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 language | English (US) |
---|---|
Pages | 878-883 |
Number of pages | 6 |
State | Published - 2001 |
Externally published | Yes |
Event | International Joint Conference on Neural Networks (IJCNN'01) - Washington, DC, United States Duration: Jul 15 2001 → Jul 19 2001 |
Other
Other | International Joint Conference on Neural Networks (IJCNN'01) |
---|---|
Country/Territory | United States |
City | Washington, DC |
Period | 7/15/01 → 7/19/01 |
ASJC Scopus subject areas
- Software
- Artificial Intelligence