76,636 research outputs found
Developmental Stages of Perception and Language Acquisition in a Perceptually Grounded Robot
The objective of this research is to develop a system for language learning based on a minimum of pre-wired language-specific functionality, that is compatible with observations of perceptual and language capabilities in the human developmental trajectory. In the proposed system, meaning (in terms of descriptions of events and spatial relations) is extracted from video images based on detection of position, motion, physical contact and their parameters. Mapping of sentence form to meaning is performed by learning grammatical constructions that are retrieved from a construction inventory based on the constellation of closed class items uniquely identifying the target sentence structure. The resulting system displays robust acquisition behavior that reproduces certain observations from developmental studies, with very modest āinnateā language specificity
UK utility data integration: overcoming schematic heterogeneity
In this paper we discuss syntactic, semantic and schematic issues which inhibit the integration of utility data in the UK. We then focus on the techniques employed within the VISTA project to overcome schematic heterogeneity. A Global
Schema based architecture is employed. Although automated approaches to Global Schema definition were attempted
the heterogeneities of the sector were too great. A manual approach to Global Schema definition was employed. The
techniques used to define and subsequently map source utility data models to this schema are discussed in detail. In order to ensure a coherent integrated model, sub and cross domain validation issues are then highlighted. Finally the proposed framework and data flow for schematic integration is introduced
Domain-general Stroop Performance and Hemispheric Asymmetries: A Resting-state EEG Study
The ability to suppress irrelevant information while executing a task or interference resistance is a function of pFC that is critical for successful goal-directed human behavior. In the study of interference resistance and, more generally, executive functions, two key questions are still open: Does pFC contribute to cognitive control abilities through lateralized but domain-general mechanisms or through hemispheric specialization of domain-specific processes? And what are the underlying causes of interindividual differences in executive control performance? To shed light on these issues, here we employed an interindividual difference approach to investigate whether participants' hemispheric asymmetry in resting-state electrophysiological brain dynamics may reflect their variability in domain-general interference resistance. We recorded participants' resting-state electroencephalographic activity and performed spectral power analyses on the estimated cortical source activity. To measure participants' lateralized brain dynamics at rest, we computed the right-left hemispheric asymmetry score for the \u3b2/\u3b1 power ratio. To measure their domain-general interference resistance ability, verbal and spatial Stroop tasks were used. Robust correlations followed by intersection analyses showed that participants with stronger resting-state-related left-lateralized activity in different pFC regions, namely the mid-posterior superior frontal gyrus, middle and posterior middle frontal gyrus, and inferior frontal junction, were more able to inhibit irrelevant information in both domains. The present results confirm and extend previous findings showing that neurophysiological difference factors may explain interindividual differences in executive functioning. They also provide support for the hypothesis of a left pFC hemispheric specialization for domain-independent phasic cognitive control processes mediating Stroop performance
Conceptual spatial representations for indoor mobile robots
We present an approach for creating conceptual representations of human-made indoor environments using mobile
robots. The concepts refer to spatial and functional properties of typical indoor environments. Following ļ¬ndings
in cognitive psychology, our model is composed of layers representing maps at diļ¬erent levels of abstraction. The
complete system is integrated in a mobile robot endowed with laser and vision sensors for place and object recognition.
The system also incorporates a linguistic framework that actively supports the map acquisition process, and which
is used for situated dialogue. Finally, we discuss the capabilities of the integrated system
Experimental Design Modulates Variance in BOLD Activation: The Variance Design General Linear Model
Typical fMRI studies have focused on either the mean trend in the
blood-oxygen-level-dependent (BOLD) time course or functional connectivity
(FC). However, other statistics of the neuroimaging data may contain important
information. Despite studies showing links between the variance in the BOLD
time series (BV) and age and cognitive performance, a formal framework for
testing these effects has not yet been developed. We introduce the Variance
Design General Linear Model (VDGLM), a novel framework that facilitates the
detection of variance effects. We designed the framework for general use in any
fMRI study by modeling both mean and variance in BOLD activation as a function
of experimental design. The flexibility of this approach allows the VDGLM to i)
simultaneously make inferences about a mean or variance effect while
controlling for the other and ii) test for variance effects that could be
associated with multiple conditions and/or noise regressors. We demonstrate the
use of the VDGLM in a working memory application and show that engagement in a
working memory task is associated with whole-brain decreases in BOLD variance.Comment: 18 pages, 7 figure
Quantifying the time course of visual object processing using ERPs: it's time to up the game
Hundreds of studies have investigated the early ERPs to faces and objects using scalp and intracranial recordings. The vast majority of these studies have used uncontrolled stimuli, inappropriate designs, peak measurements, poor figures, and poor inferential and descriptive group statistics. These problems, together with a tendency to discuss any effect p < 0.05 rather than to report effect sizes, have led to a research field very much qualitative in nature, despite its quantitative inspirations, and in which predictions do not go beyond condition A > condition B. Here we describe the main limitations of face and object ERP research and suggest alternative strategies to move forward. The problems plague intracranial and surface ERP studies, but also studies using more advanced techniques ā e.g., source space analyses and measurements of network dynamics, as well as many behavioral, fMRI, TMS, and LFP studies. In essence, it is time to stop amassing binary results and start using single-trial analyses to build models of visual perception
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