bluuebunny/crossref_metadata_2025 huggingface dataset:
Neuronal Clusters in the Primate Motor Cortex during Interceptin of Moving Targets.
Authors: Lee Daeyeol , Port Nicholas L. , Kruse Wolfgang , Georgopoulos Apostolos P.
Published: July 2002

Two rhesus monkeys were trained to intercept a moving target at a fixed location with a feedback cursor controlled bya 2-D manipulandum. The direction from which the target appeared, the time from the target onset to its arrival at the interception point, and the target acceleration were randomized for each trial, thus requiring the animal to adjust its movement according to the visual input on a trail-by-trail basis. The two animals adopted different strategies, similar to those identified previously in human subjects. Single-cell activity was recorded from the arm area of the primary motor cortex in these two animals, and the neurons were classified based on the temporal patterns in their activity, using a nonhierarchical cluster analysis. Results of this analysis revealed differences in the complexity and diversity of motor cortical activity between the two animals that paralleled those of behavioral strategies. Most clusters displayed activity closedly related to the kinematics of hand movements. In addition, some clusters displayed patterns of activation that conveyed additional information necessary for successful performance of the task, such as the initial target velocity and the interval between successive submovements, suggesting that such information is represented in selective subpopulations of neurons in the primary motor cortex. These results also suggest that conversion of information about target motion into movement-related signals takes place in a broad network of cortical areas including the primary motor cortex.
An Electrophysiological Correlate of Visual Motion Awareness in Man
Authors: Haarmeier Thomas , Thier Peter
Published: July 2002

It is usually held that perceptual spatial stability, despite smooth pursuit eye movements, is accomplished by comparing a signal reflecting retinal image slip with an internal reference signal, encoding the eye movement. The important consequence of this concept is that our subjective percept of visual motion reflects the outcome of this comparison rather than retinal image slip. In an attempt to localize the cortical networks underlying this comparison and therefore our subjective percept of visual motion, we exploited an imperfection inherent in it, which results in a movement illusion. If smooth pursuit is carried out across a stationary background, we perceive a tiny degree of illusionary background motion (Filehne illusion, or FI), rather than experiencing the ecologically optimal percept of stationarity. We have recently shown that this illusion can be modified substantially and predictably under laboratory conditions by visual motion unrelated to the eye movement. By making use of this finding, we were able to compare cortical potentials evoked by pursuit-induced retinal image slip under two conditions, which differed perceptually, while being identical physically. This approach allowed us to discern a pair of potentials, a parieto-occipital negativity (N300) followed by a frontal positivity (P300), whose amplitudes were solely determined by the subjective perception of visual motion irrespective of the physical attributes of the situation. This finding strongly suggests that subjective awareness of visual motion depends on neuronal activity in a parietooccipito-frontal network, which excludes the early stages of visual processing.
A Computational Role for Dopamine Delivery in Human Decision-Making
Authors: Egelman David M. , Person Christophe , Montague P. Read
Published: July 2002

Recent work suggests that fluctuations in dopamine delivery at target structures represent an evaluation of future events that can be used to direct learning and decision-making. To examine the behavioral consequences of this interpretation, we gave simple decision-making tasks to 66 human subjects and to a network based on a predictive model of mesencephalic dopamine systems. The human subjects displayed behavior similar to the network behavior in terms of choice allocation and the character of deliberation times. The agreement between human and model performances suggests a direct relationship between biases in human decision strategies and fluctuating dopamine delivery. We also show that the model offers a new interpretation of deficits that result when dopamine levels are increased or decreased through disease or pharmacological interventions. The bottom-up approach presented here also suggests that a variety of behavioral strategies may result from the expression of relatively simple neural mechanisms in different behavioral contexts.
Asymptotic Convergence Rate of the EM Algorithm for Gaussian Mixtures
Authors: Ma Jinwen , Xu Lei , Jordan Michael I.
Published: July 2002

It is well known that the convergence rate of the expectation-maximization (EM) algorithm can be faster than those of convention first-order iterative algorithms when the overlap in the given mixture is small. But this argument has not been mathematically proved yet. This article studies this problem asymptotically in the setting of gaussian mixtures under the theoretical framework of Xu and Jordan (1996). It has been proved that the asymptotic convergence rate of the EM algorithm for gaussian mixtures locally around the true solution Θ* is o(e0.5−ε(Θ*)), where ε > 0 is an arbitrarily small number, o(x) means that it is a higher-order infinitesimal as x → 0, and e(Θ*) is a measure of the average overlap of gaussians in the mixture. In other words, the large sample local convergence rate for the EM algorithm tends to be asymptotically superlinear when e(Θ*) tends to zero.
Nonmonotonic Generalization Bias of Gaussian Mixture Models
Authors: Akaho Shotaro , Kappen Hilbert J.
Published: July 2002

