bluuebunny/crossref_metadata_2025 huggingface dataset:
From Mercenary to Citizen Armies: Explaining Change in the Practice of War
Authors: Avant Deborah
Published: July 2002

Mercenary armies went out of style in the nineteenth century; it became common sense that armies should be staffed with citizens. I argue that even though realist explanations focusing on the fighting prowess of citizen armies and sociological explanations focusing on the fit between citizen armies and prevailing ideas can rationalize this change, they cannot explain it. I examine, instead, the politics behind the new reliance on citizen armies and argue that material and ideational turmoil provided important antecedent conditions for change. Beyond this, individual states were more likely to move toward citizen armies when they had been defeated militarily and when the ruling coalition was split or indifferent about the reforms tied to citizen armies. Finally, the apparent success of citizen armies in France and then Prussia made do mestic conditions for reform easier to obtain in other countries, reinforcing the likelihood that the solution would be replicated. I conclude that the interaction between domestic politics and path dependency provides a promising source of hypotheses for explaining the conditions under which new ways of war emerge and spread.
Violence and the Social Construction of Ethnic Identity
Authors: Fearon James D. , Laitin David D.
Published: July 2002

We examine the theoretical implications of the observation that ethnic identities are socially constructed for explaining ethnic violence, distinguishing between two classes of mechanisms. If individuals are viewed as the agents who construct identities, then constructivist explanations for ethnic violence tend to merge with analyses that stress strategic action by both elites and mass publics. In contrast, if discursive formations are the agents that construct ethnic identities, then constructivist explanations tend to merge with accounts that stress internal logics of specific cultures. Using the books under review as a “sample,” we find considerable evidence linking strategic aspects of ethnic identity construction to violence and more limited evidence implicating discursive systems. The most common narrative in these texts has largescale ethnic violence provoked by elites, often motivated by intra-ethnic conflicts. Followers follow, despite the costs, out of increased fear of thugs and armies “let go” by elites (both the other side's and their “own”) and often in pursuit of local grievances that may have little ethnic component. Several other mechanisms are also discussed, including the role of discursive systems in conditioning publics for violence and the role of violent efforts to enforce “everyday primordialism” by policing supposedly primordial ethnic boundaries.
Clear and Clean: The Fixed Effects of the Liberal Peace
Authors: Oneal John R. , Russett Bruce
Published: July 2002

In their article in this issue, Donald P. Green, Soo Yeon Kim, and David H. Yoon claim, contrary to liberal theory and extensive evidence, that neither joint democracy nor economic interdependence significantly reduces the frequency of militarized interstate disputes in pooled time-series analyses when dyadic fixed effects are taken into account. Similarly, their fixed-effects analyses contradict theory and previous evidence that democracies have higher levels of trade with one another than do other types of states. Our reexamination, however, refutes both claims and reinforces previous findings. Their fixed-effects analyses of disputes produces distorted results because they consider a relatively short time period, 1951–92, in which variation in the binary dependent variable and the key independent variables, democracy and trade, is limited. When we analyze a longer period (1886–1992), the results confirm liberal theory. The differences between our analyses of bilateral trade and those of Green, Kim, and Yoon primarily arise from a seemingly minor methodological decision. A more reasonable method confirms that democracies do have higher levels of trade than expected on purely economic grounds. Though we do not advocate a fixed-effects model for analyzing these data and have serious reservations about its general usefulness, our findings provide additional confirmation of liberal theories of international relations.
Taking Preferences Seriously: A Liberal Theory of International Politics
Authors: Moravcsik Andrew
Published: July 2002

This article reformulates liberal international relations (IR) theory in a nonideological and nonutopian form appropriate to empirical social science. Liberal IR theory elaborates the insight that state-society relations—the relationship of states to the domestic and transnational social context in which they are embedded—have a fundamental impact on state behavior in world politics. Societal ideas, interests, and institutions influence state behavior by shaping state preferences, that is, the fundamental social purposes underlying the strategic calculations of governments. For liberals, the configuration of state preferences matters most in world politics—not, as realists argue, the configuration of capabilities and not, as institutionalists (that is, functional regime theorists)maintain, the configuration of information and institutions. This article codifies this basic liberal insight in the form of three core theoretical assumptions, derives from them three variants of liberal theory, and demonstrates that the existence of a coherent liberal theory has significant theoretical, methodological, and empirical implications. Restated in this way, liberal theory deserves to be treated as a paradigmatic alternative empirically coequal with and analytically more fundamental than the two dominant theories in contemporary IR scholarship: realism and institutionalism.
Relazioni Emergenti: Experiments with the Art of Emergence
Authors: Annunziato Mauro , Pierucci Piero
Published: July 2002

