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Pubmed Article
Relative accuracy evaluation.
PLoS ONE
PUBLISHED: 08-18-2014
The quality of data plays an important role in business analysis and decision making, and data accuracy is an important aspect in data quality. Thus one necessary task for data quality management is to evaluate the accuracy of the data. And in order to solve the problem that the accuracy of the whole data set is low while a useful part may be high, it is also necessary to evaluate the accuracy of the query results, called relative accuracy. However, as far as we know, neither measure nor effective methods for the accuracy evaluation methods are proposed. Motivated by this, for relative accuracy evaluation, we propose a systematic method. We design a relative accuracy evaluation framework for relational databases based on a new metric to measure the accuracy using statistics. We apply the methods to evaluate the precision and recall of basic queries, which show the result's relative accuracy. We also propose the method to handle data update and to improve accuracy evaluation using functional dependencies. Extensive experimental results show the effectiveness and efficiency of our proposed framework and algorithms.
Authors: Gary E. Raney, Spencer J. Campbell, Joanna C. Bovee.
Published: 01-10-2014
ABSTRACT
The present article describes how to use eye tracking methodologies to study the cognitive processes involved in text comprehension. Measuring eye movements during reading is one of the most precise methods for measuring moment-by-moment (online) processing demands during text comprehension. Cognitive processing demands are reflected by several aspects of eye movement behavior, such as fixation duration, number of fixations, and number of regressions (returning to prior parts of a text). Important properties of eye tracking equipment that researchers need to consider are described, including how frequently the eye position is measured (sampling rate), accuracy of determining eye position, how much head movement is allowed, and ease of use. Also described are properties of stimuli that influence eye movements that need to be controlled in studies of text comprehension, such as the position, frequency, and length of target words. Procedural recommendations related to preparing the participant, setting up and calibrating the equipment, and running a study are given. Representative results are presented to illustrate how data can be evaluated. Although the methodology is described in terms of reading comprehension, much of the information presented can be applied to any study in which participants read verbal stimuli.
21 Related JoVE Articles!
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Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
Authors: Andreas Ender, Albert Mehl.
Institutions: University of Zürich.
Reference scanners are used in dental medicine to verify a lot of procedures. The main interest is to verify impression methods as they serve as a base for dental restorations. The current limitation of many reference scanners is the lack of accuracy scanning large objects like full dental arches, or the limited possibility to assess detailed tooth surfaces. A new reference scanner, based on focus variation scanning technique, was evaluated with regards to highest local and general accuracy. A specific scanning protocol was tested to scan original tooth surface from dental impressions. Also, different model materials were verified. The results showed a high scanning accuracy of the reference scanner with a mean deviation of 5.3 ± 1.1 µm for trueness and 1.6 ± 0.6 µm for precision in case of full arch scans. Current dental impression methods showed much higher deviations (trueness: 20.4 ± 2.2 µm, precision: 12.5 ± 2.5 µm) than the internal scanning accuracy of the reference scanner. Smaller objects like single tooth surface can be scanned with an even higher accuracy, enabling the system to assess erosive and abrasive tooth surface loss. The reference scanner can be used to measure differences for a lot of dental research fields. The different magnification levels combined with a high local and general accuracy can be used to assess changes of single teeth or restorations up to full arch changes.
Medicine, Issue 86, Laboratories, Dental, Calibration, Technology, Dental impression, Accuracy, Trueness, Precision, Full arch scan, Abrasion
51374
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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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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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The 5-Choice Serial Reaction Time Task: A Task of Attention and Impulse Control for Rodents
Authors: Samuel K. Asinof, Tracie A. Paine.
Institutions: Oberlin College.
This protocol describes the 5-choice serial reaction time task, which is an operant based task used to study attention and impulse control in rodents. Test day challenges, modifications to the standard task, can be used to systematically tax the neural systems controlling either attention or impulse control. Importantly, these challenges have consistent effects on behavior across laboratories in intact animals and can reveal either enhancements or deficits in cognitive function that are not apparent when rats are only tested on the standard task. The variety of behavioral measures that are collected can be used to determine if other factors (i.e., sedation, motivation deficits, locomotor impairments) are contributing to changes in performance. The versatility of the 5CSRTT is further enhanced because it is amenable to combination with pharmacological, molecular, and genetic techniques.
Neuroscience, Issue 90, attention, impulse control, neuroscience, cognition, rodent
51574
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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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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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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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Training Synesthetic Letter-color Associations by Reading in Color
Authors: Olympia Colizoli, Jaap M. J. Murre, Romke Rouw.
