This research was made possible with the support of grants from the National Science and Engineering Research Council (NSERC) to J. Bruce Morton.

1. Obtain Approval for Working with Human Subjects
2. fMRI Data Acquisition
<ol>
	<li>Acquire fMRI data following procedures suitable for young children (see Raschle, et al.12). Make every effort to limit possible age-related differences in task performance and motion, as these differences introduce unwanted confounds that limit one&#39;s capacity to draw inferences about developmentally-relevant differences in brain activation and functional connectivity. 
	Note: In the current protocol, a repeated-trials version of the DCCS was administered in the form of a block design13. Each run includes two 8-trial switch blocks and two 8-trial repeat blocks, where switch blocks consist of 4 switch trials and 4 repeat trials, and repeat blocks consist of 8 repeat trials. The protocol is perfectly suitable for use with event-related fMRI data. However, block designs are nice to work with when first getting acquainted with ICA, as it is easy to see task modulations in the component time courses.</li>
	<li>Preprocess fMRI data following standard fMRI preprocessing procedures.
	<ol>
		<li>Realign all functional images to the same orientation and position. Typically, the first functional volume is used as a reference image for all other volumes to be aligned to.</li>
		<li>Coregister the T1-weighted (anatomical) image with the T2*-weighted (functional) scans, so that activation is superimposed onto the correct anatomical location.</li>
		<li>Normalize all of the images to a standardized size, space, and position with the selection of a template brain (e.g. Talairach space). This helps to ensure that homologous regions from different subjects are being compared. 
		Note: Images are warped to Talairach space in the current protocol, although other templates may also be used (for example, MNI {Montreal Neurological Institute} space).</li>
		<li>Smooth all functional volumes in the data set with a 6&#160;&#160;to 10&#160;mm smoothing kernel.</li>
	</ol>
	</li>
	<li>Sequester preprocessed volumes into a separate set of directories. Use &#34;Functional scans&#34; as the top directory. Within &#34;Functional scans&#34; include a separate directory for each participant, and within each participant directory, a separate directory for each run. The data is now ready for ICA analysis.</li>
</ol>
3. Group&#160;Independent Component Analysis (ICA)
<ol>
	<li>Download and install group ICA software. There are a number of toolboxes available for implementing ICA on different types of neurophysiological data, including fMRI. While any toolbox that performs group ICA would potentially be suitable, the one utilized in the current protocol is called GIFT. GIFT was developed by Vince Calhoun and colleagues at the University of New Mexico. The GIFT toolbox is a set of MATLAB scripts that works together with SPM, a well-known fMRI analysis package. Both can be downloaded for free from the internet (GIFT: mialab.mrn.org/software/gift/index.html#; SPM: www.fil.ion.ucl.ac.uk/spm/).&#160;Once downloaded, add the GIFT toolbox and all sub-directories to the MATLAB search path and save path file.</li>
	<li>Computing a group ICA on fMRI data using GIFT makes substantial demands on RAM memory. The precise demands on memory will vary depending on the number of participants, the amount of data collected from each participant, and the resolution of the data. To avoid memory issues, it is best to run the ICA analysis on a server. If running the analysis on a local computer, the RAM requirements can be estimated through the use of a script &#34;icatb_mem_ica.m&#34; that is part of GIFT.</li>
	<li>Set-up or parameterize the analysis. Do this by modifying a pre-existing batch script called &#34;Input_data_subjects_1.m&#34; that is stored in GIFT under &#34;icatb_batch_files&#34;. 
	Note: This can also be done by using GIFT&#39;s Graphical User Interface. However, it is much easier, with a bit of practice, to set up the analysis by modifying this pre-existing script.
	<ol>
		<li>Specify data modality as fMRI</li>
		<li>Specify Type of Analysis as ICA with ICASSO. This will ensure the ICA is run with the ICASSO procedure. ICASSO estimates the reliability of the decomposition by running the ICA several times starting with different random seeds. It then tests the similarity of each result by means of clustering. Use of ICASSO is recommended as mean of checking the quality of the ICA decomposition, but will considerably extend the time it takes GIFT to complete the analysis.
		<ol>
			<li>To run the ICA with the ICASSO procedure, select &#39;2&#39; under &#34;Type of analysis&#34; and then parameterize the ICASSO procedure in the succeeding lines of the setup file.</li>
		</ol>
		</li>
		<li>Maximize the performance of the group PCA by choosing &#39;1&#39; under Group PCA performance settings. Consider setting this parameter to &#39;2&#39; should problems of insufficient RAM memory occur.</li>
		<li>To enable later sorting of resulting components using predictors from a standard SPM design matrix, specify whether or not there are different matrices for different subjects.</li>
		<li>Specify where the preprocessed functional data are stored and whether an SPM.mat file containing the design matrix is stored together with the preprocessed functional data.
		<ol>
			<li>The most straightforward way of getting GIFT to read the data is if every participant has the same number of runs, and the data directory is structured as described in Step 2.3 under fMRI data acquisition. If so, then under DataSelectionMethod, chose &#39;1&#39; for Method 1, and complete the parameter &#34;sourceDir_filePattern_flagLocation&#34; by including the filepath where the data are stored, the file format of the data, and a statement indicating that individual sessions are stored as subdirectories within each subject folder.</li>
		</ol>
		</li>
		<li>Indicate the directory where the output of the analysis should be written. Do not write the results to the same directory where the data are stored.</li>
		<li>Provide a prefix that will be added to all output files.</li>
		<li>Provide a filepath to a mask. All volumes submitted to ICA are masked. GIFT provides a default mask. For this work, an in-house script to generate a mask from the data that will be submitted to ICA. At a minimum, the mask should eliminate skull, extra-cerebral space, and especially the eyeballs. Signal from eyeball voxels will show very large fluctuations during a run and will therefore have a sizable influence on the structure of the final components. Figure 3&#160;illustrates what a good mask should look like.</li>
		<li>Specify the type of group PCA to be used. Use &#39;subject specific.&#39;</li>
		<li>Specify the back-reconstruction method. In this stage, individual subject IC&#39;s and their associated time courses are computed from the results of the group analysis. GICA is recommended for obtaining the best time courses, although there is considerable discussion in the literature on this point.</li>
		<li>Specify data pre-processing type. Use intensity normalization to avoid non-numerical values (i.e.&#160;infinites, and NaN&#39;s) in the output. In this example, we chose the default of &#39;1&#39;.</li>
		<li>Specify the type of PCA (we use standard) and accept default values under PCA Options. GIFT performs a PCA on each run of each participant and retains a number of components equal to the number of sources to be unmixed in the ICA. The PCA serves two important purposes. First, it helps to eliminate sources of noise that are unique to each participant and each run. Second, it makes the computational demands of the analysis more tractable.</li>
		<li>Specify how many PCAs to run on the data before the ICA (2 is recommended). As well, specify how many components to retain after each PCA (if running 2, it is recommended that the number of components retained after the first PCA is twice the number retained after the second).</li>
		<li>Specify how the data should be scaled. For this work, z-score scaling was used.</li>
		<li>Choose a blind source separation algorithm for the ICA. For this work, Infomax was used. GIFT offers a choice of at least 10 different algorithms.</li>
		<li>Remaining parameters can be left as is.</li>
	</ol>
	</li>
	<li>Once the ICA is completed, select from among available components those that are of potential theoretical interest. Through the GIFT GUI, choose component selection: spatial sorting sorts the spatial components by means of spatial correlation with a pre-existing template; temporal sorting sorts the component time courses by means of linear predictors from the SPM design matrix that you can store with the data (see 3.3.5). 
	Note: Both approaches to component selection have utility. However, when working with task data, temporal selection criteria are particularly useful, as they provide a means of verifying that the selected component was activated by the task. In the case of the DCCS, use of temporal sorting can be used to confirm that the selected component was more active during switch blocks than during repeat blocks.</li>
	<li>Test whether child and adult versions of these selected components differ. Aggregate child and adult components of interest into two separate groups and test by means of a two-sample t-test regions where the components vary. This is relatively easy to do through the GIFT GUI.</li>
</ol>

