Simulating PET/fMRI studies of visual and auditory pattern recognition using biologically realistic large-scale neural models

B. Horwitz, F. T. Husain, A. R. Braun, M. A. Tagamets

Research output: Contribution to conferencePaperpeer-review

Abstract

Formidable conceptual problems exist in interpreting human functional neuroimaging data in terms of the underlying neural activity. To surmount these difficulties, we have developed two neurobiologically realistic models (one for vision, one for audition) of the object recognition pathway in human neocortex in which data at multiple spatiotemporal levels can be simulated and cross-validated by multiple disciplines, including PET and fMRI. Our models, based on neurophysiological and neuroanatomical data from primate and human studies, enable us to simultaneously simulate cellular electrophysiological and PET/fMRI activities in multiple, interconnected brain regions. These types of models enable us to quantitatively combine multiple data sets so that a coherent account of human cognition can be generated. We illustrate this approach using delayed match-to-sample (DM8) tasks for visual shape and for auditory tonal patterns.

Original languageEnglish (US)
Pages878-883
Number of pages6
StatePublished - Jan 1 2001
Externally publishedYes
EventInternational Joint Conference on Neural Networks (IJCNN'01) - Washington, DC, United States
Duration: Jul 15 2001Jul 19 2001

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'01)
CountryUnited States
CityWashington, DC
Period7/15/017/19/01

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Simulating PET/fMRI studies of visual and auditory pattern recognition using biologically realistic large-scale neural models'. Together they form a unique fingerprint.

Cite this