuhn, Andre and Roosjen, Mark and Mutte, Sumanth and Dubey, Shiv Mani and Carrillo Carrasco, Vanessa Polet and Boeren, Sjef and Monzer, Aline and Koehorst, Jasper and Kohchi, Takayuki and Nishihama, Ryuichi and Fendrych, Matyas and Sprakel, Joris and Friml, Jiří and Weijers, Dolf},
  issn         = {1097-4172},
  journal      = {Cell},
  keywords     = {General Biochemistry, Genetics and Molecular Biology},
  number       = {1},
  pages        = {130--148.e17},
  publisher    = {Elsevier},
  title        = {{RAF-like protein kinases mediate a deeply conserved, rapid auxin response}},
  doi          = {10.1016/j.cell.2023.11.021},
  volume       = {187},
  year         = {2024},
}

@inproceedings{18702,
  abstract     = {In this work we prove lower bounds on the (communication) cost of maintaining a shared key among a dynamic group of users. Being “dynamic” means one can add and remove users from the group. This captures important protocols like multicast encryption (ME) and continuous group-key agreement (CGKA), which is the primitive underlying many group messaging applications. We prove our bounds in a combinatorial setting where the state of the protocol progresses in rounds. The state of the protocol in each round is captured by a set system, with each of its elements specifying a set of users who share a secret key. We show this combinatorial model implies bounds in symbolic models for ME and CGKA that capture, as building blocks, PRGs, PRFs, dual PRFs, secret sharing, and symmetric encryption in the setting of ME, and PRGs, PRFs, dual PRFs, secret sharing, public-key encryption, and key-updatable public-key encryption in the setting of CGKA. The models are related to the ones used by Micciancio and Panjwani (Eurocrypt’04) and Bienstock et al. (TCC’20) to analyze ME and CGKA, respectively. We prove – using the Bollobás’ Set Pairs Inequality – that the cost (number of uploaded ciphertexts) for replacing a set of d users in a group of size n is Ω(dln(n/d)). Our lower bound is asymptotically tight and both improves on a bound of Ω(d) by Bienstock et al. (TCC’20), and generalizes a result by Micciancio and Panjwani (Eurocrypt’04), who proved a lower bound of Ω(log(n)) for d=1. },
  author       = {Anastos, Michael and Auerbach, Benedikt and Baig, Mirza Ahad and Cueto Noval, Miguel and Kwan, Matthew Alan and Pascual Perez, Guillermo and Pietrzak, Krzysztof Z},
  booktitle    = {22nd International Conference on Theory of Cryptography},
  isbn         = {9783031780103},
  issn         = {1611-3349},
  location     = {Milan, Italy},
  pages        = {413--443},
  publisher    = {Springer Nature},
  title        = {{The cost of maintaining keys in dynamic groups with applications to multicast encryption and group messaging}},
  doi          = {10.1007/978-3-031-78011-0_14},
  volume       = {15364},
  year         = {2024},
}

@article{17373,
  abstract     = {Scanning Kelvin probe microscopy (SKPM) is a powerful technique for investigating the electrostatic properties of material surfaces, enabling the imaging of variations in work function, topology, surface charge density, or combinations thereof. Regardless of the underlying signal source, SKPM results in a voltage image, which is spatially distorted due to the finite size of the probe, long-range electrostatic interactions, mechanical and electrical noise, and the finite response time of the electronics. In order to recover the underlying signal, it is necessary to deconvolve the measurement with an appropriate point spread function (PSF) that accounts the aforementioned distortions, but determining this PSF is difficult. Here, we describe how such PSFs can be determined experimentally and show how they can be used to recover the underlying information of interest. We first consider the physical principles that enable SKPM and discuss how these affect the system PSF. We then show how one can experimentally measure PSFs by looking at well-defined features, and that these compare well to simulated PSFs, provided scans are performed extremely slowly and carefully. Next, we work at realistic scan speeds and show that the idealized PSFs fail to capture temporal distortions in the scan direction. While simulating PSFs for these situations would be quite challenging, we show that measuring PSFs with similar scan conditions works well. Our approach clarifies the basic principles and inherent challenges to SKPM measurements and gives practical methods to improve results.},
  author       = {Lenton, Isaac C and Pertl, Felix and Shafeek, Lubuna B and Waitukaitis, Scott R},
  issn         = {1089-7550},
  journal      = {Journal of Applied Physics},
  number       = {4},
  publisher    = {AIP Publishing},
  title        = {{Beyond the blur: Using experimentally determined point spread functions to improve scanning Kelvin probe imaging}},
  doi          = {10.1063/5.0215151},
  volume       = {136},
  year         = {2024},
}

