Name: cortical source analysis of high-density eeg recordings in children
Uploaded: 2014-06-30T15:00:00
Description: Watch this Scientific Journal Video about Cortical Source Analysis of High-Density EEG Recordings in Children at JoVE.com

We want to thank Prof. John Richards, University of South Carolina, for granting us access to the Developmental MRI database and helpful discussions. We would also like to thank our funders Great Ormond Street Children&#8217;s Charity, UCL Impact &#38; Grand Challenges.

1. Designing EEG &#38; Event related potential experiments for children
Note: A simple experiment was designed for the purposes of this article that may be used to investigate face processing in young children. The following section will describe the experiment and explain how to implement it using MATLAB&#160;R2012b and Psychtoolbox V3.0.1123,24.&#160; Pictures taken from the NimStim set of emotional facial expression25 were used for this example. This stimulus set is avai...

<ol>
	<li>Michel, C. M., Murray, M. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Towards+the+utilization+of+EEG+as+a+brain+imaging+tool.">Towards the utilization of EEG as a brain imaging tool.</a> NeuroImage. 61 (2), 371-385 (2012).</li><li>Brodbeck, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EEG+microstates+of+wakefulness+and+NREM+sleep.">EEG microstates of wakefulness and NREM sleep.</a> NeuroImage. 62 (3), 2129-2139 (2012).</li><li>Sanchez, C. E., Richards, J. E., Almli, C. 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The present article describes the recording and analysis of high density EEG for reconstruction of cortical generators using boundary element models based on age appropriate average MRI templates and depth weighted minimum norm estimation in a standard ERP paradigm suitable for children. In this paradigm, pictures of faces and scrambled faces are presented. Different authors used this paradigm to investigate the development of face processing mechanisms over development35. On the channel level, more negative d...

