Oscillations, phase-of-firing coding, and spike timing-dependent plasticity: an efficient learning scheme

Recent experiments have established that information can be encoded in the spike times of neurons relative to the phase of a background oscillation in the local field potential—a phenomenon referred to as “phase-of-firing coding” (PoFC). These firing phase preferences could result from combining an oscillation in the input current with a stimulus-dependent static component that would produce the variations in preferred phase, but it remains unclear whether these phases are an epiphenomenon or really affect neuronal interactions—only then could they have a functional role. Here we show that PoFC has a major impact on downstream learning and decoding with the now well established spike timing-dependent plasticity (STDP). To be precise, we demonstrate with simulations how a single neuron equipped with STDP robustly detects a pattern of input currents automatically encoded in the phases of a subset of its afferents, and repeating at random intervals. Remarkably, learning is possible even when only a small fraction of the afferents (~10%) exhibits PoFC. The ability of STDP to detect repeating patterns had been noted before in continuous activity, but it turns out that oscillations greatly facilitate learning. A benchmark with more conventional rate-based codes demonstrates the superiority of oscillations and PoFC for both STDP-based learning and the speed of decoding: the oscillation partially formats the input spike times, so that they mainly depend on the current input currents, and can be efficiently learned by STDP and then recognized in just one oscillation cycle. This suggests a major functional role for oscillatory brain activity that has been widely reported experimentally.

Marketing education, distance learning and hypermedia : teaching 'current issues in marketing' in a virtual campus

This article reports on a project at the Universitat Oberta de Catalunya (UOC: The Open University of Catalonia, Barcelona) to develop an innovative package of hypermedia-based learning materials for a new course entitled 'Current Issues in Marketing'. The UOC is a distance university entirely based on a virtual campus. The learning materials project was undertaken in order to benefit from the advantages which new communication technologies offer to the teaching of marketing in distance education. The article reviews the main issues involved in incorporating new technologies in learning materials, the development of the learning materials, and their functioning within the hypermedia based virtual campus of the UOC. An empirical study is then carried out in order to evaluate the attitudes of students to the project. Finally, suggestions for improving similar projects in the future are put forward.

Improving Searching and Browsing Capabilities of Learning Object Repositories

Learning object repositories are a basic piece of virtual learning environments used for content management. Nevertheless, learning objects have special characteristics that make traditional solutions for content management ine ective. In particular, browsing and searching for learning objects cannot be based on the typical authoritative meta-data used for describing content, such as author, title or publicationdate, among others. We propose to build a social layer on top of a learning object repository, providing nal users with additional services fordescribing, rating and curating learning objects from a teaching perspective. All these interactions among users, services and resources can be captured and further analyzed, so both browsing and searching can be personalized according to user pro le and the educational context, helping users to nd the most valuable resources for their learning process. In this paper we propose to use reputation schemes and collaborative filtering techniques for improving the user interface of a DSpace based learning object repository.

Extending Learning Objects by Means of Social Networking

Learning objects have been the promise of providing people with high quality learning resources. Initiatives such as MIT Open-CourseWare, MERLOT and others have shown the real possibilities of creating and sharing knowledge through Internet. Thousands of educational resources are available through learning object repositories. We indeed live in an age of content abundance, and content can be considered as infrastructure for building adaptive and personalized learning paths, promoting both formal and informal learning. Nevertheless, although most educational institutions are adopting a more open approach, publishing huge amounts of educational resources, the reality is that these resources are barely used in other educational contexts. This paradox can be partly explained by the dificulties in adapting such resources with respect to language, e-learning standards and specifications and, finally, granularity. Furthermore, if we want our learners to use and take advantage of learning object repositories, we need to provide them with additional services than just browsing and searching for resources. Social networks can be a first step towards creating an open social community of learning around a topic or a subject. In this paper we discuss and analyze the process of using a learning object repository and building a social network on the top of it, with respect to the information architecture needed to capture and store the interaction between learners and resources in form of learning object metadata.

Aprendizaje Servicio Universitario: creando empleo a partir de la emprendeduría social

La Universidad debe erigirse como motor de la sociedad civil y abordar con decisión los desafíos sociales contemporáneos, como es la situación de paro en España. La metodología del Aprendizaje Servicio Universitario permite integrar un aprendizaje basado en la realidad con el servicio a la comunidad concretizando la responsabilidad social de la Universidad. El artículo presenta el proyecto interfacultativo EcoSPORTech desarrollado en la Universidad de Vic cuya finalidad ha sido la creación de empleo juvenil desde la emprendeduría social. La política de comunicación ha sido clave en este proyecto.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Assessment of research competences using e-portfolio

The challenges posed by the assessment of distance learning is a topic that requires, on the one hand, evolution with new trends and, on the other improving evaluative processes, to promote good practices. This demand becomes more imperative when we are dealing with a formativescenario based on distance assessment of competence-based learning.The Open University of Catalonia has begun to work with these formative tools, promoting new practices for online education. A very clear example of these educational practices is the assessment of research competences using the e-portfolio system. To meet this aim a profound and solid process has been developed over recent years, with the intention of making this tool an assessment alternative, and providing the opportunity to use it in a formative context. The objective is to study its strengths and limitations keeping in mind the final goal of offering the higher education community a validated assessment system.

Metadata for describing learning scenarios under European Higher Education Area paradigm

In this paper we identify the requirements for creating formal descriptions of learning scenarios designed under the European HigherEducation Area paradigm, using competences and learning activities as the basic pieces of the learning process, instead of contents and learning resources, pursuing personalization. Classical arrangements of content based courses are no longer enough to describe all the richness of this new learning process, where user profiles, competences and complex hierarchical itineraries need to be properly combined. We study the intersection with the current IMS Learning Design specification and theadditional metadata required for describing such learning scenarios. This new approach involves the use of case based learning and collaborativelearning in order to acquire and develop competences, following adaptive learning paths in two structured levels.

A conceptual model for grid learning services automatic composition

Peer-reviewed

Estudio multidisciplinario del ecosistema manglar en la comunidad tradicional de Curral Velho : Estudio sobre la pesca artesanal y análisis de sus diferencias con la acuicultura del camarón

Curral Velho es una comunitat tradicional, situada al nord-est de Brasil, que manté una relació directa amb els ecosistemes que la envolten. La comunitat depèn del estat de conservació del medi natura, ja que obtenen diferents serveis ecositemics. En aquest territori es desenvolupen dos tipus d’economies amb unes bases molt diferents. Una economia tradicional, desenvolupada per la pròpia comunitat, que es basa en la propietat col·lectiva del territori i en optimitzar a llarg termini els beneficis que s’obtenen del medi; y un altre com la camaronicultura, la base de la qual es la obtenció de beneficis a curt termini i amb un territori de propietat privada. Aquesta superposició de models de producció genera impactes ambientals, i un conflicte socio-ambiental entre la comunitat i els que desenvolupen la camaronicultura. L’objectiu es realitzar un estudi econòmic de la pesca artesanal de Curral Velho caracteritzant manera de viure, creant una base de dades sobre pesca artesanal i elaborant indicador de beneficis econòmics generats per la pesca artesanal. Per contextualitzar els resultats es va fer un anàlisis de les dos economies existents a la comunitat. Els resultats obtinguts en primer lloc són que l’economia d’explotació intensiva aporta més guanys per les persones de la comunitat que tenen un relació directa que les que es dediquen a la pesca artesanal, però es important no aturar-se aquí: s’ha de realitzar un anàlisis més profund. Com a conclusió, la activitat pesquera es més rentable a llarg termini ja que els recursos extrets de manera sostenible i així són il·limitats y accessibles a tota la comunitat. A diferència de la camaronicultura, la pesca artesanal no genera desigualtats socials ni vulneracions dels drets humans. Tot el contrari, genera forts vincles entre els individus de la comunitat basats en el treball en equip i l’aprenentatge vivencial e intergeneracional.

The Transformation of Practical Teaching Focusing on Dialogic Learning

This study investigates the transformation of practical teaching in a Catalan school, connected to the design, implementation and development of project-based learning, and focusing on dialogic learning to investigate its limits and possibilities. Qualitative and design-based research (DBR) methods are applied. These methods are based on empirical educational research with the theory-driven of learning environments. DBR is proposed and applied using practical guidance for the teachers of the school. It can be associated with the current proposals for Embedding Social Sciences and Humanities in the Horizon 2020 Societal Challenges. This position statement defends the social sciences and the humanities as the most fundamental and important ideas to face all societal challenges. The results of this study show that before the training process, teachers apply dialogic learning in specific moments (for example, when they speak about the weekend); however, during the process and after the process, they work systematically with dialogic learning through the PEPT: they start and finish every activity with a individual and group reflection about their own processes, favouring motivation, reasoning and the implication of all the participants. These results prove that progressive transformations of teaching practice benefit cooperative work in class

Towards adoption of eLearning technologies at Lappeenranta University of Technology: Understanding Teachers‟ Adoption of Blackboard Learning System

The electronic learning has become crucial in higher education with increased usage of learning management systems as a key source of integration on distance learning. The objective of this study is to understand how university teachers are influenced to use and adopt web-based learning management systems. Blackboard, as one of the systems used internationally by various universities is applied as a case. Semi-structured interviews were made with professors and lecturers who are using Blackboard at Lappeenranta University of Technology. The data collected were categorized under constructs adapted from Unified Theory of Acceptance and Use of Technology (UTAUT) and interpretation and discussion were based on reviewed literature. The findings suggest that adoption of learning management systems by LUT teachers is highly influenced by perceived usefulness, facilitating conditions and gained experience. The findings also suggest that easiness of using the system and social influence appear as medium influence of adoption for teachers at LUT.