The IDIAP Brain-Computer Interface: An Asynchronous Multi-Class Approach

In this paper we give an overview of our work on a self-pace asynchronous BCI that responds every 0.5 seconds. A statistical Gaussian classifier tries to recognize three different mental tasks; it may also respond unknown for uncertain samples as the classifier has incorporated statistical rejection criteria. We report our experience with different subjects. We also describe three brain-actuated applications we have developed: a virtual keyboard, a brain game, and a mobile robot (emulating a motorized wheelchair). Finally, we discuss current research directions we are pursuing in order to improve the performance and robustness of our BCI system, especially for real-time control of brain-actuated robots.

Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform

Ugo Albanese, Alessandro Ambrosano, Nino Cauli, Oliver Denninger, Stefan Deser, Egidio Falotico, Marc-Oliver Gewaltig, Luc Guyot, Georg Hinkel, Murat Kirtay, Paul Levi, Patrick Maier, Daniel Peppicelli, Igor Peric, Eduardo Ros, Stefan Ulbrich, Patrick Van Der Smagt, Lorenzo Vannucci, Axel von Arnim, Sandro Weber

Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain-body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 "Neurorobotics" of the Human Brain Project (HBP). 1 At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.

2017

Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform

2017