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Self organized behavior generation for musculoskeletal robots
Get PDFWith the accelerated development of robot technologies, control becomes one of the central themes of research. In traditional approaches, the controller, by its internal functionality, finds appropriate actions on the basis of specific objectives for the task at hand. While very successful in many applications, self-organized control schemes seem to be favored in large complex systems with unknown dynamics or which are difficult to model. Reasons are the expected scalability, robustness, and resilience of self-organizing systems. The paper presents a self-learning neurocontroller based on extrinsic differential plasticity introduced recently, applying it to an anthropomorphic musculoskeletal robot arm with attached objects of unknown physical dynamics. The central finding of the paper is the following effect: by the mere feedback through the internal dynamics of the object, the robot is learning to relate each of the objects with a very specific sensorimotor pattern. Specifically, an attached pendulum pilots the arm into a circular motion, a half-filled bottle produces axis oriented shaking behavior, a wheel is getting rotated, and wiping patterns emerge automatically in a table-plus-brush setting. By these object-specific dynamical patterns, the robot may be said to recognize the object's identity, or in other words, it discovers dynamical affordances of objects. Furthermore, when including hand coordinates obtained from a camera, a dedicated hand-eye coordination self-organizes spontaneously. These phenomena are discussed from a specific dynamical system perspective. Central is the dedicated working regime at the border to instability with its potentially infinite reservoir of (limit cycle) attractors "waiting" to be excited. Besides converging toward one of these attractors, variate behavior is also arising from a self-induced attractor morphing driven by the learning rule. We claim that experimental investigations with this anthropomorphic, self-learning robot not only generate interesting and potentially useful behaviors, but may also help to better understand what subjective human muscle feelings are, how they can be rooted in sensorimotor patterns, and how these concepts may feed back on robotics
The infinitesimal model: Definition derivation and implications
Get PDFOur focus here is on the infinitesimal model. In this model, one or several quantitative traits are described as the sum of a genetic and a non-genetic component, the first being distributed within families as a normal random variable centred at the average of the parental genetic components, and with a variance independent of the parental traits. Thus, the variance that segregates within families is not perturbed by selection, and can be predicted from the variance components. This does not necessarily imply that the trait distribution across the whole population should be Gaussian, and indeed selection or population structure may have a substantial effect on the overall trait distribution. One of our main aims is to identify some general conditions on the allelic effects for the infinitesimal model to be accurate. We first review the long history of the infinitesimal model in quantitative genetics. Then we formulate the model at the phenotypic level in terms of individual trait values and relationships between individuals, but including different evolutionary processes: genetic drift, recombination, selection, mutation, population structure, …. We give a range of examples of its application to evolutionary questions related to stabilising selection, assortative mating, effective population size and response to selection, habitat preference and speciation. We provide a mathematical justification of the model as the limit as the number M of underlying loci tends to infinity of a model with Mendelian inheritance, mutation and environmental noise, when the genetic component of the trait is purely additive. We also show how the model generalises to include epistatic effects. We prove in particular that, within each family, the genetic components of the individual trait values in the current generation are indeed normally distributed with a variance independent of ancestral traits, up to an error of order 1∕M. Simulations suggest that in some cases the convergence may be as fast as 1∕M
Control of endogenous auxin levels in plant root development
Get PDFIn this review, we summarize the different biosynthesis-related pathways that contribute to the regulation of endogenous auxin in plants. We demonstrate that all known genes involved in auxin biosynthesis also have a role in root formation, from the initiation of a root meristem during embryogenesis to the generation of a functional root system with a primary root, secondary lateral root branches and adventitious roots. Furthermore, the versatile adaptation of root development in response to environmental challenges is mediated by both local and distant control of auxin biosynthesis. In conclusion, auxin homeostasis mediated by spatial and temporal regulation of auxin biosynthesis plays a central role in determining root architecture
Reconstructing metastatic seeding patterns of human cancers