<ol>
	<li>Diamond, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Normal+Development+of+Prefrontal+Cortex+from+Birth+to+Young+Adulthood:+Cognitive+Functions+Anatomy,+and+Biochemistry.">Normal Development of Prefrontal Cortex from Birth to Young Adulthood: Cognitive Functions Anatomy, and Biochemistry.</a> Principles of Frontal Lobe Function. , 1-38 (2002).</li><li>Zelazo, P. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Dimensional+Change+Card+Sort+(DCCS):+a+method+of+assessing+executive+function+in+children.">The Dimensional Change Card Sort (DCCS): a method of assessing executive function in children.</a> Nat Protoc. 1, 297-301 (2006).</li><li>Monsell, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Task+switching.">Task switching.</a> Trends Cogn Sci (Regul Ed. 7, 134-140 (2003).</li><li>Crone, E. A., Bunge, S. A., van der Molen, M. W., Ridderinkhof, K. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Switching+between+tasks+and+responses:+a+developmental+study.">Switching between tasks and responses: a developmental study.</a> Developmental Science. 9, 278-287 (2006).</li><li>Cole, M. W., Schneider, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+cognitive+control+network:+Integrated+cortical+regions+with+dissociable+functions.">The cognitive control network: Integrated cortical regions with dissociable functions.</a> Neuroimage. 37, 343-360 (2007).</li><li>Fair, D. A., 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=Development+of+distinct+control+networks+through+segregation+and+integration.">Development of distinct control networks through segregation and integration.</a> Proc Natl Acad Sci USA. 104, 13507-13512 (2007).</li><li>Uddin, L. Q., Supekar, K., Menon, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Typical+and+atypical+development+of+functional+human+brain+networks:+insights+from+resting-state+FMRI.">Typical and atypical development of functional human brain networks: insights from resting-state FMRI.</a> Frontiers in systems neuroscience. 4, (2010).</li><li>Calhoun, V. D., Adali, T., Pearlson, G. D., Pekar, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+method+for+making+group+inferences+from+functional+MRI+data+using+independent+component+analysis.">A method for making group inferences from functional MRI data using independent component analysis.</a> Human brain mapping. 14, 140-151 (2001).</li><li>Fransson, P., 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=Resting-state+networks+in+the+infant+brain.">Resting-state networks in the infant brain.</a> Proceedings of the National Academy of Sciences of the United States of America. 104, 15531-15536 (2007).</li><li>Supekar, K., Menon, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Developmental+maturation+of+dynamic+causal+control+signals+in+higher-order+cognition:+a+neurocognitive+network+model.">Developmental maturation of dynamic causal control signals in higher-order cognition: a neurocognitive network model.</a> PLoS computational biology. 8, (2012).</li><li>Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., Petersen, S. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spurious+but+systematic+correlations+in+functional+connectivity+MRI+networks+arise+from+subject+motion.">Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.</a> Neuroimage. 59, 2142-2154 (2012).</li><li>Raschle, N. M., 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=Making+MR+Imaging+Child's+Play+-+Pediatric+Neuroimaging+Protocol,+Guidelines+and+Procedure.">Making MR Imaging Child's Play - Pediatric Neuroimaging Protocol, Guidelines and Procedure.</a> (29), (2009).</li><li>Morton, J. B., Bosma, R., Ansari, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Age-related+changes+in+brain+activation+associated+with+dimensional+shifts+of+attention:+an+fMRI+study.">Age-related changes in brain activation associated with dimensional shifts of attention: an fMRI study.</a> Neuroimage. 46, 249-256 (2009).</li><li>Ezekiel, F., Bosma, R., Morton, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dimensional+Change+Card+Sort+performance+associated+with+age-related+differences+in+functional+connectivity+of+lateral+prefrontal+cortex.">Dimensional Change Card Sort performance associated with age-related differences in functional connectivity of lateral prefrontal cortex.</a> Developmental Cognitive Neuroscience. , (2013).</li><li>Calhoun, V. D., Kiehl, K. A., Pearlson, G. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modulation+of+temporally+coherent+brain+networks+estimated+using+ICA+at+rest+and+during+cognitive+tasks.">Modulation of temporally coherent brain networks estimated using ICA at rest and during cognitive tasks.</a> Human brain mapping. 29, 828-838 (2008).</li><li>Allen, E. A., 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=A+baseline+for+the+multivariate+comparison+of+resting-state+networks.">A baseline for the multivariate comparison of resting-state networks.</a> Front Syst Neurosci. 5, (2011).</li><li>Calhoun, V. D., Liu, J., Adali, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+review+of+group+ICA+for+fMRI+data+and+ICA+for+joint+inference+of+imaging,+genetic,+and+ERP+data.">A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data.</a> Neuroimage. 45, (2009).</li><li>Allen, E. A., 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=Tracking+whole-brain+connectivity+dynamics+in+the+resting+state.">Tracking whole-brain connectivity dynamics in the resting state.</a> Cerebral Cortex. , (2012).</li></ol>