President Barack Obama described the human brain as the next frontier of scientific discovery with high importance for health and economy3&#160;(http://www.whitehouse.gov/share/brain-initiative). However,&#160;like any other field in the natural sciences, neuroscience depends on advances in methodologies and analysis techniques for progress. Two commonly used non invasive tools in studies about brain function in humans are magnetic resonance imaging (MRI) and electroencephalography (EEG). These tool exploit different physical properties and provide different insights into brain function with unique advantages and disadvantages. MRI uses the magnetic properties of water molecules within magnetic fields to obtain images of living tissues. The subject needs to be placed in a magnet with high field strength. The participant&#39;s movement is restricted during this procedures and the participant has to tolerate noise caused by rapid changes in the magnetic field. In addition to structural images, MRI also provides the possibility to measure changes in blood oxygenation to investigate brain function (fMRI). In summary, MRI offers relatively high spatial resolution of up to 0.5 mm3 with modern high fields scanners and optimized parameters4. In contrast, the temporal resolution of fMRI is limited to the slow kinetics of the BOLD response, which only indirectly reflects the high temporal dynamics of neural activity5,6.
On the other hand, EEG measures changes in electrical activity caused by the activity of neurons through electrodes placed on the scalp. Recent advances in EEG technology allow quick and easy application of the sensors for short term or long term and stationary as well as ambulatory recordings. Because EEG is less restrictive, it is also the method of choice for certain participant populations that do not tolerate the MRI environment well like pediatric and certain geriatric and psychiatric populations. The properties of EEG show an inverse pattern to those of MRI: the temporal resolution is very high with millisecond precision, but the spatial resolution is limited. Electrical currents pass through different tissues between their generator and the EEG electrodes on the surface of the scalp. This leads to mixing and spatial smearing of source activity known as the volume conduction effect. Therefore, activity measured by the electrodes on the surface of the scalp reflects activity from multiple sources that might be distant to the position of the electrode on the head1,7.
Much work in recent years has been dedicated to the merging of MRI and EEG in order to take advantage of their respective strengths. One line of work is dedicated to the simultaneous acquisition of EEG and MRI in functional studies. Another approach is to use the spatial information provided by structural MRI to take account of the volume conduction effect through biophysical modelling. The use of structural information for source reconstruction of EEG recordings is particularly useful for studies involving a pediatric population. The investigation of the development of brain function is central to understanding how complex cognitive skills are built on top of simple precursors8.
These investigations help to highlight changes in the neural substrates and response properties that correlate with changes in behavioral performance. However, the investigation of brain function and cognition during development also poses specific challenges. Particularly, the opportunity for functional MRI studies is limited as young children and infants either have to be asleep or sedated to obtain MRI data without movement artifacts and negative impact on participant wellbeing. Further, EEG is perceived as less risky and invasive by parents, which makes the recruitment of research participants easier. Therefore, EEG is the method of choice for many investigations of brain function in young children. Methodological advances in EEG systems allow the application of high density electrode arrays with 128 or more channels within minutes. Ease of application and wearing comfort are sufficient to even allow EEG recording in the youngest infants. However, often researchers are not only interested in the temporal dynamics of responses to particular stimuli, but would also like to compare the neural substrates that mediate the responses.
A prevailing assumption in channel level ERP analysis comparing different age groups is that the same neural substrates respond, but that the timing or response amplitude varies across ages9. Similar scalp topography is often used as an indicator of similar underlying neural activity. However, many different source configurations can lead to similar scalp topographies10. By applying source estimation, this uncertainty can be reduced and quantified. The independence of observations is critical for network accounts of brain function: if the sources are mixed, correlations will be biased towards higher local connectivity. Source reconstruction can be applied to reduce this bias11. Alternatively, differences in timing and phase can be used for connectivity analysis, but these mathematical models require assumptions that are hard to evaluate in non simulated data12. In summary, source estimation provides additional information to channel level EEG and ERP analysis based on knowledge about anatomy and biophysical properties of tissue.
Different algorithms have been devised to find solutions to the inverse problem. These algorithms fall broadly into two categories: parametric and non parametric13. Parametric models assume one or multiple dipoles that may vary in location, orientation and strength. In contrast, non parametric models contain a large number of dipoles with fixed location and orientation. In these models, the scalp electrical activity is explained as a combination of activations in the fixed dipoles10,13,14. Non parametric, distributed source models can be based on knowledge about anatomy and conductivity in different media. Boundary Element Models incorporate conductivity values for the main tissues of the head with different shells for the brain, cerebro spinal fluid, and skull. This is based on the assumption that conductivity is mostly constant within each compartment, but that marked changes occur at the boundary of different compartments. Finite element models are based on further segmentation of MR scans into grey and white matter so that conductivity values can be assigned to each voxel15.
In practical terms, non parametric models are particularly useful for source reconstruction in complex cognitive tasks, in which the number of areas involved may not be known10. Boundary element models are most widely used in the current literature, probably because the more accurate Finite Element Models pose comparably high computational demands. Further, there is considerable inter individual variability in grey and white matter so that FEMs should be based on individual MRI scans.
Non parametric models require a second step for matching the scalp measured activity to the predictions of the forward model. Again, different approaches with different advantages and drawbacks have been discussed in the literature (see Michel et al. 2004 for an overview). The most widely used algorithms are based on minimum norm estimation (MNE), which matches the scalp measured activity to a current distribution in the forward model with the lowest overall intensity16. MNE is biased towards weak and superficial sources. Depth weighted MNE algorithms try to reduce the surface bias by introducing weighting matrices based on mathematical assumptions10. The widely used LORETA approach is also based on weighted MNE, but additionally minimizes the Laplacian of sources, which leads to smoother solutions17,18. LORETA has been found to perform best for single sources in simulation studies19,20. However, LORETA may lead to over smoothing of solutions. Depth weighted MNE is preferable when the sources are unknown or multiple sources are likely to be present13,16. Comparing the results of different algorithms to evaluate the influence of different model assumptions is recommended.
In summary, source reconstruction through modelling methods has been limited for children until recently. This is because most EEG analysis software relies on head models based on adult anatomy that substantially limits the accuracy of source solutions in children2,8. The cheap access to computational power and the provision of user friendly software for source reconstruction make it possible to overcome these limitations. Applying source estimation to the EEG provides two important advantages over analysis based on channel level observations alone: improved spatial resolution and independence of observations.
Source estimation may not be informative in some cases: good coverage of the head is required to distinguish sources. High density systems with 128 or more electrodes are recommended10,15; a sparser coverage will act as a spatial filter leading to more wide spread source activation or false negative results10. Furthermore, source reconstruction based on the method described in this article has only been reported for cortical generators. Therefore, it is less suitable for testing hypotheses about subcortical substrates or cortical subcortical interactions. Lastly, source analysis should be based on detailed prior hypotheses about the cortical substrates, taking the existing literature from other imaging modalities into account. Spatial filtering techniques may also be used to improve the spatial resolution of the EEG signal by reducing spatial mixing on the scalp level. Alternative methods to reduce the influence of volume conduction effects without head modelling are used, e.g., Laplacian filtering21 or Current Source Density analysis22. However, these methods do not provide more information about neural generators as volume conduction effects are not only restricted to sensors in close spatial proximity1.
In the following sections, the article describes how experiments for the investigation of brain and cognitive function in children from 2 years of age are designed at the London Baby Lab. Next, EEG data acquisition with high&#160;density low impedance systems with children is discussed. Then, EEG preprocessing and analysis on the channel level is presented. Lastly, the article focuses on the processing of structural MRI data for cortical source reconstruction and analysis of source level signals.

