Discriminating brain activated area and predicting the stimuli performed using artificial neural network
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| Natura: | Artículo científico |
| Lingua: | en |
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Universidade Nove de Julho
2007
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| _version_ | 1876484997024579584 |
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| author | Rafael do Espírito Santo |
| author_facet | Rafael do Espírito Santo |
| contents | Discriminating brain activated area and predicting the stimuli performed using artificial neural network Rafael do Espírito Santo Maria G. Moraes Martin João Ricardo Sato Ingeniería FMRI Paradigm Activation Classifier Neural networks In this work, a Multilayer Perceptron implementation MLPusing functional Magnetic Resonance Imaging (fMRI) is usedto infer stimuli performed. Sets of images of brain activationwere generated by visual, auditory and finger tapping paradigmsin 54 healthy volunteers. These images were used fortraining the MLP network in a leave-one-out manner in orderto predict the paradigm that a subject performed by usingother images, so far unseen by the MLP network. The aim inthis paper is the exploring of the influence of the number of thePrincipal Component (PC) on the performance of the MLP inclassifying fMRI paradigms. The classifier´s performance wasevaluated in terms of the Sensitivity and Specificity, PredictionAccuracy and the area Az under the receiver operating characteristics(ROC) curve. From the ROC analysis, values of Az upto 1 were obtained with 60 PCs in discriminating the visualparadigm from the auditory paradigm. 2007 artículo científico 1678-5428 https://www.redalyc.org/articulo.oa?id=81050213 en http://www.redalyc.org/revista.oa?id=810 Exacta application/pdf Universidade Nove de Julho Exacta (Brasil) Num.2 Vol.5 |
| format | Artículo científico |
| id | redalyc_81050213 |
| institution | Redalyc |
| language | en |
| publishDate | 2007 |
| publisher | Universidade Nove de Julho |
| spellingShingle | Discriminating brain activated area and predicting the stimuli performed using artificial neural network Rafael do Espírito Santo Ingeniería FMRI Paradigm Activation Classifier Neural networks Discriminating brain activated area and predicting the stimuli performed using artificial neural network Rafael do Espírito Santo Maria G. Moraes Martin João Ricardo Sato Ingeniería FMRI Paradigm Activation Classifier Neural networks In this work, a Multilayer Perceptron implementation MLPusing functional Magnetic Resonance Imaging (fMRI) is usedto infer stimuli performed. Sets of images of brain activationwere generated by visual, auditory and finger tapping paradigmsin 54 healthy volunteers. These images were used fortraining the MLP network in a leave-one-out manner in orderto predict the paradigm that a subject performed by usingother images, so far unseen by the MLP network. The aim inthis paper is the exploring of the influence of the number of thePrincipal Component (PC) on the performance of the MLP inclassifying fMRI paradigms. The classifier´s performance wasevaluated in terms of the Sensitivity and Specificity, PredictionAccuracy and the area Az under the receiver operating characteristics(ROC) curve. From the ROC analysis, values of Az upto 1 were obtained with 60 PCs in discriminating the visualparadigm from the auditory paradigm. 2007 artículo científico 1678-5428 https://www.redalyc.org/articulo.oa?id=81050213 en http://www.redalyc.org/revista.oa?id=810 Exacta application/pdf Universidade Nove de Julho Exacta (Brasil) Num.2 Vol.5 |
| title | Discriminating brain activated area and predicting the stimuli performed using artificial neural network |
| topic | Ingeniería FMRI Paradigm Activation Classifier Neural networks |
| url | https://www.redalyc.org/articulo.oa?id=81050213 |