Assessment of dynamic cerebral autoregulation in near-infrared spectroscopy using short channels: A feasibility study in acute ischemic stroke patients

Introduction

In acute ischemic stroke, progressive impairment of cerebral autoregulation (CA) is frequent and associated with unfavorable outcomes. Easy assessment of cerebral blood flow and CA in stroke units bedside tools like near-infrared spectroscopy (NIRS) might improve early detection of CA deterioration. This study aimed to assess dynamic CA with multichannel CW-NIRS in acute ischemic stroke (AIS) patients compared to agematched healthy controls.

Methods

CA reaction was amplified by changes in head of bed position. Long- and short channels were used to monitor systemic artery pressure- and intracranial oscillations simultaneously. Gain and phase shift in spontaneous low- and very low-frequency oscillations (LFO, VLFO) of blood pressure were assessed.

Results

A total of 54 participants, 27 with AIS and 27 age-matched controls were included. Gain was significantly lower in the AIS group in the LFO range (i) when the upper body was steadily elevated to 30. and (ii) after its abrupt elevation to 30°. No other differences were found between groups.

Discussion

This study demonstrates the feasibility of NIRS short channels to measure CA in AIS patients in one single instrument. A lower gain in AIS might indicate decreased CA activity in this pilot study, but further studies investigating the role of NIRS short channels in AIS are needed.

Data Processing in Functional Near-Infrared Spectroscopy (fNIRS) Motor Control Research

FNIRS pre-processing and processing methodologies are very important-how a researcher chooses to process their data can change the outcome of an experiment. The purpose of this review is to provide a guide on fNIRS pre-processing and processing techniques pertinent to the field of human motor control research. One hundred and twenty-three articles were selected from the motor control field and were examined on the basis of their fNIRS pre-processing and processing methodologies. Information was gathered about the most frequently used techniques in the field, which included frequency cutoff filters, wavelet filters, smoothing filters, and the general linear model (GLM). We discuss the methodologies of and considerations for these frequently used techniques, as well as those for some alternative techniques. Additionally, general considerations for processing are discussed.

Characteristic of Mayer Waves in Electrophysiological, Hemodynamic and Vascular Signals

We evaluated the properties of oscillations in the Mayer waves (MW) frequency range (∼0.1Hz) detected in blood pressure, heart rate variability, cerebral blood oxygenation changes and evolution of electroencephalographic (EEG) rhythms to elucidate the mechanisms of MW generation. We examined the persistence of MW in different signals and stability of their oscillations on the level of individual MW waveforms, which was achieved by applying matching pursuit (MP). MP yields adaptive time-frequency approximation of signal's structures in terms of frequency, amplitude, time occurrence, and time-span. The number of waveforms contributing to 95% of the energy of the signals was vastly different for the time series, but the average number of waveforms conforming to the MW criteria was almost the same (3.5 ± 0.4 per 120s epoch). In all the investigated signals, MW had the same distributions of frequency and the number of cycles. We show that the MW energy ratios in different signals varied strongly, p < 0.001. The highest percentage of MW energy was observed in blood pressure signals, heart rate variability, and reduced hemoglobin, in contrast to brain signals and oxygenated hemoglobin. The percentage of MW energy was related to the strength of causal influence exerted by them on the other signals. Our results indicate existence of a common mechanism of MW generation and support the hypothesis of MW generation in the baroreflex loop; however, they do not exclude the action of a central pacemaker.

Causal Coupling Between Electrophysiological Signals, Cerebral Hemodynamics and Systemic Blood Supply Oscillations in Mayer Wave Frequency Range

The aim of the study was to assess causal coupling between neuronal activity, microvascular hemodynamics and blood supply oscillations in the Mayer wave frequency range. An electroencephalogram, cerebral blood oxygenation changes, an electrocardiogram and blood pressure were recorded during rest and during a movement task. Causal coupling between them was evaluated using directed transfer function, a measure based on the Granger causality principle. The multivariate autoregressive model was fitted to all the signals simultaneously, which made it possible to construct a complete scheme of interactions between the considered signals. The obtained pattern of interactions in the resting state estimated in the 0.05-0.15 Hz band revealed a predominant influence of blood pressure oscillations on all the other variables. Reciprocal connections between blood pressure and heart rate variability time series indicated the presence of feedback loops between these signals. During movement, the pattern of connections did not change dramatically. The number of connections decreased, but the couplings between blood pressure and heart rate variability signal were not significantly changed, and the strong influence of the decreased blood hemoglobin concentration on the oxygenated hemoglobin concentration persisted. For the first time our results provided a comprehensive scheme of interactions between electrical and hemodynamic brain signals, heart rate and blood pressure oscillations. Persistent reciprocal connections between blood pressure and heart rate variability time series suggest possible feedforward and feedback coupling of cardiovascular variables which may lead to the observed oscillations in Mayer wave range.

