TY - JOUR

T1 - Neural correlates of mathematical problem solving

AU - Lin, Chun Ling

AU - Jung, Melody

AU - Wu, Ying Choon

AU - She, Hsiao-Ching

AU - Jung, Tzyy Ping

PY - 2015/3/25

Y1 - 2015/3/25

N2 - 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.

AB - 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.

KW - electroencephalogram (EEG)

KW - Mathematical problem solving

KW - solution latencies (SLs)

UR - http://www.scopus.com/inward/record.url?scp=84928409153&partnerID=8YFLogxK

U2 - 10.1142/S0129065715500045

DO - 10.1142/S0129065715500045

M3 - Article

C2 - 25666500

AN - SCOPUS:84928409153

SN - 0129-0657

VL - 25

JO - International Journal of Neural Systems

JF - International Journal of Neural Systems

IS - 2

M1 - 1550004

ER -