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Pubmed Article
Multiscale modelling and analysis of collective decision making in swarm robotics.
PUBLISHED: 01-01-2014
We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable.
Authors: Seyed Reza Hashemizad, Sam Tsitrin, Polin Yadak, Yingquan He, Daniel Cuneo, Eric Paul Williamson, Devin Liner, Weining Man.
Published: 09-26-2014
Recently, disordered photonic materials have been suggested as an alternative to periodic crystals for the formation of a complete photonic bandgap (PBG). In this article we will describe the methods for constructing and characterizing macroscopic disordered photonic structures using microwaves. The microwave regime offers the most convenient experimental sample size to build and test PBG media. Easily manipulated dielectric lattice components extend flexibility in building various 2D structures on top of pre-printed plastic templates. Once built, the structures could be quickly modified with point and line defects to make freeform waveguides and filters. Testing is done using a widely available Vector Network Analyzer and pairs of microwave horn antennas. Due to the scale invariance property of electromagnetic fields, the results we obtained in the microwave region can be directly applied to infrared and optical regions. Our approach is simple but delivers exciting new insight into the nature of light and disordered matter interaction. Our representative results include the first experimental demonstration of the existence of a complete and isotropic PBG in a two-dimensional (2D) hyperuniform disordered dielectric structure. Additionally we demonstrate experimentally the ability of this novel photonic structure to guide electromagnetic waves (EM) through freeform waveguides of arbitrary shape.
22 Related JoVE Articles!
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In Situ Neutron Powder Diffraction Using Custom-made Lithium-ion Batteries
Authors: William R. Brant, Siegbert Schmid, Guodong Du, Helen E. A. Brand, Wei Kong Pang, Vanessa K. Peterson, Zaiping Guo, Neeraj Sharma.
Institutions: University of Sydney, University of Wollongong, Australian Synchrotron, Australian Nuclear Science and Technology Organisation, University of Wollongong, University of New South Wales.
Li-ion batteries are widely used in portable electronic devices and are considered as promising candidates for higher-energy applications such as electric vehicles.1,2 However, many challenges, such as energy density and battery lifetimes, need to be overcome before this particular battery technology can be widely implemented in such applications.3 This research is challenging, and we outline a method to address these challenges using in situ NPD to probe the crystal structure of electrodes undergoing electrochemical cycling (charge/discharge) in a battery. NPD data help determine the underlying structural mechanism responsible for a range of electrode properties, and this information can direct the development of better electrodes and batteries. We briefly review six types of battery designs custom-made for NPD experiments and detail the method to construct the ‘roll-over’ cell that we have successfully used on the high-intensity NPD instrument, WOMBAT, at the Australian Nuclear Science and Technology Organisation (ANSTO). The design considerations and materials used for cell construction are discussed in conjunction with aspects of the actual in situ NPD experiment and initial directions are presented on how to analyze such complex in situ data.
Physics, Issue 93, In operando, structure-property relationships, electrochemical cycling, electrochemical cells, crystallography, battery performance
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Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
Authors: Ian Sharp, James Patton, Molly Listenberger, Emily Case.
Institutions: University of Illinois at Chicago and Rehabilitation Institute of Chicago, Rehabilitation Institute of Chicago.
Recent research that tests interactive devices for prolonged therapy practice has revealed new prospects for robotics combined with graphical and other forms of biofeedback. Previous human-robot interactive systems have required different software commands to be implemented for each robot leading to unnecessary developmental overhead time each time a new system becomes available. For example, when a haptic/graphic virtual reality environment has been coded for one specific robot to provide haptic feedback, that specific robot would not be able to be traded for another robot without recoding the program. However, recent efforts in the open source community have proposed a wrapper class approach that can elicit nearly identical responses regardless of the robot used. The result can lead researchers across the globe to perform similar experiments using shared code. Therefore modular "switching out"of one robot for another would not affect development time. In this paper, we outline the successful creation and implementation of a wrapper class for one robot into the open-source H3DAPI, which integrates the software commands most commonly used by all robots.
