Computational modelling in source space from scalp EEG to inform presurgical evaluation of epilepsy

This is the author accepted manuscript. The final version is available on open access from Elsevier via the DOI in this recordObjective: The effectiveness of intracranial electroencephalography (iEEG) to inform epilepsy surgery depends on where iEEG electrodes are implanted. This decision is informed by noninvasive recording modalities such as scalp EEG. Herein we propose a framework to interrogate scalp EEG and determine epilepsy lateralization to aid in electrode implantation. Methods: We use eLORETA to map source activities from seizure epochs recorded from scalp EEG and consider 15 regions of interest (ROIs). Functional networks are then constructed using the phase-locking value and studied using a mathematical model. By removing different ROIs from the network and simulating their impact on the network’s ability to generate seizures in silico, the framework provides predictions of epilepsy lateralization. We consider 15 individuals from the EPILEPSIAE database and study a total of 62 seizures. Results were assessed by taking into account actual intracranial implantations and surgical outcome. Results: The framework provided potentially useful information regarding epilepsy lateralization in 12 out of the 15 individuals (p=0.02, binomial test). Conclusions: Our results show promise for the use of this framework to better interrogate scalp EEG to determine epilepsy lateralization. Significance: The framework may aid clinicians in the decision process to define where to implant electrodes for intracranial monitoring.Medical Research CouncilEpilepsy Research UKEngineering and Physical Sciences Research Council (EPSRC)Wellcome TrustEngineering and Physical Sciences Research Council (EPSRC)Innovate UKEuropean Union’s Horizon 2020Alzheimer's SocietyMedical Research Counci

External Device to Incrementally Skid the Habitat (E-DISH)

A Mars habitat transport system was designed as part of the NASA Mars exploration program. The transport system, the External Device to Incrementally Skid the Habitat (E - DISH), will be used to transport Mars habitats from their landing sites to the colony base and will be detached after unloading. The system requirements for Mars were calculated and scaled for model purposes. Specific model materials are commonly found and recommendations for materials for the Mars design are included

Clumped isotope and Δ17O measurements of carbonates in CM carbonaceous chondrites: new insights into parent body thermal and fluid evolution

The CM carbonaceous chondrites are key archives for understanding the earliest history of the solar system. Their C-complex asteroid parent body(ies) underwent aqueous alteration, among the products of which are carbonate minerals that can faithfully record the conditions of their formation. In this study we report carbon, triple oxygen and clumped isotope compositions of carbonates in six CM chondrites which span a range in degrees of aqueous alteration (Allan Hills 83100, Cold Bokkeveld, LaPaz Icefield 031166, Lonewolf Nunataks 94101, Murchison, Scott Glacier 06043). Δ¹⁷O values range from −2.6 to −1.0 ‰ (±0.1), and where calcite and dolomite co-exist their Δ¹⁷O differ by 0.6 permil, suggesting precipitation from distinct fluids. Calculated crystallization temperatures range from 5 to 51 °C for calcite (typically ± 10 °C) and 75 to 101(±15) °C for dolomite. The δ¹⁸ᴼVSMOW of the aqueous fluids from which they formed ranges from −6.6 to 2.3 ‰, with no relationship to the δ¹³C of carbonates. As the population of carbonates in any one CM chondrite can include multiple generations of grains that formed at different conditions, these values represent the mode of the temperature of carbonate formation for each meteorite. We observe that in the more altered meteorites carbonate Δ¹⁷O values are lower and formation temperatures are higher. These correlations are consistent with aqueous alteration of the CM chondrites being a prograde reaction whereby the hotter fluids had undergone greater isotope exchange with the anhydrous matrix. Our data are broadly consistent with the closed system model for water/rock interaction, but carbonate mineral formation in the latter stages of aqueous alteration may be linked to fluid movement via fractures

Teaching psychology to student nurses: the use of talking heads videos

Psychology is a central part of undergraduate nursing curricula in the UK.However, student nurses report difficulties recognising the relevance and value of psychology. We sought to strengthen first-year student nurses’ application of psychology by developing a set of digital stories based around ‘Talking Head’video clips where authentic patients relate their experiences of illness and nursing care. The aim of this article is to discuss the technological, organisational and pedagogical challenges, student and staff evaluations and our recommendations for the future of Talking Heads. First-year student nurses were shown a video clip of a patient talking about their illness experiences followed by a group learning situation linking main themes to psychology and nursing. Students and staff valued the authenticity of patient’s narrative, found the video clip easy to follow,reported a raised awareness of psychological concepts and improved empathetic understanding of chronic illness. Negative evaluations were related to a sanitised, untypical representation and limited internet access. This small-scale study highlighted how patient narrative may enhance students understanding of illness experience. It chronicles the development and evaluation of a Talking Head in a specific context but which may be useful across disciplines

