Wavelet phase synchronization analysis of cerebral blood flow autoregulation

Area of Science:

• Physiology
• Biomedical Engineering
• Neuroscience

Background:

• The relationship between arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) is crucial for understanding cerebral autoregulation.
• Previous studies using linear transfer function analysis and wavelet phase synchronization have indicated non-stationarity in this relationship, particularly in the low-frequency band.
• Low coherence and synchronization indices have been observed, suggesting limitations in linear and stationary assumptions.

Purpose of the Study:

• To investigate the impact of unmeasured variability, specifically end-tidal CO(2) (P(ETCO(2))), on the dynamic relationship between ABP and CBFV.
• To analytically and computationally demonstrate how P(ETCO(2)) can distort the phase difference between ABP and CBFV.
• To develop and validate a method for correcting this phase distortion to more accurately assess cerebral autoregulation.

Main Methods:

• Analytical derivation of phase distortion caused by a third variable (P(ETCO(2))) in a multi-input system.
• Utilization of a physiologically based cerebral hemodynamic model to simulate ABP, CBFV, and P(ETCO(2)) dynamics.
• Application of a CO(2) correction term to experimental data from 13 subjects to re-evaluate ABP-CBFV synchronization.

Main Results:

• The phase difference between ABP and CBFV is shown to be distorted by P(ETCO(2)) in a multi-input scenario.
• A method for correcting this phase distortion using known or estimated transfer functions is proven effective.
• A significantly increased synchronization index in the low-frequency band was observed after applying the CO(2) correction to experimental data.

Conclusions:

• The low synchronization previously observed between ABP and CBFV in the low-frequency band can be partly attributed to unmeasured variability, particularly P(ETCO(2)).
• Accounting for P(ETCO(2)) provides a more accurate representation of the true phase shift in cerebral autoregulation.
• This study highlights the importance of considering multiple inputs when analyzing the dynamic interactions within physiological systems like cerebral autoregulation.