علوم رایانشی

علوم رایانشی

تحلیل مبتنی بر شبکه علامت‌دار تغییرات اتصال عملکردی شبکه حالت پیش‌فرض مغز در ارتباط با سطوح آمیلوئید-بتا

نوع مقاله : مقاله پژوهشی

نویسندگان
1 فارغ‌التحصیل کارشناسی ارشد رشته مهندسی کامپیوتر، دانشکده فنی و مهندسی، دانشگاه اراک، اراک، ایران
2 استادیار گروه مهندسی کامپیوتر، دانشکده فنی و مهندسی، دانشگاه اراک، اراک، ایران
10.22034/csj.2026.573180.1153
چکیده
بیماری آلزایمر[1]، شایع‌ترین علت زوال عقل است، که با تخریب تدریجی حافظه، موجب اختلال در عملکردهای شناختی بیمار می‌شود. شناسایی زودهنگام تغییرات مغزی، یکی از مهمترین راهبردها برای مداخله درمانی این بیماری، محسوب می‌شود. تحلیل و مدل‌سازی شبکه‌های پیچیده زیستی، با در نظر گرفتن اتصالات مثبت و منفی موجود در آنها، نقشی حیاتی در ادراک پایداری و رفتار توپولوژیک سیستم‌های عصبی، ایفا می‌کنند. با این‌ حال، بیشتر پژوهش‌های پیشین در حوزه تحلیل شبکه‌های زیستی، به‌منظور تحلیل شبکه‌های اتصال عملکردی[2]، یال‌های منفی را نادیده گرفتند، یا آنها را حذف کردند، که این امر، موجب از دست رفتن اطلاعات حیاتی و ارزیابی نادرست تعادل ساختاری سیستم می‌شود. در این مطالعه، تغییرات اولیه در اتصال عملکردی شبکه حالت پیش‌فرض[3] مغز در ارتباط با سطوح آمیلوئید-بتا[4]، با استفاده از تحلیل شبکه علامت‌دار[5]، بررسی شدند. داده‌های 97 شرکت‌کننده سالم از لحاظ شناختی، از پروژه ادنی[6]، با اطلس شفر[7] (شامل ۴۰۰ ناحیه)، تحلیل شدند، و پنج معیار گراف علامت‌دار، شامل معیار مرکزیت علامت‌دار[8]، شاخص فرسودگی[9]، معیار تعادل ساختاری[10]، معیار ضریب خوشه‌بندی علامت‌دار[11] و معیار همسان‌گزینی محلی[12]، در ۱۶ سطح آستانه، محاسبه گردیدند. یافته‌ها نشان دادند که با افزایش بار آمیلوئید-بتا، شبکه حالت پیش‌فرض، دچار بازآرایی توپولوژیکی غیرخطی و ناهمگون می‌شود؛ به‌طوری‌که مرکزیت علامت‌دار، همبستگی مثبت معناداری با بار آمیلوئید-بتا نشان داد (۲۶4/۰<r، مقدار پی<015/0) و متقابلاً، همسان‌گزینی محلی منفی (۲۹4/۰->r، و مقدار پی<016/0) و شاخص فرسودگی (۲5۶/۰->r، مقدار پی<۰۲۶/0) ، کاهش یافتند. از منظر نظریه سیستم‌ها، این الگو، نشان‌دهنده حرکت شبکه به‌سمت وضعیت پایدارتر، با کمینه‌سازی فرسودگی[13]، می‌باشد، و احتمالاً، بازتاب سازوکار جبرانی نورونی، در مراحل پیش‌بالینی بیماری آلزایمر، است. این یافته‌ها، می‌توانند به‌عنوان نشانگرهای زیستی مبتنی بر شبکه، امکان شناسایی زودهنگام تغییرات پاتولوژیک را، پیش از بروز علائم بالینی، فراهم سازند.



1. Alzheimer's Disease (AD)


2. Functional Connectivity


3. Default Mode Network (DMN)


4. Amyloid Beta (Aβ)


5. Signed Network Analysis


6. Alzheimer’s Disease Neuroimaging Initiative (ADNI)


7. Schaefer Atlas


8. Signed Centrality


9. Frustration Index


10. Structural Balance


11. Signed Clustering Coefficient


12. Local Assortativity


13. Energy/Frustration Minimization
کلیدواژه‌ها
موضوعات

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