Institutions: University of Amsterdam.
Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.
Behavior, Issue 84, synesthesia, training, learning, reading, vision, memory, cognition
50893
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Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Authors: Joel Ramirez, Christopher J.M. Scott, Alicia A. McNeely, Courtney Berezuk, Fuqiang Gao, Gregory M. Szilagyi, Sandra E. Black.
Institutions: Sunnybrook Health Sciences Centre, University of Toronto.
Obtaining in vivo human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are exacerbated when significant brain atrophy and age-related white matter changes (e.g. Leukoaraiosis) are present. Lesion Explorer (LE) is an accurate and reliable neuroimaging pipeline specifically developed to address such issues commonly observed on MRI of Alzheimer's disease and normal elderly. The pipeline is a complex set of semi-automatic procedures which has been previously validated in a series of internal and external reliability tests1,2. However, LE's accuracy and reliability is highly dependent on properly trained manual operators to execute commands, identify distinct anatomical landmarks, and manually edit/verify various computer-generated segmentation outputs. LE can be divided into 3 main components, each requiring a set of commands and manual operations: 1) Brain-Sizer, 2) SABRE, and 3) Lesion-Seg. Brain-Sizer's manual operations involve editing of the automatic skull-stripped total intracranial vault (TIV) extraction mask, designation of ventricular cerebrospinal fluid (vCSF), and removal of subtentorial structures. The SABRE component requires checking of image alignment along the anterior and posterior commissure (ACPC) plane, and identification of several anatomical landmarks required for regional parcellation. Finally, the Lesion-Seg component involves manual checking of the automatic lesion segmentation of subcortical hyperintensities (SH) for false positive errors. While on-site training of the LE pipeline is preferable, readily available visual teaching tools with interactive training images are a viable alternative. Developed to ensure a high degree of accuracy and reliability, the following is a step-by-step, video-guided, standardized protocol for LE's manual procedures.
Medicine, Issue 86, Brain, Vascular Diseases, Magnetic Resonance Imaging (MRI), Neuroimaging, Alzheimer Disease, Aging, Neuroanatomy, brain extraction, ventricles, white matter hyperintensities, cerebrovascular disease, Alzheimer disease
50887
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Linearization of the Bradford Protein Assay
Authors: Orna Ernst, Tsaffrir Zor.
Institutions: Tel Aviv University.
Determination of microgram quantities of protein in the Bradford Coomassie brilliant blue assay is accomplished by measurement of absorbance at 590 nm. This most common assay enables rapid and simple protein quantification in cell lysates, cellular fractions, or recombinant protein samples, for the purpose of normalization of biochemical measurements. However, an intrinsic nonlinearity compromises the sensitivity and accuracy of this method. It is shown that under standard assay conditions, the ratio of the absorbance measurements at 590 nm and 450 nm is strictly linear with protein concentration. This simple procedure increases the accuracy and improves the sensitivity of the assay about 10-fold, permitting quantification down to 50 ng of bovine serum albumin. Furthermore, the interference commonly introduced by detergents that are used to create the cell lysates is greatly reduced by the new protocol. A linear equation developed on the basis of mass action and Beer's law perfectly fits the experimental data.
Cellular Biology, Issue 38, Bradford, protein assay, protein quantification, Coomassie brilliant blue
1918
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Anticancer Metal Complexes: Synthesis and Cytotoxicity Evaluation by the MTT Assay
Authors: Nitzan Ganot, Sigalit Meker, Lilia Reytman, Avia Tzubery, Edit Y. Tshuva.
Institutions: The Hebrew University of Jerusalem.
Titanium (IV) and vanadium (V) complexes are highly potent anticancer agents. A challenge in their synthesis refers to their hydrolytic instability; therefore their preparation should be conducted under an inert atmosphere. Evaluation of the anticancer activity of these complexes can be achieved by the MTT assay. The MTT assay is a colorimetric viability assay based on enzymatic reduction of the MTT molecule to formazan when it is exposed to viable cells. The outcome of the reduction is a color change of the MTT molecule. Absorbance measurements relative to a control determine the percentage of remaining viable cancer cells following their treatment with varying concentrations of a tested compound, which is translated to the compound anticancer activity and its IC50 values. The MTT assay is widely common in cytotoxicity studies due to its accuracy, rapidity, and relative simplicity. Herein we present a detailed protocol for the synthesis of air sensitive metal based drugs and cell viability measurements, including preparation of the cell plates, incubation of the compounds with the cells, viability measurements using the MTT assay, and determination of IC50 values.