@inbook{17425,
  abstract     = {Mosaic Analysis with Double Markers (MADM) is a powerful genetic method typically used for lineage tracing and to disentangle cell autonomous and tissue-wide roles of candidate genes with single cell resolution. Given the relatively sparse labeling, depending on which of the 19 MADM chromosomes one chooses, the MADM approach represents the perfect opportunity for cell morphology analysis. Various MADM studies include reports of morphological anomalies and phenotypes in the central nervous system (CNS). MADM for any candidate gene can easily incorporate morphological analysis within the experimental workflow. Here, we describe the methods of morphological cell analysis which we developed in the course of diverse recent MADM studies. This chapter will specifically focus on methods to quantify aspects of the morphology of neurons and astrocytes within the CNS, but these methods can broadly be applied to any MADM-labeled cells throughout the entire organism. We will cover two analyses—soma volume and dendrite characterization—of physical characteristics of pyramidal neurons in the somatosensory cortex, and two analyses—volume and Sholl analysis—of astrocyte morphology.},
  author       = {Miranda, Osvaldo and Cheung, Giselle T and Hippenmeyer, Simon},
  booktitle    = {Neuronal Morphogenesis},
  editor       = {Toyooka, Kazuhito},
  isbn         = {9781071639689},
  issn         = {1940-6029},
  pages        = {283--299},
  publisher    = {Springer Nature},
  title        = {{Morphological Analysis of Neurons and Glia Using Mosaic Analysis with Double Markers}},
  doi          = {10.1007/978-1-0716-3969-6_19},
  volume       = {2831},
  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{17881,
  abstract     = {This work can be broadly classified into the study of critical phenomena in a one dimensional
array of Josephson junctions. While we study quantum criticality when the array is in thermal
equilibrium at zero bias, the non-equilibrium study involves understanding the bistability of the
array at a critical non-zero bias. This work furthers our knowledge in understanding quantum
critical behaviour at finite temperatures in a one dimensional Josephson array, while also
establishing relaxation behaviour dual to that observed in a single Josephson junction.
Chapter 1 briefly introduces the model to understand superconductor-insulator phase transition
in a one dimensional Josephson array and points out the state of the field from where we
started our zero-bias experiments. In this context it discusses the phase-charge duality observed
in a Josephson array and its dual hysteretic behaviour to that of a single junction, setting the
ground for our non-equilibrium study of the array.
Chapter 2 shows the experimental setup and the chip layout of the device we measured.
In chapter 3 we show that, unlike the typical quantum-critical broadening scenario, in one dimensional Josephson arrays temperature dramatically shifts the critical region. This shift leads
to a regime of superconductivity at high temperature, arising from the melted zero-temperature
insulator. Our results quantitatively explain the low-temperature onset of superconductivity in
nominally insulating regimes, and the transition to the strongly insulating phase. We further
present, to our knowledge, the first understanding of the onset of anomalous-metallic resistance
saturation [30]. This work demonstrates a non-trivial interplay between thermal effects and
quantum criticality. A practical consequence is that, counterintuitively, the coherence of
high-impedance quantum circuits is expected to be stabilized by thermal fluctuations.
In chapter 4, we show relaxation oscillations in a current-biased one dimensional array of
Josephson junctions. These oscillations are well described by a circuit model, dual to the
ordinary Josephson relaxation oscillations [72]. Injection locking these oscillations results in
current plateaux. The relaxation step is found to obey a characteristic self-consistent relation,
suggesting that it is governed by overheating effects.
Chapter 5 describes the various checks and analysis we performed to support our conclusions
made in chapters 3 and 4.
Finally, chapter 6 describes the nanofabrication steps and the finite element electromagnetic
simulations we performed to fabricate our devices.},
  author       = {Mukhopadhyay, Soham},
  isbn         = {978-3-99078-043-5},
  issn         = {2663-337X},
  pages        = {82},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Thermal effects in one dimensional Josephson chains}},
  doi          = {10.15479/at:ista:17881},
  year         = {2024},
}