Bioengineering, Issue 54, robotics, haptics, virtual reality, wrapper class, rehabilitation robotics, neural engineering, H3DAPI, C++
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Adaptation of a Haptic Robot in a 3T fMRI
Authors: Joseph Snider, Markus Plank, Larry May, Thomas T. Liu, Howard Poizner.
Institutions: University of California, University of California, University of California.
Functional magnetic resonance imaging (fMRI) provides excellent functional brain imaging via the BOLD signal 1 with advantages including non-ionizing radiation, millimeter spatial accuracy of anatomical and functional data 2, and nearly real-time analyses 3. Haptic robots provide precise measurement and control of position and force of a cursor in a reasonably confined space. Here we combine these two technologies to allow precision experiments involving motor control with haptic/tactile environment interaction such as reaching or grasping. The basic idea is to attach an 8 foot end effecter supported in the center to the robot 4 allowing the subject to use the robot, but shielding it and keeping it out of the most extreme part of the magnetic field from the fMRI machine (Figure 1). The Phantom Premium 3.0, 6DoF, high-force robot (SensAble Technologies, Inc.) is an excellent choice for providing force-feedback in virtual reality experiments 5, 6, but it is inherently non-MR safe, introduces significant noise to the sensitive fMRI equipment, and its electric motors may be affected by the fMRI's strongly varying magnetic field. We have constructed a table and shielding system that allows the robot to be safely introduced into the fMRI environment and limits both the degradation of the fMRI signal by the electrically noisy motors and the degradation of the electric motor performance by the strongly varying magnetic field of the fMRI. With the shield, the signal to noise ratio (SNR: mean signal/noise standard deviation) of the fMRI goes from a baseline of ˜380 to ˜330, and ˜250 without the shielding. The remaining noise appears to be uncorrelated and does not add artifacts to the fMRI of a test sphere (Figure 2). The long, stiff handle allows placement of the robot out of range of the most strongly varying parts of the magnetic field so there is no significant effect of the fMRI on the robot. The effect of the handle on the robot's kinematics is minimal since it is lightweight (˜2.6 lbs) but extremely stiff 3/4" graphite and well balanced on the 3DoF joint in the middle. The end result is an fMRI compatible, haptic system with about 1 cubic foot of working space, and, when combined with virtual reality, it allows for a new set of experiments to be performed in the fMRI environment including naturalistic reaching, passive displacement of the limb and haptic perception, adaptation learning in varying force fields, or texture identification 5, 6.
Bioengineering, Issue 56, neuroscience, haptic robot, fMRI, MRI, pointing
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Controlling the Size, Shape and Stability of Supramolecular Polymers in Water
Authors: Pol Besenius, Isja de Feijter, Nico A.J.M. Sommerdijk, Paul H.H. Bomans, Anja R. A. Palmans.
Institutions: Westfälische Wilhelms-Universität Münster, Eindhoven University of Technology, Eindhoven University of Technology.
For aqueous based supramolecular polymers, the simultaneous control over shape, size and stability is very difficult1. At the same time, the ability to do so is highly important in view of a number of applications in functional soft matter including electronics, biomedical engineering, and sensors. In the past, successful strategies to control the size and shape of supramolecular polymers typically focused on the use of templates2,3, end cappers4 or selective solvent techniques5. Here we disclose a strategy based on self-assembling discotic amphiphiles that leads to the control over stack length and shape of ordered, chiral columnar aggregates. By balancing electrostatic repulsive interactions on the hydrophilic rim and attractive non-covalent forces within the hydrophobic core of the polymerizing building block, we manage to create small and discrete spherical objects6,7. Increasing the salt concentration to screen the charges induces a sphere-to-rod transition. Intriguingly, this transition is expressed in an increase of cooperativity in the temperature-dependent self-assembly mechanism, and more stable aggregates are obtained. For our study we select a benzene-1,3,5-tricarboxamide (BTA) core connected to a hydrophilic metal chelate via a hydrophobic, fluorinated L-phenylalanine based spacer (Scheme 1). The metal chelate selected is a Gd(III)-DTPA complex that contains two overall remaining charges per complex and necessarily two counter ions. The one-dimensional growth of the aggregate is directed by π-π stacking and intermolecular hydrogen bonding. However, the electrostatic, repulsive forces that arise from the charges on the Gd(III)-DTPA complex start limiting the one-dimensional growth of the BTA-based discotic once a certain size is reached. At millimolar concentrations the formed aggregate has a spherical shape and a diameter of around 5 nm as inferred from 1H-NMR spectroscopy, small angle X-ray scattering, and cryogenic transmission electron microscopy (cryo-TEM). The strength of the electrostatic repulsive interactions between molecules can be reduced by increasing the salt concentration of the buffered solutions. This screening of the charges induces a transition from spherical aggregates into elongated rods with a length > 25 nm. Cryo-TEM allows to visualise the changes in shape and size. In addition, CD spectroscopy permits to derive the mechanistic details of the self-assembly processes before and after the addition of salt. Importantly, the cooperativity -a key feature that dictates the physical properties of the produced supramolecular polymers- increases dramatically upon screening the electrostatic interactions. This increase in cooperativity results in a significant increase in the molecular weight of the formed supramolecular polymers in water.
