Independent Component Analysis with Functional Neuroscience Data Analysis

  • سال انتشار: 1402
  • محل انتشار: مجله فیزیک و مهندسی پزشکی، دوره: 13، شماره: 2
  • کد COI اختصاصی: JR_JBPE-13-2_008
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 53
دانلود فایل این مقاله

نویسندگان

Hadeel K Aljobouri

Department of Biomedical Engineering, College of Engineering, Al-Nahrain University, Baghdad, IRAQ

چکیده

Background: Independent Component Analysis (ICA) is the most common and standard technique used in functional neuroscience data analysis. Objective: In this study, two of the significant functional brain techniques are introduced as a model for neuroscience data analysis.Material and Methods: In this experimental and analytical study, Electroencephalography (EEG) signal and functional Magnetic Resonance Imaging (fMRI) were analyzed and managed by the developed tool. The introduced package combines Independent Component Analysis (ICA) to recognize significant dimensions of the data in neuroscience. This study combines EEG and fMRI in the same package for analysis and comparison results. Results: The findings of this study indicated the performance of the ICA, which can be dealt with the presented easy-to-use and learn intuitive toolbox. The user can deal with EEG and fMRI data in the same module. Thus, all outputs were analyzed and compared at the same time; the users can then import the neurofunctional datasets easily and select the desired portions of the functional biosignal for further processing using the ICA method.  Conclusion: A new toolbox and functional graphical user interface, running in cross-platform MATLAB, was presented and applied to biomedical engineering research centers.

کلیدواژه ها

Electroencephalogram, Functional Magnetic Resonance Imaging (fMRI), Graphical User Interface (GUI), Independent Component Analysis (ICA), Functional Neuroscience

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.