Emulation of chemical stimulus triggered head movement in the C. elegans nematode

For a considerable time, it has been the goal of computational neuroscientists to understand biological nervous systems. However, the vast complexity of such systems has made it very difficult to fully understand even basic functions such as movement. Because of its small neuron count, the C. elegans nematode offers the opportunity to study a fully described connectome and attempt to link neural network activity to behaviour. In this paper a simulation of the neural network in C. elegans that responds to chemical stimulus is presented and a consequent realistic head movement demonstrated. An evolutionary algorithm (EA) has been utilised to search for estimates of the values of the synaptic conductances and also to determine whether each synapse is excitatory or inhibitory in nature. The chemotaxis neural network was designed and implemented, using the parameterization obtained with the EA, on the Si elegans platform a state-of-the-art hardware emulation platform specially designed to emulate the C. elegans nematode

Using Multidimensional Scaling to Quantify the Fidelity of Haptic Rendering of Deformable Objects

Leskovsky P, Cooke T, Ernst MO, Harders M. Using Multidimensional Scaling to Quantify the Fidelity of Haptic Rendering of Deformable Objects. In: Proceedings of the EuroHaptics 2006 International Conference (EH 2006). Paris, France; 2006: 289-295.In this paper, we examine the application of a psychophysical evaluation technique to quantify the fidelity of haptic rendering methods. The technique is based on multidimensional scaling (MDS) analysis of similarity ratings provided by users comparing pairs of haptically-presented objects. Unbeknownst to the participants, both real and virtual deformable objects were presented to them. In addition, virtual objects were either presented under higher-fidelity rendering condition or under lower-fidelity condition in which force filtering and proxy-point filtering were removed. We hypothesized that reducing fidelity of virtual rendering would exaggerate the difference between real and virtual objects. MDS analysis of pairwise similarity data provided quantitative confirmation that users perceived a clear difference between real and virtual objects in the lower-fidelity, but not in the higher-fidelity condition. In the latter, a single perceptual dimension, corresponding to stiffness, sufficed to explain similarity data, while two perceptual dimensions were needed in the former condition. This study demonstrates how MDS analysis provides an opportunity to visualize and quantify the perceptual effects of changes in rendering parameters and how it can be used in the evaluation of haptic rendering scenarios

Design and Evaluation of Haptic Soft Tissue Interaction

Harders M, Leskovsky P, Cooke T, Ernst MO, Szekely G. Design and Evaluation of Haptic Soft Tissue Interaction. In: Siciliano B, ed. The Sense of Touch and its Rendering: Progresses in Haptics Research. Springer Tracts in Advanced Robotics. Berlin, Germany: Springer; 2008: 225-244.This chapter examines the application of a psychophysical evaluation technique to quantify the fidelity of haptic rendering methods. The technique is based on multidimensional scaling analysis of similarity ratings provided by users comparing pairs of haptically-presented objects. Unbeknownst to the participants, both real and virtual deformable objects were presented. In addition, virtual objects were either rendered under high fidelity condition or under lower-fidelity condition in which filtering quality was reduced. The analysis of pairwise similarity data provides quantitative confirmation that users perceived a clear difference between real and virtual objects in the lower-fidelity, but not in the higher-fidelity condition. In the latter, a single perceptual dimension, corresponding to stiffness, sufficed to explain similarity data, while two perceptual dimensions were needed in the former condition. This demonstrates how multidimensional scaling analysis can be used in the evaluation of haptic renderin g scenarios, providing perceptual maps of real and virtual objects. It offers an opportunity to visualize and quantify the perceptual effects of changes in rendering parameters

Design and Evaluation of Haptic Soft Tissue Interaction

This chapter examines the application of a psychophysical evaluation technique to quantify the fidelity of haptic rendering methods. The technique is based on multidimensional scaling analysis of similarity ratings provided by users comparing pairs of haptically-presented objects. Unbeknownst to the participants, both real and virtual deformable objects were presented. In addition, virtual objects were either rendered under high fidelity condition or under lower-fidelity condition in which filtering quality was reduced. The analysis of pairwise similarity data provides quantitative confirmation that users perceived a clear difference between real and virtual objects in the lower-fidelity, but not in the higher-fidelity condition. In the latter, a single perceptual dimension, corresponding to stiffness, sufficed to explain similarity data, while two perceptual dimensions were needed in the former condition. This demonstrates how multidimensional scaling analysis can be used in the evaluation of haptic renderin g scenarios, providing perceptual maps of real and virtual objects. It offers an opportunity to visualize and quantify the perceptual effects of changes in rendering parameters