Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images

We propose a novel hierarchical, nonlinear model that predicts brain activity in area V1 evoked by natural images. In the study reported here brain activity was measured by means of functional magnetic resonance imaging (fMRI), a noninvasive technique that provides an indirect measure of neural activity pooled over a small volume ( 2mm cube) of brain tissue. Our model, which we call the V-SPAM model, is based on the reasonable assumption that fMRI measurements reflect the (possibly nonlinearly) pooled, rectified output of a large population of

• Type: Conference
• Year: 2008
• Where: NIPS
• Authors: Pradeep Ravikumar, Vincent Q. Vu, Bin Yu, Thomas Naselaris, Kendrick Kay, Jack L. Gallant
• Keywords: Brain Activity, Functional Magnetic Resonance Imaging, Information Technology, NIPS 2008, Nonlinear Model