21 research outputs found

    Improvements in Spelling after QEEG-based Neurofeedback in Dyslexia: A Randomized Controlled Treatment Study

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    Phonological theories of dyslexia assume a specific deficit in representation, storage and recall of phonemes. Various brain imaging techniques, including qEEG, point to the importance of a range of areas, predominantly the left hemispheric temporal areas. This study attempted to reduce reading and spelling deficits in children who are dyslexic by means of neurofeedback training based on neurophysiological differences between the participants and gender and age matched controls. Nineteen children were randomized into an experimental group receiving qEEG based neurofeedback (n = 10) and a control group (n = 9). Both groups also received remedial teaching. The experimental group improved considerably in spelling (Cohen’s d = 3). No improvement was found in reading. An indepth study of the changes in the qEEG power and coherence protocols evidenced no fronto-central changes, which is in line with the absence of reading improvements. A significant increase of alpha coherence was found, which may be an indication that attentional processes account for the improvement in spelling. Consideration of subtypes of dyslexia may refine the results of future studies

    A temporal dimension to the influence of pollen rewards on bee behaviour and fecundity in Aloe tenuior

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    The net effect of pollen production on fecundity in plants can range from negative – when self-pollen interferes with fecundity due to incompatibility mechanisms, to positive – when pollen availability is associated with increased pollinator visitation and fecundity due to its utilization as a reward. We investigated the responses of bees to pollen and nectar rewards, and the effects of these rewards on pollen deposition and fecundity in the hermaphroditic succulent shrub Aloe tenuior. Self-pollinated plants failed to set fruit, but their ovules were regularly penetrated by self-pollen tubes, which uniformly failed to develop into seeds as expected from ovarian self-incompatibility (or strong early inbreeding depression). Bees consistently foraged for pollen during the morning and early afternoon, but switched to nectar in the late afternoon. As a consequence of this differential foraging, we were able to test the relative contribution to fecundity of pollen- versus nectar-collecting flower visitors. We exposed emasculated and intact flowers in either the morning or late afternoon to foraging bees and showed that emasculation reduced pollen deposition by insects in the morning, but had little effect in the afternoon. Despite the potential for self-pollination to result in ovule discounting due to late-acting self-sterility, fecundity was severely reduced in artificially emasculated plants. Although there were temporal fluctuations in reward preference, most bee visits were for pollen rewards. Therefore the benefit of providing pollen that is accessible to bee foragers outweighs any potential costs to fitness in terms of gender interference in this species

    The integration of occlusion and disparity information for judging depth in autism spectrum disorder

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    In autism spectrum disorder (ASD), atypical integration of visual depth cues may be due to flattened perceptual priors or selective fusion. The current study attempts to disentangle these explanations by psychophysically assessing within-modality integration of ordinal (occlusion) and metric (disparity) depth cues while accounting for sensitivity to stereoscopic information. Participants included 22 individuals with ASD and 23 typically developing matched controls. Although adults with ASD were found to have significantly poorer stereoacuity, they were still able to automatically integrate conflicting depth cues, lending support to the idea that priors are intact in ASD. However, dissimilarities in response speed variability between the ASD and TD groups suggests that there may be differences in the perceptual decision-making aspect of the task

    Visual Scan Paths and Recognition of Facial Identity in Autism Spectrum Disorder and Typical Development

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    Background: Previous research suggests that many individuals with autism spectrum disorder (ASD) have impaired facial identity recognition, and also exhibit abnormal visual scanning of faces. Here, two hypotheses accounting for an association between these observations were tested: i) better facial identity recognition is associated with increased gaze time on the Eye region; ii) better facial identity recognition is associated with increased eye-movements around the face. Methodology and Principal Findings: Eye-movements of 11 children with ASD and 11 age-matched typically developing (TD) controls were recorded whilst they viewed a series of faces, and then completed a two alternative forced-choice recognition memory test for the faces. Scores on the memory task were standardized according to age. In both groups, there was no evidence of an association between the proportion of time spent looking at the Eye region of faces and age-standardized recognition performance, thus the first hypothesis was rejected. However, the 'Dynamic Scanning Index' - which was incremented each time the participant saccaded into and out of one of the core-feature interest areas - was strongly asso ciated with age-standardized face recognition scores in both groups, even after controlling for various other potential predictors of performance. Conclusions and Significance: In support of the second hypothesis, results suggested that increased saccading between core-features was associated with more accurate face recognition ability, both in typical development and ASD. Causal directions of this relationship remain undetermined.10 page(s

    Genomic comparisons reveal biogeographic and anthropogenic impacts in the koala (Phascolarctos cinereus): a dietary-specialist species distributed across heterogeneous environments

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    The Australian koala is an iconic marsupial with highly specific dietary requirements distributed across heterogeneous environments, over a large geographic range. The distribution and genetic structure of koala populations has been heavily influenced by human actions, specifically habitat modification, hunting and translocation of koalas. There is currently limited information on population diversity and gene flow at a species-wide scale, or with consideration to the potential impacts of local adaptation. Using species-wide sampling across heterogeneous environments, and high-density genome-wide markers (SNPs and PAVs), we show that most koala populations display levels of diversity comparable to other outbred species, except for those populations impacted by population reductions. Genetic clustering analysis and phylogenetic reconstruction reveals a lack of support for current taxonomic classification of three koala subspecies, with only a single evolutionary significant unit supported. Furthermore, similar to 70% of genetic variance is accounted for at the individual level. The Sydney Basin region is highlighted as a unique reservoir of genetic diversity, having higher diversity levels (i.e., Blue Mountains region; AvHe(corr)-0.20, PL% = 68.6). Broad-scale population differentiation is primarily driven by an isolation by distance genetic structure model (49% of genetic variance), with clinal local adaptation corresponding to habitat bioregions. Signatures of selection were detected between bioregions, with no single region returning evidence of strong selection. The results of this study show that although the koala is widely considered to be a dietary-specialist species, this apparent specialisation has not limited the koala's ability to maintain gene flow and adapt across divergent environments as long as the required food source is available

    Data-driven design of metal-organic frameworks for wet flue gas CO2 capture.

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    Limiting the increase of CO2 in the atmosphere is one of the largest challenges of our generation1. Because carbon capture and storage is one of the few viable technologies that can mitigate current CO2 emissions2, much effort is focused on developing solid adsorbents that can efficiently capture CO2 from flue gases emitted from anthropogenic sources3. One class of materials that has attracted considerable interest in this context is metal-organic frameworks (MOFs), in which the careful combination of organic ligands with metal-ion nodes can, in principle, give rise to innumerable structurally and chemically distinct nanoporous MOFs. However, many MOFs that are optimized for the separation of CO2 from nitrogen4-7 do not perform well when using realistic flue gas that contains water, because water competes with CO2 for the same adsorption sites and thereby causes the materials to lose their selectivity. Although flue gases can be dried, this renders the capture process prohibitively expensive8,9. Here we show that data mining of a computational screening library of over 300,000 MOFs can identify different classes of strong CO2-binding sites-which we term 'adsorbaphores'-that endow MOFs with CO2/N2 selectivity that persists in wet flue gases. We subsequently synthesized two water-stable MOFs containing the most hydrophobic adsorbaphore, and found that their carbon-capture performance is not affected by water and outperforms that of some commercial materials. Testing the performance of these MOFs in an industrial setting and consideration of the full capture process-including the targeted CO2 sink, such as geological storage or serving as a carbon source for the chemical industry-will be necessary to identify the optimal separation material
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