Electroencephalography (EEG) is an effective, efficient, and noninvasive method of assessing and recording brain activity. Given the excellent temporal resolution, EEG can be used to examine the neural response related to specific behaviors, states, or external stimuli. An example of this utility is the assessment of the mirror neuron system (MNS) in humans through the examination of the EEG mu rhythm. The EEG mu rhythm, oscillatory activity in the 8-12 Hz frequency range recorded from centrally located electrodes, is suppressed when an individual executes, or simply observes, goal directed actions. As such, it has been proposed to reflect activity of the MNS. It has been theorized that dysfunction in the mirror neuron system (MNS) plays a contributing role in the social deficits of autism spectrum disorder (ASD). The MNS can then be noninvasively examined in clinical populations by using EEG mu rhythm attenuation as an index for its activity. The described protocol provides an avenue to examine social cognitive functions theoretically linked to the MNS in individuals with typical and atypical development, such as ASD.
20 Related JoVE Articles!
Cortical Source Analysis of High-Density EEG Recordings in Children
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
Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
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
Using an Automated 3D-tracking System to Record Individual and Shoals of Adult Zebrafish
Like many aquatic animals, zebrafish (Danio rerio
) moves in a 3D space. It is thus preferable to use a 3D recording system to study its behavior. The presented automatic video tracking system accomplishes this by using a mirror system and a calibration procedure that corrects for the considerable error introduced by the transition of light from water to air. With this system it is possible to record both single and groups of adult zebrafish. Before use, the system has to be calibrated. The system consists of three modules: Recording, Path Reconstruction, and Data Processing. The step-by-step protocols for calibration and using the three modules are presented. Depending on the experimental setup, the system can be used for testing neophobia, white aversion, social cohesion, motor impairments, novel object exploration etc
. It is especially promising as a first-step tool to study the effects of drugs or mutations on basic behavioral patterns. The system provides information about vertical and horizontal distribution of the zebrafish, about the xyz-components of kinematic parameters (such as locomotion, velocity, acceleration, and turning angle) and it provides the data necessary to calculate parameters for social cohesions when testing shoals.
Behavior, Issue 82, neuroscience, Zebrafish, Danio rerio, anxiety, Shoaling, Pharmacology, 3D-tracking, MK801
Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
Institutions: Freie Universität Berlin, Charité Berlin, Freie Universität Berlin, Psychiatric University Hospital Zurich.
The main goal of this study was to assess the usability of a tablet-computer-based application (EmoCogMeter) in investigating the effects of age on cognitive functions across the lifespan in a sample of 378 healthy subjects (age range 18-89 years). Consistent with previous findings we found an age-related cognitive decline across a wide range of neuropsychological domains (memory, attention, executive functions), thereby proving the usability of our tablet-based application. Regardless of prior computer experience, subjects of all age groups were able to perform the tasks without instruction or feedback from an experimenter. Increased motivation and compliance proved to be beneficial for task performance, thereby potentially increasing the validity of the results. Our promising findings underline the great clinical and practical potential of a tablet-based application for detection and monitoring of cognitive dysfunction.
Behavior, Issue 84, Neuropsychological Testing, cognitive decline, age, tablet-computer, memory, attention, executive functions
A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
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
Measuring Oral Fatty Acid Thresholds, Fat Perception, Fatty Food Liking, and Papillae Density in Humans
Institutions: Deakin University.
Emerging evidence from a number of laboratories indicates that humans have the ability to identify fatty acids in the oral cavity, presumably via fatty acid receptors housed on taste cells. Previous research has shown that an individual's oral sensitivity to fatty acid, specifically oleic acid (C18:1) is associated with body mass index (BMI), dietary fat consumption, and the ability to identify fat in foods. We have developed a reliable and reproducible method to assess oral chemoreception of fatty acids, using a milk and C18:1 emulsion, together with an ascending forced choice triangle procedure. In parallel, a food matrix has been developed to assess an individual's ability to perceive fat, in addition to a simple method to assess fatty food liking. As an added measure tongue photography is used to assess papillae density, with higher density often being associated with increased taste sensitivity.
Neuroscience, Issue 88, taste, overweight and obesity, dietary fat, fatty acid, diet, fatty food liking, detection threshold
Preparation of Primary Myogenic Precursor Cell/Myoblast Cultures from Basal Vertebrate Lineages
Institutions: University of Alabama at Birmingham, INRA UR1067, INRA UR1037.
