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. 2025 May 6;4(2):e70105.
doi: 10.1002/pcn5.70105. eCollection 2025 Jun.

Investigating the association of self-image and brain maps in medical students: A quantitative electroencephalography study

Hamid Dehghan  1 , Arvin Hedayati  2 , Arash Mani  3
Affiliations

Investigating the association of self-image and brain maps in medical students: A quantitative electroencephalography study

Hamid Dehghan et al. PCN Rep. .

Abstract

Aim: Self-image, conceived as one's mental blueprint and a composite of thoughts, is among the hotly debated topics in psychology. Exploring the brain's structure, functionality, and physiology has also proven crucial in understanding one's self-image. In this vein, the current study aimed to examine the relationship between quantitative electroencephalography (QEEG) findings and medical students' self-image.

Methods: To measure self-image, the Offer Self-Image Questionnaire and, for the QEEG findings, a Mitsar EEG-202 device were used. To analyze the QEEG findings, the FDA-approved Neuroguide software was utilized.

Results: In the first phase, out of the 93 questionnaires returned, the maximum score, on a scale of 1 to 6, was 5.52 and the minimum was 2.36. Hence, it could be argued that the medical students who took part in this study had relatively high self-images. Results, however, showed no significant difference between the two genders regarding either their overall self-image score or any of its subcategories. In the second phase, the QEEG analyses of high- and low-self-image students suggested a statistically significant difference in their θ signal of the frontal lobes. Further analysis indicated that the difference was not localized to any single lead or lobe, but pertained to the overall function of the prefrontal cortices.

Conclusion: The relationship observed between medical students' self-image and their brain θ waves could contribute to a better understanding of people's cognitive functions.

Keywords: QEEG; brain map; gender; medical students; prefrontal lobe; self‐image.

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Conflict of interest statement

The authors declare that they have no competing interests. Although this study was partially supported by Shiraz University of Medical Sciences, study design and procedures were designed by the authors themselves. The mentioned support was received as a student grant and therefore the authors retain full publishing rights for the paper.

Figures

Figure 1
Figure 1
Quantitative electroencephalography (QEEG) signals as analyzed by software. QEEG is generally a complex recording of many waves. The measurements are fed through software that analyzes and pulls apart these different waves and categorizes them based on the wavelengths. The results shown are the δ (longest wavelength), θ, α, and β (shortest wavelength) waves, which are then used to examine different brain functions.
Figure 2
Figure 2
Quantitative electroencephalography records signals using special devices that have a certain number of electrodes. These electrodes are placed on different locations on the subjects' scalps. A sample diagram of electrode placement, which was used for the purposes of the current study, is shown.
Figure 3
Figure 3
The quantitative electroencephalography software also provides visual representations of the brain waves. Different wave amplitudes are shown with different colors for easier understanding. The final illustrations are called brain maps and are used for interpretation. Two sample brain maps from the current study are portrayed in this figure for comparison; one map belongs to a subject with a high self‐image level and the other to a subject with a low self‐image level. (a) belongs to a high self‐image subject and (b) to a low self image one.
See this image and copyright information in PMC

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