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Pubmed Article
Quantifying extinction probabilities from sighting records: inference and uncertainties.
PLoS ONE
PUBLISHED: 01-01-2014
Methods are needed to estimate the probability that a population is extinct, whether to underpin decisions regarding the continuation of a invasive species eradication program, or to decide whether further searches for a rare and endangered species could be warranted. Current models for inferring extinction probability based on sighting data typically assume a constant or declining sighting rate. We develop methods to analyse these models in a Bayesian framework to estimate detection and survival probabilities of a population conditional on sighting data. We note, however, that the assumption of a constant or declining sighting rate may be hard to justify, especially for incursions of invasive species with potentially positive population growth rates. We therefore explored introducing additional process complexity via density-dependent survival and detection probabilities, with population density no longer constrained to be constant or decreasing. These models were applied to sparse carcass discoveries associated with the recent incursion of the European red fox (Vulpes vulpes) into Tasmania, Australia. While a simple model provided apparently precise estimates of parameters and extinction probability, estimates arising from the more complex model were much more uncertain, with the sparse data unable to clearly resolve the underlying population processes. The outcome of this analysis was a much higher possibility of population persistence. We conclude that if it is safe to assume detection and survival parameters are constant, then existing models can be readily applied to sighting data to estimate extinction probability. If not, methods reliant on these simple assumptions are likely overstating their accuracy, and their use to underpin decision-making potentially fraught. Instead, researchers will need to more carefully specify priors about possible population processes.
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Published: 11-02-2012
ABSTRACT
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
25 Related JoVE Articles!
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Flying Insect Detection and Classification with Inexpensive Sensors
Authors: Yanping Chen, Adena Why, Gustavo Batista, Agenor Mafra-Neto, Eamonn Keogh.
Institutions: University of California, Riverside, University of California, Riverside, University of São Paulo - USP, ISCA Technologies.
An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect’s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.
Bioengineering, Issue 92, flying insect detection, automatic insect classification, pseudo-acoustic optical sensors, Bayesian classification framework, flight sound, circadian rhythm
52111
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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Authors: Nikki M. Curthoys, Michael J. Mlodzianoski, Dahan Kim, Samuel T. Hess.
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
50680
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Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Authors: C. R. Gallistel, Fuat Balci, David Freestone, Aaron Kheifets, Adam King.
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
51047
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A New Approach for the Comparative Analysis of Multiprotein Complexes Based on 15N Metabolic Labeling and Quantitative Mass Spectrometry
Authors: Kerstin Trompelt, Janina Steinbeck, Mia Terashima, Michael Hippler.
Institutions: University of Münster, Carnegie Institution for Science.
The introduced protocol provides a tool for the analysis of multiprotein complexes in the thylakoid membrane, by revealing insights into complex composition under different conditions. In this protocol the approach is demonstrated by comparing the composition of the protein complex responsible for cyclic electron flow (CEF) in Chlamydomonas reinhardtii, isolated from genetically different strains. The procedure comprises the isolation of thylakoid membranes, followed by their separation into multiprotein complexes by sucrose density gradient centrifugation, SDS-PAGE, immunodetection and comparative, quantitative mass spectrometry (MS) based on differential metabolic labeling (14N/15N) of the analyzed strains. Detergent solubilized thylakoid membranes are loaded on sucrose density gradients at equal chlorophyll concentration. After ultracentrifugation, the gradients are separated into fractions, which are analyzed by mass-spectrometry based on equal volume. This approach allows the investigation of the composition within the gradient fractions and moreover to analyze the migration behavior of different proteins, especially focusing on ANR1, CAS, and PGRL1. Furthermore, this method is demonstrated by confirming the results with immunoblotting and additionally by supporting the findings from previous studies (the identification and PSI-dependent migration of proteins that were previously described to be part of the CEF-supercomplex such as PGRL1, FNR, and cyt f). Notably, this approach is applicable to address a broad range of questions for which this protocol can be adopted and e.g. used for comparative analyses of multiprotein complex composition isolated from distinct environmental conditions.
Microbiology, Issue 85, Sucrose density gradients, Chlamydomonas, multiprotein complexes, 15N metabolic labeling, thylakoids
51103
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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Authors: Johannes Felix Buyel, Rainer Fischer.
