Abstract
This paper presents a detailed architecture model for the Brain Imaging Network Grid (BING) that will be the main IT infrastructure of the recently created Portuguese Brain Imaging Consortium. The proposed architecture follows a service oriented philosophy and is designed to empower medical data sharing and processing, specifically brain images. Allowing the use of computationally intensive methods like feature extraction and retrieving of structured information, this system will take advantage of Grid computing new paradigm. In BING context, Grid infrastructure is the right option to provide the ability to seamless aggregate distributed computational power, extensive storage resources and high-bandwidth networking. The goal is to develop a system that simultaneously can provide basic data services, allow collaborative research between geographically distributed partners (e.g. analysis processes, workflows) and make use of the Grid computational power.

Abstract
Recent advances in computer hardware and signal processing assert that controlling certain functions by thoughts may represent a landmark in the way we interact with many output devices. This paper exploits the possibility of achieving a communication channel between the brain and a mobile robot through the modulation of the electroencephalogram (EEG) signal during motor imagery tasks. A major concern was directed towards designing a generalized and multi-purpose framework that supports rapid prototyping of various experimental strategies and operating modes. Preliminary results of brain-state estimation using EEG signals recorded during a self-paced left/right hand movement task are also presented. The user successfully learned to operate the system and how to better perform the motor-related tasks based on outcomes produced by its mental focus.

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