文章基本信息

标题：Model for Disconnectivity Analysis in Schizophrenics for Sternberg Item Recognition Paradigm
本地全文：下载
作者：Meghana Nagori ; Madhuri S.Joshi
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2016
卷号：7
期号：1
页码：371-374
出版社：TechScience Publications
摘要：Functional magnetic resonance imaging(fMRI) hascurrently gained popularity as a method in the decisionmaking process of neuroscience due to its excellent spatialresolution and non-invasive nature . It’s key feature lies in theability to precisely localize the brain areas activated whensubjects perform various tasks. Statistical ParametricMapping (SPM) is an tool in medical imaging to assist fMRIstudy. It allows one to compare images or regions of imagesfor differences. It helps one to make inferences on a group ofsubjects. Using MATLAB and the SPM software, the authorshave done connectivity analysis on three memory cyclescommonly established in healthy controls during workingmemory task and absent in schizophrenics.The authors haveemployed SIRP(Sternberg Item recognition paradigm)working memory and used data from Fbirn site for carryingout the said fMRI study . In this study the subject is asked torecognize numerical digits between 0-9 in steps of increasingload by first identifying a single digit then three andsubsequently five. The effect of increasing memory load isanalyzed first using classical analysis in SPM.It is inferred thatas memory load is increased there is substantial decrease inactivations in schizophrenic controls as compared to healthycontrols.The disconnectivity analysis is tested for aconnectivity cycle commonly established during workingmemory tasks and alterations in the connectivity are inferred.
关键词：fMRI;SPM;classical;effective connectivity