Images of the Mind: Brain Images and Neural Networks

• Authors: John G. Taylor
• Venue: Emergent Neural Computational Architectures Based on Neuroscience - Towards Neuroscience-Inspired Computing
• Year: 2001

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 techniques presently being used 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 artificial neural networks concludes the article.