Research Papers: Neuroscience:
Analysis of the influence of memory content of auditory stimuli on the memory content of EEG signal
Metrics: PDF 512 views | HTML 1411 views | ?
Hamidreza Namazi1, Reza Khosrowabadi2,*, Jamal Hussaini3,*, Shaghayegh Habibi4,**, Ali Akhavan Farid5,** and Vladimir V. Kulish1
1 School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
2 Institute for Cognitive and Brain Science, Shahid Beheshti University, Tehran, Iran
3 Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh, Selangor, Malaysia
4 School of Medicine, Fasa University of Medical Sciences, Fasa, Iran
5 Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia
* These authors have contributed equally to this work
** These authors have contributed equally to this work
Hamidreza Namazi, email:
Keywords: auditory stimulus, electroencephalogram (EEG) signal, memory, Hurst exponent, approximate entropy
Received: June 04, 2016 Accepted: July 29, 2016 Published: August 11, 2016
One of the major challenges in brain research is to relate the structural features of the auditory stimulus to structural features of Electroencephalogram (EEG) signal. Memory content is an important feature of EEG signal and accordingly the brain. On the other hand, the memory content can also be considered in case of stimulus. Beside all works done on analysis of the effect of stimuli on human EEG and brain memory, no work discussed about the stimulus memory and also the relationship that may exist between the memory content of stimulus and the memory content of EEG signal. For this purpose we consider the Hurst exponent as the measure of memory. This study reveals the plasticity of human EEG signals in relation to the auditory stimuli. For the first time we demonstrated that the memory content of an EEG signal shifts towards the memory content of the auditory stimulus used. The results of this analysis showed that an auditory stimulus with higher memory content causes a larger increment in the memory content of an EEG signal. For the verification of this result, we benefit from approximate entropy as indicator of time series randomness. The capability, observed in this research, can be further investigated in relation to human memory.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.