Progress in the scientific understanding and simulation of natural evolutionary mechanisms may be creating the basis for a new stage in evolution: the coming of artificial beings and artificial societies. Culture itself, aesthetics and intelligence are coming to be seen as the emergent, self-organizing qualities of a collectivity, evolved over time through both genetic and linguistic evolution. This paper sketches the development of hybrid digital worlds, in which artificial beings are able to evolve their own cultures, languages and aesthetics. Finally, the authors discuss their interactive audio-visual art installation Relazioni Emergenti, based on artificial-life environments. In this work, digital beings can interact, reproduce and evolve through the mechanisms of genetic mutation. People can interact with these artificial beings, creating hybrid ecosystems.
Into the Belly of the Image: Historical Aspects of Virtual Reality
Authors: Grau Oliver
Published: July 2002

Virtual reality (VR) is a constant phenomenon in art history that can be traced back to antiquity. It can involve an area of ritual action, a private, artificial paradise, or a public sphere with politically suggestive power—in short, it encompasses a visual history that is characterized by totality. The concept of transposing viewers into an enclosed, illusionary visual space has been revived and expanded in the VR art of the current age. The more intimate ly an interface nestles into viewers' senses, the more intense their immersion will be. Such an interface weakens the viewers' sense of psychological distance and puts the relationship between art and consciousness into question.
Features, Syntax, and Categories in the Latin Perfect
Authors: Embick David
Published: July 2002

The analysis centers on the notion of category in synthetic and analytic verbal forms and on the status of the feature that determines the forms of the Latin perfect. In this part of the Latin verbal system, active forms are synthetic (“verbs”) but passive forms are analytic (i.e., participle and finite auxiliary). I show that the two perfects occur in essentially the same structure and are distinguished by a difference in movement to T; moreover, the difference in forms can be derived without reference to category labels like “Verb” or “Adjective” on the Root. In addition, the difference in perfects is determined by a feature with clear syntactic consequences, which must be associated arbitrarily with certain Roots, the deponent verbs. I discuss the implications of these points in the context of Distributed Morphology, the theory in which the analysis is framed.
Null Object and Sloppy Identity in Japanese
Authors: Hoji Hajime
Published: July 2002

I demonstrate that the null object construction (NOC) in Japanese cannot be analyzed on a par with VP-ellipsis (VPE) in English, contrary to the suggestion made in Huang 1988, 1991 and Otani and Whitman 1991. I argue that what are considered to be “sloppy identity readings” in these works are not genuine sloppy identity readings, and I argue that such readings arise quite independently of the alleged VPE status of the NOC.
Learnability in Optimality Theory
Authors: Tesar Bruce , Smolensky Paul
Published: July 2002

In this article we show how Optimality Theory yields a highly general Constraint Demotion principle for grammar learning. The resulting learning procedure specifically exploits the grammatical structure of Optimality Theory, independent of the content of substantive constraints defining any given grammatical module. We decompose the learning problem and present formal results for a central subproblem, deducing the constraint ranking particular to a target language, given structural descriptions of positive examples. The structure imposed on the space of possible grammars by Optimality Theory allows efficient convergence to a correct grammar. We discuss implications for learning from overt data only, as well as other learning issues. We argue that Optimality Theory promotes confluence of the demands of more effective learnability and deeper linguistic explanation.
First Conjunct Agreement: Against a Clausal Analysis
Authors: Munn Alan
Published: July 2002

Aoun, Benmamoun, and Sportiche (1994) propose that first conjunct agreement in Arabic is derived from clausal conjunction. This article shows that the clausal account of first conjunct agreement is empirically inadequate because it fails to distinguish clearly between syntactic and semantic agreement. It argues that an analysis of coordination as adjunction proposed in Munn 1992, 1993 accounts both for the Arabic facts and for the fact that first conjunct agreement is dependent on head government. It also shows that there are asymmetries between governed agreement and specifier-head agreement that are independent of coordination, lending support to a unified analysis of first conjunct agreement in terms of government or its equivalent.
Auditory and Visual Spatial Localization Deficits Following Bilateral Parietal Lobe Lesions in a Patient with Balint's Syndrome
Authors: Phan M. L. , Schendel K. L. , Recanzone G. H. , Robertson L. C.
Published: July 2002

Lesion and electrophysiological studies indicate that the parietal lobes play a role in visual spatial attention and in computing the spatial coordinates of visual input. Fewer studies have investigated the role of the parietal lobe in auditory spatial processing, and an extensive comparison of visual and auditory spatial processing in humans with parietal lobe lesions has yet to be conducted. We have studied such localization abilities in a Balint's syndrome patient (RM) who has bilateral parietal lobe lesions. The results indicated that this patient had a significant deficit in both visual and auditory localization relative to age-matched controls. Unlike the controls, however, RM's auditory localization ability either matched or exceeded his visual localization ability depending on the task. Accordingly, RM exhibited “auditory capture”, but not “visual capture” under conditions where control subjects showed the opposite pattern. These results are consistent with hypotheses that the parietal lobes are involved in creating multiple spatial representations and in shifting from one spatial reference point to another, but suggest that these parietal structures are not necessary for the integration of multiple sensory stimuli resulting in capture effects.
Functional Brain Imaging of Young, Nondemented, and Demented Older Adults
Authors: Buckner Randy L. , Snyder Abraham Z. , Sanders Amy L. , Raichle Marcus E. , Morris John C.
Published: July 2002