Asenapine effects in animal models of psychosis and cognitive function

Asenapine, a novel psychopharmacologic agent in the development for schizophrenia and bipolar disorder, has high affinity for serotonergic, α-adrenergic, and dopaminergic receptors, suggesting potential for antipsychotic and cognitive-enhancing properties. The effects of asenapine in rat models of antipsychotic efficacy and cognition were examined and compared with those of olanzapine and risperidone. Amphetamine-stimulated locomotor activity (Amp-LMA; 1.0 or 3.0 mg/kg s.c.) and apomorphine-disrupted prepulse inhibition (Apo-PPI; 0.5 mg/kg s.c.) were used as tests for antipsychotic activity. Delayed non-match to place (DNMTP) and five-choice serial reaction (5-CSR) tasks were used to assess short-term spatial memory and attention, respectively. Asenapine doses varied across tasks: Amp-LMA (0.01–0.3 mg/kg s.c.), Apo-PPI (0.001–0.3 mg/kg s.c.), DNMTP (0.01–0.1 mg/kg s.c.), and 5-CSR (0.003–0.3 mg/kg s.c.). Asenapine was highly potent (active at 0.03 mg/kg) in the Amp-LMA and Apo-PPI assays. DNMTP or 5-CSR performance was not improved by asenapine, olanzapine, or risperidone. All agents (P < 0.01) reduced DNMTP accuracy at short delays; post hoc analyses revealed that only 0.1 mg/kg asenapine and 0.3 mg/kg risperidone differed from vehicle. All active agents (asenapine, 0.3 mg/kg; olanzapine, 0.03–0.3 mg/kg; and risperidone, 0.01–0.1 mg/kg) significantly impaired 5-CSR accuracy (P < 0.05). Asenapine has potent antidopaminergic properties that are predictive of antipsychotic efficacy. Asenapine, like risperidone and olanzapine, did not improve cognition in normal rats. Rather, at doses greater than those required for antipsychotic activity, asenapine impaired cognitive performance due to disturbance of motor function, an effect also observed with olanzapine and risperidone

Computational Models of Classical Conditioning guest editors’ introduction

In the present special issue, the performance of current computational models of classical conditioning was evaluated under three requirements: (1) Models were to be tested against a list of previously agreed-upon phenomena; (2) the parameters were fixed across simulations; and (3) the simulations used to test the models had to be made available. These requirements resulted in three major products: (a) a list of fundamental classical-conditioning results for which there is a consensus about their reliability; (b) the necessary information to evaluate each of the models on the basis of its ordinal successes in accounting for the experimental data; and (c) a repository of computational models ready to generate simulations. We believe that the contents of this issue represent the 2012 state of the art in computational modeling of classical conditioning and provide a way to find promising avenues for future model development

A Cryogenic Silicon Interferometer for Gravitational-wave Detection

The detection of gravitational waves from compact binary mergers by LIGO has opened the era of gravitational wave astronomy, revealing a previously hidden side of the cosmos. To maximize the reach of the existing LIGO observatory facilities, we have designed a new instrument able to detect gravitational waves at distances 5 times further away than possible with Advanced LIGO, or at greater than 100 times the event rate. Observations with this new instrument will make possible dramatic steps toward understanding the physics of the nearby Universe, as well as observing the Universe out to cosmological distances by the detection of binary black hole coalescences. This article presents the instrument design and a quantitative analysis of the anticipated noise floor

A Cryogenic Silicon Interferometer for Gravitational-wave Detection

The detection of gravitational waves from compact binary mergers by LIGO has opened the era of gravitational wave astronomy, revealing a previously hidden side of the cosmos. To maximize the reach of the existing LIGO observatory facilities, we have designed a new instrument that will have 5 times the range of Advanced LIGO, or greater than 100 times the event rate. Observations with this new instrument will make possible dramatic steps toward understanding the physics of the nearby universe, as well as observing the universe out to cosmological distances by the detection of binary black hole coalescences. This article presents the instrument design and a quantitative analysis of the anticipated noise floor

Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype