Inter-subject analysis of transfer function coherence in studies of dynamic cerebral autoregulation

Area of Science:

• Neuroscience
• Biomedical Engineering
• Physiology

Background:

• Dynamic cerebral autoregulation (CA) is crucial for maintaining stable cerebral blood flow.
• Transfer function analysis (TFA) of arterial blood pressure (BP) and cerebral blood flow velocity (CBFV) are key CA metrics.
• The reliability of TFA metrics depends on the statistical significance of the magnitude squared coherence (MSC) function.

Purpose of the Study:

• To develop and validate a novel approach for estimating confidence limits of the MSC function using inter-subject data.
• To enhance the reliability and robustness of dynamic CA assessments.

Main Methods:

• Utilized five-minute beat-to-beat time series of mean arterial BP (MAP) and CBFV.
• Employed both intra-subject and inter-subject analyses, including swapping BP and CBFV data between subjects.
• Calculated 95% confidence limits of MSC using non-parametric methods for single frequency harmonics and averaged frequency intervals (0.02-0.50 Hz).

Main Results:

• Inter-subject MSC confidence limits showed excellent agreement with classical values derived from surrogate data.
• Averaging MSC over the frequency range (0.02-0.30 Hz) led to a decrease in confidence limits, stabilizing around 0.16.
• The new method demonstrated high reliability across 100 healthy subjects.

Conclusions:

• Estimating MSC using the mean value over a frequency range (0.02-0.30 Hz) offers a more robust approach than single frequency harmonics.
• This method can improve the acceptance of recordings in dynamic CA studies, particularly in clinical settings with potential noise and artifacts.
• The findings support more reliable clinical assessments of dynamic cerebral autoregulation.