Brain imaging based on functional MRI (fMRI) provides a powerful tool for characterizing age-related changes in functional anatomy. However, between-population comparisons confront potential differences in measurement properties. The present experiment explores the feasibility of conducting fMRI studies in nondemented and demented older adults by measuring hemodynamic response properties in an event-related design. A paradigm involving repeated presentation of sensory-motor response trials was administered to 41 participants (14 young adults, 14 nondemented older adults, and 13 demented older adults). For half of the trials a single sensory-motor event was presented in isolation and in the other half in pairs. Hemodynamic response characteristics to the isolated events allowed basic response properties (e.g., amplitude and variance) between subject groups to be contrasted. The paired events further allowed the summation properties of the hemodynamic response to be characterized. Robust and qualitatively similar activation maps were produced for all subject groups. Quantitative results showed that for certain regions, such as in the visual cortex, there were marked reductions in the amplitude of the hemodynamic response in older adults. In other regions, such as in the motor cortex, relatively intact response characteristics were observed. These results suggest caution should be exhibited in interpreting simple main effects in response amplitude between subject groups. However, across all regions examined, the summation of the hemodynamic response over trials was highly similar between groups. This latter finding suggests that, even if absolute measurement differences do exist between subject groups, relative activation change should be preserved. Designs that rely on group interactions between task conditions, parametric manipulations, or group interactions between regions should provide valuable data for making inferences about functional-anatomic changes between different populations.
Encoding Processes during Retrieval Tasks
Authors: Buckner Randy L. , Wheeler Mark E. , Sheridan Margaret A.
Published: July 2002

Episodic memory encoding is pervasive across many kinds of task and often arises as a secondary processing effect in tasks that do not require intentional memorization. To illustrate the pervasive nature of information processing that leads to epeisodic encoding, a form of incidental encoding was explored based on the “Testing” phenomenon: The incidental-encoding task was an episodic memory retrieval task. Behavioral data showed that performing a memory retrieval task was as effedctive as intentional instructions at promoting episodic encoding. During fMRI imaging, subjedcts veiewed old and new words adn indicated whether they remembered them. Relevant to encoding, the fate of the new words was examined using a second, surprise test of recognition after the imaging session, fMRI analysis of those new words that were later remembered revealed greater activity in left frontal regions than those that were later forgotten-the same pattern of results as previously observed for traditional incidental and intentional episodic encoding tasks. This finding may offer a partial explanation for why repeated testing improves memory performance. Furthermore, the observation of correlates of episodic memory encoding during retrieval tasks challenges some interpretations that aris from direct comparisons between: encoding tasks and “retrieval tasks” in imaging data. Encoding processes and their neural correlates may arise in many tasks, even those nominally labeled as retrieval tasks by the experimenter.
Identifying Rate-Limiting Nodes in Large-Scale Cortical Networks for Visuospatial Processing: An Illustration using fMRI
Authors: Ng V. W. K. , Bullmore E. T. , de Zubicaray G. I. , Cooper A. , Suckling J. , Williams S. C. R.
Published: July 2002

With the advent of functional neuroimaging techniques, in particular functional magnetic resonance imaging (fMRI), we have gained greater insight into the neural correlates of visuospatial function. However, it may not always be easy to identify the cerebral regions most specifically associated with performance on a given task. One approach is to examine the quantitative relationships between regional activation and behavioral performance measures. In the present study, we investigated the functional neuroanatomy of two different visuospatial processing tasks, judgement of line orientation and mental rotation Twenty-four normal participants were scanned with fMRI using blocked periodic designs for experimental task presentation. Accuracy and reaction time (RT) to each trial of both activation and baseline conditions in each experiment was recorded. Both experiments activated dorsal and ventral visual cortical areas as well as dorsolateral prefrontal cortex. More regionally specific associations with task performance were identified by estimating the association between (sinusoidal) power of functional response and mean RT to the activation condition; a permutation test based on spatial statistics was used for inference. There was significant behavioral-physiological association in right ventral extrastriate cortex for the line orientation task and in bilateral (predominantly right) superior parietal lobule for the mental rotation task. Comparable associations were not found between power of response and RT to the baseline conditions of the tasks. These data suggest that one region in a neurocognitive network may be most strongly associated with behavioral performance and this may be regarded as the computationally least efficient or rate-limiting node of the network.
Switching Attention without Shifting the Spotlight: Object-Based Attentional Modulation of Brain Potentials
Authors: Valdes-Sosa Mitchell , Bobes Maria A. , Rodriguez Valia , Pinilla Tupac
Published: July 2002

