JoVE Visualize What is visualize?
Related JoVE Video
Pubmed Article
Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU.
PUBLISHED: 01-01-2013
This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis.
Transcranial Magnetic Stimulation (TMS) is an effective method for establishing a causal link between a cortical area and cognitive/neurophysiological effects. Specifically, by creating a transient interference with the normal activity of a target region and measuring changes in an electrophysiological signal, we can establish a causal link between the stimulated brain area or network and the electrophysiological signal that we record. If target brain areas are functionally defined with prior fMRI scan, TMS could be used to link the fMRI activations with evoked potentials recorded. However, conducting such experiments presents significant technical challenges given the high amplitude artifacts introduced into the EEG signal by the magnetic pulse, and the difficulty to successfully target areas that were functionally defined by fMRI. Here we describe a methodology for combining these three common tools: TMS, EEG, and fMRI. We explain how to guide the stimulator's coil to the desired target area using anatomical or functional MRI data, how to record EEG during concurrent TMS, how to design an ERP study suitable for EEG-TMS combination and how to extract reliable ERP from the recorded data. We will provide representative results from a previously published study, in which fMRI-guided TMS was used concurrently with EEG to show that the face-selective N1 and the body-selective N1 component of the ERP are associated with distinct neural networks in extrastriate cortex. This method allows us to combine the high spatial resolution of fMRI with the high temporal resolution of TMS and EEG and therefore obtain a comprehensive understanding of the neural basis of various cognitive processes.
18 Related JoVE Articles!
Play Button
High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately
Authors: Wenjin Chen, Chung Wong, Evan Vosburgh, Arnold J. Levine, David J. Foran, Eugenia Y. Xu.
Institutions: Raymond and Beverly Sackler Foundation, New Jersey, Rutgers University, Rutgers University, Institute for Advanced Study, New Jersey.
The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application – SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min on a minimally configured laptop, or around 1 min on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary “Manual Initialize” and “Hand Draw” tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model for drug screens in industry and academia.
Cancer Biology, Issue 89, computer programming, high-throughput, image analysis, tumor spheroids, 3D, software application, cancer therapy, drug screen, neuroendocrine tumor cell line, BON-1, cancer research
Play Button
Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials
Authors: Jason R. Themanson.
Institutions: Illinois Wesleyan University.
Social exclusion is a complex social phenomenon with powerful negative consequences. Given the impact of social exclusion on mental and emotional health, an understanding of how perceptions of social exclusion develop over the course of a social interaction is important for advancing treatments aimed at lessening the harmful costs of being excluded. To date, most scientific examinations of social exclusion have looked at exclusion after a social interaction has been completed. While this has been very helpful in developing an understanding of what happens to a person following exclusion, it has not helped to clarify the moment-to-moment dynamics of the process of social exclusion. Accordingly, the current protocol was developed to obtain an improved understanding of social exclusion by examining the patterns of event-related brain activation that are present during social interactions. This protocol allows greater precision and sensitivity in detailing the social processes that lead people to feel as though they have been excluded from a social interaction. Importantly, the current protocol can be adapted to include research projects that vary the nature of exclusionary social interactions by altering how frequently participants are included, how long the periods of exclusion will last in each interaction, and when exclusion will take place during the social interactions. Further, the current protocol can be used to examine variables and constructs beyond those related to social exclusion. This capability to address a variety of applications across psychology by obtaining both neural and behavioral data during ongoing social interactions suggests the present protocol could be at the core of a developing area of scientific inquiry related to social interactions.
Behavior, Issue 93, Event-related brain potentials (ERPs), Social Exclusion, Neuroscience, N2, P3, Cognitive Control
Play Button
Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Authors: Nikki M. Curthoys, Michael J. Mlodzianoski, Dahan Kim, Samuel T. Hess.
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
Play Button
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
Authors: Jennifer J. Heisz, Anthony R. McIntosh.
Institutions: Baycrest.
