TY - JOUR AB - Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis – connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena. AU - Dura-Bernal, Salvador AU - Suter, Benjamin AU - Gleeson, Padraig AU - Cantarelli, Matteo AU - Quintana, Adrian AU - Rodriguez, Facundo AU - Kedziora, David J AU - Chadderdon, George L AU - Kerr, Cliff C AU - Neymotin, Samuel A AU - McDougal, Robert A AU - Hines, Michael AU - Shepherd, Gordon MG AU - Lytton, William W ID - 7405 JF - eLife SN - 2050-084X TI - NetPyNE, a tool for data-driven multiscale modeling of brain circuits VL - 8 ER - TY - JOUR AB - Suppressed recombination allows divergence between homologous sex chromosomes and the functionality of their genes. Here, we reveal patterns of the earliest stages of sex-chromosome evolution in the diploid dioecious herb Mercurialis annua on the basis of cytological analysis, de novo genome assembly and annotation, genetic mapping, exome resequencing of natural populations, and transcriptome analysis. The genome assembly contained 34,105 expressed genes, of which 10,076 were assigned to linkage groups. Genetic mapping and exome resequencing of individuals across the species range both identified the largest linkage group, LG1, as the sex chromosome. Although the sex chromosomes of M. annua are karyotypically homomorphic, we estimate that about one-third of the Y chromosome, containing 568 transcripts and spanning 22.3 cM in the corresponding female map, has ceased recombining. Nevertheless, we found limited evidence for Y-chromosome degeneration in terms of gene loss and pseudogenization, and most X- and Y-linked genes appear to have diverged in the period subsequent to speciation between M. annua and its sister species M. huetii, which shares the same sex-determining region. Taken together, our results suggest that the M. annua Y chromosome has at least two evolutionary strata: a small old stratum shared with M. huetii, and a more recent larger stratum that is probably unique to M. annua and that stopped recombining ∼1 MYA. Patterns of gene expression within the nonrecombining region are consistent with the idea that sexually antagonistic selection may have played a role in favoring suppressed recombination. AU - Veltsos, Paris AU - Ridout, Kate E. AU - Toups, Melissa A AU - González-Martínez, Santiago C. AU - Muyle, Aline AU - Emery, Olivier AU - Rastas, Pasi AU - Hudzieczek, Vojtech AU - Hobza, Roman AU - Vyskot, Boris AU - Marais, Gabriel A. B. AU - Filatov, Dmitry A. AU - Pannell, John R. ID - 7400 IS - 3 JF - Genetics SN - 0016-6731 TI - Early sex-chromosome evolution in the diploid dioecious plant Mercurialis annua VL - 212 ER - TY - JOUR AB - The formation of neuronal dendrite branches is fundamental for the wiring and function of the nervous system. Indeed, dendrite branching enhances the coverage of the neuron's receptive field and modulates the initial processing of incoming stimuli. Complex dendrite patterns are achieved in vivo through a dynamic process of de novo branch formation, branch extension and retraction. The first step towards branch formation is the generation of a dynamic filopodium-like branchlet. The mechanisms underlying the initiation of dendrite branchlets are therefore crucial to the shaping of dendrites. Through in vivo time-lapse imaging of the subcellular localization of actin during the process of branching of Drosophila larva sensory neurons, combined with genetic analysis and electron tomography, we have identified the Actin-related protein (Arp) 2/3 complex as the major actin nucleator involved in the initiation of dendrite branchlet formation, under the control of the activator WAVE and of the small GTPase Rac1. Transient recruitment of an Arp2/3 component marks the site of branchlet initiation in vivo. These data position the activation of Arp2/3 as an early hub for the initiation of branchlet formation. AU - Stürner, Tomke AU - Tatarnikova, Anastasia AU - Müller, Jan AU - Schaffran, Barbara AU - Cuntz, Hermann AU - Zhang, Yun AU - Nemethova, Maria AU - Bogdan, Sven AU - Small, Vic AU - Tavosanis, Gaia ID - 7404 IS - 7 JF - Development SN - 0950-1991 TI - Transient localization of the Arp2/3 complex initiates neuronal dendrite branching in vivo VL - 146 ER - TY - CONF AB - Graph planning gives rise to fundamental algorithmic questions such as shortest path, traveling salesman problem, etc. A classical problem in discrete planning is to consider a weighted graph and construct a