Discharge Synchrony during the Transition of Behavioral Goal Representations Encoded by Discharge Rates of Prefrontal Neurons

To investigate the temporal relationship between synchrony in the discharge of neuron pairs and modulation of the discharge rate, we recorded the neuronal activity of the lateral prefrontal cortex of monkeys performing a behavioral task that required them to plan an immediate goal of action to attain a final goal. Information about the final goal was retrieved via visual instruction signals, whereas information about the immediate goal was generated internally. The synchrony of neuron pair discharges was analyzed separately from changes in the firing rate of individual neurons during a preparatory period. We focused on neuron pairs that exhibited a representation of the final goal followed by a representation of the immediate goal at a later stage. We found that changes in synchrony and discharge rates appeared to be complementary at different phases of the behavioral task. Synchrony was maximized during a specific phase in the preparatory period corresponding to a transitional stage when the neuronal activity representing the final goal was replaced with that representing the immediate goal. We hypothesize that the transient increase in discharge synchrony is an indication of a process that facilitates dynamic changes in the prefrontal neural circuits in order to undergo profound state changes

Investigation of intercostal neuronal intracellular processes and connectivity by signal analysis and computer simulation

Imperial Users onl

VIOLA - A multi-purpose and web-based visualization tool for neuronal-network simulation output

Neuronal network models and corresponding computer simulations are invaluable tools to aid the interpretation of the relationship between neuron properties, connectivity and measured activity in cortical tissue. Spatiotemporal patterns of activity propagating across the cortical surface as observed experimentally can for example be described by neuronal network models with layered geometry and distance-dependent connectivity. The interpretation of the resulting stream of multi-modal and multi-dimensional simulation data calls for integrating interactive visualization steps into existing simulation-analysis workflows. Here, we present a set of interactive visualization concepts called views for the visual analysis of activity data in topological network models, and a corresponding reference implementation VIOLA (VIsualization Of Layer Activity). The software is a lightweight, open-source, web-based and platform-independent application combining and adapting modern interactive visualization paradigms, such as coordinated multiple views, for massively parallel neurophysiological data. For a use-case demonstration we consider spiking activity data of a two-population, layered point-neuron network model subject to a spatially confined excitation originating from an external population. With the multiple coordinated views, an explorative and qualitative assessment of the spatiotemporal features of neuronal activity can be performed upfront of a detailed quantitative data analysis of specific aspects of the data. Furthermore, ongoing efforts including the European Human Brain Project aim at providing online user portals for integrated model development, simulation, analysis and provenance tracking, wherein interactive visual analysis tools are one component. Browser-compatible, web-technology based solutions are therefore required. Within this scope, with VIOLA we provide a first prototype.Comment: 38 pages, 10 figures, 3 table

A flexible approach to the estimation of water budgets and its connection to the travel time theory.

The increasing impacts of climate changes on water related sectors are leading the scientists' attentions to the development of comprehensive models, allowing better descriptions of the water and solute transport processes. "Getting the right answers for the right reasons", in terms of hydrological response, is one of the main goals of most of the recent literature. Semi-distributed hydrological models, based on the partition of basins in hydrological response units (HRUs) to be connected, eventually, to describe a whole catchment, proved to be robust in the reproduction of observed catchment dynamics. 'Embedded reservoirs' are often used for each HRU, to allow a consistent representation of the processes. In this work, a new semi-disitrbuted model for runoff and evapotranspiration is presented: five different reservoirs are inter-connected in order to capture the dynamics of snow, canopy, surface flow, root-zone and groundwater compartments. The knowledge of the mass of water and solute stored and released through different outputs (e.g. discharge, evapotranspiration) allows the analysis of the hydrological travel times and solute transport in catchments. The latter have been studied extensively, with some recent benchmark contributions in the last decade. However, the literature remains obscured by different terminologies and notations, as well as model assumptions are not fully explained. The thesis presents a detailed description of a new theoretical approach that reworks the theory from the point of view of the hydrological storages and fluxes involved. Major aspects of the new theory are the 'age-ranked' definition of the hydrological variables, the explicit treatment of evaporative fluxes and of their influence on the transport, the analysis of the outflows partitioning coefficients and the explicit formulation of the 'age-ranked' equations for solutes. Moreover, the work presents concepts in a new systematic and clarified way, helping the application of the theory. To give substance to the theory, a small catchment in the prealpine area was chosen as an example and the results illustrated. The rainfall-runoff model and the travel time theory were implemented and integrated in the semi-distributed hydrological system JGrass-NewAge. Thanks to the environmental modelling framework OMS3, each part of the hydrological cycle is implemented as a component that can be selected, adopted, and connected at run-time to obtain a user-customized hydrological model. The system is flexible, expandable and applicable in a variety of modelling solutions. In this work, the model code underwent to an extensive revision: new components were added (coupled storages water budget, travel times components); old components were enhanced (Kriging, shortwave, longwave, evapotranspiration, rain-snow separation, SWE and melting components); documentation was standardized and deployed. Since the Thesis regards in wide sense the building of a collaborative system, a discussion of some general purpose tools that were implemented or improved for supporting the present research is also presented. They include the description and the verification of a software component dealing with the long-wave radiation budget and another component dealing with an implementation of some Kriging procedure