There are no competing financial interests.

Higher-order mental operations, such as the ability to switch sorting rules, develop rapidly throughout childhood and adolescence. Because these mental operations involve interactions between multiple distributed brain regions, there is growing interest in exploring the relationship between the development of higher-order cognition and age-related changes in the organization of broad-scale cortical networks. We present a method based on group independent component analysis applied to task-based fMRI data as a means of ex...

The ability to regulate behavior develops gradually in childhood and adolescence (for review, see Diamond1). In the Dimensional Change Card Sort task, for example, participants switch from sorting cards one way, such as shape, to sorting them a different way, such as color2 (see Figure 2). Switching 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 same3. The magnitude of these costs typically gets smaller as children grow older4, illustrating the fact that the capacity for behavioral regulation undergoes continued development early in life.
Because complex mental operations, such as switching, involve rapid interactions between multiple brain regions5, there is growing interest in relating the development of higher-order cognition to changes in the functional organization of broad-scale cortical networks6.
One approach to investigating developmental change in broad-scale networks is through the use of seed-based functional connectivity analysis6,7. The first step in this technique is to consult with available research literature and define a priori regions of interest, or ROIs, that seem to be relevant to the behavior in question. These ROIs, or nodes, define the basic skeleton of the network. Next, low-frequency fluctuations in activity (or T2*-weighted signal intensity) in these ROIs are measured for 5&#160;to 10&#160;min&#160;while participants are at rest in an MRI scanner. Functional connectivity between any two nodes of the network is then quantified as the correlation of their respective time courses. Nodes that are strongly connected functionally should have similar, and thus highly correlated, signal time courses. On the other hand, nodes that are weakly connected functionally should have dissimilar and thus weakly correlated, signal time courses. To complete a model of the network, edges (or links) are drawn between nodes whose time courses correlate above a chosen threshold. Tests for age-related differences in functional connectivity within a network can be conducted on any single node-to-node connection, or on the topology of the entire set of nodes and edges. These differences in functional connectivity can then be related to measures of cognitive performance collected offline.
In this paper, a different approach is described that is based on group independent component analysis of task-based fMRI data8. Independent component analysis (or ICA) is a statistical procedure for blindly revealing hidden sources underlying a set of observations such that the revealed sources are maximally independent. Applied to the analysis of fMRI data, the procedure assumes that each volume is a mixture of a finite number of spatially-independent sources. Using one of a variety of different algorithms, such as the infomax algorithm, ICA then estimates an unmixing matrix, which when applied to the original data yields a set of maximally independent sources, or components. Each component can be thought of as a network, insofar as it comprises of a set of voxels that share a common time course. Group ICA is a particular type of ICA in which a common set of group components is first estimated from an entire data set, and then participant-specific sets of the group components are computed in a back-reconstruction step. Once an entire data set is decomposed into a set of components, the next step is to discard artifactual components that represent noise sources, and identify theoretically meaningful components that correspond with networks of interest. This can be achieved either by modeling component time courses in the context of a GLM to identify networks that activate in a predicted manner, spatially correlating components with a template of a network of interest, or both. The resulting set of components can then be submitted to a group comparison to test for possible age-related differences in functional connectivity within theoretically interesting networks7,9,10.
