bluuebunny/crossref_metadata_2025 huggingface dataset:
Importance Measures of Multi-State Components in Multi-State Systems
Authors: Zio Enrico , Podofillini Luca
Published: September 2003

In system engineering a practical and difficult problem is the identification of those components that mostly influence the system behaviour with respect to safety and reliability. In this regard, the information provided by importance measures gives useful insights for the safe and efficient operation of the system.

Importance measures have received attention since the early times of risk and reliability analysis and have been defined in several ways for binary components in binary systems. Yet, there are applications for which a multi-state modelling of components and systems is required. This is the case of manufacturing production lines and power generation systems in which the components and the overall systems can operate at different, discrete, levels of performance so that the output provided is a fraction of the nominal design capacity. A similar situation occurs in transportation systems. In the limit, there is the case of systems whose performances are characterized in terms of an infinite set of continuous states. These are, for example, the passive safety systems whose utilization is becoming more and more significant in the advanced and innovative concepts of nuclear reactor design.

In this paper, the definitions of the most frequently used classical importance measures are generalized to multi-state systems constituted by multi-state components. The extensions introduced characterize the importance of a component achieving a given level of performance with respect to the overall multi-state system unavailability and performance. The informative content provided by the introduced measures is illustrated on a simple multi-state system.
Zero-One Law for the Non-Availability of Multistate Repairable Systems
Authors: Paroissin Christian , Ycart Bernard
Published: September 2003

In a monotone system whose failure depends on a large number of independent components, the non-availability should increase abruptly over a relatively short interval of time. Our first step is a reliability interpretation of a result of Friedgut and Kalai.1 Then we prove a zero-one law which is more adapted in a reliability context. In the last section some multistate extensions of classical models are considered as examples.
Preventive Maintenance of Multi-State System with Phase-Type Failure Time Distribution and Non-Zero Inspection Time
Authors: Chen Dongyan , Cao Yonghuan , Trivedi Kishor S. , Hong Yiguang
Published: September 2003

Preventive maintenance is applied to improve the system availability or decrease the operational cost. This paper addresses the optimal preventive maintenance problem for multi-state deteriorating systems, where the system experiences multiple stages of performance degradation before it fails. We consider a general case where the inspection and repair time are generally distributed. The threshold type maintenance policy is employed for preventive minor maintenance and preventive major maintenance, where minor or major maintenance is carried out when the system deterioration stage is found to be larger than certain thresholds. The mathematical model of the system is set up by means of a Markov regenerative process (MRGP). With this formulation, the system steady-state probabilities under consideration are computed.
Performance Evaluation of Decreasing Multi-State Consecutive-k-out-of-n: G Systems
Authors: Zuo Ming J. , Fang Zhide , Huang Jinsheng , Xu Xiaojian
Published: September 2003

In the binary context, a consecutive-k-out-of-n: G system works if and only if at least k consecutive components are working. In the multi-state context, a consecutive-k-out-of-n: G system is in state j or above (j = 1,2,…,M) if and only if at least kl consecutive components are in state l or above for all l (1 ≤ l ≤ j). In this paper, we use minimal path vectors to evaluate the system state distribution. When M = 3, a recursive formula is provided for evaluating the system state distribution. When M ≥ 4, an algorithm is provided to bound the system state distribution. These bounds are sharper than those reported in the literature.
Geometric Stiffness of Space Frames Using Symbolic Algebra
Authors: Levy Robert , Lin Cheng-Wei , Gal Erez , Yang Yeong-Bin
Published: September 2003

This paper is concerned with the derivation of the geometric stiffness matrix for space frames. Symbolic algebra is used to calculate the gradient of the member force vector that defines, in global coordinates, the geometric stiffness matrix. Members of solid cross-sections with no warping are considered. The independent nodal variables are the common position coordinates of the member ends. An additional independent variable, which cannot be related to the position coordinates, is the angle of twist at one end of each member. Since the angle of twist is defined locally, its effect on the stiffness matrix is found separately and then transformed to the global coordinates. The advantages of the present approach are its explicitness in derivation and clear physical insight. Finally, the geometric stiffness matrix is implanted into an existing 3D nonlinear frame analysis program. For the analytical, numerical and experimental benchmark examples studied, the present results appear to be in good agreement with the results available in the literature.
Comparison of Energy Requirements for Classical and Quantum Information Processing
Authors: Gea-Banacloche Julio , Kish Laszlo B.
Published: September 2003

By considering the energy requirements of quantum and classical computers we propose a criterion to separate the classical from the quantum regime and show that the classical scaling laws are much more favorable for conventional, general purpose computation.
Averaging Principle for Stochastic Perturbations of Multifrequency Systems
Authors: Freidlin M. I. , Wentzell A. D.
Published: September 2003