Medicine, Issue 81, Inorganic Chemicals, Therapeutics, Metals and Metallic Materials, anticancer drugs, cell viability, cisplatin, metal complex, cytotoxicity, HT-29, metal-based drugs, MTT assay, titanium (IV), vanadium (V)
50767
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Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth
Authors: Sabrina Lin, Shawn Fonteno, Shruthi Satish, Bir Bhanu, Prue Talbot.
Institutions: University of California, University of California, University of California, University of California.
Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software. Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT. To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images. To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time. The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion.
Cellular Biology, Issue 39, hESC, matrigel, stem cells, video bioinformatics, colony, growth
1933
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Determining Cell Number During Cell Culture using the Scepter Cell Counter
Authors: Kathleen Ongena, Chandreyee Das, Janet L. Smith, Sónia Gil, Grace Johnston.
Institutions: Millipore Inc.
Counting cells is often a necessary but tedious step for in vitro cell culture. Consistent cell concentrations ensure experimental reproducibility and accuracy. Cell counts are important for monitoring cell health and proliferation rate, assessing immortalization or transformation, seeding cells for subsequent experiments, transfection or infection, and preparing for cell-based assays. It is important that cell counts be accurate, consistent, and fast, particularly for quantitative measurements of cellular responses. Despite this need for speed and accuracy in cell counting, 71% of 400 researchers surveyed1 who count cells using a hemocytometer. While hemocytometry is inexpensive, it is laborious and subject to user bias and misuse, which results in inaccurate counts. Hemocytometers are made of special optical glass on which cell suspensions are loaded in specified volumes and counted under a microscope. Sources of errors in hemocytometry include: uneven cell distribution in the sample, too many or too few cells in the sample, subjective decisions as to whether a given cell falls within the defined counting area, contamination of the hemocytometer, user-to-user variation, and variation of hemocytometer filling rate2. To alleviate the tedium associated with manual counting, 29% of researchers count cells using automated cell counting devices; these include vision-based counters, systems that detect cells using the Coulter principle, or flow cytometry1. For most researchers, the main barrier to using an automated system is the price associated with these large benchtop instruments1. The Scepter cell counter is an automated handheld device that offers the automation and accuracy of Coulter counting at a relatively low cost. The system employs the Coulter principle of impedance-based particle detection3 in a miniaturized format using a combination of analog and digital hardware for sensing, signal processing, data storage, and graphical display. The disposable tip is engineered with a microfabricated, cell- sensing zone that enables discrimination by cell size and cell volume at sub-micron and sub-picoliter resolution. Enhanced with precision liquid-handling channels and electronics, the Scepter cell counter reports cell population statistics graphically displayed as a histogram.
Cellular Biology, Issue 45, Scepter, cell counting, cell culture, hemocytometer, Coulter, Impedance-based particle detection
2204
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A Protocol for Computer-Based Protein Structure and Function Prediction
Authors: Ambrish Roy, Dong Xu, Jonathan Poisson, Yang Zhang.
Institutions: University of Michigan , University of Kansas.
Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.
Biochemistry, Issue 57, On-line server, I-TASSER, protein structure prediction, function prediction
3259
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A Dual Task Procedure Combined with Rapid Serial Visual Presentation to Test Attentional Blink for Nontargets
Authors: Zhengang Lu, Jessica Goold, Ming Meng.
Institutions: Dartmouth College.
When viewers search for targets in a rapid serial visual presentation (RSVP) stream, if two targets are presented within about 500 msec of each other, the first target may be easy to spot but the second is likely to be missed. This phenomenon of attentional blink (AB) has been widely studied to probe the temporal capacity of attention for detecting visual targets. However, with the typical procedure of AB experiments, it is not possible to examine how the processing of non-target items in RSVP may be affected by attention. This paper describes a novel dual task procedure combined with RSVP to test effects of AB for nontargets at varied stimulus onset asynchronies (SOAs). In an exemplar experiment, a target category was first displayed, followed by a sequence of 8 nouns. If one of the nouns belonged to the target category, participants would respond ‘yes’ at the end of the sequence, otherwise participants would respond ‘no’. Two 2-alternative forced choice memory tasks followed the response to determine if participants remembered the words immediately before or after the target, as well as a random word from another part of the sequence. In a second exemplar experiment, the same design was used, except that 1) the memory task was counterbalanced into two groups with SOAs of either 120 or 240 msec and 2) three memory tasks followed the sequence and tested remembrance for nontarget nouns in the sequence that could be anywhere from 3 items prior the target noun position to 3 items following the target noun position. Representative results from a previously published study demonstrate that our procedure can be used to examine divergent effects of attention that not only enhance targets but also suppress nontargets. Here we show results from a representative participant that replicated the previous finding. 
