Cerebral hemodynamics during orthostatic stress assessed by nonlinear modeling

Dynamic cerebral autoregulation is preserved during orthostasis and intrathoracic pressure regulation in healthy subjects: A pilot study

Resistance breathing may restore cardiac output (CO) and cerebral blood flow (CBF) during hypovolemia. We assessed CBF and cerebral autoregulation (CA) during tilt, resistance breathing, and paced breathing in 10 healthy subjects. Blood velocities in the internal carotid artery (ICA), middle cerebral arteries (MCA, four subjects), and aorta were measured by Doppler ultrasound in 30° and 60° semi-recumbent positions. ICA blood flow and CO were calculated. Arterial blood pressure (ABP, Finometer), and end-tidal CO2 (ETCO2) were recorded. ICA blood flow response was assessed by mixed-models regression analysis. The synchronization index (SI) for the variable pairs ABP-ICA blood velocity, ABP-MCA velocities in 0.005-0.08 Hz frequency interval was calculated as a measure of CA. Passive tilting from 30° to 60° resulted in 12% decrease in CO (p = 0.001); ICA blood flow tended to fall (p = 0.04); Resistance breathing restored CO and ICA blood flow despite a 10% ETCO2 drop. ETCO2 and CO contributed to ICA blood flow variance (adjusted R2: 0.9, p < 0.0001). The median SI was low (<0.2) indicating intact CA, confirmed by surrogate date testing. The peak SI was transiently elevated during resistance breathing in the 60° position. Resistance breathing may transiently reduce CA efficiency. Paced breathing did not restore CO or ICA blood flow.

Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet)

Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant supply of blood flow, CA plays a critical role in brain function. Quantifying CA under different physiological and pathological states is crucial for understanding its implications. This knowledge may serve as a foundation for informed clinical decision-making, particularly in cases where CA may become impaired. The quantification of CA functionality typically involves constructing models that capture the relationship between CPP (or arterial blood pressure) and experimental measures of CBF. Besides describing normal CA function, these models provide a means to detect possible deviations from the latter. In this context, a recent white paper from the Cerebrovascular Research Network focused on Transfer Function Analysis (TFA), which obtains frequency domain estimates of dynamic CA. In the present paper, we consider the use of time-domain techniques as an alternative approach. Due to their increased flexibility, time-domain methods enable the mitigation of measurement/physiological noise and the incorporation of nonlinearities and time variations in CA dynamics. Here, we provide practical recommendations and guidelines to support researchers and clinicians in effectively utilizing these techniques to study CA.

Time-Series Modeling and Forecasting of Cerebral Pressure-Flow Physiology: A Scoping Systematic Review of the Human and Animal Literature

The modeling and forecasting of cerebral pressure-flow dynamics in the time-frequency domain have promising implications for veterinary and human life sciences research, enhancing clinical care by predicting cerebral blood flow (CBF)/perfusion, nutrient delivery, and intracranial pressure (ICP)/compliance behavior in advance. Despite its potential, the literature lacks coherence regarding the optimal model type, structure, data streams, and performance. This systematic scoping review comprehensively examines the current landscape of cerebral physiological time-series modeling and forecasting. It focuses on temporally resolved cerebral pressure-flow and oxygen delivery data streams obtained from invasive/non-invasive cerebral sensors. A thorough search of databases identified 88 studies for evaluation, covering diverse cerebral physiologic signals from healthy volunteers, patients with various conditions, and animal subjects. Methodologies range from traditional statistical time-series analysis to innovative machine learning algorithms. A total of 30 studies in healthy cohorts and 23 studies in patient cohorts with traumatic brain injury (TBI) concentrated on modeling CBFv and predicting ICP, respectively. Animal studies exclusively analyzed CBF/CBFv. Of the 88 studies, 65 predominantly used traditional statistical time-series analysis, with transfer function analysis (TFA), wavelet analysis, and autoregressive (AR) models being prominent. Among machine learning algorithms, support vector machine (SVM) was widely utilized, and decision trees showed promise, especially in ICP prediction. Nonlinear models and multi-input models were prevalent, emphasizing the significance of multivariate modeling and forecasting. This review clarifies knowledge gaps and sets the stage for future research to advance cerebral physiologic signal analysis, benefiting neurocritical care applications.

Can Alterations in Cerebrovascular CO2 Reactivity Be Identified Using Transfer Function Analysis without the Requirement for Carbon Dioxide Inhalation?

The present study aimed to examine the validity of a novel method to assess cerebrovascular carbon dioxide (CO₂) reactivity (CVR) that does not require a CO₂ inhalation challenge, e.g., for use in patients with respiratory disease or the elderly, etc. In twenty-one healthy participants, CVR responses to orthostatic stress (50° head-up tilt, HUT) were assessed using two methods: (1) the traditional CO₂ inhalation method, and (2) transfer function analysis (TFA) between middle cerebral artery blood velocity (MCA V) and predicted arterial partial pressure of CO₂ (PaCO₂) during spontaneous respiration. During HUT, MCA V steady-state (i.e., magnitude) and MCA V onset (i.e., time constant) responses to CO₂ inhalation were decreased (p < 0.001) and increased (p = 0.001), respectively, indicative of attenuated CVR. In contrast, TFA gain in the very low-frequency range (VLF, 0.005-0.024 Hz) was unchanged, while the TFA phase in the VLF approached zero during HUT (-0.38 ± 0.59 vs. 0.31 ± 0.78 radians, supine vs. HUT; p = 0.003), indicative of a shorter time (i.e., improved) response of CVR. These findings indicate that CVR metrics determined by TFA without a CO₂ inhalation do not track HUT-evoked reductions in CVR identified using CO₂ inhalation, suggesting that enhanced cerebral blood flow response to a change in CO₂ using CO₂ inhalation is necessary to assess CVR adequately.

Cerebral blood flow response to cardiorespiratory oscillations in healthy humans

Dynamic cerebral autoregulation (CA) characterizes the cerebral blood flow (CBF) response to abrupt changes in arterial blood pressure (ABP). CA operates at frequencies below 0.15 Hz. ABP regulation and probably CA are modified by autonomic nervous activity. We investigated the CBF response and CA dynamics to mild increase in sympathetic activity. Twelve healthy volunteers underwent oscillatory lower body negative pressure (oLBNP), which induced respiratory-related ABP oscillations at an average of 0.22 Hz. We recorded blood velocity in the internal carotid artery (ICA) by Doppler ultrasound and ABP. We quantified variability and peak wavelet power of ABP and ICA blood velocity by wavelet analysis at low frequency (LF, 0.05-0.15 Hz) and Mayer waves (0.08-0.12 Hz), respectively. CA was quantified by calculation of the wavelet synchronization gamma index for the pair ABP-ICA blood velocity in the LF and Mayer wave band. oLBNP increased ABP peak wavelet power at the Mayer wave frequency. At the Mayer wave, ABP peak wavelet power increased by >70 % from rest to oLBNP (p < 0.05), while ICA blood flow velocity peak wavelet power was unchanged, and gamma index increased (from 0.49 to 0.69, p < 0.05). At LF, variability in both ABP and ICA blood velocity and gamma index were unchanged from rest to oLBNP. Despite an increased gamma index at Mayer wave, ICA blood flow variability was unchanged during increased ABP variability. The increased synchronization during oLBNP did not cause less stable CBF or less active CA. Sympathetic activation seems to improve the mechanisms of CA.

Two-Tiered Response of Cardiorespiratory-Cerebrovascular Network to Orthostatic Challenge

Dynamic interdependencies within and between physiological systems and subsystems are key for homeostatic mechanisms to establish an optimal state of the organism. These interactions mediate regulatory responses elicited by various perturbations, such as the high-pressure baroreflex and cerebral autoregulation, alleviating the impact of orthostatic stress on cerebral hemodynamics and oxygenation. The aim of this study was to evaluate the responsiveness of the cardiorespiratory-cerebrovascular networks by capturing linear and nonlinear interdependencies to postural changes. Ten young healthy adults participated in our study. Non-invasive measurements of arterial blood pressure (from that cardiac cycle durations were derived), breath-to-breath interval, cerebral blood flow velocity (BFV, recorded by transcranial Doppler sonography), and cerebral hemodynamics (HbT, total hemoglobin content monitored by near-infrared spectroscopy) were performed for 30-min in resting state, followed by a 1-min stand-up and a 1-min sit-down period. During preprocessing, noise was filtered and the contribution of arterial blood pressure was regressed from BFV and HbT signals. Cardiorespiratory-cerebrovascular networks were reconstructed by computing pair-wise Pearson-correlation or mutual information between the resampled signals to capture their linear and/or nonlinear interdependencies, respectively. The interdependencies between cardiac, respiratory, and cerebrovascular dynamics showed a marked weakening after standing up persisting throughout the sit-down period, which could mainly be attributed to strikingly attenuated nonlinear coupling. To summarize, we found that postural changes induced topological changes in the cardiorespiratory-cerebrovascular network. The dissolution of nonlinear networks suggests that the complexity of key homeostatic mechanisms maintaining cerebral hemodynamics and oxygenation is indeed sensitive to physiological perturbations such as orthostatic stress.