When considering human neuroimaging data, an appreciation of signal variability represents a fundamental innovation in the way we think about brain signal. Typically, researchers represent the brain's response as the mean across repeated experimental trials and disregard signal fluctuations over time as "noise". However, it is becoming clear that brain signal variability conveys meaningful functional information about neural network dynamics. This article describes the novel method of multiscale entropy (MSE) for quantifying brain signal variability. MSE may be particularly informative of neural network dynamics because it shows timescale dependence and sensitivity to linear and nonlinear dynamics in the data.
Neuroscience, Issue 76, Neurobiology, Anatomy, Physiology, Medicine, Biomedical Engineering, Electroencephalography, EEG, electroencephalogram, Multiscale entropy, sample entropy, MEG, neuroimaging, variability, noise, timescale, non-linear, brain signal, information theory, brain, imaging
Play Button
Solid Phase Synthesis of a Functionalized Bis-Peptide Using "Safety Catch" Methodology
Authors: Conrad T. Pfeiffer, Christian E. Schafmeister.
Institutions: Temple University .
In 1962, R.B. Merrifield published the first procedure using solid-phase peptide synthesis as a novel route to efficiently synthesize peptides. This technique quickly proved advantageous over its solution-phase predecessor in both time and labor. Improvements concerning the nature of solid support, the protecting groups employed and the coupling methods employed over the last five decades have only increased the usefulness of Merrifield's original system. Today, use of a Boc-based protection and base/nucleophile cleavable resin strategy or Fmoc-based protection and acidic cleavable resin strategy, pioneered by R.C. Sheppard, are most commonly used for the synthesis of peptides1. Inspired by Merrifield's solid supported strategy, we have developed a Boc/tert-butyl solid-phase synthesis strategy for the assembly of functionalized bis-peptides2, which is described herein. The use of solid-phase synthesis compared to solution-phase methodology is not only advantageous in both time and labor as described by Merrifield1, but also allows greater ease in the synthesis of bis-peptide libraries. The synthesis that we demonstrate here incorporates a final cleavage stage that uses a two-step "safety catch" mechanism to release the functionalized bis-peptide from the resin by diketopiperazine formation. Bis-peptides are rigid, spiro-ladder oligomers of bis-amino acids that are able to position functionality in a predictable and designable way, controlled by the type and stereochemistry of the monomeric units and the connectivity between each monomer. Each bis-amino acid is a stereochemically pure, cyclic scaffold that contains two amino acids (a carboxylic acid with an α-amine)3,4. Our laboratory is currently investigating the potential of functional bis-peptides across a wide variety of fields including catalysis, protein-protein interactions and nanomaterials.
Chemistry, Issue 63, bis-peptides, solid phase peptide synthesis, bis-amino acids, safety catch, HMBA, DTRA
Play Button
Examining the Characteristics of Episodic Memory using Event-related Potentials in Patients with Alzheimer's Disease
Authors: Erin Hussey, Brandon Ally.
Institutions: Vanderbilt University.
Our laboratory uses event-related EEG potentials (ERPs) to understand and support behavioral investigations of episodic memory in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD). Whereas behavioral data inform us about the patients' performance, ERPs allow us to record discrete changes in brain activity. Further, ERPs can give us insight into the onset, duration, and interaction of independent cognitive processes associated with memory retrieval. In patient populations, these types of studies are used to examine which aspects of memory are impaired and which remain relatively intact compared to a control population. The methodology for collecting ERP data from a vulnerable patient population while these participants perform a recognition memory task is reviewed. This protocol includes participant preparation, quality assurance, data acquisition, and data analysis. In addition to basic setup and acquisition, we will also demonstrate localization techniques to obtain greater spatial resolution and source localization using high-density (128 channel) electrode arrays.
Medicine, Issue 54, recognition memory, episodic memory, event-related potentials, dual process, Alzheimer's disease, amnestic mild cognitive impairment
Play Button
Improved In-gel Reductive β-Elimination for Comprehensive O-linked and Sulfo-glycomics by Mass Spectrometry
Authors: David B. Nix, Tadahiro Kumagai, Toshihiko Katoh, Michael Tiemeyer, Kazuhiro Aoki.
Institutions: University of Georgia, University of Georgia, Ishikawa Prefectural University.
Separation of proteins by SDS-PAGE followed by in-gel proteolytic digestion of resolved protein bands has produced high-resolution proteomic analysis of biological samples. Similar approaches, that would allow in-depth analysis of the glycans carried by glycoproteins resolved by SDS-PAGE, require special considerations in order to maximize recovery and sensitivity when using mass spectrometry (MS) as the detection method. A major hurdle to be overcome in achieving high-quality data is the removal of gel-derived contaminants that interfere with MS analysis. The sample workflow presented here is robust, efficient, and eliminates the need for in-line HPLC clean-up prior to MS. Gel pieces containing target proteins are washed in acetonitrile, water, and ethyl acetate to remove contaminants, including polymeric acrylamide fragments. O-linked glycans are released from target proteins by in-gel reductive β-elimination and recovered through robust, simple clean-up procedures. An advantage of this workflow is that it improves sensitivity for detecting and characterizing sulfated glycans. These procedures produce an efficient separation of sulfated permethylated glycans from non-sulfated (sialylated and neutral) permethylated glycans by a rapid phase-partition prior to MS analysis, and thereby enhance glycomic and sulfoglycomic analyses of glycoproteins resolved by SDS-PAGE.
Chemistry, Issue 93, glycoprotein, glycosylation, in-gel reductive β-elimination, O-linked glycan, sulfated glycan, mass spectrometry, protein ID, SDS-PAGE, glycomics, sulfoglycomics
Play Button
Examining Local Network Processing using Multi-contact Laminar Electrode Recording
Authors: Bryan J. Hansen, Sarah Eagleman, Valentin Dragoi.
Institutions: University of Texas , University of Texas .
Cortical layers are ubiquitous structures throughout neocortex1-4 that consist of highly recurrent local networks. In recent years, significant progress has been made in our understanding of differences in response properties of neurons in different cortical layers5-8, yet there is still a great deal left to learn about whether and how neuronal populations encode information in a laminar-specific manner. Existing multi-electrode array techniques, although informative for measuring responses across many millimeters of cortical space along the cortical surface, are unsuitable to approach the issue of laminar cortical circuits. Here, we present our method for setting up and recording individual neurons and local field potentials (LFPs) across cortical layers of primary visual cortex (V1) utilizing multi-contact laminar electrodes (Figure 1; Plextrode U-Probe, Plexon Inc). The methods included are recording device construction, identification of cortical layers, and identification of receptive fields of individual neurons. To identify cortical layers, we measure the evoked response potentials (ERPs) of the LFP time-series using full-field flashed stimuli. We then perform current-source density (CSD) analysis to identify the polarity inversion accompanied by the sink-source configuration at the base of layer 4 (the sink is inside layer 4, subsequently referred to as granular layer9-12). Current-source density is useful because it provides an index of the location, direction, and density of transmembrane current flow, allowing us to accurately position electrodes to record from all layers in a single penetration6, 11, 12.
Neuroscience, Issue 55, laminar probes, cortical layers, local-field potentials, population coding
Play Button
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
Play Button
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
Play Button
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Institutions: Princeton University.
The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (, a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
Play Button
High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
Authors: Laura Ekstrand, Nikolaus Karpinsky, Yajun Wang, Song Zhang.
Institutions: Iowa State University.
Digital fringe projection (DFP) techniques provide dense 3D measurements of dynamically changing surfaces. Like the human eyes and brain, DFP uses triangulation between matching points in two views of the same scene at different angles to compute depth. However, unlike a stereo-based method, DFP uses a digital video projector to replace one of the cameras1. The projector rapidly projects a known sinusoidal pattern onto the subject, and the surface of the subject distorts these patterns in the camera’s field of view. Three distorted patterns (fringe images) from the camera can be used to compute the depth using triangulation. Unlike other 3D measurement methods, DFP techniques lead to systems that tend to be faster, lower in equipment cost, more flexible, and easier to develop. DFP systems can also achieve the same measurement resolution as the camera. For this reason, DFP and other digital structured light techniques have recently been the focus of intense research (as summarized in1-5). Taking advantage of DFP, the graphics processing unit, and optimized algorithms, we have developed a system capable of 30 Hz 3D video data acquisition, reconstruction, and display for over 300,000 measurement points per frame6,7. Binary defocusing DFP methods can achieve even greater speeds8. Diverse applications can benefit from DFP techniques. Our collaborators have used our systems for facial function analysis9, facial animation10, cardiac mechanics studies11, and fluid surface measurements, but many other potential applications exist. This video will teach the fundamentals of DFP techniques and illustrate the design and operation of a binary defocusing DFP system.
Physics, Issue 82, Structured light, Fringe projection, 3D imaging, 3D scanning, 3D video, binary defocusing, phase-shifting
Play Button
Investigating the Effects of Antipsychotics and Schizotypy on the N400 Using Event-Related Potentials and Semantic Categorization
Authors: Vivian Gu, Ola Mohamed Ali, Katherine L'Abbée Lacas, J. Bruno Debruille.
Institutions: McGill University, McGill University, McGill University, McGill University.
Within the field of cognitive neuroscience, functional magnetic resonance imaging (fMRI) is a popular method of visualizing brain function. This is in part because of its excellent spatial resolution, which allows researchers to identify brain areas associated with specific cognitive processes. However, in the quest to localize brain functions, it is relevant to note that many cognitive, sensory, and motor processes have temporal distinctions that are imperative to capture, an aspect that is left unfulfilled by fMRI’s suboptimal temporal resolution. To better understand cognitive processes, it is thus advantageous to utilize event-related potential (ERP) recording as a method of gathering information about the brain. Some of its advantages include its fantastic temporal resolution, which gives researchers the ability to follow the activity of the brain down to the millisecond. It also directly indexes both excitatory and inhibitory post-synaptic potentials by which most brain computations are performed. This sits in contrast to fMRI, which captures an index of metabolic activity. Further, the non-invasive ERP method does not require a contrast condition: raw ERPs can be examined for just one experimental condition, a distinction from fMRI where control conditions must be subtracted from the experimental condition, leading to uncertainty in associating observations with experimental or contrast conditions. While it is limited by its poor spatial and subcortical activity resolution, ERP recordings’ utility, relative cost-effectiveness, and associated advantages offer strong rationale for its use in cognitive neuroscience to track rapid temporal changes in neural activity. In an effort to foster increase in its use as a research imaging method, and to ensure proper and accurate data collection, the present article will outline – in the framework of a paradigm using semantic categorization to examine the effects of antipsychotics and schizotypy on the N400 – the procedure and key aspects associated with ERP data acquisition.
Behavior, Issue 93, Electrical brain activity, Semantic categorization, Event-related brain potentials, Neuroscience, Cognition, Psychiatry, Antipsychotic medication, N400, Schizotypy, Schizophrenia.
Play Button
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
Play Button
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 
Play Button
A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
Authors: Bianca DeBenedictis, J. Bruce Morton.
Institutions: University of Western Ontario.
The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional Change Card Sort task, participants switch from sorting cards one way, such as shape, to sorting them a different way, such as color. Adjusting behavior in this way exacts a small performance cost, or switch cost, such that responses are typically slower and more error-prone on switch trials in which the sorting rule changes as compared to repeat trials in which the sorting rule remains the same. The ability to flexibly adjust behavior is often said to develop gradually, in part because behavioral costs such as switch costs typically decrease with increasing age. Why aspects of higher-order cognition, such as behavioral flexibility, develop so gradually remains an open question. One hypothesis is that these changes occur in association with functional changes in broad-scale cognitive control networks. On this view, complex mental operations, such as switching, involve rapid interactions between several distributed brain regions, including those that update and maintain task rules, re-orient attention, and select behaviors. With development, functional connections between these regions strengthen, leading to faster and more efficient switching operations. The current video describes a method of testing this hypothesis through the collection and multivariate analysis of fMRI data from participants of different ages.