Institutions: RWTH Aachen University, Fraunhofer Gesellschaft.
Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.
Bioengineering, Issue 83, design of experiments (DoE), transient protein expression, plant-derived biopharmaceuticals, promoter, 5'UTR, fluorescent reporter protein, model building, incubation conditions, monoclonal antibody
51216
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Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning
Authors: Sarah Starosta, Maik C. Stüttgen, Onur Güntürkün.
Institutions: Ruhr-University Bochum.
While the subject of learning has attracted immense interest from both behavioral and neural scientists, only relatively few investigators have observed single-neuron activity while animals are acquiring an operantly conditioned response, or when that response is extinguished. But even in these cases, observation periods usually encompass only a single stage of learning, i.e. acquisition or extinction, but not both (exceptions include protocols employing reversal learning; see Bingman et al.1 for an example). However, acquisition and extinction entail different learning mechanisms and are therefore expected to be accompanied by different types and/or loci of neural plasticity. Accordingly, we developed a behavioral paradigm which institutes three stages of learning in a single behavioral session and which is well suited for the simultaneous recording of single neurons' action potentials. Animals are trained on a single-interval forced choice task which requires mapping each of two possible choice responses to the presentation of different novel visual stimuli (acquisition). After having reached a predefined performance criterion, one of the two choice responses is no longer reinforced (extinction). Following a certain decrement in performance level, correct responses are reinforced again (reacquisition). By using a new set of stimuli in every session, animals can undergo the acquisition-extinction-reacquisition process repeatedly. Because all three stages of learning occur in a single behavioral session, the paradigm is ideal for the simultaneous observation of the spiking output of multiple single neurons. We use pigeons as model systems, but the task can easily be adapted to any other species capable of conditioned discrimination learning.
Neuroscience, Issue 88, pigeon, single unit recording, learning, memory, extinction, spike sorting, operant conditioning, reward, electrophysiology, animal cognition, model species
51283
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
51673
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Cortical Source Analysis of High-Density EEG Recordings in Children
Authors: Joe Bathelt, Helen O'Reilly, Michelle de Haan.
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.  In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis. 
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials 
51705
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Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
Authors: Eva Wagner, Sören Brandenburg, Tobias Kohl, Stephan E. Lehnart.
Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.
In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.
Bioengineering, Issue 92, cardiac myocyte, atria, ventricle, heart, primary cell isolation, fluorescence microscopy, membrane tubule, transverse-axial tubule system, image analysis, image processing, T-tubule, collagenase
51823
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Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae
Authors: Melissa N. Patterson, Patrick H. Maxwell.
Institutions: Rensselaer Polytechnic Institute.
Saccharomyces cerevisiae has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this yeast model is relevant to many organisms, including humans, since DNA repair and DNA damage response factors are well conserved across diverse species. However, S. cerevisiae has not yet been used to fully address whether the rate of accumulating mutations changes with increasing replicative (mitotic) age due to technical constraints. For instance, measurements of yeast replicative lifespan through micromanipulation involve very small populations of cells, which prohibit detection of rare mutations. Genetic methods to enrich for mother cells in populations by inducing death of daughter cells have been developed, but population sizes are still limited by the frequency with which random mutations that compromise the selection systems occur. The current protocol takes advantage of magnetic sorting of surface-labeled yeast mother cells to obtain large enough populations of aging mother cells to quantify rare mutations through phenotypic selections. Mutation rates, measured through fluctuation tests, and mutation frequencies are first established for young cells and used to predict the frequency of mutations in mother cells of various replicative ages. Mutation frequencies are then determined for sorted mother cells, and the age of the mother cells is determined using flow cytometry by staining with a fluorescent reagent that detects bud scars formed on their cell surfaces during cell division. Comparison of predicted mutation frequencies based on the number of cell divisions to the frequencies experimentally observed for mother cells of a given replicative age can then identify whether there are age-related changes in the rate of accumulating mutations. Variations of this basic protocol provide the means to investigate the influence of alterations in specific gene functions or specific environmental conditions on mutation accumulation to address mechanisms underlying genome instability during replicative aging.