Although psychophysical evidence for object-based attention has been reported, corresponding studies with event-related potentials (ERPs) are scarce. Here subjects were presented with perceptual fields containing two superimposed objects (transparent surfaces generated by two sets of dots in rigid rotation around fixation, each set of a different color and direction of motion) or only one object (the same dots but either at rest or all rotating in the same direction). Brief (150-msec) rectilinear displacements affected either of the sets at random ISIs of 350 to 550 msec. Attention was directed to one set of dots, guided by color, in order to discriminate the direction of their displacement. Motion-onset ERPs elicited by these displacements were compared for attended and unattended dots. When the perceptual field consisted of two objects, strong suppression of P1 and N1 was obtained in the ERPs associated with the unattended object. No suppression was found with the field containing a single object, although an enhanced selection negativity was found in ERPs associated with attended dots (selected by color). Since the two objects occupied the same region of visual space, the suppression of P1/N1 cannot be explained by the space-based mechanisms but is consistent with object-based attentional selection at early stages of vision. The results highlight the role of perceptual organization in enabling alternative attentional mechanisms.
Delineating Necessary and Sufficient Neural Systems with Functional Imaging Studies of Neuropsychological Patients
Authors: Price C. J. , Mummery C. J. , Moore C. J. , Frackowiak R. S. J. , Friston K. J.
Published: July 2002

This paper demonstrates how functional imaging studies of neuropsychological patients can provide a way of determining which areas in a cognitive network are jointly necessary and sufficient. The approach is illustrated with an investigation of the neural system underlying semantic similarity judgments. Functional neuroimaging demonstrates that normal subjects activate left temporal, parietal, and inferior frontal cortices during this task relative to physical size judgments. Neuropsychology demonstrates that damage to the temporal and parietal regions results in semantic deficits, indicating that these areas are necessary for task performance. In contrast, damage to the inferior frontal cortex does not impair task performance, indicating that the inferior frontal cortex might not be necessary. However, there are two other possible accounts of intact performance following frontal lobe damage: (1) there is functional reorganization involving the right frontal cortex and (2) there is peri-infarct activity around the damaged left-hemisphere tissue. Functional imaging of the patient is required to discount these possibilities. We investigated a patient (SW), who was able to associate words and pictures on the basis of semantic relationships despite extensive damage to the left frontal, inferior parietal, and superior temporal cortices. Although SW showed peri-infarct activation in left extrasylvian temporal cortices, no activity was observed in either left or right inferior frontal cortices. These ªndings demonstrate that activity in extrasylvian temporo-parietal and medial superior frontal regions is sufªcient to perform semantic similarity judgments. In contrast, the left inferior frontal activations detected in each control subject appear not to be necessary for task performance. In conclusion, necessary and sufªcient brain systems can be delineated by functional imaging of brain-damaged patients who are not functionally impaired.
Relating Macroscopic Measures of Brain Activity to Fast, Dynamic Neuronal Interactions
Authors: Chawla D. , Lumer E. D. , Friston K. J.
Published: July 2002

In this article we used biologically plausible simulations of coupled neuronal populations to address the relationship between phasic and fast coherent neuronal interactions and macroscopic measures of activity that are integrated over time, such as the BOLD response in functional magnetic resonance imaging. Event-related, dynamic correlations were assessed using joint peristimulus time histograms and, in particular, the mutual information between stimulus-induced transients in two populations. This mutual information can be considered as an index of functional connectivity. Our simulations showed that functional connectivity or dynamic integration between two populations increases with mean background activity and stimulus-related rate modulation. Furthermore, as the background activity increases, the populations become increasingly sensitive to the intensity of the stimulus in terms of a predisposition to transient phase locking. This reflects an interaction between background activity and stimulus intensity in producing dynamic correlations, in that background activity augments stimulus-induced coherence modulation. This is interesting from a computational perspective because background activity establishes a context that may have a profound effect on event-related interactions or functional connectivity between neuronal populations. Finally, total firing rates, which subsume both background activity and stimulus-related rate modulation, were almost linearly related to the expression of dynamic correlations over large ranges of activities. These observations show that under the assumptions implicit in our model, rate-specific metrics based on rate or coherence modulation may be different perspectives on the same underlying dynamics. This suggests that activity (averaged over all peristimulus times), as measured in neuroimaging, may be tightly coupled to the expression of dynamic correlations.
Modeling Selective Attention Using a Neuromorphic Analog VLSI Device
Authors: Indiveri Giacomo
Published: July 2002

