Zhengge Wang1, Zhiqiang Zhang2, Wei Liao3, Qiang Xu4, Jie Zhang5, Wenlian Lu5, Qing Jiao4, Guanghui Chen6, Jianfeng Feng5, Guangming Lu4. 1. Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, PR China; Department of Medical Imaging, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, PR China; Jinling Hospital-Fudan University Computational Translational Medicine Center, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, PR China. 2. Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, PR China; Jinling Hospital-Fudan University Computational Translational Medicine Center, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, PR China. Electronic address: zhangzq2001@126.com. 3. Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, PR China; Center for Cognition and Brain Disorders and the Affiliated Hospital, Hangzhou Normal University, Hangzhou 310036, China. 4. Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, PR China; Jinling Hospital-Fudan University Computational Translational Medicine Center, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, PR China. 5. Center for Computational Systems Biology, Fudan University, Shanghai 200433, PR China; Jinling Hospital-Fudan University Computational Translational Medicine Center, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, PR China. 6. Department of Neurology, Jinling Hospital, Nanjing University School of Medicine, Nanjing 210002, PR China.
Abstract
PURPOSE: Amplitude of low-frequency fluctuation (ALFF) of blood-oxygenation level-dependent (BOLD) has proven a promising way to detect disease-related local brain activity. However, routine approach employs an arbitrary frequency band of 0.01-0.08 Hz, which lacks frequency specificity and blinds to the information contained in other frequency bands. This study investigated the amplitude of fluctuations in full BOLD frequency bands, and addressed how amplitudes of fluctuations change in each specific frequency range in idiopathic generalized epilepsy (IGE). METHODS: Thirty-four IGE patients with generalized tonic-clonic seizure and the same number of age- and sex-matched healthy controls were included. Functional MRI data were acquired using a 2s repetition time. Routine amplitude of low-frequency fluctuation analysis was first performed. The regions showing group difference were set as Region-of-interest for analysis of amplitudes of full-frequency. The amplitudes of BOLD fluctuations were consecutively performed at each frequency bin of 0.002 Hz, and specific frequency amplitude analyses were performed in five different frequency ranges (0-0.01 Hz, 0.01-0.027 Hz, 0.027-0.073 Hz, 0.073-0.198 Hz, and 0.198-0.25 Hz). KEY FINDINGS: The thalamus and prefrontal cortex showed significant group differences in routine amplitude analysis. For amplitude of full-frequency analysis, a reverse pattern was found in the dynamic changes between the thalamus and prefrontal cortex in IGE. Moreover, the prefrontal cortex showed amplitude difference in the 0.01-0.027 Hz band, while the thalamus showed amplitude difference in the 0.027-0.073 Hz band. Both these two regions showed amplitude differences in 0.198-0.25 Hz band. SIGNIFICANCE: We demonstrated the characteristic alterations of amplitude of BOLD fluctuations in IGE in frequency domain. The amplitude analysis of full frequency may potentially help to select specific frequency range for detecting epilepsy-related brain activity, and provide insights into the pathophysiological mechanism of IGE.
PURPOSE: Amplitude of low-frequency fluctuation (ALFF) of blood-oxygenation level-dependent (BOLD) has proven a promising way to detect disease-related local brain activity. However, routine approach employs an arbitrary frequency band of 0.01-0.08 Hz, which lacks frequency specificity and blinds to the information contained in other frequency bands. This study investigated the amplitude of fluctuations in full BOLD frequency bands, and addressed how amplitudes of fluctuations change in each specific frequency range in idiopathic generalized epilepsy (IGE). METHODS: Thirty-four IGE patients with generalized tonic-clonic seizure and the same number of age- and sex-matched healthy controls were included. Functional MRI data were acquired using a 2s repetition time. Routine amplitude of low-frequency fluctuation analysis was first performed. The regions showing group difference were set as Region-of-interest for analysis of amplitudes of full-frequency. The amplitudes of BOLD fluctuations were consecutively performed at each frequency bin of 0.002 Hz, and specific frequency amplitude analyses were performed in five different frequency ranges (0-0.01 Hz, 0.01-0.027 Hz, 0.027-0.073 Hz, 0.073-0.198 Hz, and 0.198-0.25 Hz). KEY FINDINGS: The thalamus and prefrontal cortex showed significant group differences in routine amplitude analysis. For amplitude of full-frequency analysis, a reverse pattern was found in the dynamic changes between the thalamus and prefrontal cortex in IGE. Moreover, the prefrontal cortex showed amplitude difference in the 0.01-0.027 Hz band, while the thalamus showed amplitude difference in the 0.027-0.073 Hz band. Both these two regions showed amplitude differences in 0.198-0.25 Hz band. SIGNIFICANCE: We demonstrated the characteristic alterations of amplitude of BOLD fluctuations in IGE in frequency domain. The amplitude analysis of full frequency may potentially help to select specific frequency range for detecting epilepsy-related brain activity, and provide insights into the pathophysiological mechanism of IGE.
Authors: Reza Tadayonnejad; Olusola Ajilore; Brian J Mickey; Natania A Crane; David T Hsu; Anand Kumar; Jon-Kar Zubieta; Scott A Langenecker Journal: Psychiatry Res Neuroimaging Date: 2016-04-27 Impact factor: 2.376
Authors: Yu-Chen Chen; Wenqing Xia; Bin Luo; Vijaya P K Muthaiah; Zhenyu Xiong; Jian Zhang; Jian Wang; Richard Salvi; Gao-Jun Teng Journal: Front Neural Circuits Date: 2015-10-29 Impact factor: 3.492