Get PDFWe thank Marc Attiyeh, Martin Chmelik, Alison Hill and Adeeti Ullal for valuable discussions. This work was supported by the European Research Council (ERC) start grant 279307: Graph Games (J.G.R., C.K.), Austrian Science Fund (FWF) grant no. P23499-N23 (J.G.R., K.C.), FWF NFN grant no. S11407-N23 RiSE/SHiNE (J.G.R., K.C.), a Landry Cancer Biology Fellowship (J.M.G.), National Institutes of Health grants CA179991 (C.A.I.-D., I.B.), F31CA180682 (A.P.M.-M.), CA43460 (B.V.), the Lustgarten Foundation for Pancreatic Cancer Research, The Sol Goldman Center for Pancreatic Cancer Research, The Virginia and D.K. Ludwig Fund for Cancer Research, Office of Naval Research grant N00014-16-1-2914, the Bill and Melinda Gates Foundation OPP1148627, and a gift from B Wu and Eric Larson. Benchmarking was performed on the Odyssey cluster supported by the FAS Division of Science, Research Computing Group at Harvard University
Infinite-Duration Bidding Games
Get PDFTwo-player games on graphs are widely studied in formal methods as they model the interaction between a system and its environment. The game is played by moving a token throughout a graph to produce an infinite path. There are several common modes to determine how the players move the token through the graph; e.g., in turn-based games the players alternate turns in moving the token. We study the {\em bidding} mode of moving the token, which, to the best of our knowledge, has never been studied in infinite-duration games. Both players have separate {\em budgets}, which sum up to . In each turn, a bidding takes place. Both players submit bids simultaneously, and a bid is legal if it does not exceed the available budget. The winner of the bidding pays his bid to the other player and moves the token. For reachability objectives, repeated bidding games have been studied and are called {\em Richman games} \cite{LLPU96,LLPSU99}. There, a central question is the existence and computation of {\em threshold} budgets; namely, a value such that if \PO's budget exceeds , he can win the game, and if \PT's budget exceeds , he can win the game. We focus on parity games and mean-payoff games. We show the existence of threshold budgets in these games, and reduce the problem of finding them to Richman games. We also determine the strategy-complexity of an optimal strategy. Our most interesting result shows that memoryless strategies suffice for mean-payoff bidding games
Are reprogrammed cells a useful tool for studying dopamine dysfunction in psychotic disorders? A review of the current evidence
Get PDFSince 2006, reprogrammed cells have increasingly been used as a biomedical research technique in addition to neuro-psychiatric methods. These rapidly evolving techniques allow for the generation of neuronal sub-populations, and have sparked interest not only in monogenetic neuro-psychiatric diseases, but also in poly-genetic and poly-aetiological disorders such as schizophrenia (SCZ) and bipolar disorder (BPD). This review provides a summary of 19 publications on reprogrammed adult somatic cells derived from patients with SCZ, and five publications using this technique in patients with BPD. As both disorders are complex and heterogeneous, there is a plurality of hypotheses to be tested in vitro. In SCZ, data on alterations of dopaminergic transmission in vitro are sparse, despite the great explanatory power of the so-called DA hypothesis of SCZ. Some findings correspond to perturbations of cell energy metabolism, and observations in reprogrammed cells suggest neuro-developmental alterations. Some studies also report on the efficacy of medicinal compounds to revert alterations observed in cellular models. However, due to the paucity of replication studies, no comprehensive conclusions can be drawn from studies using reprogrammed cells at the present time. In the future, findings from cell culture methods need to be integrated with clinical, epidemiological, pharmacological and imaging data in order to generate a more comprehensive picture of SCZ and BPD
Observation of the photon blockade breakdown phase transition
Get PDFNonequilibrium phase transitions exist in damped-driven open quantum systems when the continuous tuning of an external parameter leads to a transition between two robust steady states. In second-order transitions this change is abrupt at a critical point, whereas in first-order transitions the two phases can coexist in a critical hysteresis domain. Here, we report the observation of a first-order dissipative quantum phase transition in a driven circuit quantum electrodynamics system. It takes place when the photon blockade of the driven cavity-atom system is broken by increasing the drive power. The observed experimental signature is a bimodal phase space distribution with varying weights controlled by the drive strength. Our measurements show an improved stabilization of the classical attractors up to the millisecond range when the size of the quantum system is increased from one to three artificial atoms. The formation of such robust pointer states could be used for new quantum measurement schemes or to investigate multiphoton phases of finite-size, nonlinear, open quantum systems
Conic Abstractions for Hybrid Systems