Theories of learning and generalization hold that the generalization bias, defined as the difference between the training error and the generalization error, increases on average with the number of adaptive parameters. This article, however, shows that this general tendency is violated for a gaussian mixture model. For temperatures just below the first symmetry breaking point, the effective number of adaptive parameters increases and the generalization bias decreases. We compute the dependence of the neural information criterion on temperature around the symmetry breaking. Our results are confirmed by numerical cross-validation experiments.
Algebraic Analysis for Nonidentifiable Learning Machines
Authors: Watanabe Sumio
Published: July 2002

This article clarifies the relation between the learning curve and the algebraic geometrical structure of a nonidentifiable learning machine such as a multilayer neural network whose true parameter set is an analytic set with singular points. By using a concept in algebraic analysis, we rigorously prove that the Bayesian stochastic complexity or the free energy is asymptotically equal to λ1 logn − (m1 − 1) loglogn + constant, where n is the number of training samples and λ1 and m1 are the rational number and the natural number, which are determined as the birational invariant values of the singularities in the parameter space. Also we show an algorithm to calculate λ1 and m1 based on the resolution of singularities in algebraic geometry. In regular statistical models, 2λ1 is equal to the number of parameters and m1 = 1, whereas in nonregular models, such as multilayer networks, 2λ1 is not larger than the number of parameters and m1 ≥ 1. Since the increase of the stochastic complexity is equal to the learning curve or the generalization error, the nonidentifiable learning machines are better models than the regular ones if Bayesian ensemble learning is applied.
An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing
Authors: Senn Walter , Markram Henry , Tsodyks Misha
Published: July 2002

The precise times of occurrence of individual pre- and postsynaptic action potentials are known to play a key role in the modification of synaptic efficacy. Based on stimulation protocols of two synaptically connected neurons, we infer an algorithm that reproduces the experimental data by modifying the probability of vesicle discharge as a function of the relative timing of spikes in the pre- and postsynaptic neurons. The primary feature of this algorithm is an asymmetry with respect to the direction of synaptic modification depending on whether the presynaptic spikes precede or follow the postsynaptic spike. Specifically, if the presynaptic spike occurs up to 50 ms before the postsynaptic spike, the probability of vesicle discharge is upregulated, while the probability of vesicle discharge is downregulated if the presynaptic spike occurs up to 50 ms after the postsynaptic spike. When neurons fire irregularly with Poisson spike trains at constant mean firing rates, the probability of vesicle discharge converges toward a characteristic value determined by the preand postsynaptic firing rates. On the other hand, if the mean rates of the Poisson spike trains slowly change with time, our algorithm predicts modifications in the probability of release that generalize Hebbian and Bienenstock-Cooper-Munro rules. We conclude that the proposed spike- based synaptic learning algorithm provides a general framework for regulating neurotransmitter release probability.
Synchronization of the Neural Response to Noisy Periodic Synaptic Input
Authors: Burkitt A. N. , Clark G. M.
Published: July 2002

The timing information contained in the response of a neuron to noisy periodic synaptic input is analyzed for the leaky integrate-and-fire neural model. We address the question of the relationship between the timing of the synaptic inputs and the output spikes. This requires an analysis of the interspike interval distribution of the output spikes, which is obtained in the gaussian approximation. The conditional output spike density in response to noisy periodic input is evaluated as a function of the initial phase of the inputs. This enables the phase transition matrix to be calculated, which relates the phase at which the output spike is generated to the initial phase of the inputs. The interspike interval histogram and the period histogram for the neural response to ongoing periodic input are then evaluated by using the leading eigenvector of this phase transition matrix. The synchronization index of the output spikes is found to increase sharply as the inputs become synchronized. This enhancement of synchronization is most pronounced for large numbers of inputs and lower frequencies of modulation and also for rates of input near the critical input rate. However, the mutual information between the input phase of the stimulus and the timing of output spikes is found to decrease at low input rates as the number of inputs increases. The results show close agreement with those obtained from numerical simulations for large numbers of inputs.
Predictive Approaches for Choosing Hyperparameters in Gaussian Processes
Authors: Sundararajan S. , Keerthi S. S.
Published: July 2002

Gaussian processes are powerful regression models specified by parameterized mean and covariance functions. Standard approaches to choose these parameters (known by the name hyperparameters) are maximum likelihood and maximum a posteriori. In this article, we propose and investigate predictive approaches based on Geisser's predictive sample reuse (PSR) methodology and the related Stone's cross-validation (CV) methodology. More specifically, we derive results for Geisser's surrogate predictive probability (GPP), Geisser's predictive mean square error (GPE), and the standard CV error and make a comparative study. Within an approximation we arrive at the generalized cross-validation (GCV) and establish its relationship with the GPP and GPE approaches. These approaches are tested on a number of problems. Experimental results show that these approaches are strongly competitive with the existing approaches.
Robust Full Bayesian Learning for Radial Basis Networks
Authors: Andrieu Christophe , Freitas Nando de , Doucet Arnaud
Published: July 2002