We consider the averaging principle for deterministic and stochastic perturbations of multidimensional dynamical systems for which coordinates can be introduced in such a way that the "fast" coordinates change in a torus (for Hamiltonian systems, "action-angle coordinates"). Stochastic perturbations of the white-noise type are considered. Our main assumption is that the set of action values for which the frequencies of the motion on corresponding tori are rationally dependent (and so the motion reduces to a torus of smaller dimension) has Lebesgue measure zero. Our results about stochastic perturbations imply some new results for averaging of purely deterministic perturbations.
Stochastic Averaging Near a Homoclinic Orbit with Multiplicative Noise
Authors: Sowers Richard B.
Published: September 2003

We consider a randomly perturbed two-dimensional Hamiltonian dynamical system containing a homoclinic orbit. The noise is multiplicative in the position variable. We prove a result similar to the one of Freidlin and Weber; this result states that as the noise becomes smaller, a graph-valued Markov process characterizes the limiting behavior. Our analysis of the glueing conditions hinges upon a coordinate transformation introduced by Khasminskii and a perturbed test function methodology. We find that the glueing conditions exactly correspond to the solvability of a linear equation involving coupled Neumann-to-Dirichlet operators.
A Law of Large Numbers for Rescaled Random Difference Equations
Authors: Burton Robert M. , Dehling Herold G. , Rösler Uwe
Published: September 2003

We study the behavior of stochastic processes defined as an iterated function system [Formula: see text] with initial value X0= x0and a stationary ergodic input signal (Un)n≥0for small values of the parameter a. We obtain almost sure convergence of the path to the solution of the corresponding deterministic dynamical system defined by [Formula: see text], where F(y) = E(f(y,U)). The results have applications in the study of neural network learning algorithms.
Attractors for the Stochastic 3D Navier–Stokes Equations
Authors: Marín-Rubio Pedro , Robinson James C.
Published: September 2003

In a 1997 paper, Ball defined a generalised semiflow as a means to consider the solutions of equations without (or not known to possess) the property of uniqueness. In particular he used this to show that the 3D Navier–Stokes equations have a global attractor provided that all weak solutions are continuous from (0, ∞) into L2. In this paper we adapt his framework to treat stochastic equations: we introduce a notion of a stochastic generalised semiflow, and then show a similar result to Ball's concerning the attractor of the stochastic 3D Navier–Stokes equations with additive white noise.
The Application of the Wavelet Transform to Polysomnographic Signals
Authors: MacCallum M. , Almaini A. E. A.
Published: September 2003

Polysomnographic (sleep) signals are recorded from patients exhibiting symptoms of a suspected sleep disorder such as Obstructive Sleep Apnoea (OSA). These non-stationary signals are characterised by having both quantitative information in the frequency domain and rich, dynamic data in the time domain. The collected data is subsequently analysed by skilled visual evaluation to determine whether arousals are present, an approach which is both time-consuming and subjective. This paper presents a wavelet-based methodology which seeks to alleviate some of the problems of the above method by providing: (a) an automated mechanism by which the appropriate stage of sleep for disorder observation may be extracted from the composite electroencephalograph (EEG) data set and (b) an ensuing technique to assist in the diagnosis of full arousal by correlation of wavelet-extracted information from a number of specific patient data sources (e.g. pulse oximetry, electromyogram [EMG] etc.).
Computationally Efficient Atomic Representations for Nonstationary Stochastic Processes
Authors: Capobianco Enrico
Published: September 2003

Function approximation methods based on frames or other overcomplete dictionaries of approximating functions offer advantages over the orthogonal schemes due to the fact that the associated redundancy may lead to better de-noising and reconstruction power. Wavelet packets represent special wavelet frames; they combine overcompleteness with high time-frequency localization power through an optimal frequency-then-time segmentation. Compared to cosine packets, which enable optimal adaptation through time-then-frequency segmentation, wavelet packets show a different time-frequency resolution trade-off that might be useful for analyzing some kinds of non-stationary phenomena. We study the properties of covariance non-stationary stochastic processes whose realizations are observed at very high frequencies; the data are supplied by time series of a stock market return index. For these complex processes the effectiveness of wavelet and cosine packets is explored by implementing entropic optimization, greedy approximation techniques and dimension reduction methods.
Performance of Informative Wavelets for Classification and Diagnosis of Machine Faults
Authors: Ahmadi H. , Dumont G. , Sassani F. , Tafreshi R.
Published: September 2003

