Still feeling it: the time course of emotional recovery from an attentional perspective

Emotional reactivity and the time taken to recover, particularly from negative, stressful, events, are inextricably linked, and both are crucial for maintaining well-being. It is unclear, however, to what extent emotional reactivity during stimulus onset predicts the time course of recovery after stimulus offset. To address this question, 25 participants viewed arousing (negative and positive) and neutral pictures from the International Affective Picture System (IAPS) followed by task-relevant face targets, which were to be gender categorized. Faces were presented early (400–1500 ms) or late (2400–3500 ms) after picture offset to capture the time course of recovery from emotional stimuli. Measures of reaction time (RT), as well as face-locked N170 and P3 components were taken as indicators of the impact of lingering emotion on attentional facilitation or interference. Electrophysiological effects revealed negative and positive images to facilitate face-target processing on the P3 component, regardless of temporal interval. At the individual level, increased reactivity to: (1) negative pictures, quantified as the IAPS picture-locked Late Positive Potential (LPP), predicted larger attentional interference on the face-locked P3 component to faces presented in the late time window after picture offset. (2) Positive pictures, denoted by the LPP, predicted larger facilitation on the face-locked P3 component to faces presented in the earlier time window after picture offset. These results suggest that subsequent processing is still impacted up to 3500 ms after the offset of negative pictures and 1500 ms after the offset of positive pictures for individuals reacting more strongly to these pictures, respectively. Such findings emphasize the importance of individual differences in reactivity when predicting the temporality of emotional recovery. The current experimental model provides a novel basis for future research aiming to identify profiles of adaptive and maladaptive recovery.

Name agreement in picture naming: An ERP study

Name agreement is the extent to which different people agree on a name for a particular picture. Previous studies have found that it takes longer to name low name agreement pictures than high name agreement pictures. To examine the effect of name agreement in the online process of picture naming, we compared event-related potentials (ERPs) recorded whilst 19 healthy, native English speakers silently named pictures which had either high or low name agreement. A series of ERP components was examined: P1 approximately 120ms from picture onset, N1 around 170ms, P2 around 220ms, N2 around 290ms, and P3 around 400ms. Additionally, a late time window from 800 to 900ms was considered. Name agreement had an early effect, starting at P1 and possibly resulting from uncertainty of picture identity, and continuing into N2, possibly resulting from alternative names for pictures. These results support the idea that name agreement affects two consecutive processes: first, object recognition, and second, lexical selection and/or phonological encoding.

Taxonomical vs. functional responses of bee communities to fire in two contrasting climatic regions

Valuable insights into mechanisms of community responses to environmental change can be gained by analysing in tandem the variation in functional and taxonomic composition along environmental gradients. We assess the changes in species and functional trait composition (i.e. dominant traits and functional diversity) of diverse bee communities in contrasting fire-driven systems in two climatic regions: Mediterranean (scrub habitats in Israel) and temperate (chestnut forests in southern Switzerland). In both climatic regions, there were shifts in species diversity and composition related to post-fire age. In the temperate region, functional composition responded markedly to fire; however, in the Mediterranean, the taxonomic response to fire was not matched by functional replacement. These results suggest that greater functional stability to fire in the Mediterranean is achieved by replacement of functionally similar species (i.e. functional redundancy) which dominate under different environmental conditions in the heterogeneous landscapes of the region. In contrast, the greater functional response in the temperate region was attributed to a more rapid post-fire vegetation recovery and shorter time-window when favourable habitat was available relative to the Mediterranean. Bee traits can be used to predict the functional responses of bee communities to environmental changes in habitats of conservation importance in different regions with distinct disturbance regimes. However, predictions cannot be generalized from one climatic region to another where distinct habitat configurations occur.

How the brain blinks: towards a neurocognitive model of the attentional blink

When people monitor a visual stream of rapidly presented stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset-the attentional blink (AB). We provide an overview of recent neuroscientific studies devoted to analyze the neural processes underlying the AB and their temporal dynamics. The available evidence points to an attentional network involving temporal, right-parietal and frontal cortex, and suggests that the components of this neural network interact by means of synchronization and stimulus-induced desynchronization in the beta frequency range. We set up a neurocognitive scenario describing how the AB might emerge and why it depends on the presence of masks and the other event(s) the targets are embedded in. The scenario supports the idea that the AB arises from "biased competition", with the top-down bias being generated by parietal-frontal interactions and the competition taking place between stimulus codes in temporal cortex.

Lag-1 sparing in the attentional blink: benefits and costs of integrating two events into a single episode

When people monitor a visual stream of rapidly presented stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset-the attentional blink. However, if T2 immediately follows T1, performance is often reported being as good as that at long lags-the so-called Lag-1 sparing effect. Two experiments investigated the mechanisms underlying this effect. Experiment 1 showed that, at Lag 1, requiring subjects to correctly report both identity and temporal order of targets produces relatively good performance on T2 but relatively bad performance on T1. Experiment 2 confirmed that subjects often confuse target order at short lags, especially if the two targets are equally easy to discriminate. Results suggest that, if two targets appear in close succession, they compete for attentional resources. If the two competitors are of unequal strength the stronger one is more likely to win and be reported at the expense of the other. If the two are equally strong, however, they will often be integrated into the same attentional episode and thus get both access to attentional resources. But this comes with a cost, as it eliminates information about the targets' temporal order.

Short-term memory and the attentional blink: capacity versus content

When people monitor the rapid serial visual presentation (RSVP) of stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset, a phenomenon known as the attentional blink (AB). We found that overall performance in an RSVP task was impaired by a concurrent short-term memory (STM) task and, furthermore, that this effect increased when STM load was higher and when its content was more task relevant. Loading visually defined stimuli and adding articulatory suppression further impaired performance on the RSVP task, but the size of the AB over time (i.e., T1-T2 lag) remained unaffected by load or content. This suggested that at least part of the performance in an RSVP task reflects interference between competing codes within STM, as interference models have held, whereas the AB proper reflects capacity limitations in the transfer to STM, as consolidation models have claimed.

Single tap identification for fast BCI control

One of the major aims of BCI research is devoted to achieving faster and more efficient control of external devices. The identification of individual tap events in a motor imagery BCI is therefore a desirable goal. EEG is recorded from subjects performing and imagining finger taps with their left and right hands. A Differential Evolution based feature selection wrapper is used in order to identify optimal features in the spatial and frequency domains for tap identification. Channel-frequency band combinations are found which allow differentiation of tap vs. no-tap control conditions for executed and imagined taps. Left vs. right hand taps may also be differentiated with features found in this manner. A sliding time window is then used to accurately identify individual taps in the executed tap and imagined tap conditions. Highly statistically significant classification accuracies are achieved with time windows of 0.5 s and more allowing taps to be identified on a single trial basis.

Regularization techniques for ill-posed inverse problems in data assimilation

Optimal state estimation from given observations of a dynamical system by data assimilation is generally an ill-posed inverse problem. In order to solve the problem, a standard Tikhonov, or L2, regularization is used, based on certain statistical assumptions on the errors in the data. The regularization term constrains the estimate of the state to remain close to a prior estimate. In the presence of model error, this approach does not capture the initial state of the system accurately, as the initial state estimate is derived by minimizing the average error between the model predictions and the observations over a time window. Here we examine an alternative L1 regularization technique that has proved valuable in image processing. We show that for examples of flow with sharp fronts and shocks, the L1 regularization technique performs more accurately than standard L2 regularization.

Keeping the world at hand: rapid visuomotor processing for hand-object interactions

The existence of hand-centred visual processing has long been established in the macaque premotor cortex. These hand-centred mechanisms have been thought to play some general role in the sensory guidance of movements towards objects, or, more recently, in the sensory guidance of object avoidance movements. We suggest that these hand-centred mechanisms play a specific and prominent role in the rapid selection and control of manual actions following sudden changes in the properties of the objects relevant for hand-object interactions. We discuss recent anatomical and physiological evidence from human and non-human primates, which indicates the existence of rapid processing of visual information for hand-object interactions. This new evidence demonstrates how several stages of the hierarchical visual processing system may be bypassed, feeding the motor system with hand-related visual inputs within just 70 ms following a sudden event. This time window is early enough, and this processing rapid enough, to allow the generation and control of rapid hand-centred avoidance and acquisitive actions, for aversive and desired objects, respectively

A novel alternative to cryopreservation for the short-term storage of stem cells for use in cell therapy using alginate encapsulation

Efficient transport of stem/progenitor cells without affecting their survival and function is a key factor in any practical cell-based therapy. However, the current approach using liquid nitrogen for the transfer of stem cells requires a short delivery time window is technically challenging and financially expensive. The present study aims to use semipermeable alginate hydrogels (crosslinked by strontium) to encapsulate, store, and release stem cells, to replace the conventional cryopreservation method for the transport of therapeutic cells within world-wide distribution time frame. Human mesenchymal stem cell (hMSC) and mouse embryonic stem cells (mESCs) were successfully stored inside alginate hydrogels for 5 days under ambient conditions in an air-tight environment (sealed cryovial). Cell viability, of the cells extracted from alginate gel, gave 74% (mESC) and 80% (hMSC) survival rates, which compared favorably to cryopreservation. More importantly, the subsequent proliferation rate and detection of common stem cell markers (both in mRNA and protein level) from hMSCs and mESCs retrieved from alginate hydrogels were also comparable to (if not better than) results gained following cryopreservation. In conclusion, this new and simple application of alginate hydrogel encapsulation may offer a cheap and robust alternative to cryopreservation for the transport and storage of stem cells for both clinical and research purposes.

