TY - JOUR AB - Synaptic cell adhesion molecules are increasingly gaining attention for conferring specific properties to individual synapses. Netrin-G1 and netrin-G2 are trans-synaptic adhesion molecules that distribute on distinct axons, and their presence restricts the expression of their cognate receptors, NGL1 and NGL2, respectively, to specific subdendritic segments of target neurons. However, the neural circuits and functional roles of netrin-G isoform complexes remain unclear. Here, we use netrin-G-KO and NGL-KO mice to reveal that netrin-G1/NGL1 and netrin-G2/NGL2 interactions specify excitatory synapses in independent hippocampal pathways. In the hippocampal CA1 area, netrin-G1/NGL1 and netrin-G2/NGL2 were expressed in the temporoammonic and Schaffer collateral pathways, respectively. The lack of presynaptic netrin-Gs led to the dispersion of NGLs from postsynaptic membranes. In accord, netrin-G mutant synapses displayed opposing phenotypes in long-term and short-term plasticity through discrete biochemical pathways. The plasticity phenotypes in netrin-G-KOs were phenocopied in NGL-KOs, with a corresponding loss of netrin-Gs from presynaptic membranes. Our findings show that netrin-G/NGL interactions differentially control synaptic plasticity in distinct circuits via retrograde signaling mechanisms and explain how synaptic inputs are diversified to control neuronal activity. AU - Matsukawa, Hiroshi AU - Akiyoshi Nishimura, Sachiko AU - Zhang, Qi AU - Luján, Rafael AU - Yamaguchi, Kazuhiko AU - Goto, Hiromichi AU - Yaguchi, Kunio AU - Hashikawa, Tsutomu AU - Sano, Chie AU - Shigemoto, Ryuichi AU - Nakashiba, Toshiaki AU - Itohara, Shigeyoshi ID - 2018 IS - 47 JF - Journal of Neuroscience SN - 0270-6474 TI - Netrin-G/NGL complexes encode functional synaptic diversification VL - 34 ER - TY - JOUR AB - We prove that the empirical density of states of quantum spin glasses on arbitrary graphs converges to a normal distribution as long as the maximal degree is negligible compared with the total number of edges. This extends the recent results of Keating et al. (2014) that were proved for graphs with bounded chromatic number and with symmetric coupling distribution. Furthermore, we generalise the result to arbitrary hypergraphs. We test the optimality of our condition on the maximal degree for p-uniform hypergraphs that correspond to p-spin glass Hamiltonians acting on n distinguishable spin- 1/2 particles. At the critical threshold p = n1/2 we find a sharp classical-quantum phase transition between the normal distribution and the Wigner semicircle law. The former is characteristic to classical systems with commuting variables, while the latter is a signature of noncommutative random matrix theory. AU - Erdös, László AU - Schröder, Dominik J ID - 2019 IS - 3-4 JF - Mathematical Physics, Analysis and Geometry TI - Phase transition in the density of states of quantum spin glasses VL - 17 ER - TY - JOUR AB - An asymptotic theory is developed for computing volumes of regions in the parameter space of a directed Gaussian graphical model that are obtained by bounding partial correlations. We study these volumes using the method of real log canonical thresholds from algebraic geometry. Our analysis involves the computation of the singular loci of correlation hypersurfaces. Statistical applications include the strong-faithfulness assumption for the PC algorithm and the quantification of confounder bias in causal inference. A detailed analysis is presented for trees, bow ties, tripartite graphs, and complete graphs. AU - Lin, Shaowei AU - Uhler, Caroline AU - Sturmfels, Bernd AU - Bühlmann, Peter ID - 2013 IS - 5 JF - Foundations of Computational Mathematics TI - Hypersurfaces and their singularities in partial correlation testing VL - 14 ER - TY - GEN AB - Gaussian graphical models have received considerable attention during the past four decades from the statistical and machine learning communities. In Bayesian treatments of this model, the G-Wishart distribution serves as the conjugate prior for inverse covariance matrices satisfying graphical constraints. While it is straightforward to posit the unnormalized densities, the normalizing constants of these