Microbiology, Issue 92, Aging, mutations, genome instability, Saccharomyces cerevisiae, fluctuation test, magnetic sorting, mother cell, replicative aging
51850
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A Procedure to Observe Context-induced Renewal of Pavlovian-conditioned Alcohol-seeking Behavior in Rats
Authors: Jean-Marie Maddux, Franca Lacroix, Nadia Chaudhri.
Institutions: Concordia University.
Environmental contexts in which drugs of abuse are consumed can trigger craving, a subjective Pavlovian-conditioned response that can facilitate drug-seeking behavior and prompt relapse in abstinent drug users. We have developed a procedure to study the behavioral and neural processes that mediate the impact of context on alcohol-seeking behavior in rats. Following acclimation to the taste and pharmacological effects of 15% ethanol in the home cage, male Long-Evans rats receive Pavlovian discrimination training (PDT) in conditioning chambers. In each daily (Mon-Fri) PDT session, 16 trials each of two different 10 sec auditory conditioned stimuli occur. During one stimulus, the CS+, 0.2 ml of 15% ethanol is delivered into a fluid port for oral consumption. The second stimulus, the CS-, is not paired with ethanol. Across sessions, entries into the fluid port during the CS+ increase, whereas entries during the CS- stabilize at a lower level, indicating that a predictive association between the CS+ and ethanol is acquired. During PDT each chamber is equipped with a specific configuration of visual, olfactory and tactile contextual stimuli. Following PDT, extinction training is conducted in the same chamber that is now equipped with a different configuration of contextual stimuli. The CS+ and CS- are presented as before, but ethanol is withheld, which causes a gradual decline in port entries during the CS+. At test, rats are placed back into the PDT context and presented with the CS+ and CS- as before, but without ethanol. This manipulation triggers a robust and selective increase in the number of port entries made during the alcohol predictive CS+, with no change in responding during the CS-. This effect, referred to as context-induced renewal, illustrates the powerful capacity of contexts associated with alcohol consumption to stimulate alcohol-seeking behavior in response to Pavlovian alcohol cues.
Behavior, Issue 91, Behavioral neuroscience, alcoholism, relapse, addiction, Pavlovian conditioning, ethanol, reinstatement, discrimination, conditioned approach
51898
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Test Samples for Optimizing STORM Super-Resolution Microscopy
Authors: Daniel J. Metcalf, Rebecca Edwards, Neelam Kumarswami, Alex E. Knight.
Institutions: National Physical Laboratory.
STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy techniques. However, as the image is acquired in a very different way than normal, by building up an image molecule-by-molecule, there are some significant challenges for users in trying to optimize their image acquisition. In order to aid this process and gain more insight into how STORM works we present the preparation of 3 test samples and the methodology of acquiring and processing STORM super-resolution images with typical resolutions of between 30-50 nm. By combining the test samples with the use of the freely available rainSTORM processing software it is possible to obtain a great deal of information about image quality and resolution. Using these metrics it is then possible to optimize the imaging procedure from the optics, to sample preparation, dye choice, buffer conditions, and image acquisition settings. We also show examples of some common problems that result in poor image quality, such as lateral drift, where the sample moves during image acquisition and density related problems resulting in the 'mislocalization' phenomenon.
Molecular Biology, Issue 79, Genetics, Bioengineering, Biomedical Engineering, Biophysics, Basic Protocols, HeLa Cells, Actin Cytoskeleton, Coated Vesicles, Receptor, Epidermal Growth Factor, Actins, Fluorescence, Endocytosis, Microscopy, STORM, super-resolution microscopy, nanoscopy, cell biology, fluorescence microscopy, test samples, resolution, actin filaments, fiducial markers, epidermal growth factor, cell, imaging
50579
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Setting Limits on Supersymmetry Using Simplified Models
Authors: Christian Gütschow, Zachary Marshall.
Institutions: University College London, CERN, Lawrence Berkeley National Laboratories.
Experimental limits on supersymmetry and similar theories are difficult to set because of the enormous available parameter space and difficult to generalize because of the complexity of single points. Therefore, more phenomenological, simplified models are becoming popular for setting experimental limits, as they have clearer physical interpretations. The use of these simplified model limits to set a real limit on a concrete theory has not, however, been demonstrated. This paper recasts simplified model limits into limits on a specific and complete supersymmetry model, minimal supergravity. Limits obtained under various physical assumptions are comparable to those produced by directed searches. A prescription is provided for calculating conservative and aggressive limits on additional theories. Using acceptance and efficiency tables along with the expected and observed numbers of events in various signal regions, LHC experimental results can be recast in this manner into almost any theoretical framework, including nonsupersymmetric theories with supersymmetry-like signatures.