path that maximizes the sum of weights for a given time horizon T. However, in many scenarios, the time horizon is not fixed, but the stopping time is chosen according to some distribution such that the expected stopping time is T. If the stopping time distribution is not known, then to ensure robustness, the distribution is chosen by an adversary, to represent the worst-case scenario. A stationary plan for every vertex always chooses the same outgoing edge. For fixed horizon or fixed stopping-time distribution, stationary plans are not sufficient for optimality. Quite surprisingly we show that when an adversary chooses the stopping-time distribution with expected stopping time T, then stationary plans are sufficient. While computing optimal stationary plans for fixed horizon is NP-complete, we show that computing optimal stationary plans under adversarial stopping-time distribution can be achieved in polynomial time. Consequently, our polynomial-time algorithm for adversarial stopping time also computes an optimal plan among all possible plans. AU - Chatterjee, Krishnendu AU - Doyen, Laurent ID - 7402 SN - 9781728136080 T2 - 34th Annual ACM/IEEE Symposium on Logic in Computer Science TI - Graph planning with expected finite horizon ER - TY - JOUR AB - We prove that the observable telegraph signal accompanying the bistability in the photon-blockade-breakdown regime of the driven and lossy Jaynes–Cummings model is the finite-size precursor of what in the thermodynamic limit is a genuine first-order phase transition. We construct a finite-size scaling of the system parameters to a well-defined thermodynamic limit, in which the system remains the same microscopic system, but the telegraph signal becomes macroscopic both in its timescale and intensity. The existence of such a finite-size scaling completes and justifies the classification of the photon-blockade-breakdown effect as a first-order dissipative quantum phase transition. AU - Vukics, A. AU - Dombi, A. AU - Fink, Johannes M AU - Domokos, P. ID - 7451 JF - Quantum SN - 2521-327X TI - Finite-size scaling of the photon-blockade breakdown dissipative quantum phase transition VL - 3 ER - TY - CONF AB - We present a new proximal bundle method for Maximum-A-Posteriori (MAP) inference in structured energy minimization problems. The method optimizes a Lagrangean relaxation of the original energy minimization problem using a multi plane block-coordinate Frank-Wolfe method that takes advantage of the specific structure of the Lagrangean decomposition. We show empirically that our method outperforms state-of-the-art Lagrangean decomposition based algorithms on some challenging Markov Random Field, multi-label discrete tomography and graph matching problems. AU - Swoboda, Paul AU - Kolmogorov, Vladimir ID - 7468 SN - 10636919 T2 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition TI - Map inference via block-coordinate Frank-Wolfe algorithm VL - 2019-June ER - TY - JOUR AU - Morandell, Jasmin AU - Nicolas, Armel AU - Schwarz, Lena A AU - Novarino, Gaia ID - 7415 IS - Supplement 6 JF - European Neuropsychopharmacology SN - 0924-977X TI - S.16.05 Illuminating the role of the e3 ubiquitin ligase cullin3 in brain development and autism VL - 29 ER - TY - JOUR AU - Knaus, Lisa AU - Tarlungeanu, Dora-Clara AU - Novarino, Gaia ID - 7414 IS - Supplement 6 JF - European Neuropsychopharmacology SN - 0924-977X TI - S.16.03 A homozygous missense mutation in SLC7A5 leads to autism spectrum disorder and microcephaly VL - 29 ER - TY - JOUR AU - Benková, Eva AU - Dagdas, Yasin ID - 7394 IS - 12 JF - Current Opinion in Plant Biology SN - 1369-5266 TI - Editorial overview: Cell biology in the era of omics? VL - 52 ER - TY - CONF AB - Multi-exit architectures, in which a stack of processing layers is interleaved with early output layers, allow the processing of a test example to stop early and thus save computation time and/or energy. In this work, we propose a new training procedure for multi-exit architectures based on the principle of knowledge distillation. The method encourage searly exits to mimic later, more accurate exits, by matching their output probabilities. Experiments on CIFAR100 and ImageNet show that distillation-based training significantly improves the accuracy of early exits while maintaining state-of-the-art accuracy for late ones. The method is particularly beneficial when training data is limited and it allows a straightforward extension to semi-supervised