distributions have been known only for graphs that are chordal, or decomposable. Up until now, it was unknown whether the normalizing constant for a general graph could be represented explicitly, and a considerable body of computational literature emerged that attempted to avoid this apparent intractability. We close this question by providing an explicit representation of the G-Wishart normalizing constant for general graphs. AU - Caroline Uhler AU - Lenkoski, Alex AU - Richards, Donald ID - 2017 T2 - ArXiv TI - Exact formulas for the normalizing constants of Wishart distributions for graphical models ER - TY - JOUR AB - Radial glial progenitors (RGPs) are responsible for producing nearly all neocortical neurons. To gain insight into the patterns of RGP division and neuron production, we quantitatively analyzed excitatory neuron genesis in the mouse neocortex using Mosaic Analysis with Double Markers, which provides single-cell resolution of progenitor division patterns and potential in vivo. We found that RGPs progress through a coherent program in which their proliferative potential diminishes in a predictable manner. Upon entry into the neurogenic phase, individual RGPs produce ∼8–9 neurons distributed in both deep and superficial layers, indicating a unitary output in neuronal production. Removal of OTX1, a transcription factor transiently expressed in RGPs, results in both deep- and superficial-layer neuron loss and a reduction in neuronal unit size. Moreover, ∼1/6 of neurogenic RGPs proceed to produce glia. These results suggest that progenitor behavior and histogenesis in the mammalian neocortex conform to a remarkably orderly and deterministic program. AU - Gao, Peng AU - Postiglione, Maria P AU - Krieger, Teresa AU - Hernandez, Luisirene AU - Wang, Chao AU - Han, Zhi AU - Streicher, Carmen AU - Papusheva, Ekaterina AU - Insolera, Ryan AU - Chugh, Kritika AU - Kodish, Oren AU - Huang, Kun AU - Simons, Benjamin AU - Luo, Liqun AU - Hippenmeyer, Simon AU - Shi, Song ID - 2022 IS - 4 JF - Cell TI - Deterministic progenitor behavior and unitary production of neurons in the neocortex VL - 159 ER - TY - JOUR AB - The mammalian heart has long been considered a postmitotic organ, implying that the total number of cardiomyocytes is set at birth. Analysis of cell division in the mammalian heart is complicated by cardiomyocyte binucleation shortly after birth, which makes it challenging to interpret traditional assays of cell turnover [Laflamme MA, Murray CE (2011) Nature 473(7347):326–335; Bergmann O, et al. (2009) Science 324(5923):98–102]. An elegant multi-isotope imaging-mass spectrometry technique recently calculated the low, discrete rate of cardiomyocyte generation in mice [Senyo SE, et al. (2013) Nature 493(7432):433–436], yet our cellular-level understanding of postnatal cardiomyogenesis remains limited. Herein, we provide a new line of evidence for the differentiated α-myosin heavy chain-expressing cardiomyocyte as the cell of origin of postnatal cardiomyogenesis using the “mosaic analysis with double markers” mouse model. We show limited, life-long, symmetric division of cardiomyocytes as a rare event that is evident in utero but significantly diminishes after the first month of life in mice; daughter cardiomyocytes divide very seldom, which this study is the first to demonstrate, to our knowledge. Furthermore, ligation of the left anterior descending coronary artery, which causes a myocardial infarction in the mosaic analysis with double-marker mice, did not increase the rate of cardiomyocyte division above the basal level for up to 4 wk after the injury. The clonal analysis described here provides direct evidence of postnatal mammalian cardiomyogenesis. AU - Ali, Shah AU - Hippenmeyer, Simon AU - Saadat, Lily AU - Luo, Liqun AU - Weissman, Irving AU - Ardehali, Reza ID - 2020 IS - 24 JF - PNAS TI - Existing cardiomyocytes generate cardiomyocytes at a low rate after birth in mice VL - 111 ER - TY - JOUR AB - Neurotrophins regulate diverse aspects of neuronal development and plasticity, but their precise in vivo functions during neural circuit assembly in the central brain remain unclear. We show that the neurotrophin receptor tropomyosin-related kinase C (TrkC) is required for dendritic growth and branching of mouse cerebellar Purkinje cells. Sparse TrkC knockout reduced dendrite complexity, but global Purkinje cell knockout had no effect. Removal of the TrkC ligand neurotrophin-3 (NT-3) from cerebellar granule cells, which provide major afferent input to developing Purkinje cell dendrites, rescued the dendrite defects caused by sparse TrkC disruption in Purkinje cells. Our data demonstrate that NT-3 from presynaptic neurons (granule cells) is required for TrkC-dependent competitive dendrite morphogenesis in postsynaptic neurons (Purkinje cells)—a previously unknown mechanism of neural circuit development. AU - William, Joo AU - Hippenmeyer, Simon AU - Luo, Liqun ID - 2021 IS - 6209 JF - Science TI - Dendrite morphogenesis depends on relative levels of NT-3/TrkC signaling VL - 346 ER - TY - CONF AB - We present a general framework for applying machine-learning algorithms to the verification of Markov decision processes (MDPs). The primary goal of these techniques is to improve performance by avoiding an exhaustive exploration of the state space. Our framework focuses on probabilistic reachability, which is a core property for verification, and is illustrated through two distinct instantiations. The first assumes that full knowledge of the MDP is available, and performs a heuristic-driven partial exploration of the model, yielding precise lower and upper bounds on the required probability. The second tackles the case where we may only sample the MDP, and yields probabilistic guarantees, again in terms of both the lower and upper bounds, which provides efficient stopping criteria for the approximation. The latter is the first extension of statistical model checking for unbounded properties inMDPs. In contrast with other related techniques, our approach is not restricted to time-bounded (finite-horizon) or discounted properties, nor does it assume any particular properties of the MDP. We also show how our methods extend to LTL objectives. We present experimental results showing the performance of our framework on several examples. AU - Brázdil, Tomáš AU - Chatterjee, Krishnendu AU - Chmelik, Martin AU - Forejt, Vojtěch AU - Kretinsky, Jan AU - Kwiatkowska, Marta AU - Parker, David AU - Ujma, Mateusz ED - Cassez, Franck ED - Raskin, Jean-François ID - 2027 T2 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) TI - Verification of markov decision processes using learning algorithms VL - 8837 ER - TY - JOUR AB - A puzzling property of synaptic transmission, originally established at the neuromuscular junction, is that the time course of transmitter release is independent of the extracellular Ca2+ concentration ([Ca2+]o), whereas the rate of release is highly [Ca2+]o-dependent. Here, we examine the time course of release at inhibitory basket cell-Purkinje cell synapses and show that it is independent of [Ca2+]o. Modeling of Ca2+-dependent transmitter release suggests that the invariant time course of release critically depends on tight coupling between Ca2+ channels and release sensors. Experiments with exogenous Ca2+ chelators reveal that channel-sensor coupling at basket cell-Purkinje cell synapses is very tight, with a mean distance of 10–20 nm. Thus, tight channel-sensor coupling provides a mechanistic explanation for the apparent [Ca2+]o independence of the time course of release. AU - Arai, Itaru AU - Jonas, Peter M ID - 2031 JF - eLife TI - Nanodomain coupling explains Ca^2+ independence of transmitter release time course at a fast central synapse VL - 3 ER - TY - JOUR AB - The yeast Rab5 homologue, Vps21p, is known to be involved both in the vacuolar protein sorting (VPS) pathway from the trans-Golgi network to the vacuole, and in the endocytic pathway from the plasma membrane to the vacuole. However, the intracellular location at which these two pathways converge remains unclear. In addition, the endocytic pathway is not completely blocked in yeast cells lacking all Rab5 genes, suggesting the existence of an unidentified route that bypasses the Rab5-dependent endocytic pathway. Here we show that convergence of the endocytic and VPS pathways occurs upstream of the requirement for Vps21p