An important goal in neuroscience is to identify instances when EEG signals are coupled. We employ a method to measure the coupling strength between gamma signals (40-100 Hz) on a short time scale as the maximum cross-correlation over a range of time lags within a sliding variable-width window. Instances of coupling states among several signals are also identified, using a mixed multivariate beta distribution to model coupling strength across multiple gamma signals with reference to a common base signal. We first apply our variable-window method to simulated signals and compare its performance to a fixed-window approach. We then focus on gamma signals recorded in two regions of the rat hippocampus. Our results indicate that this may be a useful method for mapping coupling patterns among signals in EEG datasets.

Understanding the transcriptional regulation of pluripotent cells is of fundamental interest and will greatly inform efforts aimed at directing differentiation of embryonic stem (ES) cells or reprogramming somatic cells. We first analyzed the transcriptional profiles of mouse ES cells and primordial germ cells and identified genes upregulated in pluripotent cells both in vitro and in vivo. These genes are enriched for roles in transcription, chromatin remodeling, cell cycle, and DNA repair. We developed a novel computational algorithm, CompMoby, which combines analyses of sequences both aligned and non-aligned between different genomes with a probabilistic segmentation model to systematically predict short DNA motifs that regulate gene expression. CompMoby was used to identify conserved overrepresented motifs in genes upregulated in pluripotent cells. We show that the motifs are preferentially active in undifferentiated mouse ES and embryonic germ cells in a sequence-specific manner, and that they can act as enhancers in the context of an endogenous promoter. Importantly, the activity of the motifs is conserved in human ES cells. We further show that the transcription factor NF-Y specifically binds to one of the motifs, is differentially expressed during ES cell differentiation, and is required for ES cell proliferation. This study provides novel insights into the transcriptional regulatory networks of pluripotent cells. Our results suggest that this systematic approach can be broadly applied to understanding transcriptional networks in mammalian species.

One hallmark of the normal cognitive aging process involves alterations in executive function. Executive function can be divided into at least three separable components, including set shifting, attentional updating and monitoring, and inhibition of prepotent responses. The ability to study the neural basis of cognitive aging has been enriched by the use of animal models such as the macaque monkey. In aged macaques, changes in attentional updating and monitoring systems are poorly understood compared to changes in shifting and inhibition. A partial explanation for this is the fact that the tasks designed to study executive function in aged monkeys, to date, primarily have probed shifting and inhibition processes. Here we examine how aging impacts attentional updating and monitoring processes in monkeys using an interference task designed after a paradigm used to examine multi-tasking in older humans. Young and aged macaque monkeys were tested on this interference task as well as on an object reversal learning task to study these processes in the same animals. Relative to the young monkeys, aged animals were impaired on both tasks. Proactive and retroactive interference did not differ between age groups on an array of 40 object pairs presented each day in the object reversal learning task. The levels of performance on the interference task were not correlated with levels of performance in the object reversal task. These results suggest that attentional updating and monitoring and affective shifting are separable functions in the macaque, and that normal aging affects these mental operations independently.

Dimethylation of histone H3 lysine 9 (H3K9m2) and trimethylation of histone H3 lysine 27 (H3K27m3) are two hallmarks of transcriptional repression in many organisms. In Arabidopsis thaliana, H3K27m3 is targeted by Polycomb Group (PcG) proteins and is associated with silent protein-coding genes, while H3K9m2 is correlated with DNA methylation and is associated with transposons and repetitive sequences. Recently, ectopic genic DNA methylation in the CHG context (where H is any base except G) has been observed in globally DNA hypomethylated mutants such as met1, but neither the nature of the hypermethylated loci nor the biological significance of this epigenetic phenomenon have been investigated. Here, we generated high-resolution, genome-wide maps of both H3K9m2 and H3K27m3 in wild-type and met1 plants, which we integrated with transcriptional data, to explore the relationships between these two marks. We found that ectopic H3K9m2 observed in met1 can be due to defects in IBM1-mediated H3K9m2 demethylation at some sites, but most importantly targets H3K27m3-marked genes, suggesting an interplay between these two silencing marks. Furthermore, H3K9m2/DNA-hypermethylation at these PcG targets in met1 is coupled with a decrease in H3K27m3 marks, whereas CG/H3K9m2 hypomethylated transposons become ectopically H3K27m3 hypermethylated. Our results bear interesting similarities with cancer cells, which show global losses of DNA methylation but ectopic hypermethylation of genes previously marked by H3K27m3.

Objective

Impairments in learning are central to autism spectrum disorders. The authors investigated the cognitive and neural basis of these deficits in young adults with autism spectrum disorders using a well-characterized probabilistic reinforcement learning paradigm.

Method

The probabilistic selection task was implemented among matched participants with autism spectrum disorders (N=22) and with typical development (N=25), aged 18-40 years, using rapid event-related functional MRI. Participants were trained to choose the correct stimulus in high-probability (AB), medium-probability (CD), and low-probability (EF) pairs, presented with valid feedback 80%, 70%, and 60% of the time, respectively. Whole-brain voxel-wise and parametric modulator analyses examined early and late learning during the stimulus and feedback epochs of the task.

Results

The groups exhibited comparable performance on medium- and low-probability pairs. Typically developing persons showed higher accuracy on the high-probability pair, better win-stay performance (selection of the previously rewarded stimulus on the next trial of that type), and more robust recruitment of the anterior and medial prefrontal cortex during the stimulus epoch, suggesting development of an intact reward-based working memory for recent stimulus values. Throughout the feedback epoch, individuals with autism spectrum disorders exhibited greater recruitment of the anterior cingulate and orbito-frontal cortices compared with individuals with typical development, indicating continuing trial-by-trial activity related to feedback processing.

Conclusions

Individuals with autism spectrum disorders exhibit learning deficits reflecting impaired ability to develop an effective reward-based working memory to guide stimulus selection. Instead, they continue to rely on trial-by-trial feedback processing to support learning dependent upon engagement of the anterior cingulate and orbito-frontal cortices.

Objective

Football players are at risk of developing hip osteoarthritis (OA). Cam morphology (present in almost two of every three football players) may explain this heightened risk, but there is limited research on its role in hip OA development in younger athletes. Knowledge of this relationship will advance our understanding of the aetiology of hip OA in football players. We aimed to study the relationship between cam morphology size and MRI-defined cartilage defects and labral tears, and if this relationship differs by symptomatic state in young adult football players.

Methods

For this case-control study, 182 (288 hips) symptomatic (hip and/or groin pain >6 months and positive flexion-adduction-internal-rotation (FADIR) test) and 55 (110 hips) pain-free football players (soccer or Australian football) underwent anteroposterior and Dunn 45° radiographs, and 3-Tesla MRI. Cam morphology size was defined using alpha angle, and cartilage defects and labral tears were scored semiquantitatively. Presence, location and score (severity) of cartilage defects and labral tears were determined. Each participant completed the International Hip Outcome Tool 33 and Copenhagen Hip and Groin Outcome Score.

Results

Greater alpha angle was associated with cartilage defects (OR 1.03, 95% CI 1.01 to 1.04) and labral tears (OR 1.02, 95% CI 1.01 to 1.04). Greater alpha angle was associated with superolateral cartilage defects (OR 1.03, 95% CI 1.02 to 1.05) and superior labral tears (OR 1.03, 95% CI 1.02 to 1.05). The association of alpha angle with MRI-defined cartilage defects and labral tears was no greater in football players with symptoms than in those without (p=0.189-0.937).

Conclusion

Cam morphology size was associated with cartilage defects and labral tears in young adult football players with and without pain. This study provides evidence that cam morphology may contribute to the high prevalence of hip OA in football players. Prospective studies of football players are now needed to establish if cam morphology causes progression of cartilage defects and labral tears and development of hip OA.

The Community Earth System Model (CESM1) CAM4-chem has been used to perform the Chemistry Climate Model Initiative (CCMI) reference and sensitivity simulations. In this model, the Community Atmospheric Model version 4 (CAM4) is fully coupled to tropospheric and stratospheric chemistry. Details and specifics of each configuration, including new developments and improvements are described. CESM1 CAM4-chem is a low-top model that reaches up to approximately 40km and uses a horizontal resolution of 1.9° latitude and 2.5° longitude. For the specified dynamics experiments, the model is nudged to Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. We summarize the performance of the three reference simulations suggested by CCMI, with a focus on the last 15 years of the simulation when most observations are available. Comparisons with selected data sets are employed to demonstrate the general performance of the model. We highlight new data sets that are suited for multi-model evaluation studies. Most important improvements of the model are the treatment of stratospheric aerosols and the corresponding adjustments for radiation and optics, the updated chemistry scheme including improved polar chemistry and stratospheric dynamics and improved dry deposition rates. These updates lead to a very good representation of tropospheric ozone within 20% of values from available observations for most regions. In particular, the trend and magnitude of surface ozone is much improved compared to earlier versions of the model. Furthermore, stratospheric column ozone of the Southern Hemisphere in winter and spring is reasonably well represented. All experiments still underestimate CO most significantly in Northern Hemisphere spring and show a significant underestimation of hydrocarbons based on surface observations.