Get PDFDespite researchers' efforts in the last couple of decades, reachability analysis is still a challenging problem even for linear hybrid systems. Among the existing approaches, the most practical ones are mainly based on bounded-time reachable set over-approximations. For the purpose of unbounded-time analysis, one important strategy is to abstract the original system and find an invariant for the abstraction. In this paper, we propose an approach to constructing a new kind of abstraction called conic abstraction for affine hybrid systems, and to computing reachable sets based on this abstraction. The essential feature of a conic abstraction is that it partitions the state space of a system into a set of convex polyhedral cones which is derived from a uniform conic partition of the derivative space. Such a set of polyhedral cones is able to cut all trajectories of the system into almost straight segments so that every segment of a reach pipe in a polyhedral cone tends to be straight as well, and hence can be over-approximated tightly by polyhedra using similar techniques as \emph{HyTech} or \emph{PHAVer}. In particular, for diagonalizable affine systems, our approach can guarantee to find an invariant for unbounded reachable sets, which is beyond the capability of bounded-time reachability analysis tools. We implemented the approach in a tool and experiments on benchmarks show that our approach is more powerful than \emph{SpaceEx} and \emph{PHAVer} in dealing with diagonalizable systems
Reactivation of the hippocampal cognitive map in goal-directed spatial tasks
No full textThe hippocampus is a key brain region for memory and notably for spatial memory, and is needed for both spatial working and reference memories. Hippocampal place cells selectively discharge in specific locations of the environment to form mnemonic represen tations of space. Several behavioral protocols have been designed to test spatial memory which requires the experimental subject to utilize working memory and reference memory. However, less is known about how these memory traces are presented in the hippo campus, especially considering tasks that require both spatial working and long -term reference memory demand. The aim of my thesis was to elucidate how spatial working memory, reference memory, and the combination of both are represented in the hippocampus. In this thesis, using a radial eight -arm maze, I examined how the combined demand on these memories influenced place cell assemblies while reference memories were partially updated by changing some of the reward- arms. This was contrasted with task varian ts requiring working or reference memories only. Reference memory update led to gradual place field shifts towards the rewards on the switched arms. Cells developed enhanced firing in passes between newly -rewarded arms as compared to those containing an unchanged reward. The working memory task did not show such gradual changes. Place assemblies on occasions replayed trajectories of the maze; at decision points the next arm choice was preferentially replayed in tasks needing reference memory while in the pure working memory task the previously visited arm was replayed. Hence trajectory replay only reflected the decision of the animal in tasks needing reference memory update. At the reward locations, in all three tasks outbound trajectories of the current arm were preferentially replayed, showing the animals’ next path to the center. At reward locations trajectories were replayed preferentially in reverse temporal order. Moreover, in the center reverse replay was seen in the working memory task but in the other tasks forward replay was seen. Hence, the direction of reactivation was determined by the goal locations so that part of the trajectory which was closer to the goal was reactivated later in an HSE while places further away from the goal were reactivated earlier. Altogether my work demonstrated that reference memory update triggers several levels of reorganization of the hippocampal cognitive map which are not seen in simpler working memory demand s. Moreover, hippocampus is likely to be involved in spatial decisions through reactivating planned trajectories when reference memory recall is required for such a decision
Regulation of Drosophila hematopoietic sites by Activin-β from active sensory neurons
Get PDFAn outstanding question in animal development, tissue homeostasis and disease is how cell populations adapt to sensory inputs. During Drosophila larval development, hematopoietic sites are in direct contact with sensory neuron clusters of the peripheral nervous system (PNS), and blood cells (hemocytes) require the PNS for their survival and recruitment to these microenvironments, known as Hematopoietic Pockets. Here we report that Activin-β, a TGF-β family ligand, is expressed by sensory neurons of the PNS and regulates the proliferation and adhesion of hemocytes. These hemocyte responses depend on PNS activity, as shown by agonist treatment and transient silencing of sensory neurons. Activin-β has a key role in this regulation, which is apparent from reporter expression and mutant analyses. This mechanism of local sensory neurons controlling blood cell adaptation invites evolutionary parallels with vertebrate hematopoietic progenitors and the independent myeloid system of tissue macrophages, whose regulation by local microenvironments remain undefined