title: Integrating neuroscientific data across spatiotemporal scales.
abstract: A major challenge confronting neuroscientists is associated with the multiple spatial and temporal scales of investigation of neural structure and function. I shall discuss the use of computational neural modeling as one method to bridge some of the different spatial and temporal levels. This approach will be illustrated using large-scale, neurobiologically realistic network models of auditory and visual pattern recognition that relate neuronal dynamics to fMRI data. It will be demonstrated that the models are capable of exhibiting the salient features of both electrophysiological neuronal activities and fMRI values that are in agreement with empirically observed data.
authors.affiliation: Brain Imaging and Modeling Section, National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bldg. 10, Rm. 6C420 MSC 1591, Bethesda, MD 20892, USA. horwitz@helix.nih.gov
authors.forename: Barry
authors.initials: B
authors.lastname: Horwitz
mesh_terms: D000818:Animals; D001306:Auditory Pathways / Q000502:physiology; D006801:Humans; D008279:Magnetic Resonance Imaging; D008959:Models, Neurological; D009474:Neurons / Q000166:cytology / Q000502:physiology*; D009488:Neurosciences / Q000379:methods*; D010465:Perception; D014795:Visual Pathways / Q000502:physiology