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

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 beatto-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).

Processing of fMRI-related anxiety and bi-directional information flow between prefrontal cortex and brain stem

“…In the brainstem, two structures in the pons were selected, a more rostral part (ROI 93) and a more caudal part (ROI 103). These two ROIs showed relatively stable results on cardiac-BOLD coupling 9 . Note that the locus coeruleus (LC) in the pons is involved in physiological responses to stress, anxiety, and depression, similar to the raphe nuclei in the brainstem.…”

“…Importantly, the respiratory BOLD artefact is present and constitutes an important marker for neuro-BOLD coupling in the brainstem. Interestingly, without any preprocessing of BOLD signals side-differences were found in the brainstem, with a dominance of respiratory BOLD artefacts in the right side and BOLD signals in the left side 9 . This was the reason that for our study only BOLD signals from the left hemisphere and left brainstem, respectively, were used.…”

“…In the present study, we used a within-person anxiety classification with elevated anxiety in the first resting states and low or no anxiety in the last resting states. Related studies on elevated fMRI-induced anxiety, which focused on phase coupling between beat-to-beat interval (RRI) and BOLD oscillations, reported slow neural and vascular BOLD components; note, the former lagging the latter, and most interestingly provided first evidence for the existence of a pacemaker-like oscillatory source in the brainstem 8 , 9 . So far, an open question refers to the direction of the information flow between the cortex and the brainstem and whether a possible rhythmic source in the brainstem contributes to the decline in anxiety.…”

Signal Generation, Acquisition, and Processing in Brain Machine Interfaces: A Unified Review

“…Complete understanding of FBR in brain is also required to invent and modify existing electrode technology. As detailed in this review, BMI development switched ( Hattie and Timperley, 2007 ) from metal microwires to silicon based micromachined electrodes ( Pfurtscheller et al, 2020 ) with the advent of lithographic techniques. Recently, interest has shifted toward flexible conductive polymer-based electrodes to better match the mechanical properties of the brain and to limit the neuroinflammatory response of the brain.…”

“…Based on fixed learning rates, research also shows that online classifier training produces better results than offline classifier training ( Millan, 2004 ). Monto et al proved the existence of a slow cortical excitability cycle, possibly controlled from structures within brain stem, hence, presentation of task (e.g., motor imagery) in such subject specific intervals may help shorten the training time ( Monto et al, 2008 ; Pfurtscheller et al, 2020 ).…”