learning,i.e. making use of unlabeled data at training time. Moreover, it takes only afew lines to implement and incurs almost no computational overhead at training time, and none at all at test time. AU - Bui Thi Mai, Phuong AU - Lampert, Christoph ID - 7479 SN - 15505499 T2 - IEEE International Conference on Computer Vision TI - Distillation-based training for multi-exit architectures VL - 2019-October ER - TY - CONF AB - We present a novel class of convolutional neural networks (CNNs) for set functions,i.e., data indexed with the powerset of a finite set. The convolutions are derivedas linear, shift-equivariant functions for various notions of shifts on set functions.The framework is fundamentally different from graph convolutions based on theLaplacian, as it provides not one but several basic shifts, one for each element inthe ground set. Prototypical experiments with several set function classificationtasks on synthetic datasets and on datasets derived from real-world hypergraphsdemonstrate the potential of our new powerset CNNs. AU - Wendler, Chris AU - Alistarh, Dan-Adrian AU - Püschel, Markus ID - 7542 SN - 1049-5258 TI - Powerset convolutional neural networks VL - 32 ER - TY - CHAP AB - Social insects (i.e., ants, termites and the social bees and wasps) protect their colonies from disease using a combination of individual immunity and collectively performed defenses, termed social immunity. The first line of social immune defense is sanitary care, which is performed by colony members to protect their pathogen-exposed nestmates from developing an infection. If sanitary care fails and an infection becomes established, a second line of social immune defense is deployed to stop disease transmission within the colony and to protect the valuable queens, which together with the males are the reproductive individuals of the colony. Insect colonies are separated into these reproductive individuals and the sterile worker force, forming a superorganismal reproductive unit reminiscent of the differentiated germline and soma in a multicellular organism. Ultimately, the social immune response preserves the germline of the superorganism insect colony and increases overall fitness of the colony in case of disease. AU - Cremer, Sylvia AU - Kutzer, Megan ED - Choe, Jae ID - 7513 SN - 9780128132517 T2 - Encyclopedia of Animal Behavior TI - Social immunity ER - TY - CONF AB - Bending-active structures are able to efficiently produce complex curved shapes starting from flat panels. The desired deformation of the panels derives from the proper selection of their elastic properties. Optimized panels, called FlexMaps, are designed such that, once they are bent and assembled, the resulting static equilibrium configuration matches a desired input 3D shape. The FlexMaps elastic properties are controlled by locally varying spiraling geometric mesostructures, which are optimized in size and shape to match the global curvature (i.e., bending requests) of the target shape. The design pipeline starts from a quad mesh representing the input 3D shape, which defines the edge size and the total amount of spirals: every quad will embed one spiral. Then, an optimization algorithm tunes the geometry of the spirals by using a simplified pre-computed rod model. This rod model is derived from a non-linear regression algorithm which approximates the non-linear behavior of solid FEM spiral models subject to hundreds of load combinations. This innovative pipeline has been applied to the project of a lightweight plywood pavilion named FlexMaps Pavilion, which is a single-layer piecewise twisted arc that fits a bounding box of 3.90x3.96x3.25 meters. AU - Laccone, Francesco AU - Malomo, Luigi AU - Perez Rodriguez, Jesus AU - Pietroni, Nico AU - Ponchio, Federico AU - Bickel, Bernd AU - Cignoni, Paolo ID - 9261 SN - 2518-6582 T2 - IASS Symposium 2019 - 60th Anniversary Symposium of the International Association for Shell and Spatial Structures; Structural Membranes 2019 - 9th International Conference on Textile Composites and Inflatable Structures, FORM and FORCE TI - FlexMaps Pavilion: A twisted arc made of mesostructured flat flexible panels ER - TY - CONF AB - We propose a new model for detecting visual relationships, such as "person riding motorcycle" or "bottle on table". This task is an important step towards comprehensive structured mage understanding, going beyond detecting individual objects. Our main novelty is a Box Attention