This paper deals with an application of wavelets for feature extraction and classification of machine faults in a real-world machine data analysis environment. We have utilized informative wavelet algorithm to generate wavelets and subsequent coefficients that are used as feature variables for classification and diagnosis of machine faults. Informative wavelets are classes of functions generated from a given analyzing wavelet in a wavelet packet decomposition structure in which for the selection of best wavelets, concepts from information theory, i.e. mutual information and entropy are utilized. Training data are used to construct probability distributions required for the computation of the entropy and mutual information. In our data analysis, we have used machine data acquired from a single cylinder engine under a series of induced faults in a test environment. The objective of the experiment was to evaluate the performance of the informative wavelet algorithm for the accuracy of classification results using a real-world machine data and to examine to what extent the results were influenced by different analyzing wavelets chosen for data analysis. Accuracy of classification results as related to the correlation structure of the coefficients is also discussed in the paper.
Image Enhancement of Historical Documents Using Directional Wavelet
Authors: Wang Qian , Li Lida , Tan Chew Lim , Xia Tao
Published: September 2003

This paper proposes a novel algorithm to clean up a large collection of historical handwritten documents kept in the National Archives of Singapore. Due to the seepage of ink over long period of storage, the front page of each document has been severely marred by the reverse side writing. Earlier attempts have been made to match both sides of a page to identify the offending strokes originating from the back so as to eliminate them with the aid of a wavelet transform. Perfect matching, however, is difficult due to document skews, differing resolutions, inadvertently missing out reverse side and warped pages during image capture. A new approach is now proposed to do away with double side mapping by using a directional wavelet transform that is able to distinguish the foreground and reverse side strokes much better than the conventional wavelet transform. Experiments have shown that the method indeed enhances the readability of each document significantly after the directional wavelet operation without the need for mapping with its reverse side.
Wavelet Based Method for an Analysis of Jitter in Telecommunication Signals
Authors: Borgosz Jan , Cyganek Bogusław
Published: September 2003

This article describes a new method of the measure and analysis of the jitter phenomenon. Presented analysis is focused on the case of the telecommunication systems, but can be easily extended to other systems. This research is a continuation of the earlier work on the phase noise and jitter measurement systems. Method shown in this paper does not require generation of the reference clock in contrast to classic methods. It is rather based on the combination of the wavelet analysis and relational pattern recognition. This new approach to the jitter measurement problem gives very interesting results which are worth for further exploration. Authors give not only proposal but show measurement algorithm, which allows to estimate the jitter parameters by measure relation between the jitter wavelet base functions. In the background comparison of a classic and wavelet approaches to the jitter measurement problem is presented. In addition, such topics like the wavelet type, its order, as well as calibrating methods are also discussed.
Efficient and Adaptive Rotation Invariant Wavelet Transform
Authors: Pun Chi-Man
Published: September 2003

It is well known that the sensitivity to translations and orientations is a major drawback in 2D discrete wavelet transform (DWT). In this paper, we have proposed an effective scheme for rotation invariant adaptive wavelet packet transform. During decomposition, the wavelet coefficients are obtained by applying a polar transform (PT) followed by a row-shift invariant wavelet packet decomposition (RSIWPD). In the first stage, the polar transform generates a row-shifted image and is adaptive to the image size to achieve complete and minimum sampling rate. In the second stage, the RSIWPD is applied to the row-shifted image to generate rotation invariant but over completed subbands of wavelet coefficients. In order to reduce the redundancy and computational complexity, we adaptively select some subbands to decompose and form a best basis representation with minimal information cost with respect to an appropriate information cost function. With this best basis representation, the original image can be reconstructed easily by applying a row-shift invariant wavelet packet reconstruction (RSIWPR) followed by an inverse polar transform (IPT). In the experiments, we study the application of this representation for texture classification and achieve 96.5% classification accuracy.
Thresholding Wavelet Networks for Signal Classification
Authors: Pah Nemuel D. , Kumar Dinesh Kant
Published: September 2003

This paper reports a new signal classification tool, a modified wavelet network called Thresholding Wavelet Networks (TWN). The network is designed for the purposes of classifying signals. The philosophy of the technique is that often the difference between signals may not lie in the spectral or temporal region where the signal strength is high. Unlike other wavelet networks, this network does not concentrate necessarily on the high-energy region of the input signals. The network iteratively identifies the suitable wavelet coefficients (scale and translation) that best differentiate the different signals provided during training, irrespective of the ability of these coefficients to represent the signals. The network is not limited to the changes in temporal location of the signal identifiers. This paper also reports the testing of the network using simulated signals.
Dissecting Contributions of Prefrontal Cortex and Fusiform Face Area to Face Working Memory
Authors: Druzgal T. Jason , D'Esposito Mark
Published: September 2003

Interactions between prefrontal cortex (PFC) and stimulusspecific visual cortical association areas are hypothesized to mediate visual working memory in behaving monkeys. To clarify the roles for homologous regions in humans, event-related fMRI was used to assess neural activity in PFC and fusiform face area (FFA) of subjects performing a delay-recognition task for faces. In both PFC and FFA, activity increased parametrically with memory load during encoding and maintenance of face stimuli, despite quantitative differences in the magnitude of activation. Moreover, timing differences in PFC and FFA activation during memory encoding and retrieval implied a context dependence in the flow of neural information. These results support existing neurophysiological models of visual working memory developed in the nonhuman primate.
Cognitive Control Mechanisms Revealed by ERP and fMRI: Evidence from Repeated Task-Switching
Authors: Swainson R. , Cunnington R. , Jackson G. M. , Rorden C. , Peters A. M. , Morris P. G. , Jackson S. R.
Published: September 2003

