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Apsvalka, D.

Publications and source records attributed to Apsvalka, D..

3 recordsLinked to original sources

Longitudinal versus Cross-sectional effects of Age on MEG Power Spectra Parameters: Implications for Normative Models and Brain Ageing

Ageing produces changes in brain function. To map this process, researchers increasingly utilise Magnetoencephalography (MEG) to identify spectral shifts across large, age-diverse cohorts. However most such research has used cross-sectional designs, which may be confounded by generational differences and high inter-individual variability. To address these limitations, we analysed longitudinal resting-state MEG data from the Cam-CAN cohort, an adult lifespan cohort with a repeat MEG recording after approximately a decade. This design allowed us to contrast cross-sectional age differences between people (at baseline) with longitudinal age changes within people. Our analyses revealed four key findings. First, we observed consistency between baseline and longitudinal effects of increasing age on the slowing of the Alpha peak frequency. Second, we identified non-linear changes in Beta power, whereby power increased from youth to mid-life, but decreased from mid-life to late-life. These findings validate the use of normative charts for mapping these spectral components. Third, we detected some longitudinal effects, such as power reductions in Alpha and slowing of Beta peak frequency, that were not apparent cross-sectionally, underscoring the importance of intra-individual designs. Fourth, we did not find the commonly reported age-related flattening of the aperiodic exponent of the power spectrum, except in direct measures of cardiac activity. Together, these results demonstrate that while cross-sectional data capture major trends, longitudinal data are essential for isolating the true neurophysiological signatures of the ageing process.

neuroscience↗

Dissociable contributions of cortical thickness and surface area to cognitive ageing: evidence from multiple longitudinal cohorts.

Cortical volume, a widely-used marker of brain ageing, is the product of two genetically and developmentally dissociable morphometric features: thickness and area. However, it remains unclear whether these two features have dissociable consequences for cognitive ageing. To address this, we analyse cross-sectional and longitudinal neuroimaging and cognitive data from one discovery cohort (Cam-CAN) and two independent, pre-registered replication cohorts (OASIS-3 and HABS-HD), leveraging wide age ranges across adulthood, different follow-up intervals and diverse population backgrounds. We show that thickness declines more steeply with age than does area, and shows stronger associations with longitudinal change in fluid cognitive abilities, fairly uniformly across the cortex. Cognitive change is also dependent on baseline thickness, independent of thickness change and independent of baseline cognitive ability. In contrast, area is comparatively stable across adulthood, at least until old age, and shows weaker and more heterogeneous associations with cognitive change. Together, these findings help to reconcile inconsistencies in the literature, and indicate that thickness provides a more sensitive marker of dynamic neurobiological processes underlying cognitive ageing, whereas area seems to reflect primarily stable, trait-like variation in cognitive ability.

neuroscience↗

Dynamic targeting enables domain-general inhibitory control over action and thought by the prefrontal cortex.

Successful self-control requires the ability to stop unwanted actions or thoughts. Stopping is regarded as a central function of inhibitory control, a mechanism enabling the suppression of diverse mental content, and strongly associated with the prefrontal cortex. A domain-general inhibitory control capacity, however, would require the region or regions implementing it to dynamically shift top-down inhibitory connectivity to diverse target regions in the brain. Here we show that stopping unwanted thoughts and stopping unwanted actions engage common regions in the right anterior dorsolateral and right ventrolateral prefrontal cortex, and that both areas exhibit this dynamic targeting capacity. Within each region, pattern classifiers trained to distinguish stopping actions from making actions also could identify when people were suppressing their thoughts (and vice versa) and could predict which people successfully forgot thoughts after inhibition. Effective connectivity analysis revealed that both regions contributed to action and thought stopping, by dynamically shifting inhibitory connectivity to motor area M1 or to the hippocampus, depending on the goal, suppressing task-specific activity in those regions. These findings support the existence of a domain-general inhibitory control mechanism that contributes to self-control and establish dynamic inhibitory targeting as a key mechanism enabling these abilities.

neuroscience↗