3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Verification of a Central Pacemaker in Brain Stem by Phase-Coupling Analysis Between HR Interval- and BOLD-Oscillations in the 0.10–0.15 Hz Frequency Band

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The origin of slow intrinsic oscillations in resting states of functional magnetic resonance imaging (fMRI) signals is still a matter of debate. The present study aims to test the hypothesis that slow blood oxygenation level-dependent (BOLD) oscillations with frequency components greater than 0.10 Hz result from a central neural pacemaker located in the brain stem. We predict that a central oscillator modulates cardiac beat-to-beat interval (RRI) fluctuations rapidly, with only a short neural lag around 0.3 s. Spontaneous BOLD fluctuations in the brain stem, however, are considerably delayed due to the hemodynamic response time of about ∼2–3 s. In order to test these predictions, we analyzed the time delay between slow RRI oscillations from thorax and BOLD oscillations in the brain stem by calculating the phase locking value (PLV). Our findings show a significant time delay of 2.2 ± 0.2 s between RRI and BOLD signals in 12 out of 23 (50%) participants in axial slices of the pons/brain stem. Adding the neural lag of 0.3 s to the observed lag of 2.2 s we obtain 2.5 s, which is the time between neural activity increase and BOLD increase, termed neuro-BOLD coupling. Note, this time window for neuro-BOLD coupling in awake humans is surprisingly of similar size as in awake head-fixed adult mice ( Mateo et al., 2017).

          Related collections

          Most cited references52

          • Record: found
          • Abstract: found
          • Article: not found

          Multiband multislice GE-EPI at 7 tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain fMRI.

          Parallel imaging in the form of multiband radiofrequency excitation, together with reduced k-space coverage in the phase-encode direction, was applied to human gradient echo functional MRI at 7 T for increased volumetric coverage and concurrent high spatial and temporal resolution. Echo planar imaging with simultaneous acquisition of four coronal slices separated by 44mm and simultaneous 4-fold phase-encoding undersampling, resulting in 16-fold acceleration and up to 16-fold maximal aliasing, was investigated. Task/stimulus-induced signal changes and temporal signal behavior under basal conditions were comparable for multiband and standard single-band excitation and longer pulse repetition times. Robust, whole-brain functional mapping at 7 T, with 2 x 2 x 2mm(3) (pulse repetition time 1.25 sec) and 1 x 1 x 2mm(3) (pulse repetition time 1.5 sec) resolutions, covering fields of view of 256 x 256 x 176 mm(3) and 192 x 172 x 176 mm(3), respectively, was demonstrated with current gradient performance. (c) 2010 Wiley-Liss, Inc.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Measuring phase synchrony in brain signals

            This article presents, for the first time, a practical method for the direct quantification of frequency‐specific synchronization (i.e., transient phase‐locking) between two neuroelectric signals. The motivation for its development is to be able to examine the role of neural synchronies as a putative mechanism for long‐range neural integration during cognitive tasks. The method, called phase‐locking statistics (PLS), measures the significance of the phase covariance between two signals with a reasonable time‐resolution (<100 ms). Unlike the more traditional method of spectral coherence, PLS separates the phase and amplitude components and can be directly interpreted in the framework of neural integration. To validate synchrony values against background fluctuations, PLS uses surrogate data and thus makes no a priori assumptions on the nature of the experimental data. We also apply PLS to investigate intracortical recordings from an epileptic patient performing a visual discrimination task. We find large‐scale synchronies in the gamma band (45 Hz), e.g., between hippocampus and frontal gyrus, and local synchronies, within a limbic region, a few cm apart. We argue that whereas long‐scale effects do reflect cognitive processing, short‐scale synchronies are likely to be due to volume conduction. We discuss ways to separate such conduction effects from true signal synchrony. Hum Brain Mapping 8:194–208, 1999. © 1999 Wiley‐Liss, Inc.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI.

              Subtle changes in a subject's breathing rate or depth, which occur naturally during rest at low frequencies (<0.1 Hz), have been shown to be significantly correlated with fMRI signal changes throughout gray matter and near large vessels. The goal of this study was to investigate the impact of these low-frequency respiration variations on both task activation fMRI studies and resting-state functional connectivity analysis. Unlike MR signal changes correlated with the breathing motion ( approximately 0.3 Hz), BOLD signal changes correlated with across-breath variations in respiratory volume ( approximately 0.03 Hz) appear localized to blood vessels and regions with high blood volume, such as gray matter, similar to changes seen in response to a breath-hold challenge. In addition, the respiration-variation-induced signal changes were found to coincide with many of the areas identified as part of the 'default mode' network, a set of brain regions hypothesized to be more active at rest. Regions could therefore be classified as being part of a resting network based on their similar respiration-induced changes rather than their synchronized neuronal activity. Monitoring and removing these respiration variations led to a significant improvement in the identification of task-related activation and deactivation and only slight differences in regions correlated with the posterior cingulate at rest. Regressing out global signal changes or cueing the subject to breathe at a constant rate and depth resulted in an improved spatial overlap between deactivations and resting-state correlations among areas that showed deactivation.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                28 August 2020
                2020
                : 14
                : 922
                Affiliations
                [1] 1Institute of Neural Engineering, Graz University of Technology , Graz, Austria
                [2] 2BioTechMed Graz , Graz, Austria
                [3] 3Institute of Psychology, University of Graz , Graz, Austria
                [4] 4Carl-Ludwig-Institute of Physiology, University of Leipzig , Leipzig, Germany
                [5] 5Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon , Lisbon, Portugal
                [6] 6Division of Special Anaesthesiology, Pain and Intensive Care Medicine of Department of Anaesthesiology and Intensive Care Medicine, Medical University of Graz , Graz, Austria
                [7] 7Centre for Cognitive Neuroscience, University of Salzburg , Salzburg, Austria
                Author notes

                Edited by: Alberto Porta, University of Milan, Italy

                Reviewed by: André Diedrich, Vanderbilt University, United States; Michal Javorka, Comenius University, Slovakia

                *Correspondence: Gert Pfurtscheller, pfurtscheller@ 123456tugraz.at

                This article was submitted to Autonomic Neuroscience, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2020.00922
                7483659
                32982682
                7d1100c0-1950-452f-8152-cf9c236fd51f
                Copyright © 2020 Pfurtscheller, Schwerdtfeger, Rassler, Andrade, Schwarz and Klimesch.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 12 May 2020
                : 10 August 2020
                Page count
                Figures: 6, Tables: 3, Equations: 0, References: 70, Pages: 13, Words: 0
                Categories
                Neuroscience
                Original Research

                Neurosciences
                central pacemaker,brain stem,heart rate interval,bold oscillations,neurovascular coupling

                Comments

                Comment on this article