RECOGNITION MEMORY STATES BASED ON DISTRIBUTED PATTERNS OF FMRI

Stanford University, Stanford CA

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Abstract

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. While the brain responds differently when it experiences a novel sensory stimulus as compared to a previously encountered stimulus, conventional functional magnetic resonance imaging (fMRI) data analysis approaches, utilizing univariate statistics to compare voxel activity levels across task conditions, cannot reliably capture these mnemonic effects on single trials. We sought to exploit the wealth of information represented in distributed fMRI activity patterns, using a multi-voxel pattern analysis approach to decode the mnemonic status of individual stimuli. Prior to scanning, participants studied 200 color photographs of human faces. Subsequently, participants were scanned while they made recognition memory decisions about the 200 studied faces intermixed with 200 novel faces. For each test face, participants indicated whether they 1) recollected having studied the face, 2) were highly confident they studied it, 3) thought they studied it, 4) thought they did not study it, or 5) were highly confident they did not study it.