Brain spontaneous fluctuations in sensorimotor regions were directly related to eyes open and eyes closed: evidences from a machine learning approach
Previous studies have demonstrated that the difference between resting-state brain activations depends on whether the subject was eyes open (EO) or eyes closed (EC). However, whether the spontaneous fluctuations are directly related to these two different resting states are still largely unclear. In...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2014-08-01
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| Series: | Frontiers in Human Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnhum.2014.00645/full |
| _version_ | 1819080631155425280 |
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| author | Bishan eLiang Delong eZhang Delong eZhang Xue eWen Pengfei eXu Xiaoling ePeng Xishan eHuang Ming eLiu Ruiwang eHuang |
| author_facet | Bishan eLiang Delong eZhang Delong eZhang Xue eWen Pengfei eXu Xiaoling ePeng Xishan eHuang Ming eLiu Ruiwang eHuang |
| author_sort | Bishan eLiang |
| collection | DOAJ |
| description | Previous studies have demonstrated that the difference between resting-state brain activations depends on whether the subject was eyes open (EO) or eyes closed (EC). However, whether the spontaneous fluctuations are directly related to these two different resting states are still largely unclear. In the present study, we acquired resting-state functional magnetic resonance imaging data from 24 healthy subjects (11 males, 20.17 ± 2.74 years) under the EO and EC states. The amplitude of the spontaneous brain activity in low-frequency band was subsequently investigated by using the metric of fractional amplitude of low frequency fluctuation (fALFF) for each subject under each state. A support vector machine (SVM) analysis was then applied to evaluate whether the category of resting states could be determined from the brain spontaneous fluctuations. We demonstrated that these two resting states could be decoded from the identified pattern of brain spontaneous fluctuations, predominantly based on fALFF in the sensorimotor module. Specifically, we observed prominent relationships between increased fALFF for EC and decreased fALFF for EO in sensorimotor regions. Overall, the present results indicate that a SVM performs well in the discrimination between the brain spontaneous fluctuations of distinct resting states and provide new insight into the neural substrate of the resting states during EC and EO. |
| first_indexed | 2024-12-21T19:47:57Z |
| format | Article |
| id | doaj.art-01ac28b3dfbd4fecb6e1836eb3218e4b |
| institution | Directory Open Access Journal |
| issn | 1662-5161 |
| language | English |
| last_indexed | 2024-12-21T19:47:57Z |
| publishDate | 2014-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Human Neuroscience |
| spelling | doaj.art-01ac28b3dfbd4fecb6e1836eb3218e4b2022-12-21T18:52:16ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612014-08-01810.3389/fnhum.2014.0064589595Brain spontaneous fluctuations in sensorimotor regions were directly related to eyes open and eyes closed: evidences from a machine learning approachBishan eLiang0Delong eZhang1Delong eZhang2Xue eWen3Pengfei eXu4Xiaoling ePeng5Xishan eHuang6Ming eLiu7Ruiwang eHuang8South China Normal UniversityGuangdong Province Hospital of Traditional Chinese MedicineGuangzhou University of Chinese Medicine postdoctoral mobile research stationSouth China Normal UniversityBeijing Normal UniversitySouth China Normal UniversitySouth China Normal UniversitySouth China Normal UniversitySouth China Normal UniversityPrevious studies have demonstrated that the difference between resting-state brain activations depends on whether the subject was eyes open (EO) or eyes closed (EC). However, whether the spontaneous fluctuations are directly related to these two different resting states are still largely unclear. In the present study, we acquired resting-state functional magnetic resonance imaging data from 24 healthy subjects (11 males, 20.17 ± 2.74 years) under the EO and EC states. The amplitude of the spontaneous brain activity in low-frequency band was subsequently investigated by using the metric of fractional amplitude of low frequency fluctuation (fALFF) for each subject under each state. A support vector machine (SVM) analysis was then applied to evaluate whether the category of resting states could be determined from the brain spontaneous fluctuations. We demonstrated that these two resting states could be decoded from the identified pattern of brain spontaneous fluctuations, predominantly based on fALFF in the sensorimotor module. Specifically, we observed prominent relationships between increased fALFF for EC and decreased fALFF for EO in sensorimotor regions. Overall, the present results indicate that a SVM performs well in the discrimination between the brain spontaneous fluctuations of distinct resting states and provide new insight into the neural substrate of the resting states during EC and EO.http://journal.frontiersin.org/Journal/10.3389/fnhum.2014.00645/fullResting-state fMRIeyes openeyes closedsupport vector machine (SVM)fractional amplitude of low-frequency fluctuation (fALFF) |
| spellingShingle | Bishan eLiang Delong eZhang Delong eZhang Xue eWen Pengfei eXu Xiaoling ePeng Xishan eHuang Ming eLiu Ruiwang eHuang Brain spontaneous fluctuations in sensorimotor regions were directly related to eyes open and eyes closed: evidences from a machine learning approach Frontiers in Human Neuroscience Resting-state fMRI eyes open eyes closed support vector machine (SVM) fractional amplitude of low-frequency fluctuation (fALFF) |
| title | Brain spontaneous fluctuations in sensorimotor regions were directly related to eyes open and eyes closed: evidences from a machine learning approach |
| title_full | Brain spontaneous fluctuations in sensorimotor regions were directly related to eyes open and eyes closed: evidences from a machine learning approach |
| title_fullStr | Brain spontaneous fluctuations in sensorimotor regions were directly related to eyes open and eyes closed: evidences from a machine learning approach |
| title_full_unstemmed | Brain spontaneous fluctuations in sensorimotor regions were directly related to eyes open and eyes closed: evidences from a machine learning approach |
| title_short | Brain spontaneous fluctuations in sensorimotor regions were directly related to eyes open and eyes closed: evidences from a machine learning approach |
| title_sort | brain spontaneous fluctuations in sensorimotor regions were directly related to eyes open and eyes closed evidences from a machine learning approach |
| topic | Resting-state fMRI eyes open eyes closed support vector machine (SVM) fractional amplitude of low-frequency fluctuation (fALFF) |
| url | http://journal.frontiersin.org/Journal/10.3389/fnhum.2014.00645/full |
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