We thank Erin Douglas, Anna Evans, and Carolyn Bellion for their contributions to participant recruitment and clinical assessment. We also thank Michael Casp, Zoe Englander, Justin Woodlief, and James Carter for their contributions to data collection and analysis, and Robert M. Hamer for consultation on statistical analysis and editing of the manuscript. Finally, we thank the individuals and their families who participated in this study. 
This study was supported by Conte center grant P50 MH064065 from the National Institute of Mental Health. Dr. Hart was supported by T32 HD040127 from the National Institute of Child Health and Human Development.

The research techniques used during this study were approved by the institutional review boards (IRB) of Duke University and the University of North Carolina &#8211; Chapel Hill.
1. Imaging Task Design
<ol>
	<li>Generate an event-based behavioral task that presents infrequent target stimuli (a circle) within a sequence of more-frequent standard stimuli (scrambled images). A schematic of the task is shown in Figure 1. Present the task using CIGAL software10.</li>
</ol>
<img alt="Figure 1" src="/files/ftp_upload/51484/51484fig1.jpg" /> 
Figure 1.&#160;Schematic of Task Design. This figure has been modified from Hart et al.20, with permission. <a href="https://www.jove.com/files/ftp_upload/51484/51484fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol style="margin-left: 40px;">
	<li>Select a set of aversive stimuli and a set of neutral stimuli from the International Affective Picture System database (IAPS). IAPS images are rated on a scale of 1-9 in order to reflect levels of arousal and valence11. High numbers indicate higher positive valence and arousal. Select a set of images that are age-appropriate to the study group such as pictures of snakes, spiders, or other animals. 
	Note: The task-irrelevant aversive stimuli images used for this study had an average valence rating of 3.38 (S.D. = 1.78) and an average arousal rating of 6.14 (S.D. = 2.08). The neutral stimuli images had an average valence of 6.21 (S.D. = 0.26) and an average arousal rating of 3.72 (S.D. = 2.15).</li>
	<li>Program the task script such that images are presented in a pseudo-randomized order for 1,500 msec with a 500 msec mean inter-stimulus interval. Present target stimuli and task-irrelevant neutral images no more frequently than every 15 sec and make each about 4% of the stimuli. Jitter event onset times in order to provide better resolution of the hemodynamic response function.</li>
</ol>
<ol start="2">
	<li>Create 8 sets of images, one for each of 8 functional runs such that the participants are presented with a total of 40 targets and 40 task-irrelevant neutral images over the course of all 8 runs.</li>
</ol>
2. Participant Setup and Scanning
<ol>
	<li>Recruit children and adolescents between the ages of 9 and 18 who are either healthy control individuals or who are at familial high risk for psychosis.
	<ol>
		<li>Ensure that healthy individuals have no psychiatric illnesses or any first-degree family members with a psychiatric illness. Ensure that familial risk participants have at least one first-degree relative (parent or sibling) with schizophrenia. Do not exclude them for the presence of other psychiatric illnesses in first-degree relatives.</li>
		<li>Age and gender match healthy participants with familial risk group participants.</li>
	</ol>
	</li>
	<li>Acquire informed consent from participants over the age of 18. For minors, acquire informed consent from parents/legal guardians. Additionally, acquire written assent from minors who are taking part in the study.</li>
	<li>Place the participants in a mock MRI scanner in order to familiarize them with the environment. Play an audio recording of scanner noise and have them complete a practice run of the behavioral task in order to ensure that they understand the task instructions.</li>
	<li>Place the participant in the MRI Scanner and acquire any necessary brain localization scans and/or anatomical images.</li>
	<li>Using an MRI-safe input box, tell participants to press one button with their index finger in response to all target stimuli and another button with their middle finger for all other stimuli.</li>
	<li>Following fMRI scanning, collect subjective ratings of arousal and valence for the images used in the study from a subset of participants. The current study obtained ratings from 15 controls and 13 with familial high risk.</li>
</ol>
3. Image Acquisition
<ol>
	<li>Place participants into a 3.0 Tesla MRI scanner. First, acquire a set of structural images including a 3D coplanar anatomical T1-contrast image using a spoiled gradient-recalled acquisition pulse sequence (TR: 5.16 msec; TE: 2.04 msec; FOV: 24 cm; image matrix: 256 &#215; 256; Flip Angle: 20; voxel size: 0.94 mm &#215; 0.94 mm &#215; 1.9 mm; 68 axial slices).</li>
	<li>Acquire functional imaging data using a gradient echo echo-planar imaging sequence with full-brain coverage (TR: 2,000 msec; TE: 27 msec; FOV: 24 cm; image matrix: 64 &#215; 64; Flip Angle: 60; voxel size: 3.75 mm &#215; 3.75 mm &#215; 3.8 mm; 34 axial slices) so that brain activity can be measured during the performance of the behavioral task. Run this imaging sequence for each run of the behavioral task. Each run should consist of 120 imaging time points.</li>
