The topographic distribution of slow-wave activity (SWA, EEG power between 0.75 and 4.5 Hz) in non-rapid eye movement (NREM) sleep reflects typical age-related patterns of cortical maturation. At the same time, it is widely believed that sex differences in behavior (e.g., language) and structure (e.g., gray matter volume) are present in childhood. However, the manifestation of sex differences in sleep brain regions has not been studied in depth. Therefore, the present study explored whether gender dimorphic features are also reflected in the topography of sleep SWA.
Part.2
Method
Eleven boys and eleven girls were selected for the experiment. They had no significant age difference. Written informed consent for the experiment was obtained from the parents of the participants or from the adult participants. They were not subjected to any sleep disturbing factors until the experiment was conducted.
Part.3
Results
Sleep variables showed no significant differences between groups except that the percentage of slow wave sleep was higher in women than in men (Table 1).
During the first hour of non-REM sleep, the topographic distribution of SWA in females and males is shown in Figure 1a. Both groups showed a typical symmetrical SWA topography of local maxima and bilateral temporal power minima. We calculated the SWA ratio between females and males for each electrode (Fig. 1b). The results showed that females had higher SWA bilaterally in the temporal regions compared to males, while males had higher SWA in the central and frontal regions.
Further analysis revealed that SWA was significantly higher in right temporal lobe regions in females than in males (R2, p=0.008), with a significant trend in left temporal lobe regions (R1, p=0.052). In contrast, males had significantly higher SWA in the right frontal region than females (R3, p=0.048).
Part.4
talk over
We found that females showed higher SWA in language-related areas of the left and right brain compared to males of the same age, while males showed higher SWA in the right prefrontal cortex, which is related to spatial ability.
Compared to boys, girls showed greater cortical thickness in language-related brain regions, while no significant differences were found in the frontal brain region (R3). Differences in temporal and spatial resolution between EEG and MRI may have contributed to the deletion effect in R3.
One reason for the largest gender differences in SWA found on the right hemisphere may be that left-lateralized language functions are less pronounced in females than in males.
Part.5
Conclusion
During development, one sex exhibits higher sleep SWA in cortical control regions than the other, possibly indicating maturation of sex-specific brain functions and higher cortical plasticity.
Part.6
References
Burman, D.D., Bitan, T., Booth, J.R., 2008. sex differences in neural processing of language among children. neuropsychologia, 46, 1349- 1362.Kimura, D., 2000. Sex and Cognition. MIT Press, Cambridge, MA.Kurth, S., Ringli, M., Geiger, A., LeBourgeois, M., Jenni, O.G., Huber, R., 2010b. Mapping of cortical activity in the first two decades of life: a high- density sleep electroencephalogram study. Journal of Neuroscience, 30, 13211-13219.Luders, E., Gaser, C., Narr, K.L., Toga, A.W., 2009. why sex matters: brain size independent differences in gray matter distributions between men and women. Journal of Neuroscience, 29, 14265-14270.Plante, E., Schmithorst, V.J., Holland, S.K., Byars, A.W., 2006. Sex differences in the activation of language cortex during childhood. Neuropsychologia, 44, 1210-1221.Porter, J.N., Collins, P.F., Muetzel, R.L., Lim, K.O., Luciana, M., 2011. Associations between cortical thickness and verbal fluency in childhood, adolescence, and young adulthood. NeuroImage, 55, 1865-1877.Ringli, M., Kurth, S., Huber, R., & Jenni, O.G. (2013). The sleep EEG topography in children and adolescents shows sex differences in language areas.International Journal of Psychophysiology: Official Journal of the International Organization of Psychophysiology, 89(2), 241-245.Wolbers, T., Hegarty, M., 2010. what determines our navigational abilities? Trends in Cognitive Sciences, 14, 138-146.
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