241,658 research outputs found

    A Multi-disciplinary Approach to the Investigation of Aspects of Serial Order in Cognition

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    Serial order processing or Sequence processing underlies many human activities such as speech, language, skill learning, planning, problem solving, etc. Investigating the\ud neural bases of sequence processing enables us to understand serial order in cognition and helps us building intelligent devices. In the current paper, various\ud cognitive issues related to sequence processing will be discussed with examples. Some of the issues are: distributed versus local representation, pre-wired versus\ud adaptive origins of representation, implicit versus explicit learning, fixed/flat versus hierarchical organization, timing aspects, order information embedded in sequences, primacy versus recency in list learning and aspects of sequence perception such as recognition, recall and generation. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, theoretical frameworks based on Markov models and Reinforcement Learning paradigm will be presented. These theoretical ideas are useful for studying sequential phenomena in a principled way

    Investigation of sequence processing: A cognitive and computational neuroscience perspective

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    Serial order processing or sequence processing underlies many human activities such as speech, language, skill learning, planning, problem-solving, etc. Investigating the neural bases of sequence processing enables us to understand serial order in cognition and also helps in building intelligent devices. In this article, we review various cognitive issues related to sequence processing with examples. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, a theoretical approach based on statistical models and reinforcement learning paradigm is presented. These theoretical ideas are useful for studying sequence learning in a principled way. This article also suggests a two-way process diagram integrating experimentation (cognitive neuroscience) and theory/ computational modelling (computational neuroscience). This integrated framework is useful not only in the present study of serial order, but also for understanding many cognitive processes

    Towards memory supporting personal information management tools

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    In this article we discuss re-retrieving personal information objects and relate the task to recovering from lapse(s) in memory. We propose that fundamentally it is lapses in memory that impede users from successfully re-finding the information they need. Our hypothesis is that by learning more about memory lapses in non-computing contexts and how people cope and recover from these lapses, we can better inform the design of PIM tools and improve the user's ability to re-access and re-use objects. We describe a diary study that investigates the everyday memory problems of 25 people from a wide range of backgrounds. Based on the findings, we present a series of principles that we hypothesize will improve the design of personal information management tools. This hypothesis is validated by an evaluation of a tool for managing personal photographs, which was designed with respect to our findings. The evaluation suggests that users' performance when re-finding objects can be improved by building personal information management tools to support characteristics of human memory

    Modelling the Developing Mind: From Structure to Change

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    This paper presents a theory of cognitive change. The theory assumes that the fundamental causes of cognitive change reside in the architecture of mind. Thus, the architecture of mind as specified by the theory is described first. It is assumed that the mind is a three-level universe involving (1) a processing system that constrains processing potentials, (2) a set of specialized capacity systems that guide understanding of different reality and knowledge domains, and (3) a hypecognitive system that monitors and controls the functioning of all other systems. The paper then specifies the types of change that may occur in cognitive development (changes within the levels of mind, changes in the relations between structures across levels, changes in the efficiency of a structure) and a series of general (e.g., metarepresentation) and more specific mechanisms (e.g., bridging, interweaving, and fusion) that bring the changes about. It is argued that different types of change require different mechanisms. Finally, a general model of the nature of cognitive development is offered. The relations between the theory proposed in the paper and other theories and research in cognitive development and cognitive neuroscience is discussed throughout the paper

    Learning and Production of Movement Sequences: Behavioral, Neurophysiological, and Modeling Perspectives

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    A growing wave of behavioral studies, using a wide variety of paradigms that were introduced or greatly refined in recent years, has generated a new wealth of parametric observations about serial order behavior. What was a mere trickle of neurophysiological studies has grown to a more steady stream of probes of neural sites and mechanisms underlying sequential behavior. Moreover, simulation models of serial behavior generation have begun to open a channel to link cellular dynamics with cognitive and behavioral dynamics. Here we summarize the major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2XN, discrete sequence production, and serial reaction time. These populate a continuum from higher to lower degrees of internal control of sequential organization. The main movement classes covered are speech and keypressing, both involving small amplitude movements that are very amenable to parametric study. A brief synopsis of classes of serial order models, vis-à-vis the detailing of major effects found in the behavioral data, leads to a focus on competitive queuing (CQ) models. Recently, the many behavioral predictive successes of CQ models have been joined by successful prediction of distinctively patterend electrophysiological recordings in prefrontal cortex, wherein parallel activation dynamics of multiple neural ensembles strikingly matches the parallel dynamics predicted by CQ theory. An extended CQ simulation model-the N-STREAMS neural network model-is then examined to highlight issues in ongoing attemptes to accomodate a broader range of behavioral and neurophysiological data within a CQ-consistent theory. Important contemporary issues such as the nature of working memory representations for sequential behavior, and the development and role of chunks in hierarchial control are prominent throughout.Defense Advanced Research Projects Agency/Office of Naval Research (N00014-95-1-0409); National Institute of Mental Health (R01 DC02852

    Handwritten digit recognition by bio-inspired hierarchical networks

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    The human brain processes information showing learning and prediction abilities but the underlying neuronal mechanisms still remain unknown. Recently, many studies prove that neuronal networks are able of both generalizations and associations of sensory inputs. In this paper, following a set of neurophysiological evidences, we propose a learning framework with a strong biological plausibility that mimics prominent functions of cortical circuitries. We developed the Inductive Conceptual Network (ICN), that is a hierarchical bio-inspired network, able to learn invariant patterns by Variable-order Markov Models implemented in its nodes. The outputs of the top-most node of ICN hierarchy, representing the highest input generalization, allow for automatic classification of inputs. We found that the ICN clusterized MNIST images with an error of 5.73% and USPS images with an error of 12.56%

    Real spin glasses relax slowly in the shade of hierarchical trees

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    The Parisi solution of the mean-field spin glass has been widely accepted and celebrated. Its marginal stability in 3d and its complexity however raised the question of its relevance to real spin glasses. This paper gives a short overview of the important experimental results which could be understood within the mean-field solution. The existence of a true phase transition and the particular behaviour of the susceptibility below the freezing temperature, predicted by the theory, are clearly confirmed by the experimental results. The behaviour of the complex order parameter and of the Fluctuation Dissipation ratio are in good agreement with results of spontaneous noise measurements. The very particular ultrametric symmetry, the key feature of the theory, provided us with a simple description of the rejuvenation and memory effects observed in experiment. Finally, going a step beyond mean-field, the paper shortly discusses new analyses in terms of correlated domains characterized by their length scales, as well as new experiments on superspin glasses which compare well with recent theoretical simulations.Comment: To appear in the proceedings of "Wandering with Curiosity in Complex Landscapes", a scientific conference in honour of Giorgio Parisi for his 60th birthday, Roma, September 8-10 2008 (submitted for the special issue of the Journal of Statistical Physics, 2009

    A comprehensive approach to MPSoC security: achieving network-on-chip security : a hierarchical, multi-agent approach

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    Multiprocessor Systems-on-Chip (MPSoCs) are pervading our lives, acquiring ever increasing relevance in a large number of applications, including even safety-critical ones. MPSoCs, are becoming increasingly complex and heterogeneous; the Networks on Chip (NoC paradigm has been introduced to support scalable on-chip communication, and (in some cases) even with reconfigurability support. The increased complexity as well as the networking approach in turn make security aspects more critical. In this work we propose and implement a hierarchical multi-agent approach providing solutions to secure NoC based MPSoCs at different levels of design. We develop a flexible, scalable and modular structure that integrates protection of different elements in the MPSoC (e.g. memory, processors) from different attack scenarios. Rather than focusing on protection strategies specifically devised for an individual attack or a particular core, this work aims at providing a comprehensive, system-level protection strategy: this constitutes its main methodological contribution. We prove feasibility of the concepts via prototype realization in FPGA technology
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