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Investigating the use of support vector machine classification on structural brain images of preterm-born teenagers as a biological marker.
PUBLISHED: 04-03-2015
Preterm birth has been shown to induce an altered developmental trajectory of brain structure and function. With the aid support vector machine (SVM) classification methods we aimed to investigate whether MRI data, collected in adolescence, could be used to predict whether an individual had been born preterm or at term. To this end we collected T1-weighted anatomical MRI data from 143 individuals (69 controls, mean age 14.6y). The inclusion criteria for those born preterm were birth weight ? 1500g and gestational age < 37w. A linear SVM was trained on the grey matter segment of MR images in two different ways. First, all the individuals were used for training and classification was performed by the leave-one-out method, yielding 93% correct classification (sensitivity = 0.905, specificity = 0.942). Separately, a random half of the available data were used for training twice and each time the other, unseen, half of the data was classified, resulting 86% and 91% accurate classifications. Both gestational age (R = -0.24, p<0.04) and birth weight (R = -0.51, p < 0.001) correlated with the distance to decision boundary within the group of individuals born preterm. Statistically significant correlations were also found between IQ (R = -0.30, p < 0.001) and the distance to decision boundary. Those born small for gestational age did not form a separate subgroup in these analyses. The high rate of correct classification by the SVM motivates further investigation. The long-term goal is to automatically and non-invasively predict the outcome of preterm-born individuals on an individual basis using as early a scan as possible.
Authors: Barbara Sargent, Hendrik Reimann, Masayoshi Kubo, Linda Fetters.
Published: 06-01-2015
Task-specific actions emerge from spontaneous movement during infancy. It has been proposed that task-specific actions emerge through a discovery-learning process. Here a method is described in which 3-4 month old infants learn a task by discovery and their leg movements are captured to quantify the learning process. This discovery-learning task uses an infant activated mobile that rotates and plays music based on specified leg action of infants. Supine infants activate the mobile by moving their feet vertically across a virtual threshold. This paradigm is unique in that as infants independently discover that their leg actions activate the mobile, the infants’ leg movements are tracked using a motion capture system allowing for the quantification of the learning process. Specifically, learning is quantified in terms of the duration of mobile activation, the position variance of the end effectors (feet) that activate the mobile, changes in hip-knee coordination patterns, and changes in hip and knee muscle torque. This information describes infant exploration and exploitation at the interplay of person and environmental constraints that support task-specific action. Subsequent research using this method can investigate how specific impairments of different populations of infants at risk for movement disorders influence the discovery-learning process for task-specific action.
21 Related JoVE Articles!
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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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Analysis of Nephron Composition and Function in the Adult Zebrafish Kidney
Authors: Kristen K. McCampbell, Kristin N. Springer, Rebecca A. Wingert.
Institutions: University of Notre Dame.
The zebrafish model has emerged as a relevant system to study kidney development, regeneration and disease. Both the embryonic and adult zebrafish kidneys are composed of functional units known as nephrons, which are highly conserved with other vertebrates, including mammals. Research in zebrafish has recently demonstrated that two distinctive phenomena transpire after adult nephrons incur damage: first, there is robust regeneration within existing nephrons that replaces the destroyed tubule epithelial cells; second, entirely new nephrons are produced from renal progenitors in a process known as neonephrogenesis. In contrast, humans and other mammals seem to have only a limited ability for nephron epithelial regeneration. To date, the mechanisms responsible for these kidney regeneration phenomena remain poorly understood. Since adult zebrafish kidneys undergo both nephron epithelial regeneration and neonephrogenesis, they provide an outstanding experimental paradigm to study these events. Further, there is a wide range of genetic and pharmacological tools available in the zebrafish model that can be used to delineate the cellular and molecular mechanisms that regulate renal regeneration. One essential aspect of such research is the evaluation of nephron structure and function. This protocol describes a set of labeling techniques that can be used to gauge renal composition and test nephron functionality in the adult zebrafish kidney. Thus, these methods are widely applicable to the future phenotypic characterization of adult zebrafish kidney injury paradigms, which include but are not limited to, nephrotoxicant exposure regimes or genetic methods of targeted cell death such as the nitroreductase mediated cell ablation technique. Further, these methods could be used to study genetic perturbations in adult kidney formation and could also be applied to assess renal status during chronic disease modeling.
Cellular Biology, Issue 90, zebrafish; kidney; nephron; nephrology; renal; regeneration; proximal tubule; distal tubule; segment; mesonephros; physiology; acute kidney injury (AKI)
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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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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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Rapid Genotyping of Animals Followed by Establishing Primary Cultures of Brain Neurons
Authors: Jin-Young Koh, Sadahiro Iwabuchi, Zhengmin Huang, N. Charles Harata.
