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Abstract The blue loop stage of intermediate mass stars has been called a “magnifying glass”, where even seemingly small effects in prior stages of evolution, as well as assumptions about stellar composition, rotation, and convection, produce discernible changes. As such, blue loops, and especially the existence and properties of Cepheids, can serve as a laboratory where feebly connected Beyond Standard Model particles such as axions can be gainfully studied. We undertake a careful study of the effects of these putative particles on the blue loop, paying close attention to the evolution of the core potential and the hydrogen profile. Our simulations, performed withMESA, place bounds on the axion-photon coupling using the galactic Cepheid S Mus, with dynamically-determined mass of 6M_⊙, as a benchmark. The effects of varying convective overshoot on the core potential and hydrogen profile, and the ensuing changes in the axion constraints, are carefully studied. Along the way, we explore the “mirror principle” induced by the hydrogen burning shell and contrast our results with those existing in the literature. Less conservative (but more stringent) bounds on the axion-photon coupling are given for a 9M_⊙model, which is the heaviest that can be simulated if overshoot is incorporated, and tentative projections are given for a 12M_⊙model, which is approximately the heaviest tail of the mass distribution of galactic Cepheids determined by pulsation models using Gaia DR2. Our main message is that the reliable simulation and observation (ideally, through dynamical mass determination) of massive Cepheids constitutes an important frontier in axion searches, challenges in modeling uncertainties in the microphysics of the blue loop stage notwithstanding. 

The ability to use past experience to effectively guide decision-making declines in older adulthood. Such declines have been theorized to emerge from either impairments of striatal reinforcement learning systems (RL) or impairments of recurrent networks in prefrontal and parietal cortex that support working memory (WM). Distinguishing between these hypotheses has been challenging because either RL or WM could be used to facilitate successful decision-making in typical laboratory tasks. Here we investigated the neurocomputational correlates of age-related decision-making deficits using an RL-WM task to disentangle these mechanisms, a computational model to quantify them, and magnetic resonance spectroscopy to link them to their molecular bases. Our results reveal that task performance is worse in older age, in a manner best explained by working memory deficits, as might be expected if cortical recurrent networks were unable to sustain persistent activity across multiple trials. Consistent with this, we show that older adults had lower levels of prefrontal glutamate, the excitatory neurotransmitter thought to support persistent activity, compared to younger adults. Individuals with the lowest prefrontal glutamate levels displayed the greatest impairments in working memory after controlling for other anatomical and metabolic factors. Together, our results suggest that lower levels of prefrontal glutamate may contribute to failures of working memory systems and impaired decision-making in older adulthood.