in these pathways. We also identify a previously unidentified endocytic pathway mediated by the AP-3 complex. Importantly, the AP-3-mediated pathway appears mostly intact in Rab5-disrupted cells, and thus works as an alternative route to the vacuole/lysosome. We propose that the endocytic traffic branches into two routes to reach the vacuole: a Rab5-dependent VPS pathway and a Rab5-independent AP-3-mediated pathway. AU - Toshima, Junko AU - Nishinoaki, Show AU - Sato, Yoshifumi AU - Yamamoto, Wataru AU - Furukawa, Daiki AU - Siekhaus, Daria E AU - Sawaguchi, Akira AU - Toshima, Jiro ID - 2024 JF - Nature Communications TI - Bifurcation of the endocytic pathway into Rab5-dependent and -independent transport to the vacuole VL - 5 ER - TY - JOUR AB - Understanding the dynamics of noisy neurons remains an important challenge in neuroscience. Here, we describe a simple probabilistic model that accurately describes the firing behavior in a large class (type II) of neurons. To demonstrate the usefulness of this model, we show how it accurately predicts the interspike interval (ISI) distributions, bursting patterns and mean firing rates found by: (1) simulations of the classic Hodgkin-Huxley model with channel noise, (2) experimental data from squid giant axon with a noisy input current and (3) experimental data on noisy firing from a neuron within the suprachiasmatic nucleus (SCN). This simple model has 6 parameters, however, in some cases, two of these parameters are coupled and only 5 parameters account for much of the known behavior. From these parameters, many properties of spiking can be found through simple calculation. Thus, we show how the complex effects of noise can be understood through a simple and general probabilistic model. AU - Bodova, Katarina AU - Paydarfar, David AU - Forger, Daniel ID - 2028 JF - Journal of Theoretical Biology TI - Characterizing spiking in noisy type II neurons VL - 365 ER - TY - CONF AB - We present a tool for translating LTL formulae into deterministic ω-automata. It is the first tool that covers the whole LTL that does not use Safra’s determinization or any of its variants. This leads to smaller automata. There are several outputs of the tool: firstly, deterministic Rabin automata, which are the standard input for probabilistic model checking, e.g. for the probabilistic model-checker PRISM; secondly, deterministic generalized Rabin automata, which can also be used for probabilistic model checking and are sometimes by orders of magnitude smaller. We also link our tool to PRISM and show that this leads to a significant speed-up of probabilistic LTL model checking, especially with the generalized Rabin automata. AU - Komárková, Zuzana AU - Kretinsky, Jan ED - Cassez, Franck ED - Raskin, Jean-François ID - 2026 T2 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) TI - Rabinizer 3: Safraless translation of ltl to small deterministic automata VL - 8837 ER - TY - JOUR AB - Spin-wave theory is a key ingredient in our comprehension of quantum spin systems, and is used successfully for understanding a wide range of magnetic phenomena, including magnon condensation and stability of patterns in dipolar systems. Nevertheless, several decades of research failed to establish the validity of spin-wave theory rigorously, even for the simplest models of quantum spins. A rigorous justification of the method for the three-dimensional quantum Heisenberg ferromagnet at low temperatures is presented here. We derive sharp bounds on its free energy by combining a bosonic formulation of the model introduced by Holstein and Primakoff with probabilistic estimates and operator inequalities. AU - Correggi, Michele AU - Giuliani, Alessandro AU - Seiringer, Robert ID - 2029 IS - 2 JF - EPL TI - Validity of spin-wave theory for the quantum Heisenberg model VL - 108 ER - TY - CONF AB - The learning with privileged information setting has recently attracted a lot of attention within the machine learning community, as it allows the integration of additional knowledge into the training process of a classifier, even when this comes in the form of a data modality that is not available at test time. Here, we show that privileged information can naturally