Future directions for neural networks and intelligent systems from the brain imaging research

An overview is given of recent results coming from non-invasive brain imaging (PET, fMRI EEG & MEG), and how these relate to, and illuminate, the underpinning neural networks. The main techniques are briefly surveyed and data analysis techniquest that are presently being used are reviewed. The results of the experiments are then summarised. The most important recent technique used in analysing PET and fMRI, that of structural modelling, is briefly described, results arising from it presented, and the problems this approach presents in bridging the gap to the underlying neural networks of the brain described. New neural networks approaches are summarised which are arising from these and related results, especially associated with internal models. The relevance of these for indicating future directions for the development of intelligent systems concludes the article.