Physics, Issue 81, high energy physics, particle physics, Supersymmetry, LHC, ATLAS, CMS, New Physics Limits, Simplified Models
50419
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Characterization of Surface Modifications by White Light Interferometry: Applications in Ion Sputtering, Laser Ablation, and Tribology Experiments
Authors: Sergey V. Baryshev, Robert A. Erck, Jerry F. Moore, Alexander V. Zinovev, C. Emil Tripa, Igor V. Veryovkin.
Institutions: Argonne National Laboratory, Argonne National Laboratory, MassThink LLC.
In materials science and engineering it is often necessary to obtain quantitative measurements of surface topography with micrometer lateral resolution. From the measured surface, 3D topographic maps can be subsequently analyzed using a variety of software packages to extract the information that is needed. In this article we describe how white light interferometry, and optical profilometry (OP) in general, combined with generic surface analysis software, can be used for materials science and engineering tasks. In this article, a number of applications of white light interferometry for investigation of surface modifications in mass spectrometry, and wear phenomena in tribology and lubrication are demonstrated. We characterize the products of the interaction of semiconductors and metals with energetic ions (sputtering), and laser irradiation (ablation), as well as ex situ measurements of wear of tribological test specimens. Specifically, we will discuss: Aspects of traditional ion sputtering-based mass spectrometry such as sputtering rates/yields measurements on Si and Cu and subsequent time-to-depth conversion. Results of quantitative characterization of the interaction of femtosecond laser irradiation with a semiconductor surface. These results are important for applications such as ablation mass spectrometry, where the quantities of evaporated material can be studied and controlled via pulse duration and energy per pulse. Thus, by determining the crater geometry one can define depth and lateral resolution versus experimental setup conditions. Measurements of surface roughness parameters in two dimensions, and quantitative measurements of the surface wear that occur as a result of friction and wear tests. Some inherent drawbacks, possible artifacts, and uncertainty assessments of the white light interferometry approach will be discussed and explained.
Materials Science, Issue 72, Physics, Ion Beams (nuclear interactions), Light Reflection, Optical Properties, Semiconductor Materials, White Light Interferometry, Ion Sputtering, Laser Ablation, Femtosecond Lasers, Depth Profiling, Time-of-flight Mass Spectrometry, Tribology, Wear Analysis, Optical Profilometry, wear, friction, atomic force microscopy, AFM, scanning electron microscopy, SEM, imaging, visualization
50260
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A Procedure for Studying the Footshock-Induced Reinstatement of Cocaine Seeking in Laboratory Rats
Authors: David A. Kupferschmidt, Zenya J. Brown, Suzanne Erb.
Institutions: University of Toronto Scarborough.
The most insidious aspect of drug addiction is the high propensity for relapse. Animal models of relapse, known as reinstatement procedures, have been used extensively to study the neurobiology and phenomenology of relapse to drug use. Although procedural variations have emerged over the past several decades, the most conventional reinstatement procedures are based on the drug self-administration (SA) model. In this model, an animal is trained to perform an operant response to obtain drug. Subsequently, the behavior is extinguished by withholding response-contingent reinforcement. Reinstatement of drug seeking is then triggered by a discrete event, such as an injection of the training drug, re-exposure to drug-associated cues, or exposure to a stressor 1. Reinstatement procedures were originally developed to study the ability of acute non-contingent exposure to the training drug to reinstate drug seeking in rats and monkeys 1, 2. Reinstatement procedures have since been modified to study the role of environmental stimuli, including drug-associated cues and exposure to various forms of stress, in relapse to drug seeking 1, 3, 4. Over the past 15 years, a major focus of the reinstatement literature has been on the role of stress in drug relapse. One of the most commonly used forms of stress for studying this relationship is acute exposures to mild, intermittent, electric footshocks. The ability of footshock stress to induce reinstatement of drug seeking was originally demonstrated by Shaham and colleagues (1995) in rats with a history of intravenous heroin SA5. Subsequently, the effect was generalized to rats with histories of intravenous cocaine, methamphetamine, and nicotine SA, as well as oral ethanol SA 3, 6. Although footshock-induced reinstatement of drug seeking can be achieved reliably and robustly, it is an effect that tends to be sensitive to certain parametrical variables. These include the arrangement of extinction and reinstatement test sessions, the intensity and duration of footshock stress, and the presence of drug-associated cues during extinction and testing for reinstatement. Here we present a protocol for footshock-induced reinstatement of cocaine seeking that we have used with consistent success to study the relationship between stress and cocaine seeking.