	<li>Present the task in 8 functional runs, each lasting approximately 4 min.</li>
</ol>
4. Analyses
<ol>
	<li>Image Preprocessing: Open fMRI Expert Analysis Tool (FEAT) in FSL12. Select First-level analysis and Pre-stats.
	<ol>
		<li>On the &#8220;Data&#8221; tab, select the number of input images and enter the path to each of the MR images you are going to process. Set the Output directory. Enter the Total volumes, number of discarded acquisitions, and the TR.</li>
		<li>On the &#34;Pre-stats&#34; tab, set motion correction to MCFLIRT, Spatial smoothing FWHM to 5 mms, and &#34;Slice timing correction&#34;. Select &#34;BET brain extraction&#34; and &#34;Highpass&#34; temporal filtering but do not select B0 unwarping (uness you have a gradient field map) or &#34;Intensitiy normaization&#34;. 12,14.</li>
		<li>On the &#34;Registration&#34; tab, select &#34;Main structural image&#34;. Enter the path to the subject&#8217;s skull-stripped T1-weighted image. Use a linear normal search with at least 6 DOF. Select the Standard space check box. Enter the path to the MNI atlas image. Use a normal, linear search with 12 DOF. Press Go.</li>
		<li>Exclude participants with greater than 3 mm head motion in the X, Y, or Z directions.</li>
	</ol>
	</li>
	<li>Level 1: Compare data between task conditions within a single run. Open FEAT. Select &#34;First-level analysis&#34; and &#34;Stats + Post-stats&#34;.
	<ol>
		<li>On the Data tab, set the number of inputs and enter the path to each of the MR images. Enter a path for the &#34;Output directory&#34;. Enter the &#34;Total volumes&#34;, number of discarded acquisitions, and the TR.</li>
		<li>On the &#8220;Stats&#8221; tab, select the &#8220;Use FILM prewhitening&#8221; check box16. Press the &#8220;Full model setup&#8221; button. Set the &#8220;Number of original EVs&#8221; to the number of task conditions. For each condition, select &#8220;Custom (3 column format)&#8221; from the basic shape drop-down menu and &#8220;Double-Gama HRF from the &#8220;Convolution&#8221; drop-down menu17,18 and select a text file containing the task timing.
		<ol>
			<li>Format this text file in 3 columns with one entry for each &#8220;event&#8221; of the given type. The first column should contain the onset time (in seconds), the second should contain the duration (in seconds), and the third should contain the event weight. On the Contrasts &#38; F-tests tab, create one contrast for each task condition and one for each comparison.</li>
		</ol>
		</li>
		<li>On the &#34;Post-stats&#34; tab, select &#34;Cluster&#34; on the &#34;Thresholding&#34; drop-down menu and set the &#34;Z threshold&#34; and Cluster P threshold to 2.3 and 0.05 respectively8,19.</li>
		<li>On the &#34;Registration&#34; tab, select &#34;Main structural image&#34;. Enter the path to the subject&#8217;s skull-stripped T1-weighted image. Use a linear normal search with at least 6 DOF. Select the &#34;Standard space&#34; check box. Enter the path to the MNI atlas image. Use a normal, linear search with 12 DOF. Press &#34;Go&#34;.</li>
	</ol>
	</li>
	<li>Level 2: Compare data between runs for each task condition. Open FEAT. Select &#8220;Higher-level analysis&#8221; and &#8220;Stats + Post-stats&#8221; from the drop down menu.
	<ol>
		<li>On the Data tab, select &#34;Inputs are lower-level FEAT directories&#34;. Set the number of inputs and enter the path to each of the MR images. Enter a path for the &#34;Output directory&#34;.</li>
		<li>On the &#34;Stats&#34; tab, change the &#34;Mixed Effects: FLAME1&#34; selection box to &#34;Fixed Effects&#34;. Press the &#34;Model setup wizard&#34; button. Select &#34;single group average&#34; and click the &#34;Process&#34; button.</li>
		<li>On the &#34;Post-stats&#34; tab, select &#34;Cluster&#34; on the &#34;Thresholding&#34; drop-down menu and set the &#34;Z threshold&#34; and &#34;Cluster P&#34; threshold to 2.3 and 0.05 respectively8,19. Press &#34;Go&#34;.</li>
	</ol>
	</li>
	<li>Level 3: Compare data between subjects for each task condition across all runs. Open FEAT. Select &#8220;Higher-level analysis&#8221; and &#8220;Stats + Post-stats&#8221; from the drop down menu.
	<ol>
		<li>On the Data tab, select &#8220;Inputs are 3D cope images from FEAT directories.&#8221; Set the number of inputs and enter the path to each of the MR images. Enter a path for the &#34;Output directory&#34;.</li>
		<li>On the &#34;Stats&#34; tab, Press the &#34;Full model setup&#34;. Set the number of EVs equal to the number of group variables and covariates such as diagnostic group, age, sex, etc. Enter the values for each subject (Input 1 &#8211; Input n) for each EV. You can use the &#34;Paste&#34; window in order to copy a spreadsheet of these values.
		<ol>
			<li>On the &#34;Contrasts &#38; F-tests&#34; tab, add a contrast for each test variable and for each contrast (e.g., diagnostic group). For each test variable, set the contrast by selecting the value 1 in the column under the appropriate EV. For each contrast, set the first value to 1 and the second to -1. Select &#34;Done&#34;.</li>
		</ol>
		</li>
		<li>On the &#34;Post-stats&#34; tab, select &#34;Cluster&#34; on the &#34;Thresholding&#34; drop-down menu and set the &#34;Z threshold&#34; and &#34;Cluster P&#34; threshold to 2.3 and 0.05 respectively8,19. Press &#34;Go&#34;.</li>
	</ol>
	</li>
</ol>

<ol>
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E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Information+processing+and+attentional+functioning+in+the+developmental+course+of+schizophrenic+disorders.">Information processing and attentional functioning in the developmental course of schizophrenic disorders.</a> Schizophr Bul. 10, 160-203 (1984).</li><li>Nuechterlein, K. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+vulnerability/stress+model+of+schizophrenic+relapse:+a+longitudinal+study.">The vulnerability/stress model of schizophrenic relapse: a longitudinal study.</a> Acta Psychiatr Scand, Supp. 382, 58-64 .</li><li>Keshavan, M. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Premorbid+cognitive+deficits+in+young+relatives+of+schizophrenia+patients.">Premorbid cognitive deficits in young relatives of schizophrenia patients.</a> Front Hum Neurosc. 3 (62), (2010).</li><li>Kiehl, K. A., Liddle, P. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+event-related+functional+magnetic+resonance+imaging+study+of+an+auditory+oddball+task+in+schizophrenia.">An event-related functional magnetic resonance imaging study of an auditory oddball task in schizophrenia.</a> Schizophr Re. 48, 159-171 (2001).</li><li>Bramon, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Is+the+P300+wave+an+endophenotype+for+schizophrenia?+A+meta-analysis+and+a+family+study.">Is the P300 wave an endophenotype for schizophrenia? A meta-analysis and a family study.</a> Neuroimag. 27, 960-968 (2005).</li><li>Dichter, G. 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T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+fMRI+paradigm+control,+physiology,+and+behavior+combined+with+near+real-time+statistical+analysis.">Real-time fMRI paradigm control, physiology, and behavior combined with near real-time statistical analysis.</a> Neuroimag. 10, 91-106 (1999).</li><li>Lang, P. J., Bradley, M. M., Cuthbert, B. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> International affective picture system (IAPS): Digitized photographs, instruction manual and affective ratings. Technical Report A-6. , (2005).</li><li>Smith, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+functional+and+structural+MR+image+analysis+and+implementation+as+FSL.">Advances in functional and structural MR image analysis and implementation as FSL.</a> Neuroimag. 23, 208-219 (2004).</li><li>Smith, S. 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Dr. Perkins is currently receiving grant support from Janssen, and is a consultant to Dainippon. In the past, Dr. Perkins is or has been on speaker's bureau for Eli Lilly and AstraZeneca. Dr. Perkins has previously received grants from AstraZeneca, Bristol-Myers Squibb, Otsuka, Eli Lilly, Janssen and Pfizer; and consulting and educational fees from AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen, Glaxo Smith Kline, Forest Labs, Pfizer and Shire. All other authors declare no biomedical financial interests or potential conflict of interest.

The modified emotional oddball paradigm in the current study has been shown to elicit differences in neural recruitment during selective attention and emotional processing in children and adolescents at risk for schizophrenia. While existing paradigms using the emotional oddball task have been used to investigate neural changes in adult populations with psychiatric illness8, the current paradigm may be particularly useful for measurement of vulnerability markers in younger age groups. 
<p class='jove_conte...

Schizophrenia is a neurodevelopmental disorder with a known genetic component1,2 and with symptoms including deficits in both executive and emotional processing3,4. First-degree relatives are thought to be at an increased risk of developing schizophrenia, and have been shown to share some of these same neurocognitive deficits in both cognitive and social-emotional domains5. We therefore expect that brain activity in regions associated with executive and emotional processing may be altered in at-risk family members preceding the onset of clinical symptoms. 
Previous studies have indicated that both adults with schizophrenia and adults at familial high risk show aberrant activity within executive and emotional processing networks; however it remains unclear how these changes come about during development. Demonstrating that these changes occur early in life will be a critical first step in understanding the pathophysiology of the disorder. Therefore, this study utilizes an emotional oddball paradigm during functional MRI (fMRI) scanning in order to measure brain activity during the completion of a task that requires both executive and emotional processing in adolescents who are at risk for developing schizophrenia. Oddball paradigms are frequently used to examine the function of fronto-striate circuitry in schizophrenia6 and in individuals with familial high risk7 by measuring selective attention processes allocated to task-relevant target stimuli. Here, a standard oddball task has been modified to include task-irrelevant aversive and neutral stimuli that have been shown to elicit changes in brain activity in patients with schizophrenia8. 
This paper measures functional differences between healthy adolescents and adolescents at high familial risk for schizophrenia using an emotional oddball task. The task design is similar to that used by Fichtenholtz and colleagues9, but the selection of aversive emotional images has been modified to be appropriate for children between the ages of 9-18. The use of this task during functional MRI allowed for the identification of specific brain regions that showed patterns of hyperactivation and hypoactivation in children and adolescents with FHR for schizophrenia, in addition to age-related changes in neural activity during adolescent development.

<table><tbody><tr><td>3T MRI scanner</td><td>GE</td><td></td><td>BIAC 3T scanner (replaced)</td></tr></tbody></table>

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.

There were no differences between groups based on demographic characteristics20. Behavioral data indicated that the target detection task is at an appropriate level of difficulty for children and adolescents between the ages of 9-18. In the current study, controls correctly identified 82.36% of targets (S.D. = 0.14), and the familial risk group correctly identified 76.8% of targets (S.D. = 0.17). Both groups showed decreased accuracy when identifying emotional pictures compared to neutral pic...

Watch this Scientific Journal Video about Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia at JoVE.com

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

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 ...

measurement-fronto-limbic-activity-using-an-emotional-oddball-task

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JoVE Journal

Behavior

8.8K Views.  University of North Carolina at Chapel Hill School of Medicine. 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). 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.

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

Use of the Open Field Maze to Measure Locomotor and Anxiety-like Behavior in Mice

Animal models have proven to be invaluable to researchers trying to answer questions regarding the mechanisms of behavior. The Open Field Maze is one of the most commonly used platforms to measure behaviors in animal models. It is a fast and relatively easy test that provides a variety of behavioral information ranging from general ambulatory ability to data regarding the emotionality of the subject animal. As it relates to rodent models, the procedure allows the study of different strains of mice or rats both laboratory bred and wild-captured. The technique also readily lends itself to the investigation of different pharmacological compounds for anxiolytic or anxiogenic effects. Here, a protocol for use of the open field maze to describe mouse behaviors is detailed and a simple analysis of general locomotor ability and anxiety-related emotional behaviors between two strains of C57BL/6 mice is performed. Briefly, using the described protocol we show Wild Type mice exhibited significantly less anxiety related behaviors than did age-matched Knock Out mice while both strains exhibited similar ambulatory ability.

A protocol is provided to use an Open Field Maze to access general locomotor activity, anxiety and emotionality in a laboratory mouse model.

Animal models have proven to be invaluable to researchers trying to answer questions regarding the mechanisms of behavior. The Open Field Maze is one of ...

Brain Imaging Investigation of the Neural Correlates of Emotion Regulation

The ability to control/regulate emotions is an important coping mechanism in the face of emotionally stressful situations. Although significant progress has been made in understanding conscious/deliberate emotion regulation (ER), less is known about non-conscious/automatic ER and the associated neural correlates. This is in part due to the problems inherent in the unitary concepts of automatic and conscious processing1. Here, we present a protocol that allows investigation of the neural correlates of both deliberate and automatic ER using functional magnetic resonance imaging (fMRI). This protocol allows new avenues of inquiry into various aspects of ER. For instance, the experimental design allows manipulation of the goal to regulate emotion (conscious vs. non-conscious), as well as the intensity of the emotional challenge (high vs. low). Moreover, it allows investigation of both immediate (emotion perception) and long-term effects (emotional memory) of ER strategies on emotion processing. Therefore, this protocol may contribute to better understanding of the neural mechanisms of emotion regulation in healthy behaviour, and to gaining insight into possible causes of deficits in depression and anxiety disorders in which emotion dysregulation is often among the core debilitating features.

We present a protocol that allows investigation of the neural correlates of deliberate and automatic emotion regulation, using functional magnetic resonance imaging. This protocol can be used in healthy participants, both young and older, as well as in clinical patients.

The ability to control/regulate emotions is an important coping mechanism in the face of emotionally stressful situations. Although significant progress ...

Neuroscience

Brain Imaging Investigation of the Impairing Effect of Emotion on Cognition

Emotions can impact cognition by exerting both enhancing (e.g., better memory for emotional events) and impairing (e.g., increased emotional distractibility) effects (reviewed in 1). Complementing our recent protocol 2 describing a method that allows investigation of the neural correlates of the memory-enhancing effect of emotion (see also 1, 3-5), here we present a protocol that allows investigation of the neural correlates of the detrimental impact of emotion on cognition. The main feature of this method is that it allows identification of reciprocal modulations between activity in a ventral neural system, involved in 'hot' emotion processing (HotEmo system), and a dorsal system, involved in higher-level 'cold' cognitive/executive processing (ColdEx system), which are linked to cognitive performance and to individual variations in behavior (reviewed in 1). Since its initial introduction 6, this design has proven particularly versatile and influential in the elucidation of various aspects concerning the neural correlates of the detrimental impact of emotional distraction on cognition, with a focus on working memory (WM), and of coping with such distraction 7,11, in both healthy 8-11 and clinical participants 12-14.

We present a protocol that allows investigation of the neural mechanisms mediating the detrimental impact of emotion on cognition, using functional magnetic resonance imaging. This protocol can be used with both healthy and clinical participants.

Emotions can impact cognition by exerting both enhancing (e.g., better memory for emotional events) and impairing (e.g., increased emotional ...

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 ...

Psychophysiological Assessment of the Effectiveness of Emotion Regulation Strategies in Childhood

Effective regulation of emotion is one of the most important skills that develops in childhood. Research interest in this area is expanding, but empirical work has been limited by predominantly correlational investigations of children's skills. Relatedly, a key conceptual challenge for emotion scientists is to distinguish between emotion responding and emotion regulatory processes. This paper presents a novel method to address these conceptual and methodological issues in child samples. An experimental paradigm that assesses the effectiveness with which children regulate emotion is described. Children are randomly assigned to use specific emotion regulation strategies, negative emotions are elicited with film clips, and changes in subsequent psychophysiology index the extent to which emotion regulation is effective. Children are instructed to simply watch the emotion-eliciting film (control), distract themselves from negative emotions (cognitive distraction), or reframe the situation in a way that downplays the importance of the emotional event (cognitive reappraisal). Cardiac physiology, continuously acquired before and during the emotional task, serves as an objective measure of children's unfolding emotional responding while viewing evocative films. Key comparisons in patterns of obtained physiological reactivity are between the control and emotion regulation strategy conditions. Representative results from this approach are described, and discussion focuses on the contribution of this methodological approach to developmental science.

A detailed protocol for an experimental paradigm to assess the effectiveness with which children regulate emotion is described. Children are randomly assigned to use specific emotion regulation strategies, negative emotions are elicited with film clips, and changes in subsequent psychophysiology index the extent to which emotion regulation is effective.

Effective regulation of emotion is one of the most important skills that develops in childhood. Research interest in this area is expanding, but empirical ...

Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis

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.

The goal of our research is to correlate behavior to brain activity. Accurate behavioral measures and imaging techniques allow us to elucidate brain-behavior relationships.

The aim of this methods paper is to describe how to implement a neuroimaging technique to examine complementary brain processes engaged by two similar ...

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 ...

