Plenary Talks

Barbara Webb Institute for Perception, Action and Behaviour School of Informatics, University of Edinburgh, UK

Ant navigation: lessons for, and from, robots

Ants are highly capable navigators. They have been the focus of behavioural and ethological study for many years, and a range of algorithmic models of their behaviour have been proposed, often tested in robot implementations. Our recent work has focussed on bridging the gap to understanding the neural circuits that underlie capacities such as visual orientation, path integration, and the combination of multiple cues. In each case there is an important interplay between exploiting critical sensory cues in the natural environment, and the efficient and robust computation that supports behavioural control. Maintaining a tight loop between behavioural, modelling and robot studies has been key to progress in this field.

Thomas Speck University of Freiburg, Plant Biomechanics Group, Botanic Garden, Faculty of Biology, Competence Networks 

Biomimetic Materials: Smart and Multifunctional Solutions for Technical Challenges of the 21st Century
Biomimetics and BIOKON, Freiburg Materials Research Centre (FMF) and Freiburg Centre for Interactive Materials and Bio-Inspired Technologies (FIT). During the last decades biomimetics has attracted increasing attention as well from basic and applied research as from various fields of industry. Biomimetics has a high innovation potential and offers the possibility for the development of sustainable technical products and production chains. Novel sophisticated methods for quantitatively analyzing and simulating the form-structure-function-relationship on various hierarchical levels allow new fascination insights in multi-scale mechanics and other functions of biological materials and surfaces. On the other hand, new production methods enable for the first time the transfer of many outstanding properties of the biological role models into innovative biomimetic products for reasonable 

Antonio Bicchi  Italian Institute of Technology IIT. Genova, Italy

On the Soft Synergy Model and Its Applications to Artificial Hands.    There is a long history of beautiful and sophisticated artificial hands which had little or no impact on affordable and usable devices for robotics or prosthetics. In an effort to overcome such limitations, it is apparent that simplicity is at a premium, but also that ``simple'' is not necessarily ``easy''. Our work in recent years focused on trying to understand what is at the core of human upper limb functionalities, to develop a principled design approach to simplification. Not surprisingly, we found that some principles from human motor control can lead to a better design and control of artificial hands. I will present the main idea we used to enable such simplification, i.e. the notion of ``soft synergies'', which merges the concepts of motor synergies with an equilibrium-point hypothesis, and recent results in the development of the SoftHand Pro, a prosthetic derivative of the Pisa/IIT SoftHand technology.

Frank Hirth College London, Institute of Psychiatry, Psychology, Neuroscience, Department of Basic Clinical Neuroscience, London/UK.

Neural mechanisms and computations underlying the selection and maintenance of behavioural activity. 
Action selection is a neural mechanism underlying adaptive behaviour. It mediates selection and maintenance of behavioural actions and their organization into action sequences by facilitating appropriate, while inhibiting competing, motor programs. This action selection process involves neural circuits in the central brain of insects and vertebrates, including the central complex and the basal ganglia, respectively. Previous studies led to insights into the functional anatomy of basal ganglia substructures and their role in adaptive behaviour. In addition, neural computation models have been developed which allow specific predictions to be tested. Thus far, however, the in vivo mechanisms and computations underlying action selection remained largely elusive. We recently resolved a highly conserved structural and functional ground pattern organization of the insect central complex and the vertebrate basal ganglia. Our comparative analyses reveal that central complex and basal ganglia circuitries share pattern-generating algorithms that implement comparable connections and associated functionalities. These are characterized by neural mechanisms and computations that implement dimensionality reduction and transition through attractor states, whereby spatially organised parallel projecting loops integrate and convey sensorimotor representations for the selection and maintenance of behavioural activity. In both taxa, these neural systems are modulated by dopamine signalling that also mediates memory-like processes. Using the insect species Drosophila as a paradigmatic example, I will illustrate some of the emerging principles and discuss their relevance for 'living machines'.

Yoshihiko Nakamura University of Tokio, Japan

Computer simulation of the human wholebody neuromuscular system is a grand challenge of supercomputing.
The system includes the central and peripheral nerve systems, and the wholebody musculoskeletal system. As a member of the team in K-Computer project for predictive medicine, we have worked on the modeling of neuron pools of motor neurons in the spine and sensory neurons in the spinal nerves as well as of the wholebody skeletal muscles. The neurons were modeled by spiking neurons model using the leaky integral-and-fire circuit. The muscles were modeled by viscoelastic continuum bodies using the FEM. This talk will introduce the hypotheses and algorithms we have based on and a very preliminary result of computation.