Neuroscience, Issue 47, Relapse, Reinstatement, Cocaine, Rat, Footshock, Stress, Intravenous, Self-administration, Operant Conditioning
2265
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A Noninvasive Hair Sampling Technique to Obtain High Quality DNA from Elusive Small Mammals
Authors: Philippe Henry, Alison Henry, Michael A. Russello.
Institutions: University of British Columbia, Okanagan Campus.
Noninvasive genetic sampling approaches are becoming increasingly important to study wildlife populations. A number of studies have reported using noninvasive sampling techniques to investigate population genetics and demography of wild populations1. This approach has proven to be especially useful when dealing with rare or elusive species2. While a number of these methods have been developed to sample hair, feces and other biological material from carnivores and medium-sized mammals, they have largely remained untested in elusive small mammals. In this video, we present a novel, inexpensive and noninvasive hair snare targeted at an elusive small mammal, the American pika (Ochotona princeps). We describe the general set-up of the hair snare, which consists of strips of packing tape arranged in a web-like fashion and placed along travelling routes in the pikas’ habitat. We illustrate the efficiency of the snare at collecting a large quantity of hair that can then be collected and brought back to the lab. We then demonstrate the use of the DNA IQ system (Promega) to isolate DNA and showcase the utility of this method to amplify commonly used molecular markers including nuclear microsatellites, amplified fragment length polymorphisms (AFLPs), mitochondrial sequences (800bp) as well as a molecular sexing marker. Overall, we demonstrate the utility of this novel noninvasive hair snare as a sampling technique for wildlife population biologists. We anticipate that this approach will be applicable to a variety of small mammals, opening up areas of investigation within natural populations, while minimizing impact to study organisms.
Genetics, Issue 49, Conservation genetics, noninvasive genetic sampling, Hair snares, Microsatellites, AFLPs, American pika, Ochotona princeps
2791
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Aseptic Laboratory Techniques: Plating Methods
Authors: Erin R. Sanders.
Institutions: University of California, Los Angeles .
Microorganisms are present on all inanimate surfaces creating ubiquitous sources of possible contamination in the laboratory. Experimental success relies on the ability of a scientist to sterilize work surfaces and equipment as well as prevent contact of sterile instruments and solutions with non-sterile surfaces. Here we present the steps for several plating methods routinely used in the laboratory to isolate, propagate, or enumerate microorganisms such as bacteria and phage. All five methods incorporate aseptic technique, or procedures that maintain the sterility of experimental materials. Procedures described include (1) streak-plating bacterial cultures to isolate single colonies, (2) pour-plating and (3) spread-plating to enumerate viable bacterial colonies, (4) soft agar overlays to isolate phage and enumerate plaques, and (5) replica-plating to transfer cells from one plate to another in an identical spatial pattern. These procedures can be performed at the laboratory bench, provided they involve non-pathogenic strains of microorganisms (Biosafety Level 1, BSL-1). If working with BSL-2 organisms, then these manipulations must take place in a biosafety cabinet. Consult the most current edition of the Biosafety in Microbiological and Biomedical Laboratories (BMBL) as well as Material Safety Data Sheets (MSDS) for Infectious Substances to determine the biohazard classification as well as the safety precautions and containment facilities required for the microorganism in question. Bacterial strains and phage stocks can be obtained from research investigators, companies, and collections maintained by particular organizations such as the American Type Culture Collection (ATCC). It is recommended that non-pathogenic strains be used when learning the various plating methods. By following the procedures described in this protocol, students should be able to: ● Perform plating procedures without contaminating media. ● Isolate single bacterial colonies by the streak-plating method. ● Use pour-plating and spread-plating methods to determine the concentration of bacteria. ● Perform soft agar overlays when working with phage. ● Transfer bacterial cells from one plate to another using the replica-plating procedure. ● Given an experimental task, select the appropriate plating method.
