Key result
Extended autoregressive modeling improves spectral quantification of baroreflex and cardiac run-off mechanisms.
Why the study?
Conventional Granger causality analyses of coupled physiological time series often neglect instantaneous dependencies despite their potential to reflect physiologically meaningful effects.
Does a single extended autoregressive model incorporating causally-oriented instantaneous dependencies improve the quantification of cardiovascular interactions (baroreflex and cardiac run-off mechanisms) compared to strictly causal and Geweke autoregressive models in healthy subjects during postural and mental stress?
Does a single extended autoregressive model incorporating causally-oriented instantaneous dependencies improve the quantification of cardiovascular interactions (baroreflex and cardiac run-off mechanisms) compared to strictly causal and Geweke autoregressive models in healthy subjects during postural and mental stress?
Accounting for causally-oriented instantaneous dependencies within a single extended autoregressive model enables more accurate time- and frequency-domain quantification of short-term cardiovascular regulation, including baroreflex and cardiac run-off mechanisms.
Answers are grounded in this paper and cite their sources.
May enhance cardiovascular coupling analysis in research; leaves open clinical validation before practice adoption.
The quantification of dynamic interactions in coupled physiological time series is a central question in biomedical signal processing. A critical issue is the presence of instantaneous dependencies, often neglected in conventional Granger causality (GC) analyses despite potentially reflecting physiologically meaningful effects. We investigate time- and frequency-domain measures of causality within the linear autoregressive (AR) framework, treating instantaneous dependencies according to three formulations: (i) the classical strictly causal AR model, providing spectral measures of time-lagged GC and instantaneous interaction; (ii) the Geweke approach, assigning instantaneous dependencies to the direction opposite to that under investigation; (iii) a single extended AR model incorporating causally-oriented instantaneous dependencies, yielding spectral GC measures accounting for both instantaneous and time-lagged causality. The three approaches are evaluated in simulated Gaussian systems, where dynamic measures can be derived analytically and compared with the expected coupling structure. The single extended AR model emerges as the most consistent formulation when instantaneous dependencies have a physiologically meaningful causal direction and is then applied to cardiovascular interactions between heart period (HP) and systolic (SAP) or diastolic arterial pressure (DAP) in healthy subjects during postural and mental stress. Accounting for instantaneous dependencies substantially affects HP-SAP and HP-DAP interactions, enabling better quantification of baroreflex and cardiac run-off mechanisms and characterization of their responses to stress and of low- and high-frequency dynamics. Overall, the framework provides consistent representation of causal interactions across time and frequency and highlights the importance of accounting for instantaneous dependencies in physiological coupling.
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Mijatović et al. (2026) studied Cardiovascular variability in healthy subjects during postural and mental stress. Single extended autoregressive (AR) model incorporating causally-oriented instantaneous dependencies vs. Classical strictly causal AR model and Geweke orthogonalized extended AR models was evaluated on Time- and frequency-domain Granger causality and total coupling between heart period (HP) and systolic (SAP) or diastolic arterial pressure (DAP). A single extended autoregressive model accounting for instantaneous causality provides non-negative spectral Granger causality measures and improves quantification of baroreflex and cardiac run-off mechanisms.
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