Physiology of Human Hemorrhage and Compensation

Hemorrhage is a leading cause of death following traumatic injuries in the United States. Much of the previous work in assessing the physiology and pathophysiology underlying blood loss has focused on descriptive measures of hemodynamic responses such as blood pressure, cardiac output, stroke volume, heart rate, and vascular resistance as indicators of changes in organ perfusion. More recent work has shifted the focus toward understanding mechanisms of compensation for reduced systemic delivery and cellular utilization of oxygen as a more comprehensive approach to understanding the complex physiologic changes that occur following and during blood loss. In this article, we begin with applying dimensional analysis for comparison of animal models, and progress to descriptions of various physiological consequences of hemorrhage. We then introduce the complementary side of compensation by detailing the complexity and integration of various compensatory mechanisms that are activated from the initiation of hemorrhage and serve to maintain adequate vital organ perfusion and hemodynamic stability in the scenario of reduced systemic delivery of oxygen until the onset of hemodynamic decompensation. New data are introduced that challenge legacy concepts related to mechanisms that underlie baroreflex functions and provide novel insights into the measurement of the integrated response of compensation to central hypovolemia known as the compensatory reserve. The impact of demographic and environmental factors on tolerance to hemorrhage is also reviewed. Finally, we describe how understanding the physiology of compensation can be translated to applications for early assessment of the clinical status and accurate triage of hypovolemic and hypotensive patients. © 2021 American Physiological Society. Compr Physiol 11:1531-1574, 2021.

Sex differences in the autonomic and cerebrovascular responses to upright tilt

Sex differences in the regulation of autonomic and cerebrovascular responses to orthostatic stress remain unclear. The objectives of this study were to concurrently investigate autonomic control and cerebrovascular resistance indices, including critical closing pressure (CrCP) and resistance area product (RAP), during upright tilt in men and women. In 13 women and 14 men (18-29 years), ECG, non-invasive blood pressure, middle cerebral artery blood velocity, and end-tidal CO₂ (ETCO₂) were continuously measured during supine rest and 70° tilt. Heart rate variability (HRV), cardiovagal baroreflex sensitivity (cBRS), and transfer function parameters of dynamic cerebral autoregulation were calculated. Compared to supine, upright tilt increased the low frequency-to-high frequency ratio of HRV in men only (P = 0.044), and decreased cBRS more in women (P = 0.001). Cerebrovascular resistance index (CVRi) increased during tilt only in men (sex-by-time interaction: P = 0.004). RAP was lower in women throughout tilt (main effect of sex: P = 0.022). CrCP decreased during tilt in both sexes (main effect of time: P < 0.001). Normalizing to ETCO2 did not alter the effect of tilt on cerebrovascular resistance. Men displayed a greater increase of sympathetic indices and CVRi during tilt while women had greater parasympathetic withdrawal. We hypothesize that increased sympathetic activity in men may drive sex differences in the cerebrovascular response to upright posture.

Rude mechanicals in brain haemodynamics: non-neural actors that influence blood flow

Fluctuations in blood oxygenation and flow are widely used to infer brain activity during resting-state functional magnetic resonance imaging (fMRI). However, there are strong systemic and vascular contributions to resting-state signals that are unrelated to ongoing neural activity. Importantly, these non-neural contributions to haemodynamic signals (or 'rude mechanicals') can be as large as or larger than the neurally evoked components. Here, we review the two broad classes of drivers of these signals. One is systemic and is tied to fluctuations in external drivers such as heart rate and breathing, and the robust autoregulatory mechanisms that try to maintain a constant milieu in the brain. The other class comprises local, active fluctuations that appear to be intrinsic to vascular tissue and are likely similar to active local fluctuations seen in vasculature all over the body. In this review, we describe these non-neural fluctuations and some of the tools developed to correct for them when interpreting fMRI recordings. However, we also emphasize the links between these vascular fluctuations and brain physiology and point to ways in which fMRI measurements can be used to exploit such links to gain valuable information about neurovascular health and about internal brain states. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

Quantification of dynamic cerebral autoregulation and CO2 dynamic vasomotor reactivity impairment in essential hypertension

The study of dynamic cerebral autoregulation (DCA) in essential hypertension has received considerable attention because of its clinical importance. Several studies have examined the dynamic relationship between spontaneous beat-to-beat arterial blood pressure data and contemporaneous cerebral blood flow velocity measurements (obtained via transcranial Doppler at the middle cerebral arteries) in the form of a linear input-output model using transfer function analysis. This analysis is more reliable when the contemporaneous effects of changes in blood CO₂ tension are also taken into account, because of the significant effects of CO₂ dynamic vasomotor reactivity (DVR) upon cerebral flow. In this article, we extract such input-output predictive models from spontaneous time series hemodynamic data of 24 patients with essential hypertension and 20 normotensive control subjects under resting conditions, using the novel methodology of principal dynamic modes (PDMs) that achieves improved estimation accuracy over previous methods for relatively short and noisy data. The obtained data-based models are subsequently used to compute indexes and markers that quantify DCA and DVR in each subject or patient and therefore can be used to assess the effects of essential hypertension. These model-based DCA and DVR indexes were properly defined to capture the observed effects of DCA and VR and found to be significantly different (P < 0.05) in the hypertensive patients. We also found significant differences between patients and control subjects in the relative contribution of three PDMs to the model output prediction, a finding that offers the prospect of identifying the physiological mechanisms affected by essential hypertension when the PDMs are interpreted in terms of specific physiological mechanisms.NEW & NOTEWORTHY This article presents novel model-based methodology for obtaining diagnostic indexes of dynamic cerebral autoregulation and dynamic vasomotor reactivity in hypertension.

Cerebrovascular Dynamics During Continuous Motor Task

We investigated the cerebral autoregulation (CA) dynamics parameter phase and gain change when exposed to a longlasting motor task. 25 healthy subjects (mean age ± SE, 38±2.6 years, 13 females) underwent simultaneous recordings of spontaneous fluctuations in blood pressure (BP), cerebral blood flow velocity (CBFV), and end-tidal CO(2) (ETCO(2)) over 5 min of rest followed by 5 min of left elbow flexion at a frequency of 1 Hz. Tansfer function gain and phase between BP and CBFV were assessed in the frequency ranges of very low frequencies (VLF, 0.02-0.07 Hz), low frequencies (LF, 0.07-0.15), and high frequencies (HF, >0.15). CBFV increased on both sides rapidly to maintain an elevated steady state until movement stopped. Cerebrovascular resistance fell on the right side (rest 1.35±0.06, movement 1.28±0.06, p<0.01), LF gain decreased from baseline (right side 0.97±0.07 %/mm Hg, left 1.01±0.09) to movement epoch (right 0.73±0.08, left 0.76±0.06, p</=0.01). VLF phase decreased from baseline (right 1.03±0.05 radians, left 1.10±0.06) to the movement epoch (right 0.81±0.07, left 0.82±0.10, p?0.05). CA regulates continuous motor efforts by changes in resistance, gain and phase.