Basic Protocols, Issue 63, Streak plates, pour plates, soft agar overlays, spread plates, replica plates, bacteria, colonies, phage, plaques, dilutions
3064
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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Authors: Ifat Levy, Lior Rosenberg Belmaker, Kirk Manson, Agnieszka Tymula, Paul W. Glimcher.
Institutions: Yale School of Medicine, Yale School of Medicine, New York University , New York University , New York University .
Most of the choices we make have uncertain consequences. In some cases the probabilities for different possible outcomes are precisely known, a condition termed "risky". In other cases when probabilities cannot be estimated, this is a condition described as "ambiguous". While most people are averse to both risk and ambiguity1,2, the degree of those aversions vary substantially across individuals, such that the subjective value of the same risky or ambiguous option can be very different for different individuals. We combine functional MRI (fMRI) with an experimental economics-based method3 to assess the neural representation of the subjective values of risky and ambiguous options4. This technique can be now used to study these neural representations in different populations, such as different age groups and different patient populations. In our experiment, subjects make consequential choices between two alternatives while their neural activation is tracked using fMRI. On each trial subjects choose between lotteries that vary in their monetary amount and in either the probability of winning that amount or the ambiguity level associated with winning. Our parametric design allows us to use each individual's choice behavior to estimate their attitudes towards risk and ambiguity, and thus to estimate the subjective values that each option held for them. Another important feature of the design is that the outcome of the chosen lottery is not revealed during the experiment, so that no learning can take place, and thus the ambiguous options remain ambiguous and risk attitudes are stable. Instead, at the end of the scanning session one or few trials are randomly selected and played for real money. Since subjects do not know beforehand which trials will be selected, they must treat each and every trial as if it and it alone was the one trial on which they will be paid. This design ensures that we can estimate the true subjective value of each option to each subject. We then look for areas in the brain whose activation is correlated with the subjective value of risky options and for areas whose activation is correlated with the subjective value of ambiguous options.
Neuroscience, Issue 67, Medicine, Molecular Biology, fMRI, magnetic resonance imaging, decision-making, value, uncertainty, risk, ambiguity
3724
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Extinction Training During the Reconsolidation Window Prevents Recovery of Fear
Authors: Daniela Schiller, Candace M. Raio, Elizabeth A. Phelps.
Institutions: Mt. Sinai School of Medicine, New York University , New York University .
Fear is maladaptive when it persists long after circumstances have become safe. It is therefore crucial to develop an approach that persistently prevents the return of fear. Pavlovian fear-conditioning paradigms are commonly employed to create a controlled, novel fear association in the laboratory. After pairing an innocuous stimulus (conditioned stimulus, CS) with an aversive outcome (unconditioned stimulus, US) we can elicit a fear response (conditioned response, or CR) by presenting just the stimulus alone1,2 . Once fear is acquired, it can be diminished using extinction training, whereby the conditioned stimulus is repeatedly presented without the aversive outcome until fear is no longer expressed3. This inhibitory learning creates a new, safe representation for the CS, which competes for expression with the original fear memory4. Although extinction is effective at inhibiting fear, it is not permanent. Fear can spontaneously recover with the passage of time. Exposure to stress or returning to the context of initial learning can also cause fear to resurface3,4. Our protocol addresses the transient nature of extinction by targeting the reconsolidation window to modify emotional memory in a more permanent manner. Ample evidence suggests that reactivating a consolidated memory returns it to a labile state, during which the memory is again susceptible to interference5-9. This window of opportunity appears to open shortly after reactivation and close approximately 6hrs later5,11,16, although this may vary depending on the strength and age of the memory15. By allowing new information to incorporate into the original memory trace, this memory may be updated as it reconsolidates10,11. Studies involving non-human animals have successfully blocked the expression of fear memory by introducing pharmacological manipulations within the reconsolidation window, however, most agents used are either toxic to humans or show equivocal effects when used in human studies12-14. Our protocol addresses these challenges by offering an effective, yet non-invasive, behavioral manipulation that is safe for humans. By prompting fear memory retrieval prior to extinction, we essentially trigger the reconsolidation process, allowing new safety information (i.e., extinction) to be incorporated while the fear memory is still susceptible to interference. A recent study employing this behavioral manipulation in rats has successfully blocked fear memory using these temporal parameters11. Additional studies in humans have demonstrated that introducing new information after the retrieval of previously consolidated motor16, episodic17, or declarative18 memories leads to interference with the original memory trace14. We outline below a novel protocol used to block fear recovery in humans.