Chemical Engineering, Issue 66, Chemistry, Physics, Self-assembly, cryogenic transmission electron microscopy, circular dichroism, controlled architecture, discotic amphiphile
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High-throughput, Automated Extraction of DNA and RNA from Clinical Samples using TruTip Technology on Common Liquid Handling Robots
Authors: Rebecca C. Holmberg, Alissa Gindlesperger, Tinsley Stokes, Dane Brady, Nitu Thakore, Philip Belgrader, Christopher G. Cooney, Darrell P. Chandler.
Institutions: Akonni Biosystems, Inc., Akonni Biosystems, Inc., Akonni Biosystems, Inc., Akonni Biosystems, Inc..
TruTip is a simple nucleic acid extraction technology whereby a porous, monolithic binding matrix is inserted into a pipette tip. The geometry of the monolith can be adapted for specific pipette tips ranging in volume from 1.0 to 5.0 ml. The large porosity of the monolith enables viscous or complex samples to readily pass through it with minimal fluidic backpressure. Bi-directional flow maximizes residence time between the monolith and sample, and enables large sample volumes to be processed within a single TruTip. The fundamental steps, irrespective of sample volume or TruTip geometry, include cell lysis, nucleic acid binding to the inner pores of the TruTip monolith, washing away unbound sample components and lysis buffers, and eluting purified and concentrated nucleic acids into an appropriate buffer. The attributes and adaptability of TruTip are demonstrated in three automated clinical sample processing protocols using an Eppendorf epMotion 5070, Hamilton STAR and STARplus liquid handling robots, including RNA isolation from nasopharyngeal aspirate, genomic DNA isolation from whole blood, and fetal DNA extraction and enrichment from large volumes of maternal plasma (respectively).
Genetics, Issue 76, Bioengineering, Biomedical Engineering, Molecular Biology, Automation, Laboratory, Clinical Laboratory Techniques, Molecular Diagnostic Techniques, Analytic Sample Preparation Methods, Clinical Laboratory Techniques, Molecular Diagnostic Techniques, Genetic Techniques, Molecular Diagnostic Techniques, Automation, Laboratory, Chemistry, Clinical, DNA/RNA extraction, automation, nucleic acid isolation, sample preparation, nasopharyngeal aspirate, blood, plasma, high-throughput, sequencing
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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
Authors: Jennifer J. Heisz, Anthony R. McIntosh.
Institutions: Baycrest.
When considering human neuroimaging data, an appreciation of signal variability represents a fundamental innovation in the way we think about brain signal. Typically, researchers represent the brain's response as the mean across repeated experimental trials and disregard signal fluctuations over time as "noise". However, it is becoming clear that brain signal variability conveys meaningful functional information about neural network dynamics. This article describes the novel method of multiscale entropy (MSE) for quantifying brain signal variability. MSE may be particularly informative of neural network dynamics because it shows timescale dependence and sensitivity to linear and nonlinear dynamics in the data.
Neuroscience, Issue 76, Neurobiology, Anatomy, Physiology, Medicine, Biomedical Engineering, Electroencephalography, EEG, electroencephalogram, Multiscale entropy, sample entropy, MEG, neuroimaging, variability, noise, timescale, non-linear, brain signal, information theory, brain, imaging
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Preparation of Primary Neurons for Visualizing Neurites in a Frozen-hydrated State Using Cryo-Electron Tomography
Authors: Sarah H. Shahmoradian, Mauricio R. Galiano, Chengbiao Wu, Shurui Chen, Matthew N. Rasband, William C. Mobley, Wah Chiu.
Institutions: Baylor College of Medicine, Baylor College of Medicine, University of California at San Diego, Baylor College of Medicine.
Neurites, both dendrites and axons, are neuronal cellular processes that enable the conduction of electrical impulses between neurons. Defining the structure of neurites is critical to understanding how these processes move materials and signals that support synaptic communication. Electron microscopy (EM) has been traditionally used to assess the ultrastructural features within neurites; however, the exposure to organic solvent during dehydration and resin embedding can distort structures. An important unmet goal is the formulation of procedures that allow for structural evaluations not impacted by such artifacts. Here, we have established a detailed and reproducible protocol for growing and flash-freezing whole neurites of different primary neurons on electron microscopy grids followed by their examination with cryo-electron tomography (cryo-ET). This technique allows for 3-D visualization of frozen, hydrated neurites at nanometer resolution, facilitating assessment of their morphological differences. Our protocol yields an unprecedented view of dorsal root ganglion (DRG) neurites, and a visualization of hippocampal neurites in their near-native state. As such, these methods create a foundation for future studies on neurites of both normal neurons and those impacted by neurological disorders.
Neuroscience, Issue 84, Neurons, Cryo-electron Microscopy, Electron Microscope Tomography, Brain, rat, primary neuron culture, morphological assay
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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 
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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
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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
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The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
Authors: Ludovico Carbone, Paul Fulda, Charlotte Bond, Frank Brueckner, Daniel Brown, Mengyao Wang, Deepali Lodhia, Rebecca Palmer, Andreas Freise.
Institutions: University of Birmingham.
Thermal noise in high-reflectivity mirrors is a major impediment for several types of high-precision interferometric experiments that aim to reach the standard quantum limit or to cool mechanical systems to their quantum ground state. This is for example the case of future gravitational wave observatories, whose sensitivity to gravitational wave signals is expected to be limited in the most sensitive frequency band, by atomic vibration of their mirror masses. One promising approach being pursued to overcome this limitation is to employ higher-order Laguerre-Gauss (LG) optical beams in place of the conventionally used fundamental mode. Owing to their more homogeneous light intensity distribution these beams average more effectively over the thermally driven fluctuations of the mirror surface, which in turn reduces the uncertainty in the mirror position sensed by the laser light. We demonstrate a promising method to generate higher-order LG beams by shaping a fundamental Gaussian beam with the help of diffractive optical elements. We show that with conventional sensing and control techniques that are known for stabilizing fundamental laser beams, higher-order LG modes can be purified and stabilized just as well at a comparably high level. A set of diagnostic tools allows us to control and tailor the properties of generated LG beams. This enabled us to produce an LG beam with the highest purity reported to date. The demonstrated compatibility of higher-order LG modes with standard interferometry techniques and with the use of standard spherical optics makes them an ideal candidate for application in a future generation of high-precision interferometry.
Physics, Issue 78, Optics, Astronomy, Astrophysics, Gravitational waves, Laser interferometry, Metrology, Thermal noise, Laguerre-Gauss modes, interferometry
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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
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
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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
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Recording Multicellular Behavior in Myxococcus xanthus Biofilms using Time-lapse Microcinematography
Authors: Rion G. Taylor, Roy D. Welch.
Institutions: University of South Carolina (USC), Syracuse University.
A swarm of the δ-proteobacterium Myxococcus xanthus contains millions of cells that act as a collective, coordinating movement through a series of signals to create complex, dynamic patterns as a response to environmental cues. These patterns are self-organizing and emergent; they cannot be predicted by observing the behavior of the individual cells. Using a time-lapse microcinematography tracking assay, we identified a distinct emergent pattern in M. xanthus called chemotaxis, defined as the directed movement of a swarm up a nutrient gradient toward its source 1. In order to efficiently characterize chemotaxis via time-lapse microcinematography, we developed a highly modifiable plate complex (Figure 1) and constructed a cluster of 8 microscopes (Figure 2), each capable of capturing time-lapse videos. The assay is rigorous enough to allow consistent replication of quantifiable data, and the resulting videos allow us to observe and track subtle changes in swarm behavior. Once captured, the videos are transferred to an analysis/storage computer with enough memory to process and store thousands of videos. The flexibility of this setup has proven useful to several members of the M. xanthus community.
Microbiology, Issue 42, microcinematography, Myxococcus, chemotaxis, time-lapse
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Tissue Engineering of Tumor Stromal Microenvironment with Application to Cancer Cell Invasion
Authors: Yi-Zhen Ng, Andrew P. South.
Institutions: University of Dundee, A*Star, Singapore.
3D organotypic cultures of epithelial cells on a matrix embedded with mesenchymal cells are widely used to study epithelial cell differentiation and invasion. Rat tail type I collagen and/or matrix derived from Engelbreth-Holm-Swarm mouse sarcoma cells have been traditionally employed as the substrates to model the matrix or stromal microenvironment into which mesenchymal cells (usually fibroblasts) are populated. Although experiments using such matrices are very informative, it can be argued that due to an overriding presence of a single protein (such as in type I Collagen) or a high content of basement membrane components and growth factors (such as in matrix derived from mouse sarcoma cells), these substrates do not best reflect the contribution to matrix composition made by the stromal cells themselves. To study native matrices produced by primary dermal fibroblasts isolated from patients with a tumor prone, genetic blistering disorder (recessive dystrophic epidermolysis bullosa), we have adapted an existing native matrix protocol to study tumor cell invasion. Fibroblasts are induced to produce their own matrix over a prolonged period in culture. This native matrix is then detached from the culture dish and epithelial cells are seeded onto it before the entire coculture is raised to the air-liquid interface. Cellular differentiation and/or invasion can then be assessed over time. This technique provides the ability to assess epithelial-mesenchymal cell interactions in a 3D setting without the need for a synthetic or foreign matrix with the only disadvantage being the prolonged period of time required to produce the native matrix. Here we describe the application of this technique to assess the ability of a single molecule expressed by fibroblasts, type VII collagen, to inhibit tumor cell invasion.
Biomedical Engineering, Issue 85, tumor microenvironment, stromal fibroblasts, extracellular matrix, tissue engineering, dermal equivalent, collagen, native matrix
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Institutions: Princeton University.
The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (, a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
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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
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Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches
Authors: Dominique Martinez, Lotfi Arhidi, Elodie Demondion, Jean-Baptiste Masson, Philippe Lucas.
Institutions: Centre National de la Recherche Scientifique (CNRS), Institut d'Ecologie et des Sciences de l'Environnement de Paris, Institut Pasteur.
Robots designed to track chemical leaks in hazardous industrial facilities1 or explosive traces in landmine fields2 face the same problem as insects foraging for food or searching for mates3: the olfactory search is constrained by the physics of turbulent transport4. The concentration landscape of wind borne odors is discontinuous and consists of sporadically located patches. A pre-requisite to olfactory search is that intermittent odor patches are detected. Because of its high speed and sensitivity5-6, the olfactory organ of insects provides a unique opportunity for detection. Insect antennae have been used in the past to detect not only sex pheromones7 but also chemicals that are relevant to humans, e.g., volatile compounds emanating from cancer cells8 or toxic and illicit substances9-11. We describe here a protocol for using insect antennae on autonomous robots and present a proof of concept for tracking odor plumes to their source. The global response of olfactory neurons is recorded in situ in the form of electroantennograms (EAGs). Our experimental design, based on a whole insect preparation, allows stable recordings within a working day. In comparison, EAGs on excised antennae have a lifetime of 2 hr. A custom hardware/software interface was developed between the EAG electrodes and a robot. The measurement system resolves individual odor patches up to 10 Hz, which exceeds the time scale of artificial chemical sensors12. The efficiency of EAG sensors for olfactory searches is further demonstrated in driving the robot toward a source of pheromone. By using identical olfactory stimuli and sensors as in real animals, our robotic platform provides a direct means for testing biological hypotheses about olfactory coding and search strategies13. It may also prove beneficial for detecting other odorants of interests by combining EAGs from different insect species in a bioelectronic nose configuration14 or using nanostructured gas sensors that mimic insect antennae15.