Lower Body Negative Pressure: Physiological Effects, Applications, and Implementation

This review presents lower body negative pressure (LBNP) as a unique tool to investigate the physiology of integrated systemic compensatory responses to altered hemodynamic patterns during conditions of central hypovolemia in humans. An early review published in Physiological Reviews over 40 yr ago (Wolthuis et al. Physiol Rev 54: 566-595, 1974) focused on the use of LBNP as a tool to study effects of central hypovolemia, while more than a decade ago a review appeared that focused on LBNP as a model of hemorrhagic shock (Cooke et al. J Appl Physiol (1985) 96: 1249-1261, 2004). Since then there has been a great deal of new research that has applied LBNP to investigate complex physiological responses to a variety of challenges including orthostasis, hemorrhage, and other important stressors seen in humans such as microgravity encountered during spaceflight. The LBNP stimulus has provided novel insights into the physiology underlying areas such as intolerance to reduced central blood volume, sex differences concerning blood pressure regulation, autonomic dysfunctions, adaptations to exercise training, and effects of space flight. Furthermore, approaching cardiovascular assessment using prediction models for orthostatic capacity in healthy populations, derived from LBNP tolerance protocols, has provided important insights into the mechanisms of orthostatic hypotension and central hypovolemia, especially in some patient populations as well as in healthy subjects. This review also presents a concise discussion of mathematical modeling regarding compensatory responses induced by LBNP. Given the diverse applications of LBNP, it is to be expected that new and innovative applications of LBNP will be developed to explore the complex physiological mechanisms that underline health and disease.

Lower body negative pressure to safely reduce intracranial pressure

KEY POINTS

During long-term missions, some astronauts experience structural and functional changes of the eyes and brain which resemble signs/symptoms experienced by patients with intracranial hypertension. Weightlessness prevents the normal cerebral volume and pressure 'unloading' associated with upright postures on Earth, which may be part of the cerebral and ocular pathophysiology. By placing the lower body in a negative pressure device (LBNP) that pulls fluid away from cranial compartments, we simulated effects of gravity and significantly lowered pressure within the brain parenchyma and ventricle compartments. Application of incremental LBNP demonstrated a non-linear dose-response curve, suggesting 20 mmHg LBNP as the optimal level for reducing pressure in the brain without impairing cerebral perfusion pressure. This non-invasive method of reducing pressure in the brain holds potential as a countermeasure in space as well as having treatment potential for patients on Earth with traumatic brain injury or other pathology leading to intracranial hypertension.

ABSTRACT

Patients with elevated intracranial pressure (ICP) exhibit neuro-ocular symptoms including headache, papilloedema and loss of vision. Some of these symptoms are also present in astronauts during and after prolonged space-flight where lack of gravitational stress prevents daily lowering of ICP associated with upright posture. Lower body negative pressure (LBNP) simulates the effects of gravity by displacing fluid caudally and we hypothesized that LBNP would lower ICP without compromising cerebral perfusion. Ten cerebrally intact volunteers were included: six ambulatory neurosurgical patients with parenchymal ICP-sensors and four former cancer patients with Ommaya-reservoirs to the frontal horn of a lateral ventricle. We applied LBNP while recording ICP and blood pressure while supine, and during simulated intracranial hypertension by 15° head-down tilt. LBNP from 0 to 50 mmHg at increments of 10 mmHg lowered ICP in a non-linear dose-dependent fashion; when supine (n = 10), ICP was decreased from 15 ± 2 mmHg to 14 ± 4, 12 ± 5, 11 ± 4, 10 ± 3 and 9 ± 4 mmHg, respectively (P < 0.0001). Cerebral perfusion pressure (CPP), calculated as mean arterial blood pressure at midbrain level minus ICP, was unchanged (from 70 ± 12 mmHg to 67 ± 9, 69 ± 10, 70 ± 12, 72 ± 13 and 74 ± 15 mmHg; P = 0.02). A 15° head-down tilt (n = 6) increased ICP to 26 ± 4 mmHg, while application of LBNP lowered ICP (to 21 ± 4, 20 ± 4, 18 ± 4, 17 ± 4 and 17 ± 4 mmHg; P < 0.0001) and increased CPP (P < 0.01). An LBNP of 20 mmHg may be the optimal level to lower ICP without impairing CPP to counteract spaceflight-associated neuro-ocular syndrome in astronauts. Furthermore, LBNP holds clinical potential as a safe, non-invasive method for lowering ICP and improving CPP for patients with pathologically elevated ICP on Earth.

Prediction of the Time to Syncope Occurrence in Patients Diagnosed with Vasovagal Syncope

OBJECTIVE

In this study we aimed to predict the time to syncope occurrence (TSO) in patients with vasovagal syncope (VVS), solely based on measurements recorded during the supine position of the head-up tilt (HUT) testing protocol.

METHODS

We extracted various time and frequency domain features related to morphological aspects of arterial blood pressure (ABP) and the electrocardiogram (ECG) raw signals as well as to dynamic interactions between beat-to-beat ABP, heart rate, and cerebral blood flow velocity. From these we identified the most predictive features related to TSO.

RESULTS

Specifically, when no orthostatic stress is involved, TSO in VVS patients can be predicted with high accuracy from a set of only five ECG features.

Dynamic cerebral autoregulation during cognitive task: effect of hypoxia

Changes in cerebral blood flow (CBF) subsequent to alterations in the partial pressures of oxygen and carbon dioxide can modify dynamic cerebral autoregulation (CA). While cognitive activity increases CBF, the extent to which it impacts CA remains to be established. In the present study we determined whether dynamic CA would decrease during a cognitive task and whether hypoxia would further compound impairment. Fourteen young healthy subjects performed a simple Go/No-go task during normoxia and hypoxia (inspired O₂ fraction = 12%), and the corresponding relationship between mean arterial pressure (MAP) and mean middle cerebral artery blood velocity (MCA V_mean) was examined. Dynamic CA and steady-state changes in MCA V in relation to changes in arterial pressure were evaluated with transfer function analysis. While MCA V_mean increased during the cognitive activity ( P < 0.001), hypoxia did not cause any additional changes ( P = 0.804 vs. normoxia). Cognitive performance was also unaffected by hypoxia (reaction time, P = 0.712; error, P = 0.653). A decrease in the very low- and low-frequency phase shift (VLF and LF; P = 0.021 and P = 0.01) and an increase in LF gain were observed ( P = 0.037) during cognitive activity, implying impaired dynamic CA. While hypoxia also increased VLF gain ( P < 0.001), it failed to cause any additional modifications in dynamic CA. Collectively, our findings suggest that dynamic CA is impaired during cognitive activity independent of altered systemic O₂ availability, although we acknowledge the interpretive complications associated with additional competing, albeit undefined, inputs that could potentially distort the MAP-MCA V_mean relationship. NEW & NOTEWORTHY During normoxia, cognitive activity while increasing cerebral perfusion was shown to attenuate dynamic cerebral autoregulation (CA) yet failed to alter reaction time, thereby questioning its functional significance. No further changes were observed during hypoxia, suggesting that impaired dynamic CA occurs independently of altered systemic O₂ availability. However, impaired dynamic CA may reflect a technical artifact, given the confounding influence of additional inputs that could potentially distort the mean arterial pressure-mean middle cerebral artery blood velocity relationship.

Applying time-frequency analysis to assess cerebral autoregulation during hypercapnia

OBJECTIVE

Classic methods for assessing cerebral autoregulation involve a transfer function analysis performed using the Fourier transform to quantify relationship between fluctuations in arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV). This approach usually assumes the signals and the system to be stationary. Such an presumption is restrictive and may lead to unreliable results. The aim of this study is to present an alternative method that accounts for intrinsic non-stationarity of cerebral autoregulation and the signals used for its assessment.

METHODS

Continuous recording of CBFV, ABP, ECG, and end-tidal CO2 were performed in 50 young volunteers during normocapnia and hypercapnia. Hypercapnia served as a surrogate of the cerebral autoregulation impairment. Fluctuations in ABP, CBFV, and phase shift between them were tested for stationarity using sphericity based test. The Zhao-Atlas-Marks distribution was utilized to estimate the time-frequency coherence (TFCoh) and phase shift (TFPS) between ABP and CBFV in three frequency ranges: 0.02-0.07 Hz (VLF), 0.07-0.20 Hz (LF), and 0.20-0.35 Hz (HF). TFPS was estimated in regions locally validated by statistically justified value of TFCoh. The comparison of TFPS with spectral phase shift determined using transfer function approach was performed.

RESULTS

The hypothesis of stationarity for ABP and CBFV fluctuations and the phase shift was rejected. Reduced TFPS was associated with hypercapnia in the VLF and the LF but not in the HF. Spectral phase shift was also decreased during hypercapnia in the VLF and the LF but increased in the HF. Time-frequency method led to lower dispersion of phase estimates than the spectral method, mainly during normocapnia in the VLF and the LF.

CONCLUSION

The time-frequency method performed no worse than the classic one and yet may offer benefits from lower dispersion of phase shift as well as a more in-depth insight into the dynamic nature of cerebral autoregulation.

Indexes of cerebral autoregulation do not reflect impairment in syncope: insights from head-up tilt test of vasovagal and autonomic failure subjects

PURPOSE

The study of dynamic cerebral autoregulation (CA), which adapts cerebral blood flow to arterial blood pressure (ABP) fluctuations, has been limited in orthostatic intolerance syndromes, mainly due to its stationary prerequisites hardly to meet during maneuvers to provoke syncope itself. New techniques of continuous estimates of CA could overcome this pitfall. We aimed to evaluate CA during head-up tilt test in common conditions causing syncope.

METHODS

We compared three groups: eight controls; eight patients with autonomic failure due to familial amyloidotic polyneuropathy; eight patients with vasovagal syncope (VVS). ABP and cerebral blood flow velocity (CBFV) were measured with Finometer^® and transcranial Doppler. We calculated cerebrovascular resistance index (CVRi), critical closing pressure (CrCP) and resistance area product (RAP), and derived CA continuously from autoregulation index [ARI(t)].

RESULTS

With HUTT, AF subjects showed a pronounced decrease in CBFV (-36 ± 17 versus -7 ± 6%, p < 0.0001), ABP (-29 ± 27 versus 7 ± 12%, p < 0.0001) and RAP (-17 ± 23 versus 3 ± 18%, p < 0.0001) but not CVRi (p = 0.110). VVS subjects showed progressive cerebral vasoconstriction prior to syncope, (reduced CBFV 19 ± 15 versus 1 ± 6, p < 0.000; increased RAP 12 ± 18 versus 2 ± 3%, p = 0.024 and CVRi 12 ± 18 versus 2 ± 3%, p = 0.005). ARI(t) increased significantly in AF patients (5.7 ± 1.2 versus 6.9 ± 1.2, p = 0.040) and VVS (5.8 ± 1.2 versus 7.3 ± 1.2, p = 0.015) in response to ABP fall during syncope.

CONCLUSIONS

Our data suggest that dynamic cerebral autoregulatory response to orthostatic challenge is neither affected by autonomic dysfunction nor in neutrally mediated syncope. This study also emphasizes that RAP + CrCP model is more informative than CVRi, mainly during cerebral vasodilatory response to orthostatic hypotension.

Detection of Impaired Sympathetic Cerebrovascular Control Using Functional Biomarkers Based on Principal Dynamic Mode Analysis

This study sought to determine whether models of cerebrovascular function based on Laguerre-Volterra kernels that account for nonlinear cerebral blood flow (CBF) dynamics can detect the effects of functional cerebral sympathetic blockade. We retrospectively analyzed continuous beat-to-beat blood pressure, middle cerebral blood velocity, and partial-pressure of end-tidal CO₂ (P_ETCO₂) recordings from eighteen healthy individuals who were treated with either an oral dose of the α₁-adrenergic receptor blocker Prazosin or a placebo treatment. The global principal dynamic modes (PDMs) were analyzed using Laguerre-Volterra kernels to examine the nonlinear system dynamics. Our principal findings were: (1) very low frequency (<0.03 Hz) linear components of first-order kernels for BP and P_ETCO₂ are mutually coupled to CBF dynamics with the ability to separate individuals between control and blockade conditions, and (2) the gains of the nonlinear functions associated with low-pass and ≈0.03 Hz global PDMs for the BP are sensitive to sympathetic blockade. Collectively these results suggest that very low frequency global PDMs for BP may have potential utility as functional biomarkers of sympathetic neurovascular dysfunction which can occur in conditions like autonomic failure, stroke and traumatic brain injury.

Comparison of Model-Based Indices of Cerebral Autoregulation and Vasomotor Reactivity Using Transcranial Doppler versus Near-Infrared Spectroscopy in Patients with Amnestic Mild Cognitive Impairment

We recently introduced model-based "physiomarkers" of dynamic cerebral autoregulation and CO2 vasomotor reactivity as an aid for diagnosis of early-stage Alzheimer's disease (AD) [1], where significant impairment of dynamic vasomotor reactivity (DVR) was observed in early-stage AD patients relative to age-matched controls. Milder impairment of DVR was shown in patients with amnestic mild cognitive impairment (MCI) using the same approach in a subsequent study [2]. The advocated approach utilizes subject-specific data-based models of cerebral hemodynamics to quantify the dynamic effects of resting-state changes in arterial blood pressure and end-tidal CO2 (the putative inputs) upon cerebral blood flow velocity (the putative output) measured at the middle cerebral artery via transcranial Doppler (TCD). The obtained input-output models are then used to compute model-based indices of DCA and DVR from model-predicted responses to an input pressure pulse or an input CO2 pulse, respectively. In this paper, we compare these model-based indices of DVR and DCA in 46 amnestic MCI patients, relative to 20 age-matched controls, using TCD measurements with their counterparts using Near-Infrared Spectroscopy (NIRS) measurements of blood oxygenation at the lateral prefrontal cortex in 43 patients and 22 age-matched controls. The goal of the study is to assess whether NIRS measurements can be used instead of TCD measurements to obtain model-based physiomarkers with comparable diagnostic utility. The results corroborate this view in terms of the ability of either output to yield model-based physiomarkers that can differentiate the group of aMCI patients from age-matched healthy controls.

The Leicester cerebral haemodynamics database: normative values and the influence of age and sex

Normative values of physiological parameters hold significance in modern day clinical decision-making. Lack of such normative values has been a major hurdle in the translation of research into clinical practice. A large database containing uniform recordings was constructed to allow more robust estimates of normative ranges and also assess the influence of age and sex. Doppler recordings were performed on healthy volunteers in the same laboratory, using similar protocols and equipment. Beat-to-beat blood pressure, heart-rate, electrocardiogram, and end-tidal CO2 were measured continuously. Bilateral insonation of the middle cerebral arteries (MCAs) was performed using TCD following a 15 min stabilisation, and a 5 min baseline recording. Good quality Doppler recordings for both MCAs were obtained in 129 participants (57 female) with a median age of 57 years (range 20-82). Age was found to influence baseline haemodynamic and transfer function analysis parameters. Cerebral blood flow velocity and critical closing pressure were the only sex-related differences found, which was significantly higher in females than males. Normative values for cerebral haemodynamic parameters have been defined in a large, healthy population. Such age/sex-defined normal values can be used to reduce the burden of collecting additional control data in future studies, as well as to identify disease-associated changes.

Multiple-input nonlinear modelling of cerebral haemodynamics using spontaneous arterial blood pressure, end-tidal CO2 and heart rate measurements

In order to examine the effect of changes in heart rate (HR) upon cerebral perfusion and autoregulation, we include the HR signal recorded from 18 control subjects as a third input in a two-input model of cerebral haemodynamics that has been used previously to quantify the dynamic effects of changes in arterial blood pressure and end-tidal CO2upon cerebral blood flow velocity (CBFV) measured at the middle cerebral arteries via transcranial Doppler ultrasound. It is shown that the inclusion of HR as a third input reduces the output prediction error in a statistically significant manner, which implies that there is a functional connection between HR changes and CBFV. The inclusion of nonlinearities in the model causes further statistically significant reduction of the output prediction error. To achieve this task, we employ the concept of principal dynamic modes (PDMs) that yields dynamic nonlinear models of multi-input systems using relatively short data records. The obtained PDMs suggest model-driven quantitative hypotheses for the role of sympathetic and parasympathetic activity (corresponding to distinct PDMs) in the underlying physiological mechanisms by virtue of their relative contributions to the model output. These relative PDM contributions are subject-specific and, therefore, may be used to assess personalized characteristics for diagnostic purposes.