Mimicking human neuronal pathways in silico: an emergent model on the effective connectivity

International audienceWe present a novel computational model that detects temporal configurations of a given human neuronal pathway and constructs its artificial replication. This poses a great challenge since direct recordings from individual neurons are impossible in the human central nervous system and therefore the underlying neuronal pathway has to be considered as a black box. For tackling this challenge, we used a branch of complex systems modeling called artificial self-organization in which large sets of software entities interacting locally give rise to bottom-up collective behaviors. The result is an emergent model where each software entity represents an integrate-and-fire neuron. We then applied the model to the reflex responses of single motor units obtained from conscious human subjects. Experimental results show that the model recovers functionality of real human neuronal pathways by comparing it to appropriate surrogate data. What makes the model promising is the fact that, to the best of our knowledge, it is the first realistic model to self-wire an artificial neuronal network by efficiently combining neuroscience with artificial self-organization. Although there is no evidence yet of the model's connectivity mapping onto the human connectivity, we anticipate this model will help neuroscientists to learn much more about human neuronal networks, and could also be used for predicting hypotheses to lead future experiments

Pattern recognition of neural data: methods and algorithms for spike sorting and their optimal performance in prefrontal cortex recordings

Programa de Doctorado en NeurocienciasPattern recognition of neuronal discharges is the electrophysiological basis of the functional characterization of brain processes, so the implementation of a Spike Sorting algorithm is an essential step for the analysis of neural codes and neural interactions in a network or brain circuit. Extracted information from the neural action potential can be used to characterize neural activity events and correlate them during behavioral and cognitive processes, including different types of associative learning tasks. In particular, feature extraction is a critical step in the spike sorting procedure, which is prior to the clustering step and subsequent to the spike detection-identification step in a Spike Sorting algorithm. In the present doctoral thesis, the implementation of an automatic and unsupervised computational algorithm, called 'Unsupervised Automatic Algorithm', is proposed for the detection, identification and classification of the neural action potentials distributed across the electrophysiological recordings; and for clustering of these potentials in function of the shape, phase and distribution features, which are extracted from the first-order derivative of the potentials under study. For this, an efficient and unsupervised clustering method was developed, which integrate the K-means method with two clustering measures (validity and error indices) to verify both the cohesion-dispersion among neural spike during classification and the misclassification of clustering, respectively. In additions, this algorithm was implemented in a customized spike sorting software called VISSOR (Viability of Integrated Spike Sorting of Real Recordings). On the other hand, a supervised grouping method of neural activity profiles was performed to allow the recognition of specific patterns of neural discharges. Validity and effectiveness of these methods and algorithms were tested in this doctoral thesis by the classification of the detected action potentials from extracellular recordings of the rostro-medial prefrontal cortex of rabbits during the classical eyelid conditioning. After comparing the spike-sorting methods/algorithms proposed in this work with other methods also based on feature extraction of the action potentials, it was observed that this one had a better performance during the classification. That is, the methods/algorithms proposed here allowed obtaining: (1) the optimal number of clusters of neuronal spikes (according to the criterion of the maximum value of the cohesion-dispersion index) and (2) the optimal clustering of these spike-events (according to the criterion of the minimum value of the error index). The analytical implication of these results was that the feature extraction based on the shape, phase and distribution features of the action potential, together with the application of an alternative method of unsupervised classification with validity and error indices; guaranteed an efficient classification of neural events, especially for those detected from extracellular or multi-unitary recordings. Rabbits were conditioned with a delay paradigm consisting of a tone as conditioned stimulus. The conditioned stimulus started 50, 250, 500, 1000, or 2000 ms before and co-terminated with an air puff directed at the cornea as unconditioned stimulus. The results obtained indicated that the firing rate of each recorded neuron presented a single peak of activity with a frequency dependent on the inter-stimulus interval (i.e., ¿ 12 Hz for 250 ms, ¿ 6 Hz for 500 ms, and ¿ 3 Hz for 1000 ms). Interestingly, the recorded neurons from the rostro-medial prefrontal cortex presented their dominant firing peaks at three precise times evenly distributed with respect to conditioned stimulus start, and also depending on the duration of the inter-stimulus interval (only for intervals of 250, 500, and 1000 ms). No significant neural responses were recorded at very short (50 ms) or long (2000 ms) conditioned stimulus-unconditioned stimulus time intervals. Furthermore, the eyelid movements were recorded with the magnetic search coil technique and the electromyographic (EMG) activity of the orbicularis oculi muscle. Reflex and conditioned eyelid responses presented a dominant oscillatory frequency of ¿ 12 Hz. The experimental implication of these results is that the recorded neurons from the rostro-medial prefrontal cortex seem not to encode the oscillatory properties characterizing conditioned eyelid responses in rabbits. As a general experimental conclusion, it could be said that rostro-medial prefrontal cortex neurons are probably involved in the determination of CS-US intervals of an intermediate range (250-1000 ms).Universidad Pablo de Olavide. Departamento de Fisiología, Anatomía y Biología CelularPostprin

