Age differences in encoding-related alpha power reflect sentence comprehension difficulties

When sentence processing taxes verbal working memory, comprehension difficulties arise. This is specifically the case when processing resources decline with advancing adult age. Such decline likely affects the encoding of sentences into working memory, which constitutes the basis for successful comprehension. To assess age differences in encoding-related electrophysiological activity, we recorded the electroencephalogram from three age groups (24, 43, and 65 years). Using an auditory sentence comprehension task, age differences in encoding-related oscillatory power were examined with respect to the accuracy of the given response. That is, the difference in oscillatory power between correctly and incorrectly encoded sentences, yielding subsequent memory effects (SME), was compared across age groups. Across age groups, we observed an age-related SME inversion in the alpha band from a power decrease in younger adults to a power increase in older adults. We suggest that this SME inversion underlies age-related comprehension difficulties. With alpha being commonly linked to inhibitory processes, this shift may reflect a change in the cortical inhibition–disinhibition balance. A cortical disinhibition may imply enriched sentence encoding in younger adults. In contrast, resource limitations in older adults may necessitate an increase in cortical inhibition during sentence encoding to avoid an information overload. Overall, our findings tentatively suggest that age-related comprehension difficulties are associated with alterations to the electrophysiological dynamics subserving general higher cognitive functions

New Era, New Opportunity, Is GES DISC Ready for Big Data Challenge?

The new era of Big Data has opened doors for many new opportunities, as well as new challenges, for both Earth science research/application and data communities. As one of the twelve NASA data centers - Goddard Earth Sciences Data and Information Services Center (GES DISC), one of our great challenges has been how to help research/application community efficiently (quickly and properly) accessing, visualizing and analyzing the massive and diverse data in natural hazard research, management, or even prediction. GES DISC has archived over 2000 TB data on premises and distributed over 23,000 TB of data since 2010. Our data has been widely used in every phase of natural hazard management and research, i.e. long term risk assessment and reduction, forecasting and predicting, monitoring and detection, early warning, damage assessment and response. The big data challenge is not just about data storage, but also about data discoverability and accessibility, and even more, about data migration/mirroring in the cloud. This paper is going to demonstrate GES DISCs efforts and approaches of evolving our overall Web services and powerful Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) tool into further improving data discoverability and accessibility. Prototype works will also be presented

Unravelling functional neurology: A scoping review of theories and clinical applications in a context of chiropractic manual therapy

Background: Functional Neurology (FN), a seemingly attractive treatment approach used by some chiropractors, proposes to have an effect on a multitude of conditions but some of its concepts are controversial. Objectives and design: A scoping review was performed to describe, in the context of chiropractic manual therapy, 1) the FN theories, and 2) its clinical applications (i.e. its indications, examination procedures, treatment modalities, treatment plans, and clinical outcomes) using four sources: i) one key textbook, ii) the scientific peer-reviewed literature, iii) websites from chiropractors using FN, and iv) semi-structured interviews of chiropractors using FN. Methods: The scientific literature was searched in PubMed, PsycINFO, and SPORTDiscus, completed by a hand search in the journal Functional Neurology, Rehabilitation and Ergonomics (November 2016 and March 2017, respectively). The only textbook on the topic we found was included and articles were chosen if they had an element of manual therapy. There was no restriction for study design but discussion papers were excluded. Websites were found in Google using the search term "Functional Neurology". Chiropractors, known to use FN, were invited based on their geographical location. Theories were mainly uncovered in the textbook as were all aspects of the clinical applications except treatment plans. The other three sources were used for the five aspects of clinical applications. Results were summarized and reported extensively in tables. Results: Eleven articles were included, five websites scrutinized, and four semi-structured interviews performed. FN is based on the belief that reversible lesions in the nervous system are the cause of a multitude of conditions and that specific clusters of neurons can be positively affected by manipulative therapy, but also by many other stimuli. Diagnostic procedures include both conventional and unusual tests, with an interpretation specific to FN. Initial treatment is intense and clinical outcomes reported as positive. Conclusion: FN gives the impression to be a complex alternative to the old variant of the chiropractic subluxation model, in which the vertebral subluxation is replaced by "physiological lesions" of the brain, and the treatment, spinal adjustments, are complemented by various neurological stimuli. Both models purport to treat not the symptoms but the cause. We conclude there is a need for more scientific documentation on the validity of FN

