Linear and nonlinear analysis of human dynamic cerebral autoregulation

Abstract

The linear dynamic relationship between systemic arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) was studied by time- and frequency-domain analysis methods. A nonlinear moving-average approach was also implemented using Volterra-Wiener kernels. In 47 normal subjects, ABP was measured with Finapres and CBFV was recorded with Doppler ultrasound in both middle cerebral arteries at rest in the supine position and also during ABP drops induced by the sudden deflation of thigh cuffs. Impulse response functions estimated by Fourier transfer function analysis, a second-order mathematical model proposed by Tiecks, and the linear kernel of the Volterra-Wiener moving-average representation provided reconstructed velocity model responses, for the same segment of data, with significant correlations to CBFV recordings corresponding to r = 0.52 ± 0.19, 0.53 ± 0.16, and 0.67 ± 0.12 (mean ± SD), respectively. The correlation coefficient for the linear plus quadratic kernels was 0.82 ± 0.08, significantly superior to that for the linear models ( P < 10−6). The supine linear impulse responses were also used to predict the velocity transient of a different baseline segment of data and of the thigh cuff velocity response with significant correlations. In both cases, the three linear methods provided equivalent model performances, but the correlation coefficient for the nonlinear model dropped to 0.26 ± 0.25 for the baseline test set of data and to 0.21 ± 0.42 for the thigh cuff data. Whereas it is possible to model dynamic cerebral autoregulation in humans with different linear methods, in the supine position a second-order nonlinear component contributes significantly to improve model accuracy for the same segment of data used to estimate model parameters, but it cannot be automatically extended to represent the nonlinear component of velocity responses of different segments of data or transient changes induced by the thigh cuff test.

Aging blunts hyperventilation-induced hypocapnia and reduction in cerebral blood flow velocity during maximal exercise

“…Although we did not measure cerebral autoregulation (CA; i.e. the ability of the brain to regulate CBF relatively independent of changes in BP (Panerai et al 1999;Brys et al 2003;Paulson et al 1990)), CA is maintained during mildto-moderate exercise in YA (Ogoh et al 2005a), at rest in OA (reviewed in van Beek et al 2008) and during mild exercise in middle-aged OA (Ogoh et al 2005a;Fisher et al 2008). Some additional insight into CA may be provided from consideration of cerebrovascular resistance or conductance (Table 1).…”

Measuring cerebrovascular autoregulation in preterm infants using near-infrared spectroscopy: an overview of the literature

“…Whether sufficient coherence is a prerequisite for reliable autoregulation calculation using gain and TFA or coherence has value on its own for assessing autoregulation is still a matter of debate [64]. Despite this, the coherence variable itself is frequently used to describe autoregulation status in preterm infants.…”

Optimising the assessment of cerebral autoregulation from black box models

“…These segments of the recordings were normalised by their respective mean values (as used in previous works e.g. [8,22,23]), and the relative change (expressed in %) will be denoted by %ABP and %CBFV, respectively -see Figure 1.…”

“…Most of the studies of CA focus on linear methods [5,[7][8][9][10] with the more recent inclusion of some nonlinear approaches [8,[10][11][12][13]. Although nonlinear techniques can provide improved model fits, their benefit in assessing CA is still unclear with few studies having systematically compared them to linear alternatives.…”

“…Examples of such autoregulatory parameters include gain, phase and coherence in selected frequency ranges [5,7,8,14], or alternatively features of the step-response -e.g. slopes or amplitudes at selected points [9,14].…”