ISTA Thesis

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

Multipotent progenitors instruct ontogeny of the superior colliculus

The superior colliculus (SC) in the mammalian midbrain is essential for multisensory integration and is composed of a rich diversity of excitatory and inhibitory neurons and glia. However, the developmental principles directing the generation of SC cell-type diversity are not understood. Here, we pursued systematic cell lineage tracing in silico and in vivo, preserving full spatial information, using genetic mosaic analysis with double markers (MADM)-based clonal analysis with single-cell sequencing (MADM-CloneSeq). The analysis of clonally related cell lineages revealed that radial glial progenitors (RGPs) in SC are exceptionally multipotent. Individual resident RGPs have the capacity to produce all excitatory and inhibitory SC neuron types, even at the stage of terminal division. While individual clonal units show no pre-defined cellular composition, the establishment of appropriate relative proportions of distinct neuronal types occurs in a PTEN-dependent manner. Collectively, our findings provide an inaugural framework at the single-RGP/-cell level of the mammalian SC ontogeny

Weighted packet selection for rechargeable links in cryptocurrency networks: Complexity and approximation

We consider a natural problem dealing with weighted packet selection across a rechargeable link, which e.g., finds applications in cryptocurrency networks. The capacity of a link (u, v) is determined by how many nodes u and v allocate for this link. Specifically, the input is a finite ordered sequence of packets that arrive in both directions along a link. Given (u, v) and a packet of weight x going from u to v, node u can either accept or reject the packet. If u accepts the packet, the capacity on link (u, v) decreases by x. Correspondingly, v's capacity on increases by x. If a node rejects the packet, this will entail a cost affinely linear in the weight of the packet. A link is “rechargeable” in the sense that the total capacity of the link has to remain constant, but the allocation of capacity at the ends of the link can depend arbitrarily on the nodes' decisions. The goal is to minimise the sum of the capacity injected into the link and the cost of rejecting packets. We show that the problem is NP-hard, but can be approximated efficiently with a ratio of (1+E) . (1+3) for some arbitrary E>0

A dynamic duo: Understanding the roles of FtsZ and FtsA for Escherichia coli cell division through in vitro approaches

Bacteria divide by binary fission. The protein machine responsible for this process is the divisome, a transient assembly of more than 30 proteins in and on the surface of the cytoplasmic membrane. Together, they constrict the cell envelope and remodel the peptidoglycan layer to eventually split the cell into two. For Escherichia coli, most molecular players involved in this process have probably been identified, but obtaining the quantitative information needed for a mechanistic understanding can often not be achieved from experiments in vivo alone. Since the discovery of the Z-ring more than 30 years ago, in vitro reconstitution experiments have been crucial to shed light on molecular processes normally hidden in the complex environment of the living cell. In this review, we summarize how rebuilding the divisome from purified components – or at least parts of it - have been instrumental to obtain the detailed mechanistic understanding of the bacterial cell division machinery that we have today

Die faszinierende Topologie rotierender Quanten

Die Quantenrotation ist ein spannendes Phänomen, das in vielen verschiedenen Systemen auftritt, von Molekülen und Atomen bis hin zu subatomaren Teilchen wie Neutronen und Protonen. Durch den Einsatz von starken Laserpulsen ist es möglich, die mathematisch anspruchsvolle Topologie der Rotation von Molekülen aufzudecken und topologisch geschützte Zustände zu erzeugen, die unerwartetes Verhalten zeigen. Diese Entdeckungen könnten Auswirkungen auf die Molekülphysik und physikalische Chemie haben und die Entwicklung neuer Technologien ermöglichen. Die Verbindung von Quantenrotation und Topologie stellt ein aufregendes, interdisziplinäres Forschungsfeld dar und bietet neue Wege zur Kontrolle und Nutzung von quantenmechanischen Phänomenen

A discovery tour in random Riemannian geometry

We study random perturbations of a Riemannian manifold (M, g) by means of so-called Fractional Gaussian Fields, which are defined intrinsically by the given manifold. The fields h• : ω → hω will act on the manifold via the conformal transformation g → gω := e2hω g. Our focus will be on the regular case with Hurst parameter H > 0, the critical case H = 0 being the celebrated Liouville geometry in two dimensions. We want to understand how basic geometric and functional-analytic quantities like diameter, volume, heat kernel, Brownian motion, spectral bound, or spectral gap change under the influence of the noise. And if so, is it possible to quantify these dependencies in terms of key parameters of the noise? Another goal is to define and analyze in detail the Fractional Gaussian Fields on a general Riemannian manifold, a fascinating object of independent interest

