Complementary Roles of Systems Representing Sensory Evidence and Systems Detecting Task Difficulty During Perceptual Decision Making

Perceptual decision making is a multi-stage process where incoming sensory information is used to select one option from several alternatives. Researchers typically have adopted one of two conceptual frameworks to define the criteria for determining whether a brain region is involved in decision computations. One framework, building on single-unit recordings in monkeys, posits that activity in a region involved in decision making reflects the accumulation of evidence toward a decision threshold, thus showing the lowest level of BOLD signal during the hardest decisions. The other framework instead posits that activity in a decision-making region reflects the difficulty of a decision, thus showing the highest level of BOLD signal during the hardest decisions. We had subjects perform a face detection task on degraded face images while we simultaneously recorded BOLD activity. We searched for brain regions where changes in BOLD activity during this task supported either of these frameworks by calculating the correlation of BOLD activity with reaction time – a measure of task difficulty. We found that the right supplementary eye field, right frontal eye field, and right inferior frontal gyrus had increased activity relative to baseline that positively correlated with reaction time, while the left superior frontal sulcus and left middle temporal gyrus had decreased activity relative to baseline that negatively correlated with reaction time. We propose that a simple mechanism that scales a region's activity based on task demands can explain our results

Effects of forward contour modification on the aerodynamic characteristics of the NACA 641-212 airfoil section

Two different forward contour modifications designed to increase the maximum lift coefficient of the NACA 64 sub 1-212 airfoil section were evaluated experimentally at low speeds. One modification consisted of a slight droop of the leading edge with an increased leading-edge radius; the other modification incorporated increased thickness over the forward 35 percent of the upper surface of the profile. Both modified airfoil sections were found to provide substantially higher maximum lift coefficients than the 64 sub 1-212 section. The drooped leading-edge modification incurred a drag penalty of approximately 10 percent at low and moderate lift coefficients and exhibited a greater nosedown pitching moment than the 64 sub 1-212 profile. The upper surface modification produced about the same drag level as the 64 sub 1-212 section at low and moderate lift coefficients and less nosedown pitching moment than the 64 sub 1-212 profile. Both modified airfoil sections had lower drag coefficients than the 64 sub 1-212 section at high lift coefficients

Laboratory diagnosis of Streptococcus pneumoniae infections: past and future

Streptococcus pneumoniae is one of the most important causative agent of pneumonia, meningitis, bacteremia, sinusitis and otitis media. The gold standard diagnostic method is still culture evenif bacteriological diagnosis is making progress in molecular biol- ogy and in proteomics areas. The full article is free available on www.jpmh.or

Knowing what you know in brain segmentation using Bayesian deep neural networks

In this paper, we describe a Bayesian deep neural network (DNN) for predicting FreeSurfer segmentations of structural MRI volumes, in minutes rather than hours. The network was trained and evaluated on a large dataset (n = 11,480), obtained by combining data from more than a hundred different sites, and also evaluated on another completely held-out dataset (n = 418). The network was trained using a novel spike-and-slab dropout-based variational inference approach. We show that, on these datasets, the proposed Bayesian DNN outperforms previously proposed methods, in terms of the similarity between the segmentation predictions and the FreeSurfer labels, and the usefulness of the estimate uncertainty of these predictions. In particular, we demonstrated that the prediction uncertainty of this network at each voxel is a good indicator of whether the network has made an error and that the uncertainty across the whole brain can predict the manual quality control ratings of a scan. The proposed Bayesian DNN method should be applicable to any new network architecture for addressing the segmentation problem.Comment: Submitted to Frontiers in Neuroinformatic

Maintenance of therapeutic concentrations of micafungin administered 5 days/week in a leukemic adolescent with invasive candidiasis

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Human hippocampal processing of environmental novelty during spatial navigation.