Behavior, Issue 94, Dual task, attentional blink, RSVP, target detection, recognition, visual psychophysics
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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
4375
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The Dig Task: A Simple Scent Discrimination Reveals Deficits Following Frontal Brain Damage
Authors: Kris M. Martens, Cole Vonder Haar, Blake A. Hutsell, Michael R. Hoane.
Institutions: Southern Illinois University at Carbondale.
Cognitive impairment is the most frequent cause of disability in humans following brain damage, yet the behavioral tasks used to assess cognition in rodent models of brain injury is lacking. Borrowing from the operant literature our laboratory utilized a basic scent discrimination paradigm1-4 in order to assess deficits in frontally-injured rats. Previously we have briefly described the Dig task and demonstrated that rats with frontal brain damage show severe deficits across multiple tests within the task5. Here we present a more detailed protocol for this task. Rats are placed into a chamber and allowed to discriminate between two scented sands, one of which contains a reinforcer. The trial ends after the rat either correctly discriminates (defined as digging in the correct scented sand), incorrectly discriminates, or 30 sec elapses. Rats that correctly discriminate are allowed to recover and consume the reinforcer. Rats that discriminate incorrectly are immediately removed from the chamber. This can continue through a variety of reversals and novel scents. The primary analysis is the accuracy for each scent pairing (cumulative proportion correct for each scent). The general findings from the Dig task suggest that it is a simple experimental preparation that can assess deficits in rats with bilateral frontal cortical damage compared to rats with unilateral parietal damage. The Dig task can also be easily incorporated into an existing cognitive test battery. The use of more tasks such as this one can lead to more accurate testing of frontal function following injury, which may lead to therapeutic options for treatment. All animal use was conducted in accordance with protocols approved by the Institutional Animal Care and Use Committee.
Neuroscience, Issue 71, Medicine, Neurobiology, Anatomy, Physiology, Psychology, Behavior, cognitive assessment, dig task, scent discrimination, olfactory, brain injury, traumatic brain injury, TBI, brain damage, rats, animal model
50033
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
50319
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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 (http://www.proteinwisdom.org), 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
50476
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Concentration Determination of Nucleic Acids and Proteins Using the Micro-volume Bio-spec Nano Spectrophotometer
Authors: Suja Sukumaran.
Institutions: Scientific Instruments.
Nucleic Acid quantitation procedures have advanced significantly in the last three decades. More and more, molecular biologists require consistent small-volume analysis of nucleic acid samples for their experiments. The BioSpec-nano provides a potential solution to the problems of inaccurate, non-reproducible results, inherent in current DNA quantitation methods, via specialized optics and a sensitive PDA detector. The BioSpec-nano also has automated functionality such that mounting, measurement, and cleaning are done by the instrument, thereby eliminating tedious, repetitive, and inconsistent placement of the fiber optic element and manual cleaning. In this study, data is presented on the quantification of DNA and protein, as well as on measurement reproducibility and accuracy. Automated sample contact and rapid scanning allows measurement in three seconds, resulting in excellent throughput. Data analysis is carried out using the built-in features of the software. The formula used for calculating DNA concentration is: Sample Concentration = DF · (OD260-OD320)· NACF (1) Where DF = sample dilution factor and NACF = nucleic acid concentration factor. The Nucleic Acid concentration factor is set in accordance with the analyte selected1. Protein concentration results can be expressed as μg/ mL or as moles/L by entering e280 and molecular weight values respectively. When residue values for Tyr, Trp and Cysteine (S-S bond) are entered in the e280Calc tab, the extinction coefficient values are calculated as e280 = 5500 x (Trp residues) + 1490 x (Tyr residues) + 125 x (cysteine S-S bond). The e280 value is used by the software for concentration calculation. In addition to concentration determination of nucleic acids and protein, the BioSpec-nano can be used as an ultra micro-volume spectrophotometer for many other analytes or as a standard spectrophotometer using 5 mm pathlength cells.
Molecular Biology, Issue 48, Nucleic acid quantitation, protein quantitation, micro-volume analysis, label quantitation
2699
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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Authors: Wenan Chen, Ashwin Belle, Charles Cockrell, Kevin R. Ward, Kayvan Najarian.
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques
3871
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