No abstract

SignificanceLocus coeruleus (LC) integrity in cognitively normal older adults is a potentially important preclinical marker in dementia. Our study establishes a link between variability in LC integrity and cognitive decline related to noradrenergic modulation in old age. We find that in older adults, reduced LC integrity explains lower memory performance. This effect was more pronounced for memory related to negative events, and accompanied by increased pupil diameter size in response to negative events. The study provides a strong motivation for future research investigating the role of LC integrity in healthy, as well as in pathological, aging.

10 The average power of rhythmic neural responses as captured by MEG/EEG/LFP recordings is a 11 prevalent index of human brain function. Increasing evidence questions the utility of trial-/group 12 averaged power estimates however, as seemingly sustained activity patterns may be brought about 13 by time-varying transient signals in each single trial. Hence, it is crucial to accurately describe the 14 duration and power of rhythmic and arrhythmic neural responses on the single trial-level. However, 15 it is less clear how well this can be achieved in empirical MEG/EEG/LFP recordings. Here, we 16 extend an existing rhythm detection algorithm (extended Better OSCillation detection: "eBOSC"; 17 cf. Whitten et al., 2011) to systematically investigate boundary conditions for estimating neural 18rhythms at the single-trial level. Using simulations as well as resting and task-based EEG recordings 19 from a micro-longitudinal assessment, we show that alpha rhythms can be successfully captured in 20 single trials with high specificity, but that the quality of single-trial estimates varies greatly between 21 subjects. Despite those signal-to-noise-based limitations, we highlight the utility and potential of 22 rhythm detection with multiple proof-of-concept examples, and discuss implications for single-trial 23 analyses of neural rhythms in electrophysiological recordings. Using an applied example of 24 working memory retention, rhythm detection indicated load-related increases in the duration of 25 frontal theta and posterior alpha rhythms, in addition to a frequency decrease of frontal theta 26 rhythms that was observed exclusively through amplification of rhythmic amplitudes. 27 28Highlights: 29• Traditional narrow-band rhythm metrics conflate the power and duration of rhythmic and arrhythmic 30 periods. We extend a state-of-the-art rhythm detection method (eBOSC) to derive rhythmic episodes in 31 single trials that can disambiguate rhythmic and arrhythmic periods. 32• Simulations indicate that this can be done with high specificity given sufficient rhythmic power, but with 33 strongly impaired sensitivity when rhythmic SNR is low. Empirically, surface EEG recordings exhibit 34 stable inter-individual differences in α-rhythmicity in ranges where simulations suggest a gradual bias, 35 leading to high collinearity between narrow-band and rhythm-specific estimates. 36• Beyond these limitations, we highlight multiple empirical benefits of characterizing rhythmic episodes 37 in single trials, such as (a) a principled separation of rhythmic and arrhythmic content, (b) an 38 amplification of rhythmic amplitudes, and (c) a specific characterization of sustained and transient 39 events. 40• In an exemplary application, rhythm-specific estimates increase sensitivity to working memory load 41 effects, in addition to indicating a frequency modulation of frontal theta rhythms through the 42 amplification of rhythmic power. 43 44