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Optical mapping of the dominant frequency of brain signal oscillations in motor systems

Recent neuroimaging studies revealed that the dominant frequency of neural oscillations is brain-region-specific and can vary with frequency-specific reorganization of brain networks during cognition. In this study, we examined the dominant frequency in low-frequency neural oscillations represented...

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Detalles Bibliográficos
Autores principales: Lu, Feng-Mei, Wang, Yi-Feng, Zhang, Juan, Chen, Hua-Fu, Yuan, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5677051/
https://www.ncbi.nlm.nih.gov/pubmed/29116158
http://dx.doi.org/10.1038/s41598-017-15046-9
Descripción
Sumario:Recent neuroimaging studies revealed that the dominant frequency of neural oscillations is brain-region-specific and can vary with frequency-specific reorganization of brain networks during cognition. In this study, we examined the dominant frequency in low-frequency neural oscillations represented by oxygenated hemoglobin measurements after the hemodynamic response function (HRF) deconvolution. Twenty-nine healthy college subjects were recruited to perform a serial finger tapping task at the frequency of 0.2 Hz. Functional near-infrared spectroscopy (fNIRS) was applied to record the hemodynamic signals over the primary motor cortex, supplementary motor area (SMA), premotor cortex, and prefrontal area. We then explored the low frequency steady-state brain response (lfSSBR), which was evoked in the motor systems at the fundamental frequency (0.2 Hz) and its harmonics (0.4, 0.6, and 0.8 Hz). In particular, after HRF deconvolution, the lfSSBR at the frequency of 0.4 Hz in the SMA was identified as the dominant frequency. Interestingly, the domain frequency exhibited the correlation with behavior data such as reaction time, indicating that the physiological implication of lfSSBR is related to the brain anatomy, stimulus frequency and cognition. More importantly, the HRF deconvolution showed its capability for recovering signals probably reflecting neural-level events and revealing the physiological meaning of lfSSBR.