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.
23 Related JoVE Articles!
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
Investigating Protein-protein Interactions in Live Cells Using Bioluminescence Resonance Energy Transfer
Institutions: Max Planck Institute for Psycholinguistics, Donders Institute for Brain, Cognition and Behaviour.
Assays based on Bioluminescence Resonance Energy Transfer (BRET) provide a sensitive and reliable means to monitor protein-protein interactions in live cells. BRET is the non-radiative transfer of energy from a 'donor' luciferase enzyme to an 'acceptor' fluorescent protein. In the most common configuration of this assay, the donor is Renilla reniformis
luciferase and the acceptor is Yellow Fluorescent Protein (YFP). Because the efficiency of energy transfer is strongly distance-dependent, observation of the BRET phenomenon requires that the donor and acceptor be in close proximity. To test for an interaction between two proteins of interest in cultured mammalian cells, one protein is expressed as a fusion with luciferase and the second as a fusion with YFP. An interaction between the two proteins of interest may bring the donor and acceptor sufficiently close for energy transfer to occur. Compared to other techniques for investigating protein-protein interactions, the BRET assay is sensitive, requires little hands-on time and few reagents, and is able to detect interactions which are weak, transient, or dependent on the biochemical environment found within a live cell. It is therefore an ideal approach for confirming putative interactions suggested by yeast two-hybrid or mass spectrometry proteomics studies, and in addition it is well-suited for mapping interacting regions, assessing the effect of post-translational modifications on protein-protein interactions, and evaluating the impact of mutations identified in patient DNA.
Cellular Biology, Issue 87, Protein-protein interactions, Bioluminescence Resonance Energy Transfer, Live cell, Transfection, Luciferase, Yellow Fluorescent Protein, Mutations
Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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
Using Eye Movements to Evaluate the Cognitive Processes Involved in Text Comprehension
Institutions: University of Illinois at Chicago.
The present article describes how to use eye tracking methodologies to study the cognitive processes involved in text comprehension. Measuring eye movements during reading is one of the most precise methods for measuring moment-by-moment (online) processing demands during text comprehension. Cognitive processing demands are reflected by several aspects of eye movement behavior, such as fixation duration, number of fixations, and number of regressions (returning to prior parts of a text). Important properties of eye tracking equipment that researchers need to consider are described, including how frequently the eye position is measured (sampling rate), accuracy of determining eye position, how much head movement is allowed, and ease of use. Also described are properties of stimuli that influence eye movements that need to be controlled in studies of text comprehension, such as the position, frequency, and length of target words. Procedural recommendations related to preparing the participant, setting up and calibrating the equipment, and running a study are given. Representative results are presented to illustrate how data can be evaluated. Although the methodology is described in terms of reading comprehension, much of the information presented can be applied to any study in which participants read verbal stimuli.
Behavior, Issue 83, Eye movements, Eye tracking, Text comprehension, Reading, Cognition
Portable Intermodal Preferential Looking (IPL): Investigating Language Comprehension in Typically Developing Toddlers and Young Children with Autism
Institutions: University of Connecticut.
One of the defining characteristics of autism spectrum disorder (ASD) is difficulty with language and communication.1
Children with ASD's onset of speaking is usually delayed, and many children with ASD consistently produce language less frequently and of lower lexical and grammatical complexity than their typically developing (TD) peers.6,8,12,23
However, children with ASD also exhibit a significant social deficit, and researchers and clinicians continue to debate the extent to which the deficits in social interaction account for or contribute to the deficits in language production.5,14,19,25
Standardized assessments of language in children with ASD usually do include a comprehension component; however, many such comprehension tasks assess just one aspect of language (e.g.
or include a significant motor component (e.g.