We investigated the extent to which a common neural mechanism is involved in task set-switching and response withholding, factors that are frequently confounded in taskswitching and go/no-go paradigms. Subjects' brain activity was measured using event-related electrical potentials (ERPs) and event-related functional MRI (fMRI) neuroimaging in separate studies using the same cognitive paradigm. Subjects made compatible left/right keypress responses to left/right arrow stimuli of 1000 msec duration; they switched every two trials between responding at stimulus onset (GO task—green arrows) and stimulus offset (WAIT task—red arrows). Withholding an immediate response (WAIT vs. GO) elicited an enhancement of the frontal N2 ERP and lateral PFC activation of the right hemisphere, both previously associated with the “nogo” response, but only on switch trials. Task-switching (switch vs. nonswitch) was associated with frontal N2 amplification and right hemisphere ventrolateral PFC activation, but only for the WAIT task. The anterior cingulate cortex (ACC) was the only brain region to be activated for both types of task switch, but this activation was located more rostrally for the WAIT than for the GO switch trials. We conclude that the frontal N2 ERP and lateral PFC activation are not markers for withholding an immediate response or switching tasks per se, but are associated with switching into a response-suppression mode. Different regions within the ACC may be involved in two processes integral to task-switching: processing response conflict (rostral ACC) and overcoming prior response suppression (caudal ACC).
Perceiving Biological Motion: Dissociating Visible Speech from Walking
Authors: Santi Andrea , Servos Philip , Vatikiotis-Bateson Eric , Kuratate Takaaki , Munhall Kevin
Published: September 2003

Neuropsychological research suggests that the neural system underlying visible speech on the basis of kinematics is distinct from the system underlying visible speech of static images of the face and identifying whole-body actions from kinematics alone. Functional magnetic resonance imaging was used to identify the neural systems underlying point-light visible speech, as well as perception of a walking/jumping point-light body, to determine if they are independent. Although both point-light stimuli produced overlapping activation in the right middle occipital gyrus encompassing area KO and the right inferior temporal gyrus, they also activated distinct areas. Perception of walking biological motion activated a medial occipital area along the lingual gyrus close to the cuneus border, and the ventromedial frontal cortex, neither of which was activated by visible speech biological motion. In contrast, perception of visible speech biological motion activated right V5 and a network of motor-related areas (Broca's area, PM, M1, and supplementary motor area (SMA)), none of which were activated by walking biological motion. Many of the areas activated by seeing visible speech biological motion are similar to those activated while speechreading from an actual face, with the exception of M1 and medial SMA. The motor-related areas found to be active during point-light visible speech are consistent with recent work characterizing the human “mirror” system (Rizzolatti, Fadiga, Gallese, & Fogassi, 1996).
The Effects of Gender on the Neural Substrates of Pitch Memory
Authors: Gaab Nadine , Keenan Julian Paul , Schlaug Gottfried
Published: September 2003

Imaging studies have indicated that males and females differ anatomically in brain regions thought to underlie language functions. Functional studies have corroborated this difference by showing gender differences in terms of language processing with females relying on less lateralized processing strategies than males. Gender differences in musical functions might show similar differences in functional asymmetries, although no detailed study has been performed. The current study employed a pitch memory task while acquiring functional magnetic resonance images to investigate possible differences in hemispheric processing between males and females. Gender differences were found in the time course of activation (during the first four imaging time points after the end of the auditory stimulus—“perceptual phase”—and the subsequent three imaging time points after the end of the auditory stimulus—“memory phase”) in both anterior and posterior perisylvian regions. Male subjects had greater lateralized activations (left > right) in anterior and posterior perisylvian regions during the “perceptual” as well as during the “memory” phase. There was a trend for males to have more cerebellar activation than females. Females showed more prominently posterior cingulate/retrosplenial cortex activation compared to males. Although activation patterns differed, there was no difference in the behavioral performance between both genders. These data indicate that similar to language studies, males rely more on left lateralized hemispheric processing even for basic pitch tasks.
A Computational Model of Prefrontal Control in Free Recall: Strategic Memory Use in the California Verbal Learning Task
Authors: Becker Suzanna , Lim Jean
Published: September 2003