Neuroscience, Issue 66, Medicine, Psychology, Physiology, Fear conditioning, extinction, reconsolidation, emotional memory, spontaneous recovery, skin conductance response
3893
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Authors: Haipeng Xing, Willey Liao, Yifan Mo, Michael Q. Zhang.
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work. Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized. Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types. To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
4273
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Quantifying Agonist Activity at G Protein-coupled Receptors
Authors: Frederick J. Ehlert, Hinako Suga, Michael T. Griffin.
Institutions: University of California, Irvine, University of California, Chapman University.
When an agonist activates a population of G protein-coupled receptors (GPCRs), it elicits a signaling pathway that culminates in the response of the cell or tissue. This process can be analyzed at the level of a single receptor, a population of receptors, or a downstream response. Here we describe how to analyze the downstream response to obtain an estimate of the agonist affinity constant for the active state of single receptors. Receptors behave as quantal switches that alternate between active and inactive states (Figure 1). The active state interacts with specific G proteins or other signaling partners. In the absence of ligands, the inactive state predominates. The binding of agonist increases the probability that the receptor will switch into the active state because its affinity constant for the active state (Kb) is much greater than that for the inactive state (Ka). The summation of the random outputs of all of the receptors in the population yields a constant level of receptor activation in time. The reciprocal of the concentration of agonist eliciting half-maximal receptor activation is equivalent to the observed affinity constant (Kobs), and the fraction of agonist-receptor complexes in the active state is defined as efficacy (ε) (Figure 2). Methods for analyzing the downstream responses of GPCRs have been developed that enable the estimation of the Kobs and relative efficacy of an agonist 1,2. In this report, we show how to modify this analysis to estimate the agonist Kb value relative to that of another agonist. For assays that exhibit constitutive activity, we show how to estimate Kb in absolute units of M-1. Our method of analyzing agonist concentration-response curves 3,4 consists of global nonlinear regression using the operational model 5. We describe a procedure using the software application, Prism (GraphPad Software, Inc., San Diego, CA). The analysis yields an estimate of the product of Kobs and a parameter proportional to efficacy (τ). The estimate of τKobs of one agonist, divided by that of another, is a relative measure of Kb (RAi) 6. For any receptor exhibiting constitutive activity, it is possible to estimate a parameter proportional to the efficacy of the free receptor complex (τsys). In this case, the Kb value of an agonist is equivalent to τKobssys 3. Our method is useful for determining the selectivity of an agonist for receptor subtypes and for quantifying agonist-receptor signaling through different G proteins.
Molecular Biology, Issue 58, agonist activity, active state, ligand bias, constitutive activity, G protein-coupled receptor
3179
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Authors: Sergey Rabotyagov, Todd Campbell, Adriana Valcu, Philip Gassman, Manoj Jha, Keith Schilling, Calvin Wolter, Catherine Kling.
Institutions: University of Washington, Iowa State University, North Carolina A&T University, Iowa Geological and Water Survey.
Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,5,12,20) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization. Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods3,4,9,10,13-15,17-19,22,23,25. In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model7 with a multiobjective evolutionary algorithm SPEA226, and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.
Environmental Sciences, Issue 70, Plant Biology, Civil Engineering, Forest Sciences, Water quality, multiobjective optimization, evolutionary algorithms, cost efficiency, agriculture, development
4009
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A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Authors: Gauthier Julie, Fadi F. Hamdan, Guy A. Rouleau.
Institutions: Universite de Montreal, Universite de Montreal, Universite de Montreal.
