Browsing by Author "Wang, Hongye"

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    Effect of Scrabble© Expertise on Brain Ageing as Measured with Brain Signal Variability and Event-Related Potentials
    (2016) Wang, Hongye; Protzner, Andrea; Bray, Signe; Pexman, Penny
    We examined the effect of Scrabble expertise on brain ageing using brain signal variability as measured with multiscale entropy (MSE) and brain signal mean as measured with event-related potentials (ERP). We collected ERP data while age-matched Scrabble experts and controls (age range: 24 to 83) performed an expertise-related task (lexical decision task; LDT) and a non-expertise-related task (symbol decision task; SDT). During both tasks, fine-scale MSE increased with age for both groups, suggesting that short-range neural communication increases with age. Midscale MSE increased with age for experts but decreased for controls, suggesting that longer-range neural communication is maintained through older age for experts but not for controls. In addition, experts did not show the typical age-related decrease in frontal P300 amplitude. However, all age-related effects, regardless of direction, were associated with worse performance in both groups. This study provides a better understanding of how expertise affects brain ageing.
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    Understanding Brain Signal Variability and Why it Matters in Maturation from Childhood to Adulthood
    (2023-01-16) Wang, Hongye; Protzner, Andrea; Iaria, Giuseppe; Dukelow, Sean; Borowsky, Ron; Kopala-Sibley, Daniel
    Blood oxygen level dependent (BOLD) signal variability characterizes the inherently time-varying features of brain signal and has provided complementary perspectives into aging research. As a strong age predictor, age-related brain patterns that are associated with BOLD SD barely overlap with those from the mean BOLD signal. The three studies in this thesis elucidate what BOLD signal variability (quantified by standard deviation (SD) of BOLD time series) can tell us about brain structure and function relationships across the lifespan from childhood to adulthood. Study 1 explored the association between BOLD SD, age, and white matter development during early childhood. Across- and within-participant analyses demonstrated that white matter maturation was closely linked to alterations in brain function as measured by BOLD SD. Study 2 examined the relationship between age and brain function for healthy men and women using a context memory task. Although men and women performed equally well behaviorally, neurotypical aging showed different trajectories between the sexes; BOLD SD in women showed age vs performance trade-offs in widespread cortical and subcortical regions, whereas in men, BOLD SD patterns associated with age and performance were orthogonal and task-specific. To better understand how BOLD SD relates to other, more commonly used measures of brain function, Study 3 related BOLD SD to other metrics, some of them reflecting brain dynamics, e.g., BOLD signal complexity (quantified by multi-scale entropy), functional connectivity and dynamic functional connectivity. This work suggests that the relationship between BOLD SD and complexity is time scale dependent, with a positive correlation at fine scales but a negative one at coarse scale. The link between BOLD SD and dynamic functional connectivity preserved only part of the associations between BOLD SD and static functional connectivity, which revealed how brain signal and brain functional connectivity co-evolved over time. Taken together, these studies suggest that BOLD SD can be used to elucidate maturational-, aging- and sex-associated differences in brain structure and function. Relating BOLD SD to other measures of brain function may improve our understanding of how the dynamic features of brain states evolve across the lifespan.