Neural correlates of mathematical problem solving

Chun Ling Lin, Melody Jung, Ying Choon Wu, Hsiao-Ching She, Tzyy Ping Jung*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

This study explores electroencephalography (EEG) brain dynamics associated with mathematical problem solving. EEG and solution latencies (SLs) were recorded as 11 neurologically healthy volunteers worked on intellectually challenging math puzzles that involved combining four single-digit numbers through basic arithmetic operators (addition, subtraction, division, multiplication) to create an arithmetic expression equaling 24. Estimates of EEG spectral power were computed in three frequency bands-θ (4-7 Hz), α (8-13 Hz) and β (14-30 Hz)-over a widely distributed montage of scalp electrode sites. The magnitude of power estimates was found to change in a linear fashion with SLs-that is, relative to a base of power spectrum, theta power increased with longer SLs, while alpha and beta power tended to decrease. Further, the topographic distribution of spectral fluctuations was characterized by more pronounced asymmetries along the left-right and anterior-posterior axes for solutions that involved a longer search phase. These findings reveal for the first time the topography and dynamics of EEG spectral activities important for sustained solution search during arithmetical problem solving.

Original languageEnglish
Article number1550004
JournalInternational journal of neural systems
Volume25
Issue number2
DOIs
StatePublished - 25 Mar 2015

Keywords

  • electroencephalogram (EEG)
  • Mathematical problem solving
  • solution latencies (SLs)

Fingerprint

Dive into the research topics of 'Neural correlates of mathematical problem solving'. Together they form a unique fingerprint.

Cite this