Monitoring of learning is only accurate at some time after learning. It is thought that immediate monitoring is based on working memory, whereas later monitoring requires re-activation of stored items, yielding accurate judgements. Such interpretations are difficult to test because they require reverse inference, which presupposes specificity of brain activity for the hidden cognitive processes. We investigated whether multivariate pattern classification can provide this specificity. We used a word recall task to create single trial examples of immediate and long term retrieval and trained a learning algorithm to discriminate them. Next, participants performed a similar task involving monitoring instead of recall. The recall-trained classifier recognized the retrieval patterns underlying immediate and long term monitoring and classified delayed monitoring examples as long-term retrieval. This result demonstrates the feasibility of decoding cognitive processes, instead of their content.

Additional Metadata
Keywords Educational psychology, Functional MRI, Judgement of learning, Metacognition, Working memory
Persistent URL dx.doi.org/10.1016/j.neuroimage.2016.02.008, hdl.handle.net/1765/82038
Journal NeuroImage
Citation
Stiers, P, Falbo, L, Goulas, A, van Gog, T.A.J.M, & de Bruin, A.B.H. (2016). Reverse inference of memory retrieval processes underlying metacognitive monitoring of learning using multivariate pattern analysis. NeuroImage, 132, 11–23. doi:10.1016/j.neuroimage.2016.02.008