We propose a hierarchical full Bayesian model for radial basis networks. This model treats the model dimension (number of neurons), model parameters, regularization parameters, and noise parameters as unknown random variables. We develop a reversible-jump Markov chain Monte Carlo (MCMC) method to perform the Bayesian computation. We find that the results obtained using this method are not only better than the ones reported previously, but also appear to be robust with respect to the prior specification. In addition, we propose a novel and computationally efficient reversible-jump MCMC simulated annealing algorithm to optimize neural networks. This algorithm enables us to maximize the joint posterior distribution of the network parameters and the number of basis function. It performs a global search in the joint space of the parameters and number of parameters, thereby surmounting the problem of local minima to a large extent. We show that by calibrating the full hierarchical Bayesian prior, we can obtain the classical Akaike information criterion, Bayesian information criterion, and minimum description length model selection criteria within a penalized likelihood framework. Finally, we present a geometric convergence theorem for the algorithm with homogeneous transition kernel and a convergence theorem for the reversible-jump MCMC simulated annealing method.
Temporal Correlations in Stochastic Networks of Spiking Neurons
Authors: Meyer Carsten , Vreeswijk Carl van
Published: July 2002

The determination of temporal and spatial correlations in neuronal activity is one of the most important neurophysiological tools to gain insight into the mechanisms of information processing in the brain. Its interpretation is complicated by the difficulty of disambiguating the effects of architecture, single-neuron properties, and network dynamics. We present a theory that describes the contribution of the network dynamics in a network of “spiking” neurons. For a simple neuron model including refractory properties, we calculate the temporal cross-correlations in a completely homogeneous, excitatory, fully connected network in a stable, stationary state, for stochastic dynamics in both discrete and continuous time. We show that even for this simple network architecture, the cross-correlations exhibit a large variety of qualitatively different properties, strongly dependent on the level of noise, the decay constant of the refractory function, and the network activity. At the critical point, the cross-correlations oscillate with a frequency that depends on the refractory properties or decay exponentially with a diverging damping constant (for “weak” refractory properties). We also investigate the effect of the synaptic time constants. It is shown that these time constants may, apart from their influence on the asymmetric peak arising from the direct synaptic connection, also affect the long-term properties of the cross-correlations.
Supervised Dimension Reduction of Intrinsically Low-Dimensional Data
Authors: Vlassis Nikos , Motomura Yoichi , Kröse Ben
Published: July 2002

High-dimensional data generated by a system with limited degrees of freedom are often constrained in low-dimensional manifolds in the original space. In this article, we investigate dimension-reduction methods for such intrinsically low-dimensional data through linear projections that preserve the manifold structure of the data. For intrinsically one-dimensional data, this implies projecting to a curve on the plane with as few intersections as possible. We are proposing a supervised projection pursuit method that can be regarded as an extension of the single-index model for nonparametric regression. We show results from a toy and two robotic applications.
Clustering Based on Conditional Distributions in an Auxiliary Space
Authors: Sinkkonen Janne , Kaski Samuel
Published: July 2002

We study the problem of learning groups or categories that are local in the continuous primary space but homogeneous by the distributions of an associated auxiliary random variable over a discrete auxiliary space. Assuming that variation in the auxiliary space is meaningful, categories will emphasize similarly meaningful aspects of the primary space. From a data set consisting of pairs of primary and auxiliary items, the categories are learned by minimizing a Kullback-Leibler divergence-based distortion between (implicitly estimated) distributions of the auxiliary data, conditioned on the primary data. Still, the categories are defined in terms of the primary space. An online algorithm resembling the traditional Hebb-type competitive learning is introduced for learning the categories. Minimizing the distortion criterion turns out to be equivalent to maximizing the mutual information between the categories and the auxiliary data. In addition, connections to density estimation and to the distributional clustering paradigm are outlined. The method is demonstrated by clustering yeast gene expression data from DNA chips, with biological knowledge about the functional classes of the genes as the auxiliary data.
Stable Propagation of Activity Pulses in Populations of Spiking Neurons
Authors: Kistler Werner M. , Gerstner Wulfram
Published: July 2002

We investigate the propagation of pulses of spike activity in a neuronal network with feedforward couplings. The neurons are of the spike-response type with a firing probability that depends linearly on the membrane potential. After firing, neurons enter a phase of refractoriness. Spike packets are described in terms of the moments of the firing-time distribution so as to allow for an analytical treatment of the evolution of the spike packet as it propagates from one layer to the next. Analytical results and simulations show that depending on the synaptic coupling strength, a stable propagation of the packet with constant waveform is possible. Crucial for this observation is neither the existence of a firing threshold nor a sigmoidal gain function—both are absent in our model—but the refractory behavior of the neurons.
Local Overfitting Control via Leverages
Authors: Monari Gaétan , Dreyfus Gérard
Published: July 2002

