The cost of space independence in P300-BCI spellers.

Background: Though non-invasive EEG-based Brain Computer Interfaces (BCI) have been researched extensively over the last two decades, most designs require control of spatial attention and/or gaze on the part of the user. Methods: In healthy adults, we compared the offline performance of a space-independent P300-based BCI for spelling words using Rapid Serial Visual Presentation (RSVP), to the well-known space-dependent Matrix P300 speller. Results: EEG classifiability with the RSVP speller was as good as with the Matrix speller. While the Matrix speller’s performance was significantly reliant on early, gaze-dependent Visual Evoked Potentials (VEPs), the RSVP speller depended only on the space-independent P300b. However, there was a cost to true spatial independence: the RSVP speller was less efficient in terms of spelling speed. Conclusions: The advantage of space independence in the RSVP speller was concomitant with a marked reduction in spelling efficiency. Nevertheless, with key improvements to the RSVP design, truly space-independent BCIs could approach efficiencies on par with the Matrix speller. With sufficiently high letter spelling rates fused with predictive language modelling, they would be viable for potential applications with patients unable to direct overt visual gaze or covert attentional focus

Ocean Acidification Changes Abiotic Processes but Not Biotic Processes in Coral Reef Sediments

In coral reefs, sediments play a crucial role in element cycling by contributing to primary production and the remineralization of organic matter. We studied how future ocean acidification (OA) will affect biotic and abiotic processes in sediments from two coral reefs of the Great Barrier Reef, Australia. This was investigated in the laboratory under conditions where water-sediment exchange was dominated by molecular diffusion (Magnetic Island) or by porewater advection (Davies Reef). OA conditions (+ΔpCO2: 170–900 μatm, −ΔpH: 0.1–0.4) did not affect photosynthesis, aerobic and anaerobic organic matter remineralization, and growth of microphytobenthos. However, microsensor measurements showed that OA conditions reduced the porewater pH. Under diffusive conditions these changes were limited to the upper sediment layers. In contrast, advective conditions caused a deeper penetration of low pH water into the sediment resulting in an earlier pH buffering by dissolution of calcium carbonate (CaCO3). This increased the dissolution of Davis Reef sediments turning them from net precipitating (−0.8 g CaCO3 m−2 d−1) under ambient to net dissolving (1 g CaCO3 m−2 d−1) under OA conditions. Comparisons with in-situ studies on other reef sediments show that our dissolution rates are reasonable estimates for field settings. We estimate that enhanced dissolution due to OA will only have a minor effect on net ecosystem calcification of the Davies Reef flat (<4%). However, it could decrease recent sediment accumulation rates in the lagoon by up to 31% (by 0.2–0.4 mm year−1), reducing valuable reef space. Furthermore, our results indicate that high-magnesium calcite is predominantly dissolving in the studied sediments and a drastic reduction in this mineral can be expected on Davis Reef lagoon in the near future, leaving sediments of an altered mineral composition. This study demonstrates that biotic sediment processes will likely not directly be affected by OA. Ensuing indirect effects of OA-induced sediment dissolution on biotic processes are discussed

Temporal dynamics of the default mode network characterise meditation induced alterations in consciousness

Current research suggests that human consciousness is associated with complex, synchronous interactions between multiple cortical networks. In particular, the default mode network (DMN) of the resting brain is thought to be altered by changes in consciousness, including the meditative state. However, it remains unclear how meditation alters the fast and ever-changing dynamics of brain activity within this network. Here we addressed this question using simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to compare the spatial extents and temporal dynamics of the DMN during rest and meditation. Using fMRI, we identified key reductions in the posterior cingulate hub of the DMN, along with increases in right frontal and left temporal areas, in experienced meditators during rest and during meditation, in comparison to healthy controls (HCs). We employed the simultaneously recorded EEG data to identify the topographical microstate corresponding to activation of the DMN. Analysis of the temporal dynamics of this microstate revealed that the average duration and frequency of occurrence of DMN microstate was higher in meditators compared to HCs. Both these temporal parameters increased during meditation, reflecting the state effect of meditation. In particular, we found that the alteration in the duration of the DMN microstate when meditators entered the meditative state correlated negatively with their years of meditation experience. This reflected a trait effect of meditation, highlighting its role in producing durable changes in temporal dynamics of the DMN. Taken together, these findings shed new light on short and long-term consequences of meditation practice on this key brain network

Brain Connectivity Dissociates Responsiveness from Drug Exposure during Propofol-Induced Transitions of Consciousness.