Institutions: University of Iowa Carver College of Medicine, University of Iowa Carver College of Medicine, EZ BioResearch LLC.
High-resolution analysis of the morphology and function of mammalian neurons often requires the genotyping of individual animals followed by the analysis of primary cultures of neurons. We describe a set of procedures for: labeling newborn mice to be genotyped, rapid genotyping, and establishing low-density cultures of brain neurons from these mice. Individual mice are labeled by tattooing, which allows for long-term identification lasting into adulthood. Genotyping by the described protocol is fast and efficient, and allows for automated extraction of nucleic acid with good reliability. This is useful under circumstances where sufficient time for conventional genotyping is not available, e.g., in mice that suffer from neonatal lethality. Primary neuronal cultures are generated at low density, which enables imaging experiments at high spatial resolution. This culture method requires the preparation of glial feeder layers prior to neuronal plating. The protocol is applied in its entirety to a mouse model of the movement disorder DYT1 dystonia (ΔE-torsinA knock-in mice), and neuronal cultures are prepared from the hippocampus, cerebral cortex and striatum of these mice. This protocol can be applied to mice with other genetic mutations, as well as to animals of other species. Furthermore, individual components of the protocol can be used for isolated sub-projects. Thus this protocol will have wide applications, not only in neuroscience but also in other fields of biological and medical sciences.
Neuroscience, Issue 95, AP2, genotyping, glial feeder layer, mouse tail, neuronal culture, nucleic-acid extraction, PCR, tattoo, torsinA
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Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression
Authors: Caitlin L. Carew, Erica L. Tatham, Andrea M. Milne, Glenda M. MacQueen, Geoffrey B.C. Hall.
Institutions: McMaster University, McMaster University, University of Calgary, McMaster University.
Ruminative brooding is associated with increased vulnerability to major depression. Individuals who regularly ruminate will often try to reduce the frequency of their negative thoughts by actively suppressing them. We aim to identify the neural correlates underlying thought suppression in at-risk and depressed individuals. Three groups of women were studied; a major depressive disorder group, an at-risk group (having a first degree relative with depression) and controls. Participants performed a mixed block-event fMRI paradigm involving thought suppression, free thought and motor control periods. Participants identified the re-emergence of “to-be-suppressed” thoughts (“popping” back into conscious awareness) with a button press. During thought suppression the control group showed the greatest activation of the dorsolateral prefrontal cortex, followed by the at-risk, then depressed group. During the re-emergence of intrusive thoughts compared to successful re-suppression of those thoughts, the control group showed the greatest activation of the anterior cingulate cortices, followed by the at-risk, then depressed group. At-risk participants displayed anomalies in the neural regulation of thought suppression resembling the dysregulation found in depressed individuals. The predictive value of these changes in the onset of depression remains to be determined.
Behavior, Issue 99, Major Depressive Disorder, Risk, Thought Suppression, fMRI, Women, Rumination, Thought Intrusion
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Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks
Authors: Theresa Sukal-Moulton, Ana Carolina de Campos, Christopher J. Stanley, Diane L. Damiano.
Institutions: National Institutes of Health.
There are several advantages that functional near-infrared spectroscopy (fNIRS) presents in the study of the neural control of human movement. It is relatively flexible with respect to participant positioning and allows for some head movements during tasks. Additionally, it is inexpensive, light weight, and portable, with very few contraindications to its use. This presents a unique opportunity to study functional brain activity during motor tasks in individuals who are typically developing, as well as those with movement disorders, such as cerebral palsy. An additional consideration when studying movement disorders, however, is the quality of actual movements performed and the potential for additional, unintended movements. Therefore, concurrent monitoring of both blood flow changes in the brain and actual movements of the body during testing is required for appropriate interpretation of fNIRS results. Here, we show a protocol for the combination of fNIRS with muscle and kinematic monitoring during motor tasks. We explore gait, a unilateral multi-joint movement (cycling), and two unilateral single-joint movements (isolated ankle dorsiflexion, and isolated hand squeezing). The techniques presented can be useful in studying both typical and atypical motor control, and can be modified to investigate a broad range of tasks and scientific questions.
Behavior, Issue 94, functional near infrared spectroscopy, fNIRS, brain activity, gait, motor tasks, cerebral palsy, coordination
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Moderate Prenatal Alcohol Exposure and Quantification of Social Behavior in Adult Rats
Authors: Derek A. Hamilton, Christy M. Magcalas, Daniel Barto, Clark W. Bird, Carlos I. Rodriguez, Brandi C. Fink, Sergio M. Pellis, Suzy Davies, Daniel D. Savage.