We present a novel approach to dealing with overfitting in black box models. It is based on the leverages of the samples, that is, on the influence that each observation has on the parameters of the model. Since overfitting is the consequence of the model specializing on specific data points during training, we present a selection method for nonlinear models based on the estimation of leverages and confidence intervals. It allows both the selection among various models of equivalent complexities corresponding to different minima of the cost function (e.g., neural nets with the same number of hidden units) and the selection among models having different complexities (e.g., neural nets with different numbers of hidden units). A complete model selection methodology is derived.
Density Estimation by Mixture Models with Smoothing Priors
Authors: Utsugi Akio
Published: July 2002

In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a gaussian mixture model with a gaussian smoothing prior on the centroid parameters. The values of the hyperparameters and the topological structure are selected on the basis of a statistical principle. However, since the component selection probabilities are fixed to a common value, the centroids concentrate on areas with high data density. This deforms a coordinate system on an extracted manifold and makes smoothness evaluation for the manifold inaccurate. In this article, we study an extended SOM model whose component selection probabilities are variable. To stabilize the estimation, a smoothing prior on the component selection probabilities is introduced. An estimation algorithm for the parameters and the hyperparameters based on empirical Bayesian inference is obtained. The performance of density estimation by the new model and the SOM model is compared via simulation experiments.
Toward Optimally Distributed Computation
Authors: Edwards Peter J. , Murray Alan F.
Published: July 2002

This article introduces the concept of optimally distributed computation in feedforward neural networks via regularization of weight saliency. By constraining the relative importance of the parameters, computation can be distributed thinly and evenly throughout the network. We propose that this will have beneficial effects on fault-tolerance performance and generalization ability in large network architectures. These theoretical predictions are verified by simulation experiments on two problems: one artificial and the other a real-world task. In summary, this article presents regularization terms for distributing neural computation optimally.
Analysis of Direction Selectivity Arising from Recurrent Cortical Interactions
Authors: Mineiro Paul , Zipser David
Published: July 2002

The relative contributions of feedforward and recurrent connectivity to the direction-selective responses of cells in layer IVB of primary visual cortex are currently the subject of debate in the neuroscience community. Recently, biophysically detailed simulations have shown that realistic direction-selective responses can be achieved via recurrent cortical interactions between cells with nondirection-selective feedforward input (Suarez et al., 1995; Maex & Orban, 1996). Unfortunately these models, while desirable for detailed comparison with biology, are complex and thus difficult to analyze mathematically. In this article, a relatively simple cortical dynamical model is used to analyze the emergence of direction-selective responses via recurrent interactions. A comparison between a model based on our analysis and physiological data is presented. The approach also allows analysis of the recurrently propagated signal, revealing the predictive nature of the implementation.
Stochastic Learning of Strategic Equilibria for Auctions
Authors: Bengio Samy , Bengio Yoshua , Robert Jacques , Bélanger Gilles
Published: July 2002

This article presents a new application of stochastic adaptive learning algorithms to the computation of strategic equilibria in auctions. The proposed approach addresses the problems of tracking a moving target and balancing exploration (of action space) versus exploitation (of better modeled regions of action space). Neural networks are used to represent a stochastic decision model for each bidder. Experiments confirm the correctness and usefulness of the approach.
Recurrent Sampling Models for the Helmholtz Machine
Authors: Dayan Peter
Published: July 2002

Many recent analysis-by-synthesis density estimation models of cortical learning and processing have made the crucial simplifying assumption that units within a single layer are mutually independent given the states of units in the layer below or the layer above. In this article, we suggest using either a Markov random field or an alternative stochastic sampling architecture to capture explicitly particular forms of dependence within each layer. We develop the architectures in the context of real and binary Helmholtz machines. Recurrent sampling can be used to capture correlations within layers in the generative or the recognition models, and we also show how these can be combined.
Response to “Building a Bridge between Different Scientific Communities: On Sheridan's Eclectic Ontology of Presence”
Authors: Sheridan Thomas B.
Published: July 2002

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Theoretical Analysis of Mutation-Adaptive Evolutionary Algorithms
Authors: Agapie Alexandru
Published: July 2002

Adaptive evolutionary algorithms require a more sophisticated modeling than their static-parameter counterparts. Taking into account the current population is not enough when implementing parameter-adaptation rules based on success rates (evolution strategies) or on premature convergence (genetic algorithms). Instead of Markov chains, we use random systems with complete connections - accounting for a complete, rather than recent, history of the algorithm's evolution. Under the new paradigm, we analyze the convergence of several mutation-adaptive algorithms: a binary genetic algorithm, the 1/5 success rule evolution strategy, a continuous, respectively a dynamic (1+1) evolutionary algorithm.
Ansatz for Dynamical Hierarchies
Authors: Rasmussen Steen , Baas Nils A. , Mayer Bernd , Nilsson Martin
Published: July 2002

