title: Network analysis of PET-mapped visual pathways in Alzheimer type dementia.
abstract: Using path analysis to determine the systems-level neural networks mediating specific tasks from regional cerebral blood flow (rCBF) data obtained by positron emission tomography (PET), we recently found in young subjects strong functional linkages during a face matching task along a right hemisphere ventral network including occipital, temporal, and frontal regions. In this study, PET data obtained during a face matching task from mildly affected patients with dementia of the Alzheimer type (DAT) and healthy matched controls showed that (1) the neural model obtained in young subjects provides a good fit to data from old subjects; (2) although the DAT patients could perform this task with the same accuracy as controls, they did not use the same functional network.
authors: Laboratory of Neurosciences, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA.
authors: B
authors: B
authors: Horwitz
authors: A R
authors: AR
authors: McIntosh
authors: J V
authors: JV
authors: Haxby
authors: M
authors: M
authors: Furey
authors: J A
authors: JA
authors: Salerno
authors: M B
authors: MB
authors: Schapiro
authors: S I
authors: SI
authors: Rapoport
authors: C L
authors: CL
authors: Grady
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000000981:diagnostic imaging / Q000503:physiopathology*; D002560:Cerebrovascular Circulation / Q000502:physiology; D003071:Cognition / Q000502:physiology; D005260:Female; D005625:Frontal Lobe / Q000098:blood supply / Q000000981:diagnostic imaging / Q000502:physiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D009415:Nerve Net / Q000000981:diagnostic imaging / Q000502:physiology*; D014055:Tomography, Emission-Computed; D014793:Visual Cortex / Q000098:blood supply / Q000000981:diagnostic imaging / Q000502:physiology; D014795:Visual Pathways / Q000000981:diagnostic imaging / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology