Grid Cell Hexagonal Patterns Formed by Fast Self-Organized Learning within Entorhinal Cortex

Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. How these hexagonal patterns arise has excited intense interest. It has previously been shown how a selforganizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? A neural model is proposed that converts path integration signals into hexagonal grid cell patterns of multiple scales. This GRID model creates only grid cell patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support a unified computational framework for explaining how entorhinal-hippocampal interactions support spatial navigation.CELEST, a National Science Foundation Science of Learning Center (SBE-0354378); SyNAPSE program of Defense Advanced Research Projects Agency (HR00ll-09-3-0001, HR0011-09-C-0011

Decision Makers\u27 Thinking During the Design and Implementation of a K-5 High-Computer-Access (HCA) Program

As present trends in education indicate, learning with technology is increasingly being considered as a means of instructional delivery for K-1 2 learners. Educational leaders must be informed of how to provide the experiences, skills, and knowledge required of the learners for whom they are responsible. This qualitative study examined the conceptualization of a school district\u27s attempt to design and implement a high-computer-access (HCA) program. Research methodologies included interview, observation, and analysis of related documents. The results comprised the thinking of the HCA program designers and how they viewed learning theory and effective instruction principles in relationship to the HCA environments they were creating. The findings from this study indicated that designing and implementing an HCA program into a school district involves several issues. These issues were organized into the following themes: (a) goals and assumptions; (b) appropriation; (c) transformative teaching; (d) child-centered instruction; and (e) logistics. The goals and assumptions theme addressed the participants\u27 thinking about the organization\u27s and the designers\u27 goals that evolved during the design phase. The appropriations theme encompassed the use of computer as a learning and teaching tool. Reported changes in instructional planning and delivery are represented in the transformative teaching theme. The child-centered instruction theme resulted from participants\u27 numerous references to learning theory. The fifth theme, logistics, included the procurement, maintenance, and knowledge acquisition inherent in HCA environments. Further investigation of these themes may assist educational leaders who would choose to implement HCA environments into their schools

Evolutionarily conserved mechanisms for the selection and maintenance of behavioural activity

Survival and reproduction entail the selection of adaptive behavioural repertoires. This selection manifests as phylogenetically acquired activities that depend on evolved nervous system circuitries. Lorenz and Tinbergen already postulated that heritable behaviours and their reliable performance are specified by genetically determined programs. Here we compare the functional anatomy of the insect central complex and vertebrate basal ganglia to illustrate their role in mediating selection and maintenance of adaptive behaviours. Comparative analyses reveal that central complex and basal ganglia circuitries share comparable lineage relationships within clusters of functionally integrated neurons. These clusters are specified by genetic mechanisms that link birth time and order to their neuronal identities and functions. Their subsequent connections and associated functions are characterized by similar mechanisms that implement dimensionality reduction and transition through attractor states, whereby spatially organized parallel-projecting loops integrate and convey sensorimotor representations that select and maintain behavioural activity. In both taxa, these neural systems are modulated by dopamine signalling that also mediates memory-like processes. The multiplicity of similarities between central complex and basal ganglia suggests evolutionarily conserved computational mechanisms for action selection. We speculate that these may have originated from ancestral ground pattern circuitries present in the brain of the last common ancestor of insects and vertebrates

Component-based software engineering

To solve the problems coming with the current software development methodologies, component-based software engineering has caught many researchers\u27 attention recently. In component-based software engineering, a software system is considered as a set of software components assembled together instead of as a set of functions from the traditional perspective. Software components can be bought from third party vendors as off-the-shelf components and be assembled together. Component-based software engineering, though very promising, needs to solve several core issues before it becomes a mature software development strategy. The goal of this dissertation is to establish an infrastructure for component-based software development. The author identifies and studies some of the core issues such as component planning, component building, component assembling, component representation, and component retrieval. A software development process model is developed in this dissertation to emphasize the reuse of existing software components. The software development process model addresses how a software system should be planned and built to maximize the reuse of software components. It conducts domain engineering and application engineering simultaneously to map a software system to a set of existing components in such a way that the development of a software system can reuse the existing software components to the full extent. Besides the planning of software development based on component technology, the migration and integration of legacy systems, most of which are non-component-based systems, to the component-based software systems are studied. A framework and several methodologies are developed to serve as the guidelines of adopting component technology in legacy systems. Component retrieval is also studied in this dissertation. One of the most important issues in component-based software engineering is how to find a software component quickly and accurately in a component repository. A component representation framework is developed in this dissertation to represent software components. Based on the component representation framework, an efficient searching method that combines neural network, information retrieval, and Bayesian inference technology is developed. Finally a prototype component retrieval system is implemented to demonstrate the correctness and feasibility of the proposed method