, pointing, act-out), and/or require children to deliberately choose between a number of alternatives. These last two behaviors are known to also be challenging to children with ASD.7,12,13,16
We present a method which can assess the language comprehension of young typically developing children (9-36 months) and children with autism.2,4,9,11,22
This method, Portable Intermodal Preferential Looking (P-IPL), projects side-by-side video images from a laptop onto a portable screen. The video images are paired first with a 'baseline' (nondirecting) audio, and then presented again paired with a 'test' linguistic audio that matches only one of the video images. Children's eye movements while watching the video are filmed and later coded. Children who understand the linguistic audio will look more quickly to, and longer at, the video that matches the linguistic audio.2,4,11,18,22,26
This paradigm includes a number of components that have recently been miniaturized (projector, camcorder, digitizer) to enable portability and easy setup in children's homes. This is a crucial point for assessing young children with ASD, who are frequently uncomfortable in new (e.g.
, laboratory) settings. Videos can be created to assess a wide range of specific components of linguistic knowledge, such as Subject-Verb-Object word order, wh-questions, and tense/aspect suffixes on verbs; videos can also assess principles of word learning such as a noun bias, a shape bias, and syntactic bootstrapping.10,14,17,21,24
Videos include characters and speech that are visually and acoustically salient and well tolerated by children with ASD.
Medicine, Issue 70, Neuroscience, Psychology, Behavior, Intermodal preferential looking, language comprehension, children with autism, child development, autism
Training Synesthetic Letter-color Associations by Reading in Color
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
Utilizing Repetitive Transcranial Magnetic Stimulation to Improve Language Function in Stroke Patients with Chronic Non-fluent Aphasia
Institutions: University of Pennsylvania , University of Pennsylvania , Veterans Affairs Boston Healthcare System, Boston University School of Medicine, Boston University School of Medicine.
Transcranial magnetic stimulation (TMS) has been shown to significantly improve language function in patients with non-fluent aphasia1
. In this experiment, we demonstrate the administration of low-frequency repetitive TMS (rTMS) to an optimal stimulation site in the right hemisphere in patients with chronic non-fluent aphasia. A battery of standardized language measures is administered in order to assess baseline performance. Patients are subsequently randomized to either receive real rTMS or initial sham stimulation. Patients in the real stimulation undergo a site-finding phase, comprised of a series of six rTMS sessions administered over five days; stimulation is delivered to a different site in the right frontal lobe during each of these sessions. Each site-finding session consists of 600 pulses of 1 Hz rTMS, preceded and followed by a picture-naming task. By comparing the degree of transient change in naming ability elicited by stimulation of candidate sites, we are able to locate the area of optimal response for each individual patient. We then administer rTMS to this site during the treatment phase. During treatment, patients undergo a total of ten days of stimulation over the span of two weeks; each session is comprised of 20 min of 1 Hz rTMS delivered at 90% resting motor threshold. Stimulation is paired with an fMRI-naming task on the first and last days of treatment. After the treatment phase is complete, the language battery obtained at baseline is repeated two and six months following stimulation in order to identify rTMS-induced changes in performance. The fMRI-naming task is also repeated two and six months following treatment. Patients who are randomized to the sham arm of the study undergo sham site-finding, sham treatment, fMRI-naming studies, and repeat language testing two months after completing sham treatment. Sham patients then cross over into the real stimulation arm, completing real site-finding, real treatment, fMRI, and two- and six-month post-stimulation language testing.
Medicine, Issue 77, Neurobiology, Neuroscience, Anatomy, Physiology, Biomedical Engineering, Molecular Biology, Neurology, Stroke, Aphasia, Transcranial Magnetic Stimulation, TMS, language, neurorehabilitation, optimal site-finding, functional magnetic resonance imaging, fMRI, brain, stimulation, imaging, clinical techniques, clinical applications
Setting-up an In Vitro Model of Rat Blood-brain Barrier (BBB): A Focus on BBB Impermeability and Receptor-mediated Transport
Institutions: VECT-HORUS SAS, CNRS, NICN UMR 7259.
