Towards an Estimate of the Neural Information of the BOLD Signal
published: Dec. 3, 2012, recorded: September 2012, views: 2338
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
The blood oxygen level dependent (BOLD) signal as measured by functional magnetic resonance imaging (fMRI) has become a standard marker of neural activity. The relationship between neural activity and its hemodynamic response is characterized by complex spatiotemporal dynamics. Most analyses rely on simple models of neurovascular coupling and thus underestimate the neural information in the BOLD signal. We use machine learning methods to obtain a model free estimate of the neural information in BOLD contrast data from simultaneous recordings of high resolution fMRI signals and intracranially measured neural bandpower signals. These estimates can help to guide parameter selection in fMRI studies for optimal decoding of stimulus information and might serve as a baseline to which studies without intracranial neural measurements can be compared.
Download slides: bbci2012_biessmann_neural_information_01.pdf (4.0 MB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !