Functional magnetic resonance imaging (fMRI) is increasingly recognized as a standard technique for brain mapping and determining the connectivity between cortical regions. Statistical approaches to determining cortical connectivity, e.g. structural equation modeling between various regions of interest in the active brain can be computationally inefficient. This study explores the utility of a Hopfield neural network to determine cortical connectivity in an fMRI data set.
- Artificial neural networks
- Functional magnetic resonance imaging
- Neural network
ASJC Scopus subject areas
- Computer Science Applications
- Cognitive Neuroscience
- Artificial Intelligence