Open AccessPredicting human functional maps with neural net modeling
Author(s) -
Horwitz Barry,
Tagamets M.A.
Publication year - 1999
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(1999)8:2/3<137::aid-hbm11>3.0.co;2-b
Subject(s) - neuroscience , neuroimaging , functional magnetic resonance imaging , hum , positron emission tomography , artificial intelligence , temporal resolution , functional imaging , premovement neuronal activity , afferent , brain activity and meditation , functional neuroimaging , computer science , brain mapping , magnetoencephalography , neural activity , psychology , pattern recognition (psychology) , electroencephalography , physics , quantum mechanics , art , performance art , art history
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., action potentials) measured in nonhuman studies by single unit electrodes to hemodynamic measurements reflecting synaptic activity. Also, regional hemodynamic measurements correspond to a mixture of local and afferent synaptic activity. To surmount these difficulties, we propose using large‐scale neurobiologically realistic models in which data at various spatial and temporal levels can be simulated and cross‐validated by multiple disciplines, including functional neuroimaging. A delayed match‐to‐sample visual task is used to illustrate this approach. Hum. Brain Mapping 8:137–142, 1999. © 1999 Wiley‐Liss, Inc.