<table border="0" cellpadding="0" cellspacing="0" width="1256">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:473px;">High-density EEG sensor net (128 or 256 channels)</td>
			<td style="width:448px;">HydroCel Geodesic Sensor Net 128</td>
			<td style="width:247px;">Electrical Geodesic Inc., Oregon, US</td>
			<td style="width:88px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">EEG high impendance amplifier</td>
			<td>NetAmps 200</td>
			<td>Electrical Geodesic Inc., Oregon, US</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Data Acquisition Computer&#160;</td>
			<td>PowerMac G4</td>
			<td>Apple Inc, California, US</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Stimulus Presentation Computer</td>
			<td>Optiplex 745</td>
			<td>Dell Computers Inc., Texas, US</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Stimulus Presentation Software</td>
			<td>Matlab R2012b with PsychToolBox</td>
			<td>Brainard et al. 1997</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">EEG recording software</td>
			<td>NetStation 4.5.1</td>
			<td>Electrical Geodesic Inc., Oregon, US</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">EEG analysis software</td>
			<td>Matlab R2012b</td>
			<td>The Mathworks Inc.,&#160;</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;"></td>
			<td>EEGLAB</td>
			<td>Delorme et al. 2004</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;"></td>
			<td>BrainStorm</td>
			<td>Sylvain et al. 2001</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MRI processing software</td>
			<td>FreeSurfer</td>
			<td>Fischl et al. 2004</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;"></td>
			<td>OpenMEEG</td>
			<td>Gramfort et al. 2010</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;"></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">References</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td colspan="4" height="21" style="height:21px;">Delorme, A., &#38; Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9&#8211;21.</td>
		</tr>
		<tr height="21">
			<td colspan="3" height="21" style="height:21px;">Sylvain, B., John, C., Dimitrios, P., &#38; Richard, M. (2011). Brainstorm: A User-Friendly Application for MEG/EEG Analysis. Computational Intelligence and Neuroscience, 2011, 1&#8211;13.</td>
			<td></td>
		</tr>
		<tr height="21">
			<td colspan="3" height="21" style="height:21px;">Fischl, B., Van Der Kouwe, A., Destrieux, C., Halgren, E., S&#233;gonne, F., Salat, D. H., et al. (2004). Automatically parcellating the human cerebral cortex. Cerebral Cortex, 14(1), 11&#8211;22.</td>
			<td></td>
		</tr>
		<tr height="21">
			<td colspan="4" height="21" style="height:21px;">Gramfort, A., Papadopoulo, T., Olivi, E., &#38; Clerc, M. (2010). OpenMEEG: opensource software for quasistatic bioelectromagnetics. BioMedical Engineering OnLine, 9(1), 45. doi:10.1186/1475-925X-9-45</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Brainard, D. H. (1997). The psychophysics toolbox. Spatial vision.</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

cortical source analysis of high-density eeg recordings in children

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.&#160;
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&#160;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.&#160;

Designing ERP experiments for infants and children is often challenging, because of their limited capacity to tolerate long repetitive experiments30. This problem is further aggravated when the experimenter plans to apply source reconstruction, because accurate source reconstruction will require a high signal to noise ratio1. Figure 1 displays an experimental protocol for the investigation of face processing mechanisms that can be used with very young children. The paradigm is adapt...

Watch this Scientific Journal Video about Cortical Source Analysis of High-Density EEG Recordings in Children at JoVE.com

Cortical Source Analysis of High-Density EEG Recordings in Children

In recent years, there has been increasing interest in estimating the cortical sources of scalp measured electrical activity for cognitive neuroscience experiments. This article describes how high density EEG is acquired and how recordings are processed for cortical source estimation in children from the age of 2 years at the London Baby Lab.

EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and ...

cortical-source-analysis-of-high-density-eeg-recordings-in-children

Research

JoVE Journal

Behavior

Quantitative Assessment of Cortical Auditory-tactile Processing in Children with Disabilities

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology to quantitatively assess children&#39;s cortical processing of light touch, speech sounds and the multisensory processing of the 2 stimuli, without requiring active subject participation or causing children discomfort. To accomplish this we developed a dual channel, time and strength calibrated air puff stimulator that allows both tactile stimulation and sham control. We combined this with the use of event-related potential methodology to allow for high temporal resolution of signals from the primary and secondary somatosensory cortices as well as higher order processing. This methodology also allowed us to measure a multisensory response to auditory-tactile stimulation.

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology to quantitatively assess infants and children&#39;s cortical processing of light touch, speech sounds, and the multisensory processing of the 2 stimuli, without requiring active subject participation or causing discomfort in vulnerable patients.

Objective and easy measurement of sensory processing is extremely difficult in nonverbal or vulnerable pediatric patients. We developed a new methodology ...

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with schizophrenia who are at familial high risk (FHR) may show similar cognitive and emotional changes. However, the neurological changes underlying the emergence of these symptoms remain unclear. This study sought to identify differences in frontal, striatal, and limbic regions in children and adolescents with FHR using functional magnetic resonance imaging. Groups of 21 children and adolescents at FHR and 21 healthy controls completed an emotional oddball task that relied on selective attention and the suppression of task-irrelevant emotional information. The standard oddball task was modified to include aversive and neutral distractors in order to examine potential group differences in both emotional and executive processing. This task was designed specifically to allow for children and adolescents to complete by keeping the difficulty and emotional image content age-appropriate. Furthermore, we demonstrate a technique for suitable fMRI registration for children and adolescent participants. This paradigm may also be applied in future studies to measure changes in neural activity in other populations with hypothesized developmental changes in executive and emotional processing.

This paper describes how to use the emotional oddball task and fMRI to measure brain activation in children and adolescents at familial high risk for schizophrenia (FHR).&#160;FMRI was used to measure differences in fronto-striato-limbic regions during an emotional oddball task. Children with FHR exhibited abnormal functional activation during adolescence.

Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with ...

Measuring Attentional Biases for Threat in Children and Adults

Investigators have long been interested in the human propensity for the rapid detection of threatening stimuli. However, until recently, research in this domain has focused almost exclusively on adult participants, completely ignoring the topic of threat detection over the course of development. One of the biggest reasons for the lack of developmental work in this area is likely the absence of a reliable paradigm that can measure perceptual biases for threat in children. To address this issue, we recently designed a modified visual search paradigm similar to the standard adult paradigm that is appropriate for studying threat detection in preschool-aged participants. Here we describe this new procedure. In the general paradigm, we present participants with matrices of color photographs, and ask them to find and touch a target on the screen. Latency to touch the target is recorded. Using a touch-screen monitor makes the procedure simple and easy, allowing us to collect data in participants ranging from 3 years of age to adults. Thus far, the paradigm has consistently shown that both adults and children detect threatening stimuli (e.g., snakes, spiders, angry/fearful faces) more quickly than neutral stimuli (e.g., flowers, mushrooms, happy/neutral faces). Altogether, this procedure provides an important new tool for researchers interested in studying the development of attentional biases for threat.

Here we describe a touch-screen visual search paradigm that can be used to study threat detection across the lifespan. The paradigm has already been used in various studies demonstrating that both children and adults detect threatening stimuli like snakes, spiders, and angry faces faster than non-threatening stimuli.

Investigators have long been interested in the human propensity for the rapid detection of threatening stimuli. However, until recently, research in this ...

Testing Sensory and Multisensory Function in Children with Autism Spectrum Disorder

In addition to impairments in social communication and the presence of restricted interests and repetitive behaviors, deficits in sensory processing are now recognized as a core symptom in autism spectrum disorder (ASD). Our ability to perceive and interact with the external world is rooted in sensory processing. For example, listening to a conversation entails processing the auditory cues coming from the speaker (speech content, prosody, syntax) as well as the associated visual information (facial expressions, gestures). Collectively, the &#8220;integration&#8221; of these multisensory (i.e., combined audiovisual) pieces of information results in better comprehension. Such multisensory integration has been shown to be strongly dependent upon the temporal relationship of the paired stimuli. Thus, stimuli that occur in close temporal proximity are highly likely to result in behavioral and perceptual benefits &#8211; gains believed to be reflective of the perceptual system&#39;s judgment of the likelihood that these two stimuli came from the same source. Changes in this temporal integration are expected to strongly alter perceptual processes, and are likely to diminish the ability to accurately perceive and interact with our world. Here, a battery of tasks designed to characterize various aspects of sensory and multisensory temporal processing in children with ASD is described. In addition to its utility in autism, this battery has great potential for characterizing changes in sensory function in other clinical populations, as well as being used to examine changes in these processes across the lifespan.