@unpublished{18057,
  abstract     = {We report relaxation oscillations in a one-dimensional array of Josephson
junctions. The oscillations are circuit-dual to those ordinarily observed in
single junctions. The dual circuit quantitatively accounts for temporal
dynamics of the array, including the dependence on biasing conditions.
Injection locking the oscillations results in well-developed current plateaux.
A thermal model explains the relaxation step of the oscillations.},
  author       = {Mukhopadhyay, Soham and Lancheros Naranjo, Diego A and Senior, Jorden L and Higginbotham, Andrew P},
  booktitle    = {arXiv},
  title        = {{Dual relaxation oscillations in a Josephson junction array}},
  doi          = {10.48550/arXiv.2408.07829},
  year         = {2024},
}

@article{17890,
  abstract     = {Our understanding of the molecular pathways that regulate oogenesis and define cellular identity in the Arthropod female reproductive system and the extent of their conservation is currently very limited. This is due to the focus on model systems, including Drosophila and Daphnia, which do not reflect the observed diversity of morphologies, reproductive modes, and sex chromosome systems. We use single-nucleus RNA and ATAC sequencing to produce a comprehensive single nucleus atlas of the adult Artemia franciscana female reproductive system. We map our data to the Fly Cell Atlas single-nucleus dataset of the Drosophila melanogaster ovary, shedding light on the conserved regulatory programs between the two distantly related Arthropod species. We identify the major cell types known to be present in the Artemia ovary, including germ cells, follicle cells, and ovarian muscle cells. Additionally, we use the germ cells to explore gene regulation and expression of the Z chromosome during meiosis, highlighting its unique regulatory dynamics and allowing us to explore the presence of meiotic sex chromosome silencing in this group.},
  author       = {Elkrewi, Marwan N and Vicoso, Beatriz},
  issn         = {1553-7404},
  journal      = {PLoS Genetics},
  number       = {8},
  publisher    = {Public Library of Science},
  title        = {{Single-nucleus atlas of the Artemia female reproductive system suggests germline repression of the Z chromosome}},
  doi          = {10.1371/journal.pgen.1011376},
  volume       = {20},
  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{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{14843,
  abstract     = {The coupling between Ca2+ channels and release sensors is a key factor defining the signaling properties of a synapse. However, the coupling nanotopography at many synapses remains unknown, and it is unclear how it changes during development. To address these questions, we examined coupling at the cerebellar inhibitory basket cell (BC)-Purkinje cell (PC) synapse. Biophysical analysis of transmission by paired recording and intracellular pipette perfusion revealed that the effects of exogenous Ca2+ chelators decreased during development, despite constant reliance of release on P/Q-type Ca2+ channels. Structural analysis by freeze-fracture replica labeling (FRL) and transmission electron microscopy (EM) indicated that presynaptic P/Q-type Ca2+ channels formed nanoclusters throughout development, whereas docked vesicles were only clustered at later developmental stages. Modeling suggested a developmental transformation from a more random to a more clustered coupling nanotopography. Thus, presynaptic signaling developmentally approaches a point-to-point configuration, optimizing speed, reliability, and energy efficiency of synaptic transmission.},
  author       = {Chen, JingJing and Kaufmann, Walter and Chen, Chong and Arai, Itaru and Kim, Olena and Shigemoto, Ryuichi and Jonas, Peter M},
  issn         = {1097-4199},
  journal      = {Neuron},
  number       = {5},
  pages        = {755--771.e9},
  publisher    = {Elsevier},
  title        = {{Developmental transformation of Ca2+ channel-vesicle nanotopography at a central GABAergic synapse}},
  doi          = {10.1016/j.neuron.2023.12.002},
  volume       = {112},
  year         = {2024},
}

