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 -