Studying age-related changes in functional connectivity through the application of group ICA to task-based fMRI data has several advantages over the application of seed-based techniques to resting-state fMRI data. First, unlike seed-based techniques that focus on a small set of a priori defined ROIs, the current group ICA approach utilizes all voxels comprising a volumetric time series. This diminishes opportunities for bias that necessarily arise when a small group of seeds are selected a priori as regions of interest. Second, applying functional connectivity analysis (ICA-based or otherwise) to task- rather than resting-state fMRI data has the advantage of allowing network organization and network function to be more directly associated. If, for example, examining the cognitive or behavioral implications of functional connectivity (such as variation in DCCS performance) is a priority, it is important to show that the network of interest is associated with task performance. With resting-state protocols, this is very difficult because the researcher has no record of any cognitive, behavioral, or affective states experienced by the participant during data acquisition. It is therefore impossible to provide direct evidence that any network of interest is relevant for task performance. By contrast, when functional connectivity analysis, such as ICA, is applied to task-data, it is possible to confirm that the network of interest is at least associated with the performance of a task. Finally, ICA is less subject to the adverse influence of noise. Noise sources, such as those associated with subject motion and the cardiac rhythm, have unique spatio-temporal profiles. Therefore, in the context of a group ICA, these sources are isolated and assigned to separate components, leaving remaining components relatively free of these unwelcome sources of variance. Because seed-based analyses use raw time courses in the estimation of functional connectivity, and time courses are, by definition, mixtures of neurophysiological signal and artifactual noise, group differences in functional connectivity estimates can reflect true group differences in underlying neurophysiology, group differences in the structure of noise, or both11.

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			<td height="30" style="height:30px;width:185px;">Name of equipment</td>
			<td style="width:185px;">Company</td>
			<td style="width:185px;">Catalog Number</td>
			<td style="width:185px;">Comments (optional)</td>
		</tr>
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			<td height="30" style="height:30px;width:185px;">SPM8</td>
			<td style="width:185px;">The MathWorks, Inc.</td>
			<td style="width:185px;">R2013a</td>
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a method for investigating age-related differences in the functional connectivity of cognitive control networks associated with dimensional change card sort performance

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.

Group ICA, even on a relatively small fMRI data set, will return a set of components comparable to those observed in other studies. Figure 4&#160;is a superimposition of 5 such components and their associated time courses unmixed from a sample of 12 children and 13 adults, with approximately 800 volumes per participant. As shown in Figure 4, default mode, fronto-parietal, cingulo-insular, and visual networks can readily be seen from the results of this decomposition. As well, notice how ...

Watch this Scientific Journal Video about A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort P

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

This video presents a method of examining age-related changes in functional connectivity of cognitive control networks engaged by targeted tasks/processes. The technique is based on multi-variate analysis of fMRI data.

The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional ...

a-method-for-investigating-age-related-differences-functional

Research

JoVE Journal

Behavior

10.1K Görüntüleme.  University of Western Ontario.  Bu video hedeflenen görevler / süreçlerle meşgul bilişsel kontrol ağlarının fonksiyonel bağlantı yaşa bağlı değişiklikleri inceleyen bir yöntem sunuyor. Bu teknik fMRI verilerin çok değişkenli analiz temel alır. 