Complex, robust functionalities can be generated naturally in at least two ways: by the assembly of structures and by the evolution of structures. This work is concerned with spontaneous formation of structures. We define the notion of dynamical hierarchies in natural systems and show the importance of this particular kind of organization for living systems. We then define a framework that enables us to formulate, investigate, and manipulate such dynamical hierarchies. This framework allows us to simultaneously investigate different levels of description together with their interrelationship, which is necessary to understand the nature of dynamical hierarchies. Our framework is then applied to a concrete and very simple formal, physicochemical, dynamical hierarchy involving water and monomers at level one, polymers and water at level two, and micelles (polymer aggregates) and water at level three. Formulating this system as a simple two-dimensional molecular dynamics (MD) lattice gas allows us within one dynamical system to demonstrate the successive emergence of two higher levels (three levels all together) of robust structures with associated properties. Second, we demonstrate how the framework for dynamical hierarchies can be used for realistic (predictive) physicochemical simulation of molecular self-assembly and self-organization processes. We discuss the detailed process of micellation using the three-dimensional MD lattice gas. Finally, from these examples we can infer principles about formal dynamical hierarchies. We present an ansatz for how to generate robust, higher-order emergent properties in formal dynamical systems that is based on a conjecture of a necessary minimal complexity within the fundamental interacting structures once a particular simulation framework is chosen.
Comparison of Different Genotype Encodings for Simulated Three-Dimensional Agents
Authors: Komosiński Maciej , Rotaru-Varga Adam
Published: July 2002

We analyze the effect of different genetic encodings used for evolving three-dimensional agents with physical morphologies. The complex phenotypes used in such systems often require nontrivial encodings. Different encodings used in Framsticks—a system for evolving three-dimensional agents—are presented. These include a low-level direct mapping and two higher-level encodings: one recurrent and one developmental. Quantitative results are presented from three simple optimization tasks (passive height, active height, and locomotion speed). The low-level encoding produced solutions of lower fitness than the two higher-level encodings under similar conditions. Results from recurrent and developmental encodings had similar fitness values but displayed qualitative differences. Desirable advantages and some drawbacks of more complex encodings are established.
The Nagorno-Karabakh Conflict Revisited: Was the War Inevitable?
Authors: Melander Erik
Published: July 2002

This article explains why the conflict over Nagorno-Karabakh escalated into full-scale ethnic warfare in the late 1980s and early 1990s. The article uses newly available sources to test the explanatory value of recent theories of conflict and strategic uncertainty. The evidence shows that in the summer of 1991 the Armenian separatist movement in Nagorno-Karabakh offered the Azerbaijani authorities virtual capitulation in exchange for a cessation of the offensive initiated against the region in the preceding spring. Because a more radical Armenian leadership gained the upper hand in Nagorno-Karabakh, and because the coup attempt in Moscow in August 1991 distracted Soviet leaders, the conflict soon became a full-fledged war.
RHETORIC AND DOMESTIC VIOLENCE IN EZEKIEL 16
Authors: Day Linda
Published: July 2002

Ezekiel 16 presents the narration of a man's relationship with his woman as an extended metaphor of Yhwh's relationship with Jerusalem. In consideration of its rhetoric, we discover that the speaking voice is exclusively male. The man Yhwh focuses upon sexual possession of the woman Jerusalem, uses shaming tactics, mandates voyeurism, and exhibits faulty logic in his condemnation of her. On a second level, when we compare the incident presented in the text with situations of domestic violence, we find that the textual interaction exhibits charac47 teristics similar to those of men who physically abuse women. Ezekiel 16 reflects a situation of woman battering in its content and progression. Its male speaker, Yhwh, exhibits those traits of a woman abuser: jealousy, possessiveness, and censuring. As batterers tend to wrongly suspect their women of affairs, this comparison serves to question the veracity of the male speaker in this text. On a third level, one finds that many who have interpreted this passage have overwhelmingly tended to believe the statements of the man Yhwh that the woman Jerusalem deserves the abuse. These male readers have taken a perspective similar to that of a battered woman before she leaves the relationship; they speak with a female voice.
IF DAVID HAD NOT CLIMBED THE MOUNT OF OLIVES
Authors: Thompson Thomas
Published: July 2002

The history of Israel has always been a virtual history. Until recently, historical debate in the field has confined itself almost entirely to a discussion about alternative fictional scenarios for the past: the patriarchs and the conquest stories as an alternative to the exodus and settlement narratives; Moses or Ezra; Josiah or John Hyrcanus. Evidence, when it has been of interest to the field at all, has ever been in regard to any given scenario's persuasiveness. The story of David on the Mount of Olives is used as an example of the theological world at stake in the Bible's virtual history; particularly in regard to the motif of Yahweh as 'the lord of history'. Recognition of such virtuality in the biblical tradition aids the contemporary historian of intellectual history. The story of Jesus on the Mount of Olives is used to illustrate this.
ISLAMIC INSTITUTIONS AND PROPERTY RIGHTS: THE CASE OF THE 'PUBLIC GOOD' WAQF
Authors: Shatzmiller Maya
Published: July 2002