Accurately measuring the neural correlates of consciousness is a grand challenge for neuroscience. Despite theoretical advances, developing reliable brain measures to track the loss of reportable consciousness during sedation is hampered by significant individual variability in susceptibility to anaesthetics. We addressed this challenge using high-density electroencephalography to characterise changes in brain networks during propofol sedation. Assessments of spectral connectivity networks before, during and after sedation were combined with measurements of behavioural responsiveness and drug concentrations in blood. Strikingly, we found that participants who had weaker alpha band networks at baseline were more likely to become unresponsive during sedation, despite registering similar levels of drug in blood. In contrast, phase-amplitude coupling between slow and alpha oscillations correlated with drug concentrations in blood. Our findings highlight novel markers that prognosticate individual differences in susceptibility to propofol and track drug exposure. These advances could inform accurate drug titration and brain state monitoring during anaesthesia.This work was supported by grants from the James S. McDonnell Foundation, the Wellcome Trust [WT093811MA to TAB], and the British Oxygen Professorship from the Royal College of Anaesthetists [to DKM]. The research was also supported by the NIHR Brain Injury Healthcare Technology Co-operative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR or the UK Department of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This is the final version of the article. It was first available from PLOS via http://dx.doi.org/10.1371/journal.pcbi.100466

Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren't.

UNLABELLED: There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called "mismatch response"). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an "omission" response). This situation arguably provides a more direct measure of "top-down" predictions in the absence of confounding "bottom-up" input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG and MEG to an auditory paradigm in which we factorially crossed the presence versus absence of "bottom-up" stimuli with the presence versus absence of "top-down" attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward "prediction" connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction. SIGNIFICANCE STATEMENT: Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known "mismatch response." But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain's electromagnetic activity, we show that it also generates an "omission response" that is contingent on the presence of attention. We model these responses computationally, revealing that mismatch and omission responses only differ in the location of inputs into the same underlying neuronal network. In both cases, we show that attention selectively strengthens the brain's prediction of the future.This work was supported by the UK Medical Research Council Programme [MC-A060-5PR10 to RH], in addition to grants from the Wellcome Trust [WT093811MA to TAB], the James S. McDonnell Foundation, and the Evelyn Trust [15/07 to SC].This is the final version of the article. It first appeared from the Society for Neuroscience via http://dx.doi.org/10.1523/JNEUROSCI.1125-16.201

On Feature Binding in Space and Time

When presented with a yellow Volkswagen and a red Ferrari, how does the brain ?gure out which color goes with which car? The binding problem refers to how the visual system pre-consciously combines visual features of objects in the physical world to create coherent mental equivalents in our consciousness. I discuss why feature binding is a problem for our brains despite its seemingly e?ortless resolution in every-day life. Drawing from experimental cognitive psychology, I demonstrate how it manifests in space and time

Analysis of microseismic events associated with hydraulic fracture propagation

Previous practice to determine the source mechanism of microseismic events associated with hydraulic fracture typically includes only far-field terms in moment tensor inversion. The intermediate-field terms and near-field term are normally ignored because of increased complexity in the calculation. Source-receiver distances in hydraulic fracturing are usually 1000 ft and the effects of near and intermediate-field terms are still unknown. We perform a study to improve the precision of the source mechanism by including the intermediate-field term in moment tensor inversion. We find that the intermediate-field term contributes 1/3 of the signal amplitude when the source-receiver distance is 1000 ft. The intermediate-field term contributes 1/20 of the signal amplitude when the source-receiver distance is 6700 ft. Note that 1/20 is at the noise level. Thus, when source-receiver distance is less than 6700ft, we need to consider the intermediate-field term. Especially, when the distance is 1000ft, the intermediate-field term becomes significant. Similarly, near-field terms contribute less than 1/20 of the signal amplitude when distances are larger than 300 ft. In our case, we confirm that the near-field term can be ignored in microseismic analysis. Our results indicate that the intermediate-field terms can improve moment tensor inversion by 2% to 40% at source-receiver ranges less than 1000 ft. When distances are larger than 6700, the improvement is limited to 1%. In the presence of noise, the intermediate-field terms help to improve the moment tensor inversion (15% improvement with noise present vs 3% improvement without noise). Our study provides a foundation for using intermediate-field terms in moment tensor inversion in the studies of hydraulic fractures

