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Background: Sleep slow oscillations (SOs), characteristic of NREM sleep, are causally tied to cognitive outcomes and the health-promoting homeostatic functions of sleep. Due to these known benefits, brain stimulation techniques aiming to enhance SOs are being developed, with great potential to contribute to clinical interventions, as they hold promise for improving sleep functions in populations with identified SO deficits (e.g., mild cognitive impairment). SO-targeting closed-loop stimulation protocols currently strive to identify SO occurrences in real time, a computationally intensive step that can lead to reduced precision (compared to post-hoc detection). These approaches are also often limited to focusing on only one electrode location, thus inherently precluding targeting of SOs that is informed by the overall organization of SOs in space-time. Prediction of SO emergence across the electrode manifold would establish an alternative to online detection, thus greatly advancing the development of personalized and flexible brain stimulation paradigms. This study presents a computational model that predicts SO occurrences at multiple locations across a night of sleep. In combination with our previous study on optimizing brain stimulation protocols using the spatiotemporal properties of SOs, this model contributes to increasing the accuracy of SO targeting in brain stimulation applications. Methods: SOs were detected in a dataset of nighttime sleep of 22 subjects (9 females), acquired with polysomnography including 64 EEG channels. Modeling of SO occurrence was achieved for SOs in stage N3, or in a combination of stages N2 and N3 (N2&N3). We study SO emergence at progressively more refined time scales. First, the cumulative SO occurrences in successive sleep cycles were successfully fit with exponentials. Secondly, the SO timing in each individual was modeled with a renewal point process. Using an inverse Gaussian model, we estimated the probability density function of SO timing and its parameters µ (mean) and λ (shape, representing skewness) in successive cycles. Results: We observed a declining trend in the SO count across sleep cycles, which we modeled using a power law relationship. The decay rate per cycle was 1.473 for N3 and 1.139 for N2&N3, with variances of the decay rates across participants being 1 and 0.53, respectively. This pattern mirrors the declining trend of slow wave activity (SWA) across sleep cycles, likely due to the inherent relationship between SWA and SO. Additionally, the SO timing model for N3 showed an increasing trend in the model parameters (µ, λ) across cycles. The increase rate per cycle followed a power law relationship with a rate of 0.83 and an exponential relationship with a rate of 4.59, respectively. The variances of the increase rates were 0.02 for µ and 0.44 for λ across participants. Conclusion: This study establishes a predictive model for SO occurrence during NREM sleep, providing insights into its organization in successive cycles and at different EEG channels, which is relevant to development of personalized stimulation paradigms. These findings imply that personalized model parameters can be estimated by incorporating SO information in the first sleep cycle, and hence SO timing can be predicted before its occurrence with a probability distribution, enabling more precise targeting of SOs.
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Background: Given sleep's crucial role in health and cognition, numerous sleep-based brain interventions are being developed, aiming to enhance cognitive function, particularly memory consolidation, by improving sleep. Research has shown that Transcranial Alternating Current Stimulation (tACS) during sleep can enhance memory performance, especially when used in a closed-loop (cl-tACS) mode that coordinates with sleep slow oscillations (SOs, 0.5-1.5Hz). However, sleep tACS research is characterized by mixed results across individuals, which are often attributed to individual variability. Objective/Hypothesis: This study targets a specific type of SOs, widespread on the electrode manifold in a short delay ("global SOs"), due to their close relationship with long-term memory consolidation. We propose a model-based approach to optimize cl-tACS paradigms, targeting global SOs not only by considering their temporal properties but also their spatial profile. Methods: We introduce selective targeting of global SOs using a classification-based approach. We first estimate the current elicited by various stimulation paradigms, and optimize parameters to match currents found in natural sleep during a global SO. Then, we employ an ensemble classifier trained on sleep data to identify effective paradigms. Finally, the best stimulation protocol is determined based on classification performance. Results: Our study introduces a model-driven cl-tACS approach that specifically targets global SOs, with the potential to extend to other brain dynamics. This method establishes a connection between brain dynamics and stimulation optimization. Conclusion: Our research presents a novel approach to optimize cl-tACS during sleep, with a focus on targeting global SOs. This approach holds promise for improving cl-tACS not only for global SOs but also for other physiological events, benefiting both research and clinical applications in sleep and cognition.
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INTRODUCTION: Correcting sexual beliefs can affect women's sexual function. There are very limited interventional studies on correcting the sexual dysfunction beliefs in postmenopausal women living in rural areas. Therefore, the present study was carried out with the aim of investigating the effect of a midwife-based group education on sexual dysfunction beliefs in one group of rural postmenopausal women. METHODS: The present study was a quasi-experimental pre-post design without a control group. The study population included rural menopausal women who referred to rural health centers. The study sample consisted of 50 participants who have all received education program. The education was held in six group discussion sessions. The data gathering tool used in this study was the Sexual Dysfunctional Beliefs Questionnaire which was completed before and after the education. This questionnaire consists of 33 items and includes 6 subscales. RESULTS: The mean age of participants was 53.26 years. Approximately half of the participants (48%) had primary education. The mean scores of sexual dysfunction beliefs before and after education were 114.58 and 58.56, respectively (p-value<0.001). The mean scores of sexual conersations, affection primacy, motherhood-related beliefs, sexual desire and pleasure as sin beliefs, age-related beliefs, and body image beliefs before intervention were 14.38, 21.38, 13.9, 23.64, 20.74, 17.04, respectively, and after intervention were 6.9, 11.80, 8.64, 12.48, 7.7, 9.40, respectively. CONCLUSION: Rural postmenopausal women had problems with sexual dysfunction beliefs. A midwife-based group discussion education on this matter had significantly improved the sexual dysfunction beliefs in them. Further studies are needed in this regard.
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OBJECTIVE: Melissa officinalis is a perennial herb from the Lamiaceae family which has shown to have modulating effects on serum lipid profile. The aim of the current study is to explore the effects of M. officinalis supplementation on serum biochemical parameters of patients with borderline hyperlipidemia. METHODS: 58 hyperlipidemic patients were allocated randomly to 2 groups: first group received capsules containing 1000mg M. officinalis leaf powder (MO group), and the second group received placebo capsules (P group) 3 times per day for 2 months. Fasting blood glucose (FBG), HDL, LDL, Triglyceride, Creatinine and liver function enzymes including AST and ALT were evaluated before and after study. RESULTS: The mean of LDL in MO group significantly decreased compared with P group after the supplementation (P=0.02). Although the level of Cholesterol, FBG, HDL, Triglyceride, Creatinine and ALT did not show significant difference between two groups after 2 months (P≥0.05), the level of AST exhibited a significant difference between two groups (P=0.009). CONCLUSIONS: Our findings demonstrated that M. officinalis supplementation as a rich source of antioxidants and bioactive compounds can be effective in remission of LDL and AST levels in patients with borderline hyperlipidemia.