mechanism that allows to model pairwise interactions between objects using standard object detection pipelines. The resulting model is conceptually clean, expressive and relies on well-justified training and prediction procedures. Moreover, unlike previously proposed approaches, our model does not introduce any additional complex components or hyperparameters on top of those already required by the underlying detection model. We conduct an experimental evaluation on two datasets, V-COCO and Open Images, demonstrating strong quantitative and qualitative results. AU - Kolesnikov, Alexander AU - Kuznetsova, Alina AU - Lampert, Christoph AU - Ferrari, Vittorio ID - 7640 SN - 9781728150239 T2 - Proceedings of the 2019 International Conference on Computer Vision Workshop TI - Detecting visual relationships using box attention ER - TY - CONF AB - Deep neural networks (DNNs) have become increasingly important due to their excellent empirical performance on a wide range of problems. However, regularization is generally achieved by indirect means, largely due to the complex set of functions defined by a network and the difficulty in measuring function complexity. There exists no method in the literature for additive regularization based on a norm of the function, as is classically considered in statistical learning theory. In this work, we study the tractability of function norms for deep neural networks with ReLU activations. We provide, to the best of our knowledge, the first proof in the literature of the NP-hardness of computing function norms of DNNs of 3 or more layers. We also highlight a fundamental difference between shallow and deep networks. In the light on these results, we propose a new regularization strategy based on approximate function norms, and show its efficiency on a segmentation task with a DNN. AU - Rannen-Triki, Amal AU - Berman, Maxim AU - Kolmogorov, Vladimir AU - Blaschko, Matthew B. ID - 7639 SN - 9781728150239 T2 - Proceedings of the 2019 International Conference on Computer Vision Workshop TI - Function norms for neural networks ER - TY - CHAP AB - We review the history of population genetics, starting with its origins a century ago from the synthesis between Mendel and Darwin's ideas, through to the recent development of sophisticated schemes of inference from sequence data, based on the coalescent. We explain the close relation between the coalescent and a diffusion process, which we illustrate by their application to understand spatial structure. We summarise the powerful methods available for analysis of multiple loci, when linkage equilibrium can be assumed, and then discuss approaches to the more challenging case, where associations between alleles require that we follow genotype, rather than allele, frequencies. Though we can hardly cover the whole of population genetics, we give an overview of the current state of the subject, and future challenges to it. AU - Barton, Nicholas H AU - Etheridge, Alison ED - Balding, David ED - Moltke, Ida ED - Marioni, John ID - 8281 SN - 9781119429142 T2 - Handbook of statistical genomics TI - Mathematical models in population genetics ER - TY - GEN AB - Denote by ∆N the N-dimensional simplex. A map f : ∆N → Rd is an almost r-embedding if fσ1∩. . .∩fσr = ∅ whenever σ1, . . . , σr are pairwise disjoint faces. A counterexample to the topological Tverberg conjecture asserts that if r is not a prime power and d ≥ 2r + 1, then there is an almost r-embedding ∆(d+1)(r−1) → Rd. This was improved by Blagojevi´c–Frick–Ziegler using a simple construction of higher-dimensional counterexamples by taking k-fold join power of lower-dimensional ones. We improve this further (for d large compared to r): If r is not a prime power and N := (d+ 1)r−r l d + 2 r + 1 m−2, then there is an almost r-embedding ∆N → Rd. For the r-fold van Kampen–Flores conjecture we also produce counterexamples which are stronger than previously known. Our proof is based on generalizations of the Mabillard–Wagner theorem on construction of almost r-embeddings from equivariant maps, and of the Ozaydin theorem on existence of equivariant maps. AU - Avvakumov, Sergey AU - Karasev, R. AU - Skopenkov, A. ID - 8184 T2 - arXiv TI - Stronger counterexamples to the topological Tverberg conjecture ER - TY - CONF AB - A proxy re-encryption (PRE) scheme is a public-key encryption scheme that allows the holder of a key pk to derive a re-encryption key for any other key 𝑝𝑘′. This re-encryption key lets