دانلود مقاله تحلیل شبکه مغزی در افسردگی اضطرابی و غیر اضطرابی بر اساس بازسازی منبع EEG
خلاصه
1. معرفی
2. مواد و روش ها
3. نتایج
4. بحث
5. نتیجه گیری
اعلامیه منافع رقابتی
تصدیق
در دسترس بودن داده ها
منابع
Abstract
1. Introduction
2. Materials and methods
3. Results
4. Discussion
5. Conclusion
Declaration of Competing Interest
Acknowledgement
Data availability
References
چکیده
بیماران مبتلا به افسردگی مضطرب نسبت به بیماران مبتلا به افسردگی غیراضطرابی علائم شدیدتر، عوارض جانبی بیشتر و مقاومت بالاتری نسبت به درمان دارند. بنابراین، روشن کردن تفاوت بین این دو نوع بیمار بسیار مهم است. در این مطالعه، یک نوار مغزی 5 دقیقه‌ای استراحت در 15 بیمار مبتلا به افسردگی مضطرب و 9 بیمار مبتلا به افسردگی غیراضطرابی زیر چشم‌های باز و بسته ثبت شد. شصت و هشت ناحیه زیر قشری با استفاده از توموگرافی الکترومغناطیسی مغز با وضوح پایین (eLORETA) استخراج شد. سپس تابع انتقال هدایت شده برای ساخت شبکه های مغزی مورد استفاده قرار گرفت. ویژگی های خاص بر اساس تئوری گراف از جمله قدرت اتصال و مرکزیت بین (BC) از شبکه ها محاسبه شد. در نهایت، ویژگی‌های معنی‌دار با استفاده از آزمون Mann-Whitney U انتخاب شدند و بیماران با استفاده از ماشین بردار پشتیبان (SVM) به دو گروه افسردگی مضطرب و غیر مضطرب طبقه‌بندی شدند. نتایج نشان داد که ویژگی‌های قدرت اتصال به بیرون منجر به بالاترین دقت، امتیاز F و ویژگی به ترتیب با 91.66%، 87.5% و 100% در حالت چشم بسته است. علاوه بر این، ما دریافتیم که قدرت اتصال در هر دو جهت برای گروه افسرده مضطرب در حالت چشم باز افزایش یافته است. به ویژه، ارتباط بیرونی بالاتری در نیمکره راست برای گروه افسرده مضطرب مشاهده شد. یافته‌های بیشتر همچنین نشان داد که ویژگی‌هایی با بیشترین تفاوت عمدتاً با باند بتا مرتبط بودند. علاوه بر این، افزایش قابل توجه اتصال به داخل و خارج و کاهش مرکزیت گره در مناطق خلفی شبکه حالت پیش فرض مشاهده شد. این یافته های اولیه ممکن است بینش جدیدی را در مورد شناخت بیماران افسرده مضطرب ارائه دهد.
Abstract
Patients with anxious depression have more severe symptoms, more side effects, and higher resistance to treatment than patients with non-anxious depression; therefore, it is crucial to clarify the differences between these two types of patients. In this study, a 5-minute resting EEG was recorded in 15 patients with anxious depression and 9 patients with non-anxious depression under eyes open and closed conditions. Sixty-eight subcortical regions were extracted using exact low resolution brain electromagnetic tomography (eLORETA). The directed transfer function was then used to construct brain networks. Specific features based on graph theory including the strength of connectivity and betweenness centrality (BC) were calculated from the networks. Finally, significant features were selected using the Mann-Whitney U test, and patients were classified into anxious and non-anxious depressive groups using the Support Vector Machine (SVM). Results showed that features of outward connectivity strength led to the highest accuracy, F-score, and specificity with 91.66%, 87. 5%, and 100% in the eyes-closed state, respectively. Moreover, we found that the strength of connectivity in both directions increased for the anxious depressive group during the eyes-open state. In particular, higher outward connectivity was observed in the right hemisphere for the anxious depressive group. Further findings also revealed that features with the most significant difference were mainly associated with the beta band. In addition, significant increased inward and outward connectivity and decreased nodal centrality were observed in the posterior regions of the default mode network. These preliminary findings might provide new insights into the recognition of anxious depressed patients.
1. Introduction
Major depressive disorder (MDD) affects 6% of the global adult population annually and is one of the most prevalent psychiatric disorders [1]. About half of MDD patients also have anxiety, such as social anxiety disorder (SAD), generalized anxiety disorder (GAD), or panic disorder (PD) [2]. When MDD co-occurs with anxiety, the risk of suicide becomes greater, and patients may require long-term treatment [3,4]. Currently, however, there is a lack of accepted treatment for patients with anxious depression. They usually receive the same treatment strategies that are given for depression or anxiety. Consequently, the rate of treatment resistance is higher for them than for patients with pure depression or anxiety [5]. Moreover, the rate of medical utilization increased rapidly for patients with comorbid depression and anxiety [4]. Therefore, it is necessary to distinguish anxious depressed patients from non-anxious depressed patients in order to improve diagnosis and treatment methods.
5. Conclusion
To the best of our knowledge, this is the first study that has investigated differences in the directed brain network in anxious and nonanxious depressed patients using an effective connectivity measure and the EEG source connectivity method. Network metrics comprising directed node strength and BC were analyzed by a statistical test and the machine learning approach. Classification results demonstrate outward connectivity strength had the highest performance in separating the two groups of patients, while all features performed better in the eyes-closed state than in the eyes-open state. Our main findings related to the strength of connectivity consist of increased node strength during the eyes-open condition, especially a higher out-strength in the right hemisphere for the anxious depressive group. In addition, we found that beta oscillations reflect the most altered brain network in terms of node strength and BC. Further analysis revealed that connectivity and centrality in most regions of posterior DMN were changed significantly. To conclude, the obtained results could potentially lead to the understanding of the underlying brain network of patients with comorbid depression-anxiety disorder, however, more research still is needed regarding the anxious depressive disorder.