A P300-based cognitive assessment battery

© 2015 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.Background: It is well established that some patients who are diagnosed as being in a vegetative state or a minimally conscious state show reliable signs of volition that may only be detected by measuring neural responses. A pertinent question is whether these patients are capable of higher cognitive processes. Methods: Here, we develop a series of EEG paradigms that probe several core aspects of cognition at the bedside without the need for motor responses and explore the sensitivity of this approach in a group of healthy controls. Results: Using analysis of ERPs alone, this method can determine with high reliability whether individual participants are able to attend a stimulus stream, maintain items in working memory, or solve complex grammatical reasoning problems. Conclusion: We suggest that this approach could form the basis of a brain-based battery for assessing higher cognition in patients with severe motor impairments or disorders of consciousness

A Trillion Coral Reef Colors: Deeply Annotated Underwater Hyperspectral Images for Automated Classification and Habitat Mapping

This paper describes a large dataset of underwater hyperspectral imagery that can be used by researchers in the domains of computer vision, machine learning, remote sensing, and coral reef ecology. We present the details of underwater data acquisition, processing and curation to create this large dataset of coral reef imagery annotated for habitat mapping. A diver-operated hyperspectral imaging system (HyperDiver) was used to survey 147 transects at 8 coral reef sites around the Caribbean island of Curacao. The underwater proximal sensing approach produced fine-scale images of the seafloor, with more than 2.2 billion points of detailed optical spectra. Of these, more than 10 million data points have been annotated for habitat descriptors or taxonomic identity with a total of 47 class labels up to genus- and species-levels. In addition to HyperDiver survey data, we also include images and annotations from traditional (color photo) quadrat surveys conducted along 23 of the 147 transects, which enables comparative reef description between two types of reef survey methods. This dataset promises benefits for efforts in classification algorithms, hyperspectral image segmentation and automated habitat mapping. Dataset: https://doi.org/10.1594/PANGAEA.911300 Dataset License: CC-BY-N

Spectral signatures of reorganised brain networks in disorders of consciousness.

Theoretical advances in the science of consciousness have proposed that it is concomitant with balanced cortical integration and differentiation, enabled by efficient networks of information transfer across multiple scales. Here, we apply graph theory to compare key signatures of such networks in high-density electroencephalographic data from 32 patients with chronic disorders of consciousness, against normative data from healthy controls. Based on connectivity within canonical frequency bands, we found that patient networks had reduced local and global efficiency, and fewer hubs in the alpha band. We devised a novel topographical metric, termed modular span, which showed that the alpha network modules in patients were also spatially circumscribed, lacking the structured long-distance interactions commonly observed in the healthy controls. Importantly however, these differences between graph-theoretic metrics were partially reversed in delta and theta band networks, which were also significantly more similar to each other in patients than controls. Going further, we found that metrics of alpha network efficiency also correlated with the degree of behavioural awareness. Intriguingly, some patients in behaviourally unresponsive vegetative states who demonstrated evidence of covert awareness with functional neuroimaging stood out from this trend: they had alpha networks that were remarkably well preserved and similar to those observed in the controls. Taken together, our findings inform current understanding of disorders of consciousness by highlighting the distinctive brain networks that characterise them. In the significant minority of vegetative patients who follow commands in neuroimaging tests, they point to putative network mechanisms that could support cognitive function and consciousness despite profound behavioural impairment.This work was supported by grants from the Wellcome Trust [WT093811MA to T.B.]; the James S. McDonnell Foundation [to A.M.O. and J.D.P.]; the UK Medical Research Council [U.1055.01.002.00001.01 to A.M.O. and J.D.P.]; the Canada Excellence Research Chairs program [to A.M.O.]; the National Institute for Health Research Cambridge Biomedical Research Centre [to J.D.P.]; and the National Institute for Health Research Senior Investigator and Healthcare Technology Cooperative awards [to J.D.P.].This is the final version of the article. It first appeared from PLOS via http://dx.doi.org