The blood brain barrier (BBB) specifically regulates molecular and cellular flux between the blood and the nervous tissue. Our aim was to develop and characterize a highly reproducible rat syngeneic in vitro
model of the BBB using co-cultures of primary rat brain endothelial cells (RBEC) and astrocytes to study receptors involved in transcytosis across the endothelial cell monolayer. Astrocytes were isolated by mechanical dissection following trypsin digestion and were frozen for later co-culture. RBEC were isolated from 5-week-old rat cortices. The brains were cleaned of meninges and white matter, and mechanically dissociated following enzymatic digestion. Thereafter, the tissue homogenate was centrifuged in bovine serum albumin to separate vessel fragments from nervous tissue. The vessel fragments underwent a second enzymatic digestion to free endothelial cells from their extracellular matrix. The remaining contaminating cells such as pericytes were further eliminated by plating the microvessel fragments in puromycin-containing medium. They were then passaged onto filters for co-culture with astrocytes grown on the bottom of the wells. RBEC expressed high levels of tight junction (TJ) proteins such as occludin, claudin-5 and ZO-1 with a typical localization at the cell borders. The transendothelial electrical resistance (TEER) of brain endothelial monolayers, indicating the tightness of TJs reached 300 ohm·cm2
on average. The endothelial permeability coefficients (Pe) for lucifer yellow (LY) was highly reproducible with an average of 0.26 ± 0.11 x 10-3
cm/min. Brain endothelial cells organized in monolayers expressed the efflux transporter P-glycoprotein (P-gp), showed a polarized transport of rhodamine 123, a ligand for P-gp, and showed specific transport of transferrin-Cy3 and DiILDL across the endothelial cell monolayer. In conclusion, we provide a protocol for setting up an in vitro
BBB model that is highly reproducible due to the quality assurance methods, and that is suitable for research on BBB transporters and receptors.
Medicine, Issue 88, rat brain endothelial cells (RBEC), mouse, spinal cord, tight junction (TJ), receptor-mediated transport (RMT), low density lipoprotein (LDL), LDLR, transferrin, TfR, P-glycoprotein (P-gp), transendothelial electrical resistance (TEER),
A Dual Task Procedure Combined with Rapid Serial Visual Presentation to Test Attentional Blink for Nontargets
Institutions: Dartmouth College.
When viewers search for targets in a rapid serial visual presentation (RSVP) stream, if two targets are presented within about 500 msec of each other, the first target may be easy to spot but the second is likely to be missed. This phenomenon of attentional blink (AB) has been widely studied to probe the temporal capacity of attention for detecting visual targets. However, with the typical procedure of AB experiments, it is not possible to examine how the processing of non-target items in RSVP may be affected by attention. This paper describes a novel dual task procedure combined with RSVP to test effects of AB for nontargets at varied stimulus onset asynchronies (SOAs). In an exemplar experiment, a target category was first displayed, followed by a sequence of 8 nouns. If one of the nouns belonged to the target category, participants would respond ‘yes’ at the end of the sequence, otherwise participants would respond ‘no’. Two 2-alternative forced choice memory tasks followed the response to determine if participants remembered the words immediately before or after the target, as well as a random word from another part of the sequence. In a second exemplar experiment, the same design was used, except that 1) the memory task was counterbalanced into two groups with SOAs of either 120 or 240 msec and 2) three memory tasks followed the sequence and tested remembrance for nontarget nouns in the sequence that could be anywhere from 3 items prior the target noun position to 3 items following the target noun position. Representative results from a previously published study demonstrate that our procedure can be used to examine divergent effects of attention that not only enhance targets but also suppress nontargets. Here we show results from a representative participant that replicated the previous finding.
Behavior, Issue 94, Dual task, attentional blink, RSVP, target detection, recognition, visual psychophysics
Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis
Institutions: Centre for Vision Research, York University, Centre for Vision Research, York University.