Several decades of research into the function of the frontal lobes in brain-damaged patients, and more recently in intact individuals using function brain imaging, has delineated the complex executive functions of the frontal cortex. And yet, the mechanisms by which the brain achieves these functions remain poorly understood. Here, we present a computational model of the role of the prefrontal cortex (PFC) in controlled memory use that may help to shed light on the mechanisms underlying one aspect of frontal control: the development and deployment of recall strategies. The model accounts for interactions between the PFC and medial temporal lobe in strategic memory use. The PFC self-organizes its own mnemonic codes using internally derived performance measures. These mnemonic codes serve as retrieval cues by biasing retrieval in the medial temporal lobe memory system. We present data from three simulation experiments that demonstrate strategic encoding and retrieval in the free recall of categorized lists of words. Experiment 1 compares the performance of the model with two control networks to evaluate the contribution of various components of the model. Experiment 2 compares the performance of normal and frontally lesioned models to data from several studies using frontally intact and frontally lesioned individuals, as well as normal, healthy individuals under conditions of divided attention. Experiment 3 compares the model's performance on the recall of blocked and unblocked categorized lists of words to data from Stuss et al. (1994) for individuals with control and frontal lobe lesions. Overall, our model captures a number of aspects of human performance on free recall tasks: an increase in total words recalled and in semantic clustering scores across trials, superiority on blocked lists of related items compared to unblocked lists of related items, and similar patterns of performance across trials in the normal and frontally lesioned models, with poorer overall performance of the lesioned models on all measures. The model also has a number of shortcomings, in light of which we suggest extensions to the model that would enable more sophisticated forms of strategic control.
The Neural Substrates of Visual Implicit Memory: Do the Two Hemispheres Play Different Roles?
Authors: Kroll N. E. A. , Yonelinas A. P. , Kishiyama M. M. , Baynes K. , Knight R. T. , Gazzaniga M. S.
Published: September 2003

Identification of visually presented words is facilitated by implicit memory, or visual priming, for past visual experiences with those words. There is disagreement over the neuroanatomical substrates of this form of implicit memory. Several studies have suggested that this form of priming relies on a visual word-form system localized in the right occipital lobe, whereas other studies have indicated that both hemispheres are equally involved. The discrepancies may be related to the types of priming tasks that have been used because the former studies have relied primarily on word-stem completion tasks and the latter on tasks like word-fragment completion. The present experiments compared word-fragment and word-stem measurements of visual implicit memory in patients with right occipital lobe lesions and patients with complete callosotomies. The patients showed normal visual implicit memory on fragment completion tests, but essentially no visual priming on standard stem completion tests. However, when we used a set of word stems that had only one correct solution for each test item, as was true of the items in the fragment completion tests, the patients showed normal priming effects. The results indicate that visual implicit memory for words is not solely dependent upon the right hemisphere, rather it reflects changes in processing efficiency in bilateral visual regions involved in the initial processing of the items. However, under conditions of high lexical competition (i.e., multiple completion word stems), the lexical processes, which are dominant in the left hemisphere, overshadow the visual priming supported by the left hemisphere.
Retrieval Orientation and the Control of Recollection
Authors: Herron Jane E. , Rugg Michael D.
Published: September 2003

Event-related potentials (ERPs) were employed to investigate whether recognition test items are processed differently according to whether they are used to probe memory for previously studied words or pictures. In each of two study-test blocks, subjects encoded a mixed list of words and pictures, and then performed a recognition memory task with words as the test items. In one block, the requirement was to respond positively to test items corresponding to studied words, and to reject both new items and items corresponding to the studied pictures. In the other block, positive responses were made to test items corresponding to pictures, and items corresponding to words were classified along with the new items. ERPs elicited during the test phase by correctly classified new items differed according to whether words or pictures were the sought-for modality. This finding was interpreted as a neural correlate of the different retrieval orientations adopted when searching memory for words versus pictures. Relative to new items, correctly classified items studied in both target modalities elicited robust, positive-going “old/new” effects. When pictures were targets, test items corresponding to studied words also elicited large effects. By contrast, when words were targets, old/ new effects were absent for the items corresponding to studied pictures. These findings were interpreted as evidence that, in some circumstances, adoption of an appropriate retrieval orientation permits retrieval cues to be employed with a high degree of specificity.
The Role of Prefrontal Cortex in Verbal Episodic Memory: rTMS Evidence
Authors: Sandrini Marco , Cappa Stefano F. , Rossi Simone , Rossini Paolo M. , Miniussi Carlo
Published: September 2003

Long-term, episodic memory processing is supposed to involve the prefrontal cortex asymmetrically. Here we investigate the role of the dorsolateral prefrontal cortex (DLPFC) in encoding and retrieval of semantically related or unrelated word pairs. Subjects were required to perform a task consisting of two parts: a study phase (encoding), in which word pairs were presented, and a test phase (retrieval), during which stimuli previously presented had to be recognized among other stimuli. Consistently with our previous findings using pictures, repetitive transcranial magnetic stimulation (rTMS) had a significant impact on episodic memory. The performance was significantly disrupted when rTMS was applied to the left or right DLPFC during encoding, and to the right DLPFC in retrieval, but only for unrelated word pairs. These results indicate that the nature of the material to be remembered interacts with the encoding–retrieval DLPFC asymmetry; moreover, the crucial role of DLPFC is evident only for novel stimuli.
Shadows in the Brain
Authors: Castiello Umberto , Lusher Dean , Burton Carol , Disler Peter
Published: September 2003