Neuroscience, Issue 90, robotics, electroantennogram, EAG, gas sensor, electronic nose, olfactory search, surge and casting, moth, insect, olfaction, neuron
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Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
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Using Learning Outcome Measures to assess Doctoral Nursing Education
Authors: Glenn H. Raup, Jeff King, Romana J. Hughes, Natasha Faidley.
Institutions: Harris College of Nursing and Health Sciences, Texas Christian University.
Education programs at all levels must be able to demonstrate successful program outcomes. Grades alone do not represent a comprehensive measurement methodology for assessing student learning outcomes at either the course or program level. The development and application of assessment rubrics provides an unequivocal measurement methodology to ensure a quality learning experience by providing a foundation for improvement based on qualitative and quantitatively measurable, aggregate course and program outcomes. Learning outcomes are the embodiment of the total learning experience and should incorporate assessment of both qualitative and quantitative program outcomes. The assessment of qualitative measures represents a challenge for educators in any level of a learning program. Nursing provides a unique challenge and opportunity as it is the application of science through the art of caring. Quantification of desired student learning outcomes may be enhanced through the development of assessment rubrics designed to measure quantitative and qualitative aspects of the nursing education and learning process. They provide a mechanism for uniform assessment by nursing faculty of concepts and constructs that are otherwise difficult to describe and measure. A protocol is presented and applied to a doctoral nursing education program with recommendations for application and transformation of the assessment rubric to other education programs. Through application of these specially designed rubrics, all aspects of an education program can be adequately assessed to provide information for program assessment that facilitates the closure of the gap between desired and actual student learning outcomes for any desired educational competency.
Medicine, Issue 40, learning, outcomes, measurement, program, assessment, rubric
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Designing and Implementing Nervous System Simulations on LEGO Robots
Authors: Daniel Blustein, Nikolai Rosenthal, Joseph Ayers.
Institutions: Northeastern University, Bremen University of Applied Sciences.
We present a method to use the commercially available LEGO Mindstorms NXT robotics platform to test systems level neuroscience hypotheses. The first step of the method is to develop a nervous system simulation of specific reflexive behaviors of an appropriate model organism; here we use the American Lobster. Exteroceptive reflexes mediated by decussating (crossing) neural connections can explain an animal's taxis towards or away from a stimulus as described by Braitenberg and are particularly well suited for investigation using the NXT platform.1 The nervous system simulation is programmed using LabVIEW software on the LEGO Mindstorms platform. Once the nervous system is tuned properly, behavioral experiments are run on the robot and on the animal under identical environmental conditions. By controlling the sensory milieu experienced by the specimens, differences in behavioral outputs can be observed. These differences may point to specific deficiencies in the nervous system model and serve to inform the iteration of the model for the particular behavior under study. This method allows for the experimental manipulation of electronic nervous systems and serves as a way to explore neuroscience hypotheses specifically regarding the neurophysiological basis of simple innate reflexive behaviors. The LEGO Mindstorms NXT kit provides an affordable and efficient platform on which to test preliminary biomimetic robot control schemes. The approach is also well suited for the high school classroom to serve as the foundation for a hands-on inquiry-based biorobotics curriculum.
Neuroscience, Issue 75, Neurobiology, Bioengineering, Behavior, Mechanical Engineering, Computer Science, Marine Biology, Biomimetics, Marine Science, Neurosciences, Synthetic Biology, Robotics, robots, Modeling, models, Sensory Fusion, nervous system, Educational Tools, programming, software, lobster, Homarus americanus, animal model
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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

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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.