23 research outputs found

    Amphetamine modulates brain signal variability and working memory in younger and older adults

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    Better-performing younger adults typically express greater brain signal variability relative to older, poorer performers. Mechanisms for age and performance-graded differences in brain dynamics have, however, not yet been uncovered. Given the age-related decline of the dopamine (DA) system in normal cognitive aging, DA neuromodulation is one plausible mechanism. Hence, agents that boost systemic DA [such as d-amphetamine (AMPH)] may help to restore deficient signal variability levels. Furthermore, despite the standard practice of counterbalancing drug session order (AMPH first vs. placebo first), it remains understudied how AMPH may interact with practice effects, possibly influencing whether DA up-regulation is functional. We examined the effects of AMPH on functional-MRI–based blood oxygen level-dependent (BOLD) signal variability (SDBOLD) in younger and older adults during a working memory task (letter n-back). Older adults expressed lower brain signal variability at placebo, but met or exceeded young adult SDBOLD levels in the presence of AMPH. Drug session order greatly moderated change–change relations between AMPH-driven SDBOLD and reaction time means (RTmean) and SDs (RTSD). Older adults who received AMPH in the first session tended to improve in RTmean and RTSD when SDBOLD was boosted on AMPH, whereas younger and older adults who received AMPH in the second session showed either a performance improvement when SDBOLD decreased (for RTmean) or no effect at all (for RTSD). The present findings support the hypothesis that age differences in brain signal variability reflect aging-induced changes in dopaminergic neuromodulation. The observed interactions among AMPH, age, and session order highlight the state- and practice-dependent neurochemical basis of human brain dynamics

    A novel method for the analysis of clinical biomarkers to investigate the effect of diet on health in a rat model

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    Experiments into the relationship between diet and health have been an area of high interest for a long time. In this study, we investigate the application of multivariate data analysis to differentiate between rat populations fed on two different diets: normal rat diet (control) and Western affluent diet (WAD). Two sets of data were acquired and analysed: one from a biochemical clinical analyser, taking measurements of blood-based biochemical markers; the other from the analysis of the volatile organic compounds (VOCs) emitted from faecal samples from the same animals using selected ion flow tube mass spectrometry (SIFT-MS). Five classes were considered: weanlings, 12 month controls, 12 month WADs, 18 month controls, and 18 month WADs. Data from the biochemical analyser, weanlings and 18 month WAD fed rats showed significant differences from the other measurement classes. This was shown in both the exploratory analysis and through multivariate classification. Classification of control diet versus WAD diets suggested there are differences between classes with 92% accuracy for the 12 month classes and 91% for the 18 month classes. Cholesterol markers, especially as low density lipoprotein-cholesterol (LDL), were the main factor in influencing WAD samples. The data from the SIFT-MS analysis also produced very good classification accuracies. Classification of control diet versus WAD diets using the H3O+ precursor ion data suggested there are differences between classes with 71% accuracy for the 12 month classes and 100% for the 18 month classes. These findings confirm that total cholesterol and LDL-cholesterol are elevated in the 18 month WAD-fed rats. We therefore suggest that the analysis of VOCs from faecal samples in conjunction with multivariate data analysis may be a useful alternative to blood analysis for the detection of parameters of health
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