Institutions: University of New Mexico, University of New Mexico, University of New Mexico, University of Lethbridge.
Alterations in social behavior are among the major negative consequences observed in children with Fetal Alcohol Spectrum Disorders (FASDs). Several independent laboratories have demonstrated robust alterations in the social behavior of rodents exposed to alcohol during brain development across a wide range of exposure durations, timing, doses, and ages at the time of behavioral quantification. Prior work from this laboratory has identified reliable alterations in specific forms of social interaction following moderate prenatal alcohol exposure (PAE) in the rat that persist well into adulthood, including increased wrestling and decreased investigation. These behavioral alterations have been useful in identifying neural circuits altered by moderate PAE1, and may hold importance for progressing toward a more complete understanding of the neural bases of PAE-related alterations in social behavior. This paper describes procedures for performing moderate PAE in which rat dams voluntarily consume ethanol or saccharin (control) throughout gestation, and measurement of social behaviors in adult offspring.
Neuroscience, Issue 94, Aggression, Alcohol Teratogenesis, Alcohol-related Neurodevelopmental Disorders, ARND, Fetal Alcohol Spectrum Disorders, FASD, Fetal Alcohol Syndrome, FAS, Social interaction
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Intrauterine Telemetry to Measure Mouse Contractile Pressure In Vivo
Authors: Cara C. Rada, Stephanie L. Pierce, Chad A. Grotegut, Sarah K. England.
Institutions: Washington University in St. Louis, Duke University.
A complex integration of molecular and electrical signals is needed to transform a quiescent uterus into a contractile organ at the end of pregnancy. Despite the discovery of key regulators of uterine contractility, this process is still not fully understood. Transgenic mice provide an ideal model in which to study parturition. Previously, the only method to study uterine contractility in the mouse was ex vivo isometric tension recordings, which are suboptimal for several reasons. The uterus must be removed from its physiological environment, a limited time course of investigation is possible, and the mice must be sacrificed. The recent development of radiometric telemetry has allowed for longitudinal, real-time measurements of in vivo intrauterine pressure in mice. Here, the implantation of an intrauterine telemeter to measure pressure changes in the mouse uterus from mid-pregnancy until delivery is described. By comparing differences in pressures between wild type and transgenic mice, the physiological impact of a gene of interest can be elucidated. This technique should expedite the development of therapeutics used to treat myometrial disorders during pregnancy, including preterm labor.
Medicine, Issue 98, Intrauterine pressure, telemetry, pregnancy, mouse, uterus, in vivo recording, preterm labor, reproductive
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
Authors: Marc N. Coutanche, Sharon L. Thompson-Schill.
Institutions: University of Pennsylvania.
It is now appreciated that condition-relevant information can be present within distributed patterns of functional magnetic resonance imaging (fMRI) brain activity, even for conditions with similar levels of univariate activation. Multi-voxel pattern (MVP) analysis has been used to decode this information with great success. FMRI investigators also often seek to understand how brain regions interact in interconnected networks, and use functional connectivity (FC) to identify regions that have correlated responses over time. Just as univariate analyses can be insensitive to information in MVPs, FC may not fully characterize the brain networks that process conditions with characteristic MVP signatures. The method described here, informational connectivity (IC), can identify regions with correlated changes in MVP-discriminability across time, revealing connectivity that is not accessible to FC. The method can be exploratory, using searchlights to identify seed-connected areas, or planned, between pre-selected regions-of-interest. The results can elucidate networks of regions that process MVP-related conditions, can breakdown MVPA searchlight maps into separate networks, or can be compared across tasks and patient groups.
Neuroscience, Issue 89, fMRI, MVPA, connectivity, informational connectivity, functional connectivity, networks, multi-voxel pattern analysis, decoding, classification, method, multivariate
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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
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A Mouse Model of in Utero Transplantation
Authors: Amar Nijagal, Tom Le, Marta Wegorzewska, Tippi C. MacKenzie.
Institutions: University of California, University of California, University of California.
The transplantation of stem cells and viruses in utero has tremendous potential for treating congenital disorders in the human fetus. For example, in utero transplantation (IUT) of hematopoietic stem cells has been used to successfully treat patients with severe combined immunodeficiency.1,2 In several other conditions, however, IUT has been attempted without success.3 Given these mixed results, the availability of an efficient non-human model to study the biological sequelae of stem cell transplantation and gene therapy is critical to advance this field. We and others have used the mouse model of IUT to study factors affecting successful engraftment of in utero transplanted hematopoietic stem cells in both wild-type mice4-7 and those with genetic diseases.8,9 The fetal environment also offers considerable advantages for the success of in utero gene therapy. For example, the delivery of adenoviral10, adeno-associated viral10, retroviral11, and lentiviral vectors12,13 into the fetus has resulted in the transduction of multiple organs distant from the site of injection with long-term gene expression. in utero gene therapy may therefore be considered as a possible treatment strategy for single gene disorders such as muscular dystrophy or cystic fibrosis. Another potential advantage of IUT is the ability to induce immune tolerance to a specific antigen. As seen in mice with hemophilia, the introduction of Factor IX early in development results in tolerance to this protein.14 In addition to its use in investigating potential human therapies, the mouse model of IUT can be a powerful tool to study basic questions in developmental and stem cell biology. For example, one can deliver various small molecules to induce or inhibit specific gene expression at defined gestational stages and manipulate developmental pathways. The impact of these alterations can be assessed at various timepoints after the initial transplantation. Furthermore, one can transplant pluripotent or lineage specific progenitor cells into the fetal environment to study stem cell differentiation in a non-irradiated and unperturbed host environment. The mouse model of IUT has already provided numerous insights within the fields of immunology, and developmental and stem cell biology. In this video-based protocol, we describe a step-by-step approach to performing IUT in mouse fetuses and outline the critical steps and potential pitfalls of this technique.
Medicine, Issue 47, development, stem cells, transplantation, in utero
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Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Authors: Barry M. Lester, Lynne Andreozzi-Fontaine, Edward Tronick, Rosemarie Bigsby.
Institutions: Brown University, Women & Infants Hospital of Rhode Island, University of Massachusetts, Boston.
There has been a long-standing interest in the assessment of the neurobehavioral integrity of the newborn infant. The NICU Network Neurobehavioral Scale (NNNS) was developed as an assessment for the at-risk infant. These are infants who are at increased risk for poor developmental outcome because of insults during prenatal development, such as substance exposure or prematurity or factors such as poverty, poor nutrition or lack of prenatal care that can have adverse effects on the intrauterine environment and affect the developing fetus. The NNNS assesses the full range of infant neurobehavioral performance including neurological integrity, behavioral functioning, and signs of stress/abstinence. The NNNS is a noninvasive neonatal assessment tool with demonstrated validity as a predictor, not only of medical outcomes such as cerebral palsy diagnosis, neurological abnormalities, and diseases with risks to the brain, but also of developmental outcomes such as mental and motor functioning, behavior problems, school readiness, and IQ. The NNNS can identify infants at high risk for abnormal developmental outcome and is an important clinical tool that enables medical researchers and health practitioners to identify these infants and develop intervention programs to optimize the development of these infants as early as possible. The video shows the NNNS procedures, shows examples of normal and abnormal performance and the various clinical populations in which the exam can be used.
Behavior, Issue 90, NICU Network Neurobehavioral Scale, NNNS, High risk infant, Assessment, Evaluation, Prediction, Long term outcome
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Assessing Teratogenic Changes in a Zebrafish Model of Fetal Alcohol Exposure
Authors: Evyn Loucks, Sara Ahlgren.
Institutions: Children's Memorial Research Center, Northwestern University.
Fetal alcohol syndrome (FAS) is a severe manifestation of embryonic exposure to ethanol. It presents with characteristic defects to the face and organs, including mental retardation due to disordered and damaged brain development. Fetal alcohol spectrum disorder (FASD) is a term used to cover a continuum of birth defects that occur due to maternal alcohol consumption, and occurs in approximately 4% of children born in the United States. With 50% of child-bearing age women reporting consumption of alcohol, and half of all pregnancies being unplanned, unintentional exposure is a continuing issue2. In order to best understand the damage produced by ethanol, plus produce a model with which to test potential interventions, we developed a model of developmental ethanol exposure using the zebrafish embryo. Zebrafish are ideal for this kind of teratogen study3-8. Each pair lays hundreds of eggs, which can then be collected without harming the adult fish. The zebrafish embryo is transparent and can be readily imaged with any number of stains. Analysis of these embryos after exposure to ethanol at different doses and times of duration and application shows that the gross developmental defects produced by ethanol are consistent with the human birth defect. Described here are the basic techniques used to study and manipulate the zebrafish FAS model.
Medicine, Issue 61, Zebrafish, fetal alcohol exposure, Danio rerio, development, mRNA expression, morpholino, ethanol exposure
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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Authors: Ifat Levy, Lior Rosenberg Belmaker, Kirk Manson, Agnieszka Tymula, Paul W. Glimcher.
