Download Advances in Artificial/Computational Intelligence and Neuroscience

AI-2010 Thirtieth SGAI International Conference on Artificial Intelligence
CAMBRIDGE, ENGLAND 14-16 DECEMBER 2010
Workshop on
Advances in Artificial/Computational Intelligence and Neuroscience for BrainComputer Interfaces
Organizer:- Dr. Damien Coyle, Intelligent Systems Research Centre, University of Ulster, Northern
Ireland ([email protected])
Program
Stream 1 – Afternoon 14th December (15.15-16.45 and 17.00-18.30 Upper Hall)
15.15 An Introduction to BCIs and applying AI in BCI designs
Dr Damien Coyle, Intelligent System Research Centre, University of Ulster
BCI technology enables communication which does not rely on neuromuscular control thereby offering
assistance to those who require alternative communicatory and control mechanisms because of
neuromuscular deficiencies due to disease, or spinal/brain damage. BCIs have advanced significantly in
the past few years but there remain a significant number of problems and issues to be resolved due to
the high level of noise, and the non-stationary nature of the neural signals used in BCI. This presentation
will introduce the basics of BCIs, focusing in particular on how non-invasive movement imagination
(motor imagery) based BCIs operate and how information is extracted from the electroencephalogram
(EEG) using a range of methods. Details of how Artificial/Computational Intelligence based techniques,
including particle swarm optimization (PSO) and self-organizing fuzzy neural networks (SOFNN) amongst
others, are deployed for processes such as data preprocessing, feature extraction, classification,
unsupervised adaptation and prediction in a complete BCI system will be presented along with a
demonstration of BCI controlled games and robots.
15.45 ERP based BCIs, past, present and future
Dr Mathew Salvaris, Brain Computer Interfaces Group, University of Essex
ERP based BCIs, past, present and future?
The field of non-invasive Brain Computer Interfaces (BCIs) has grown significantly over the past
decade. As our understanding of the cognitive processes we seek to harness improves so do the
tools used to analyse and interpret them. With these seemingly perpetual advances it is hoped
that one day efficient non-invasive BCIs will becomes a reality. P300 based BCIs are often
considered a practical choice since they require little training yet boast some of the fastest
information transfer rates in non-invasive BCIs. Even with their viability broadly established
many hurdles still remain, including the seemingly inherent limitations of such paradigms. In
this seminar the past, present as well as possible future of P300 and more generally ERP based
BCIs will be discussed.
16.15 Plasticity at the Brain-Computer Interface
Dr Andrew Jackson, Institute of Neuroscience, Newcastle University
The brain has a remarkable ability to learn new motor tasks, for example playing sports or
musical instruments. Neuroscience has begun to understand mechanisms underlying this ability
emphasizing, for example, the importance of adaptive internal models for feed-forward control
and the optimisation of behaviour to cope with noisy signals. Brain-Computer Interfaces (BCIs)
present new challenges to the brain, and skilful control will require users to incorporate them
into their motor repertoire. BCI paradigms also present a unique opportunity to study directly
the neural correlates of motor learning, as they represent simplified experimental models of
the complex sensori-motor interactions that govern normal behaviour. I will describe
experiments in humans and monkeys that reveal how activity in the motor system combines
with sensory feedback to shape neural connectivity and drive adaptation of behaviour. We
hope that by elucidating these mechanisms, a new generation of intelligent BCIs can be
designed to exploit neural plasticity and become incorporated as natural extensions of the
motor system.
Break 16.45
17.00 Robot Animats: investigating the computational capacity of cultured neuronal
networks in a closed loop
Dr Slawomir Nasuto, Cybernetic Intelligence Research Group, University of Reading
Animats, a type of Brain Machine Interfaces, are hybrid platforms in which the nervous system
forms a part of a closed loop with an artefact. Such systems enable study of the neural
information processing, sensory motor coupling as well as dynamics of the nervous structures.
They also are very promising tools in studying the most fundamental problems in cognitive
robotics.
The long term goals for research in BMI in general and in Animats in particular is to provide
severely disabled with functional communication channels with the external world, to provide
alternative experimental platforms for drug testing and to lead to the next generation ‘semisentient’ robot companions.