An investigation to study the feasibility of on-line bibliographic information retrieval system using an APP

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.This thesis reports an investigation on the feasibility study of a searching mechanism using an APP suitable for an on-line bibliographic retrieval, operation, especially for retrospective searches. From the study of the searching methods used in the conventional systems it is seen that elaborate file- and data- structures are introduced to improve the response time of the system. These consequently lead to software and hardware redundancies. To mask these complexities of the system an expensive computer with higher capabilities and more powerful instruction set is commonly used. Thus the service of the systen becomes cost-ineffective. On the other hand the primitive operations of a searching mechanism, such as, association, domain selection, intersection and unions, are the intrinsic features of an associative parallel processor. Therefore it is important to establish the feasibility of an APP as a cost-effective searching mechanise. In this thesis a searching mechanism using an 'ON-THE-FLY' searching technique has been proposed. The parallel search unit uses a Byte-oriented VRL-APP for efficient character string processing. At the time of undertaking this work the specification for neither the retrieval systems nor the BO-VRL APP's were well established; hence a two-phase investigation was originated. In the Phase I of the work a bottom up approach was adopted to derive a formal and precise specification for the BO-VRL-APP. During the Phase II of the work a top-down approach was opted for the implementation of the searching mechanism. An experimental research vehicle has been developed to establish the feasibility of an APP as a cost-effective searching mechanism. Although rigorous proof of the feasibility has not been obtained, the thesis establishes that the APP is well suited for on-line bibligraphic information retrieval operations where substring searches including boolean selection and threshold weights are efficiently supported

T2HSOM: Understanding the Lexicon by Simulating Memory Processes for Serial Order

Over the last several years, both theoretical and empirical approaches to lexical knowledge and encoding have prompted a radical reappraisal of the traditional dichotomy between lexicon and grammar. The lexicon is not simply a large waste basket of exceptions and sub-regularities, but a dynamic, possibly redundant repository of linguistic knowledge whose principles of relational organization are the driving force of productive generalizations. In this paper, we overview a few models of dynamic lexical organization based on neural network architectures that are purported to meet this challenging view. In particular, we illustrate a novel family of Kohonen self-organizing maps (T2HSOMs) that have the potential of simulating competitive storage of symbolic time series while exhibiting interesting properties of morphological organization and generalization. The model, tested on training samples of as morphologically diverse languages as Italian, German and Arabic, shows sensitivity to manifold types of morphological structure and can be used to bootstrap morphological knowledge in an unsupervised way

Episodic memory across the lifespan: The contributions of associative and strategic components

The structural and functional brain circuitries supporting episodic memory undergo profound reorganization in childhood and old age. We propose a two-component framework that combines and integrates evidence from child development and aging. It posits that episodic memory builds on two interacting components: (a) the strategic component, which refers to memory control operations, and (b) the associative component, which refers to mechanisms that bind different features of a memory episode into a compound representation. We hypothesize that: (a) children's difficulties in episodic memory primarily originate from low levels of strategic operations, and reflect the protracted development of the prefrontal cortex (PFC); (b) deficits in episodic memory performance among older adults originate from impairments in both strategic and associative components, reflecting senescent changes in the PFC and the medio-temporal lobes (MTL). Initial behavioral and neural evidence is consistent with both hypotheses. The two-component framework highlights the specificities of episodic memory in different age periods, helps to identify and dissociate its components, and contributes to understanding the interplay among maturation, learning, and senescence