@phdthesis{15101,
  abstract     = {The coupling between presynaptic Ca2+ channels and release sensors is a key factor that
determines speed and efficacy of synapse transmission. At some excitatory synapses,
channel–sensor coupling becomes tighter during development, and tightening is often
associated with a switch in the reliance on different Ca2+ channel subtypes. However, the
coupling topography at many synapses remains unknown, and it is unclear how it changes
during development. To address this question, we analyzed the coupling configuration at the
cerebellar basket cell (BC) to Purkinje cell (PC) synapse at different developmental stages,
combining biophysical analysis, structural analysis, and modeling.
Quantal analysis of BC–PC indicated that release probability decreased, while the
number of functional sites increased during development. Although transmitter release
persistently relied on P/Q-type Ca2+ channels in the time period postnatal day 7–23, effects
of the Ca2+ chelator EGTA and BAPTA applied by intracellular pipette perfusion decreased
during development, indicative of tightening of source-sensor coupling. Furthermore,
presynaptic action potentials became shorter during development, suggesting reduced
efficacy of Ca2+ channel activation.
Structural analysis by freeze-fracture replica labeling (FRL) and transmission electron
microscopy (EM) indicated that presynaptic P/Q-type Ca2+ channels formed nanoclusters
throughout development, whereas docked vesicles were only clustered at later
developmental stages. The number of functional release sites correlated better with the AZ
number early in development, but match better with the Ca2+ channel cluster number at later
stages.
Modeling suggested a developmental transformation from a more random to a more
clustered coupling nanotopography. Thus, presynaptic signaling developmentally approaches
a point-to-point configuration, optimizing speed, reliability, and energy efficiency of synaptic
transmission.},
  author       = {Chen, JingJing},
  issn         = {2663-337X},
  pages        = {84},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Developmental transformation of nanodomain coupling between Ca2+ channels and release sensors at a central GABAergic synapse}},
  doi          = {10.15479/at:ista:15101},
  year         = {2024},
}

@phdthesis{18471,
  abstract     = {Spatial omics technologies are enriching our understanding of complex biological samples, by
allowing us to study their molecular composition while preserving the spatial relationships
between molecules in their native context. As the field continues to advance, there are
technical challenges that need to be addressed in order to take full advantage of the spatial
capabilities of these methods. In this work, I present two technical developments that I
established for multiplexed error robust FISH (MERFISH) throughout my PhD: (1) pushing the
spatial resolution limits to the nanoscale, and (2) adding rich tissue context to the mouse brain
transcriptome. To achieve nanoscale resolution with MERFISH in cultured cells, I combined it
with stimulated emission depletion (STED) and expansion microscopy (ExM) to achieve a
spatial resolution as low as ~20 nm, and explored the compatibility of MERFISH with singlemolecule localization microscopy (SMLM) techniques. To visualize targeted mRNAs in mouse
brain tissue, I applied the comprehensive analysis of tissues across scales (CATS) toolbox, which
provides an unbiased morphological readout by labeling the extracellular domain. I
successfully established this method, which we call CATS-MERFISH-ExM, to work with thick
mouse brain slices, being able to extract transcriptomics information with 3D tissue context.
CATS-MERFISH-ExM enabled us to identify cell types and further visualize the subcellular
distribution of transcripts in mouse brain tissue, shedding light on the neuropil-specific
transcriptome. This method provides integrated information on cellular structure and
transcriptomes in situ, and could potentially be applied with other modalities, opening new
avenues for scientific discovery. },
  author       = {Agudelo Duenas, Nathalie},
  isbn         = {978-3-99078-044-2},
  issn         = {2663-337X},
  pages        = {97},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Visualizing the neuronal transcriptional landscape with tissue context}},
  doi          = {10.15479/at:ista:18471},
  year         = {2024},
}

@phdthesis{18574,
  abstract     = {Biological vision is unlike a camera; rather than transmitting light information faithfully, early
visual circuits process the visual scene to convey only the relevant information in an efficient
manner. Consequentially, the nature of this visual processing then depends on what is the
relevant information in a scene and on the notion of efficiency. In this work, I study how visual
processing is modulated by two different variations in the visual scene. First, I discovered that
in the mouse (Mus musculus) retina, Retinal Ganglion Cells in the upper and lower visual
field have differences in the center surround structure of their receptive fields. Comparison
with models of efficient coding show that this adaptation likely evolved to cope with the
brightness gradient from the sky to the ground that is pervasive in natural scenes. In the
second project, I study how the downstream neurons in the Superior Colliculus dynamically
change their temporal selectivity depending on the ambient luminance and behavioral state.
As the scene gets darker or when the animal is is less aroused, the neuronal responses get
laggier, while still maintaining their relative timing with respect to the population. Overall, this
work emphasises the need to understand visual processing in the context of specific demands
of the animal in its the environment. The adaptive changes in the visual system, from the
retinal ganglion cells to the superior colliculus, highlight the intricate ways in which biological
vision optimizes the processing of visual information.
},
  author       = {Gupta, Divyansh},
  isbn         = {978-3-99078-050-3},
  issn         = {2663-337X},
  pages        = {86},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Visual adaptations to natural statistics}},
  doi          = {10.15479/at:ista:18574},
  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},
}