Model-based indices describing cerebrovascular dynamics

Understanding the dynamic relationship between cerebral blood flow (CBF) and the circulation of cerebrospinal fluid (CSF) can facilitate management of cerebral pathologies. For this reason, various hydrodynamic models have been introduced in order to simulate the phenomena governing the interaction between CBF and CSF. The identification of hydrodynamic models requires an array of signals as input, with the most common of them being arterial blood pressure, intracranial pressure, and cerebral blood flow velocity; monitoring all of them is considered as a standard practice in neurointensive care. Based on these signals, physiological parameters like cerebrovascular resistance, compliances of cerebrovascular bed, and CSF space could then be estimated. Various secondary model-based indices describing cerebrovascular dynamics have been introduced, like the cerebral arterial time constant or critical closing pressure. This review presents model-derived indices that describe cerebrovascular phenomena, the nature of which is both physiological (carbon dioxide reactivity and arterial hypotension) and pathological (cerebral artery stenosis, intracranial hypertension, and cerebral vasospasm). In a neurointensive environment, real-time monitoring of a patient with these indices may be able to provide a detection of the onset of a cerebrovascular phenomenon, which could have otherwise been missed. This potentially "early warning" indicator may then prove to be important for the therapeutic management of the patient.

Effects of cerebral ischemia on human neurovascular coupling, CO2 reactivity, and dynamic cerebral autoregulation

Cerebral blood flow (CBF) regulation can be impaired in acute ischemic stroke but the combined effects of dynamic cerebral autoregulation (CA), CO2 cerebrovascular reactivity (CVR), and neurovascular coupling (NVC), obtained from simultaneous measurements, have not been described. CBF velocity in the middle cerebral artery (MCA) (CBFv, transcranial Doppler), blood pressure (BP, Finometer), and end-tidal Pco2 (PetCO2 , infrared capnography) were recorded during a 1-min passive movement of the arm in 27 healthy controls [mean age (SD) 61.4 (6.0) yr] and 27 acute stroke patients [age 63 (11.7) yr]. A multivariate autoregressive-moving average model was used to separate the contributions of BP, arterial Pco2 (PaCO2 ), and the neural activation to the CBFv responses. CBFv step responses for the BP, CO2, and stimulus inputs were also obtained. The contribution of the stimulus to the CBFv response was highly significant for the difference between the affected side [area under the curve (AUC) 104.5 (4.5)%] and controls [AUC 106.9 (4.3)%; P = 0.008]. CBFv step responses to CO2 [affected hemisphere 0.39 (0.7), unaffected 0.55 (0.8), controls 1.39 (0.9)%/mmHg; P = 0.01, affected vs. controls; P = 0.025, unaffected vs. controls] and motor stimulus inputs [affected hemisphere 0.20 (0.1), unaffected 0.22 (0.2), controls 0.37 (0.2) arbitrary units; P = 0.009, affected vs. controls; P = 0.02, unaffected vs. controls] were reduced in the stroke group compared with controls. The CBFv step responses to the BP input at baseline and during the paradigm were not different between groups (P = 0.07), but PetCO2 was lower in the stroke group (P < 0.05). These results provide new insights into the interaction of CA, CVR, and NVC in both health and disease states.

A comparison of dynamic cerebral autoregulation across changes in cerebral blood flow velocity for 200 s

Objectives: The dynamic interaction between blood pressure (BP) and cerebral blood flow velocity (CBFV) is not fully understood, especially for CBFV changes lasting longer than 50 s. The interaction between BP and CBFV is relatively well characterized for periods <50 s using transfer function (TF) estimations of phase, gain, and coherence. We used TF estimations to compare the phase and gain for periods >50 s with those for periods <50 s.

Materials and Methods: BP and CBFV (of the middle cerebral artery) were simultaneously recorded in 23 healthy subjects (10 men, 13 women, mean age 35 ± 10 years) under normo- and hypocapnia (induced by hyperventilation). TF and coherence estimations were based on Welch's periodogram method with a windowing of 200 s (frequency resolution, 0.005 Hz, corresponding to a period of 200 s). Means of the phase, gain, and coherence were calculated over frequency periods of 0.005–0.02 Hz (sVLF), 0.02–0.07 Hz (VLF), 0.07–0.15 Hz (LF), and 0.15–0.40 Hz (HF) and analyzed using the t-test and Pearson correlation.

Results: Compared with the VLF range, normo- and hypocapnia phases were slightly but significantly lower in sVLF, while gain and coherence were not different. Hypocapnia induced significant (mostly p < 0.01) phase increases and gain decreases as well as coherence decreases in all frequency ranges. The phase and gain correlated significantly (−0.87 < r > −0.99) (p < 0.001) and inversely in all frequency ranges <0.15 Hz under both respiratory conditions. In some instances, the phase indicated disturbed autoregulation.

Conclusion: In the frequency range <0.15 Hz, the phase and gain correlate highly and linearly with high consistency. The phase, gain, and coherence were similar in sVLF and VLF ranges. The phase was slightly lower in the sVLF range than in the VLF range. Notably, the data suggest that autoregulatory failure may occur in healthy persons.

Autonomic dysfunction affects dynamic cerebral autoregulation during Valsalva maneuver: comparison between healthy and autonomic dysfunction subjects

The role of autonomic nervous system (ANS) in adapting cerebral blood flow (CBF) to arterial blood pressure (ABP) fluctuations [cerebral autoregulation (CA)] is still controversial. We aimed to study the repercussion of autonomic failure (AF) on dynamic CA during the Valsalva maneuver (VM). Eight AF subjects with familial amyloidotic polineuropahty (FAP) were compared with eight healthy controls. ABP and CBF velocity (CBFV) were measured continuously with Finapres and transcranial Doppler, respectively. Cerebrovascular response was evaluated by cerebrovascular resistance index (CVRi), critical closing pressure (CrCP), and resistance-area product (RAP) changes. Dynamic CA was derived from continuous estimates of autoregulatory index (ARI) [ARI(t)]. During phase II of VM, FAP subjects showed a more pronounced decrease in normalized CBFV (78 ± 19 and 111 ± 16%; P = 0.002), ABP (78 ± 19 and 124 ± 12%; P = 0.0003), and RAP (67 ± 17 and 89 ± 17%; P = 0.019) compared with controls. CrCP and CVRi increased similarly in both groups during strain. ARI(t) showed a biphasic variation in controls with initial increase followed by a decrease during phase II but in FAP this response was blunted (5.4 ± 3.0 and 2.0 ± 2.9; P = 0.033). Our data suggest that dynamic cerebral autoregulatory response is a time-varying phenomena during VM and that it is disturbed by autonomic dysfunction. This study also emphasizes the fact that RAP + CrCP model allowed additional insights into understanding of cerebral hemodynamics, showing a higher vasodilatory response expressed by RAP in AF and an equal CrCP response in both groups during the increased intracranial and intrathoracic pressure, while classical CVRi paradoxically suggests a cerebral vasoconstriction.

Model-based physiomarkers of cerebral hemodynamics in patients with mild cognitive impairment

In our previous studies, we have introduced model-based "functional biomarkers" or "physiomarkers" of cerebral hemodynamics that hold promise for improved diagnosis of early-stage Alzheimer's disease (AD). The advocated methodology utilizes subject-specific data-based dynamic nonlinear models of cerebral hemodynamics to compute indices (serving as possible diagnostic physiomarkers) that quantify the state of cerebral blood flow autoregulation to pressure-changes (CFAP) and cerebral CO2 vasomotor reactivity (CVMR) in each subject. The model is estimated from beat-to-beat measurements of mean arterial blood pressure, mean cerebral blood flow velocity and end-tidal CO2, which can be made reliably and non-invasively under resting conditions. In a previous study, it was found that a CVMR index quantifying the impairment in CO2 vasomotor reactivity correlates with clinical indications of early AD, offering the prospect of a potentially useful diagnostic tool. In this paper, we explore the use of the same model-based indices for patients with amnestic Mild Cognitive Impairment (MCI), a preclinical stage of AD, relative to a control subjects and clinical cognitive assessments. It was found that the model-based CVMR values were lower for MCI patients relative to the control subjects.

Influence of CO2 on neurovascular coupling: interaction with dynamic cerebral autoregulation and cerebrovascular reactivity

PaCO₂ affects cerebral blood flow (CBF) and its regulatory mechanisms, but the interaction between neurovascular coupling (NVC), cerebral autoregulation (CA), and cerebrovascular reactivity to CO₂ (CVR), in response to hypercapnia, is not known. Recordings of cerebral blood flow velocity (CBFv), blood pressure (BP), heart rate, and end‐tidal CO₂ (EtCO₂) were performed in 18 subjects during normocapnia and 5% CO₂ inhalation while performing a passive motor paradigm. Together with BP and EtCO₂, a gate signal to represent the effect of stimulation was used as input to a multivariate autoregressive‐moving average model to calculate their separate effects on CBFv. Hypercapnia led to a depression of dynamic CA at rest and during stimulation in both hemispheres (P <0.02) as well as impairment of the NVC response, particularly in the ipsilateral hemisphere (P <0.01). Neither hypercapnia nor the passive motor stimulation influenced CVR. Dynamic CA was not influenced by the motor paradigm during normocapnia. The CBFv step responses to each individual input (BP, EtCO₂, stimulation) allowed identification of the influences of hypercapnia and neuromotor stimulation on CA, CVR, and NVC, which have not been previously described, and also confirmed the depressing effects of hypercapnia on CA and NVC. The stability of CVR during these maneuvers and the lack of influence of stimulation on dynamic CA are novel findings which deserve further investigation. Dynamic multivariate modeling can identify the complex interplay between different CBF regulatory mechanisms and should be recommended for studies involving similar interactions, such as the effects of exercise or posture on cerebral hemodynamics.

The influence of hypercapnia on dynamic cerebral autoregulation (CA), CO₂ vasoreactivity (CVR), and neurovascular coupling (NVC) was described based on a single recording during motor stimulation coupled to a new multivariate modeling approach. Hypercapnia led to a depression of CA at rest and during stimulation in both hemispheres as well as impairment of the NVC response. Neither hypercapnia nor the passive motor stimulation influenced CVR. Dynamic CA was not influenced by the motor paradigm during normocapnia. The stability of CVR during these maneuvers and the lack of influence of stimulation on dynamic CA are novel findings which deserve further investigation.

Multivariate nonstationary modeling of cerebral hemodynamics

We extracted adaptive univariate and multivariate dynamic models of cerebral hemodynamics during resting and hypercapnic conditions using a Recursive Least Squares estimation scheme with multiple adaptive forgetting factors. The time dependent relationship between mean arterial blood pressure (MABP), end-tidal CO2 tension (PETCO2) and middle cerebral artery blood flow velocity (CBFV) was assessed using Laguerre - Volterra models with time varying coefficients. The results suggest that the addition of PETCO2 as a second input yields more accurate and less nonstationary estimates, indicating that unobservable physiological variables are important in the context of nonstationary systems modeling, and particularly for assessing cerebral hemodynamics and autoregulation.

Model-based quantification of cerebral hemodynamics as a physiomarker for Alzheimer's disease?

Previous studies have found that Alzheimer's disease (AD) impairs cerebral vascular function, even at early stages of the disease. This offers the prospect of a useful diagnostic method for AD, if cerebral vascular dysfunction can be quantified reliably within practical clinical constraints. We present a recently developed methodology that utilizes a data-based dynamic nonlinear closed-loop model of cerebral hemodynamics to compute "physiomarkers" quantifying the state of cerebral flow autoregulation to pressure-changes (CA) and cerebral CO2 vasomotor reactivity (CVMR) in each subject. This model is estimated from beat-to-beat measurements of mean arterial blood pressure, mean cerebral blood flow velocity and end-tidal CO2, which can be made reliably and non-invasively under resting conditions. This model may also take an open-loop form and comparisons are made with the closed-loop counterpart. The proposed model-based physiomarkers take the form of two indices that quantify the gain of the CA and CVMR processes in each subject. It was found in an initial set of clinical data that the CVMR index delineates AD patients from control subjects and, therefore, may prove useful in the improved diagnosis of early-stage AD.

Time-varying modeling of cerebral hemodynamics

The scientific and clinical importance of cerebral hemodynamics has generated considerable interest in their quantitative understanding via computational modeling. In particular, two aspects of cerebral hemodynamics, cerebral flow autoregulation (CFA) and CO2 vasomotor reactivity (CVR), have attracted much attention because they are implicated in many important clinical conditions and pathologies (orthostatic intolerance, syncope, hypertension, stroke, vascular dementia, mild cognitive impairment, Alzheimer's disease, and other neurodegenerative diseases with cerebrovascular components). Both CFA and CVR are dynamic physiological processes by which cerebral blood flow is regulated in response to fluctuations in cerebral perfusion pressure and blood CO2 tension. Several modeling studies to date have analyzed beat-to-beat hemodynamic data in order to advance our quantitative understanding of CFA-CVR dynamics. A confounding factor in these studies is the fact that the dynamics of the CFA-CVR processes appear to vary with time (i.e., changes in cerebrovascular characteristics) due to neural, endocrine, and metabolic effects. This paper seeks to address this issue by tracking the changes in linear time-invariant models obtained from short successive segments of data from ten healthy human subjects. The results suggest that systemic variations exist but have stationary statistics and, therefore, the use of time-invariant modeling yields "time-averaged models" of physiological and clinical utility.

Closed-loop dynamic modeling of cerebral hemodynamics

The dynamics of cerebral hemodynamics have been studied extensively because of their fundamental physiological and clinical importance. In particular, the dynamic processes of cerebral flow autoregulation (CFA) and CO2 vasomotor reactivity have attracted broad attention because of their involvement in a host of pathologies and clinical conditions (e.g., hypertension, syncope, stroke, traumatic brain injury, vascular dementia, Alzheimer's disease, mild cognitive impairment etc.). This raises the prospect of useful diagnostic methods being developed on the basis of quantitative models of cerebral hemodynamics, if cerebral vascular dysfunction can be quantified reliably from data collected within practical clinical constraints. This paper presents a modeling method that utilizes beat-to-beat measurements of mean arterial blood pressure, cerebral blood flow velocity and end-tidal CO2 (collected non-invasively under resting conditions) to quantify the dynamics of CFA and cerebral vasomotor reactivity (CVMR). The unique and novel aspect of this dynamic model is that it is nonlinear and operates in a closed-loop configuration.

Lower body negative pressure-induced vagal reaction: role for the osmopressor response?

BACKGROUND

Water ingestion elicits an osmopressor response in patients with impaired baroreflexes. In young, healthy subjects, water elicits sympathetic vasoconstriction. This study investigated the effect of water on the lower body negative pressure (LBNP)-induced vasovagal reaction and also analyzed its effect on the change of regional cerebral blood flow during LBNP.

METHODS

Twelve young healthy subjects underwent LBNP (40 mm Hg) tolerance testing for 45 minutes or until presyncopal symptoms occurred. Subjects received either LBNP or no LBNP with or without prior water ingestion. The severity of vasovagal reaction was determined by participant self-report rating of orthostatic symptoms during the LBNP test. Changes of regional cerebral blood flow (rCBF) between LBNP and water ingestion with LBNP groups were assessed using statistical parametrical mapping analyses.

RESULTS

Water ingestion attenuated the severity of symptomatic scores during LBNP (P = 0.004). Water ingestion increased Total peripheral vascular resistance (P < 0.001) and attenuated the blood pressure drop (P < 0.001) at the cessation of study. LBNP decreased rCBF over the left superior prefrontal gyrus, limbic-parahippocampal gyrus, left sublobar-caudate body, and hypothalamus (P < 0.001). Water increased rCBF significantly over the right frontal lobe, including the inferior and medial prefrontal gyrus, subcallosal, and sublobar insula, during LBNP stimulation (P < 0.001).

CONCLUSIONS

Water ingestion strongly reduces symptomatic burden of the vasovagal reaction induced by LBNP stimulation. The cortical activation of limbic and prefrontal cortex likely indicates the involvement of osmopressor response in central autonomic cardiovascular physiology. The central cortical activation of osmopressor response might provide insight into the mechanisms by which water ingestion reduces the vasovagal reaction.

Vasomotor reactivity as a predictor for syncope in patients with orthostatism

OBJECTIVES

Syncope in patients with orthostatic hypotension (OH) may be the result of impaired cerebral autoregulation. Cerebral autoregulation status can be determined by assessing cerebral vasomotor reactivity (VMR). We assessed and compared VMR in patients with OH with and without syncope.

MATERIAL AND METHODS

Twenty-nine patients with OH underwent transcranial Doppler (TCD) and the Diamox test (1 g acetazolamide IV) for assessing VMR during elaboration of their OH syndrome. The percent difference between cerebral blood flow velocities (BFV) in the middle cerebral (MCA) and vertebral (VA) arteries before and after acetazolamide was defined as VMR%. We considered increases of BFV of ≥ 40% as being indicative of good VMR and classified our study patients as having good or impaired VMRs accordingly.

