197,015 research outputs found

    Identification and bisection of temporal durations and tone frequencies: common models for temporal and nontemporal stimuli

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    Two experiments examined identification and bisection of tones varying in temporal duration (Experiment 1) or frequency (Experiment 2). Absolute identification of both durations and frequencies was influenced by prior stimuli and by stimulus distribution. Stimulus distribution influenced bisection for both stimulus types consistently, with more positively skewed distributions producing lower bisection points. The effect of distribution was greater when the ratio of the largest to smallest stimulus magnitude was greater. A simple mathematical model, temporal range frequency theory, was applied. It is concluded that (a) similar principles describe identification of temporal durations and other stimulus dimensions and (b) temporal bisection point shifts can be understood in terms of psychophysical principles independently developed in nontemporal domains, such as A. Parducci's (1965) range frequency theory

    Encoding of temporal probabilities in the human brain

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    Anticipating the timing of future events is a necessary precursor to preparing actions and allocating resources to sensory processing. This requires elapsed time to be represented in the brain and used to predict the temporal probability of upcoming events. While neuropsychological, imaging, magnetic stimulation studies, and single-unit recordings implicate the role of higher parietal and motor-related areas in temporal estimation, the role of earlier, purely sensory structures remains more controversial. Here we demonstrate that the temporal probability of expected visual events is encoded not by a single area but by a wide network that importantly includes neuronal populations at the very earliest cortical stages of visual processing. Moreover, we show that activity in those areas changes dynamically in a manner that closely accords with temporal expectations

    Multigranular spatio-temporal models: implementation challenges

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    Multiple granularities provide an essential support for extracting significant knowledge from spatio-temporal datasets at different levels of details. They enable to zoom-in and zoom-out spatio-temporal datasets, thus enhancing the data modelling exibility and improving the analysis of information. In this paper we investigate the implementation issues arising when a data model and a query language are enriched with spatio-temporal multigranularity. We introduce appropriate representations for space and time dimensions, granularities, granules, and multi-granular values. Finally, we discuss how multigranular spatio-temporal conversions affect data usability and how such important property may be guaranteed

    Different brain circuits underlie motor and perceptual representations of temporal intervals

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    In everyday life, temporal information is used for both perception and action, but whether these two functions reflect the operation of similar or different neural circuits is unclear. We used functional magnetic resonance imaging to investigate the neural correlates of processing temporal information when either a motor or a perceptual representation is used. Participants viewed two identical sequences of visual stimuli and used the information differently to perform either a temporal reproduction or a temporal estimation task. By comparing brain activity evoked by these tasks and control conditions, we explored commonalities and differences in brain areas involved in reproduction and estimation of temporal intervals. The basal ganglia and the cerebellum were commonly active in both temporal tasks, consistent with suggestions that perception and production of time are subserved by the same mechanisms. However, only in the reproduction task was activity observed in a wider cortical network including the right pre-SMA, left middle frontal gyrus, left premotor cortex, with a more reliable activity in the right inferior parietal cortex, left fusiform gyrus, and the right extrastriate visual area V5/MT. Our findings point to a role for the parietal cortex as an interface between sensory and motor processes and suggest that it may be a key node in translation of temporal information into action. Furthermore, we discuss the potential importance of the extrastriate cortex in processing visual time in the context of recent findings

    Imaging memory in temporal lobe epilepsy: predicting the effects of temporal lobe resection

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    Functional magnetic resonance imaging can demonstrate the functional anatomy of cognitive processes. In patients with refractory temporal lobe epilepsy, evaluation of preoperative verbal and visual memory function is important as anterior temporal lobe resections may result in material specific memory impairment, typically verbal memory decline following left and visual memory decline after right anterior temporal lobe resection. This study aimed to investigate reorganization of memory functions in temporal lobe epilepsy and to determine whether preoperative memory functional magnetic resonance imaging may predict memory changes following anterior temporal lobe resection. We studied 72 patients with unilateral medial temporal lobe epilepsy (41 left) and 20 healthy controls. A functional magnetic resonance imaging memory encoding paradigm for pictures, words and faces was used testing verbal and visual memory in a single scanning session on a 3T magnetic resonance imaging scanner. Fifty-four patients subsequently underwent left (29) or right (25) anterior temporal lobe resection. Verbal and design learning were assessed before and 4 months after surgery. Event-related functional magnetic resonance imaging analysis revealed that in left temporal lobe epilepsy, greater left hippocampal activation for word encoding correlated with better verbal memory. In right temporal lobe epilepsy, greater right hippocampal activation for face encoding correlated with better visual memory. In left temporal lobe epilepsy, greater left than right anterior hippocampal activation on word encoding correlated with greater verbal memory decline after left anterior temporal lobe resection, while greater left than right posterior hippocampal activation correlated with better postoperative verbal memory outcome. In right temporal lobe epilepsy, greater right than left anterior hippocampal functional magnetic resonance imaging activation on face encoding predicted greater visual memory decline after right anterior temporal lobe resection, while greater right than left posterior hippocampal activation correlated with better visual memory outcome. Stepwise linear regression identified asymmetry of activation for encoding words and faces in the ipsilateral anterior medial temporal lobe as strongest predictors for postoperative verbal and visual memory decline. Activation asymmetry, language lateralization and performance on preoperative neuropsychological tests predicted clinically significant verbal memory decline in all patients who underwent left anterior temporal lobe resection, but were less able to predict visual memory decline after right anterior temporal lobe resection. Preoperative memory functional magnetic resonance imaging was the strongest predictor of verbal and visual memory decline following anterior temporal lobe resection. Preoperatively, verbal and visual memory function utilized the damaged, ipsilateral hippocampus and also the contralateral hippocampus. Memory function in the ipsilateral posterior hippocampus may contribute to better preservation of memory after surgery

