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.

Las técnicas de investigación utilizadas en este estudio fueron aprobados por las juntas de revisión institucional (IRB) de la Universidad de Duke y la Universidad de Carolina del Norte - Chapel Hill. 1. Imaging Diseño de tareas <ol><li> Generar una tarea conductual basada en eventos que presenta estímulos objetivo infrecuentes (un círculo) dentro de una secuencia de estímulos estándar más frecuentes (imágenes revueltos). Un esquema de la tarea se muestra en la Figura 1. Presentar la tarea utilizando software CIGAL 10. </li></ol><img alt="Figura 1" src="/files/ftp_upload/51484/51484fig1.jpg" /> Figura 1. Esquema de Diseño de tareas. Esta cifra ha sido modificado desde Hart et al. 20, con permiso. <a href="https://www.jove.com/files/ftp_upload/51484/51484fig1large.jpg" target="_blank">Por favor haga clic aquí para ver una versión más grande de esta figura.</a> <ol style="margin-left: 40px;"><li> Seleccionar comoet de estímulos aversivos y un conjunto de estímulos neutros de la base de datos International Affective Picture System (IAPS). Imágenes del IAPS se clasifican en una escala de 1.9 a fin de reflejar los niveles de excitación y valencia 11. Los altos números indican valencia positiva más alta y la excitación. Seleccione un conjunto de imágenes que son apropiados para la edad para el grupo de estudio, tales como imágenes de serpientes, arañas, u otros animales. Nota: Las imágenes estímulos aversivos irrelevantes para la tarea utilizados para este estudio tenían una calificación promedio valencia de 3,38 (SD = 1,78) y una calificación promedio de excitación de 6,14 (SD = 2,08). Las imágenes estímulos neutros tenían una valencia media de 6,21 (SD = 0,26) y una calificación promedio de excitación de 3,72 (SD = 2,15). </li><li> Programa de la secuencia de comandos de tareas de tal manera que las imágenes se presentan en un orden pseudo-aleatorio de 1.500 mseg con un 500 ms significa intervalo entre estímulos. Presente estímulos diana y las imágenes neutrales irrelevantes para la tarea no más frecuentemente que cada 15 segundos y hacen que cada uno de aproximadamente 4% de los estímulos. Jievento tter tiempos de inicio a fin de proporcionar una mejor resolución de la función de respuesta hemodinámica. </li></ol><ol start="2"><li> Crear 8 conjuntos de imágenes, una para cada uno de 8 carreras funcionales tales que los participantes son presentados con un total de 40 metas y 40 imágenes neutros irrelevantes para la tarea en el transcurso de los 8 carreras. </li></ol> 2. Configuración del Participante y Digitalización <ol><li> Reclutar niños y adolescentes entre las edades de 9 y 18 años que son o bien los individuos control sanos o que están en alto riesgo familiar de psicosis. <ol><li> Asegúrese de que los individuos sanos no tienen enfermedades psiquiátricas o algún familiar de primer grado con una enfermedad psiquiátrica. Asegúrese de que los participantes de riesgo familiares tienen al menos un familiar de primer grado (padres o hermanos) con esquizofrenia. No excluirlos de la presencia de otras enfermedades psiquiátricas en familiares de primer grado. </li><li> Participantes sanos de edad y de los partidos de género con los participantes del grupo de riesgo familiars. </li></ol></li><li> Adquirir el consentimiento informado de los participantes sobre la edad de 18. Para los menores, adquieren el consentimiento informado de los padres / tutores legales. Además, adquirir consentimiento por escrito de los menores que participan en el estudio. </li><li> Coloca los participantes en un escáner de resonancia magnética simulacro con el fin de familiarizarlos con el medio ambiente. Reproducir una grabación de audio de ruido del escáner y pídales que completen una práctica de ejecución de la tarea de comportamiento a fin de asegurarse de que comprenden las instrucciones de la tarea. </li><li> Coloque el participante en el MRI Scanner y adquirir cualquier análisis de localización cerebral necesarios y / o imágenes anatómicas. </li><li> El uso de un cuadro de entrada-MRI segura, dígale a los participantes que pulsar un botón con el dedo índice en la respuesta a todos los estímulos objetivo y otro botón con su dedo medio para el resto de los estímulos. </li><li> Tras la exploración de resonancia magnética funcional, recoger calificaciones subjetivas de excitación y valencia de las imágenes utilizadas en el estudio de un subgrupo de participantes. Los current estudio obtuvo calificaciones de 15 controles y 13 con alto riesgo familiar. </li></ol> 3. Adquisición de imágenes <ol><li> Coloque los participantes en un 3,0 Tesla escáner de resonancia magnética. En primer lugar, adquirir un conjunto de imágenes estructurales, incluyendo una imagen 3D anatómica T1-contraste coplanar usando una secuencia de pulsos de adquisición gradiente-recordó mimada (TR: 5,16 ms; TE: 2,04 ms; FOV: 24 cm; matriz de la imagen: 256 × 256; tirón Ángulo: 20; tamaño de voxel: 0,94 mm x 0,94 mm x 1,9 mm; 68 cortes axiales). </li><li> Adquirir datos de imagen funcional utilizando un gradiente de eco secuencia de imágenes de eco-planar con una cobertura cerebral completa (TR: 2000 ms; TE: 27 ms; FOV: 24 cm; matriz de imagen: 64 × 64; Voltear Ángulo: 60; tamaño de voxel: 3.75 mm x 3,75 mm x 3,8 mm; 34 cortes axiales) de modo que la actividad del cerebro se puede medir durante la ejecución de la tarea de comportamiento. Ejecutar esta secuencia de imágenes para cada ejecución de la tarea conductual. Cada ejecución debe consistir en 120 puntos de tiempo de imagen. </li><li> Presentar la task en 8 carreras funcionales, con una duración de aproximadamente 4 min. </li></ol> 4. Análisis <ol><li> Preprocesamiento Image: Abrir herramienta fMRI Experto Análisis (FEAT) en FSL 12. Seleccione el análisis del primer nivel y Pre-stats. <ol><li> En la ficha &quot;Datos&quot;, seleccione el número de imágenes de entrada y escriba la ruta de acceso a cada una de las imágenes de RM que se van a procesar. Establezca el directorio de salida. Introduzca los volúmenes totales, número de adquisiciones desechados, y el TR. </li><li> En la pestaña &quot;Pre-stats&quot;, ajuste la corrección de movimiento para MCFLIRT, espacial suavizado FWHM a 5 mm, y &quot;corrección de temporización Slice&quot;. Seleccione &quot;extracción cerebral BET&quot; y filtrado temporal &quot;paso alto&quot;, pero no seleccione unwarping B0 (UNESS tienes un mapa de gradiente de campo) o &quot;Yo ntensitiy normaization&quot;. 12,14. </li><li> En la pestaña &quot;Registro&quot;, seleccione &quot;estru Principalctural imagen &quot;. Introduzca la ruta a la imagen ponderada en T1-cráneo-despojado del sujeto. Utilice una búsqueda normal lineal con al menos 6 DOF. Seleccione la casilla de verificación espacio estándar. Introduzca la ruta a la imagen del atlas MNI. Utilice un normal lineal buscar con 12 DOF. Pulse Continuar. </li><li> Excluir los participantes con más de 3 mm de movimiento de la cabeza en el X, Y o Z. </li></ol></li><li> Nivel 1: Comparación de los datos entre las condiciones de trabajo dentro de un mismo plazo. FEAT Abrir. Seleccione &quot;análisis de primer nivel&quot; y &quot;Estadísticas + Post-stats&quot;. <ol><li> En la ficha Datos, establezca el número de entradas y escriba la ruta a cada una de las imágenes de RM. Escriba una ruta para el &quot;directorio de salida&quot;. Introduzca los &quot;volúmenes totales&quot;, número de adquisiciones desechados, y el TR. </li><li> En la pestaña &quot;Estadísticas&quot;, active la casilla de verificación &quot;Usar FILM prewhitening&quot; 16. Pulse el &quot;modelo completo en síbotón tup &quot;. Ajuste el &quot;Número de vehículos eléctricos originales&quot; en el número de condiciones de trabajo. Para cada condición, seleccione &quot;Personalizada (3 Formato de columna)&quot; en el menú desplegable de forma básica y &quot;doble Gama HRF del&quot; &quot;menú desplegable convolución 17,18 y seleccione un archivo de texto que contiene el calendario de tareas. <ol><li> Formatear este archivo de texto en 3 columnas con una entrada para cada &quot;evento&quot; del tipo dado. La primera columna debe contener el tiempo de inicio (en segundos), el segundo debe contener la duración (en segundos), y el tercero debe contener el peso evento. En la ficha Contrastes y pruebas F, cree uno contraste para cada condición de trabajo y uno para cada comparación. </li></ol></li><li> En los &quot;Post-stats&quot;, seleccione &quot;Cluster&quot; en el menú desplegable &quot;Umbral&quot; y establecer el &quot;umbral Z&quot; y Cluster P threshold a 2,3 y 0,05, respectivamente, 8,19. </li><li> En la ficha &quot;Registro&quot;, seleccione &quot;Principal imagen estructural&quot;. Introduzca la ruta a la imagen ponderada en T1-cráneo-despojado del sujeto. Utilice una búsqueda normal lineal con al menos 6 DOF. Seleccione la casilla de verificación &quot;Standard espacio&quot;. Introduzca la ruta a la imagen del atlas MNI. Utilice una búsqueda normal, lineal con 12 DOF. Pulse el botón &quot;Go&quot;. </li></ol></li><li> Nivel 2: Comparación de datos entre carreras para cada condición de trabajo. FEAT Abrir. Seleccione &quot;análisis a nivel superior&quot; y &quot;Estadísticas + Post-stats&quot; desde el menú desplegable. <ol><li> En la ficha Datos, seleccionar &quot;Los insumos son directorios FEAT de nivel inferior&quot;. Establecer el número de entradas y escriba la ruta a cada una de las imágenes de RM. Escriba una ruta para el &quot;directorio de salida&quot;. </li><li> En la pestaña &quot;Estadísticas&quot;, cambiar los &quot;Efectos mixtos: flame1&quot; cuadro de selección a &quot;Fijo Efectos &quot;. Pulse el&quot; asistente de configuración de modelo &quot;botón. Seleccione&quot; promedio del grupo sencillo &quot;y haga clic en el botón&quot; Proceso &quot;. </li><li> En la pestaña &quot;Post-estadísticas&quot;, seleccione &quot;clúster&quot; en el menú desplegable &quot;Umbral&quot; y establecer el &quot;umbral Z&quot; y el umbral &quot;Cluster P&quot; a 2,3 y 0,05, respectivamente, 8,19. Pulse el botón &quot;Go&quot;. </li></ol></li><li> Nivel 3: Comparación de datos entre los sujetos para cada condición de trabajo en todas las carreras. FEAT Abrir. Seleccione &quot;análisis a nivel superior&quot; y &quot;Estadísticas + Post-stats&quot; desde el menú desplegable. <ol><li> En la ficha Datos, seleccionar &quot;Los insumos son 3D lidiar imágenes de directorios FEAT.&quot; Establecer el número de entradas y entrar en la ruta de acceso a cada una de las imágenes de RM. Escriba una ruta para el &quot;directorio de salida&quot;. </li><li> En la &quot;estadísticas&quot; tab, la prensa de la &quot;configuración completa modelo&quot;. Ajuste el número de vehículos eléctricos igual al número de variables grupales y covariables como grupo diagnóstico, edad, sexo, etc. Introduzca los valores para cada sujeto (entrada 1 - entrada n) para cada EV. Puede utilizar la ventana &quot;Pegar&quot; para copiar una hoja de cálculo de estos valores. <ol><li> En la pestaña &quot;Contrastes y pruebas F&quot;, añade un contraste para cada variable de prueba y para cada contraste (por ejemplo, el grupo de diagnóstico). Para cada variable de contraste, ajuste el contraste seleccionando el valor 1 en la columna bajo el EV apropiado. Para cada cambio, establecer el primer valor a 1 y el segundo a -1. Seleccione &quot;Hecho&quot;. </li></ol></li><li> En la ficha &quot;Post-stats&quot;, seleccione &quot;Cluster&quot; en el menú desplegable &quot;Umbral&quot; y establecer el &quot;umbral Z&quot; y el umbral &quot;Cluster P&quot; a 2,3 y 0,05, respectivamente, 8,19 </sup&gt;. Pulse el botón &quot;Go&quot;. </li></ol></li></ol>

<ol>
	<li>Kety, S. S., Rosenthal, D., Wender, P. H., Schulsinger, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mental+illness+in+the+biological+and+adoptive+families+of+adpoted+schizophrenics.">Mental illness in the biological and adoptive families of adpoted schizophrenics.</a> Am J Psyc. 128, 302-306 (1971).</li><li>Weinberger, D. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Implications+of+normal+brain+development+for+the+pathogenesis+of+schizophrenia.">Implications of normal brain development for the pathogenesis of schizophrenia.</a> Arch Gen Psychia. 44, 660-669 (1987).</li><li>Nuechterlein, K. H., Dawson, M. 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. S., Bellion, C., Casp, M., Belger, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impaired+modulation+of+attention+and+emotion+in+schizophrenia.">Impaired modulation of attention and emotion in schizophrenia.</a> Schizophr Bul. 36, 595-606 (2010).</li><li>Fichtenholtz, H. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Emotion-attention+network+interactions+during+a+visual+oddball+task.">Emotion-attention network interactions during a visual oddball task.</a> Brain Res Cogn Brain Re. 20, 67-80 (2004).</li><li>Voyvodic, J. 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. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fast+robust+automated+brain+extraction.">Fast robust automated brain extraction.</a> Hum Brain Map. 17, 143-155 (2002).</li><li>Jenkinson, M., Bannister, P., Brady, M., Smith, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improved+optimization+for+the+robust+and+accurate+linear+registration+and+motion+correction+of+brain+images.">Improved optimization for the robust and accurate linear registration and motion correction of brain images.</a> Neuroimag. 17, 825-841 (2002).</li><li>Jenkinson, M., Smith, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+global+optimisation+method+for+robust+affine+registration+of+brain+images.">A global optimisation method for robust affine registration of brain images.</a> Med Image Ana. 5, 143-156 (2001).</li><li>Woolrich, M. W., Ripley, B. D., Brady, M., 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=Temporal+autocorrelation+in+univariate+linear+modeling+of+FMRI+data.">Temporal autocorrelation in univariate linear modeling of FMRI data.</a> Neuroimag. 14, 1370-1386 (2001).</li><li>Beckmann, C. F., Jenkinson, M., 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=General+multilevel+linear+modeling+for+group+analysis+in+FMRI.">General multilevel linear modeling for group analysis in FMRI.</a> Neuroimag. 20, 1052-1063 (2003).</li><li>Woolrich, M. W., Behrens, T. E., Beckmann, C. F., Jenkinson, M., 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=Multilevel+linear+modelling+for+FMRI+group+analysis+using+Bayesian+inference.">Multilevel linear modelling for FMRI group analysis using Bayesian inference.</a> Neuroimag. 21, 1732-1747 (2004).</li><li>Genovese, C. R., Lazar, N. A., Nichols, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thresholding+of+statistical+maps+in+functional+neuroimaging+using+the+false+discovery+rate.">Thresholding of statistical maps in functional neuroimaging using the false discovery rate.</a> Neuroimag. 15, 870-878 (2002).</li><li>Hart, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Altered+fronto-limbic+activity+in+children+and+adolescents+with+familial+high+risk+for+schizophrenia..">Altered fronto-limbic activity in children and adolescents with familial high risk for schizophrenia..</a> Psychiatry Re. 212, 19-27 (2013).</li><li>Hariri, A. R., Bookheimer, S. Y., Mazziotta, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modulating+emotional+responses:+effects+of+a+neocortical+network+on+the+limbic+system.">Modulating emotional responses: effects of a neocortical network on the limbic system.</a> Neurorepor. 11, 43-48 (2000).</li><li>Gottesman, I. I., Gould, T. 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+endophenotype+concept+in+psychiatry:+etymology+and+strategic+intentions.">The endophenotype concept in psychiatry: etymology and strategic intentions.</a> Am J Psyc. 160, 636-645 (2003).</li><li>Glahn, D. C., Thompson, P. M., Blangero, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neuroimaging+endophenotypes:+strategies+for+finding+genes+influencing+brain+structure+and+function.">Neuroimaging endophenotypes: strategies for finding genes influencing brain structure and function.</a> Hum Brain Map. 28, 488-501 (2007).</li></ol>

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 border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td class="xl63">3T MRI scanner</td>
			<td class="xl63">GE</td>
			<td class="xl63"></td>
			<td class="xl63">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.

No hubo diferencias entre los grupos en función de las características demográficas 20. Datos de comportamiento indicaron que la tarea de detección de objetivo en un nivel apropiado de dificultad para los niños y adolescentes entre las edades de 9.18. En el estudio actual, los controles correctamente identificados 82,36% de blancos (SD = 0,14), y el grupo de riesgo familiar identificó correctamente el 76,8% de los blancos (SD = 0,17). Ambos grupos mostraron disminución de la exactitud...

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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.

Medición de Fronto-límbico Actividad Usando una Emocional bicho raro de tareas en niños con alto riesgo familiar para la esquizofrenia

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

Research

JoVE Journal

Behavior

8.8K vistas.  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

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale

There has been a long-standing interest in the assessment of the neurobehavioral integrity of the newborn infant. The NICU Network Neurobehavioral Scale (NNNS) was developed as an assessment for the at-risk infant. These are infants who are at increased risk for poor developmental outcome because of insults during prenatal development, such as substance exposure or prematurity or factors such as poverty, poor nutrition or lack of prenatal care that can have adverse effects on the intrauterine environment and affect the developing fetus. The NNNS assesses the full range of infant neurobehavioral performance including neurological integrity, behavioral functioning, and signs of stress/abstinence. The NNNS is a noninvasive neonatal assessment tool with demonstrated validity as a predictor, not only of medical outcomes such as cerebral palsy diagnosis, neurological abnormalities, and diseases with risks to the brain, but also of developmental outcomes such as mental and motor functioning, behavior problems, school readiness, and IQ. The NNNS can identify infants at high risk for abnormal developmental outcome and is an important clinical tool that enables medical researchers and health practitioners to identify these infants and develop intervention programs to optimize the development of these infants as early as possible. The video shows the NNNS procedures, shows examples of normal and abnormal performance and the various clinical populations in which the exam can be used.

The NICU Network Neurobehavioral Scale (NNNS) was developed as an assessment for the at-risk infant. The purpose of this article is to describe the NNNS, provide video examples of the NNNS procedures and discuss the ways in which the exam has been used.

Valoración y Evaluación del neonato de alto riesgo: La Escala UCIN Red neuroconductual

There has been a long-standing interest in the assessment of the neurobehavioral integrity of the newborn infant.  The NICU Network Neurobehavioral Scale ...

Investigación

Comportamiento

Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Na&#239;ve Adolescents at High Risk for Psychosis

Growing evidence suggests that movement abnormalities are a core feature of psychosis. One marker of movement abnormality, dyskinesia, is a result of impaired neuromodulation of dopamine in fronto-striatal pathways. The traditional methods for identifying movement abnormalities include observer-based reports and force stability gauges. The drawbacks of these methods are long training times for raters, experimenter bias, large site differences in instrumental apparatus, and suboptimal reliability. Taking these drawbacks into account has guided the development of better&#160;standardized and more efficient procedures to examine movement abnormalities through handwriting analysis software and tablet. Individuals at&#160;risk for psychosis showed significantly more dysfluent pen movements (a proximal measure for dyskinesia) in a handwriting task. Handwriting kinematics offers a great advance over previous methods of assessing dyskinesia, which could clearly be beneficial for understanding the etiology of psychosis.

Handwriting Analysis Indicates Spontaneous Dyskinesias in Neuroleptic Na&amp;#239;ve Adolescents at High Risk for Psychosis

Handwriting analysis software significantly improves upon existing instruments measuring movement disorders. Individuals at&#160;risk for psychosis and healthy controls completed handwriting tasks to test for dyskinesia. Results suggest that youth at&#160;risk for psychosis exhibit dyskinesia and that handwriting analysis could significantly contribute to wider dissemination of early identification efforts

Análisis de la Letra Indica discinesias espontáneas en neurolépticos Naïve adolescentes en alto riesgo de psicosis

Growing evidence suggests that movement abnormalities are a core feature of psychosis. One marker of movement abnormality, dyskinesia, is a result of ...

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;

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.

Cortical Análisis Fuente de Alta Densidad EEG Grabaciones en niños

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

Design and Implementation of an fMRI Study Examining Thought Suppression in Young Women with, and At-risk, for Depression

Ruminative brooding is associated with increased vulnerability to major depression. Individuals who regularly ruminate will often try to reduce the frequency of their negative thoughts by actively suppressing them. We aim to identify the neural correlates underlying thought suppression in at-risk and depressed individuals. Three groups of women were studied; a major depressive disorder group, an at-risk group (having a first degree relative with depression) and controls. Participants performed a mixed block-event fMRI paradigm involving thought suppression, free thought and motor control periods. Participants identified the re-emergence of &#8220;to-be-suppressed&#8221; thoughts (&#8220;popping&#8221; back into conscious awareness) with a button press. During thought suppression the control group showed the greatest activation of the dorsolateral prefrontal cortex, followed by the at-risk, then depressed group. During the re-emergence of intrusive thoughts compared to successful re-suppression of those thoughts, the control group showed the greatest activation of the anterior cingulate cortices, followed by the at-risk, then depressed group. At-risk participants displayed anomalies in the neural regulation of thought suppression resembling the dysregulation found in depressed individuals. The predictive value of these changes in the onset of depression remains to be determined.