RESULTS

Mean VMR% values of the MCA and VA in patients with OH with syncope (n = 12) were significantly lower as compared with patients with OH without syncope (n = 17): 25.2 ± 20.5% and 42.5 ± 18.6%; 20.9 ± 15.5% and 40.8 ± 28.5%, respectively (P < 0.05).

CONCLUSIONS

Among patients with OH, we found an association between the presence of syncope and impaired VMR. Assessment of VMR among patients with OH may predict those who are at higher risk to faint and fall and to support more aggressive intervention.

Multichannel near infrared spectroscopy indicates regional variations in cerebral autoregulation in infants supported on extracorporeal membrane oxygenation

Assessing noninvasively cerebral autoregulation, the protective mechanism of the brain to maintain constant cerebral blood flow despite changes in blood pressure, is challenging. Infants on life support system (ECMO) for cardiorespiratory failure are at risk of cerebral autoregulation impairment and consequent neurological problems. We measured oxyhaemoglobin concentration (HbO(2)) by multichannel (12 channels) near-infrared spectroscopy (NIRS) in six infants during sequential changes in ECMO flow. Wavelet cross-correlation (WCC) between mean arterial pressure (MAP) and HbO(2) was used to construct a time-frequency representation of the concordance between the two signals to assess the nonstationary aspect of cerebral autoregulation and investigate regional variations. Group data showed that WCC increases with decreasing ECMO flow indicating higher concordance between MAP and HbO(2) and demonstrating loss of cerebral autoregulation at low ECMO flows. Statistically significant differences in WCC were observed between channels placed on the right and left scalp with channels on the right exhibiting higher values of WCC suggesting that the right hemisphere was more susceptible to disruption of cerebral autoregulation. Multichannel NIRS in conjunction with wavelet analysis methods can be used to assess regional variations in dynamic cerebral autoregulation with important clinical application in the management of critically ill children on life support systems.

Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes

Cerebral Flow Autoregulation (CFA) is the dynamic process by which cerebral blood flow is maintained within physiologically acceptable bounds during fluctuations of cerebral perfusion pressure. The distinction is made with “static” flow autoregulation under steady-state conditions of perfusion pressure, described by the celebrated “autoregulatory curve” with a homeostatic plateau. This paper studies the dynamic CFA during changes in perfusion pressure, which attains critical clinical importance in patients with stroke, traumatic brain injury and neurodegenerative disease with a cerebrovascular component. Mathematical and computational models have been used to advance our quantitative understanding of dynamic CFA and to elucidate the underlying physiological mechanisms by analyzing the relation between beat-to-beat data of mean arterial blood pressure (viewed as input) and mean cerebral blood flow velocity(viewed as output) of a putative CFA system. Although previous studies have shown that the dynamic CFA process is nonlinear, most modeling studies to date have been linear. It has also been shown that blood CO2 tension affects the CFA process. This paper presents a nonlinear modeling methodology that includes the dynamic effects of CO2 tension (or its surrogate, end-tidal CO2) as a second input and quantifies CFA from short data-records of healthy human subjects by use of the modeling concept of Principal Dynamic Modes (PDMs). The PDMs improve the robustness of the obtained nonlinear models and facilitate their physiological interpretation. The results demonstrate the importance of including the CO2 input in the dynamic CFA study and the utility of nonlinear models under hypercapnic or hypocapnic conditions.

Linear and nonlinear modeling of cerebral flow autoregulation using principal dynamic modes

Cerebral Flow Autoregulation (CFA) is the dynamic process by which cerebral blood flow is maintained within physiologically acceptable bounds during fluctuations of cerebral perfusion pressure. The distinction is made with “static” flow autoregulation under steady-state conditions of perfusion pressure, described by the celebrated “autoregulatory curve” with a homeostatic plateau. This paper studies the dynamic CFA during changes in perfusion pressure, which attains critical clinical importance in patients with stroke, traumatic brain injury and neurodegenerative disease with a cerebrovascular component. Mathematical and computational models have been used to advance our quantitative understanding of dynamic CFA and to elucidate the underlying physiological mechanisms by analyzing the relation between beat-to-beat data of mean arterial blood pressure (viewed as input) and mean cerebral blood flow velocity(viewed as output) of a putative CFA system. Although previous studies have shown that the dynamic CFA process is nonlinear, most modeling studies to date have been linear. It has also been shown that blood CO2 tension affects the CFA process. This paper presents a nonlinear modeling methodology that includes the dynamic effects of CO2 tension (or its surrogate, end-tidal CO2) as a second input and quantifies CFA from short data-records of healthy human subjects by use of the modeling concept of Principal Dynamic Modes (PDMs). The PDMs improve the robustness of the obtained nonlinear models and facilitate their physiological interpretation. The results demonstrate the importance of including the CO2 input in the dynamic CFA study and the utility of nonlinear models under hypercapnic or hypocapnic conditions.

Random perturbations of arterial blood pressure for the assessment of dynamic cerebral autoregulation

The assessment of cerebral autoregulation (CA) relies mostly on methods that modulate arterial blood pressure (ABP). Despite advances, the gold standard of assessment remains elusive and clinical practicality is limited. We investigate a novel approach of assessing CA, consisting of the intermittent application of thigh cuffs using square wave sequences. Our aim was to increase ABP variability whilst minimizing volunteer discomfort, thus improving assessment acceptability. Two random square wave sequences and two maximum pressure settings (80 and 150 mmHg) were used, corresponding to four manoeuvres that were conducted in random order after a baseline recording. The intermittent application of thigh cuffs resulted in an amplitude dependent increase in ABP (p = 0.001) and cerebral blood flow velocity (CBFV) variability (p = 0.026) compared to baseline. No statistically significant differences in mean heart rate or heart rate variability were observed (p = 0.108 and p = 0.350, respectively), suggesting that no significant sympathetic response was elicited. No significant differences in the CBFV step response were observed, suggesting no distortion of autoregulatory parameters resulted from the use of thigh cuffs. We conclude that pseudorandom binary sequences are an effective and safe alternative for increasing ABP variability. This new approach shows great promise as a tool for the robust assessment of CA.

Nonlinear, multiple-input modeling of cerebral autoregulation using Volterra Kernel estimation

Autoregulation refers to the automatic adjustment of blood flow to supply the required oxygen and glucose and remove waste, in proportion to the tissue's requirement at any instant of time. For the brain, cerebral autoregulation is an active process by which cerebral blood flow is controlled at an approximately steady level despite changes in the arterial blood pressure. Robust assessment of the cerebral autoregulation by a model that characterizes this system has been the goal of many studies, searching for techniques that can be used in clinical scenarios to detect potentially dangerous impairment of control. Multiple input, single output (MISO) models can be used to assess autoregulation, and system parameters can be estimated from spontaneous beat-to-beat variations in arterial blood pressure (ABP) and breath-by-breath end-tidal carbon dioxide (P(ETCO2)) as inputs, and cerebral blood flow velocity (CBFV) as the output. In this study a non-linear, multivariate approach, based on Volterra-type kernel estimation models is employed. The results are compared with linear models as well as nonlinear single-input single-output (SISO) models. The normalized mean squared error was used as the criteria of performance of each model in assessing cerebral autoregulation. Our simulation results indicate that for relatively short signals (around 300 sec), nonlinear, multiple-input models based on Volterra systems performed best, though the benefit varied considerably between subjects. When using a fixed model for all recordings, a linear SISO model with ABP as input provided the smallest average modeling error.

A systematic study of linear dynamic modeling of intracranial pressure dynamics

Our group has proposed a generic time series data mining framework and demonstrated its potential as a noninvasive intracranial pressure (ICP) assessment approach. The linear dynamic model (LDM) was used in our previous work without rigorous justification. In the current study, we performed a systematic study of the practical performance of the LDM for ICP dynamics by investigating three important aspects to consider in using the LDM to model ICP dynamics. Those three aspects include the fitness of the LDM to data, the generalizability of the models, and the choice of input signals to the models. Our study results show that the fitness of the LDM to data is excellent and the LDM for ICP dynamics is well generalizable, which is of particular interest to adopting our time series data mining framework for noninvasive ICP assessment.