The detection and processing of novel information encountered as we explore our environment is crucial for learning and adaptive behavior. The human hippocampus has been strongly implicated in laboratory tests of novelty detection and episodic memory, but has been less well studied during more ethological tasks such as spatial navigation, typically used in animals. We examined fMRI BOLD activity as a function of environmental and object novelty as humans performed an object-location virtual navigation task. We found greater BOLD response to novel relative to familiar environments in the hippocampus and adjacent parahippocampal gyrus. Object novelty was associated with increased activity in the posterior parahippocampal/fusiform gyrus and anterior hippocampus extending into the amygdala and superior temporal sulcus. Importantly, whilst mid-posterior hippocampus was more sensitive to environmental novelty than object novelty, the anterior hippocampus responded similarly to both forms of novelty. By investigating how participants learn and utilize different forms of information during spatial navigation, we found that MTL activity reflects both the novelty of the environment and of the object located within it. Crucially, this novelty processing is likely supported by distinct, but partially overlapping, sets of regions within the MTL. © 2014 Wiley Periodicals, Inc

Performance of the galactomannan antigen detection test in the diagnosis of invasive aspergillosis in children with cancer or undergoing haemopoietic stem cell transplantation

AbstractSerum galactomannan (GM) antigen detection is not recommended for defining invasive aspergillosis (IA) in children undergoing aggressive chemotherapy or allogeneic haemopoietic stem cell transplantation (HSCT). The ability of the GM test to identify IA in children was retrospectively evaluated in a cohort of children. Test performance was evaluated on samples that were collected during 195 periods at risk of IA. Proven IA was diagnosed in seven periods, all with positive GM test results (true positives, 4%), and possible IA was diagnosed in 15 periods, all with negative GM test results (false negatives, 8%). The test result was positive with negative microbiological, histological and clinical features in three periods (false positives, 1%), and in 170 periods it was negative with negative microbiological, histological and clinical features (true negatives, 87%). The sensitivity was 0.32 and the specificity was 0.98; the positive predictive value was 0.70 and the negative predictive value was 0.92. The efficiency of the test was 0.91, the positive likelihood ratio was 18.3, and the negative likelihood ratio was 1.4. The probability of missing an IA because of a negative test result was 0.03. Test performance proved to be better during at-risk periods following chemotherapy than in periods following allogeneic HSCT. The GM assay is useful for identifying periods of IA in children undergoing aggressive chemotherapy or allogeneic HSCT

Movement-related theta rhythm in humans: coordinating self-directed hippocampal learning.

The hippocampus is crucial for episodic or declarative memory and the theta rhythm has been implicated in mnemonic processing, but the functional contribution of theta to memory remains the subject of intense speculation. Recent evidence suggests that the hippocampus might function as a network hub for volitional learning. In contrast to human experiments, electrophysiological recordings in the hippocampus of behaving rodents are dominated by theta oscillations reflecting volitional movement, which has been linked to spatial exploration and encoding. This literature makes the surprising cross-species prediction that the human hippocampal theta rhythm supports memory by coordinating exploratory movements in the service of self-directed learning. We examined the links between theta, spatial exploration, and memory encoding by designing an interactive human spatial navigation paradigm combined with multimodal neuroimaging. We used both non-invasive whole-head Magnetoencephalography (MEG) to look at theta oscillations and Functional Magnetic Resonance Imaging (fMRI) to look at brain regions associated with volitional movement and learning. We found that theta power increases during the self-initiation of virtual movement, additionally correlating with subsequent memory performance and environmental familiarity. Performance-related hippocampal theta increases were observed during a static pre-navigation retrieval phase, where planning for subsequent navigation occurred. Furthermore, periods of the task showing movement-related theta increases showed decreased fMRI activity in the parahippocampus and increased activity in the hippocampus and other brain regions that strikingly overlap with the previously observed volitional learning network (the reverse pattern was seen for stationary periods). These fMRI changes also correlated with participant's performance. Our findings suggest that the human hippocampal theta rhythm supports memory by coordinating exploratory movements in the service of self-directed learning. These findings directly extend the role of the hippocampus in spatial exploration in rodents to human memory and self-directed learning