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Processing Tasks (processing + task)
Selected AbstractsReduced parietal and visual cortical activation during global processing in Williams syndromeDEVELOPMENTAL MEDICINE & CHILD NEUROLOGY, Issue 6 2007Dean Mobbs BSc Several lines of investigation suggest that individuals with Williams syndrome (WS), a neurodevelopmental disorder of well-characterized genetic etiology, have selective impairments in integrating local image elements into global configurations. We compared global processing abilities in 10 clinically and genetically diagnosed participants with WS (eight females, two males; mean age 31y 10mo [SD 9y 7mo], range 15y 5mo-48y 4mo) with a typically developed (TD) age- and sex-matched comparison group (seven females, one male; mean age 35y 2mo [SD 10y 10mo], range 24y-54y 7mo) using functional magnetic resonance imaging (fMRI). Behavioral data showed participants with WS to be significantly less accurate (p<0.042) together with a non-significant trend to be slower than the TD comparison group while performing the global processing task. fMRI data showed participants with WS to possess reduced activation in the visual and parietal cortices. Participants with WS also showed relatively normal activation in the ventral occipitotemporal cortex, but elevated activation in several posterior thalamic nuclei. These preliminary results largely confirm previous research findings and neural models implicating neurodevelopmental abnormalities in extended subcortical and cortical visual systems in WS, most notably dorsal-stream pathways. [source] Infant information processing and family history of specific language impairment: converging evidence for RAP deficits from two paradigmsDEVELOPMENTAL SCIENCE, Issue 2 2007Naseem Choudhury An infant's ability to process auditory signals presented in rapid succession (i.e. rapid auditory processing abilities [RAP]) has been shown to predict differences in language outcomes in toddlers and preschool children. Early deficits in RAP abilities may serve as a behavioral marker for language-based learning disabilities. The purpose of this study is to determine if performance on infant information processing measures designed to tap RAP and global processing skills differ as a function of family history of specific language impairment (SLI) and/or the particular demand characteristics of the paradigm used. Seventeen 6- to 9-month-old infants from families with a history of specific language impairment (FH+) and 29 control infants (FH,) participated in this study. Infants' performance on two different RAP paradigms (head-turn procedure [HT] and auditory-visual habituation/recognition memory [AVH/RM]) and on a global processing task (visual habituation/recognition memory [VH/RM]) was assessed at 6 and 9 months. Toddler language and cognitive skills were evaluated at 12 and 16 months. A number of significant group differences were seen: FH+ infants showed significantly poorer discrimination of fast rate stimuli on both RAP tasks, took longer to habituate on both habituation/recognition memory measures, and had lower novelty preference scores on the visual habituation/recognition memory task. Infants' performance on the two RAP measures provided independent but converging contributions to outcome. Thus, different mechanisms appear to underlie performance on operantly conditioned tasks as compared to habituation/recognition memory paradigms. Further, infant RAP processing abilities predicted to 12- and 16-month language scores above and beyond family history of SLI. The results of this study provide additional support for the validity of infant RAP abilities as a behavioral marker for later language outcome. Finally, this is the first study to use a battery of infant tasks to demonstrate multi-modal processing deficits in infants at risk for SLI. [source] CNN applications from the hardware point of view: video sequence segmentationINTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, Issue 2-3 2002Asko Kananen Abstract In this paper, the problems present in hardware implementations of cellular non-linear network (CNN) type parallel processors are discussed. Instead of designing a multipurpose processor, or even a full image size application specific parallel processor, we suggest a division of the processing task into categories depending on the cell dynamics and on the spread of the influence of a cell. In this way, drastic savings can be achieved in silicon size and in processing speed. As an example, we use a CNN algorithm that was designed for video image segmentation for object-based compression of video signal. We start with discussion of the problems related to implementation of the algorithm with current multipurpose processors. We then introduce hardware structures that can be used in obtaining certain functionalities. In the same section, we also deal with the division of the processing task. We also compare the introduced hardware solution for the algorithm with multipurpose processor structures in silicon size, power consumption and in processing speed. Copyright © 2002 John Wiley & Sons, Ltd. [source] Motor and nonmotor event-related potentials during a complex processing taskPSYCHOPHYSIOLOGY, Issue 6 2000Charles H. Hillman Identification of the necessary stimulus properties to elicit the stimulus preceding negativity (SPN) has been the impetus for numerous research studies. The current study was conducted to explore the possibility that the SPN is an index of cognitive resource allocation. An auditory warning stimulus (S1) indicated whether an easy or difficult discrimination would occur at S2. The SPN was collected before a nonmotor discrimination task (S2) that consisted of identifying the higher of two bars. To eliminate the influence of motor processing prior to S2, a button press on the side of the higher bar was held until perception of a response cue (S3). Additionally, P3, contingent negative variation (CNV), and behavioral measures were collected to assist in assessing the SPN. Results indicated that although the SPN exhibited increased negativity, no differences were observed based on task difficulty. However, task difficulty did affect P3 data for both the warning tone and the discrimination task, an effect not observed for the CNV. Overall, the data did not support that hypothesis that the SPN provides an index of cognitive demand. [source] Freeform Shape Representations for Efficient Geometry ProcessingCOMPUTER GRAPHICS FORUM, Issue 3 2003Leif Kobbelt The most important concepts for the handling and storage of freeform shapes in geometry processing applications are parametric representations and volumetric representations. Both have their specific advantages and drawbacks. While the algebraic complexity of volumetric representations is independent from the shape complexity, the domain of a parametric representation usually has to have the same structure as the surface itself (which sometimes makes it necessary to update the domain when the surface is modified). On the other hand, the topology of a parametrically defined surface can be controlled explicitly while in a volumetric representation, the surface topology can change accidentally during deformation. A volumetric representation reduces distance queries or inside/outside tests to mere function