نوع مقاله: مقاله کامل پژوهشی

نویسندگان

1 استادیار، گروه مهندسی برق، دانشکده فنی و مهندسی، دانشگاه نیشابور، نیشابور

2 دانشیار، گروه مهندسی پزشکی، دانشکده مهندسی برق و کامپیوتر، دانشگاه تربیت مدرس، تهران

3 استادیار، گروه ریاضی، دانشکده علوم پایه، دانشگاه ایلام، ایلام

10.22041/ijbme.2014.13291

چکیده

تغییرات عملکردی شبکه­ی حرکتی مغز در بیماری پارکینسون نقش اساسی در بروز علائم بالینی بر عهده دارد. بررسی فعّالیّت مغز انسان با استفاده­از دادگان تصویربرداری تشدید مغناطیسی عملکردی (fMRI) نشان می­دهد که در حالت استراحت شبکه­ای، ارتباط­ها و فعّالیّت نوسان­های خودبه­خودی در نواحی مختلف مغز وجود دارد که در بیماری­های مختلف تحت تأثیر قرار می­گیرند. درین تحقیق، تغییرات وابستگی عملکردی بین نواحی آناتومیکی حرکتی در بیماری پارکینسون با استفاده­از تئوری تابع مفصل در دادگان حالت استراحت fMRI بررسی شد. پارامتر مفصل در پنج تابع مختلف از خانواده­ی مفصل با استفاده­از فرایند ماکزیمم شباهت تخمین زده شد. میزان شباهت بین مفصل تخمین زده شده و مفصل تجربی با روش­های جذر میانگین مجموع مربع­های خطا و فاصله­ی kulback-leibler محاسبه شد. مقایسه­ی پارامترهای تخمین زده شده بین افراد سالم و بیماران پارکینسونی با آزمون­های آماری پارامتریک و ناپارامتریک نشان داد که هم­بستگی عملکردی بین مخچه و هسته­های قاعده­ای در گروه بیماران، قوی­تر از افراد سالم است. درین مقاله برای نخستین بار پیشنهاد شده که توزیع مشترک سری زمانی فعّالیّت نواحی مختلف مغز می­تواند به عنوان روشی برای آنالیز ارتباطات عملکردی در دادگان fMRI ، حاوی ویژگی­های متمایز کننده بین بیماران و افراد سالم باشد.
 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Detecting Dependency Structure of the Brain Motor Network in Resting State fMRI data of Parkinson Disease using Copulas

نویسندگان [English]

  • Mahdie Ghasemi 1
  • Ali Mahloojifar 2
  • Mehdi Omidi 3

1 Assisstant Professor, Electrical Engineering Department, Faculty of Engineering, University of Neyshabur

2 Associate Professor, Electrical and Computer Engineering Department, Tarbiat Modares University

3 Assisstant Professor of Statistics, Department of Mathematics, Faculty of Science, Ilam University

چکیده [English]

Functional changes in the brain motor network are responsible for the major clinical features of Parkinson’s disease (PD). Recent studies on investigation of the brain function show that there are spontaneous fluctuations between regions at rest as resting state network affected in various disorders. In this paper, we examine changes of functional dependency between brain regions of interest associated with known anatomical pathology in Parkinson Disease (PD) using copula theory on resting state fMRI. Five types of copulas were tested: Gaussian and t (Euclidean), Clayton, Gumbel and Frank (Archimedean). We used an efficient maximum likelihood procedure for estimating copula parameters. Goodness of fits was tested using root mean square error (RMSE) and kulback-leibler divergence between each copula function and joint empirical cumulative distribution. Control vs PD group comparison was also done on dependency parameter using parametric and nonparametric tests. The results show that functional dependency between cerebellum and basal ganglia is much stronger in PD than in control. In this paper, we proposed for the first time that joint distribution characteristics could potentially provide information on discriminative features for functional connectivity analysis between healthy and patients.

کلیدواژه‌ها [English]

  • functional Magnetic Resonance Imaging (fMRI)
  • Functional Connectivity
  • Resting State
  • Parkinson Disease (PD)
  • Copulas

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