@article{15084,
  abstract     = {GABAB receptor (GBR) activation inhibits neurotransmitter release in axon terminals in the brain, except in medial habenula (MHb) terminals, which show robust potentiation. However, mechanisms underlying this enigmatic potentiation remain elusive. Here, we report that GBR activation on MHb terminals induces an activity-dependent transition from a facilitating, tonic to a depressing, phasic neurotransmitter release mode. This transition is accompanied by a 4.1-fold increase in readily releasable vesicle pool (RRP) size and a 3.5-fold increase of docked synaptic vesicles (SVs) at the presynaptic active zone (AZ). Strikingly, the depressing phasic release exhibits looser coupling distance than the tonic release. Furthermore, the tonic and phasic release are selectively affected by deletion of synaptoporin (SPO) and Ca
            <jats:sup>2+</jats:sup>
            -dependent activator protein for secretion 2 (CAPS2), respectively. SPO modulates augmentation, the short-term plasticity associated with tonic release, and CAPS2 retains the increased RRP for initial responses in phasic response trains. The cytosolic protein CAPS2 showed a SV-associated distribution similar to the vesicular transmembrane protein SPO, and they were colocalized in the same terminals. We developed the “Flash and Freeze-fracture” method, and revealed the release of SPO-associated vesicles in both tonic and phasic modes and activity-dependent recruitment of CAPS2 to the AZ during phasic release, which lasted several minutes. Overall, these results indicate that GBR activation translocates CAPS2 to the AZ along with the fusion of CAPS2-associated SVs, contributing to persistency of the RRP increase. Thus, we identified structural and molecular mechanisms underlying tonic and phasic neurotransmitter release and their transition by GBR activation in MHb terminals.},
  author       = {Koppensteiner, Peter and Bhandari, Pradeep and Önal, Hüseyin C and Borges Merjane, Carolina and Le Monnier, Elodie and Roy, Utsa and Nakamura, Yukihiro and Sadakata, Tetsushi and Sanbo, Makoto and Hirabayashi, Masumi and Rhee, JeongSeop and Brose, Nils and Jonas, Peter M and Shigemoto, Ryuichi},
  issn         = {1091-6490},
  journal      = {Proceedings of the National Academy of Sciences of the United States of America},
  number       = {8},
  publisher    = {National Academy of Sciences},
  title        = {{GABAB receptors induce phasic release from medial habenula terminals through activity-dependent recruitment of release-ready vesicles}},
  doi          = {10.1073/pnas.2301449121},
  volume       = {121},
  year         = {2024},
}

@article{17148,
  abstract     = {During neural tube (NT) development, the notochord induces an organizer, the floorplate, which secretes Sonic Hedgehog (SHH) to pattern neural progenitors. Conversely, NT organoids (NTOs) from embryonic stem cells (ESCs) spontaneously form floorplates without the notochord, demonstrating that stem cells can self-organize without embryonic inducers. Here, we investigated floorplate self-organization in clonal mouse NTOs. Expression of the floorplate marker FOXA2 was initially spatially scattered before resolving into multiple clusters, which underwent competition and sorting, resulting in a stable “winning” floorplate. We identified that BMP signaling governed long-range cluster competition. FOXA2+ clusters expressed BMP4, suppressing FOXA2 in receiving cells while simultaneously expressing the BMP-inhibitor NOGGIN, promoting cluster persistence. Noggin mutation perturbed floorplate formation in NTOs and in the NT in vivo at mid/hindbrain regions, demonstrating how the floorplate can form autonomously without the notochord. Identifying the pathways governing organizer self-organization is critical for harnessing the developmental plasticity of stem cells in tissue engineering.},
  author       = {Krammer, Teresa and Stuart, Hannah T. and Gromberg, Elena and Ishihara, Keisuke and Cislo, Dillon and Melchionda, Manuela and Becerril Perez, Fernando and Wang, Jingkui and Costantini, Elena and Rus, Stefanie and Arbanas, Laura and Hörmann, Alexandra and Neumüller, Ralph A. and Elvassore, Nicola and Siggia, Eric and Briscoe, James and Kicheva, Anna and Tanaka, Elly M.},
  issn         = {1878-1551},
  journal      = {Developmental Cell},
  number       = {15},
  pages        = {1940--1953.e10},
  publisher    = {Elsevier},
  title        = {{Mouse neural tube organoids self-organize floorplate through BMP-mediated cluster competition}},
  doi          = {10.1016/j.devcel.2024.04.021},
  volume       = {59},
  year         = {2024},
}

