The Existence of Two Variant Processes in Human Declarative Memory: Evidence Using Machine Learning Classification Techniques in Retrieval Tasks

This work use supervised machine learning methods on fMRI brain scans, taken/measured during a memory-retrieval task, to support establishing the existence of two distinct systems for human declarative memory (“Explicit Encoding” (EE) and “Fast Mapping” (FM)). The importance of using retrieval is that it allows a direct comparison between exemplars designed to use EE and those designed to use FM. This is not directly available under acquisition tasks because of the nature of the purported memory systems since the tasks are necessarily somewhat distinct between the two systems under acquisition. This means that there could be a confounding of the distinction in the task with the difference in the representation and mechanism of the internal memory system during analysis. Retrieval tasks, on the other hand allow for identity of task. Thus this work fills a lacuna in earlier work which used memory acquisition tasks. In addition, since the data used in this work was gathered over a two day period, the classification methods is also able to identify a distinction in the consolidation of the memories in the two systems. The results presented here clearly support the existence of the two distinct memory systems.