There are several lines of evidence supporting the role of de novo mutations as a mechanism for common disorders, such as autism and schizophrenia. First, the de novo mutation rate in humans is relatively high, so new mutations are generated at a high frequency in the population. However, de novo mutations have not been reported in most common diseases. Mutations in genes leading to severe diseases where there is a strong negative selection against the phenotype, such as lethality in embryonic stages or reduced reproductive fitness, will not be transmitted to multiple family members, and therefore will not be detected by linkage gene mapping or association studies. The observation of very high concordance in monozygotic twins and very low concordance in dizygotic twins also strongly supports the hypothesis that a significant fraction of cases may result from new mutations. Such is the case for diseases such as autism and schizophrenia. Second, despite reduced reproductive fitness1 and extremely variable environmental factors, the incidence of some diseases is maintained worldwide at a relatively high and constant rate. This is the case for autism and schizophrenia, with an incidence of approximately 1% worldwide. Mutational load can be thought of as a balance between selection for or against a deleterious mutation and its production by de novo mutation. Lower rates of reproduction constitute a negative selection factor that should reduce the number of mutant alleles in the population, ultimately leading to decreased disease prevalence. These selective pressures tend to be of different intensity in different environments. Nonetheless, these severe mental disorders have been maintained at a constant relatively high prevalence in the worldwide population across a wide range of cultures and countries despite a strong negative selection against them2. This is not what one would predict in diseases with reduced reproductive fitness, unless there was a high new mutation rate. Finally, the effects of paternal age: there is a significantly increased risk of the disease with increasing paternal age, which could result from the age related increase in paternal de novo mutations. This is the case for autism and schizophrenia3. The male-to-female ratio of mutation rate is estimated at about 4–6:1, presumably due to a higher number of germ-cell divisions with age in males. Therefore, one would predict that de novo mutations would more frequently come from males, particularly older males4. A high rate of new mutations may in part explain why genetic studies have so far failed to identify many genes predisposing to complexes diseases genes, such as autism and schizophrenia, and why diseases have been identified for a mere 3% of genes in the human genome. Identification for de novo mutations as a cause of a disease requires a targeted molecular approach, which includes studying parents and affected subjects. The process for determining if the genetic basis of a disease may result in part from de novo mutations and the molecular approach to establish this link will be illustrated, using autism and schizophrenia as examples.
Medicine, Issue 52, de novo mutation, complex diseases, schizophrenia, autism, rare variations, DNA sequencing
2534
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Functional Mapping with Simultaneous MEG and EEG
Authors: Hesheng Liu, Naoaki Tanaka, Steven Stufflebeam, Seppo Ahlfors, Matti Hämäläinen.
Institutions: MGH - Massachusetts General Hospital.
We use magnetoencephalography (MEG) and electroencephalography (EEG) to locate and determine the temporal evolution in brain areas involved in the processing of simple sensory stimuli. We will use somatosensory stimuli to locate the hand somatosensory areas, auditory stimuli to locate the auditory cortices, visual stimuli in four quadrants of the visual field to locate the early visual areas. These type of experiments are used for functional mapping in epileptic and brain tumor patients to locate eloquent cortices. In basic neuroscience similar experimental protocols are used to study the orchestration of cortical activity. The acquisition protocol includes quality assurance procedures, subject preparation for the combined MEG/EEG study, and acquisition of evoked-response data with somatosensory, auditory, and visual stimuli. We also demonstrate analysis of the data using the equivalent current dipole model and cortically-constrained minimum-norm estimates. Anatomical MRI data are employed in the analysis for visualization and for deriving boundaries of tissue boundaries for forward modeling and cortical location and orientation constraints for the minimum-norm estimates.
JoVE neuroscience, Issue 40, neuroscience, brain, MEG, EEG, functional imaging
1668
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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Authors: John Marshall, Koji Morikawa, Nicholas Manoukis, Charles Taylor.
Institutions: University of California, Los Angeles.
Charles Taylor and John Marshall explain the utility of mathematical modeling for evaluating the effectiveness of population replacement strategy. Insight is given into how computational models can provide information on the population dynamics of mosquitoes and the spread of transposable elements through A. gambiae subspecies. The ethical considerations of releasing genetically modified mosquitoes into the wild are discussed.
Cellular Biology, Issue 5, mosquito, malaria, popuulation, replacement, modeling, infectious disease
227
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.