Sleep spindles are discrete, intermittent patterns of brain activity that arise as a result of interactions of several circuits in the brain. Increasingly, these oscillations are of biological and clinical interest because of their role in development, learning, and neurological disorders. We used an internet interface to ‘crowdsource’ spindle identification from human experts and non-experts, and compared performance with 6 automated detection algorithms in middle-to-older aged subjects from the general population. We also developed a method for forming group consensus, and refined methods of evaluating the performance of event detectors in physiological data such as polysomnography. Compared to the gold standard, the highest performance was by individual experts and the non-expert group consensus, followed by automated spindle detectors. Crowdsourcing the scoring of sleep data is an efficient method to collect large datasets, even for difficult tasks such as spindle identification. Further refinements to automated sleep spindle algorithms are needed for middle-to-older aged subjects.

Post-translational processes are essential for the generation and dynamics of mammalian circadian rhythms. In particular, phosphorylation of the key circadian protein PER2 precisely controls the period and phase of circadian oscillations. However, the mechanisms underlying that control are poorly understood. Here, we identified in a high-throughput RNAi-based genetic screen casein kinase 2 (CK2) as a PER2-phosphorylating kinase and novel component of the mammalian circadian clock. When CK2 subunits are silenced by RNAi or when CK2 activity is inhibited pharmacologically, circadian rhythms are disrupted. CK2 binds to PER2 in vivo, phosphorylates PER2 specifically at N-terminal residues in vitro, and supports normal nuclear PER2 accumulation. Mutation of CK2 phosphorylation sites decreases PER2 stability and copies CK2 inhibition regarding oscillation dynamics. We propose a new concept of how PER2 phosphorylation and stabilization can set the clock speed in opposite directions, dependent on the phase of action.[Keywords: Circadian clock; casein kinase 2; period 2; RNAi screen; phosphorylation] Supplemental material is available at http://www.genesdev.org.

Antarctic krill, Euphausia superba, shapes the structure of the Southern Ocean ecosystem. Its central position in the food web, the ongoing environmental changes due to climatic warming, and increasing commercial interest on this species emphasize the urgency of understanding the adaptability of krill to its environment. Krill has evolved rhythmic physiological and behavioral functions which are synchronized with the daily and seasonal cycles of the complex Southern Ocean ecosystem. The mechanisms, however, leading to these rhythms are essentially unknown. Here, we show that krill possesses an endogenous circadian clock that governs metabolic and physiological output rhythms. We found that expression of the canonical clock gene cry2 was highly rhythmic both in a light-dark cycle and in constant darkness. We detected a remarkable short circadian period, which we interpret as a special feature of the krill's circadian clock that helps to entrain the circadian system to the extreme range of photoperiods krill is exposed to throughout the year. Furthermore, we found that important key metabolic enzymes of krill showed bimodal circadian oscillations (∼9–12 h period) in transcript abundance and enzymatic activity. Oxygen consumption of krill showed ∼9–12 h oscillations that correlated with the temporal activity profile of key enzymes of aerobic energy metabolism. Our results demonstrate the first report of an endogenous circadian timing system in Antarctic krill and its likely link to metabolic key processes. Krill's circadian clock may not only be critical for synchronization to the solar day but also for the control of seasonal events. This study provides a powerful basis for the investigation into the mechanisms of temporal synchronization in this marine key species and will also lead to the first comprehensive analyses of the circadian clock of a polar marine organism through the entire photoperiodic cycle.

Objectives To measure the inter-expert and intra-expert agreement in sleep spindle scoring, and to quantify how many experts are needed to build a reliable dataset of sleep spindle scorings. Methods The EEG dataset was comprised of 400 randomly selected 115 s segments of stage 2 sleep from 110 sleeping subjects in the general population (57±8, range: 42-72 years). To assess expert agreement, a total of 24 Registered Polysomnographic Technologists (RPSGTs) scored spindles in a subset of the EEG dataset at a single electrode location (C3-M2). Intra-expert and inter-expert agreements were calculated as F1-scores, Cohen’s kappa (κ), and intra-class correlation coefficient (ICC). Results We found an average intra-expert F1-score agreement of 72±7 % (κ: 0.66±0.07). The average inter-expert agreement was 61±6 % (κ: 0.52±0.07). Amplitude and frequency of discrete spindles were calculated with higher reliability than the estimation of spindle duration. Reliability of sleep spindle scoring can be improved by using qualitative confidence scores, rather than a dichotomous yes/no scoring system. Conclusions We estimate that 2-3 experts are needed to build a spindle scoring dataset with ‘substantial’ reliability (κ: 0.61-0.8), and 4 or more experts are needed to build a dataset with ‘almost perfect’ reliability (κ: 0.81-1). Significance Spindle scoring is a critical part of sleep staging, and spindles are believed to play an important role in development, aging, and diseases of the nervous system.