be treated as noise in the latent function of a Gaussian process classifier (GPC). That is, in contrast to the standard GPC setting, the latent function is not just a nuisance but a feature: it becomes a natural measure of confidence about the training data by modulating the slope of the GPC probit likelihood function. Extensive experiments on public datasets show that the proposed GPC method using privileged noise, called GPC+, improves over a standard GPC without privileged knowledge, and also over the current state-of-the-art SVM-based method, SVM+. Moreover, we show that advanced neural networks and deep learning methods can be compressed as privileged information. AU - Hernandez Lobato, Daniel AU - Sharmanska, Viktoriia AU - Kersting, Kristian AU - Lampert, Christoph AU - Quadrianto, Novi ID - 2033 IS - January T2 - Advances in Neural Information Processing Systems TI - Mind the nuisance: Gaussian process classification using privileged noise VL - 1 ER - TY - JOUR AB - As light-based control of fundamental signaling pathways is becoming a reality, the field of optogenetics is rapidly moving beyond neuroscience. We have recently developed receptor tyrosine kinases that are activated by light and control cell proliferation, epithelial–mesenchymal transition, and angiogenic sprouting—cell behaviors central to cancer progression. AU - Inglés Prieto, Álvaro AU - Gschaider-Reichhart, Eva AU - Schelch, Karin AU - Janovjak, Harald L AU - Grusch, Michael ID - 2032 IS - 4 JF - Molecular and Cellular Oncology TI - The optogenetic promise for oncology: Episode I VL - 1 ER - TY - CONF AB - We introduce and study a new notion of enhanced chosen-ciphertext security (ECCA) for public-key encryption. Loosely speaking, in the ECCA security experiment, the decryption oracle provided to the adversary is augmented to return not only the output of the decryption algorithm on a queried ciphertext but also of a randomness-recovery algorithm associated to the scheme. Our results mainly concern the case where the randomness-recovery algorithm is efficient. We provide constructions of ECCA-secure encryption from adaptive trapdoor functions as defined by Kiltz et al. (EUROCRYPT 2010), resulting in ECCA encryption from standard number-theoretic assumptions. We then give two applications of ECCA-secure encryption: (1) We use it as a unifying concept in showing equivalence of adaptive trapdoor functions and tag-based adaptive trapdoor functions, resolving an open question of Kiltz et al. (2) We show that ECCA-secure encryption can be used to securely realize an approach to public-key encryption with non-interactive opening (PKENO) originally suggested by Damgård and Thorbek (EUROCRYPT 2007), resulting in new and practical PKENO schemes quite different from those in prior work. Our results demonstrate that ECCA security is of both practical and theoretical interest. AU - Dachman Soled, Dana AU - Fuchsbauer, Georg AU - Mohassel, Payman AU - O’Neill, Adam ED - Krawczyk, Hugo ID - 2045 T2 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) TI - Enhanced chosen-ciphertext security and applications VL - 8383 ER - TY - JOUR AB - Background: CRISPR is a microbial immune system likely to be involved in host-parasite coevolution. It functions using target sequences encoded by the bacterial genome, which interfere with invading nucleic acids using a homology-dependent system. The system also requires protospacer associated motifs (PAMs), short motifs close to the target sequence that are required for interference in CRISPR types I and II. Here, we investigate whether PAMs are depleted in phage genomes due to selection pressure to escape recognition.Results: To this end, we analyzed two data sets. Phages infecting all bacterial hosts were analyzed first, followed by a detailed analysis of phages infecting the genus Streptococcus, where PAMs are best understood. We use two different measures of motif underrepresentation that control for codon bias and the frequency of submotifs. We compare phages infecting species with a particular CRISPR type to those infecting species without that type. Since only known PAMs were investigated, the analysis is restricted to CRISPR types I-C and I-E and