Predicting human functional maps with neural net modeling

Formidable difficulties exist in interpreting positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) hemodynamic signals in terms of the underlying neural activity. These include issues of spatial and temporal resolution and problems relating neuronal activity (i.e., act ion potentials) measured in nonhuman studies by single unit electrodes to h emodynamic measurements reflecting synaptic activity. Also, regional hemody namic measurements correspond to a mixture of local and afferent synaptic a ctivity. To surmount these difficulties, we propose using large-scale neuro biologically realistic models in which data at various spatial and temporal levels can be simulated and cross-validated by multiple disciplines, inclu ding functional neuroimaging. A delayed match-to-sample visual task is used to illustrate this approach. (C) 1999 Wiley-Liss, Inc.