Attentional mechanisms are required to overcome the problem of flooding a limited processing capacity system with information. They are present in biological sensory systems and can be a useful engineering tool for artificial visual systems. In this article we present a hardware model of a selective attention mechanism implemented on a very large-scale integration (VLSI) chip, using analog neuromorphic circuits. The chip exploits a spike-based representation to receive, process, and transmit signals. It can be used as a transceiver module for building multichip neuromorphic vision systems. We describe the circuits that carry out the main processing stages of the selective attention mechanism and provide experimental data for each circuit. We demonstrate the expected behavior of the model at the system level by stimulating the chip with both artificially generated control signals and signals obtained from a saliency map, computed from an image containing several salient features.
Separating Style and Content with Bilinear Models
Authors: Tenenbaum Joshua B. , Freeman William T.
Published: July 2002

Perceptual systems routinely separate “content” from “style,” classifying familiar words spoken in an unfamiliar accent, identifying a font or handwriting style across letters, or recognizing a familiar face or object seen under unfamiliar viewing conditions. Yet a general and tractable computational model of this ability to untangle the underlying factors of perceptual observations remains elusive (Hofstadter, 1985). Existing factor models (Mardia, Kent, & Bibby, 1979; Hinton & Zemel, 1994; Ghahramani, 1995; Bell & Sejnowski, 1995; Hinton, Dayan, Frey, & Neal, 1995; Dayan, Hinton, Neal, & Zemel, 1995; Hinton & Ghahramani, 1997) are either insufficiently rich to capture the complex interactions of perceptually meaningful factors such as phoneme and speaker accent or letter and font, or do not allow efficient learning algorithms. We present a general framework for learning to solve two-factor tasks using bilinear models, which provide sufficiently expressive representations of factor interactions but can nonetheless be fit to data using efficient algorithms based on the singular value decomposition and expectation-maximization. We report promising results on three different tasks in three different perceptual domains: spoken vowel classification with a benchmark multi-speaker database, extrapolation of fonts to unseen letters, and translation of faces to novel illuminants.
Expanding NEURON's Repertoire of Mechanisms with NMODL
Authors: Hines M. L. , Carnevale N. T.
Published: July 2002

Neuronal function involves the interaction of electrical and chemical signals that are distributed in time and space. The mechanisms that generate these signals and regulate their interactions are marked by a rich diversity of properties that precludes a “one size fits all” approach to modeling. This article presents a summary of how the model description language NMODL enables the neuronal simulation environment NEURON to accommodate these differences.
Variational Learning for Switching State-Space Models
Authors: Ghahramani Zoubin , Hinton Geoffrey E.
Published: July 2002

We introduce a new statistical model for time series that iteratively segments data into regimes with approximately linear dynamics and learns the parameters of each of these linear regimes. This model combines and generalizes two of the most widely used stochastic time-series models—hidden Markov models and linear dynamical systems—and is closely related to models that are widely used in the control and econometrics literatures. It can also be derived by extending the mixture of experts neural network (Jacobs, Jordan, Nowlan, & Hinton, 1991) to its fully dynamical version, in which both expert and gating networks are recurrent. Inferring the posterior probabilities of the hidden states of this model is computationally intractable, and therefore the exact expectation maximization (EM) algorithm cannot be applied. However, we present a variational approximation that maximizes a lower bound on the log-likelihood and makes use of both the forward and backward recursions for hidden Markov models and the Kalman filter recursions for linear dynamical systems. We tested the algorithm on artificial data sets and a natural data set of respiration force from a patient with sleep apnea. The results suggest that variational approximations are a viable method for inference and learning in switching state-space models.
On-line EM Algorithm for the Normalized Gaussian Network
Authors: Sato Masa-aki , Ishii Shin
Published: July 2002

A normalized gaussian network (NGnet) (Moody & Darken, 1989) is a network of local linear regression units. The model softly partitions the input space by normalized gaussian functions, and each local unit linearly approximates the output within the partition. In this article, we propose a new on-line EM algorithm for the NGnet, which is derived from the batch EM algorithm (Xu, Jordan, & Hinton 1995), by introducing a discount factor. We show that the on-line EM algorithm is equivalent to the batch EM algorithm if a specific scheduling of the discount factor is employed. In addition, we show that the on-line EM algorithm can be considered as a stochastic approximation method to find the maximum likelihood estimator. A new regularization method is proposed in order to deal with a singular input distribution. In order to manage dynamic environments, where the input-output distribution of data changes over time, unit manipulation mechanisms such as unit production, unit deletion, and unit division are also introduced based on probabilistic interpretation. Experimental results show that our approach is suitable for function approximation problems in dynamic environments. We also apply our on-line EM algorithm to robot dynamics problems and compare our algorithm with the mixtures-of-experts family.
Correctness of Local Probability Propagation in Graphical Models with Loops
Authors: Weiss Yair
Published: July 2002

Graphical models, such as Bayesian networks and Markov networks, represent joint distributions over a set of variables by means of a graph. When the graph is singly connected, local propagation rules of the sort proposed by Pearl (1988) are guaranteed to converge to the correct posterior probabilities. Recently a number of researchers have empirically demonstrated good performance of these same local propagation schemes on graphs with loops, but a theoretical understanding of this performance has yet to be achieved.