The aim of this methods paper is to describe how to implement a neuroimaging technique to examine complementary brain processes engaged by two similar tasks. Participants' behavior during task performance in an fMRI scanner can then be correlated to the brain activity using the blood-oxygen-level-dependent signal. We measure behavior to be able to sort correct trials, where the subject performed the task correctly and then be able to examine the brain signals related to correct performance. Conversely, if subjects do not perform the task correctly, and these trials are included in the same analysis with the correct trials we would introduce trials that were not only for correct performance. Thus, in many cases these errors can be used themselves to then correlate brain activity to them. We describe two complementary tasks that are used in our lab to examine the brain during suppression of an automatic responses: the stroop1
and anti-saccade tasks. The emotional stroop paradigm instructs participants to either report the superimposed emotional 'word' across the affective faces or the facial 'expressions' of the face stimuli1,2
. When the word and the facial expression refer to different emotions, a conflict between what must be said and what is automatically read occurs. The participant has to resolve the conflict between two simultaneously competing processes of word reading and facial expression. Our urge to read out a word leads to strong 'stimulus-response (SR)' associations; hence inhibiting these strong SR's is difficult and participants are prone to making errors. Overcoming this conflict and directing attention away from the face or the word requires the subject to inhibit bottom up processes which typically directs attention to the more salient stimulus. Similarly, in the anti-saccade task3,4,5,6
, where an instruction cue is used to direct only attention to a peripheral stimulus location but then the eye movement is made to the mirror opposite position. Yet again we measure behavior by recording the eye movements of participants which allows for the sorting of the behavioral responses into correct and error trials7
which then can be correlated to brain activity. Neuroimaging now allows researchers to measure different behaviors of correct and error trials that are indicative of different cognitive processes and pinpoint the different neural networks involved.
Neuroscience, Issue 64, fMRI, eyetracking, BOLD, attention, inhibition, Magnetic Resonance Imaging, MRI
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
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
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Institutions: Baylor College of Medicine, Michael E. DeBakey VA Medical Center, University of California, Los Angeles, University of California, Los Angeles.
Functional connectivity MRI (fcMRI) is an fMRI method that examines the connectivity of different brain areas based on the correlation of BOLD signal fluctuations over time. Temporal Lobe Epilepsy (TLE) is the most common type of adult epilepsy and involves multiple brain networks. The default mode network (DMN) is involved in conscious, resting state cognition and is thought to be affected in TLE where seizures cause impairment of consciousness. The DMN in epilepsy was examined using seed based fcMRI. The anterior and posterior hubs of the DMN were used as seeds in this analysis. The results show a disconnection between the anterior and posterior hubs of the DMN in TLE during the basal state. In addition, increased DMN connectivity to other brain regions in left TLE along with decreased connectivity in right TLE is revealed. The analysis demonstrates how seed-based fcMRI can be used to probe cerebral networks in brain disorders such as TLE.
Medicine, Issue 90, Default Mode Network (DMN), Temporal Lobe Epilepsy (TLE), fMRI, MRI, functional connectivity MRI (fcMRI), blood oxygenation level dependent (BOLD)
Transcranial Magnetic Stimulation for Investigating Causal Brain-behavioral Relationships and their Time Course
Institutions: University College London.
Transcranial magnetic stimulation (TMS) is a safe, non-invasive brain stimulation technique that uses a strong electromagnet in order to temporarily disrupt information processing in a brain region, generating a short-lived “virtual lesion.” Stimulation that interferes with task performance indicates that the affected brain region is necessary to perform the task normally. In other words, unlike neuroimaging methods such as functional magnetic resonance imaging (fMRI) that indicate correlations between brain and behavior, TMS can be used to demonstrate causal brain-behavior relations. Furthermore, by varying the duration and onset of the virtual lesion, TMS can also reveal the time course of normal processing. As a result, TMS has become an important tool in cognitive neuroscience. Advantages of the technique over lesion-deficit studies include better spatial-temporal precision of the disruption effect, the ability to use participants as their own control subjects, and the accessibility of participants. Limitations include concurrent auditory and somatosensory stimulation that may influence task performance, limited access to structures more than a few centimeters from the surface of the scalp, and the relatively large space of free parameters that need to be optimized in order for the experiment to work. Experimental designs that give careful consideration to appropriate control conditions help to address these concerns. This article illustrates these issues with TMS results that investigate the spatial and temporal contributions of the left supramarginal gyrus (SMG) to reading.
Behavior, Issue 89,
Transcranial magnetic stimulation, virtual lesion, chronometric, cognition, brain, behavior
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
Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
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
Extracting Visual Evoked Potentials from EEG Data Recorded During fMRI-guided Transcranial Magnetic Stimulation
Institutions: Tel-Aviv University, Tel-Aviv University.
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.
