Sensorimotor maps can be dynamically calibrated using an adaptive-filter model of the cerebellum

Substantial experimental evidence suggests the cerebellum is involved in calibrating sensorimotor maps. Consistent with this involvement is the well-known, but little understood, massive cerebellar projection to maps in the superior colliculus. Map calibration would be a significant new role for the cerebellum given the ubiquity of map representations in the brain, but how it could perform such a task is unclear. Here we investigated a dynamic method for map calibration, based on electrophysiological recordings from the superior colliculus, that used a standard adaptive-filter cerebellar model. The method proved effective for complex distortions of both unimodal and bimodal maps, and also for predictive map-based tracking of moving targets. These results provide the first computational evidence for a novel role for the cerebellum in dynamic sensorimotor map calibration, of potential importance for coordinate alignment during ongoing motor control, and for map calibration in future biomimetic systems. This computational evidence also provides testable experimental predictions concerning the role of the connections between cerebellum and superior colliculus in previously observed dynamic coordinate transformations

Adaptive biomedical treatment and robust control

Abstract An adaptive treatment strategy is a set of rules for choosing effective medical treatments for individual patients. In the statistical literature, methods for optimal dynamic treatment (ODT) include Q-learning and A-learning methods, which are linked to machine learning in engineering and computer science. The research project behind this article aims to develop new methodology for both ODT and engineering control, through the integration of techniques and approaches that have been developed in both fields, with a particular focus on the problem of robustness. The methodological framework is based on a regret-regression approach from the statistical literature and non-minimal state-space methods from control. This article provides an introduction to some of these concepts and presents preliminary novel contributions based on the application of robust H∞ methods to ODT problems

A single bacterial genus maintains root growth in a complex microbiome

Plants grow within a complex web of species that interact with each other and with the plant1–10. These interactions are governed by a wide repertoire of chemical signals, and the resulting chemical landscape of the rhizosphere can strongly affect root health and development7–9,11–18. Here, to understand how interactions between microorganisms influence root growth in Arabidopsis, we established a model system for interactions between plants, microorganisms and the environment. We inoculated seedlings with a 185-member bacterial synthetic community, manipulated the abiotic environment and measured bacterial colonization of the plant. This enabled us to classify the synthetic community into four modules of co-occurring strains. We deconstructed the synthetic community on the basis of these modules, and identified interactions between microorganisms that determine root phenotype. These interactions primarily involve a single bacterial genus (Variovorax), which completely reverses the severe inhibition of root growth that is induced by a wide diversity of bacterial strains as well as by the entire 185-member community. We demonstrate that Variovorax manipulates plant hormone levels to balance the effects of our ecologically realistic synthetic root community on root growth. We identify an auxin-degradation operon that is conserved in all available genomes of Variovorax and is necessary and sufficient for the reversion of root growth inhibition. Therefore, metabolic signal interference shapes bacteria–plant communication networks and is essential for maintaining the stereotypic developmental programme of the root. Optimizing the feedbacks that shape chemical interaction networks in the rhizosphere provides a promising ecological strategy for developing more resilient and productive crops

Electronics Letters

The optimal refined instrumental variable method for the estimation of the Box-Jenkins (BJ) model is modified so that it functions as an optimal filter and state-estimation algorithm. In contrast to the previously developed minimal and non-minimal state-space (NMSS) forms for an Auto-Regressive Moving Average with eXogenous variables (ARMAX) model, the new algorithm requires the introduction of a novel extended NMSS form. This facilitates representation of the more general noise component of the BJ model. The approach can be used for adaptive filtering and state variable feedback control

Limits on the monopole magnetic field from measurements of the electric dipole moments of atoms, molecules and the neutron

A radial magnetic field can induce a time invariance violating electric dipole moment (EDM) in quantum systems. The EDMs of the Tl, Cs, Xe and Hg atoms and the neutron that are produced by such a field are estimated. The contributions of such a field to the constants, $\chi$ of the T,P-odd interactions $\chi_e {\bf N} \cdot {\bf s}/s$ and $\chi_N {\bf N} \cdot {\bf I}/I$ are also estimated for the TlF, HgF and YbF molecules (where ${\bf s}$ (${\bf I}$) is the electron (nuclear) spin and ${\bf N}$ is the molecular axis). The best limit on the contact monopole field can be obtained from the measured value of the Tl EDM. The possibility of such a field being produced from polarization of the vacuum of electrically charged magnetic monopoles (dyons) by a Coulomb field is discussed, as well as the limit on these dyons. An alternative mechanism involves chromomagnetic and chromoelectric fields in QCD.Comment: Uses RevTex, 16 pages, 4 postscript figures. An explanation of why there is no orbital contribution to the EDM has been added, and the presentation has been improved in genera