We aim to identify the neural correlates underlying sustained and transient thought suppression, and thought re-emergence in controls, at-risk and depressed individuals. Activation was greatest for controls compared to the at-risk and the depressed group in the dorsolateral prefrontal cortex during thought suppression and anterior cingulate cortex during thought re-emergence.

Diseño e Implementación de un Estudio de fMRI Examinar supresión del pensamiento en las Mujeres Jóvenes con y en situación de riesgo, para la depresión

Ruminative brooding is associated with increased vulnerability to major depression. Individuals who regularly ruminate will often try to reduce the ...

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Delay discounting refers to a decline in the value of a reward when it is delayed relative to when it is immediately available. Delay discounting tasks are used to identify indifference points, which reflect equal preference for two dichotomous reward alternatives differing in both delay and magnitude. Indifference points are key to assessing the shape of a delay-discounting gradient because they allow us to isolate the effect of delay on value. For example, if at a 1 week delay and a maximum of $1,000, the indifference point is at $700 we know that, for that participant, a 1-week delay corresponds to a 30% reduction in value. This video outlines an adjusting amount delay-discounting task that identifies indifference points relatively quickly and is inexpensive and easy to administer. Once data have been collected, non-linear regression techniques are typically used to generate discounting curves. The steepness of the discounting curve reflects the degree of impulsive choice of a group or individual. These techniques have been used with a wide range of commodities and have identified populations that are relatively impulsive. For example, people with substance abuse problems discount delayed rewards more steeply than control participants. Although degree of discounting varies as a function of the commodity examined, discounting of one commodity correlates with discounting of other commodities, which suggests that discounting may be a persistent pattern of behavior1.

Delay discounting refers to a decline in the value of a reward when it is delayed relative to when it is immediately available. We outline a computer-based delay discounting task that is easy to implement and allows for the quantification of the degree of delay discounting in human participants.

Medición de demora descuento en humanos Utilizando un Grupo de Ajuste Monto

Delay discounting refers to a decline in the value of a reward when it is delayed relative to when it is immediately available. Delay discounting tasks ...

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.

La tarea Stroop emocional: Evaluación del desempeño cognitivo bajo la exposición a contenido emocional

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 ...

Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery

Human pain models are useful in the assessing the analgesic effect of drugs, providing information about a drug&#39;s pharmacology and identify potentially suitable therapeutic populations. The need to use a comprehensive battery of pain models is highlighted by studies whereby only a single pain model, thought to relate to the clinical situation, demonstrates lack of efficacy. No single experimental model can mimic the complex nature of clinical pain. The integrated, multi-modal pain task&#160;battery presented here encompasses the electrical stimulation task, pressure stimulation task, cold pressor task, the UVB inflammatory model which includes a thermal task and a paradigm for inhibitory conditioned pain modulation. These human pain models have been tested for predicative validity and reliability both in their own right and in combination, and can be used repeatedly, quickly, in short succession, with minimum burden for the subject and with a modest quantity of equipment. This allows a drug to be fully characterized and profiled for analgesic effect which is especially useful for drugs with a novel or untested mechanism of action.

Human pain models are valuable tools used to assess the analgesic potential of novel compounds and predict their clinical efficacy, especially when used in an integrated manner. Although implementation of these models is complex, with proper execution, the pain models described in this protocol can provide predictive and reliable results.

La determinación de detección de dolor y umbrales de tolerancia Usando un sistema integrado, multi-modal de Dolor de tareas de la batería

Human pain models are useful in the assessing the analgesic effect of drugs, providing information about a drug&#39;s pharmacology and identify ...

