Biology subjects

Michie, P. T.

Publications and source records attributed to Michie, P. T..

4 recordsLinked to original sources

bioRxiv2025

Region-specific associations between cerebral arterial elasticity and grey matter volume: Evidence for lateral prefrontal vulnerability

BackgroundAgeing is associated with increased cardiovascular health risks and disproportionate atrophy in frontotemporal brain. Regional cerebral arterial elasticity correlates with regional grey matter volume, with stronger associations frontally and in older adults. Cardiorespiratory fitness (CRF) is linked to preserved brain structure and greater arterial elasticity, while sex differences exist in the timing of vascular versus structural changes. This study examines whether regional cerebral arterial elasticity in frontotemporal cortex mediates the association between age and corresponding grey matter volume decline, and whether sex and/or CRF moderate this relationship. MethodsWe analysed data from 162 healthy adults (60-70 years) with structural MRI and diffuse optical tomography of the cerebral arterial pulse (Pulse-DOT) from the ACTIVate cohort. CRF was estimated from demographic and physiological measures. Pulse Relaxation Function (PReFx), an optical index of regional arterial elasticity, was measured across 28 frontal, temporal, and parietal regions of interest (ROI). Grey matter (GM) volume was quantified for corresponding ROIs. Mediation and moderated mediation models tested whether PReFx mediated the relationship between age and GM volume at bilateral frontal and temporal ROIs, and whether biological sex or CRF moderated this relationship. ResultsRegional bivariate correlations identified associations between age, PReFx and GM volume across multiple ROIs, which PReFx and GM volume being associated primarily in left frontal and temporal areas. PReFx partially mediated the effect of age on GM volume in a left mid-inferior frontal ROI, accounting for approximately 16% of the total age effect and this relationship was only evident in females. Although higher CRF was associated with greater PReFx, it did not moderate the relationship between age, PReFx and GM volume. ConclusionsConsistent with cascade models of neurovascular aging, cerebral arterial stiffening was found to partially explain the effect of increasing age on frontal GM volume, even in this highly age-restricted and high functioning cohort. This effect was only significant over the left prefrontal cortex, consistent with greater vulnerability of frontal brain and associated cognitive functions. It was also exclusively present in females, who had better cardiovascular health, larger grey matter volume and greater arterial elasticity than males. These findings are consistent with pulse-DOT measures of cerebral arterial elasticity being more sensitive to subclinical brain structural variability.

neuroscience↗

bioRxiv2025

Cardiorespiratory fitness and cardiometabolic health are associated with distinct cognitive domains in cognitively healthy older adults.

BackgroundAging is associated with progressive cognitive decline, as well as increased prevalence of cardiometabolic risk factors and reduced cardiorespiratory fitness. In fact, reduced cardiometabolic health and cardiorespiratory fitness are both associated with a decline in cognitive functioning. This study examines the common and distinct contributions of these cardiovascular health factors on cognitive variability across different domains in cognitively healthy older adults. Methods and ResultsWe apply structural equation modelling (SEM) to model cross-sectional relationships between cardiometabolic health, cardiorespiratory fitness and performance across multiple cognitive domains in an age-restricted sample of healthy older adults from the ACTIVate Study (n=345; 60-70 yrs). Participants completed a series of cognitive and clinical assessments (including brachial blood pressure, heart rate, blood-based metabolic markers). We designed a cognitive model (Model 1) with four latent factors that are differentially impacted by aging (Processing Speed, Executive Function, Verbal Memory and Crystallized Ability) and used it to test effects on cognition of two theory-driven dimensions of cardiovascular health: Cardiorespiratory Fitness (Model 2) and Cardiometabolic Health (Model 3). Model 4 included both predictors and examined their joint and distinct effects on these cognitive domains. When controlling for their joint variance, Cardiometabolic Health and Cardiorespiratory Fitness showed evidence consistent with a double dissociation on cognitive domains. Specifically, cardiorespiratory fitness significantly predicted processing speed (r=0.28, p<0.05) and executive function (r=0.66, p<0.05), but not verbal memory and crystallized ability. In contrast, cardiometabolic health predicted crystallized ability (r=0.31, p<0.05) and verbal memory (r=0.28, p<0.05), but not executive function and processing speed. ConclusionsThis study shows the first evidence that cardiorespiratory fitness and cardiometabolic health are associated with distinct cognitive domains in a large cross-sectional, age-restricted and high functioning cohort. These findings emphasize the importance of healthy aging approaches that target both health literacy and lifestyle behaviors to promote functional capacity across the lifespan.