Experimental Paradigm for Measuring the Effects of Self-distancing in Young Children

Self-distancing (i.e., creating mental distance between the self and a stimulus by adopting a less egocentric perspective) has been studied as a way to improve adolescents' and adults' emotion regulation. These studies instruct adolescents and adults to use visual imagery or language to create distance from the self before engaging in self-regulation tasks and when thinking about past and future events. For example, adults are asked to recall past, negative emotional experiences from either a first-person perspective (no distance) or a third-person perspective (self-distanced). These studies show that a self-distanced perspective allows adults to cope more adaptively when recalling negative feelings. However, the self-distancing paradigm used with adults was not developmentally appropriate for young children. This modified self-distancing paradigm involves instructing children to think about their thoughts, feelings, and actions from different perspectives that vary in their distance from the self while completing a self-regulation task. The paradigm involves randomly assigning children to use one of three perspectives: self-immersed, third-person, or exemplar. In the self-immersed condition, children are asked to think about themselves using the first-person perspective (e.g., "How am I feeling?") and no distance is created from the self. In the third-person condition, children are asked to create distance from the self by using the third-person perspective (e.g., "How is [child's name] feeling?"). In the exemplar condition, the greatest distance from the self is created by asking children to pretend to be a media character and to think about that character's thoughts and feelings (e.g., "How is Batman feeling?"). Studies using the self-distancing paradigm with 4-6-year-olds have found that as the amount of distance from the self increases (self-immersed &lt; third-person &lt; exemplar), children perform better on self-regulation tasks. These findings suggest that the strategies implemented in the self-distancing protocol may be useful to include in self-regulation interventions for young children.

An experimental paradigm was created to measure the effects of self-distancing in young children (4-6-year-olds). Self-distancing is a process through which individuals adopt a less egocentric perspective. This paradigm has been used to examine the effects of self-distancing on young children&#39;s self-regulation.

Self-distancing (i.e., creating mental distance between the self and a stimulus by adopting a less egocentric perspective) has been studied as a way to ...

The Use of Traditional Fear Tests to Evaluate Different Emotional Circuits in Cattle

Animal temperament is complex and has implications for productivity and economic profitability. Quantifying an animal&#39;s response to differing stimuli may facilitate breeding selections and identify animals that are better suited to specific management strategies. Multiple tests have been developed to evaluate cattle temperament (e.g., exit velocity, chute score, pen score, open field test, startle test, bovine zero maze), but each of these tests evaluates the animal&#39;s response to different stimuli (e.g., isolation, novel environment, startle, willingness to enter an enclosed area). Cattle temperament has been observed to be relatively stable over time. However, the evaluation of temperament has the potential to be influenced by current conditions, previous experiences, and observer bias. Many of these temperament tests have been improperly categorized as fear tests and have also been criticized for being subjective. This paper provides a framework for standardizing behavioral tests for cattle and suggests that these different evaluations assess different aspects of the animal&#39;s overall temperament.

Here, we present a protocol to conduct a variety of behavioral tests in cattle that have been designed to evaluate emotions. A battery of behavioral tests (open field test, startle test, bovine zero maze, exit velocity, pen score, and chute score) were conducted to evaluate different components of animal temperament.

Animal temperament is complex and has implications for productivity and economic profitability. Quantifying an animal&#39;s response to differing stimuli ...

Exploring the Neural Correlates of Cognitive Reappraisal in Obsessive-Compulsive Disorder Using Task-based Functional Magnetic Resonance Imaging

Patients with obsessive-compulsive disorder (OCD) show heightened brain activity in limbic and orbitofrontal regions when confronted with negative emotions, which could be associated with impairments in emotion regulation skills. The ability to regulate emotions is a necessary coping mechanism when facing emotionally distressing situations, and deliberate emotion regulation strategies such as cognitive reappraisal have been extensively studied in the general population. Despite this, little is known about potential deliberate emotion regulation deficits in OCD patients and the associated neural correlates. Here, we describe a protocol to investigate the neural correlates of deliberate emotion regulation (cognitive reappraisal) using functional magnetic resonance imaging (fMRI) in OCD patients in comparison to a matched control sample. This protocol follows current gold standards for neuroimaging studies and includes both task activation and connectivity analysis (as well as behavioral data) to allow a more complete investigation. Therefore, we expect it will contribute to expanding the knowledge of the neural correlates of emotion (dys)regulation in OCD, and it could also be applied to explore emotion regulation deficits in other psychiatric disorders.

We introduce a protocol for exploring the neural correlates of a cognitive emotion regulation task, namely cognitive reappraisal, using functional magnetic resonance imaging. This protocol was used in patients with obsessive-compulsive disorder and healthy controls but can also be used in other clinical samples.