The paper examines the institutional economic performance of the public good waqf with the intent of demonstrating the relevance of institutions to the momentous debate over Islamic backwardness and European progress and the waqf's role as supporter of learning institutions and promoter of social integration. Through the application of two sets of theoretical paradigms designed for measuring institutional behaviour, property rights and institutional arrangements, to legal cases supplied by fatwās from North Africa and Muslim Spain it will be possible to analyze and evaluate the impact of one of the major institutions of the premodern Islamic world on economic progress. L'article étudie la performance économique du waqf fiduciaire public, (waqf khairī), en tant qu'institution économique. Le but est de démontrer la pertinence de cette performance quant au débat sur la décadence économique des sociétés musulmanes par rapport au progrès que connut l'Europe. Sera étudié le rôle de l'activité économique institutionelle du waqf en général, et particulièrement dans les fonctions qui lui étaient attribuées, comme le soutien des institutions scolaires ainsi que la promotion de l'integrité sociale. Par l'application de deux paradigmes théoriques conçues pour mesurer le comportement institutionel, les droits de propriété et l'adaptation aux changements dans les conditions économiques rapportés par les documents juridiques tels les fatwās de l'Afrique du Nord et de l'Espagne musulmane, il sera possible d'analyser et d'évaluer l'impact de l'une des plus importantes institutions du monde islamique pré-moderne sur le progrès économique.
ON HINDU, HINDUSTĀN, HINDUISM AND HINDUTVA
Authors: Sharma Arvind
Published: July 2002

This paper sets out to examine the emergence and significance of the word Hindu (and associated terminology) in discourse about India, in order to determine the light it sheds on what is currently happening in India. It concludes that the word, and its derivatives, contain a series of semantic bivalences characterised by unresolved tensions, and further that these tensions help account for the complexities generated by the induction of the word Hindu (and associated terminology) in modern Indian political discourse.
Lies, Mistakes, and Blessings: Defining and Characteristic Features in Conceptual Development
Authors: Siegal Michael , Surian Luca , Nemeroff Carol , Peterson Candida
Published: July 2002

In this study, we examined the extent to which young children can be influenced by the perceived blessed status of an actor in their evaluations of behavior as a lie or mistake. Children aged 4 and 5 years attending Catholic schools in an urban center in Northern Italy were provided with a situation in which two girls in church were blessed with holy water ("blessed condition") or shook the priest's hand ("not blessed"). The girls were then placed in a setting in which each told a third girl that contaminated juice was good to drink: one deliberately lied and the other had no knowledge of the contaminant and made a mistake. Significantly more children judged both girls to have made a mistake in the blessed condition than in the not blessed condition. Their accuracy in distinguishing mistakes from lies in the not blessed condition resembled that reported in previous research in which traits such as blessedness (or its absence) were not assigned to the perpetrators. Thus children often perceived lying as uncharacteristic of the blessed whereas they applied the definition of lying as involving intentional falsehood for the not blessed. The results are discussed in terms of an early cultural cognition that involves beliefs about processes of purification and positive contagion.
THE EFFECT OF CASTRATION ON AGGRESSION IN THE NONBREEDING SEASON IS AGE-DEPENDENT IN MALE EUROPEAN STARLINGS
Authors: Pinxten Rianne , De Ridder Elke , Balthazart Jacques , Berghman Luc , Eens Marcel
Published: July 2002

In birds, testosterone (T) regulates aggression during the breeding season. However, in some avian species, including European starlings (Sturnus vulgaris), males also display high levels of aggression during the nonbreeding season (autumn and winter), when plasma T levels are low or non-detectable and even after castration. This nonbreeding aggression is generally believed to be independent of testicular T. Moreover, in European starlings several laboratory experiments even indicated that fighting ability was increased rather than decreased by castration. Here, we examined the effect of castration on nonbreeding aggression in captive male European starlings by pairing castrated males with sham-castrated males of the same age in dyadic trials and determining which male was significantly more aggressive when both birds were competing over access for a nestbox to roost in. Birds were (sham) castrated on 9 October and the dominance trials were run between December 2 and Febuary 7. In adults, we found no evidence that castration affected the frequency of nonbreeding aggression, despite the fact that T-levels in castrated males were significantly lower than in sham-castrated birds. In contrast, in yearling males that were castrated at the age of 4-5 months, castration significantly decreased nonbreeding aggression, although T-levels were only marginally decreased by the surgery. The maintenance of aggressive behaviour after castration in adults may be the result of experience or of the action of nongonadal sex steroids. The marked decrease in aggressive behaviour observed in castrated yearlings might be due to the fact that castration at this young age could have inhibited the ontogenetic development of behavioural and physiological mechanisms requiring signals from the gonads. Taken together, these results indicate that the effects of castration on nonbreeding aggression in male European starlings markedly depend on the age at the time of castration.
THE EFFECT OF CHANGING CALL DURATION AND CALLING BOUTS ON VIGILANCE IN BRANTS' WHISTLING RAT, PAROTOMYS BRANTSII
Authors: Roux Aliza Le , Jackson Tim , Cherry Michael
Published: July 2002