neuroscience↗

bioRxiv2019

Reconsidering electrophysiological markers of response inhibition in light of trigger failures in the stop-signal task

We investigate the neural correlates underpinning response inhibition using a parametric ex-Gaussian model of stop-signal task performance, fit with hierarchical Bayesian methods, in a large healthy sample (N=156). The parametric model accounted for trigger failure (i.e., failures to initiate the inhibition process) and returned an SSRT estimate (SSRTEXG3) that was attenuated by {approx}65ms compared to traditional non-parametric SSRT estimates (SSRTint). The amplitude and latency of the N1 and P3 event related potential components were derived for both stop-success and stop-failure trials and compared to behavioural estimates derived from traditional (SSRTint) and parametric (SSRTEXG3, trigger failure) models. Both the fronto-central N1 and P3 peaked earlier and were larger for stop-success than stop-failure trials. For stop-failure trials only, N1 peak latency correlated with both SSRT estimates as well as trigger failure and temporally coincided with SSRTEXG3, but not SSRTint. In contrast, P3 peak and onset latency were not associated with any behavioural estimates of inhibition for either trial type. While overall the N1 peaked earlier for stop-success than stop-failure trials, this effect was not found in poor task performers (i.e., high trigger failure/slow SSRT). These findings are consistent with attentional modulation of both the speed and reliability of the inhibition process, but not for poor performers. Together with the absence of any P3 onset latency effect, our findings suggest that attentional mechanisms are important in supporting speeded and reliable inhibition processes required in the stop-signal task.

neuroscience↗

bioRxiv2017

Auditory prediction errors as individual biomarkers of schizophrenia

Schizophrenia is a complex psychiatric disorder, typically diagnosed through symptomatic evidence collected through patient interview. We aim to develop an objective biologically-based computational tool which aids diagnosis and relies on accessible imaging technologies such as electroencephalography (EEG). To achieve this, we used machine learning techniques and a combination of paradigms designed to elicit prediction errors or Mismatch Negativity (MMN) responses. MMN, an EEG component elicited by unpredictable changes in sequences of auditory stimuli, has previously been shown to be reduced in people with schizophrenia and this is arguably one of the most reproducible neurophysiological markers of schizophrenia.\n\nEEG data were acquired from 21 patients with schizophrenia and 22 healthy controls whilst they listened to three auditory oddball paradigms comprising sequences of tones which deviated in 10% of trials from regularly occurring standard tones. Deviant tones shared the same properties as standard tones, except for one physical aspect: 1) duration-the deviant stimulus was twice the duration of the standard; 2) monaural gap-deviants had a silent interval omitted from the standard, or 3) inter-aural timing difference, which caused the deviant location to be perceived as 90{degrees} away from the standards.\n\nWe used multivariate pattern analysis, a machine learning technique implemented in the Pattern Recognition for Neuroimaging Toolbox (PRoNTo) to classify images generated through statistical parametric mapping (SPM) of spatiotemporal EEG data, i.e. event-related potentials measured on the two-dimensional surface of the scalp over time. Using support vector machine (SVM) and Gaussian processes classifiers (GPC), we were able classify individual patients and controls with balanced accuracies of up to 80.48% (p-values = 0.0326, FDR corrected) and an ROC analysis yielding an AUC of 0.87. Crucially, a GPC regression revealed that MMN predicted global assessment of functioning (GAF) scores (correlation = 0.73, R2 = 0.53, p = 0.0006)

neuroscience↗