Due to the inherent difficulty and time involved with studying the myogenic program in vivo
, primary culture systems derived from the resident adult stem cells of skeletal muscle, the myogenic precursor cells (MPCs), have proven indispensible to our understanding of mammalian skeletal muscle development and growth. Particularly among the basal taxa of Vertebrata,
however, data are limited describing the molecular mechanisms controlling the self-renewal, proliferation, and differentiation of MPCs. Of particular interest are potential mechanisms that underlie the ability of basal vertebrates to undergo considerable postlarval skeletal myofiber hyperplasia (i.e.
teleost fish) and full regeneration following appendage loss (i.e.
urodele amphibians). Additionally, the use of cultured myoblasts could aid in the understanding of regeneration and the recapitulation of the myogenic program and the differences between them. To this end, we describe in detail a robust and efficient protocol (and variations therein) for isolating and maintaining MPCs and their progeny, myoblasts and immature myotubes, in cell culture as a platform for understanding the evolution of the myogenic program, beginning with the more basal vertebrates. Capitalizing on the model organism status of the zebrafish (Danio rerio
), we report on the application of this protocol to small fishes of the cyprinid clade Danioninae
. In tandem, this protocol can be utilized to realize a broader comparative approach by isolating MPCs from the Mexican axolotl (Ambystomamexicanum
) and even laboratory rodents. This protocol is now widely used in studying myogenesis in several fish species, including rainbow trout, salmon, and sea bream1-4
Basic Protocol, Issue 86, myogenesis, zebrafish, myoblast, cell culture, giant danio, moustached danio, myotubes, proliferation, differentiation, Danioninae, axolotl
Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
Institutions: Alpert Medical School, Brown University, University of Georgia.
Complementary structural and functional neuroimaging techniques used to examine the Default Mode Network (DMN) could potentially improve assessments of psychiatric illness severity and provide added validity to the clinical diagnostic process. Recent neuroimaging research suggests that DMN processes may be disrupted in a number of stress-related psychiatric illnesses, such as posttraumatic stress disorder (PTSD).
Although specific DMN functions remain under investigation, it is generally thought to be involved in introspection and self-processing. In healthy individuals it exhibits greatest activity during periods of rest, with less activity, observed as deactivation, during cognitive tasks, e.g.
, working memory. This network consists of the medial prefrontal cortex, posterior cingulate cortex/precuneus, lateral parietal cortices and medial temporal regions.
Multiple functional and structural imaging approaches have been developed to study the DMN. These have unprecedented potential to further the understanding of the function and dysfunction of this network. Functional approaches, such as the evaluation of resting state connectivity and task-induced deactivation, have excellent potential to identify targeted neurocognitive and neuroaffective (functional) diagnostic markers and may indicate illness severity and prognosis with increased accuracy or specificity. Structural approaches, such as evaluation of morphometry and connectivity, may provide unique markers of etiology and long-term outcomes. Combined, functional and structural methods provide strong multimodal, complementary and synergistic approaches to develop valid DMN-based imaging phenotypes in stress-related psychiatric conditions. This protocol aims to integrate these methods to investigate DMN structure and function in PTSD, relating findings to illness severity and relevant clinical factors.
Medicine, Issue 89, default mode network, neuroimaging, functional magnetic resonance imaging, diffusion tensor imaging, structural connectivity, functional connectivity, posttraumatic stress disorder
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
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
Trajectory Data Analyses for Pedestrian Space-time Activity Study
Institutions: Kean University, University of Wisconsin-Madison.
It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission1-3
. An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data4
Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling.
The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an automatic module. Trajectory segmentation5
involves the identification of indoor and outdoor parts from pre-processed space-time tracks. Again, both interactive visual segmentation and automatic segmentation are supported. Segmented space-time tracks are then analyzed to derive characteristics of one's activity space such as activity radius etc.
Density estimation and visualization are used to examine large amount of trajectory data to model hot spots and interactions. We demonstrate both density surface mapping6
and density volume rendering7
. We also include a couple of other exploratory data analyses (EDA) and visualizations tools, such as Google Earth animation support and connection analysis. The suite of analytical as well as visual methods presented in this paper may be applied to any trajectory data for space-time activity studies.
Environmental Sciences, Issue 72, Computer Science, Behavior, Infectious Diseases, Geography, Cartography, Data Display, Disease Outbreaks, cartography, human behavior, Trajectory data, space-time activity, GPS, GIS, ArcGIS, spatiotemporal analysis, visualization, segmentation, density surface, density volume, exploratory data analysis, modelling
A Video Demonstration of Preserved Piloting by Scent Tracking but Impaired Dead Reckoning After Fimbria-Fornix Lesions in the Rat
Institutions: Canadian Centre for Behavioural Neuroscience, University of Lethbridge.
