EEG Analysis based on Spectral Edge Frequency during Mental Arithmetic Task

Brain dynamics variables and features are critical in electroencephalogram (EEG)-based human cognition research. They allow researchers to investigate how functionality changes based on the environment and how a task is carried out. This work gives a unique perspective of EEG analysis based on spectral edge frequency 50% (SEF50) methodologies to examine the differentiation of brain electrical activity during mental arithmetic task based on two circumstances (a) rest and task; and (b) mental arithmetic task success rate. According to our findings, the spectral edge frequency of the signals is increasing in beta and gamma-wave activity during mental arithmetic activities compared to rest state. In terms of performance, trends in the SEF50 curves indicate that average performers and bad performers likely expend more cognitive effort than good performers, particularly in higher-frequency ranges. Notably, the data revealed that frontal and pre-frontal brain regions indicate the brain activity compare to other brain regions. In conclusion, the SEF50 techniques used in this research are insightful and can be regarded as a feature of EEG data.