Abnormal Functional Resting-State Networks in ADHD: Graph Theory and Pattern Recognition Analysis of fMRI Data
المؤلفون المشاركون
dos Santos Siqueira, Anderson
Biazoli Junior, Claudinei Eduardo
Comfort, William Edgar
Rohde, Luis Augusto
Sato, João Ricardo
المصدر
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-08-28
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
The framework of graph theory provides useful tools for investigating the neural substrates of neuropsychiatric disorders.
Graph description measures may be useful as predictor variables in classification procedures.
Here, we consider several centrality measures as predictor features in a classification algorithm to identify nodes of resting-state networks containing predictive information that can discriminate between typical developing children and patients with attention-deficit/hyperactivity disorder (ADHD).
The prediction was based on a support vector machines classifier.
The analyses were performed in a multisite and publicly available resting-state fMRI dataset of healthy children and ADHD patients: the ADHD-200 database.
Network centrality measures contained little predictive information for the discrimination between ADHD patients and healthy subjects.
However, the classification between inattentive and combined ADHD subtypes was more promising, achieving accuracies higher than 65% (balance between sensitivity and specificity) in some sites.
Finally, brain regions were ranked according to the amount of discriminant information and the most relevant were mapped.
As hypothesized, we found that brain regions in motor, frontoparietal, and default mode networks contained the most predictive information.
We concluded that the functional connectivity estimations are strongly dependent on the sample characteristics.
Thus different acquisition protocols and clinical heterogeneity decrease the predictive values of the graph descriptors.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
dos Santos Siqueira, Anderson& Biazoli Junior, Claudinei Eduardo& Comfort, William Edgar& Rohde, Luis Augusto& Sato, João Ricardo. 2014. Abnormal Functional Resting-State Networks in ADHD: Graph Theory and Pattern Recognition Analysis of fMRI Data. BioMed Research International،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1016262
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
dos Santos Siqueira, Anderson…[et al.]. Abnormal Functional Resting-State Networks in ADHD: Graph Theory and Pattern Recognition Analysis of fMRI Data. BioMed Research International No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1016262
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
dos Santos Siqueira, Anderson& Biazoli Junior, Claudinei Eduardo& Comfort, William Edgar& Rohde, Luis Augusto& Sato, João Ricardo. Abnormal Functional Resting-State Networks in ADHD: Graph Theory and Pattern Recognition Analysis of fMRI Data. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1016262
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1016262
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