We describe how to implement a battery of behavioral tasks to examine the processing and integration of sensory stimuli in children with ASD. The goal is to characterize individual differences in temporal processing of simple auditory and visual stimuli and relate these to higher order perceptual skills like speech perception.

In addition to impairments in social communication and the presence of restricted interests and repetitive behaviors, deficits in sensory processing are ...

Psychophysical Tracking Method to Measure Taste Preferences in Children and Adults

The Monell two-series, forced-choice, paired-comparison tracking method provides a reliable measure of sweet taste preferences from childhood to adulthood. The method, which is identical for children, adolescents, and adults, is of short duration (&#60; 15 min), does not rely on sustained attention or place demands on memory (which would yield spurious age differences), and minimizes the impact of language development, making this method amenable to the cognitive limitations of pediatric populations. In this whole-mouth tasting method, subjects are asked to taste (without swallowing) pairs of solutions of different sucrose concentrations and to point to the solution they prefer. Each subsequent pair contains the participant&#39;s preceding preferred concentration and an adjacent stimulus concentration. The procedure continues until the subject chooses either a given concentration of sucrose when paired with both a higher and a lower concentration, or the highest or lowest concentration two consecutive times. Subjects are prevented from reaching response criteria on the basis of first or second position bias by the two-series design of the method, which counterbalances the order of solution presentation within each pair between the series (the weaker concentration is presented first in Series 1, second in Series 2). The geometric mean of the two sucrose concentrations chosen in Series 1 and 2 is an estimate of the participant&#39;s most preferred level of sucrose. Sucrose preference as determined with this laboratory-based measure has been shown to be associated with preference for sugars in foods and beverages and with taste receptor genotype, family history of alcoholism, and race/ethnicity, as well as depressive symptomatology among pediatric populations. The method has real-world relevance and has been applied to determine most preferred level of other tastes (e.g., salt), making it a valuable psychophysical tool.

Sweet taste has powerful hedonic appeal among people of all ages, particularly children. Described herein is a reliable and valid method that can be used to determine the level of sweetness most preferred, making it a valuable psychophysical tool for scientists.

The Monell two-series, forced-choice, paired-comparison tracking method provides a reliable measure of sweet taste preferences from childhood to ...

Automatic Detection of Highly Organized Theta Oscillations in the Murine EEG

Theta activity is generated in the septohippocampal system and can be recorded using deep intrahippocampal electrodes and implantable electroencephalography (EEG) radiotelemetry or tether system approaches. Pharmacologically, hippocampal theta is heterogeneous (see dualistic theory) and can be differentiated into type I and type II theta. These individual EEG subtypes are related to specific cognitive and behavioral states, such as arousal, exploration, learning and memory, higher integrative functions, etc. In neurodegenerative diseases such as Alzheimer&#39;s, structural and functional alterations of the septohippocampal system can result in impaired theta activity/oscillations. A standard quantitative analysis of the hippocampal EEG includes a Fast-Fourier-Transformation (FFT)-based frequency analysis. However, this procedure does not provide details about theta activity in general and highly-organized theta oscillations in particular. In order to obtain detailed information on highly-organized theta oscillations in the hippocampus, we have developed a new analytical approach. This approach allows for time- and cost-effective quantification of the duration of highly-organized theta oscillations and their frequency characteristics.

Theta activity in the hippocampus is related to specific cognitive and behavioral stages. Here, we describe an analytical method to detect highly-organized theta oscillations within the hippocampus using a time-frequency (i.e., wavelet analysis)-based approach.

Theta activity is generated in the septohippocampal system and can be recorded using deep intrahippocampal electrodes and implantable ...

Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children &#8211; Working Memory (CABC-WM)

The Comprehensive Assessment Battery for Children - Working Memory (CABC-WM) is a computer-based battery designed to assess different components of working memory in young school-age children. Working memory deficits have been identified in children with language-based learning disabilities, including dyslexia1,2 and language impairment3,4, but it is not clear whether these children exhibit deficits in subcomponents of working memory, such as visuospatial or phonological working memory. The CABC-WM is administered on a desktop computer with a touchscreen interface and was specifically developed to be engaging and motivating for children. Although the long-term goal of the CABC-WM is to provide individualized working memory profiles in children, the present study focuses on the initial success and utility of the CABC-WM for measuring central executive, visuospatial, phonological loop, and binding constructs in children with typical development. Immediate next steps are to administer the CABC-WM to children with specific language impairment, dyslexia, and comorbid specific language impairment and dyslexia.

