Interdisciplinary collaborations at work in brain-machine interfacing

Intention Concepts and Brain-Machine Interfacing

Intentions, including their temporal properties and semantic content, are receiving increased attention, and neuroscientific studies in humans vary with respect to the topography of intention-related neural responses. This may reflect the fact that the kind of intentions investigated in one study may not be exactly the same kind investigated in the other. Fine-grained intention taxonomies devel...

Immersive Empathic Design for Interdisciplinary Collaborations

Machine Learning and Applications for Brain-Computer Interfacing

This paper discusses machine learning methods and their application to Brain-Computer Interfacing. A particular focus is placed on linear classification methods which can be applied in the BCI context. Finally, we provide an overview on the Berlin-Brain Computer Interface (BBCI).

Brain-machine interfacing control of whole-body humanoid motion

We propose to tackle in this paper the problem of controlling whole-body humanoid robot behavior through non-invasive brain-machine interfacing (BMI), motivated by the perspective of mapping human motor control strategies to human-like mechanical avatar. Our solution is based on the adequate reduction of the controllable dimensionality of a high-DOF humanoid motion in line with the state-of-the...

Supplementary Information for GraphSpace: Stimulating Interdisciplinary Collaborations in Network Biology

Department of Computer Science, Virginia Tech, Blacksburg, VA, USA Biology Department, Reed College, Portland OR, USA Department of Statistics, Virginia Tech, Blacksburg, VA, USA RedOwl Analytics, San Francisco, CA, USA Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO, USA Center ...