The Experts below are selected from a list of 94005 Experts worldwide ranked by ideXlab platform
Sara Jane Spaulding - One of the best experts on this subject based on the ideXlab platform.
-
Differential Cardiac Response to visual and auditory stimulation in the young child.
Psychophysiology, 2008Co-Authors: Michael Lewis, Sara Jane SpauldingAbstract:In this study, 24 infants, 6 months old, each received a series of visual and auditory stimuli. An analysis of their Cardiac Response indicates that onset of stimulus presentation results in a monophasic Response of Cardiac deceleration. Further, their Response to onset of presentation was compared to their Response to onset of visual orientation, and the data reveal that is it important for E to differentiate the Cardiac Response to presentation (E operation) from the onset of orientation (S operation). These results were used to explain the discrepancy between the Cardiac Responses of neonates and 6-month-old infants to stimulus presentation. (M. Lewis.)
Jerzy Bodurka - One of the best experts on this subject based on the ideXlab platform.
-
subject specific bold fmri respiratory and Cardiac Response functions obtained from global signal
NeuroImage, 2013Co-Authors: Maryam Falahpour, Hazem H Refai, Jerzy BodurkaAbstract:Subtle changes in either breathing pattern or Cardiac pulse rate alter blood oxygen level dependent functional magnetic resonance imaging signal (BOLD fMRI). This is problematic because such fluctuations could possibly not be related to underlying neuronal activations of interest but instead the source of physiological noise. Several methods have been proposed to eliminate physiological noise in BOLD fMRI data. One such method is to derive a template based on average multi-subject data for respiratory Response function (RRF) and Cardiac Response function (CRF) by simultaneously utilizing an external recording of Cardiac and respiratory waveforms with the fMRI. Standard templates can then be used to model, map, and remove respiration and Cardiac fluctuations from fMRI data. Utilizing these does not, however, account for intra-subject variations in physiological Response. Thus, performing a more individualized approach for single subject physiological noise correction becomes more desirable, especially for clinical purposes. Here we propose a novel approach that employs subject-specific RRF and CRF Response functions obtained from the whole brain or brain tissue-specific global signals (GS). Averaging multiple voxels in global signal computation ensures physiological noise dominance over thermal and system noise in even high-spatial-resolution fMRI data, making the GS suitable for deriving robust estimations of both RRF and CRF for individual subjects. Using these individualized Response functions instead of standard templates based on multi-subject averages judiciously removes physiological noise from the data, assuming that there is minimal neuronal contribution in the derived individualized filters. Subject-specific physiological Response functions obtained from the GS better maps individuals' physiological characteristics.
Gary H. Glover - One of the best experts on this subject based on the ideXlab platform.
-
influence of heart rate on the bold signal the Cardiac Response function
NeuroImage, 2009Co-Authors: Catie Chang, John P. Cunningham, Gary H. GloverAbstract:Abstract It has previously been shown that low-frequency fluctuations in both respiratory volume and Cardiac rate can induce changes in the blood-oxygen level dependent (BOLD) signal. Such physiological noise can obscure the detection of neural activation using fMRI, and it is therefore important to model and remove the effects of this noise. While a hemodynamic Response function relating respiratory variation (RV) and the BOLD signal has been described [Birn, R.M., Smith, M.A., Jones, T.B., Bandettini, P.A., 2008b. The respiration Response function: The temporal dynamics of fMRI signal fluctuations related to changes in respiration. Neuroimage 40, 644–654.], no such mapping for heart rate (HR) has been proposed. In the current study, the effects of RV and HR are simultaneously deconvolved from resting state fMRI. It is demonstrated that a convolution model including RV and HR can explain significantly more variance in gray matter BOLD signal than a model that includes RV alone, and an average HR Response function is proposed that well characterizes our subject population. It is observed that the voxel-wise morphology of the deconvolved RV Responses is preserved when HR is included in the model, and that its form is adequately modeled by Birn et al.'s previously-described respiration Response function. Furthermore, it is shown that modeling out RV and HR can significantly alter functional connectivity maps of the default-mode network.
Michael Lewis - One of the best experts on this subject based on the ideXlab platform.
-
Differential Cardiac Response to visual and auditory stimulation in the young child.
Psychophysiology, 2008Co-Authors: Michael Lewis, Sara Jane SpauldingAbstract:In this study, 24 infants, 6 months old, each received a series of visual and auditory stimuli. An analysis of their Cardiac Response indicates that onset of stimulus presentation results in a monophasic Response of Cardiac deceleration. Further, their Response to onset of presentation was compared to their Response to onset of visual orientation, and the data reveal that is it important for E to differentiate the Cardiac Response to presentation (E operation) from the onset of orientation (S operation). These results were used to explain the discrepancy between the Cardiac Responses of neonates and 6-month-old infants to stimulus presentation. (M. Lewis.)
Maryam Falahpour - One of the best experts on this subject based on the ideXlab platform.
-
subject specific bold fmri respiratory and Cardiac Response functions obtained from global signal
NeuroImage, 2013Co-Authors: Maryam Falahpour, Hazem H Refai, Jerzy BodurkaAbstract:Subtle changes in either breathing pattern or Cardiac pulse rate alter blood oxygen level dependent functional magnetic resonance imaging signal (BOLD fMRI). This is problematic because such fluctuations could possibly not be related to underlying neuronal activations of interest but instead the source of physiological noise. Several methods have been proposed to eliminate physiological noise in BOLD fMRI data. One such method is to derive a template based on average multi-subject data for respiratory Response function (RRF) and Cardiac Response function (CRF) by simultaneously utilizing an external recording of Cardiac and respiratory waveforms with the fMRI. Standard templates can then be used to model, map, and remove respiration and Cardiac fluctuations from fMRI data. Utilizing these does not, however, account for intra-subject variations in physiological Response. Thus, performing a more individualized approach for single subject physiological noise correction becomes more desirable, especially for clinical purposes. Here we propose a novel approach that employs subject-specific RRF and CRF Response functions obtained from the whole brain or brain tissue-specific global signals (GS). Averaging multiple voxels in global signal computation ensures physiological noise dominance over thermal and system noise in even high-spatial-resolution fMRI data, making the GS suitable for deriving robust estimations of both RRF and CRF for individual subjects. Using these individualized Response functions instead of standard templates based on multi-subject averages judiciously removes physiological noise from the data, assuming that there is minimal neuronal contribution in the derived individualized filters. Subject-specific physiological Response functions obtained from the GS better maps individuals' physiological characteristics.