Open AccessOn the relation between brain images and brain neural networks
Author(s) -
Taylor J.G.,
Krause B.,
Shah N.J.,
Horwitz B.,
MuellerGaertner H.W.
Publication year - 2000
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/(sici)1097-0193(200003)9:3<165::aid-hbm5>3.0.co;2-p
Subject(s) - artificial neural network , neural activity , covariance , brain activity and meditation , artificial intelligence , computer science , relation (database) , neuroscience , electroencephalography , domain (mathematical analysis) , structural equation modeling , pattern recognition (psychology) , psychology , mathematics , machine learning , mathematical analysis , data mining , statistics
The relationship between brain images observed by PET and fMRI and the underlying neural activity is analysed using recent results on the detailed nature of averaged and synchronised activity of coupled neural networks and on a simplifying model of the level of blood flow caused by neural activity. The conditions on the coupled neural systems are specified that lead to structural equation models, giving support to analysis of the covariance structural equation modelling of brain imaging data. The relation between the resulting models and possible neural codes are analysed. Furthermore, a new form of structural equation model is derived, in which all neuronal activity arises as hidden variables. We discuss how the results of such analyses can be transported back to the domain of coupled temporally dynamic neural systems in the brain appropriate to EEG and MEG observations. Hum. Brain Mapping 9:165–182, 2000. © 2000 Wiley‐Liss, Inc.