For graphical models with a single loop, we derive an analytical relationship between the probabilities computed using local propagation and the correct marginals. Using this relationship we show a category of graphical models with loops for which local propagation gives rise to provably optimal maximum a posteriori assignments (although the computed marginals will be incorrect). We also show how nodes can use local information in the messages they receive in order to correct their computed marginals.

We discuss how these results can be extended to graphical models with multiple loops and show simulation results suggesting that some properties of propagation on single-loop graphs may hold for a larger class of graphs. Specifically we discuss the implication of our results for understanding a class of recently proposed error-correcting codes known as turbo codes.
Localist Attractor Networks
Authors: Zemel Richard S. , Mozer Michael C.
Published: July 2002

Attractor networks, which map an input space to a discrete output space, are useful for pattern completion—cleaning up noisy or missing input features. However, designing a net to have a given set of attractors is notoriously tricky; training procedures are CPU intensive and often produce spurious attractors and ill-conditioned attractor basins. These difficulties occur because each connection in the network participates in the encoding of multiple attractors. We describe an alternative formulation of attractor networks in which the encoding of knowledge is local, not distributed. Although localist attractor networks have similar dynamics to their distributed counterparts, they are much easier to work with and interpret. We propose a statistical formulation of localist attractor net dynamics, which yields a convergence proof and a mathematical interpretation of model parameters. We present simulation experiments that explore the behavior of localist attractor networks, showing that they yield few spurious attractors, and they readily exhibit two desirable properties of psychological and neurobiological models: priming (faster convergence to an attractor if the attractor has been recently visited) and gang effects (in which the presence of an attractor enhances the attractor basins of neighboring attractors).
Subspace Information Criterion for Model Selection
Authors: Sugiyama Masashi , Ogawa Hidemitsu
Published: July 2002

The problem of model selection is considerably important for acquiring higher levels of generalization capability in supervised learning. In this article, we propose a new criterion for model selection, the subspace information criterion (SIC), which is a generalization of Mallows's CL. It is assumed that the learning target function belongs to a specified functional Hilbert space and the generalization error is defined as the Hilbert space squared norm of the difference between the learning result function and target function. SIC gives an unbiased estimate of the generalization error so defined. SIC assumes the availability of an unbiased estimate of the target function and the noise covariance matrix, which are generally unknown. A practical calculation method of SIC for least-mean-squares learning is provided under the assumption that the dimension of the Hilbert space is less than the number of training examples. Finally, computer simulations in two examples show that SIC works well even when the number of training examples is small.
Topographic Independent Component Analysis
Authors: Hyvärinen Aapo , Hoyer Patrik O. , Inki Mika
Published: July 2002

In ordinary independent component analysis, the components are assumed to be completely independent, and they do not necessarily have any meaningful order relationships. In practice, however, the estimated “independent” components are often not at all independent. We propose that this residual dependence structure could be used to define a topo-graphic order for the components. In particular, a distance between two components could be defined using their higher-order correlations, and this distance could be used to create a topographic representation. Thus, we obtain a linear decomposition into approximately independent components, where the dependence of two components is approximated by the proximity of the components in the topographic representation.
Predictability, Complexity, and Learning
Authors: Bialek William , Nemenman Ilya , Tishby Naftali
Published: July 2002

We define predictive information Ipred(T) as the mutual information between the past and the future of a time series. Three qualitatively different behaviors are found in the limit of large observation times T: Ipred(T) can remain finite, grow logarithmically, or grow as a fractional power law. If the time series allows us to learn a model with a finite number of parameters, then Ipred(T) grows logarithmically with a coefficient that counts the dimensionality of the model space. In contrast, power-law growth is associated, for example, with the learning of infinite parameter (or non-parametric) models such as continuous functions with smoothness constraints. There are connections between the predictive information and measures of complexity that have been defined both in learning theory and the analysis of physical systems through statistical mechanics and dynamical systems theory. Furthermore, in the same way that entropy provides the unique measure of available information consistent with some simple and plausible conditions, we argue that the divergent part of Ipred(T) provides the unique measure for the complexity of dynamics underlying a time series. Finally, we discuss how these ideas may be useful in problems in physics, statistics, and biology.
Ion Channel Stochasticity May Be Critical in Determining the Reliability and Precision of Spike Timing
Authors: Schneidman Elad , Freedman Barry , Segev Idan
Published: July 2002