The aims of the present study were to investigate whether the processing of an object shadow occurs implicitly, that is without conscious awareness, and where physically within the human brain shadows are processed. Here we present neurological evidence, obtained from studies of brain-injured patients with visual neglect, that shadows are implicitly processed and that this processing may take place within the temporal lobe. Neglect patients with lesions that do not involve the right temporal lobe were still able to process shadows to optimize object shape perception. In contrast, shadow processing was not found to be as efficient in neglect patients with lesions that involve the right temporal lobe.
Set Size Effects in the Macaque Striate Cortex
Authors: Landman Rogier , Spekreijse Henk , Lamme Victor A. F.
Published: September 2003

Attentive processing is often described as a competition for resources among stimuli by mutual suppression. This is supported by findings that activity in extrastriate cortex is suppressed when several stimuli are presented simultaneously, compared to a single stimulus. In this study, we randomly varied the number of simultaneously presented figures (set size) in an attention-demanding change detection task, while we recorded multiunit activity in striate cortex (V1) in monkeys. After figure–background segregation, activity was suppressed as set size increased. This effect was stronger and started earlier among cells stimulated by the background than those stimulated by the figures themselves. As a consequence, contextual modulation, a correlate of figure–background segregation, increased with set size, approximately 100 msec after its initial generation. The results indicate that suppression of responses under increasing attentional demands differentially affects figure and background responses in area V1.
Interplay between Syntax and Semantics during Sentence Comprehension: ERP Effects of Combining Syntactic and Semantic Violations
Authors: Hagoort Peter
Published: September 2003

This study investigated the effects of combined semantic and syntactic violations in relation to the effects of single semantic and single syntactic violations on language-related event-related brain potential (ERP) effects (N400 and P600/ SPS). Syntactic violations consisted of a mismatch in grammatical gender or number features of the definite article and the noun in sentence-internal or sentence-final noun phrases (NPs). Semantic violations consisted of semantically implausible adjective–noun combinations in the same NPs. Combined syntactic and semantic violations were a summation of these two respective violation types. ERPs were recorded while subjects read the sentences with the different types of violations and the correct control sentences. ERP effects were computed relative to ERPs elicited by the sentence-internal or sentence-final nouns. The size of the N400 effect to the semantic violation was increased by an additional syntactic violation (the syntactic boost). In contrast, the size of the P600/ SPS to the syntactic violation was not affected by an additional semantic violation. This suggests that in the absence of syntactic ambiguity, the assignment of syntactic structure is independent of semantic context. However, semantic integration is influenced by syntactic processing. In the sentence-final position, additional global processing consequences were obtained as a result of earlier violations in the sentence. The resulting increase in the N400 amplitude to sentence-final words was independent of the nature of the violation. A speeded anomaly detection task revealed that it takes substantially longer to detect semantic than syntactic anomalies. These results are discussed in relation to the latency and processing characteristics of the N400 and P600/SPS effects. Overall, the results reveal an asymmetry in the interplay between syntax and semantics during on-line sentence comprehension.
Electrophysiological Correlates of Age and Gender Perception on Human Faces
Authors: Mouchetant-Rostaing Y. , Giard M. H.
Published: September 2003

In a previous experiment using scalp event-related potentials (ERPs), we have described the neuroelectric activities associated with the processing of gender information on human faces (Mouchetant-Rostaing, Giard, Bentin, Aguera, & Pernier, 2000). Here we extend this study by examining the processing of age on faces using a similar experimental paradigm, and we compare age and gender processing. In one session, faces were of the same gender (women) and of one age range (young or old), to reduce gender and age processing. In a second session, faces of young and old women were randomly intermixed but age was irrelevant for the task, hence, age discrimination, if any, was assumed to be incidental. In the third and fourth sessions, faces had to be explicitly categorized according to their age or gender, respectively (intentional discrimination). Neither age nor gender processing affected the occipito-temporal N170 component often associated with the detection of physiognomic features and global structural encoding of faces. Rather, the three age and gender discrimination conditions induced similar fronto-central activities around 145–185 msec. In our previous experiment, this ERP pattern was also found for implicit and explicit categorization of gender from faces but not in a control condition manipulating hand stimuli (Mouchetant-Rostaing, Giard, Bentin, et al., 2000). Whatever their exact nature, these 145–185 msec effects therefore suggest, first, that similar mechanisms could be engaged in age and gender perception, and second, that age and gender may be implicitly processed irrespective of their relevance to the task, through somewhat specialized mechanisms. Additional ERP effects were found at early latencies (45–90 msec) in all three discrimination conditions, and around 200–400 msec during explicit age and gender discrimination. These effects have been previously found in control conditions manipulating nonfacial stimuli and may therefore be related to more general categorization processes.
How the Self Controls Its “Automatic Pilot” when Processing Subliminal Information
Authors: Jaśkowski Piotr , Skalska Blandyna , Verleger Rolf
Published: September 2003