Piloting and dead reckoning navigation strategies use very different cue constellations and computational processes (Darwin, 1873; Barlow, 1964; O’Keefe and Nadel, 1978; Mittelstaedt and Mittelstaedt, 1980; Landeau et al., 1984; Etienne, 1987; Gallistel, 1990;
Maurer and Séguinot, 1995). Piloting requires the use of the relationships between relatively stable external (visual, olfactory, auditory) cues, whereas dead reckoning requires the integration of cues generated by self-movement. Animals obtain self-movement information from vestibular receptors, and possibly muscle and joint receptors, and efference copy of commands that generate movement. An animal may also use the flows of visual, auditory, and olfactory stimuli caused by its movements. Using a piloting strategy an animal can use geometrical calculations to determine directions and distances to places in its environment, whereas using an dead reckoning strategy it can integrate cues generated by its previous movements to return to a just left location. Dead reckoning is colloquially called "sense of direction" and "sense of distance."
Although there is considerable evidence that the hippocampus is involved in piloting (O’Keefe and Nadel, 1978; O’Keefe and Speakman, 1987), there is also evidence from behavioral (Whishaw et al., 1997; Whishaw and Maaswinkel, 1998; Maaswinkel and Whishaw, 1999), modeling (Samsonovich and McNaughton, 1997), and electrophysiological (O’Mare et al., 1994; Sharp et al., 1995; Taube and Burton, 1995; Blair and Sharp, 1996; McNaughton et al., 1996; Wiener, 1996; Golob and Taube, 1997) studies that the hippocampal formation is involved in dead reckoning. The relative contribution of the hippocampus to the two forms of navigation is still uncertain, however. Ordinarily, it is difficult to be certain that an animal is using a piloting versus a dead reckoning strategy because animals are very flexible in their use of strategies and cues (Etienne et al., 1996; Dudchenko et al., 1997; Martin et al., 1997; Maaswinkel and Whishaw, 1999). The objective of the present video demonstrations was to solve the problem of cue specification in order to examine the relative contribution of the hippocampus in the use of these strategies. The rats were trained in a new task in which they followed linear or polygon scented trails to obtain a large food pellet hidden on an open field. Because rats have a proclivity to carry the food back to the refuge, accuracy and the cues used to return to the home base were dependent variables (Whishaw and Tomie, 1997). To force an animal to use a a dead reckoning strategy to reach its refuge with the food, the rats were tested when blindfolded or under infrared light, a spectral wavelength in which they cannot see, and in some experiments the scent trail was additionally removed once an animal reached the food. To examine the relative contribution of the hippocampus, fimbria–fornix (FF) lesions, which disrupt information flow in the hippocampal formation (Bland, 1986), impair memory (Gaffan and Gaffan, 1991), and produce spatial deficits (Whishaw and Jarrard, 1995), were used.
Neuroscience, Issue 26, Dead reckoning, fimbria-fornix, hippocampus, odor tracking, path integration, spatial learning, spatial navigation, piloting, rat, Canadian Centre for Behavioural Neuroscience
Changes in Mammary Gland Morphology and Breast Cancer Risk in Rats
Institutions: Georgetown University, University of Turku Medical Faculty.
Studies in rodent models of breast cancer show that exposures to dietary/hormonal factors during the in utero
and pubertal periods, when the mammary gland undergoes extensive modeling and re-modeling, alter susceptibility to carcinogen-induced mammary tumors. Similar findings have been described in humans: for example, high birthweight increases later risk of developing breast cancer, and dietary intake of soy during childhood decreases breast cancer risk. It is thought that these prenatal and postnatal dietary modifications induce persistent morphological changes in the mammary gland that in turn modify breast cancer risk later in life. These morphological changes likely reflect epigenetic modifications, such as changes in DNA methylation, histones and miRNA expression that then affect gene transcription . In this article we describe how changes in mammary gland morphology can predict mammary cancer risk in rats. Our protocol specifically describes how to dissect and remove the rat abdominal mammary gland and how to prepare mammary gland whole mounts. It also describes how to analyze mammary gland morphology according to three end-points (number of terminal end buds, epithelial elongation and differentiation) and to use the data to predict risk of developing mammary cancer.
Medicine, Issue 44, mammary gland morphology, terminal end buds, mammary cancer, maternal dietary exposures, pregnancy, prepubertal dietay exposures
One Dimensional Turing-Like Handshake Test for Motor Intelligence
Institutions: Ben-Gurion University.