The firing reliability and precision of an isopotential membrane patch consisting of a realistically large number of ion channels is investigated using a stochastic Hodgkin-Huxley (HH) model. In sharp contrast to the deterministic HH model, the biophysically inspired stochastic model reproduces qualitatively the different reliability and precision characteristics of spike firing in response to DC and fluctuating current input in neocortical neurons, as reported by Mainen & Sejnowski (1995). For DC inputs, spike timing is highly unreliable; the reliability and precision are significantly increased for fluctuating current input. This behavior is critically determined by the relatively small number of excitable channels that are opened near threshold for spike firing rather than by the total number of channels that exist in the membrane patch. Channel fluctuations, together with the inherent bistability in the HH equations, give rise to three additional experimentally observed phenomena: subthreshold oscillations in the membrane voltage for DC input, “spontaneous” spikes for subthreshold inputs, and “missing” spikes for suprathreshold inputs. We suggest that the noise inherent in the operation of ion channels enables neurons to act as “smart” encoders. Slowly varying, uncorrelated inputs are coded with low reliability and accuracy and, hence, the information about such inputs is encoded almost exclusively by the spike rate. On the other hand, correlated presynaptic activity produces sharp fluctuations in the input to the postsynaptic cell, which are then encoded with high reliability and accuracy. In this case, information about the input exists in the exact timing of the spikes. We conclude that channel stochasticity should be considered in realistic models of neurons.
Learning to Design Synergetic Computers with an Extended Symmetric Diffusion Network
Authors: Okuhara Koji , Osaki Shunji , Kijima Masaaki
Published: July 2002

This article proposes an extended symmetric diffusion network that is applied to the design of synergetic computers. The state of a synergetic computer is translated to that of order parameters whose dynamics is described by a stochastic differential equation. The order parameter converges to the Boltzmann distribution, under some condition on the drift term, derived by the Fokker-Planck equation. The network can learn the dynamics of the order parameters from a nonlinear potential. This property is necessary to design the coefficient values of the synergetic computer. We propose a searching function for the image processing executed by the synergetic computer. It is shown that the image processing with the searching function is superior to the usual image-associative function of synergetic computation. The proposed network can be related, as a special case, to the discrete-state Boltzmann machine by some transformation. Finally, the extended symmetric diffusion network is applied to the estimation problem of an entire density function, as well as the proposed searching function for the image processing.
On Cross Validation for Model Selection
Authors: Rivals Isabelle , Personnaz Léon
Published: July 2002

In response to Zhu and Rower (1996), a recent communication (Goutte, 1997) established that leave-one-out cross validation is not subject to the “no-free-lunch” criticism. Despite this optimistic conclusion, we show here that cross validation has very poor performances for the selection of linear models as compared to classic statistical tests. We conclude that the statistical tests are preferable to cross validation for linear as well as for nonlinear model selection.
A Unifying Review of Linear Gaussian Models
Authors: Roweis Sam , Ghahramani Zoubin
Published: July 2002

Factor analysis, principal component analysis, mixtures of gaussian clusters, vector quantization, Kalman filter models, and hidden Markov models can all be unified as variations of unsupervised learning under a single basic generative model. This is achieved by collecting together disparate observations and derivations made by many previous authors and introducing a new way of linking discrete and continuous state models using a simple nonlinearity. Through the use of other nonlinearities, we show how independent component analysis is also a variation of the same basic generative model. We show that factor analysis and mixtures of gaussians can be implemented in autoencoder neural networks and learned using squared error plus the same regularization term. We introduce a new model for static data, known as sensible principal component analysis, as well as a novel concept of spatially adaptive observation noise. We also review some of the literature involving global and local mixtures of the basic models and provide pseudocode for inference and learning for all the basic models.
Propagating Distributions Up Directed Acyclic Graphs
Authors: Baum Eric B. , Smith Warren D.
Published: July 2002

In a previous article, we considered game trees as graphical models. Adopting an evaluation function that returned a probability distribution over values likely to be taken at a given position, we described how to build a model of uncertainty and use it for utility-directed growth of the search tree and for deciding on a move after search was completed. In some games, such as chess and Othello, the same position can occur more than once, collapsing the game tree to a directed acyclic graph (DAG). This induces correlations among the distributions at sibling nodes. This article discusses some issues that arise in extending our algorithms to a DAG. We give a simply described algorithm for correctly propagating distributions up a game DAG, taking account of dependencies induced by the DAG structure. This algorithm is exponential time in the worst case. We prove that it is #P complete to propagate distributions up a game DAG correctly. We suggest how our exact propagation algorithm can yield a fast but inexact heuristic.
Welded to the Ladle: Steelbound and Non-Radicality in Community-Based Theatre
Authors: Brady Sara
Published: July 2002