Institutions: Yale School of Medicine, Yale School of Medicine, New York University , New York University , New York University .
Most of the choices we make have uncertain consequences. In some cases the probabilities for different possible outcomes are precisely known, a condition termed "risky". In other cases when probabilities cannot be estimated, this is a condition described as "ambiguous". While most people are averse to both risk and ambiguity1,2, the degree of those aversions vary substantially across individuals, such that the subjective value of the same risky or ambiguous option can be very different for different individuals. We combine functional MRI (fMRI) with an experimental economics-based method3 to assess the neural representation of the subjective values of risky and ambiguous options4. This technique can be now used to study these neural representations in different populations, such as different age groups and different patient populations. In our experiment, subjects make consequential choices between two alternatives while their neural activation is tracked using fMRI. On each trial subjects choose between lotteries that vary in their monetary amount and in either the probability of winning that amount or the ambiguity level associated with winning. Our parametric design allows us to use each individual's choice behavior to estimate their attitudes towards risk and ambiguity, and thus to estimate the subjective values that each option held for them. Another important feature of the design is that the outcome of the chosen lottery is not revealed during the experiment, so that no learning can take place, and thus the ambiguous options remain ambiguous and risk attitudes are stable. Instead, at the end of the scanning session one or few trials are randomly selected and played for real money. Since subjects do not know beforehand which trials will be selected, they must treat each and every trial as if it and it alone was the one trial on which they will be paid. This design ensures that we can estimate the true subjective value of each option to each subject. We then look for areas in the brain whose activation is correlated with the subjective value of risky options and for areas whose activation is correlated with the subjective value of ambiguous options.
Neuroscience, Issue 67, Medicine, Molecular Biology, fMRI, magnetic resonance imaging, decision-making, value, uncertainty, risk, ambiguity
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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
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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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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
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Functional Interrogation of Adult Hypothalamic Neurogenesis with Focal Radiological Inhibition
Authors: Daniel A. Lee, Juan Salvatierra, Esteban Velarde, John Wong, Eric C. Ford, Seth Blackshaw.
Institutions: California Institute of Technology, Johns Hopkins University School of Medicine, Johns Hopkins University School of Medicine, University Of Washington Medical Center, Johns Hopkins University School of Medicine.
The functional characterization of adult-born neurons remains a significant challenge. Approaches to inhibit adult neurogenesis via invasive viral delivery or transgenic animals have potential confounds that make interpretation of results from these studies difficult. New radiological tools are emerging, however, that allow one to noninvasively investigate the function of select groups of adult-born neurons through accurate and precise anatomical targeting in small animals. Focal ionizing radiation inhibits the birth and differentiation of new neurons, and allows targeting of specific neural progenitor regions. In order to illuminate the potential functional role that adult hypothalamic neurogenesis plays in the regulation of physiological processes, we developed a noninvasive focal irradiation technique to selectively inhibit the birth of adult-born neurons in the hypothalamic median eminence. We describe a method for Computer tomography-guided focal irradiation (CFIR) delivery to enable precise and accurate anatomical targeting in small animals. CFIR uses three-dimensional volumetric image guidance for localization and targeting of the radiation dose, minimizes radiation exposure to nontargeted brain regions, and allows for conformal dose distribution with sharp beam boundaries. This protocol allows one to ask questions regarding the function of adult-born neurons, but also opens areas to questions in areas of radiobiology, tumor biology, and immunology. These radiological tools will facilitate the translation of discoveries at the bench to the bedside.
Neuroscience, Issue 81, Neural Stem Cells (NSCs), Body Weight, Radiotherapy, Image-Guided, Metabolism, Energy Metabolism, Neurogenesis, Cell Proliferation, Neurosciences, Irradiation, Radiological treatment, Computer-tomography (CT) imaging, Hypothalamus, Hypothalamic Proliferative Zone (HPZ), Median Eminence (ME), Small Animal Radiation Research Platform (SARRP)
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Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
Authors: Savannah E. Sanchez, Daniel A. Cuevas, Jason E. Rostron, Tiffany Y. Liang, Cullen G. Pivaroff, Matthew R. Haynes, Jim Nulton, Ben Felts, Barbara A. Bailey, Peter Salamon, Robert A. Edwards, Alex B. Burgin, Anca M. Segall, Forest Rohwer.
Institutions: San Diego State University, San Diego State University, San Diego State University, San Diego State University, San Diego State University, Argonne National Laboratory, Broad Institute.
Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.
Immunology, Issue 100, phenomics, phage, viral metagenome, Multi-phenotype Assay Plates (MAPs), continuous culture, metabolomics
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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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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.