Plasmonic excitations in noble metals: The case of Ag

The delicate interplay between plasmonic excitations and interband transitions in noble metals is described by means of {\it ab initio} calculations and a simple model in which the conduction electron plasmon is coupled to the continuum of electron-hole pairs. Band structure effects, specially the energy at which the excitation of the $d$-like bands takes place, determine the existence of a subthreshold plasmonic mode, which manifests itself in Ag as a sharp resonance at 3.8 eV. However, such a resonance is not observed in the other noble metals. Here, this different behavior is also analyzed and an explanation is provided.Comment: 9 pages, 8 figure

Dynamical mean-field theory of spiking neuron ensembles: response to a single spike with independent noises

Dynamics of an ensemble of $N$-unit FitzHugh-Nagumo (FN) neurons subject to white noises has been studied by using a semi-analytical dynamical mean-field (DMF) theory in which the original $2 N$-dimensional {\it stochastic} differential equations are replaced by 8-dimensional {\it deterministic} differential equations expressed in terms of moments of local and global variables. Our DMF theory, which assumes weak noises and the Gaussian distribution of state variables, goes beyond weak couplings among constituent neurons. By using the expression for the firing probability due to an applied single spike, we have discussed effects of noises, synaptic couplings and the size of the ensemble on the spike timing precision, which is shown to be improved by increasing the size of the neuron ensemble, even when there are no couplings among neurons. When the coupling is introduced, neurons in ensembles respond to an input spike with a partial synchronization. DMF theory is extended to a large cluster which can be divided into multiple sub-clusters according to their functions. A model calculation has shown that when the noise intensity is moderate, the spike propagation with a fairly precise timing is possible among noisy sub-clusters with feed-forward couplings, as in the synfire chain. Results calculated by our DMF theory are nicely compared to those obtained by direct simulations. A comparison of DMF theory with the conventional moment method is also discussed.Comment: 29 pages, 2 figures; augmented the text and added Appendice

The Self Model and the Conception of Biological Identity in Immunology

The self/non-self model, first proposed by F.M. Burnet, has dominated immunology for sixty years now. According to this model, any foreign element will trigger an immune reaction in an organism, whereas endogenous elements will not, in normal circumstances, induce an immune reaction. In this paper we show that the self/non-self model is no longer an appropriate explanation of experimental data in immunology, and that this inadequacy may be rooted in an excessively strong metaphysical conception of biological identity. We suggest that another hypothesis, one based on the notion of continuity, gives a better account of immune phenomena. Finally, we underscore the mapping between this metaphysical deflation from self to continuity in immunology and the philosophical debate between substantialism and empiricism about identity

Persuasion as a form of inter-agent negotiation

Agents in a multi-agent environment must often cooperate to achieve their objectives. In this paper an agent, B, cooperates with another agent, A, if B adopts a goal that furthers A's objectives in the environment. If agents are independent and motivated by their own interests, cooperation cannot be relied upon and it may be necessary for A to persuade B to adopt a cooperative goal. This paper is concerned with the organisation and construction of persuasive argument, and examines how a rational agent comes to hold a belief, and thus, how new beliefs might be engendered and existing beliefs altered, through the process of argumentation. Argument represents an opportunity for an agent to convince a possibly sceptical or resistant audience of the veracity of its own beliefs. This ability is a vital component of rich communication, facilitating explanation, instruction, cooperation and conflict resolution. An architecture is described in which a hierarchical planner is used to develop discourse plans which can be realised in natural language using the LOLITA system. Planning is concerned with the intentional, contextual and pragmatic aspects of discourse structure as well as with the logical form of the argument and its stylistic organisation. In this paper attention is restricted to the planning of persuasive discourse, or monologue