    Jeeg: Temporal Constraints for the Synchronization of Concurrent Objects

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    We introduce Jeeg, a dialect of Java based on a declarative replacement of the synchronization mechanisms of Java that results in a complete decoupling of the 'business' and the 'synchronization' code of classes. Synchronization constraints in Jeeg are expressed in a linear temporal logic which allows to effectively limit the occurrence of the inheritance anomaly that commonly affects concurrent object oriented languages. Jeeg is inspired by the current trend in aspect oriented languages. In a Jeeg program the sequential and concurrent aspects of object behaviors are decoupled: specified separately by the programmer these are then weaved together by the Jeeg compiler

    Universal Solutions in Temporal Data Exchange

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    During the past fifteen years, data exchange has been explored in depth and in a variety of different settings. Even though temporal databases constitute a mature area of research studied over several decades, the investigation of temporal data exchange was initiated only very recently. We analyze the properties of universal solutions in temporal data exchange with emphasis on the relationship between universal solutions in the context of concrete time and universal solutions in the context of abstract time. We show that challenges arise even in the setting in which the data exchange specifications involve a single temporal variable. After this, we identify settings, including data exchange settings that involve multiple temporal variables, in which these challenges can be overcome

    Temporal Considerations in DJ Mix Information Retrieval and Generation

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    Music is the art of arranging sounds in time so as to produce a continuous, unified, and evocative composition. Electronic dance music (EDM) is a collection of musical sub-genres produced using computers and electronic instruments and often presented through the medium of DJing, where tracks are curated and mixed sequentially into a continuous stream of music to offer unique listening and dancing experiences over time periods ranging from several minutes to several hours. A DJ's actions and decisions occur at several levels of temporal granularity, from real-time audio manipulation (e.g. of tempo) for smooth inter-track transitions to long-term planning of track selection and sequencing for mix content and flow. While human DJs can instinctively operate across these different temporal resolutions, replicating this capability in an end-to-end automated DJing system presents significant challenges. In this paper, we analyse existing works in DJ mix information retrieval and generation from this temporal perspective. We first explain the close link between DJing and the temporal notion of musical rhythm, then describe a framework for categorising DJing actions by temporal granularity. Using this framework, we summarise and contrast potential approaches for automating and augmenting sequential DJ decision making, and discuss the unique characteristics of DJ mix track selection as a sequential recommendation task. In doing so, we hope to facilitate the implementation of more robust and complete automated DJing systems in future research

    Evolving temporal association rules with genetic algorithms

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    A novel framework for mining temporal association rules by discovering itemsets with a genetic algorithm is introduced. Metaheuristics have been applied to association rule mining, we show the efficacy of extending this to another variant - temporal association rule mining. Our framework is an enhancement to existing temporal association rule mining methods as it employs a genetic algorithm to simultaneously search the rule space and temporal space. A methodology for validating the ability of the proposed framework isolates target temporal itemsets in synthetic datasets. The Iterative Rule Learning method successfully discovers these targets in datasets with varying levels of difficulty

    Information diffusion backbones in temporal networks

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    Progress has been made in understanding how temporal network features affect the percentage of nodes reached by an information diffusion process. In this work, we explore further: which node pairs are likely to contribute to the actual diffusion of information, i.e., appear in a diffusion trajectory? How is this likelihood related to the local temporal connection features of the node pair? Such deep understanding of the role of node pairs is crucial to tackle challenging optimization problems such as which kind of node pairs or temporal contacts should be stimulated in order to maximize the prevalence of information spreading. We start by using Susceptible-Infected (SI) model, in which an infected (information possessing) node could spread the information to a susceptible node with a given infection probability β whenever a contact happens between the two nodes, as the information diffusion process. We consider a large number of real-world temporal networks. First, we propose the construction of an information diffusion backbone G B (β) for a SI spreading process with an infection probability β on a temporal network. The backbone is a weighted network where the weight of each node pair indicates how likely the node pair appears in a diffusion trajectory starting from an arbitrary node. Second, we investigate the relation between the backbones with different infection probabilities on a temporal network. We find that the backbone topology obtained for low and high infection probabilities approach the backbone G B (β → 0) and G B (β = 1), respectively. The backbone G B (β → 0) equals the integrated weighted network, where the weight of a node pair counts the total number of contacts in between. Finally, we explore node pairs with what local connection features tend to appear in G B (β = 1), thus actually contribute to the global information diffusion. We discover that a local connection feature among many other features we proposed, could well identify the (high-weight) links in G B (β = 1). This local feature encodes the time that each contact occurs, pointing out the importance of temporal features in determining the role of node pairs in a dynamic process. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Multimedia ComputingIntelligent System
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