The function of variation in single call duration and alarm calling bouts was investigated in Brants' whistling rat, Parotomys brantsii, by means of playback experiments and video analyses of the vigilance displayed. Short calls are produced in high-risk situations, and long calls in low-risk encounters, but these calls apparently do not communicate this variance in risk to conspecifics. Both short and long single calls induced heightened vigilance in receivers, but rats did not respond differentially to the two call types, and it was concluded that P.brantsii alarm calls are not functionally referential. Multiple calls maintained a state of increased alertness in receivers for a longer period than single calls, even after the bouts had ended, but long bouts (duration: 64 s) did not lead to longer periods of vigilance than short bouts (29 s). Thus the tonic communication hypothesis is only partially supported by our study.
VARIATION OF SOUND PARAMETERS AFFECTS THE EVALUATION OF HUMAN LAUGHTER
Authors: Kipper Silke , Todt Dietmar
Published: July 2002

Sounds of human laughter compose quite effectual stimuli that usually facilitate positive responses. We have studied the mechanisms of such effects and investigated how changes in particular acoustical signal parameters affect the evaluation of laughter. Effects were assessed by evaluating self-report data of human subjects who had been exposed to playbacks of experimentally modified laughter material and, for control, also to samples of natural laughter. The modified laughter phrases were generated by first analysing samples of natural laughter, and then using these data to synthesise new laughter material. Analyses of subjects' responses revealed that not only samples that resembled the rhythm of natural laughter (repetition interval of about 0.2 s) were evaluated positively. Instead we found that series with a wide range of repetition intervals were perceived as laughter. The mode of parameter changes within the model series had an additional clear effect on the rating of a given playback sample. Thus, an intra-serial variation of rhythm or pitch received ratings that were closer to ratings of natural laughter (control) than did a stereotyped patterning of stimuli. Especially stimuli with decreases in pitch were well suited to elicit positive reactions. In conclusion, our results showed that features of parameter variations can make human laughter particularly effectual.
AN EXPERIMENTAL EVALUATION OF THE CONSISTENCY OF COMPETITIVE ABILITY AND AGONISTIC DOMINANCE IN DIFFERENT SOCIAL CONTEXTS IN CAPTIVE BONOBOS
Authors: Vervaecke Hilde , Vries Han De , Elsacker Linda Van
Published: July 2002

Bonobos have been described as a relatively egalitarian and female dominant species. The exact nature and quality of their dominance relationships and the existence of female dominance are current topics of dispute. We investigated the consistency across social contexts, the stability in time, and the degree of expression of the competitive feeding ability and agonistic dominance in a captive group of bonobos. First, we examined whether the competitive feeding ranks and agonistic ranks differed in different dyadic contexts, triadic contexts and the whole group context. For some pairs of animals the dominance relationships with respect to competitive feeding altered with different group compositions. The agonistic dominance relationships changed accordingly. The competitive feeding ranks and agonistic ranks in the experiments correlated strongly with each other. The alpha position was occupied by a female, but not all females outranked all males. We suggest that females can profit from each others presence to gain inter-sexual dominance. Second, although the agonistic rank order in the whole group remained the same over at least five years, some dyadic competitive feeding ranks changed over time, resulting in a stronger female intersexual dominance. Third, the degree of expression of the behaviors used to quantify dyadic competitive and agonistic dominance was not high, in line with the popular 'egalitarian' epithet. Notwithstanding its low consistency across contexts, the dominance hierarchy in the whole group has a strong predictive value for other social relationships such as grooming. Given this strong effect of rank on other behaviours and given the strong dependency of rank on social context, the choice of the right party members may be a crucial factor in the fission-fusion processes of free-ranging bonobos.
Chemical composition of smectites formed in clastic sediments. Implications for the smectite-illite transformation
Authors: Drief A. , Nieto F.
Published: July 2002

Analytical electron microscopy of representative smectites from soils and sediments revealed that K was present in significant proportions. It was the major interlayer cation in soils from pelitic rocks, continental and marine sediments, independent of their diagenetic grade. Sodium was predominant only in soils from basic rock. Fluvial sediments contained smectites with both kinds of interlayer compositions. The octahedral composition of each sample ranged widely, covering various fields of dioctahedral smectites. The most important trend was the substitution of Al by Fe and Mg; the chemistry of each smectite particle was determined by the parent mineral from which it formed. The real interlayer composition has important implications for the diagenetic smectite–illite transformation. When considering a typical K content, the smectite–illite reaction, with chlorite and quartz as subproducts, needs only 0.21 K atoms. For more K-rich compositions, a reaction is possible without an external supply of K.
Clay mineral mixtures as alteration products in pillow basalts from the eastern flank of Juan de Fuca Ridge: a TEM-AEM study
Authors: Giorgetti G. , Marescotti P. , Cabella R. , Lucchetti G.
Published: July 2002

