نوع مقاله: مقاله کامل پژوهشی

نویسندگان

1 دانشجوی دکتری مهندسی پزشکی، گروه بیوالکتریک، دانشکده‌ی مهندسی پزشکی، دانشگاه صنعتی امیرکبیر، تهران، ایران

2 استادیار، گروه بیوالکتریک، دانشکده‌ی مهندسی پزشکی، دانشگاه صنعتی امیرکبیر، تهران، ایران

چکیده

مغز به عنوان پیچیده‌ترین عضو بدن انسان، از جنبه‌های مختلفی مورد مطالعه قرار می‌گیرد. بیش‌ترین منشا این پیچیدگی از آن‌جا ناشی می‌شود که با وجود ثبات معماری ساختاری (اتصالات فیزیکی)، اتصالات کارکردی دینامیک و مختلفی در مغز وجود دارد. در بیماری‌های مغزی، معمولا هر دو اتصال ساختاری و کارکردی مغز و هم‌چنین ارتباط میان آن‌ها دچار تغییر شده و علایم رفتاری متفاوتی را ناشی می‌شود. مطالعه‌ی تغییرات اتصالات مغزی در این‌گونه بیماری‌ها، به شناخت بهتر ارتباط میان ساختار و کارکرد مغز کمک می‌کند. یکی از اختلالات روانی رایج، بیماری اسکیزوفرنی است که از سایر بیماری‌های روان‌شناختی، وخیم‌تر بوده و هر دو بخش ساختار و کارکرد مغز را به طور گسترده‌ای درگیر می‌کند. در میان روش‌هایی که تا کنون برای بررسی ارتباط میان داده‌های مغز پیشنهاد شده، رویکرد آنالیز توام، به دلیل توانایی استخراج اطلاعات متناظر در چند مدالیته، مورد توجه بسیاری از پژوهش‌گران قرار گرفته است. با وجود یافته‌های ارزشمند این روش‌ها، از آن‌جا که آنالیز آن‌ها تا کنون محدود به واکسل‌های تصویر بوده، اطلاعاتی از ارتباط میان اتصالات مغزی با استفاده از این روش‌ها فراهم نشده است. در این پژوهش از الگوریتم پیوندی آنالیز مولفه‌های مستقل به منظور تحلیل ارتباط میان تغییرات اتصالات کارکردی و ساختاری مغز بیماران اسکیزوفرنی در مقایسه با افراد سالم استفاده شده است. نتایج این مطالعه تایید می‌کند که ارتباط میان اتصالات مغزی الزاما به صورت یک-به-یک نمی‌باشد. هم‌چنین یافته‌های این پژوهش نشان داده که تغییرات اتصالات ساختاری مانند فاسیکولوس طولی فوقانی و فاسیکولوس طولی تحتانی با تغییرات کارکردی در نواحی مختلف مغزی مانند لوب‌های گیج‌گاهی و پیشانی مرتبط است. با مقایسه‌ی قدرت گره و طول کوتاه‌ترین مسیر در زیرشبکه‌های به دست آمده، کاهش بازدهی در انتقال موازی اطلاعات کارکردی در بیماران اسکیزوفرنی مشاهده گردید. با توجه به این یافته‌ها می‌توان نتیجه گرفت که آنالیز توام در سطح اتصالات مغزی می‌تواند به درک بهتر ارتباط میان تغییرات به وجود آمده در اتصالات ساختاری و کارکردی مغز کمک کند. 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Fusion Analysis of Brain Functional and Structural Connectivity to Discriminate Schizophrenia in Network Level

نویسندگان [English]

  • Farzaneh Keyvanfard 1
  • Abbas Nasiraei Moghaddam 2

1 Ph.D. Student, Bioelectric Department, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran

2 Assistant Professor, Bioelectric Department, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran

چکیده [English]

Brain as the most complex organ in the human body has been investigated from various aspects. The greatest origin of this complexity is due to the fact that, despite the fixed architecture of brain structure (physical connections), the functional connectivity is in a constantly changing state, resulting to different behaviors. In many mental diseases, both brain structural and functional connectivities and their relationship are changed and cause different symptoms. Investigation of brain connectivity variations in the disease may help to better understanding of the relationship between brain structure and function. One of the most severe and debilitating brain disorders is Schizophrenia in which both brain structure and function are involved. Among all available methods, multimodal analysis of data has been recently gained great interest to provide the capability of extracting association between separate neuroimaging data. However, due to their voxel based viewpoint, relationship between brain connectivities cannot be inferred. In this study, the joint independent component analysis (jICA) has been proposed to investigate the relationship between brain functional and structural connectivity. We applied the suggested approach to combine functional and structural connectivity, in order to assess abnormalities underlying schizophrenic patients relative to healthy people. The findings suggest that the correspondence between brain function and structure is not necessarily one-to-one. The results also indicated that variations in several structural fibers, such as superior longitudinal fasciculus and inferior longitudinal fasciculus, are associated with functional changes in the temporal and frontal lobes. Besides, analyzing the nodal strength and shortest path length in the obtained subnetworks demonstrates that the functional subnetworks efficiency in parallel information transfer in schizophrenic patients is reduced. Overall, the outcomes point out the capability of the proposed method to better understanding of brain functional and structural connectivity association and its variations in brain disorders. 

کلیدواژه‌ها [English]

  • Magnetic resonance imaging
  • Fusion analysis
  • Functional and structural connectivity
  • Schizophrenia
  • Network perspective

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