A method to assess individual research outputs

We present here a straightforward method which can be used to obtain a quantitative indication of an individual research output for an academic. Different versions, selections and options are presented to enable a user to easily calculate values both for stand-alone papers and overall for the collection of outputs for a person. The procedure is particularly useful as a metric to give a quantitative indication of the research output of a person over a time window. Examples are included to show how the method works in practice and how it compares to alternative techniques.

Implication of methodological uncertainties for mid-Holocene sea surface temperature reconstructions

We present and examine a multi-sensor global compilation of mid-Holocene (MH) sea surface temperatures (SST), based on Mg/Ca and alkenone palaeothermometry and reconstructions obtained using planktonic foraminifera and organic-walled dinoflagellate cyst census counts. We assess the uncertainties originating from using different methodologies and evaluate the potential of MH SST reconstructions as a benchmark for climate-model simulations. The comparison between different analytical approaches (time frame, baseline climate) shows the choice of time window for the MH has a negligible effect on the reconstructed SST pattern, but the choice of baseline climate affects both the magnitude and spatial pattern of the reconstructed SSTs. Comparison of the SST reconstructions made using different sensors shows significant discrepancies at a regional scale, with uncertainties often exceeding the reconstructed SST anomaly. Apparent patterns in SST may largely be a reflection of the use of different sensors in different regions. Overall, the uncertainties associated with the SST reconstructions are generally larger than the MH anomalies. Thus, the SST data currently available cannot serve as a target for benchmarking model simulations. Further evaluations of potential subsurface and/or seasonal artifacts that may contribute to obscure the MH SST reconstructions are urgently needed to provide reliable benchmarks for model evaluations.

Using high-frequency water quality data to assess sampling strategies for the EU Water Framework Directive

The EU Water Framework Directive (WFD) requires that the ecological and chemical status of water bodies in Europe should be assessed, and action taken where possible to ensure that at least "good" quality is attained in each case by 2015. This paper is concerned with the accuracy and precision with which chemical status in rivers can be measured given certain sampling strategies, and how this can be improved. High-frequency (hourly) chemical data from four rivers in southern England were subsampled to simulate different sampling strategies for four parameters used for WFD classification: dissolved phosphorus, dissolved oxygen, pH and water temperature. These data sub-sets were then used to calculate the WFD classification for each site. Monthly sampling was less precise than weekly sampling, but the effect on WFD classification depended on the closeness of the range of concentrations to the class boundaries. In some cases, monthly sampling for a year could result in the same water body being assigned to three or four of the WFD classes with 95% confidence, due to random sampling effects, whereas with weekly sampling this was one or two classes for the same cases. In the most extreme case, the same water body could have been assigned to any of the five WFD quality classes. Weekly sampling considerably reduces the uncertainties compared to monthly sampling. The width of the weekly sampled confidence intervals was about 33% that of the monthly for P species and pH, about 50% for dissolved oxygen, and about 67% for water temperature. For water temperature, which is assessed as the 98th percentile in the UK, monthly sampling biases the mean downwards by about 1 °C compared to the true value, due to problems of assessing high percentiles with limited data. Low-frequency measurements will generally be unsuitable for assessing standards expressed as high percentiles. Confining sampling to the working week compared to all 7 days made little difference, but a modest improvement in precision could be obtained by sampling at the same time of day within a 3 h time window, and this is recommended. For parameters with a strong diel variation, such as dissolved oxygen, the value obtained, and thus possibly the WFD classification, can depend markedly on when in the cycle the sample was taken. Specifying this in the sampling regime would be a straightforward way to improve precision, but there needs to be agreement about how best to characterise risk in different types of river. These results suggest that in some cases it will be difficult to assign accurate WFD chemical classes or to detect likely trends using current sampling regimes, even for these largely groundwater-fed rivers. A more critical approach to sampling is needed to ensure that management actions are appropriate and supported by data.

An improved algorithm for generating global window brightness temperatures from multiple satellite infrared imagery

An improved algorithm for the generation of gridded window brightness temperatures is presented. The primary data source is the International Satellite Cloud Climatology Project, level B3 data, covering the period from July 1983 to the present. The algorithm rakes window brightness, temperatures from multiple satellites, both geostationary and polar orbiting, which have already been navigated and normalized radiometrically to the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer, and generates 3-hourly global images on a 0.5 degrees by 0.5 degrees latitude-longitude grid. The gridding uses a hierarchical scheme based on spherical kernel estimators. As part of the gridding procedure, the geostationary data are corrected for limb effects using a simple empirical correction to the radiances, from which the corrected temperatures are computed. This is in addition to the application of satellite zenith angle weighting to downweight limb pixels in preference to nearer-nadir pixels. The polar orbiter data are windowed on the target time with temporal weighting to account for the noncontemporaneous nature of the data. Large regions of missing data are interpolated from adjacent processed images using a form of motion compensated interpolation based on the estimation of motion vectors using an hierarchical block matching scheme. Examples are shown of the various stages in the process. Also shown are examples of the usefulness of this type of data in GCM validation.

Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model

This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.