Proceedings of the International Conference Sensory Motor Concepts in Language & Cognition

This volume contains selected papers of the 2008 annual conference of the German Association for Social Science Research on Japan (Vereinigung für sozialwissenschaftliche Japanforschung e.V. – VSJF). The academic meeting has addressed the issue of demographic change in Japan in comparison to the social developments of ageing in Germany and other member states of the European Union. The conference was organized by the Institute for Modern Japanese Studies at Heinrich-Heine-University of Duesseldorf and took place at the Mutter Haus in Kaiserswerth (an ancient part of Duesseldorf). Speakers from Germany, England, Japan and the Netherlands presented their papers in four sessions on the topics “Demographic Trends and Social Analysis”, “Family and Welfare Policies”, “Ageing Society and the Organization of Households” and “Demographic Change and the Economy”. Central to all transnational and national studies on demographic change is the question of how societies can be reconstructed and be made adaptive to these changes in order to survive as solidarity communities. The authors of this volume attend to this question by discussing on recent trends of social and economic restructuring and giving insight into new research developments such as in the area of households and housing, family care work, medical insurance, robot technology or the employment sector

Compositionality in neural control: an interdisciplinary study of scribbling movements in primates

This article discusses the compositional structure of hand movements by analyzing and modeling neural and behavioral data obtained from experiments where a monkey (Macaca fascicularis) performed scribbling movements induced by a search task. Using geometrically based approaches to movement segmentation, it is shown that the hand trajectories are composed of elementary segments that are primarily parabolic in shape. The segments could be categorized into a small number of classes on the basis of decreasing intra-class variance over the course of training. A separate classification of the neural data employing a hidden Markov model showed a coincidence of the neural states with the behavioral categories. An additional analysis of both types of data by a data mining method provided evidence that the neural activity patterns underlying the behavioral primitives were formed by sets of specific and precise spike patterns. A geometric description of the movement trajectories, together with precise neural timing data indicates a compositional variant of a realistic synfire chain model. This model reproduces the typical shapes and temporal properties of the trajectories; hence the structure and composition of the primitives may reflect meaningful behavior

Embodied learning of a generative neural model for biological motion perception and inference

Although an action observation network and mirror neurons for understanding the actions and intentions of others have been under deep, interdisciplinary consideration over recent years, it remains largely unknown how the brain manages to map visually perceived biological motion of others onto its own motor system. This paper shows how such a mapping may be established, even if the biologically motion is visually perceived from a new vantage point. We introduce a learning artificial neural network model and evaluate it on full body motion tracking recordings. The model implements an embodied, predictive inference approach. It first learns to correlate and segment multimodal sensory streams of own bodily motion. In doing so, it becomes able to anticipate motion progression, to complete missing modal information, and to self-generate learned motion sequences. When biological motion of another person is observed, this self-knowledge is utilized to recognize similar motion patterns and predict their progress. Due to the relative encodings, the model shows strong robustness in recognition despite observing rather large varieties of body morphology and posture dynamics. By additionally equipping the model with the capability to rotate its visual frame of reference, it is able to deduce the visual perspective onto the observed person, establishing full consistency to the embodied self-motion encodings by means of active inference. In further support of its neuro-cognitive plausibility, we also model typical bistable perceptions when crucial depth information is missing. In sum, the introduced neural model proposes a solution to the problem of how the human brain may establish correspondence between observed bodily motion and its own motor system, thus offering a mechanism that supports the development of mirror neurons

Integrative (Synchronisations-)Mechanismen der (Neuro-)Kognition vor dem Hintergrund des (Neo-)Konnektionismus, der Theorie der nichtlinearen dynamischen Systeme, der Informationstheorie und des Selbstorganisationsparadigmas

Der Gegenstand der vorliegenden Arbeit besteht darin, aufbauend auf dem (Haupt-)Thema, der Darlegung und Untersuchung der Lösung des Bindungsproblems anhand von temporalen integrativen (Synchronisations-)Mechanismen im Rahmen der kognitiven (Neuro-)Architekturen im (Neo-)Konnektionismus mit Bezug auf die Wahrnehmungs- und Sprachkognition, vor allem mit Bezug auf die dabei auftretende Kompositionalitäts- und Systematizitätsproblematik, die Konstruktion einer noch zu entwickelnden integrativen Theorie der (Neuro-)Kognition zu skizzie-ren, auf der Basis des Repräsentationsformats einer sog. „vektoriellen Form“, u.z. vor dem Hintergrund des (Neo-)Konnektionismus, der Theorie der nichtlinearen dynamischen Systeme, der Informationstheorie und des Selbstorganisations-Paradigmas

Conditions for cognitive self-organisation implied by visual-word processing

In order to find conditions for biologically plausible, cognitive self-organisation, an adequate representation of the final stage of this process is crucial. The implications of this assumption are analysed for the area of visual-word processing, in particular for position-specific top-down processes from a word – to a letter representation. These processes pose a problem to reviewed models of word reading and computational models in general. A solution in the form of a conceptual network is proposed. In this general model for cognitive brain processes, neural binding of identity and location and of identity and position play a fundamental role: temporary connections emerge during word recognition and are reactivated later, when a letter at given position has to be identified. It is shown how modules active in word recognition are “re-used” in letter identification. In simulations, the role of a critical threshold of cell-assemblies is shown and the selective propagation of activation loops at task-dependent time scales. Requirements for prospective studies on cognitive self-organisation and relations with new empirical work on visual-word processing are discussed

How mobile robots can self-organise a vocabulary

One of the hardest problems in science is the symbol grounding problem, a question that has intrigued philosophers and linguists for more than a century. With the rise of artificial intelligence, the question has become very actual, especially within the field of robotics. The problem is that an agent, be it a robot or a human, perceives the world in analogue signals. Yet humans have the ability to categorise the world in symbols that they, for instance, may use for language.This book presents a series of experiments in which two robots try to solve the symbol grounding problem. The experiments are based on the language game paradigm, and involve real mobile robots that are able to develop a grounded lexicon about the objects that they can detect in their world. Crucially, neither the lexicon nor the ontology of the robots has been preprogrammed, so the experiments demonstrate how a population of embodied language users can develop their own vocabularies from scratch