When big steel left Bethlehem, Pennsylvania, thousands of workers were out of jobs. A community-based theatre project adapts Aeschylus's Prometheus Bound to recollect and deal with the situation. But is Bethlehem Steel off the hook?
Performing Exclusion and Resistance: Anti-Chinese League and Chee Kung Tong Parades in Territorial Arizona
Authors: Cheung Floyd
Published: July 2002

Both Euro-Americans and Chinese paraded to reinforce their tenuous authority in the liminal space of Territorial Arizona. Although most Chinese practiced strategies of avoidance on the city streets, many also paraded in Chee Kung Tong meeting halls invoking through their performance a palimpsest of legendary geographies and heroic memories.
Shadowtrack: A Novel Tracking System Based on Spreadspectrum Spatio-Temporal Illumination
Authors: Palovuori Karri T. , Vanhala Jukka J. , Kivikoski Markku A.
Published: July 2002

This paper presents a novel tracking system combining the advantages of light-beam scanning and spread-spectrum techniques. Tracking is performed by scanning the tracking volume with several unique light patterns and detecting the variations in illumination at the tracked points. Due to the low correlation of the patterns, their phases can be individually detected and the absolute position of the detection point calculated. The light patterns can be produced with simple lamps using rotating shadow masks, yielding greater power and range while being safer and of lower cost than comparable lasers. The use of spread-spectrum sequences in the patterns makes the detection insensitive towards external or cross-coupled optical noise. A simple prototype system is demonstrated to be capable of an angular tracking accuracy of 2 mrad with a range of several meters. The limitations of the method together with some unconventional applications and modifications of the system are discussed.
Using Presence Questionnaires in Reality
Authors: Usoh Martin , Catena Ernest , Arman Sima , Slater Mel
Published: July 2002

A between-group experiment was carried out to assess whether two different presence questionnaires can distinguish between real and virtual experiences. One group of ten subjects searched for a box in a real office environment. A second group of ten subjects carried out the same task in a virtual environment that simulated the same office. Immediately after their experience, subjects were given two different presence questionnaires in randomized order: the Witmer and Singer Presence (WS), and the questionnaire developed by Slater, Usoh, and Steed (SUS). The paper argues that questionnaires should be able to pass a “reality test” whereby under current conditions the presence scores should be higher for real experiences than for virtual ones. Nevertheless, only the SUS had a marginally higher mean score for the real compared to the virtual, and there was no significant difference at all between the WS mean scores. It is concluded that, although such questionnaires may be useful when all subjects experience the same type of environment, their utility is doubtful for the comparison of experiences across environments, such as immersive virtual compared to real, or desktop compared to immersive virtual.
Equilibrium Theory Revisited: Mutual Gaze and Personal Space in Virtual Environments
Authors: Bailenson Jeremy N. , Blascovich Jim , Beall Andrew C. , Loomis Jack M.
Published: July 2002

During the last half of the twentieth century, psychologists and anthropologists have studied proxemics, or spacing behavior, among people in many contexts. As we enter the twenty-first century, immersive virtual environment technology promises new experimental venues in which researchers can study proxemics. Immersive virtual environments provide realistic and compelling experimental settings without sacrificing experimental control. The experiment reported here tested Argyle and Dean's (1965) equilibrium theory's specification of an inverse relationship between mutual gaze, a nonverbal cue signaling intimacy, and interpersonal distance. Participants were immersed in a three-dimensional virtual room in which a virtual human representation (that is, an embodied agent) stood. Under the guise of a memory task, participants walked towards and around the agent. Distance between the participant and agent was tracked automatically via our immersive virtual environment system. All participants maintained more space around agents than they did around similarly sized and shaped but nonhuman-like objects. Female participants maintained more interpersonal distance between themselves and agents who engaged them in eye contact (that is, mutual gaze behavior) than between themselves and agents who did not engage them in eye contact, whereas male participants did not. Implications are discussed for the study of proxemics via immersive virtual environment technology, as well as the design of virtual environments and virtual humans.
Presence as Being-in-the-World
Authors: Zahorik Pavel , Jenison Rick L.
Published: July 2002

An alternative view of presence is introduced based on existential philosophy and ecological psychology. This view favors a Heideggerian/Gibsonian metaphysic over the more conventional rationalistic orientation. In this alternative view, notions of subjective presence and objective presence no longer exist. Presence is instead tied to one's successfully supported action in the environment, this environment being either virtual or real. The coupling between perception and action is crucial for determining the extent to which actions are successfully supported. It is argued that this alternative view provides needed guidance and simplification for the evaluation of presence.