Video: A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

The speed and accuracy of object recognition is compromised by a change in viewpoint; demonstrating that human observers are sensitive to this transformation. Here we discuss a novel method for simulating the appearance of an object that has undergone a rotation-in-depth, and include an exposition of the differences between perspective and orthographic projections. Next we describe a method by which human sensitivity to rotation-in-depth can be measured. Finally we discuss an apparatus for creating a vivid percept of a 3-dimensional rotation-in-depth; the Wheatstone Eight Mirror Stereoscope. By doing so, we reveal a means by which to evaluate the role of stereoscopic cues in the discrimination of viewpoint rotated shapes and objects.

We discuss a novel method forviewpoint-rotation of visual stimuli, and demonstrate using a mirror stereoscopethe three-dimensional percept of rotation-in-depth. The technique can be used to investigate the role of stereoscopic cues in encoding viewpoint-rotated figures.

The speed and accuracy of object recognition is compromised by a change in viewpoint; demonstrating that human observers are sensitive to this ...

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach

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.

We tested the usability of a tablet-computer-based application (EmoCogMeter) in investigating the effects of age on cognition. Results show an age-related cognitive decline, thereby proving the usability of our application. Findings underline the great clinical and practical potential of a tablet-based application for detection and monitoring of cognitive dysfunction.

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 ...

A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments

Rodents have been traditionally used as a standard animal model in laboratory experiments involving a myriad of sensory, cognitive, and motor tasks. Higher cognitive functions that require precise control over sensorimotor responses such as decision-making and attentional modulation, however, are typically assessed in nonhuman primates. Despite the richness of primate behavior that allows multiple variants of these functions to be studied, the rodent model remains an attractive, cost-effective alternative to primate models. Furthermore, the ability to fully automate operant conditioning in rodents adds unique advantages over the labor intensive training of nonhuman primates while studying a broad range of these complex functions.
Here, we introduce a protocol for operantly conditioning rats on performing working memory tasks. During critical epochs of the task, the protocol ensures that the animal's overt movement is minimized by requiring the animal to 'fixate' until a Go cue is delivered, akin to nonhuman primate experimental design. A simple two alternative forced choice task is implemented to demonstrate the performance. We discuss the application of this paradigm to other tasks.

A fully automated protocol for rodent operant conditioning is proposed. The protocol relies on precise temporal control of behavioral events to investigate the extent to which this control influences neural activity underlying sensorimotor integration and cognitive control experiments.

Rodents have been traditionally used as a standard animal model in laboratory experiments involving a myriad of sensory, cognitive, and motor tasks. ...

Assessing Functional Performance in the Mdx Mouse Model

Duchenne muscular dystrophy (DMD) is a severe and progressive muscle wasting disorder for which no cure is available. Nevertheless, several potential pharmaceutical compounds and gene therapy approaches have progressed into clinical trials. With improvement in muscle function being the most important end point in these trials, a lot of emphasis has been placed on setting up reliable, reproducible, and easy to perform functional tests to pre clinically assess muscle function, strength, condition, and coordination in the mdx mouse model for DMD. Both invasive and noninvasive tests are available. Tests that do not exacerbate the disease can be used to determine the natural history of the disease and the effects of therapeutic interventions (e.g. forelimb grip strength test, two different hanging tests using either a wire or a grid and rotarod running). Alternatively, forced treadmill running can be used to enhance disease progression and/or assess protective effects of therapeutic interventions on disease pathology. We here describe how to perform these most commonly used functional tests in a reliable and reproducible manner. Using these protocols based on standard operating procedures enables comparison of data between different laboratories.

Assessing Functional Performance in the Mdx Mouse Model

The primary outcome measure in clinical trials for neuromuscular disorders is generally improved muscle function. Therefore, assessing the effect of potential therapeutic compounds on muscle performance pre clinically in mouse models is of great importance. We here describe several functional tests to address this.