In the Turing test, a computer model is deemed to "think intelligently" if it can generate answers that are not distinguishable from those of a human. However, this test is limited to the linguistic aspects of machine intelligence. A salient function of the brain is the control of movement, and the movement of the human hand is a sophisticated demonstration of this function. Therefore, we propose a Turing-like handshake test, for machine motor intelligence. We administer the test through a telerobotic system in which the interrogator is engaged in a task of holding a robotic stylus and interacting with another party (human or artificial). Instead of asking the interrogator whether the other party is a person or a computer program, we employ a two-alternative forced choice method and ask which of two systems is more human-like. We extract a quantitative grade for each model according to its resemblance to the human handshake motion and name it "Model Human-Likeness Grade" (MHLG). We present three methods to estimate the MHLG. (i) By calculating the proportion of subjects' answers that the model is more human-like than the human; (ii) By comparing two weighted sums of human and model handshakes we fit a psychometric curve and extract the point of subjective equality (PSE); (iii) By comparing a given model with a weighted sum of human and random signal, we fit a psychometric curve to the answers of the interrogator and extract the PSE for the weight of the human in the weighted sum. Altogether, we provide a protocol to test computational models of the human handshake. We believe that building a model is a necessary step in understanding any phenomenon and, in this case, in understanding the neural mechanisms responsible for the generation of the human handshake.
Neuroscience, Issue 46, Turing test, Human Machine Interface, Haptics, Teleoperation, Motor Control, Motor Behavior, Diagnostics, Perception, handshake, telepresence
Studying Cell Rolling Trajectories on Asymmetric Receptor Patterns
Institutions: MIT - Massachusetts Institute of Technology, MIT - Massachusetts Institute of Technology, Brigham and Women's Hospital and Harvard Medical School.
Lateral displacement of cells orthogonal to a flow stream by rolling on asymmetric receptor patterns presents an opportunity for development of new devices for label-free separation and analysis of cells1
. Such devices may use lateral displacement for continuous-flow separation, or receptor patterns that modulate adhesion to distinguish between different cell phenotypes or levels of receptor expression. Understanding the nature of cell rolling trajectories on receptor-patterned substrates is necessary for engineering of the substrates and design of such devices.
Here, we demonstrate a protocol for studying cell rolling trajectories on asymmetric receptor patterns that support cell rolling adhesion2
. Well-defined, μm-scale patterns of P-selectin receptors were fabricated using microcontact printing on gold-coated slides that were incorporated in a flow chamber. HL60 cells expressing the PSGL-1 ligand 3
were flowed across a field of patterned lines and visualized on an inverted bright field microscope. The cells rolled and tracked along the inclined edges of the patterns, resulting in lateral deflection1
. Each cell typically rolled for a certain distance along the pattern edges (defined as the edge tracking length), detached from the edge, and reattached to a downstream pattern. Although this detachment makes it difficult to track the entire trajectory of a cell from entrance to exit in the flow chamber, particle-tracking software was used to analyze and yield the rolling trajectories of the cells during the time when they were moving on a single receptor-patterned line. The trajectories were then examined to obtain distributions of cell rolling velocities and the edge tracking lengths for each cell for different patterns.
This protocol is useful for quantifying cell rolling trajectories on receptor patterns and relating these to engineering parameters such as pattern angle and shear stress. Such data will be useful for design of microfluidic devices for label-free cell separation and analysis.
Bioengineering, Issue 48, cell rolling, microcontact printing, cell adhesion, cell analysis, cell separation, P-selectin
Solid Plate-based Dietary Restriction in Caenorhabditis elegans
Institutions: University of Michigan, University of Michigan.
Reduction of food intake without malnutrition or starvation is known to increase lifespan and delay the onset of various age-related diseases in a wide range of species, including mammals. It also causes a decrease in body weight and fertility, as well as lower levels of plasma glucose, insulin, and IGF-1 in these animals. This treatment is often referred to as dietary restriction (DR) or caloric restriction (CR). The nematode Caenorhabditis elegans
has emerged as an important model organism for studying the biology of aging. Both environmental and genetic manipulations have been used to model DR and have shown to extend lifespan in C. elegans
. However, many of the reported DR studies in C. elegans
were done by propagating animals in liquid media, while most of the genetic studies in the aging field were done on the standard solid agar in petri plates. Here we present a DR protocol using standard solid NGM agar-based plate with killed bacteria.
Developmental Biology, Issue 51, Dietary restriction, caloric restriction, C. elegans, longevity
Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
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
How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index
Institutions: University of Geneva School of Medicine, École Polytechnique Fédérale de Lausanne, University Hospital Center and University of Lausanne, Massachusetts General Hospital.
Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues2
, several methods exist to quantify different characteristics of gyrification. For instance, sulcal morphometry can be used to measure shape descriptors such as the depth, length or indices of inter-hemispheric asymmetry3
. These geometrical properties have the advantage of being easy to interpret. However, sulcal morphometry tightly relies on the accurate identification of a given set of sulci and hence provides a fragmented description of gyrification. A more fine-grained quantification of gyrification can be achieved with curvature-based measurements, where smoothed absolute mean curvature is typically computed at thousands of points over the cortical surface4
. The curvature is however not straightforward to comprehend, as it remains unclear if there is any direct relationship between the curvedness and a biologically meaningful correlate such as cortical volume or surface. To address the diverse issues raised by the measurement of cortical folding, we previously developed an algorithm to quantify local gyrification with an exquisite spatial resolution and of simple interpretation. Our method is inspired of the Gyrification Index5
, a method originally used in comparative neuroanatomy to evaluate the cortical folding differences across species. In our implementation, which we name l
ocal Gyrification Index (l
), we measure the amount of cortex buried within the sulcal folds as compared with the amount of visible cortex in circular regions of interest. Given that the cortex grows primarily through radial expansion6
, our method was specifically designed to identify early defects of cortical development.
In this article, we detail the computation of local Gyrification Index, which is now freely distributed as a part of the FreeSurfer
Software (http://surfer.nmr.mgh.harvard.edu/, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). FreeSurfer
provides a set of automated reconstruction tools of the brain's cortical surface from structural MRI data. The cortical surface extracted in the native space of the images with sub-millimeter accuracy is then further used for the creation of an outer surface, which will serve as a basis for the l
GI calculation. A circular region of interest is then delineated on the outer surface, and its corresponding region of interest on the cortical surface is identified using a matching algorithm as described in our validation study1
. This process is repeatedly iterated with largely overlapping regions of interest, resulting in cortical maps of gyrification for subsequent statistical comparisons (Fig. 1). Of note, another measurement of local gyrification with a similar inspiration was proposed by Toro and colleagues7
, where the folding index at each point is computed as the ratio of the cortical area contained in a sphere divided by the area of a disc with the same radius. The two implementations differ in that the one by Toro et al. is based on Euclidian distances and thus considers discontinuous patches of cortical area, whereas ours uses a strict geodesic algorithm and include only the continuous patch of cortical area opening at the brain surface in a circular region of interest.
Medicine, Issue 59, neuroimaging, brain, cortical complexity, cortical development
The Ladder Rung Walking Task: A Scoring System and its Practical Application.
Institutions: University of Lethbridge.
Progress in the development of animal models for/stroke, spinal cord injury, and other neurodegenerative disease requires tests of high sensitivity to elaborate distinct aspects of motor function and to determine even subtle loss of movement capacity. To enhance efficacy and resolution of testing, tests should permit qualitative and quantitative measures of motor function and be sensitive to changes in performance during recovery periods. The present study describes a new task to assess skilled walking in the rat to measure both forelimb and hindlimb function at the same time. Animals are required to walk along a horizontal ladder on which the spacing of the rungs is variable and is periodically changed. Changes in rung spacing prevent animals from learning the absolute and relative location of the rungs and so minimize the ability of the animals to compensate for impairments through learning. In addition, changing the spacing between the rungs allows the test to be used repeatedly in long-term studies. Methods are described for both quantitative and qualitative description of both fore- and hindlimb performance, including limb placing, stepping, co-ordination. Furthermore, use of compensatory strategies is indicated by missteps or compensatory steps in response to another limb’s misplacement.
Neuroscience, Issue 28, rat, animal model of walking, skilled movement, ladder test, rung test, neuroscience
Use of Rotorod as a Method for the Qualitative Analysis of Walking in Rat
Institutions: University of Lethbridge.
High speed videoanalysis of the details of movement can provide a source of information about qualitative aspects of walking movements. When walking on a rotorod, animals remain in approximately the same place making repetitive movements of stepping. Thus the task provides a rich source of information on the details of foot stepping movements. Subjects were hemi-Parkinson analogue rats, produced by injection of 6-hydroxydopamine (6-OHDA) into the right nigrostriatal bundle to deplete nigrostriatal dopamine (DA). The present report provides a video analysis illustration of animals previously were filmed from frontal, lateral, and posterior views as they walked (15). Rating scales and frame-by-frame replay of the video records of stepping behavior indicated that the hemi-Parkinson rats were chronically impaired in posture and limb use contralateral to the DA-depletion. The contralateral limbs participated less in initiating and sustaining propulsion than the ipsilateral limbs. These deficits secondary to unilateral DA-depletion show that the rotorod provides a use task for the analysis of stepping movements.
Neuroscience, Issue 22, Rat walking, gait analysis, rotorod, rat forelimb, Parkinson disease model, dopamine depletion