The impact of training methodology and representation on rule-based categorization: An fMRI study

Cogn Affect Behav Neurosci. 2021 Aug;21(4):717-735. doi: 10.3758/s13415-021-00882-0. Epub 2021 Apr 6.

Abstract

Hélie, Shamloo, & Ell (2017) showed that regular classification learning instructions (A/B) promote between-category knowledge in rule-based categorization whereas conceptual learning instructions (YES/NO) promote learning within-category knowledge with the same categories. Here we explore how these tasks affect brain activity using fMRI. Participants learned two sets of two categories. Computational models were fit to the behavioral data to determine the type of knowledge learned by each participant. fMRI contrasts were computed to compare BOLD signal between the tasks and between the types of knowledge. The results show that participants in the YES/NO task had more activity in the pre-supplementary motor area, prefrontal cortex, and the angular/supramarginal gyrus. These brain areas are related to working memory and part of the dorsal attention network, which showed increased task-based functional connectivity with the medial temporal lobes. In contrast, participants in the A/B task had more activity in the thalamus and caudate. These results suggest that participants in the YES/NO task used bivalent rules and may have treated each contextual question as a separate task, switching task each time the question changed. Activity in the A/B condition was more consistent with participants applying direct Stimulus → Response rules. With regards to knowledge representation, there was a large shared network of brain areas, but participants learning between-category information showed additional posterior parietal activity, which may be related to the inhibition of incorrect motor programs.

Keywords: Category representation; Rule-based categorization; fMRI.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Brain / diagnostic imaging
  • Brain Mapping
  • Concept Formation*
  • Humans
  • Learning
  • Magnetic Resonance Imaging*