in Streptococcus to types I-C and II. We found evidence for PAM depletion in Streptococcus phages infecting hosts with CRISPR type I-C, in Vibrio phages infecting hosts with CRISPR type I-E and in Streptococcus thermopilus phages infecting hosts with type II-A, known as CRISPR3.Conclusions: The observed motif depletion in phages with hosts having CRISPR can be attributed to selection rather than to mutational bias, as mutational bias should affect the phages of all hosts. This observation implies that the CRISPR system has been efficient in the groups discussed here. AU - Kupczok, Anne AU - Bollback, Jonathan P ID - 2042 IS - 1 JF - BMC Genomics TI - Motif depletion in bacteriophages infecting hosts with CRISPR systems VL - 15 ER - TY - CONF AB - Persistent homology is a popular and powerful tool for capturing topological features of data. Advances in algorithms for computing persistent homology have reduced the computation time drastically – as long as the algorithm does not exhaust the available memory. Following up on a recently presented parallel method for persistence computation on shared memory systems [1], we demonstrate that a simple adaption of the standard reduction algorithm leads to a variant for distributed systems. Our algorithmic design ensures that the data is distributed over the nodes without redundancy; this permits the computation of much larger instances than on a single machine. Moreover, we observe that the parallelism at least compensates for the overhead caused by communication between nodes, and often even speeds up the computation compared to sequential and even parallel shared memory algorithms. In our experiments, we were able to compute the persistent homology of filtrations with more than a billion (109) elements within seconds on a cluster with 32 nodes using less than 6GB of memory per node. AU - Bauer, Ulrich AU - Kerber, Michael AU - Reininghaus, Jan ED - McGeoch, Catherine ED - Meyer, Ulrich ID - 2043 T2 - Proceedings of the Workshop on Algorithm Engineering and Experiments TI - Distributed computation of persistent homology ER - TY - JOUR AB - The hippocampus mediates several higher brain functions, such as learning, memory, and spatial coding. The input region of the hippocampus, the dentate gyrus, plays a critical role in these processes. Several lines of evidence suggest that the dentate gyrus acts as a preprocessor of incoming information, preparing it for subsequent processing in CA3. For example, the dentate gyrus converts input from the entorhinal cortex, where cells have multiple spatial fields, into the spatially more specific place cell activity characteristic of the CA3 region. Furthermore, the dentate gyrus is involved in pattern separation, transforming relatively similar input patterns into substantially different output patterns. Finally, the dentate gyrus produces a very sparse coding scheme in which only a very small fraction of neurons are active at any one time. AU - Jonas, Peter M AU - Lisman, John ID - 2041 JF - Frontiers in Neural Circuits TI - Structure, function and plasticity of hippocampal dentate gyrus microcircuits VL - 8 ER - TY - CHAP AB - We present a parallel algorithm for computing the persistent homology of a filtered chain complex. Our approach differs from the commonly used reduction algorithm by first computing persistence pairs within local chunks, then simplifying the unpaired columns, and finally applying standard reduction on the simplified matrix. The approach generalizes a technique by Günther et al., which uses discrete Morse Theory to compute persistence; we derive the same worst-case complexity bound in a more general context. The algorithm employs several practical optimization techniques, which are of independent interest. Our sequential implementation of the algorithm is competitive with state-of-the-art methods, and we further improve the performance through parallel computation. AU - Bauer, Ulrich AU - Kerber, Michael AU - Reininghaus, Jan ED - Bremer, Peer-Timo ED - Hotz, Ingrid ED - Pascucci, Valerio ED - Peikert, Ronald ID - 2044 T2 - Topological Methods in Data Analysis and Visualization III TI - Clear and Compress: Computing Persistent Homology in Chunks ER -