2017
DOI: 10.1007/s10278-017-0020-4
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Differences Between Schizophrenic and Normal Subjects Using Network Properties from fMRI

Abstract: Schizophrenia has been proposed to result from impairment of functional connectivity. We aimed to use machine learning to distinguish schizophrenic subjects from normal controls using a publicly available functional MRI (fMRI) data set. Global and local parameters of functional connectivity were extracted for classification. We found decreased global and local network connectivity in subjects with schizophrenia, particularly in the anterior right cingulate cortex, the superior right temporal region, and the in… Show more

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Cited by 39 publications
(24 citation statements)
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“…Each functional volume contained 35 slices. To minimize the effects of scanner signal stabilization, the first five volumes of each subject were excluded from all analysesOrbitofrontal cortexThe systematically different medications for SCZ and MDD may have different effects on functional connectivity; the medicated patients were in stable condition and this may have an impact on the functional connectivity of cortical networksWang, 201726rs-fMRI 3T79 subjects:-48 drug-naïve AOS-31 HCSVMFC analysisLIBSVMROC92.4%Sn 89.6%Sp 96.8%Authors used regional homogeneity (ReHo), a measurement that reflects brain local functional connectivity or synchronization and indicates regional integration of information processingRight middle frontal gyrus, right superior medial prefrontal cortex, left superior temporal gyrusSVM analysis applied to an independent datasetBae, 201740fMRI 3T75 subjects:-21 SCZ-54 HCSVM92.1%±10.5Sn 92.0±15.8%Sp 92.1±8.1%Precision 94±6.3%Authors created anatomic labels for 90 ROIs from the image database. Any subject with fewer than 85 ROIs automatically labeled was excludedAnterior right cingulate cortex, superior right temporal region, inferior left parietal regionPossible influence of pharmacological treatment and disease stage on the investigated functional connections, they used only n-back tests without rs-fMRIQureshi, 201744rs-fMRI 3T144 subjects:-72 SCZ-72 HCELMSVMLDARF99.3%Sn 100%Sp 98, 6%Authors used measures including the mean cortical thickness, cortical thickness standard deviation, surface area, volume, mean curvature, white matter volume, subcortical segment volume, subcortical intensity, and overall brain volume and intensity as the structural featuresCortical thickness, Surface area, WM/subcortical/overall volume, curvature, global average functional connectivityAuthors developed an ELM, whose effectiveness was compared with that of more known ML methodsReavis, 201725fMRI 3T148 subjects:-50 SCZ-51 BD-47 HCMVPA41%N.A.Structural data were processed and parcellated into anatomical regions used to constrain ROI definitionsLateral occipital lobeThe paper shows MVPA can be used successfully to classify individual perceptual stimuli in SCZ and BD.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Each functional volume contained 35 slices. To minimize the effects of scanner signal stabilization, the first five volumes of each subject were excluded from all analysesOrbitofrontal cortexThe systematically different medications for SCZ and MDD may have different effects on functional connectivity; the medicated patients were in stable condition and this may have an impact on the functional connectivity of cortical networksWang, 201726rs-fMRI 3T79 subjects:-48 drug-naïve AOS-31 HCSVMFC analysisLIBSVMROC92.4%Sn 89.6%Sp 96.8%Authors used regional homogeneity (ReHo), a measurement that reflects brain local functional connectivity or synchronization and indicates regional integration of information processingRight middle frontal gyrus, right superior medial prefrontal cortex, left superior temporal gyrusSVM analysis applied to an independent datasetBae, 201740fMRI 3T75 subjects:-21 SCZ-54 HCSVM92.1%±10.5Sn 92.0±15.8%Sp 92.1±8.1%Precision 94±6.3%Authors created anatomic labels for 90 ROIs from the image database. Any subject with fewer than 85 ROIs automatically labeled was excludedAnterior right cingulate cortex, superior right temporal region, inferior left parietal regionPossible influence of pharmacological treatment and disease stage on the investigated functional connections, they used only n-back tests without rs-fMRIQureshi, 201744rs-fMRI 3T144 subjects:-72 SCZ-72 HCELMSVMLDARF99.3%Sn 100%Sp 98, 6%Authors used measures including the mean cortical thickness, cortical thickness standard deviation, surface area, volume, mean curvature, white matter volume, subcortical segment volume, subcortical intensity, and overall brain volume and intensity as the structural featuresCortical thickness, Surface area, WM/subcortical/overall volume, curvature, global average functional connectivityAuthors developed an ELM, whose effectiveness was compared with that of more known ML methodsReavis, 201725fMRI 3T148 subjects:-50 SCZ-51 BD-47 HCMVPA41%N.A.Structural data were processed and parcellated into anatomical regions used to constrain ROI definitionsLateral occipital lobeThe paper shows MVPA can be used successfully to classify individual perceptual stimuli in SCZ and BD.…”
Section: Resultsmentioning
confidence: 99%
“…The accuracy was 92.1% using SVM and 10-fold cross-validation (sensitivity 92%, specificity 92.1%, precision 94%); this suggests important and significant differences regarding the regional brain activity through fMRI in both groups. The aim of their work was to demonstrate that brain connectivity was significantly altered in patients with SCZ compared with HC and that these differences could be efficiently and more easily detected by ML analysis 40…”
Section: Resultsmentioning
confidence: 99%
“…Our study has some limitations. First, although the sample size is limited, it is relatively larger when compared to previous studies [ 1 , 21 , 31 , 50 , 65 ]. A larger sample size should be recruited in the future to replicate and enrich our findings.…”
Section: Discussionmentioning
confidence: 96%
“…Schizophrenia (SZ) is a severe psychiatric illness characterized by aberrant sensory perceptions, cognition, concrete thinking, and a restricted range of emotion, and it affects about 1% of the general population [1][2][3][4][5]. SZ is a heterogeneous disorder, and current diagnoses are based on subjective indicators such as self-report, observation, and clinical history, and its reliable diagnosis is challenging [1,4,6,7], and the pathological mechanism is still unclear [4].…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, the age affects network integrity in a more global way so it could be used as a specific flag of functional dysregulation in particular networks affected in SCZ ( 33 ). The results of Bae's study reported a decrease in the global and local network connectivity in SCZ patients compared with HC, especially in the superior right temporal region, in the anterior right cingulate cortex, and the inferior left parietal region with an accuracy of 92.1%, sensitivity of 92%, specificity of 92.1% and precision 94% ( 31 ). One of the largest studies on SCZ (200 patients vs 200 HC) reported a high diagnostic accuracy (84%) using data from several locations.…”
Section: Discussionmentioning
confidence: 99%