Cerebral blood flow response rate to task-activation using a novel method can discriminate cognitive impairment from healthy aging

Cognitive activity significantly affects the dynamic cerebral autoregulation, but not the dynamic vasoreactivity, in healthy adults

Introduction

Neurovascular coupling (NVC) is an important mechanism for the regulation of cerebral perfusion during intensive cognitive activity. Thus, it should be examined in terms of its effects on the regulation dynamics of cerebral perfusion and its possible alterations during cognitive impairment. The dynamic dependence of continuous changes in cerebral blood velocity (CBv), which can be measured noninvasively using transcranial Doppler upon fluctuations in arterial blood pressure (ABP) and CO2 tension, using end-tidal CO2 (EtCO2) as a proxy, can be quantified via data-based dynamic modeling to yield insights into two key regulatory mechanisms: the dynamic cerebral autoregulation (dCA) and dynamic vasomotor reactivity (DVR), respectively.

Methods

Using the Laguerre Expansion Technique (LET), this study extracted such models from data in supine resting vs cognitively active conditions (during attention, fluency, and memory tasks from the Addenbrooke's Cognitive Examination III, ACE-III) to elucidate possible changes in dCA and DVR due to cognitive stimulation of NVC. Healthy volunteers (n = 39) were recruited at the University of Leicester and continuous measurements of CBv, ABP, and EtCO2 were recorded.

Results

Modeling analysis of the dynamic ABP-to-CBv and CO2-to-CBv relationships showed significant changes in dCA, but not DVR, under cognitively active conditions compared to resting state.

Discussion

Interpretation of these changes through Principal Dynamic Mode (PDM) analysis is discussed in terms of possible associations between stronger NVC stimulation during cognitive tasks and enhanced sympathetic activation.

Functional near infrared spectroscopy detects cortical activation changes concurrent with memory loss in postmenopausal women with Type II Diabetes

Older adults with Type II Diabetes Mellitus (DM) experience mild cognitive impairment, specifically in the domain of recall/working memory. No consistent causative structural cortical deficits have been identified in persons with DM (PwDM). Memory deficits may be exacerbated in older adult females, who are at the highest risk of cardiovascular decline due to DM. The focus of the current study was to evaluate functional cortical hemodynamic activity during memory tasks in postmenopausal PwDM. Functional Near Infrared Spectroscopy (fNIRS) was used to monitor oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) during memory-based tasks in a cross-sectional sample of postmenopausal women with DM. Twenty-one community-dwelling DM females (age = 65 ± 6 years) and twenty-one age- and sex-matched healthy controls (age = 66 ± 6 years) were evaluated. Working memory performance (via N-back) was evaluated while study participants donned cortical fNIRS. Health state, metabolic data, and menopausal status data were also collected. Deficits in working memory accuracy were found in the DM group as compared to controls. Differences in HbO responses emerged in the DM group. The DM group exhibited altered PFC activity magnitudes and increased functional cortical activity across ROIs compared to controls. HbO and HbR responses were not associated with worsened health state measures. These data indicate a shift in cortical activity patterns with memory deficits in postmenopausal PwDM. This DM-specific shift of HbO is a novel finding that is unlikely to be detected by fMRI. This underscores the value of using non-MRI-based neuroimaging techniques to evaluate cortical hemodynamic function to detect early mild cognitive impairment.

Neurovascular coupling on trial: How the number of trials completed impacts the accuracy and precision of temporally derived neurovascular coupling estimates

Standard practices for quantifying neurovascular coupling (NVC) with transcranial Doppler ultrasound (TCD) require participants to complete one-to-ten repetitive trials. However, limited empirical evidence exists regarding how the number of trials completed influences the validity and reliability of temporally derived NVC metrics. Secondary analyses was performed on 60 young healthy participants (30 females/30 males) who completed eight cyclical eyes-closed (20-seconds), eyes-open (40-seconds) NVC trials, using the "Where's Waldo?" visual paradigm. TCD data was obtained in posterior and middle cerebral arteries (PCA and MCA, respectively). The within-day (n = 11) and between-day (n = 17) reliability were assessed at seven- and three-time points, respectively. Repeat testing from the reliability aims were also used for the concurrent validity analysis (n = 160). PCA metrics (i.e., baseline, peak, percent increase, and area-under-the-curve) demonstrated five trials produced excellent intraclass correlation coefficient (ICC) 95% confidence intervals for validity and within-day reliability (>0.900), whereas between-day reliability was good-to-excellent (>0.750). Likewise, 95% confidence intervals for coefficient of variation (CoV) measures ranged from acceptable (<20%) to excellent (<5%) with five-or-more trials. Employing fewer than five trials produced poor/unacceptable ICC and CoV metrics. Future NVC, TCD-based research should therefore have participants complete a minimum of five trials when quantifying the NVC response with TCD via a "Where's Waldo?" paradigm.

Principal component analysis to identify the major contributors to task-activated neurovascular responses

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A range of metrics are available to measure to cerebrovascular responses to task activation.

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We used principal component analysis to reduce dimensionality in a large dataset and determine physiological variables with the greatest contribution to the cerebrovascular response.

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Peak percentage change in cerebrovascular response was a consistent marker across datasets and the visuospatial task contributed the most variance.

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There was limited overlap between cognitive tasks and domains suggesting lack of redundancy in the data.

Background

Consensus on the optimal metrics for neurovascular coupling (NVC) is lacking. The aim of this study was to use principal component analysis (PCA) to determine the most significant contributors to NVC responses in healthy adults (HC), Alzheimer's disease (AD), and mild cognitive impairment (MCI).

New method

PCA was applied to three datasets: 1) 69 HC, 2) 30 older HC, 34 AD, and 22 MCI, 3) 1&2 combined. Data were extracted on peak percentage change in cerebral blood flow velocity (CBFv), variance ratio (VR), cross-correlation function peak (CCF), and blood pressure, for five cognitive tasks. An equamax rotation was applied and factors were significant where the eignevalue was ≥1. Rotated factor loadings ≥0.4 determined significant NVC variables.

Results

PCA identified 12 significant factors accounting for 78% of variance (all datasets). Contributing variables loaded differently on the factors across the datasets. In datasets 1&2, peak percentage change in CBFv contributed to factors explaining the most variance (45–58%), whereas cognitive test scores, fluency and memory domains contributed the least (15–37%). In the combined dataset, CBFv, CCF and fluency domain contributed the majority (33–43%), whereas VR and attention the least (6–24%).

Conclusions

Peak percentage change in CBFv and the visuospatial task consistently accounted for a large proportion of the variance, suggesting these are robust NVC markers for future studies.