anyone transform ciphertexts under pk into ciphertexts under 𝑝𝑘′ without having to know the underlying message, while transformations from 𝑝𝑘′ to pk should not be possible (unidirectional). Security is defined in a multi-user setting against an adversary that gets the users’ public keys and can ask for re-encryption keys and can corrupt users by requesting their secret keys. Any ciphertext that the adversary cannot trivially decrypt given the obtained secret and re-encryption keys should be secure. All existing security proofs for PRE only show selective security, where the adversary must first declare the users it wants to corrupt. This can be lifted to more meaningful adaptive security by guessing the set of corrupted users among the n users, which loses a factor exponential in Open image in new window , rendering the result meaningless already for moderate Open image in new window . Jafargholi et al. (CRYPTO’17) proposed a framework that in some cases allows to give adaptive security proofs for schemes which were previously only known to be selectively secure, while avoiding the exponential loss that results from guessing the adaptive choices made by an adversary. We apply their framework to PREs that satisfy some natural additional properties. Concretely, we give a more fine-grained reduction for several unidirectional PREs, proving adaptive security at a much smaller loss. The loss depends on the graph of users whose edges represent the re-encryption keys queried by the adversary. For trees and chains the loss is quasi-polynomial in the size and for general graphs it is exponential in their depth and indegree (instead of their size as for previous reductions). Fortunately, trees and low-depth graphs cover many, if not most, interesting applications. Our results apply e.g. to the bilinear-map based PRE schemes by Ateniese et al. (NDSS’05 and CT-RSA’09), Gentry’s FHE-based scheme (STOC’09) and the LWE-based scheme by Chandran et al. (PKC’14). AU - Fuchsbauer, Georg AU - Kamath Hosdurg, Chethan AU - Klein, Karen AU - Pietrzak, Krzysztof Z ID - 6430 SN - 03029743 TI - Adaptively secure proxy re-encryption VL - 11443 ER - TY - JOUR AB - Electron transport in two-dimensional conducting materials such as graphene, with dominant electron–electron interaction, exhibits unusual vortex flow that leads to a nonlocal current-field relation (negative resistance), distinct from the classical Ohm’s law. The transport behavior of these materials is best described by low Reynolds number hydrodynamics, where the constitutive pressure–speed relation is Stoke’s law. Here we report evidence of such vortices observed in a viscous flow of Newtonian fluid in a microfluidic device consisting of a rectangular cavity—analogous to the electronic system. We extend our experimental observations to elliptic cavities of different eccentricities, and validate them by numerically solving bi-harmonic equation obtained for the viscous flow with no-slip boundary conditions. We verify the existence of a predicted threshold at which vortices appear. Strikingly, we find that a two-dimensional theoretical model captures the essential features of three-dimensional Stokes flow in experiments. AU - Mayzel, Jonathan AU - Steinberg, Victor AU - Varshney, Atul ID - 6069 JF - Nature Communications SN - 2041-1723 TI - Stokes flow analogous to viscous electron current in graphene VL - 10 ER - TY - JOUR AB - Speed of sound waves in gases and liquids are governed by the compressibility of the medium. There exists another type of non-dispersive wave where the wave speed depends on stress instead of elasticity of the medium. A well-known example is the Alfven wave, which propagates through plasma permeated by a magnetic field with the speed determined by magnetic tension. An elastic analogue of Alfven waves has been predicted in a flow of dilute polymer solution where the elastic stress of the stretching polymers determines the elastic wave speed. Here we present quantitative evidence of elastic Alfven waves in elastic turbulence of a viscoelastic creeping flow between two obstacles in channel flow. The key finding in the experimental proof is a nonlinear dependence of the elastic wave speed cel on the Weissenberg number Wi, which deviates from predictions based on a model of linear polymer elasticity. AU - Varshney, Atul AU - Steinberg, Victor ID - 6014 JF - Nature Communications SN - 2041-1723 TI - Elastic alfven waves in elastic turbulence VL - 10 ER -