imagine-decoding-challenge

Can you decode which images people were thinking of from data recorded while they were visually seeing these images? In memory research, decoders are often trained on localizer data to extract neural activation patterns of specific stimuli (e.g., “what pattern occurs when we see a clown”). Taken as evidence for reprocessing, these decoders are then used to detect pattern presence in other parts of the experiment (e.g., “after learning something about clowns, we can see the activation pattern of ‘clown’ being more active than expected; that means knowledge is being consolidated”). But how well does this actually work? We recorded a simple paradigm in the Magnetoencephalograph (MEG) in which we showed ten different visual items many times to participants. Later, we played back spoken words describing the items while they had their eyes closed and asked them to mentally visualize the items associated with the word as vividly as possible. Can you train a decoder on the visual presentation (localizer) and decode which item people imagined? see https://github.com/skjerns/the-imagine-decoding-challenge/ and https://github.com/skjerns/imagine-decoding-challenge