Behavior, Issue 87, Neurosciences, fMRI, Cognitive Control, Development, Functional Connectivity
Play Button
Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization
Authors: Kwyn A. Meagher, Benjamin N. Doblack, Mercedes Ramirez, Lilian P. Davila.
Institutions: University of California Merced, University of California Merced.
Spring-like materials are ubiquitous in nature and of interest in nanotechnology for energy harvesting, hydrogen storage, and biological sensing applications.  For predictive simulations, it has become increasingly important to be able to model the structure of nanohelices accurately.  To study the effect of local structure on the properties of these complex geometries one must develop realistic models.  To date, software packages are rather limited in creating atomistic helical models.  This work focuses on producing atomistic models of silica glass (SiO2) nanoribbons and nanosprings for molecular dynamics (MD) simulations. Using an MD model of “bulk” silica glass, two computational procedures to precisely create the shape of nanoribbons and nanosprings are presented.  The first method employs the AWK programming language and open-source software to effectively carve various shapes of silica nanoribbons from the initial bulk model, using desired dimensions and parametric equations to define a helix.  With this method, accurate atomistic silica nanoribbons can be generated for a range of pitch values and dimensions.  The second method involves a more robust code which allows flexibility in modeling nanohelical structures.  This approach utilizes a C++ code particularly written to implement pre-screening methods as well as the mathematical equations for a helix, resulting in greater precision and efficiency when creating nanospring models.  Using these codes, well-defined and scalable nanoribbons and nanosprings suited for atomistic simulations can be effectively created.  An added value in both open-source codes is that they can be adapted to reproduce different helical structures, independent of material.  In addition, a MATLAB graphical user interface (GUI) is used to enhance learning through visualization and interaction for a general user with the atomistic helical structures.  One application of these methods is the recent study of nanohelices via MD simulations for mechanical energy harvesting purposes.
Physics, Issue 93, Helical atomistic models; open-source coding; graphical user interface; visualization software; molecular dynamics simulations; graphical processing unit accelerated simulations.
Play Button
High Density Event-related Potential Data Acquisition in Cognitive Neuroscience
Authors: Scott D. Slotnick.
Institutions: Boston College.
Functional magnetic resonance imaging (fMRI) is currently the standard method of evaluating brain function in the field of Cognitive Neuroscience, in part because fMRI data acquisition and analysis techniques are readily available. Because fMRI has excellent spatial resolution but poor temporal resolution, this method can only be used to identify the spatial location of brain activity associated with a given cognitive process (and reveals virtually nothing about the time course of brain activity). By contrast, event-related potential (ERP) recording, a method that is used much less frequently than fMRI, has excellent temporal resolution and thus can track rapid temporal modulations in neural activity. Unfortunately, ERPs are under utilized in Cognitive Neuroscience because data acquisition techniques are not readily available and low density ERP recording has poor spatial resolution. In an effort to foster the increased use of ERPs in Cognitive Neuroscience, the present article details key techniques involved in high density ERP data acquisition. Critically, high density ERPs offer the promise of excellent temporal resolution and good spatial resolution (or excellent spatial resolution if coupled with fMRI), which is necessary to capture the spatial-temporal dynamics of human brain function.
Neuroscience, Issue 38, ERP, electrodes, methods, setup
Copyright © JoVE 2006-2015. All Rights Reserved.
Policies | License Agreement | ISSN 1940-087X
simple hit counter

What is Visualize?

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

How does it work?

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

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

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