222 research outputs found

    A novel approach to detect hot-spots in large-scale multivariate data

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    Background: Progressive advances in the measurement of complex multifactorial components of biological processes involving both spatial and temporal domains have made it difficult to identify the variables (genes, proteins, neurons etc.) significantly changed activities in response to a stimulus within large data sets using conventional statistical approaches. The set of all changed variables is termed hot-spots. The detection of such hot spots is considered to be an NP hard problem, but by first establishing its theoretical foundation we have been able to develop an algorithm that provides a solution. Results: Our results show that a first-order phase transition is observable whose critical point separates the hot-spot set from the remaining variables. Its application is also found to be more successful than existing approaches in identifying statistically significant hot-spots both with simulated data sets and in real large-scale multivariate data sets from gene arrays, electrophysiological recording and functional magnetic resonance imaging experiments. Conclusion: In summary, this new statistical algorithm should provide a powerful new analytical tool to extract the maximum information from complex biological multivariate data

    A neuronal effect of testosterone

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    This thesis investigates the effects of testosterone and its metabolites on the electrical activity of single corticomedial amygdala neurones in the male rat. Experiments concentrate, in particular, on those corticomedial amygdala neurones which project directly to the medial preoptic/anterior hypothalamic junction. An attempt to relate the observed neuronal effects of testosterone to sexual behaviour has also been made. The first Chapter reviews the electrophysiological experiments on the effects of sex steroids on single neurones in the central and peripheral nervous system. The second Chapter describes experiments which show that long term castration lengthens the absolute refractory periods of corticomedial amygdala neurones which project to the medial preoptlc/anterlor hypothalamic junction. Adjacent corticomedial amygdala neurones which project to the capsule of the ventromedial nucleus of the hypothalamus did not show this effect. Chapter 3 describes an experiment which shows that long term testosterone treatment reduces the absolute refractory periods of corticomedial amygdala neurones which project to the medial preoptlc/anterlor hypothalamic junction, In castrated rats. Results show a direct effect of testosterone In the central nervous system. Chapter k Investigates the effects of two major metabolites of testosterone, oestradlol and dihydrotestosterone, on the absolute refractory periods of these corticomedial amygdala neurones. Oestradlol, but not dihydrotestosterone produces the same reduction effect as testosterone. Results provide direct evidence that oestradlol has the same effect as testosterone In the central nervous system. Chapter 5 describes two similar experiments which show that the testosterone reduction of the absolute refractory periods of these corticomedial amygdala neurones Is correlated with the time at which the hormone stimulates full sexual behaviour. Chapter 6 discusses the significance of the testosterone effect on corticomedial amygdala neurone absolute refractory periods

    Pheromones: The Scent of a Male

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    SummaryThere has been an enduring fascination with discovering biological odours which can evoke behavioral and physiological responses in mammals. New findings in goats have now identified a key molecule involved in the effect male odours have on female reproductive cycles

    Social cognition in sheep: Welfare implications

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    More research has been carried out on social cognition in sheep than in other farm animal species. Although this has often been featured widely in the media, there is still limited public awareness of it. Marino & Merskin’s review is therefore both important and timely. In my commentary, I focus primarily on what has been established about the complexity of sheep social cognition, at the level of both brain and behavior, and on some of these findings for sheep welfare

    The Coronal Analysis of SHocks and Waves (CASHeW) Framework

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    Coronal Bright Fronts (CBF) are large-scale wavelike disturbances in the solar corona, related to solar eruptions. They are observed in extreme ultraviolet (EUV) light as transient bright fronts of finite width, propagating away from the eruption source. Recent studies of individual solar eruptive events have used EUV observations of CBFs and metric radio type II burst observations to show the intimate connection between low coronal waves and coronal mass ejection (CME)-driven shocks. EUV imaging with the Atmospheric Imaging Assembly(AIA) instrument on the Solar Dynamics Observatory (SDO) has proven particularly useful for detecting CBFs, which, combined with radio and in situ observations, holds great promise for early CME-driven shock characterization capability. This characterization can further be automated, and related to models of particle acceleration to produce estimates of particle fluxes in the corona and in the near Earth environment early in events. We present a framework for the Coronal Analysis of SHocks and Waves (CASHeW). It combines analysis of NASA Heliophysics System Observatory data products and relevant data-driven models, into an automated system for the characterization of off-limb coronal waves and shocks and the evaluation of their capability to accelerate solar energetic particles (SEPs). The system utilizes EUV observations and models written in the Interactive Data Language (IDL). In addition, it leverages analysis tools from the SolarSoft package of libraries, as well as third party libraries. We have tested the CASHeW framework on a representative list of coronal bright front events. Here we present its features, as well as initial results. With this framework, we hope to contribute to the overall understanding of coronal shock waves, their importance for energetic particle acceleration, as well as to the better ability to forecast SEP events fluxes.Comment: Accepted for publication in the Journal of Space Weather and Space Climate (SWSC

    Learning alters theta-nested gamma oscillations in inferotemporal cortex

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    How coupled brain rhythms influence cortical information processing to support learning is unresolved. Local field potential and neuronal activity recordings from 64- electrode arrays in sheep inferotemporal cortex showed that visual discrimination learning increased the amplitude of theta oscillations during stimulus presentation. Coupling between theta and gamma oscillations, the theta/gamma ratio and the regularity of theta phase were also increased, but not neuronal firing rates. A neural network model with fast and slow inhibitory interneurons was developed which generated theta nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity similar learning-evoked changes could be produced. The model revealed that altered theta nested gamma could potentiate downstream neuron responses by temporal desynchronization of excitatory neuron output independent of changes in overall firing frequency. This learning-associated desynchronization was also exhibited by inferotemporal cortex neurons. Changes in theta nested gamma may therefore facilitate learning-associated potentiation by temporal modulation of neuronal firing

