Detecting Individual Memories Through the Neural Decoding of Memory States and Past Experience

A wealth of neuroscientific evidence indicates that our brains respond differently to previously encountered than to novel stimuli. There has been an upswell of interest in the prospect that functional MRI (fMRI), when coupled with multivariate data analysis techniques, might allow the presence or absence of individual memories to be detected from brain activity patterns. This could have profound implications for forensic investigations and legal proceedings, and thus the merits and limitations of such an approach are in critical need of empirical evaluation. We conducted two experiments to investigate whether neural signatures of recognition memory can be reliably decoded from fMRI data. In Exp. 1, participants were scanned while making explicit recognition judgments for studied and novel faces. Multivoxel pattern analysis (MVPA) revealed a robust ability to classify whether a given face was subjectively experienced as old or new, as well as whether recognition was accompanied by recollection, strong familiarity, or weak familiarity. Moreover, a participant's subjective mnemonic experiences could be reliably decoded even when the classifier was trained on the brain data from other individuals. In contrast, the ability to classify a face's objective old/new status, when holding subjective status constant, was severely limited. This important boundary condition was further evidenced in Exp. 2, which demonstrated that mnemonic decoding is poor when memory is indirectly (implicitly) probed. Thus, although subjective memory states can be decoded quite accurately under controlled experimental conditions, fMRI has uncertain utility for objectively detecting an individual's past experiences.