Diagnostic biomarkers for Alzheimer's disease using dynamic nonlinear models based on Principal Dynamic Modes

Sensitive and robust diagnostic biomarkers for Alzheimer's disease (AD) were sought using dynamic nonlinear models of the causal interrelationships among time-series (beat-to-beat) data of arterial blood pressure, end-tidal CO(2) and cerebral blood flow velocity collected in human subjects (4 AD patients and 4 control subjects). These models were based on Principal Dynamic Modes (PDM) and yielded a reliable biomarker for AD diagnosis in the form of the "Effective CO(2) Reactivity Index" (ECRI). The results from this initial set of subjects corroborated the efficacy of the ECRI biomarker for accurate AD diagnosis.

The psychophysiology of blood-injection-injury phobia: looking beyond the diphasic response paradigm

Blood-injection-injury (BII) phobia is an anxiety disorder that may be accompanied by vasovagal fainting during confrontation with the feared stimuli. The underlying pattern of autonomic regulation has been characterized as a diphasic response, with initial increases in heart rate and blood pressure that are typical of a fight-flight response, and subsequent drops in blood pressure and/or heart rate that may precipitate vasovagal fainting. Tensing skeletal muscles of the arms, legs, and trunk (applied tension) has been proposed as a technique to cope with this dysregulation. This review critically examines the empirical basis for the diphasic response and its treatment by applied tension in BII phobia. An alternative perspective on the psychophysiology of BII phobia and vasovagal fainting is offered by focusing on hypocapnia that leads to cerebral blood flow reductions, a perspective supported by research on neurocardiogenic and orthostatically-induced syncope. The evidence may indicate a role for respiration-focused coping techniques in BII phobia.

Autonomic neural control of cerebral hemodynamics

Despite the rich innervation of the cerebral vasculature by both sympathetic and parasympathetic nerves, the role of autonomic control in cerebral circulation and, particularly, cerebral hemodynamics is not entirely clear. Previous animal studies have reported inconsistent results regarding the effects of electrical stimulation or denervation on cerebral blood flow (CBF), cerebral pressure-flow relationship, and cerebral vessel response to metabolic stimuli. Moreover, with the advance of transcranial Doppler ultrasound (TCD), which yields accurate measurements of CBF velocity (CBFV) with high time resolution, it has been found that in humans CBFV in the middle cerebral artery decreased substantially during lower body negative pressure (LBNP) and head-up tilt in the absence of systemic hypotension, which suggests the presence of cerebral vasoconstriction associated with augmented sympathetic nerve activity during orthostatic stress. These observations were based on assessing static measures of cerebral circulation, i.e., mean values of artevial blood pressure (ABP) and CBF with a low time resolution.

Continuous estimates of dynamic cerebral autoregulation during transient hypocapnia and hypercapnia

Dynamic cerebral autoregulation (CA) is the transient response of cerebral blood flow (CBF) to rapid blood pressure changes: it improves in hypocapnia and becomes impaired during hypercapnia. Batch-processing techniques have mostly been used to measure CA, providing a single estimate for an entire recording. A new approach to increase the temporal resolution of dynamic CA parameters was applied to transient hypercapnia and hypocapnia to describe the time-varying properties of dynamic CA during these conditions. Thirty healthy subjects (mean +/- SD: 25 +/- 6 yr, 9 men) were recruited. CBF velocity was recorded in both middle cerebral arteries (MCAs) with transcranial Doppler ultrasound. Arterial blood pressure (Finapres), end-tidal CO(2) (ET(CO(2)); infrared capnograph), and a three-lead ECG were also measured at rest and during repeated breath hold and hyperventilation. A moving window autoregressive moving average model provided continuous values of the dynamic CA index [autoregulation index (ARI)] and unconstrained gain. Breath hold led to significant increase in ET(CO(2)) (+5.4 +/- 6.1 mmHg), with concomitant increase in CBF velocity in both MCAs. Continuous dynamic CA parameters showed highly significant changes (P < 0.001), with a temporal pattern reflecting a delayed dynamic response of CA to changes in arterial Pco(2) and a maximal reduction in ARI of -5.1 +/- 2.4 and -5.1 +/- 2.3 for the right and left MCA, respectively. Hyperventilation led to a marked decrease in ET(CO(2)) (-7.2 +/- 4.1 mmHg, P < 0.001). Unexpectedly, CA efficiency dropped significantly with the inception of the metronome-controlled hyperventilation, but, after approximately 30 s, the ARI increased gradually to show a maximum change of 5.7 +/- 2.9 and 5.3 +/- 3.0 for the right and left MCA, respectively (P < 0.001). These results confirm the potential of continuous estimates of dynamic CA to improve our understanding of human cerebrovascular physiology and represent a promising new approach to improve the sensitivity of clinical applications of dynamic CA modeling.

Nonlinear, data-driven modeling of cardiorespiratory control mechanisms

We present applications of recently developed algorithms for data-driven nonlinear systems identification to the study of cardiovascular and respiratory control mechanisms on an integrated systems level, utilizing experimental data obtained during resting conditions. Specifically, we consider cerebrovascular regulation during normal conditions, orthostatic stress and autonomic blockade in a two-input context, as well as respiratory control during a model opioid drug (remifentanil) infusion in a closed-loop context. The results illustrate the potential of using data-driven modeling approaches, which do not rely on prior assumptions about model structure, for modeling physiological systems, as they are well-suited to their complexity. They also illustrate the potential of utilizing spontaneous physiological variability, which can be monitored noninvasively and does not require experimental interventions, to extract rich information about the function of the underlying mechanisms. We also discuss some important practical issues, such as the presence of nonstationarities and model order selection, related to the application of similar approaches to the analysis of physiological systems.

Decreased upright cerebral blood flow and cerebral autoregulation in normocapnic postural tachycardia syndrome

Postural tachycardia syndrome (POTS), a chronic form of orthostatic intolerance, has signs and symptoms of lightheadedness, loss of vision, headache, fatigue, and neurocognitive deficits consistent with reductions in cerebrovascular perfusion. We hypothesized that young, normocapnic POTS patients exhibit abnormal cerebral autoregulation (CA) that results in decreased static and dynamic cerebral blood flow (CBF) autoregulation. All subjects had continuous recordings of mean arterial pressure (MAP) and CBF velocity (CBFV) using transcranial Doppler sonography in both the supine supine position and during a 70 degrees head-up tilt. During tilt, POTS patients (n = 9) demonstrated a higher heart rate than controls (n = 7) (109 +/- 6 vs. 80 +/- 2 beats/min, P < 0.05), whereas controls demonstrated a higher MAP than POTS (87 +/- 2 vs. 77 +/- 3 mmHg, P < 0.05). Also during tilt, mean CBFV decreased 19.5 +/- 2.6% in POTS patients versus 10.3 +/- 2.0% in controls (P < 0.05). We then used a transfer function analysis of MAP and CFBV in the frequency domain to quantify these changes. The low-frequency (LF; 0.04-0.15 Hz) component of CBFV variability increased during tilt in POTS patients (supine: 3 +/- 0.9 vs. tilt: 9 +/- 2, P < 0.02). In POTS patients, there was an increase in LF and high-frequency coherence between MAP and CBFV, an increase in LF gain, and a lack of significant change in phase. Static CA may be less effective in POTS patients compared with controls, since immediately after tilt CBFV decreased more in POTS patients and was highly oscillatory and autoregulation did not restore CBFV to baseline values until the subjects became supine. Dynamic CA may be less effective in POTS patients because MAP and CBFV during tilt became almost perfectly synchronous. We conclude that dynamic and static autoregulation of CBF are less effective in POTS patients compared with control subjects during orthostatic challenge.

Transcranial Doppler for evaluation of cerebral autoregulation

Transcranial Doppler ultrasound (TCD) can measure cerebral blood flow velocity in the main intracranial vessels non-invasively and with high accuracy. Combined with the availability of non-invasive devices for continuous measurement of arterial blood pressure, the relatively low cost, ease-of-use, and excellent temporal resolution of TCD have stimulated the development of new techniques to assess cerebral autoregulation in the laboratory or bedside using a dynamic approach, instead of the more classical 'static' method. Clinical applications have shown consistent results in certain conditions such as severe head injury and carotid artery disease. Studies in syncopal patients revealed a more complex pattern due to aetiological non-homogeneity and methodological limitations mainly due to inadequate sample-size. Different analytical models to quantify autoregulatory performance have also contributed to the diversity of results in the literature. The review concludes with specific recommendations for areas where further validation and research are needed to improve the reliability and usefulness of TCD in clinical practice.