Assessing low-frequency oscillations in cerebrovascular diseases and related conditions with near-infrared spectroscopy: a plausible method for evaluating cerebral autoregulation?

BACKGROUND

Cerebral autoregulation (CA) is the brain's ability to always maintain an adequate and relatively constant blood supply, which is often impaired in cerebrovascular diseases. Near-infrared spectroscopy (NIRS) examines oxygenated hemoglobin (OxyHb) in the cerebral cortex. Low- and very low-frequency oscillations ( LFOs ≈ 0.1    Hz and VLFOs ≈ 0.05 to 0.01 Hz) in OxyHb have been proposed to reflect CA.

AIM

To systematically review published results on OxyHb LFOs and VLFOs in cerebrovascular diseases and related conditions measured with NIRS.

APPROACH

A systematic search was performed in the MEDLINE database, which generated 36 studies relevant for inclusion.

RESULTS

Healthy people have relatively stable LFOs. LFO amplitude seems to reflect myogenic CA being decreased by vasomotor paralysis in stroke, by smooth muscle damage or as compensatory action in other conditions but can also be influenced by the sympathetic tone. VLFO amplitude is believed to reflect neurogenic and metabolic CA and is lower in stroke, atherosclerosis, and with aging. Both LFO and VLFO synchronizations appear disturbed in stroke, while the former is also altered in internal carotid stenosis and hypertension.

CONCLUSION

We conclude that amplitudes of LFOs and VLFOs are relatively robust measures for evaluating mechanisms of CA and synchronization analyses can show temporal disruption of CA. Further research and more coherent methodologies are needed.

Synchronization of intrinsic 0.1-Hz blood-oxygen-level-dependent oscillations in amygdala and prefrontal cortex in subjects with increased state anxiety

Low-frequency oscillations with a dominant frequency at 0.1 Hz are one of the most influential intrinsic blood-oxygen-level-dependent (BOLD) signals. This raises the question if vascular BOLD oscillations (originating from blood flow in the brain) and intrinsic slow neural activity fluctuations (neural BOLD oscillations) can be differentiated. In this study, we report on two different approaches: first, on computing the phase-locking value in the frequency band 0.07-0.13 Hz between heart beat-to-beat interval (RRI) and BOLD oscillations and second, between multiple BOLD oscillations (functional connectivity) in four resting states in 23 scanner-naïve, anxious healthy subjects. The first method revealed that vascular 0.1-Hz BOLD oscillations preceded those in RRI signals by 1.7 ± 0.6 s and neural BOLD oscillations lagged RRI oscillations by 0.8 ± 0.5 s. Together, vascular BOLD oscillations preceded neural BOLD oscillations by ~90° or ~2.5 s. To verify this discrimination, connectivity patterns of neural and vascular 0.1-Hz BOLD oscillations were compared in 26 regions involved in processing of emotions. Neural BOLD oscillations revealed significant phase-coupling between amygdala and medial frontal cortex, while vascular BOLD oscillations showed highly significant phase-coupling between amygdala and multiple regions in the supply areas of the anterior and medial cerebral arteries. This suggests that not only slow neural and vascular BOLD oscillations can be dissociated but also that two strategies may exist to optimize regulation of anxiety, that is increased functional connectivity between amygdala and medial frontal cortex, and increased cerebral blood flow in amygdala and related structures.

Brain-heart communication: Evidence for "central pacemaker" oscillations with a dominant frequency at 0.1Hz in the cingulum

OBJECTIVES

In the brain and heart, oscillations at about 0.1Hz are conspicuous. It is therefore worthwhile to study the interaction between intrinsic BOLD oscillations (0.1Hz) and slow oscillations in heart rate interval (RRI) signals and differentiate between their neural and vascular origin.

