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Steady-state BOLD response modulates low frequency neural oscillations.

Wang YF, Liu F, Long ZL, Duan XJ, Cui Q, Yan JH, Chen HF - Sci Rep (2014)

Bottom Line: Specifically, the harmonic phenomenon of SSBR was task-related and independent of the neurovascular coupling.These findings suggested that the SSBRs represent non-linear neural oscillations but not brain activations.In comparison with the conventional general linear model, the SSBRs provide us novel insights into the non-linear brain activities, low frequency neural oscillations, and neuroplasticity of brain training and cognitive activities.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China.

ABSTRACT
Neural oscillations are the intrinsic characteristics of brain activities. Traditional electrophysiological techniques (e.g., the steady-state evoked potential, SSEP) have provided important insights into the mechanisms of neural oscillations in the high frequency ranges (>1 Hz). However, the neural oscillations within the low frequency ranges (<1 Hz) and deep brain areas are rarely examined. Based on the advantages of the low frequency blood oxygen level dependent (BOLD) fluctuations, we expected that the steady-state BOLD responses (SSBRs) would be elicited and modulate low frequency neural oscillations. Twenty six participants completed a simple reaction time task with the constant stimuli frequencies of 0.0625 Hz and 0.125 Hz. Power analysis and hemodynamic response function deconvolution method were used to extract SSBRs and recover neural level signals. The SSEP-like waveforms were observed at the whole brain level and at several task-related brain regions. Specifically, the harmonic phenomenon of SSBR was task-related and independent of the neurovascular coupling. These findings suggested that the SSBRs represent non-linear neural oscillations but not brain activations. In comparison with the conventional general linear model, the SSBRs provide us novel insights into the non-linear brain activities, low frequency neural oscillations, and neuroplasticity of brain training and cognitive activities.

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Related in: MedlinePlus

The relationship of signals before and after HRF deconvolution.The HRF changed the phase but not the frequency (A). The signals on task conditions were in negative correlation before and after HRF deconvolution (B). The signals were extracted from the left sensorimotor area as the average of all subjects and normalized by z-transformation. BD: Before HRF Deconvolution; AD: After HRF Deconvolution.
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f4: The relationship of signals before and after HRF deconvolution.The HRF changed the phase but not the frequency (A). The signals on task conditions were in negative correlation before and after HRF deconvolution (B). The signals were extracted from the left sensorimotor area as the average of all subjects and normalized by z-transformation. BD: Before HRF Deconvolution; AD: After HRF Deconvolution.

Mentions: Figure 1 suggests that the HRF significantly contributed to the amplitude of BOLD signals. In addition, the HRF deconvolution changed the phase of task signals (1/2 ~ 3/4 cycle for the HF condition, 1/4 ~ 3/8 cycle for the LF condition; Figure 4A), because a 4–6 s delay of the neurovascular coupling was eliminated16. Due to the phase changes, the task signals showed negative correlations (LF: r = −0.353, p <0.001; HF: r = −0.0.783, p <0.001; Resting: r = 0.089, p = 0.139) before and after HRF deconvolution. In summary, the HRF changed the amplitude (Figure 1) and the phase (Figure 4) of BOLD signals, and the patterns of energy distribution along the frequency ranges (Figure 1), rather than the relative power (Figure 1, 2) of SSBRs. The results suggest that the effect of SSBRs was clear and independent of neurovascular coupling.


Steady-state BOLD response modulates low frequency neural oscillations.

Wang YF, Liu F, Long ZL, Duan XJ, Cui Q, Yan JH, Chen HF - Sci Rep (2014)

The relationship of signals before and after HRF deconvolution.The HRF changed the phase but not the frequency (A). The signals on task conditions were in negative correlation before and after HRF deconvolution (B). The signals were extracted from the left sensorimotor area as the average of all subjects and normalized by z-transformation. BD: Before HRF Deconvolution; AD: After HRF Deconvolution.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4260215&req=5

f4: The relationship of signals before and after HRF deconvolution.The HRF changed the phase but not the frequency (A). The signals on task conditions were in negative correlation before and after HRF deconvolution (B). The signals were extracted from the left sensorimotor area as the average of all subjects and normalized by z-transformation. BD: Before HRF Deconvolution; AD: After HRF Deconvolution.
Mentions: Figure 1 suggests that the HRF significantly contributed to the amplitude of BOLD signals. In addition, the HRF deconvolution changed the phase of task signals (1/2 ~ 3/4 cycle for the HF condition, 1/4 ~ 3/8 cycle for the LF condition; Figure 4A), because a 4–6 s delay of the neurovascular coupling was eliminated16. Due to the phase changes, the task signals showed negative correlations (LF: r = −0.353, p <0.001; HF: r = −0.0.783, p <0.001; Resting: r = 0.089, p = 0.139) before and after HRF deconvolution. In summary, the HRF changed the amplitude (Figure 1) and the phase (Figure 4) of BOLD signals, and the patterns of energy distribution along the frequency ranges (Figure 1), rather than the relative power (Figure 1, 2) of SSBRs. The results suggest that the effect of SSBRs was clear and independent of neurovascular coupling.

Bottom Line: Specifically, the harmonic phenomenon of SSBR was task-related and independent of the neurovascular coupling.These findings suggested that the SSBRs represent non-linear neural oscillations but not brain activations.In comparison with the conventional general linear model, the SSBRs provide us novel insights into the non-linear brain activities, low frequency neural oscillations, and neuroplasticity of brain training and cognitive activities.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China.

ABSTRACT
Neural oscillations are the intrinsic characteristics of brain activities. Traditional electrophysiological techniques (e.g., the steady-state evoked potential, SSEP) have provided important insights into the mechanisms of neural oscillations in the high frequency ranges (>1 Hz). However, the neural oscillations within the low frequency ranges (<1 Hz) and deep brain areas are rarely examined. Based on the advantages of the low frequency blood oxygen level dependent (BOLD) fluctuations, we expected that the steady-state BOLD responses (SSBRs) would be elicited and modulate low frequency neural oscillations. Twenty six participants completed a simple reaction time task with the constant stimuli frequencies of 0.0625 Hz and 0.125 Hz. Power analysis and hemodynamic response function deconvolution method were used to extract SSBRs and recover neural level signals. The SSEP-like waveforms were observed at the whole brain level and at several task-related brain regions. Specifically, the harmonic phenomenon of SSBR was task-related and independent of the neurovascular coupling. These findings suggested that the SSBRs represent non-linear neural oscillations but not brain activations. In comparison with the conventional general linear model, the SSBRs provide us novel insights into the non-linear brain activities, low frequency neural oscillations, and neuroplasticity of brain training and cognitive activities.

Show MeSH
Related in: MedlinePlus