evaluations but the geodesic neighborhood relation between surface points is difficult to resolve. As a consequence, it seems promising to combine parametric and volumetric representations to effectively exploit both advantages. In this talk, a number of projects are presented and discussed in which such a combination leads to efficient and numerically stable algorithms for the solution of various geometry processing tasks. Applications include global error control for mesh decimation and smoothing, topology control for level-set surfaces, and shape modeling with unstructured point clouds. [source] Analogy retrieval and processing with distributed vector representationsEXPERT SYSTEMS, Issue 1 2000Tony A. Plate Holographic reduced representations (HRRs) are a method for encoding nested relational structures in fixed-width vector representations. HRRs encode relational structures as vector representations in such a way that the superficial similarity of the vectors reflects both superficial and structural similarity of the relational structures. HRRs also support a number of operations that could be very useful in psychological models of human analogy processing: fast estimation of superficial and structural similarity via a vector dot-product; finding corresponding objects in two structures; and chunking of vector representations. Although similarity assessment and discovery of corresponding objects both theoretically take exponential time to perform fully and accurately, with HRRs one can obtain approximate solutions in constant time. The accuracy of these operations with HRRs mirrors patterns of human performance on analog retrieval and processing tasks. [source] ACE4k: An analog I/O 64×64 visual microprocessor chip with 7-bit analog accuracyINTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, Issue 2-3 2002G. Liñán Abstract This paper describes a full-custom mixed-signal chip which embeds distributed optical signal acquisition, digitally-programmable analog parallel processing, and distributed image memory cache on a common silicon substrate. This chip, designed in a 0.5 µm standard CMOS technology contains around 1.000.000 transistors, of which operate in analog mode; it is hence one the most complex mixed-signal chip reported to now. Chip functional features are: local interactions, spatial-invariant array architecture; programmable local interactions among cells; randomly-selectable memory of instructions (elementary instructions are defined by specific values of the cell local interactions); random storage/retrieval of intermediate images; capability to complete algorithmic image processing tasks controlled by the user-selected stored instructions and interacting with the cache memory, etc. Thus, as illustrated in this paper, the chip is capable to complete complex spatio-temporal image processing tasks within short computation time (<300 ns for linear convolutions) and using a low power budget (<1.2 W for the complete chip). The internal circuitry of the chip has been designed to operate in robust manner with >7-bits equivalent accuracy in the internal analog operations, which has been confirmed by experimental measurements. Such 7-bits accuracy is enough for most image processing applications. ACE4k has been demonstrated capable to implement up to 30 template,-either directly or through template decomposition. This means the 100% of the 3×3 linear templates reported in Roska et al. 1998, [1]. Copyright © 2002 John Wiley & Sons, Ltd. [source] Compact CMOS implementation of a low-power, current-mode programmable cellular neural network,INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, Issue 3 2001L. Ravezzi Abstract We report on the design and characterization of a full-analog programmable current-mode cellular neural network (CNN) in CMOS technology. In the proposed CNN, a novel cell-core topology, which allows for an easy programming of both feedback and control templates over a wide range of values, including all those required for many signal processing tasks, is employed. The CMOS implementation of this network features both low-power consumption and small-area occupation, making it suitable for the realization of large cell-grid sizes. Device level and Monte Carlo simulations of the network proved that the proposed CNN can be successfully adopted for several applications in both grey-scale and binary image processing tasks. Results from the characterization of a preliminary CNN test-chip (8×1 array), intended as a simple demonstrator of the proposed circuit technique, are also reported and discussed. Copyright © 2001 John Wiley & Sons, Ltd. [source] An fMRI Study of Number Processing in Children With Fetal Alcohol SyndromeALCOHOLISM, Issue 8 2010Ernesta M. Meintjes Background:, Number processing deficits are frequently seen in children exposed to alcohol in utero. Methods:, Functional magnetic resonance imaging was used to examine the neural correlates of number processing in 15 right-handed, 8- to 12-year-old children diagnosed with fetal alcohol syndrome (FAS) or partial FAS (PFAS) and 18 right-handed, age- and gender-matched controls from the Cape Coloured (mixed ancestry) community in Cape Town, South Africa, using Proximity Judgment and Exact Addition tasks. Results:, Control children activated the expected fronto-parietal network during both tasks, including the anterior horizontal intraparietal sulcus (HIPS), left posterior HIPS, left precentral sulcus, and posterior medial frontal cortex. By contrast, on the Proximity Judgment task, the exposed children recruited additional parietal pathways involving the right and left angular gyrus and posterior cingulate/precuneus, which may entail verbally mediated recitation of numbers and/or subtraction to assess relative numerical distances. During Exact Addition, the exposed children exhibited more diffuse and widespread activations, including the cerebellar vermis and cortex, which have been found to be activated in adults engaged in particularly challenging number processing problems. Conclusions:, The data suggest that, whereas control children rely primarily on the fronto-parietal network identified in previous studies to mediate number processing, children with FAS/PFAS recruit a broader range of brain regions to perform these relatively simple number processing tasks. Our results are consistent with structural neuroimaging findings indicating that the parietal lobe is relatively more affected by prenatal alcohol exposure and provide the first evidence for brain activation abnormalities during number processing in children with FAS/PFAS, effects that persist even after controlling statistically for group differences in total intracranial volume and IQ. [source] The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic GrowthCOGNITIVE SCIENCE - A MULTIDISCIPLINARY JOURNAL, Issue 1 2005Mark Steyvers Abstract We present statistical analyses of the large-scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small-world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale-free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These regularities have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high-dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small-world statistics and power-law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. [source] | ||||||||||||||||