Neuroscience, Issue 87, Transcranial Magnetic Stimulation, Neuroimaging, Neuronavigation, Visual Perception, Evoked Potentials, Electroencephalography, Event-related potential, fMRI, Combined Neuroimaging Methods, Face perception, Body Perception
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
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
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
) (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
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
Investigating Social Cognition in Infants and Adults Using Dense Array Electroencephalography (dEEG)
Institutions: University Toronto Scarborough.
Dense array electroencephalography (d
EEG), which provides a non-invasive window for measuring brain activity and a temporal resolution unsurpassed by any other current brain imaging technology1,2
, is being used increasingly in the study of social cognitive functioning in infants and adults. While d
EEG is enabling researchers to examine brain activity patterns with unprecedented levels of sensitivity, conventional EEG recording systems continue to face certain limitations, including 1) poor spatial resolution and source localization3,4
,2) the physical discomfort for test subjects of enduring the individual application of numerous electrodes to the surface of the scalp, and 3) the complexity for researchers of learning to use multiple software packages to collect and process data. Here we present an overview of an established methodology that represents a significant improvement on conventional methodologies for studying EEG in infants and adults. Although several analytical software techniques can be used to establish indirect indices of source localization to improve the spatial resolution of d
EEG, the HydroCel Geodesic Sensor Net (HCGSN) by Electrical Geodesics, Inc. (EGI), a dense sensory array that maintains equal distances among adjacent recording electrodes on all surfaces of the scalp, further enhances spatial resolution4,5,6
compared to standard d
EEG systems. The sponge-based HCGSN can be applied rapidly and without scalp abrasion, making it ideal for use with adults7,8
, and infants12
, in both research and clinical4,5,6,13,14,15
settings. This feature allows for considerable cost and time savings by decreasing the average net application time compared to other d
EEG systems. Moreover, the HCGSN includes unified, seamless software applications for all phases of data, greatly simplifying the collection, processing, and analysis of d
The HCGSN features a low-profile electrode pedestal, which, when filled with electrolyte solution, creates a sealed microenvironment and an electrode-scalp interface. In all Geodesic d
EEG systems, EEG sensors detect changes in voltage originating from the participant's scalp, along with a small amount of electrical noise originating from the room environment. Electrical signals from all sensors of the Geodesic sensor net are received simultaneously by the amplifier, where they are automatically processed, packaged, and sent to the data-acquisition computer (DAC). Once received by the DAC, scalp electrical activity can be isolated from artifacts for analysis using the filtering and artifact detection tools included in the EGI software. Typically, the HCGSN can be used continuously for only up to two hours because the electrolyte solution dries out over time, gradually decreasing the quality of the scalp-electrode interface.
In the Parent-Infant Research Lab at the University of Toronto, we are using d
EEG to study social cognitive processes including memory, emotion, goals, intentionality, anticipation, and executive functioning in both adult and infant participants.
Neuroscience, Issue 52, Developmental Affective Neuroscience, high density EEG, social cognition, infancy, and parenting
Brain Imaging Investigation of the Memory-Enhancing Effect of Emotion
Institutions: University of Alberta, University of Illinois, Urbana-Champaign, Duke University, University of Illinois, Urbana-Champaign.
Emotional events tend to be better remembered than non-emotional events1,2
. One goal of cognitive and affective neuroscientists is
to understand the neural mechanisms underlying this enhancing effect of emotion on memory. A method that has proven particularly influential in the
investigation of the memory-enhancing effect of emotion is the so-called subsequent memory paradigm (SMP). This method was originally used to investigate the
neural correlates of non-emotional memories3
, and more recently we and others also applied it successfully to studies of emotional memory (reviewed in4, 5-7
Here, we describe a protocol that allows investigation of the neural correlates of the memory-enhancing effect of emotion using the SMP in conjunction with
event-related functional magnetic resonance imaging (fMRI). An important feature of the SMP is that it allows separation of brain activity specifically
associated with memory from more general activity associated with perception. Moreover, in the context of investigating the impact of emotional stimuli,
SMP allows identification of brain regions whose activity is susceptible to emotional modulation of both general/perceptual and memory-specific processing.