METHODS

We studied the phase-coupling with a 3T scanner with high scanning rate between BOLD signals in 22 regions and simultaneously recorded RRI oscillations in 23 individuals in two resting states.

RESULTS

By applying a hierarchical cluster analysis, it was possible to separate two clusters of phase-coupling between slow BOLD and RRI oscillations in the midcingulum, one representative for neural and the other for vascular BOLD oscillations. About half of the participants revealed positive time delays characteristic for neural BOLD oscillations and neurally-driven RRI oscillations.

CONCLUSIONS

The results suggest that slow vascular and neural BOLD oscillations can be differentiated and that intrinsic oscillations (0.1Hz) originate in the cingulum or its close vicinity and contribute to heart rate variability (HRV).

SIGNIFICANCE

The study provides new insights into the dynamics of resting state activities, helps to explain HRV, and offers the possibility to investigate slow rhythmic neural activity changes in different brain regions without EEG recording.

Separating heart and brain: on the reduction of physiological noise from multichannel functional near-infrared spectroscopy (fNIRS) signals

OBJECTIVE

Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain-computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)).

APPROACH

We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses.

MAIN RESULTS

All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found.

SIGNIFICANCE

The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.

Entrainment of spontaneous cerebral hemodynamic oscillations to behavioral responses

Entrainment in physiological systems can be manifest in cases where phase-coupling (synchronization) between slow intrinsic oscillations and periodic motor responses, or vice versa, takes place. To test whether voluntary movement has something in common with entrainment of slow hemodynamic oscillations to motor responses, we studied blood pressure (BP), heart rate beat-to-beat intervals (RRI) and prefrontal (de)oxyhemoglobin (Hb/HbO2) during 5min of rest, 10min of self-paced, voluntary movements and 10min of stimulus-paced movements at 10s intervals in 9 subjects. Subjects were divided into 2 groups according to the timing of voluntary finger movements. It appeared that these movements occurred at relatively regular intervals of approximately 10s in 5 subjects (group A); while 4 subjects showed random or very short inter-movement intervals (group B). Two remarkable results were obtained: first, the phase coupling (COH(2)) between BP and RRI showed a significant (p=0.0061) interaction between activity (rest vs. movement) and group (A vs. B), with an increased (p=0.0003) coupling in group A. Second, the COH(2) between BP and Hb oscillations showed a significant (p=0.034) interaction between activity and group, with a decreased (p=0.079) coupling in group B. These results suggest that subjects able to initiate self-paced, voluntary movements at relatively regular intervals of ∼10s show an entrainment potential between physiological oscillations and motor responses. This also provides the first evidence that not only physiological oscillations can be entrained to motor responses, but also motor responses (voluntary movements) can be entrained to slow intrinsic oscillations.

Coupling between intrinsic prefrontal HbO2 and central EEG beta power oscillations in the resting brain

There is increasing interest in the intrinsic activity in the resting brain, especially that of ultraslow and slow oscillations. Using near-infrared spectroscopy (NIRS), electroencephalography (EEG), blood pressure (BP), respiration and heart rate recordings during 5 minutes of rest, combined with cross spectral and sliding cross correlation calculations, we identified a short-lasting coupling (duration [Formula: see text] s) between prefrontal oxyhemoglobin (HbO2) in the frequency band between 0.07 and 0.13 Hz and central EEG alpha and/or beta power oscillations in 8 of the 9 subjects investigated. The HbO2 peaks preceded the EEG band power peaks by 3.7 s in 6 subjects, with moderate or no coupling between BP and HbO2 oscillations. HbO2 and EEG band power oscillations were approximately in phase with BP oscillations in the 2 subjects with an extremely high coupling (squared coherence [Formula: see text]) between BP and HbO2 oscillation. No coupling was identified in one subject. These results indicate that slow precentral (de)oxyhemoglobin concentration oscillations during awake rest can be temporarily coupled with EEG fluctuations in sensorimotor areas and modulate the excitability level in the brains' motor areas, respectively. Therefore, this provides support for the idea that resting state networks fluctuate with frequencies of between 0.01 and 0.1 Hz (Mantini et.al. PNAS 2007).