Multilayered visuo-haptic hair simulation

Over the last fifteen years, research on hair simulation has made great advances in the domains of modeling, animation and rendering, and is now moving towards more innovative interaction modalities. The combination of visual and haptic interaction within a virtual hairstyling simulation framework represents an important concept evolving in this direction. Our visuo-haptic hair interaction framework consists of two layers which handle the response to the user’s interaction at a local level (around the contact area), and at a global level (on the full hairstyle). Two distinct simulation models compute individual and collective hair behavior. Our multilayered approach can be used to efficiently address the specific requirements of haptics and vision. Haptic interaction with both models has been tested with virtual hairstyling tools

DCM for complex-valued data: Cross-spectra, coherence and phase-delays

This note describes an extension of Bayesian model inversion procedures for the Dynamic Causal Modeling (DCM) of complex-valued data. Modeling complex data can be particularly useful in the analysis of multivariate ergodic (stationary) time-series. We illustrate this with a generalization of DCM for steady-state responses that models both the real and imaginary parts of sample cross-spectra. DCM allows one to infer underlying biophysical parameters generating data (like synaptic time constants, connection strengths and conduction delays). Because transfer functions and complex cross-spectra can be generated from these parameters, one can also describe the implicit system architecture in terms of conventional (linear systems) measures; like coherence, phase-delay or cross-correlation functions. Crucially, these measures can be derived in both sensor and source-space. In other words, one can examine the cross-correlation or phase-delay functions between hidden neuronal sources using non-invasive data and relate these functions to synaptic parameters and neuronal conduction delays. We illustrate these points using local field potential recordings from the subthalamic nucleus and globus pallidus, with a special focus on the relationship between conduction delays and the ensuing phase relationships and cross-correlation time lags between population activities