    Algorithms for FFT Beamforming Radio Interferometers

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    Radio interferometers consisting of identical antennas arranged on a regular lattice permit fast Fourier transform beamforming, which reduces the correlation cost from O(n2)\mathcal{O}(n^2) in the number of antennas to O(nlogn)\mathcal{O}(n\log n). We develop a formalism for describing this process and apply this formalism to derive a number of algorithms with a range of observational applications. These include algorithms for forming arbitrarily pointed tied-array beams from the regularly spaced Fourier-transform formed beams, sculpting the beams to suppress sidelobes while only losing percent-level sensitivity, and optimally estimating the position of a detected source from its observed brightness in the set of beams. We also discuss the effect that correlations in the visibility-space noise, due to cross-talk and sky contributions, have on the optimality of Fourier transform beamforming, showing that it does not strictly preserve the sky information of the n2n^2 correlation, even for an idealized array. Our results have applications to a number of upcoming interferometers, in particular the Canadian Hydrogen Intensity Mapping Experiment--Fast Radio Burst (CHIME/FRB) project.Comment: 17 pages, 4 figures, accepted to Ap

    The fault lies on the other side: altered brain functional connectivity in psychiatric disorders is mainly caused by counterpart regions in the opposite hemisphere

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    Many psychiatric disorders are associated with abnormal resting-state functional connectivity between pairs of brain regions, although it remains unclear whether the fault resides within the pair of regions themselves or other regions connected to them. Identifying the source of dysfunction is crucial for understanding the etiology of different disorders. Using pathway- and network-based techniques to analyze resting-state functional magnetic imaging data from a large population of patients with attention-deficit-hyperactivity-disorder (239 patients, 251 controls), major depression (69 patients, 67 controls) and schizophrenia (169 patients, 162 controls), we show for the first time that only network-based cross-correlation identifies significant functional-connectivity changes in all three disorders which survive correction. This demonstrates that the primary source of dysfunction resides not in the regional pairs themselves but in their external connections. Combining pathway and network-based functional-connectivity analysis we established that in all three disorders, th

    Oxytocin Facilitates Social Learning by Promoting Conformity to Trusted Individuals

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    There is considerable interest in the role of the neuropeptide oxytocin in promoting social cohesion both in terms of promoting specific social bonds and also more generally for increasing our willingness to trust others and/or to conform to their opinions. These latter findings may also be important in the context of a modulatory role for oxytocin in improving the efficacy of behavioral therapy in psychiatric disorders. However, the original landmark studies claiming an important role for oxytocin in enhancing trust in others, primarily using economic game strategies, have been questioned by subsequent meta-analytic approaches or failure to reproduce findings in different contexts. On the other hand, a growing number of studies have consistently reported that oxytocin promotes conformity to the views of groups of in-group individuals. Most recently we have found that oxytocin can increase acceptance of social advice given by individual experts without influencing their perceived trustworthiness per se, but that increased conformity in this context is associated with how much an expert is initially trusted and liked. Oxytocin can also enhance the impact of information given by experts by facilitating expectancy and placebo effects. Here we therefore propose that a key role for oxytocin is not in facilitating social trust per se but in conforming to, and learning from, trusted individuals who are either in-group members and/or perceived experts. The implications of this for social learning and use of oxytocin as an adjunct to behavioral therapy in psychiatric disorders are discussed

    Learning alters theta amplitude, theta-gamma coupling and neuronal synchronization in inferotemporal cortex.

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    BACKGROUND: How oscillatory brain rhythms alone, or in combination, influence cortical information processing to support learning has yet to be fully established. Local field potential and multi-unit neuronal activity recordings were made from 64-electrode arrays in the inferotemporal cortex of conscious sheep during and after visual discrimination learning of face or object pairs. A neural network model has been developed to simulate and aid functional interpretation of learning-evoked changes. RESULTS: Following learning the amplitude of theta (4-8 Hz), but not gamma (30-70 Hz) oscillations was increased, as was the ratio of theta to gamma. Over 75% of electrodes showed significant coupling between theta phase and gamma amplitude (theta-nested gamma). The strength of this coupling was also increased following learning and this was not simply a consequence of increased theta amplitude. Actual discrimination performance was significantly correlated with theta and theta-gamma coupling changes. Neuronal activity was phase-locked with theta but learning had no effect on firing rates or the magnitude or latencies of visual evoked potentials during stimuli. The neural network model developed showed that a combination of fast and slow inhibitory interneurons could generate theta-nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity in the model similar changes were produced as in inferotemporal cortex after learning. The model showed that these changes could potentiate the firing of downstream neurons by a temporal desynchronization of excitatory neuron output without increasing the firing frequencies of the latter. This desynchronization effect was confirmed in IT neuronal activity following learning and its magnitude was correlated with discrimination performance. CONCLUSIONS: Face discrimination learning produces significant increases in both theta amplitude and the strength of theta-gamma coupling in the inferotemporal cortex which are correlated with behavioral performance. A network model which can reproduce these changes suggests that a key function of such learning-evoked alterations in theta and theta-nested gamma activity may be increased temporal desynchronization in neuronal firing leading to optimal timing of inputs to downstream neural networks potentiating their responses. In this way learning can produce potentiation in neural networks simply through altering the temporal pattern of their inputs.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are
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