The talk will overview the wider area of the Brain Machine Interfaces and will then discuss the
research performed at Reading on the ‘rat-brain robot’
17.30 Taking Brain-computer interfaces into people’s home: The challenges ahead
Dr Francisco Sepulveda, Brain Computer Interfaces Group, University of Essex
Brain-computer interfaces have become the latest fad in the computer games community and
may soon be commercialized for various other domestic applications, especially in North
America. However, the commercial devices available today rely mostly on inexpensive wetelectrode technology or on high-noise dry electrodes. Either way the devices use very low
quality signals and it is unlikely that they use brain signals alone, thus making the usual
‘thought-based control’ claim more a marketing coup than reality. Nonetheless, the technology
does have potential for serious and ethical commercial exploration in the near future, if not
necessarily now. In this seminar I will discuss my views on what directions the UK’s R&D BCI
community needs to take in order to bring the technology out of the laboratory and into the
‘real world’.
18.00 Discussion and Panel Questions
End 18.30
Workshop over view
Brain-computer interface (BCI) research is growing at a significant pace and, since the beginning of the
21st century, has seen explosive growth. The depth and breadth of BCI research in progress today is
indicative of its application potential – this is exemplified by the year-on-year exponential increase in
peer review journal publications, regular news items in the media, formation of BCI related companies
and substantial investment in BCI-specific projects. BCI technology enables communication which does
not rely on neuromuscular control thereby offering assistance to those who require alternative
communicatory and control mechanisms because of neuromuscular deficiencies due to disease, or
spinal/brain damage. Other applications of BCI include neurofeedback for stroke rehabilitation, the
treatment of attention deficit disorder, driver alertness detection and electrophysiologically interactive
computer systems and gaming. BCI can also be applied to monitor, maintain, or track human cognitive
functions such as their perception, attention, awareness and decision making in daily life activities and
BCI based biofeedback can be used to augment human performance. There have been many advances
but there are still a significant number of problems and issues to be resolved. The non-stationary nature
of the EEG poses a major challenge for the successful exploitation of non-invasive BCIs and can be due
to unstable recordings, varying mental and behavioral states caused by fatigue or stress or the inherent
adaptive nature of the brain itself, which modifies its activity to the subject’s/user's experience. There
are still many advances necessary before complete brain-computer symbiosis is achieved, as outlined by
Schalk (2008). It is generally accepted that there is a communication bottleneck between the brain and
computer due to the low communication speed supported by our nervous system. Our brain uses highly
complex semantic relationships to put the input to the brain in context yet we use syntactic commands
(not semantic) when we communicate with the computer, making communication less efficient. To
exploit the brain's resources and bypass the communication bottleneck through high information
transfer (IT) rate BCIs we also need to develop a better understanding of the coding scheme the brain
actually uses to encode information, the dynamics of behavior, the predictive nature of the
sensorimotor internal models and the adaptive nature of the brain. To tackle these issues we believe the
Computational Intelligence and Computational Neuroscience communities are well placed and BCI is an
ideal domain for the study and application of Computationally Intelligent algorithms.
A workshop on the application of Artificial/Computational Intelligence in Brain-Computer Interface will
be held at the Thirtieth SGAI International Conference on Artificial Intelligence (AI-2010). The aim is to
present the state-of-the-art in BCI systems developed by some of the BCI laboratories and groups in the
UK. BCI systems require intelligence to allow BCI users to communicate and control their environment
using weak and noisy signals from the brain. This may be achieved through complex and adaptable
biosignal processing tools, as well as intelligent control and environment manipulation in BCI
applications such as prostheses, robotics and cognitive feedback.
The workshop will include introductory material and outline the application of AI/CI in the field of BrainComputer Interface as well as neuroscience and computational modelling studies relevant to BCI designs
and signal processing. In BCI applications and biosignal processing and analysis the objective may be to
differentiate between signals from different domains, uniquely fingerprint signals for identification,
feature extraction, classification, modelling, prediction and more and therefore this workshop should be
off interest to a wide audience of AI researchers.