587 resultados para BRAIN NETWORKS


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Many of the 5,500 threatened species of vertebrates found worldwide are highly protected and generally unavailable for scientific investigation. Here we describe a noninvasive protocol to visualize the structure and size of brain in postmortem specimens. We demonstrate its utility by examining four endangered species of kiwi (Apteryx spp.). Frozen specimens are thawed and imaged using MRI, revealing internal details of brain structure. External brain morphology and an estimate of brain volume can be reliably obtained by creating 3D models. This method has facilitated a comparison of brain structure in the different kiwi species, one of which is on the brink of extinction. This new approach has the potential to extend our knowledge of brain structure to species that have until now been outside the reach of anatomical investigation.

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Time-expanded and heterodyned echolocation calls of the New Zealand long-tailed Chalinolobus tuberculatus and lesser short-tailed bat Mystacina tuberculata were recorded and digitally analysed. Temporal and spectral parameters were measured from time-expanded calls and power spectra generated for both time-expanded and heterodyned calls. Artificial neural networks were trained to classify the calls of both species using temporal and spectral parameters and power spectra as input data. Networks were then tested using data not previously seen. Calls could be unambiguously identified using parameters and power spectra from time-expanded calls. A neural network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 40 kHz (the frequency with the most energy of the fundamental of C. tuberculatus call), could identify 99% and 84% of calls of C. tuberculatus and M. tuberculata, respectively. A second network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 27 kHz (the frequency with the most energy of the fundamental of M. tuberculata call), could identify 34% and 100% of calls of C. tuberculatus and M. tuberculata, respectively. This study represents the first use of neural networks for the identification of bats from their echolocation calls. It is also the first study to use power spectra of time-expanded and heterodyned calls for identification of chiropteran species. The ability of neural networks to identify bats from their echolocation calls is discussed, as is the ecology of both species in relation to the design of their echolocation calls.

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We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

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Background: Adults with primary brain tumors and their caregivers have significant information needs. This review assessed the effect of interventions to improve information provision for adult primary brain tumor patients and/or their caregivers. Methods: We included randomized or nonrandomized trials testing educational interventions that had outcomes of information provision, knowledge, understanding, recall, or satisfaction with the intervention, for adults diagnosed with primary brain tumors and/or their family or caregivers. PubMed, MEDLINE, EMBASE and Cochrane Reviews databases were searched for studies published between 1980 and June 2014. Results: Two randomized controlled, one non-randomized controlled, and 10 single group pre-post trials enrolled more than 411 participants. Five group, four practice/process change and four individual interventions assessed satisfaction (12 studies), knowledge (four studies) or information provision (2 studies). Nine studies reported high rates of satisfaction. Three studies showed statistically significant improvements over time in knowledge and two showed greater information was provided to intervention than control group participants, although statistical testing was not performed. Discussion: The trials assessed intermediate outcomes such as satisfaction, and only 4/13 reported on knowledge improvements. Few trials had a randomized controlled design and risk of bias was either evident or could not be assessed in most domains.

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This chapter presents the stability analysis based on bifurcation theory of the distribution static compensator (DSTATCOM) operating both in current control mode as in voltage control mode. The bifurcation analysis allows delimiting the operating zones of nonlinear power systems and hence the computation of these boundaries is of interest for practical design and planning purposes. Suitable mathematical representations of the DSTATCOM are proposed to carry out the bifurcation analyses efficiently. The stability regions in the Thevenin equivalent plane are computed for different power factors at the Point of Common Coupling (PCC). In addition, the stability regions in the control gain space are computed, and the DC capacitor and AC capacitor impact on the stability are analyzed in detail. It is shown through bifurcation analysis that the loss of stability in the DSTATCOM is in general due to the emergence of oscillatory dynamics. The observations are verified through detailed simulation studies.

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In this work, we present the challenges associated with the two-way recommendation methods in social networks and the solutions. We discuss them from the perspective of community-type social networks such as online dating networks.

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Objective: This study investigated the influence of injury cause, contact-sport participation, and prior knowledge of mild traumatic brain injury (mTBI) on injury beliefs and chronic symptom expectations of mTBI. Method: A total of 185 non-contact-sport players (non-CSPs) and 59 contact-sport players (CSPs) with no history of mTBI were randomly allocated to one of two conditions in which they read either a vignette depicting a sport-related mTBI (mTBIsport) or a motor-vehicle-accident-related mTBI (mTBIMVA). The vignettes were otherwise standardized to convey the same injury parameters (e.g., duration of loss of consciousness). After reading a vignette, participants reported their injury beliefs (i.e., perceptions of injury undesirability, chronicity, and consequences) and their expectations of chronic postconcussion syndrome (PCS) and posttraumatic stress disorder (PTSD) symptoms. Results: Non-CSPs held significantly more negative beliefs and expected greater PTSD symptomatology and greater PCS affective symptomatology from an mTBIMVA vignette thann mTBIsport vignette, but this difference was not found for CSPs. Unlike CSPs, non-CSPs who personally knew someone who had sustained an mTBI expected significantly less PCS symptomatology than those who did not. Despite these different results for non-CSPs and CSPs, overall, contact-sport participation did not significantly affect injury beliefs and symptom expectations from an mTBIsport. Conclusions: Expectations of persistent problems after an mTBI are influenced by factors such as injury cause even when injury parameters are held constant. Personal knowledge of mTBI, but not contact sport participation, may account for some variability in mTBI beliefs and expectations. These factors require consideration when assessing mTBI outcome.

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Objective: To formally evaluate the written discharge advice for people with mild traumatic brain injury (mTBI). Methods: Eleven publications met the inclusion criteria: (1) intended for adults; (2) ≤two A4 pages; (3) published in English; (4) freely accessible; and (5) currently used (or suitable for use) in Australian hospital emergency departments or similar settings. Two independent raters evaluated the content and style of each publication against established standards. The readability of the publication, the diagnostic term(s) contained in it and a modified Patient Literature Usefulness Index (mPLUI) were also evaluated. Results: The mean content score was 19.18 ± 8.53 (maximum = 31) and the mean style score was 6.8 ± 1.34 (maximum = 8). The mean Flesch-Kincaid reading ease score was 66.42 ± 4.3. The mean mPLUI score was 65.86 ± 14.97 (maximum = 100). Higher scores on these metrics indicate more desirable properties. Over 80% of the publications used mixed diagnostic terminology. One publication scored optimally on two of the four metrics and highly on the others. Discussion: The content, style, readability and usefulness of written mTBI discharge advice was highly variable. The provision of written information to patients with mTBI is advised, but this variability in materials highlights the need for evaluation before distribution. Areas are identified to guide the improvement of written mTBI discharge advice.