2019
DOI: 10.1016/j.brs.2019.02.003
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The influence of respiration on brainstem and cardiovagal response to auricular vagus nerve stimulation: A multimodal ultrahigh-field (7T) fMRI study

Abstract: Background: There is significant evidence for cognitive decline following deep brain stimulation (DBS). Current stimulation paradigms utilize gamma frequency stimulation for optimal motor benefits; however, little has been done to optimize stimulation parameters for cognition. Recent evidence implicates subthalamic nucleus (STN) theta oscillations in executive function, and theta oscillations are well-known to relate to episodic memory, suggesting that theta frequency stimulation could potentially improve cogn… Show more

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Cited by 129 publications
(152 citation statements)
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“…However, optimized response for different clinical indications may depend on specific neuromodulation parameters, and systematic assessments of their influence are still needed to optimize the effects of this promising approach. Our study followed up on our previous work demonstrating enhanced brainstem response to taVNS delivered in the cymba conchae of the left ear during the exhalation phase of respiration (RAVANS [4,7,26]), and characterized the brainstem Fig. 3.…”
Section: Discussionmentioning
confidence: 97%
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“…However, optimized response for different clinical indications may depend on specific neuromodulation parameters, and systematic assessments of their influence are still needed to optimize the effects of this promising approach. Our study followed up on our previous work demonstrating enhanced brainstem response to taVNS delivered in the cymba conchae of the left ear during the exhalation phase of respiration (RAVANS [4,7,26]), and characterized the brainstem Fig. 3.…”
Section: Discussionmentioning
confidence: 97%
“…First-level General Linear Model (GLM) analyses were carried out for each subject and each scan run using an event-related design and the fMRI Expert Analysis Tool (FEAT v6.00, FSL). For each scan run, stimulation timings (recorded via Labview computer) were convolved with a set of three basis functions chosen by the FMRIB's Linear Optimal Basis Set (FLOBS, FSL) algorithm to account for the potential deviation of the brainstem response from the canonical hemodynamic impulse response function as well as the systematic influence of hemodynamic response to the prior exhalation/stimulus event, as in our previous brainstem-focused analyses [26]. Additional regressors of no interest were used for censoring of motion outliers (as estimated through the fsl_motio-n_outliers tool) and for cardiogenic pulsatility reduction in fMRI signals by convolving heart rate with the previously-reported cardiac response function [36].…”
Section: Brainstem-focused Fmri Data Analysesmentioning
confidence: 99%
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