Duchenne muscular dystrophy (DMD) is a severe and progressive muscle wasting disorder for which no cure is available. Nevertheless, several potential ...

Transcranial Magnetic Stimulation for Investigating Causal Brain-behavioral Relationships and their Time Course

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 &#8220;virtual lesion.&#8221; 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.

Transcranial magnetic stimulation (TMS) is a technique for non-invasively disrupting neural information processing and measuring its effect on behavior. When TMS interferes with a task, it indicates that the stimulated brain region is necessary for normal task performance, allowing one to systematically relate brain regions to cognitive functions.

Transcranial magnetic stimulation (TMS) is a safe, non-invasive brain stimulation technique that uses a strong electromagnet in order to temporarily ...

Combined Invasive Subcortical and Non-invasive Surface Neurophysiological Recordings for the Assessment of Cognitive and Emotional Functions in Humans

In spite of the success in applying non-invasive electroencephalography (EEG), magneto-encephalography (MEG) and functional magnetic resonance imaging (fMRI) for extracting crucial information about the mechanism of the human brain, such methods remain insufficient to provide information about physiological processes reflecting cognitive and emotional functions at the subcortical level. In this respect, modern invasive clinical approaches in humans, such as deep brain stimulation (DBS), offer a tremendous possibility to record subcortical brain activity, namely local field potentials (LFPs) representing coherent activity of neural assemblies from localized basal ganglia or thalamic regions. Notwithstanding the fact that invasive approaches in humans are applied only after medical indication and thus recorded data correspond to altered brain circuits, valuable insight can be gained regarding the presence of intact brain functions in relation to brain oscillatory activity and the pathophysiology of disorders in response to experimental cognitive paradigms. In this direction, a growing number of DBS studies in patients with Parkinson&#39;s disease (PD) target not only motor functions but also higher level processes such as emotions, decision-making, attention, memory and sensory perception. Recent clinical trials also emphasize the role of DBS as an alternative treatment in neuropsychiatric disorders ranging from obsessive compulsive disorder (OCD) to chronic disorders of consciousness (DOC). Consequently, we focus on the use of combined invasive (LFP) and non-invasive (EEG) human brain recordings in assessing the role of cortical-subcortical structures in cognitive and emotional processing trough experimental paradigms (e.g. speech stimuli with emotional connotation or paradigms of cognitive control such as the Flanker task), for patients undergoing DBS treatment.

The present protocol aims at assessing cognitive-emotional functions in the basal ganglia by simultaneous neurophysiological recording of local field potentials and non-invasive brain cortical activity (EEG). The procedure is exemplified by the use of paradigms involving speech stimuli with emotional connotation or the Flanker task involving cognitive control.

In spite of the success in applying non-invasive electroencephalography (EEG), magneto-encephalography (MEG) and functional magnetic resonance imaging ...

The Emotional Stroop Task: Assessing Cognitive Performance under Exposure to Emotional Content

The emotional Stroop effect (ESE) is the result of longer naming latencies to ink colors of emotion words than to ink colors of neutral words. The difference shows that people are affected by the emotional content conveyed by the carrier words even though they are irrelevant to the color-naming task at hand. The ESE has been widely deployed with patient populations, as well as with non-selected populations, because the emotion words can be selected to match the tested pathology. The ESE is a powerful tool, yet it is vulnerable to various threats to its validity. This report refers to potential sources of confounding and includes a modal experiment that provides the means to control for them. The most prevalent threat to the validity of existing ESE studies is sustained effects and habituation wrought about by repeated exposure to emotion stimuli. Consequently, the order of exposure to emotion and neutral stimuli is of utmost importance. We show that in the standard design, only one specific order produces the ESE.

The emotional Stroop effect (ESE) is the result of longer naming latencies to ink colors of emotion words than those of neutral words. This report refers to potential sources of confounding and includes a modal experiment that provides the means to control for them.

The emotional Stroop effect (ESE) is the result of longer naming latencies to ink colors of emotion words than to ink colors of neutral words. The ...