This protocol can be used in healthy subjects8-15
, as well as in clinical patients where there are alterations in the neural correlates of emotion perception
and biases in remembering emotional events, such as those suffering from depression and post-traumatic stress disorder (PTSD)16, 17
Neuroscience, Issue 51, Affect, Recognition, Recollection, Dm Effect, Neuroimaging
Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Institutions: University of Alabama at Birmingham.
Newly emerging theories suggest that the brain does not function as a cohesive unit in autism, and this discordance is reflected in the behavioral symptoms displayed by individuals with autism. While structural neuroimaging findings have provided some insights into brain abnormalities in autism, the consistency of such findings is questionable. Functional neuroimaging, on the other hand, has been more fruitful in this regard because autism is a disorder of dynamic processing and allows examination of communication between cortical networks, which appears to be where the underlying problem occurs in autism. Functional connectivity is defined as the temporal correlation of spatially separate neurological events1. Findings from a number of recent fMRI studies have supported the idea that there is weaker coordination between different parts of the brain that should be working together to accomplish complex social or language problems2,3,4,5,6
. One of the mysteries of autism is the coexistence of deficits in several domains along with relatively intact, sometimes enhanced, abilities. Such complex manifestation of autism calls for a global and comprehensive examination of the disorder at the neural level. A compelling recent account of the brain functioning in autism, the cortical underconnectivity theory,2,7
provides an integrating framework for the neurobiological bases of autism. The cortical underconnectivity theory of autism suggests that any language, social, or psychological function that is dependent on the integration of multiple brain regions is susceptible to disruption as the processing demand increases. In autism, the underfunctioning of integrative circuitry in the brain may cause widespread underconnectivity. In other words, people with autism may interpret information in a piecemeal fashion at the expense of the whole. Since cortical underconnectivity among brain regions, especially the frontal cortex and more posterior areas 3,6
, has now been relatively well established, we can begin to further understand brain connectivity as a critical component of autism symptomatology.
A logical next step in this direction is to examine the anatomical connections that may mediate the functional connections mentioned above. Diffusion Tensor Imaging (DTI) is a relatively novel neuroimaging technique that helps probe the diffusion of water in the brain to infer the integrity of white matter fibers. In this technique, water diffusion in the brain is examined in several directions using diffusion gradients. While functional connectivity provides information about the synchronization of brain activation across different brain areas during a task or during rest, DTI helps in understanding the underlying axonal organization which may facilitate the cross-talk among brain areas. This paper will describe these techniques as valuable tools in understanding the brain in autism and the challenges involved in this line of research.
Medicine, Issue 55, Functional magnetic resonance imaging (fMRI), MRI, Diffusion tensor imaging (DTI), Functional Connectivity, Neuroscience, Developmental disorders, Autism, Fractional Anisotropy
Brain Imaging Investigation of the Neural Correlates of Observing Virtual Social Interactions
Institutions: University of Alberta, University of Illinois, University of Alberta, University of Alberta, University of Alberta, University of Illinois at Urbana-Champaign, University of Illinois at Urbana-Champaign.
The ability to gauge social interactions is crucial in the assessment of others’ intentions. Factors such as facial expressions and body language affect our decisions in personal and professional life alike 1
. These "friend or foe
" judgements are often based on first impressions, which in turn may affect our decisions to "approach or avoid
". Previous studies investigating the neural correlates of social cognition tended to use static facial stimuli 2
. Here, we illustrate an experimental design in which whole-body animated characters were used in conjunction with functional magnetic resonance imaging (fMRI) recordings. Fifteen participants were presented with short movie-clips of guest-host interactions in a business setting, while fMRI data were recorded; at the end of each movie, participants also provided ratings of the host behaviour. This design mimics more closely real-life situations, and hence may contribute to better understanding of the neural mechanisms of social interactions in healthy behaviour, and to gaining insight into possible causes of deficits in social behaviour in such clinical conditions as social anxiety and autism 3
Neuroscience, Issue 53, Social Perception, Social Knowledge, Social Cognition Network, Non-Verbal Communication, Decision-Making, Event-Related fMRI