Working memory predicts a significant amount of variance for a variety of cognitive tasks, including speaking, reading, and writing. However, few tools are available to assess working memory in children. We present an innovative, computer-based battery that comprehensively assesses different components of working memory in school-age children.

The Comprehensive Assessment Battery for Children - Working Memory (CABC-WM) is a computer-based battery designed to assess different components of ...

Reversible Cooling-induced Deactivations to Study Cortical Contributions to Obstacle Memory in the Walking Cat

On complex, naturalistic terrain, sensory information about an environmental obstacle can be used to rapidly adjust locomotor movements for avoidance. For example, in the cat, visual information about an impending obstacle can modulate stepping for avoidance. Locomotor adaptation can also occur independent of vision, as sudden tactile inputs to the leg by an expected obstacle can modify the stepping of all four legs for avoidance. Such complex locomotor coordination involves supraspinal structures, such as the parietal cortex. This protocol describes the use of reversible, cooling-induced cortical deactivation to assess parietal cortex contributions to memory-guided obstacle locomotion in the cat. Small cooling loops, known as cryoloops, are specially shaped to deactivate discrete regions of interest to assess their contributions to an overt behavior. Such methods have been used to elucidate the role of parietal area 5 in memory-guided obstacle avoidance in the cat.

Complex locomotion in naturalistic environments requiring careful coordination of the limbs involves regions of the parietal cortex. The following protocol describes the use of reversible cooling-induced deactivation to demonstrate the role of parietal area 5 in memory-guided obstacle avoidance in the walking cat.

On complex, naturalistic terrain, sensory information about an environmental obstacle can be used to rapidly adjust locomotor movements for avoidance. For ...

Classical Short-Delay Eyeblink Conditioning in One-Year-Old Children

Classical eyeblink conditioning (EBC) refers to the learned association between a conditioned stimulus (an auditory tone) and an unconditioned stimulus (a puff of air to the cornea). Eyeblink conditioning is often used experimentally to detect abnormalities in cerebellar-dependent learning and memory that underlies this type of associative learning. While experiments in adults and older children are relatively simple to administer using commercial equipment, eyeblink conditioning in infants is more challenging due to their poor compliance, which makes correct positioning of the equipment difficult. To achieve conditioning in one-year-old infants, a custom-made or an adapted commercial system can be used to deliver the air puff to the infant's cornea. The main challenge lies in successfully detecting and classifying the behavioral responses. We report that automated blink detection methods are unreliable in this population, and that conditioning experiments should be analyzed using frame-by-frame analysis of supplementary video camera recordings. This method can be applied to study developmental changes in eyeblink conditioning and to examine whether this paradigm can detect children with neurological disorders.

This protocol describes an eyeblink conditioning paradigm appropriate for experiments with one-year-old infants. Commercial or custom-made equipment can be used to deliver the stimuli, and data collection and analysis should be performed on the video recordings.

Classical eyeblink conditioning (EBC) refers to the learned association between a conditioned stimulus (an auditory tone) and an unconditioned stimulus (a ...

An Electrophysiology Protocol to Measure Reward Anticipation and Processing in Children

We present a protocol designed to measure the neural correlates of reward in children. The protocol allows researchers to measure both reward anticipation and processing. Its purpose is to create a reward task that is appropriate for young children with and without autism while controlling reward properties between two conditions: social and nonsocial. The current protocol allows for comparisons of brain activity between social and nonsocial reward conditions while keeping the reward itself identical between conditions. Using this protocol, we found evidence that neurotypical children demonstrate enhanced anticipatory brain activity during the social condition. Furthermore, we found that neurotypical children anticipate social reward more robustly than children with autism diagnoses. As the task uses snacks as a reward, it is most appropriate for young children. However, the protocol may be adapted for use with adolescent or adult populations if snacks are replaced by monetary incentives. The protocol is designed to measure electrophysiological events (event-related potentials), but it may be customized for use with eye-tracking or fMRI.

This protocol is designed to measure reward anticipation and processing in young children with and without autism. Specifically, the protocol is designed to study the neural correlates of reward during social and nonsocial conditions while controlling for reward between conditions.

We present a protocol designed to measure the neural correlates of reward in children. The protocol allows researchers to measure both reward anticipation ...