Phase Sensitivity of a Mach-Zehnder Interferometer

The best performance of a Mach-Zehnder interferometer is achieved with the input state |N_T/2 + 1>|N_T/2-1 > + |N_T/2 - 1>|N_T/2+1>, being N_T the total number of atoms/photons. This gives: i) a phase-shift error confidence C_{68%}=2.67/N_T with ii) a single interferometric measurement. Different input quantum states can achieve the Heisenberg scaling ~ 1/N_T but with higher prefactors and at the price of a statistical analysis of two or more independent measurements.Comment: 4 figure

A Neural-Symbolic Cognitive Agent for Online Learning and Reasoning

In real-world applications, the effective integration of learning and reasoning in a cognitive agent model is a difficult task. However, such integration may lead to a better understanding, use and construction of more realistic models. Unfortunately, existing models are either oversimplified or require much processing time, which is unsuitable for online learning and reasoning. Currently, controlled environments like training simulators do not effectively integrate learning and reasoning. In particular, higher-order concepts and cognitive abilities have many unknown temporal relations with the data, making it impossible to represent such relationships by hand. We introduce a novel cognitive agent model and architecture for online learning and reasoning that seeks to effectively represent, learn and reason in complex training environments. The agent architecture of the model combines neural learning with symbolic knowledge representation. It is capable of learning new hypotheses from observed data, and infer new beliefs based on these hypotheses. Furthermore, it deals with uncertainty and errors in the data using a Bayesian inference model. The validation of the model on real-time simulations and the results presented here indicate the promise of the approach when performing online learning and reasoning in real-world scenarios, with possible applications in a range of areas

Non-adiabatic effects during the dissociative adsorption of O2 at Ag(111)? A first-principles divide and conquer study

We study the gas-surface dynamics of O2 at Ag(111) with the particular objective to unravel whether electronic non-adiabatic effects are contributing to the experimentally established inertness of the surface with respect to oxygen uptake. We employ a first-principles divide and conquer approach based on an extensive density-functional theory mapping of the adiabatic potential energy surface (PES) along the six O2 molecular degrees of freedom. Neural networks are subsequently used to interpolate this grid data to a continuous representation. The low computational cost with which forces are available from this PES representation allows then for a sufficiently large number of molecular dynamics trajectories to quantitatively determine the very low initial dissociative sticking coefficient at this surface. Already these adiabatic calculations yield dissociation probabilities close to the scattered experimental data. Our analysis shows that this low reactivity is governed by large energy barriers in excess of 1.1 eV very close to the surface. Unfortunately, these adiabatic PES characteristics render the dissociative sticking a rather insensitive quantity with respect to a potential spin or charge non-adiabaticity in the O2-Ag(111) interaction. We correspondingly attribute the remaining deviations between the computed and measured dissociation probabilities primarily to unresolved experimental issues with respect to surface imperfections.Comment: 18 pages including 6 figure

Systematic review of risk factors for eating psychopathology in athletes: A critique of an etiological model

Objective: The theoretical model by Petrie and Greenleaf (2007, 2012) is an admirable attempt to collate the causal factors of disordered eating in athletes. The aims of this systematic review are (a) to provide an overview of the findings from the relevant literature, (b) to assess whether the model is supported by the existing research, (c) to evaluate the different designs, methods, and measures used to test the mediators in the model, and (d) to highlight areas for improvements and future research. Method: A systematic review of four major online databases identified 37 relevant papers on risk factors of disordered eating in athletes, which were reviewed and critically compared with the theoretical model. Results: There is a lack of longitudinal research with the relevant mediators in athlete populations, which makes it difficult to determine whether the potential mediators described by Petrie and Greenleaf are causal risk factors rather than simply correlates of disordered eating for athletes. Findings for all the potential mediators are inconsistent, and the range of measures used makes it problematic to draw conclusions. Conclusions: Future research needs to use gold standard measures and longitudinal designs in order to fully test and possibly update the model