Transmission electron microscope-analytical electron microscope analyses have been carried out on secondary minerals from pillow basalts with various degrees of alteration from the Juan de Fuca Ridge (ODP Leg 168). The electron microscopic data indicate that the alteration products consist mainly of phyllosilicate mixtures. The least altered sample shows poorly crystalline phyllosilicates occurrring as flakes with 10 Å -spaced lattice fringes. They have compositions of celadonite mixed with smectite and/or Fe oxyhydroxides and Mg-rich smectite. Proceeding towards older, more altered basalts, the alteration products consist of: (1) poorly crystalline celadonite mixtures and Mg-rich smectite; and (2) phyllosilicates with a higher degree of crystallinity, showing lattice fringes with 9.1 Å -spacing and with a talc-like composition. Changes in phyllosilicate association occur as the type of alteration changes from an oxidizing, water-dominated system (occurrence of celadonite mixtures with Fe hydroxides) to a reducing, rock-dominated system (occurrence of Fe-smectite and talc-like mixtures).
K-rich rectorite from kaolinized micaschist of the Sesia-Lanzo Zone, Italy
Authors: Benincasa E. , Brigatti M. F. , Medici L. , Poppi L.
Published: July 2002

Rectorite crystals [[4](Si6.81Al1.19)[6](Al3.26Ti0.04Fe0.553+Mg0.18Mn0.01)[12](Na0.02K0.88Mg0.16Ca0.01)O20(OH)4·0.75H2O] found in micaschist of the Sesia-Lanzo Zone (NW Italy) were studied using a variety of techniques including microprobe analysis, infrared spectroscopy, single crystal and powder X-ray diffraction, atomic force microscopy and thermal analysis. Chemical data and exchangeable cation determination indicate that K+is the dominant non-exchangeable interlayer cation, and thus is believed to occupy the mica interlayer site; Mg2+together with small amounts of Ca2+, Na+and K+represent the exchangeable cations and can therefore be related to the smectite-like component. The coefficient of variation, CV, ofd(00l) values (CVnatural= 0.47; CVglycolated= 0.43) demonstrates the regularity of the mica-smectite interstratification, whereas the unit-cell parameters obtained by single crystal methods suggest different layer-stacking models.
Assessment of surface energetic heterogeneity of synthetic Na- saponites. The role of layer charge
Authors: Michot L. J. , Villiéras F.
Published: July 2002

High-resolution gas adsorption techniques were used to analyse the evolution of the aspect ratio and adsorption energy distribution on synthetic saponite samples with increasing layer charge. Using Ar as a gaseous probe, the aspect ratio of the saponite particles can be determined easily by decomposing the derivative adsorption isotherms and taking into account high-energy sites which can be assigned to talc-like ditrigonal cavities. Changes in the shape of the elementary particles are observed for layer charges above 1.30, i.e. when all the ditrigonal cavities contain at least one Al atom substituting for Si. When N2is used as a probe, high-energy sites that could be wrongly interpreted as micropores on the basis of classical t-plot treatments are observed whatever the layer charge. Using the information obtained from both Ar and N2, schemes for describing adsorption can be proposed for all layer charges and suggest complex adsorption mechanisms for charged clay minerals.
Clay mineral alteration associated with meteorite impact in the marine environment (Barents Sea)
Authors: Dypvik H. , Ferrell R. E.
Published: July 2002

More than 50 samples from a Barents Sea borehole near the Mjolnir Structure (an extraterrestrial impact feature) were used to investigate changes in the clay assemblage associated with the submarine impact. Seismic evidence, the presence of shocked quartz and a prominent Ir anomaly restricted the potential impact affected zone to a 10 m interval, straddling the Jurassic/Cretaceous boundary.

Increased abundance (up to 30 wt%) of a smectite, a randomly interstratified smectite-illite with 85% smectite layers, forms the basis for a two-layer oceanic impact clay model that differs from published terrestrial cases. The smectite is assumed to represent seawater-altered impact glass from the ejecta blanket material that was mixed with resuspended shelf sediments by the collision generated waves. The smectite-rich interval is almost 5 m thick. It is overlain by a coarser unit (~2 m thick) containing abundant smectite, shocked quartz grains, and anomalous Ix contents at its base. The smectite-rich interval may have originated as a density/turbidity current, generated by the impact and the collapse and erosion of the crater rim. Seawater alteration of volcanic glass and changes in the tectonic regime of the provenance area, or changing oceanic current circulation patterns could produce similar variations in the clay mineral assemblage. The most compelling evidence for the possible impact derivation of this clay assemblage is the direct association with the Mjolnir Impact Structure and associated mineralogical and geochemical anomalies.