Human performance may be primed by information not consciously available. Can such priming become so overwhelming that observers cannot help but act accordingly? In the present study, well-visible stimuli were preceded by whole series of unidentifiable stimuli. These series had strong, additive priming effects on behavior. However, their effect depended on the frequency with which they provided information conflicting to the visible main stimuli. Thus, effects of subliminal priming are under observers' strategic control, with the criterion presumably set as a function of the openly observable error frequency. Electrical brain potentials show that this criterion acts simultaneously at the level of visual discrimination of the primes and at motor activation evoked by the primes, thereby shielding observers from unwanted information.
Doubly Distributional Population Codes: Simultaneous Representation of Uncertainty and Multiplicity
Authors: Sahani Maneesh , Dayan Peter
Published: September 2003

Perceptual inference fundamentally involves uncertainty, arising from noise in sensation and the ill-posed nature of many perceptual problems. Accurate perception requires that this uncertainty be correctly represented, manipulated, and learned about. The choicessubjects makein various psychophysical experiments suggest that they do indeed take such uncertainty into account when making perceptual inferences, posing the question as to how uncertainty is represented in the activities of neuronal populations. Most theoretical investigations of population coding have ignored this issue altogether; the few existing proposals that address it do so in such a way that it is fatally conflated with another facet of perceptual problems that also needs correct handling: multiplicity (that is, the simultaneous presence of multiple distinct stimuli). We present and validate a more powerful proposal for the way that population activity may encode uncertainty, both distinctly from and simultaneously with multiplicity.
Firing Rate of the Noisy Quadratic Integrate-and-Fire Neuron
Authors: Brunel Nicolas , Latham Peter E.
Published: September 2003

We calculate the firing rate of the quadratic integrate-and-fire neuron in response to a colored noise input current. Such an input current is a good approximation to the noise due to the random bombardment of spikes, with the correlation time of the noise corresponding to the decay time of the synapses. The key parameter that determines the firing rate is the ratio of the correlation time of the colored noise, τs, to the neuronal time constant, τm. We calculate the firing rate exactly in two limits: when the ratio, τs/τm, goes to zero (white noise) and when it goes to infinity. The correction to the short correlation time limit is O(τs/τm), which is qualitatively different from that of the leaky integrate-and-fire neuron, where the correction is O(√τs/τm). The difference is due to the different boundary conditions of the probability density function of the membrane potential of the neuron at firing threshold. The correction to the long correlation time limit is O(τm/τs). By combining the short and long correlation time limits, we derive an expression that provides a good approximation to the firing rate over the whole range of τs/τm in the suprathreshold regime—that is, in a regime in which the average current is sufficient to make the cell fire. In the subthreshold regime, the expression breaks down somewhat when τs becomes large compared to τm.
Pattern Filtering for Detection of Neural Activity, with Examples from HVc Activity During Sleep in Zebra Finches
Authors: Chi Zhiyi , Rauske Peter L. , Margoliash Daniel
Published: September 2003

The detection of patterned spiking activity is important in the study of neural coding. A pattern filtering approach is developed for pattern detection under the framework of point processes, which offers flexibility in combining temporal details and firing rates. The detection combines multiple steps of filtering in a coarse-to-fine manner. Under some conditional Poisson assumptions on the spiking activity, each filtering step is equivalent to classifying by likelihood ratios all the data segments as targets or as background sequences. Unlike previous studies, where global surrogate data were used to evaluate the statistical significance of the detected patterns, a localizedp-test procedure is developed, which better accounts for firing modulation and nonstationarity in spiking activity. Common temporal structures of patterned activity are learned using an entropy-based alignment procedure, without relying on metrics or pair-wise alignment. Applications of pattern filtering to single, presumptive interneurons recorded in the nucleus HVc of zebra finch are illustrated. These demonstrate a match between the auditory-evoked response to playback of the individual bird's own song and spontaneous activity during sleep. Small temporal compression or expansion, or both, is required for optimal matching of spontaneous patterns to stimulus-evoked activity.
Synaptic Depression Leads to Nonmonotonic Frequency Dependence in the Coincidence Detector
Authors: Mikula Shawn , Niebur Ernst
Published: September 2003