The End of Time?

I discuss J. Barbour's Machian theories of dynamics, and his proposal that a Machian perspective enables one to solve the problem of time in quantum geometrodynamics (by saying that there is no time). I concentrate on his recent book 'The End of Time' (1999).Comment: 48 pages Latex. A shortened version will appear in 'The British Journal for Philosophy of Science

Challenges and New Trends in Power Electronic Devices Reliability

The rapid increase in new power electronic devices and converters for electric transportation and smart grid technologies requires a deepanalysis of their component performances, considering all of the different environmental scenarios, overload conditions, and high stressoperations. Therefore, evaluation of the reliability and availability of these devices becomes fundamental both from technical and economicalpoints of view. The rapid evolution of technologies and the high reliability level offered by these components have shown that estimating reliability through the traditional approaches is difficult, as historical failure data and/or past observed scenarios demonstrate. With the aim topropose new approaches for the evaluation of reliability, in this book, eleven innovative contributions are collected, all focusedon the reliability assessment of power electronic devices and related components

Contract Law\u27s Inefficiency

Neoclassical economic theory seems to aptly characterize contract law’s essence. Contracts enable two parties to reach a mutually beneficial agreement, thereby facilitating economically efficient transactions. It would seem to follow that the achievement of economic efficiency serves as contract law’s major goal. This article, however, examines an alternative hypothesis, that contract law is about enforcing inefficient bargains in order to provide enough security to facilitate cooperation among economic actors over long periods of time. On this account, contract law manages change over time, rather than achieves static efficiency. While recognizing that parties execute contracts in order to realize an efficient exchange, this article argues that contract law exists largely to enforce bargains that have become inefficient over time. It argues that inefficient contract law performs important macroeconomic functions in stimulating economic growth. The analysis developing this tension between efficient contracting and inefficient contract law casts some doubt on a major rationale for making efficiency the dominant goal for contract law. It also adds an important dimension to the existing explanation of the scholarly literature’s many inconsistencies in conclusions about the efficiency of contract rules. Finally, it helps explains the major exceptions to the rule that courts enforce inefficient contracts found in the impossibility and impracticability doctrines. This article endorses an economic dynamic approach to contact law in light of the tension between efficient contracting and inefficient contract law and describes the components of an economic dynamic analysis rooted in institutional economics. It shows that some of our leading scholars have already tacitly employed this approach effectively to shed new light on contract law