Local controls on near-surface glacier cooling under warm atmospheric conditions

The near-surface boundary layer can mediate the response of mountain glaciers to external climate, cooling the overlying air and promoting a density-driven glacier wind. The fundamental processes are conceptually well understood, though the magnitudes of cooling and presence of glacier winds are poorly quantified in space and time, increasing the forcing uncertainty for melt models. We utilize a new data set of on-glacier meteorological measurements on three neighboring glaciers in the Swiss Alps to explore their distinct response to regional climate under the extreme 2022 summer. We find that synoptic wind origins and local terrain modifications, not only glacier size, play an important role in the ability of a glacier to cool the near-surface air. Warm air intrusions from valley or synoptically-driven winds onto the glacier can occur between ∼19% and 64% of the time and contribute between 3% and 81% of the total sensible heat flux to the surface during warm afternoon hours, depending on the fetch of the glacier flowline and its susceptibility to boundary layer erosion. In the context of extreme summer warmth, indicative of future conditions, the boundary layer cooling (up to 6.5°C cooler than its surroundings) and resultant katabatic wind flow are highly heterogeneous between the study glaciers, highlighting the complex and likely non-linear response of glaciers to an uncertain future

Experimental evaluation of fully dynamic k-means via coresets

For a set of points in Rd, the Euclidean k-means problems consists of finding k centers such that the sum of distances squared from each data point to its closest center is minimized. Coresets are one the main tools developed recently to solve this problem in a big data context. They allow to compress the initial dataset while preserving its structure: running any algorithm on the coreset provides a guarantee almost equivalent to running it on the full data. In this work, we study coresets in a fully-dynamic setting: points are added and deleted with the goal to efficiently maintain a coreset with which a k-means solution can be computed. Based on an algorithm from Henzinger and Kale [ESA'20], we present an efficient and practical implementation of a fully dynamic coreset algorithm, that improves the running time by up to a factor of 20 compared to our non-optimized implementation of the algorithm by Henzinger and Kale, without sacrificing more than 7% on the quality of the k-means solution

Interface engineering modulation combined with electronic structure modification of Zn-doped NiO heterostructure for efficient water-splitting activity

Production of hydrogen at large scale requires development of non-noble, inexpensive, and high-performing catalysts for constructing water-splitting devices. Herein, we report the synthesis of Zn-doped NiO heterostructure (ZnNiO) catalysts at room temperature via a coprecipitation method followed by drying (at 80 °C, 6 h) and calcination at an elevated temperature of 400 °C for 5 h under three distinct conditions, namely, air, N2, and vacuum. The vacuum-synthesized catalyst demonstrates a low overpotential of 88 mV at −10 mA cm–2 and a small Tafel slope of 73 mV dec–1 suggesting relatively higher charge transfer kinetics for hydrogen evolution reactions (HER) compared with the specimens synthesized under N2 or O2 atmosphere. It also demonstrates an oxygen evolution (OER) overpotential of 260 mV at 10 mA cm–2 with a low Tafel slope of 63 mV dec–1. In a full-cell water-splitting device, the vacuum-synthesized ZnNiO heterostructure demonstrates a cell voltage of 1.94 V at 50 mA cm–2 and shows remarkable stability over 24 h at a high current density of 100 mA cm–2. It is also demonstrated in this study that Zn-doping, surface, and interface engineering in transition-metal oxides play a crucial role in efficient electrocatalytic water splitting. Also, the results obtained from density functional theory (DFT + U = 0–8 eV), where U is the on-site Coulomb repulsion parameter also known as Hubbard U, based electronic structure calculations confirm that Zn doping constructively modifies the electronic structure, in both the valence band and the conduction band, and found to be suitable in tailoring the carrier’s effective masses of electrons and holes. The decrease in electron’s effective masses together with large differences between the effective masses of electrons and holes is noticed, which is found to be mainly responsible for achieving the best water-splitting performance from a 9% Zn-doped NiO sample prepared under vacuum

A structurally precise mechanism links an epilepsy-associated KCNC2 potassium channel mutation to interneuron dysfunction

De novo heterozygous variants in KCNC2 encoding the voltage-gated potassium (K+) channel subunit Kv3.2 are a recently described cause of developmental and epileptic encephalopathy (DEE). A de novo variant in KCNC2 c.374G > A (p.Cys125Tyr) was identified via exome sequencing in a patient with DEE. Relative to wild-type Kv3.2, Kv3.2-p.Cys125Tyr induces K+ currents exhibiting a large hyperpolarizing shift in the voltage dependence of activation, accelerated activation, and delayed deactivation consistent with a relative stabilization of the open conformation, along with increased current density. Leveraging the cryogenic electron microscopy (cryo-EM) structure of Kv3.1, molecular dynamic simulations suggest that a strong π-π stacking interaction between the variant Tyr125 and Tyr156 in the α-6 helix of the T1 domain promotes a relative stabilization of the open conformation of the channel, which underlies the observed gain of function. A multicompartment computational model of a Kv3-expressing parvalbumin-positive cerebral cortex fast-spiking γ-aminobutyric acidergic (GABAergic) interneuron (PV-IN) demonstrates how the Kv3.2-Cys125Tyr variant impairs neuronal excitability and dysregulates inhibition in cerebral cortex circuits to explain the resulting epilepsy