Analysis of Residual Dependencies of Independent Components Extracted from fMRI Data
المؤلفون المشاركون
Landini, Luigi
Vanello, N.
Ricciardi, E.
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-12-29
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data can be employed as an exploratory method.
The lack in the ICA model of strong a priori assumptions about the signal or about the noise leads to difficult interpretations of the results.
Moreover, the statistical independence of the components is only approximated.
Residual dependencies among the components can reveal informative structure in the data.
A major problem is related to model order selection, that is, the number of components to be extracted.
Specifically, overestimation may lead to component splitting.
In this work, a method based on hierarchical clustering of ICA applied to fMRI datasets is investigated.
The clustering algorithm uses a metric based on the mutual information between the ICs.
To estimate the similarity measure, a histogram-based technique and one based on kernel density estimation are tested on simulated datasets.
Simulations results indicate that the method could be used to cluster components related to the same task and resulting from a splitting process occurring at different model orders.
Different performances of the similarity measures were found and discussed.
Preliminary results on real data are reported and show that the method can group task related and transiently task related components.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Vanello, N.& Ricciardi, E.& Landini, Luigi. 2015. Analysis of Residual Dependencies of Independent Components Extracted from fMRI Data. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1099622
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Vanello, N.…[et al.]. Analysis of Residual Dependencies of Independent Components Extracted from fMRI Data. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-15.
https://search.emarefa.net/detail/BIM-1099622
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Vanello, N.& Ricciardi, E.& Landini, Luigi. Analysis of Residual Dependencies of Independent Components Extracted from fMRI Data. Computational Intelligence and Neuroscience. 2015. Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1099622
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1099622
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر