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What Neural Substrates Trigger the Adept Scientific Pattern Discovery by Biologists?

  • Jun Ki Lee
  • , Yong Ju Kwon*
  • *Corresponding author for this work
  • Korea National University of Education
  • Massachusetts General Hospital

Research output: Contribution to journalJournal articlepeer-review

Abstract

This study investigated the neural correlates of experts and novices during biological object pattern detection using an fMRI approach in order to reveal the neural correlates of a biologist's superior pattern discovery ability. Sixteen healthy male participants (8 biologists and 8 non-biologists) volunteered for the study. Participants were shown fifteen series of organism pictures and asked to detect patterns amid stimulus pictures. Primary findings showed significant activations in the right middle temporal gyrus and inferior parietal lobule amongst participants in the biologist (expert) group. Interestingly, the left superior temporal gyrus was activated in participants from the non-biologist (novice) group. These results suggested that superior pattern discovery ability could be related to a functional facilitation of the parieto-temporal network, which is particularly driven by the right middle temporal gyrus and inferior parietal lobule in addition to the recruitment of additional brain regions. Furthermore, the functional facilitation of the network might actually pertain to high coherent processing skills and visual working memory capacity. Hence, study results suggested that adept scientific thinking ability can be detected by neuronal substrates, which may be used as criteria for developing and evaluating a brain-based science curriculum and test instrument.

Original languageEnglish
Pages (from-to)117-122
Number of pages6
JournalJournal of Science Education and Technology
Volume20
Issue number2
DOIs
StatePublished - 2011.04

Keywords

  • Adept pattern discovery
  • Biological pattern discovery
  • Brain-based science curriculum
  • fMRI
  • Neural substrates of scientific discovery
  • Parieto-temporal network

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