In this letter, we extend our previous analytical results (Mikula & Niebur, 2003) for the coincidence detector by taking into account probabilistic frequency-dependent synaptic depression. We present a solution for the steady-state output rate of an ideal coincidence detector receiving an arbitrary number of input spike trains with identical binomial count distributions (which includes Poisson statistics as a special case) and identical arbitrary pairwise cross-correlations, from zero correlation (independent processes) to perfect correlation (identical processes). Synapses vary their efficacy probabilistically according to the observed depression mechanisms. Our results show that synaptic depression, if made sufficiently strong, will result in an inverted U-shaped curve for the output rate of a coincidence detector as a function of input rate. This leads to the counterintuitive prediction that higher presynaptic (input) rates may lead to lower postsynaptic (output) rates where the output rate may fall faster than the inverse of the input rate.
Probing Changes in Neural Interaction During Adaptation
Authors: Zhu Liqiang , Lai Ying-Cheng , Hoppensteadt Frank C. , He Jiping
Published: September 2003

A procedure is developed to probe the changes in the functional interactions among neurons in primary motor cortex of the monkey brain during adaptation. A monkey is trained to learn a new skill, moving its arm to reach a target under the influence of external perturbations. The spike trains of multiple neurons in the primary motor cortex are recorded simultaneously. We utilize the methodology of directed transfer function, derived from a class of linear stochastic models, to quantify the causal interactions between the neurons. We find that the coupling between the motor neurons tends to increase during the adaptation but return to the original level after the adaptation. Furthermore, there is evidence that adaptation tends to affect the topology of the neural network, despite the approximate conservation of the average coupling strength in the network before and after the adaptation.
Memory Encoding by Theta Phase Precession in the Hippocampal Network
Authors: Sato Naoyuki , Yamaguchi Yoko
Published: September 2003

Recent experimental evidence on spike-timing-dependent plasticity and on phase precession (i.e., the theta rhythm dependent firing of rat hippocampalcells) associates the contribution of phase precession to episodic memory. This article aims at clarifying the role of phase precession in memory storage. Computer simulations show that the memory storage in the behavioral timescale varies in timescale of the temporal sequence from half a second to several seconds. In contrast, the memory storage caused by traditional rate coding is restricted to the temporal sequence within 40 ms. During phase precession, memory storage of a single trial experience is possible, even in the presence of noise. It is therefore concluded that encoding by phase precession is appropriate for memory storage of the temporal sequence in the behavioral timescale.
A Computational Model as Neurodecoder Based on Synchronous Oscillation in the Visual Cortex
Authors: Songnian Zhao , Xiaoyun Xiong , Guozheng Yao , Zhi Fu
Published: September 2003

Based on synchronized responses of neuronal populations in the visual cortex to external stimuli, we proposed a computational model consisting primarily of a neuronal phase-locked loop (NPLL) and multiscaled operator. The former reveals the function of synchronous oscillations in the visual cortex. Regardless of which of these patterns of the spike trains may be an average firing-rate code, a spike-timing code, or a rate-time code, the NPLL can decode original visual information from neuronal spike trains modulated with patterns of external stimuli, because a voltage-controlled oscillator (VCO), which is included in the NPLL, can precisely track neuronal spike trains and instantaneous variations, that is, VCO can make a copy of an external stimulus pattern. The latter, however, describes multi-scaled properties of visual information processing, but not merely edge and contour detection. In this study, in which we combined NPLL with a multiscaled operator and maximum likelihood estimation, we proved that the model, as a neurodecoder, implements optimum algorithm decoding visual information from neuronal spike trains at the system level. At the same time, the model also obtains increasingly important supports, which come from a series of experimental results of neurobiology on stimulus-specific neuronal oscillations or synchronized responses of the neuronal population in the visual cortex. In addition, the problem of how to describe visual acuity and multiresolution of vision by wavelet transform is also discussed. The results indicate that the model provides a deeper understanding of the role of synchronized responses in decoding visual information.
Parameter Estimation of Sigmoid Superpositions: Dynamical System Approach
Authors: Tyukin Ivan , Leeuwen Cees van , Prokhorov Danil
Published: September 2003

Superposition of sigmoid function over a finite time interval is shown to be equivalent to the linear combination of the solutions of a linearly parameterized system of logistic differential equations. Due to the linearity with respect to the parameters of the system, it is possible to design an effective procedure for parameter adjustment. Stability properties of this procedure are analyzed.
On the Partitioning Capabilities of Feedforward Neural Networks with Sigmoid Nodes
Authors: Koutroumbas K.
Published: September 2003

In this letter, the capabilities of feedforward neural networks (FNNs) on the realization and approximation of functions of the form g: R1 → A, which partition the R1 space into polyhedral sets, each one being assigned to one out of the c classes of A, are investigated. More specifically, a constructive proof is given for the fact that FNNs consisting of nodes having sigmoid output functions are capable of approximating any function g with arbitrary accuracy. Also, the capabilities of FNNs consisting of nodes having the hard limiter as output function are reviewed. In both cases, the two-class as well as the multiclass cases are considered.