Using the Visual World Paradigm to Study Sentence Comprehension in Mandarin-Speaking Children with Autism

Sentence comprehension relies on the ability to rapidly integrate different types of linguistic and non-linguistic information. However, there is currently a paucity of research exploring how preschool children with autism understand sentences using different types of cues. The mechanisms underlying sentence comprehension remains largely unclear. The present study presents a protocol to examine the sentence comprehension abilities of preschool children with autism. More specifically, a visual world paradigm of eye-tracking is used to explore the moment-to-moment sentence comprehension in the children. The paradigm has multiple advantages. First, it is sensitive to the time course of sentence comprehension and thus can provide rich information about how sentence comprehension unfolds over time. Second, it requires minimal task and communication demands, so it is ideal for testing children with autism. To further minimize the computational burden of children, the present study measures eye movements that arise as automatic responses to linguistic input rather than measuring eye movements that accompany conscious responses to spoken instructions.

We present a protocol to examine the use of morphological cues during real-time sentence comprehension by children with autism.

Utilizando el paradigma de mundo Visual para el estudio de comprensión de la frase en mandarín-los niños con autismo

Sentence comprehension relies on the ability to rapidly integrate different types of linguistic and non-linguistic information. However, there is ...

Impact of High-intensity Interval Exercise and Moderate-Intensity Continuous Exercise on the Cardiac Troponin T Level at an Early Stage of Training

An elevation in cardiac troponin T (cTnT), as a highly specific biomarker of cardiomyocyte damage, after moderate-intensity continuous exercise (MCE) has been described. The exercise-induced cTnT response distorts the diagnostic role of the cTnT assay. Although high-intensity interval exercise (HIE) is growing in popularity and concerns remain about its safety, available data related to cTnT release after HIE is limited, which hampers the use of HIE as a health intervention. Here, we present three representative HIE protocols [traditional HIE (repeated 4 min cycling at 90% V&#775;O2max interspersed with 3 min rest, 200 kJ/session); sprint interval exercise (SIE, repeated 1 min cycling at 120% V&#775;O2max interspersed with 1.5 min rest, 200 kJ/session); and repeated sprint exercise (RSE, 40 x 6 s all-out sprints interspersed with 9 s rest)] and one representative MCE protocol (continuous cycling exercise at an intensity of 60% V&#775;O2max, 200 kJ/session). Forty-seven sedentary, overweight young women were randomly assigned to one of four groups (HIE, SIE, RSE, and MCE). Six bouts of respective exercise were performed by every single group, with each being 48 h apart. Meanwhile, for four groups, the duration of the entire testing period was identical, being 10 days. Before and after the first and final exercise bouts, an assessment was conducted of cTnT. The current study provides a frame of reference giving a clear picture of how a specific exercise session affects the circulating cTnT concentration at the early stage of training. The information may assist with clinical interpretations of post-exercise cTnT elevation and guide the prescription of exercise, especially for HIE.

Here, we present protocols of high-intensity interval and moderate-intensity continuous exercise to observe the response of circulating cardiac troponin T (cTnT) concentration to acute exercise over 10 days. The information may assist with clinical interpretations of post-exercise cTnT elevation and guide the prescription of exercise.

Impacto del ejercicio de intervalo de alta intensidad y ejercicio continuo de intensidad moderada en el nivel T de troponina cardíaca en una etapa temprana de entrenamiento

An elevation in cardiac troponin T (cTnT), as a highly specific biomarker of cardiomyocyte damage, after moderate-intensity continuous exercise (MCE) has ...

A Within-Subject Experimental Design using an Object Location Task in Rats

Object place recognition is a prominent method used to investigate spatial memory in rodents. This object place recognition memory forms the basis of the object location task. This paper provides an extensive protocol to guide the establishment of an object location task with the option of up to four repetitions using the same cohort of rats. Both weak and strong encoding protocols can be used to study short- and long-term spatial memories of varying strength and to enable the implementation of relevant memory-inhibiting or -enhancing manipulations. In addition, repetition of the test with the counterbalancing presented here allows the combination of results from two or more tests for within-subject comparison to reduce variability between rats. This method helps to increase statistical power and is strongly recommended, particularly when running experiments that produce high variation in individual behavior. This directly refines the study by increasing the data obtained from each animal and reducing the overall number of animals needed.&#160;Finally, implementation of the repeated object location task increases the efficiency of studies that involve surgical procedures by saving time and labor.

This protocol provides detailed steps for an object location task with four repetitions using the same cohort of rats. Weak and strong encoding can produce short- and long-term memories. The flexibility of the protocol with repetition can be beneficial for studies involving surgical operations by saving time and labor.

Un diseño experimental dentro del sujeto utilizando una tarea de ubicación de objetos en ratas

Object place recognition is a prominent method used to investigate spatial memory in rodents. This object place recognition memory forms the basis of the ...