A Pressure Injection System for Investigating the Neuropharmacology of Information Processing in Awake Behaving Macaque Monkey Cortex

The top-down modulation of feed-forward cortical information processing is functionally important for many cognitive processes, including the modulation of sensory information processing by attention. However, little is known about which neurotransmitter systems are involved in such modulations. A practical way to address this question is to combine single-cell recording with local and temporary neuropharmacological manipulation in a suitable animal model. Here we demonstrate a technique combining acute single-cell recordings with the injection of neuropharmacological agents in the direct vicinity of the recording electrode. The video shows the preparation of the pressure injection/recording system, including preparation of the substance to be injected. We show a rhesus monkey performing a visual attention task and the procedure of single-unit recording with block-wise pharmacological manipulations.

Here, we show the pressure injection of neuropharmacological substances during single-cell recording in an awake, behaving macaque monkey. This procedure allows pharmacological manipulation in the direct vicinity of a cortical recording site.

The top-down modulation of feed-forward cortical information processing is functionally important for many cognitive processes, including the modulation ...

The Rodent Psychomotor Vigilance Test (rPVT): A Method for Assessing Neurobehavioral Performance in Rats and Mice

The human Psychomotor Vigilance Test (PVT) is a widely used procedure for measuring changes in fatigue and sustained attention. The present article describes a rodent version of the PVT&#8212;termed the &#34;rPVT&#34;&#8212;that measures similar aspects of attention (i.e., performance accuracy, motor speed, premature responding, and lapses in attention). Data are presented that demonstrate both the short- and long-term usefulness of the rPVT when employed with laboratory rats. Rats easily learn the rPVT, and learning to perform the basic procedure takes less than two weeks of training. Once acquired, rat performances in the rPVT show a high degree of similarity to these same performance measures in the human PVT, including similarities in, lapses in attention, reaction times, vigilance decrements across session time (i.e., the human &#34;time-on-task&#34; effects), and the response-stimulus interval (RSI) effect described for humans. Thus the rPVT can be an extremely valuable tool for assessing the effects of a wide range of variables on sustained attention quite similar to human PVT performances, and thus can be useful for developing novel treatments for neurobehavioral dysfunctions.

The Rodent Psychomotor Vigilance Test rPVT: A Method for Assessing Neurobehavioral Performance in Rats and Mice

A rat version of the human Psychomotor Vigilance Test (PVT) is described that measures aspects of attention similar to those measured with the human PVT, including aspects of human vigilance such as performance accuracy, motor speed, premature responding, and lapses in attention.

The human Psychomotor Vigilance Test (PVT) is a widely used procedure for measuring changes in fatigue and sustained attention. The present article ...

Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder with pathological involvement of upper and lower motoneurons, subsequently leading to progressive loss of motor and speech abilities. In addition, cognitive functions are impaired in a subset of patients. To evaluate these potential deficits in severely physically impaired ALS patients, eye-tracking is a promising means to conduct cognitive tests. The present article focuses on how eye movements, an indirect means of communication for physically disabled patients, can be utilized to allow for detailed neuropsychological assessment. The requirements, in terms of oculomotor parameters that have to be met for sufficient eye-tracking in ALS patients are presented. The properties of stimuli, including type of neuropsychological tests and style of presentation, best suited to successfully assess cognitive functioning, are also described. Furthermore, recommendations regarding procedural requirements are provided. Overall, this methodology provides a reliable, easy to administer and fast approach for assessing cognitive deficits in patients who are unable to speak or write such as patients with severe ALS. The only confounding factor might be deficits in voluntary eye movement control in a subset of ALS patients.

Cognitive deficits are common in about one third of patients with amyotrophic lateral sclerosis, a neurological condition leading to progressive impairments in speech and movement abilities. To conduct cognitive tests in patients unable to speak or write a reliable and easy to administer eye-tracking paradigm was developed.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder with pathological involvement of upper and lower motoneurons, subsequently leading to ...