Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-26T21:40:53.109Z Has data issue: false hasContentIssue false
  • English
  • Français

Violence exposure and neural systems underlying working memory for emotional stimuli in youth

Published online by Cambridge University Press:  16 November 2017

Jessica L. Jenness Open the ORCID record for Jessica L. Jenness [Opens in a new window] ,
Maya L. Rosen ,
Kelly A. Sambrook ,
Meg J. Dennison ,
Hilary K. Lambert ,
Margaret A. Sheridan  and
Katie A. McLaughlin Open the ORCID record for Katie A. McLaughlin [Opens in a new window]
Jessica L. Jenness
Affiliation:
University of Washington
Maya L. Rosen
Affiliation:
University of Washington
Kelly A. Sambrook
Affiliation:
University of Washington
Meg J. Dennison
Affiliation:
University of Melbourne
Hilary K. Lambert
Affiliation:
University of Washington
Margaret A. Sheridan
Affiliation:
University of North Carolina, Chapel Hill
Katie A. McLaughlin*
Affiliation:
University of Washington
*
Address correspondence and reprint requests to: Katie McLaughlin, Department of Psychology, University of Washington, Box 351525, Seattle, WA 98195; E-mail: mclaughk@uw.edu.
Get access Rights & Permissions [Opens in a new window]

Abstract

Violence exposure during childhood is common and associated with poor cognitive and academic functioning. However, little is known about how violence exposure influences cognitive processes that might contribute to these disparities, such as working memory, or their neural underpinnings, particularly for cognitive processes that occur in emotionally salient contexts. We address this gap in a sample of 54 participants aged 8 to 19 years (50% female), half with exposure to interpersonal violence. Participants completed a delayed match to sample task for emotional faces while undergoing functional magnetic resonance imaging scanning. Violence-exposed youth performed worse than controls on happy and neutral, but not angry, trials. In whole-brain analysis, violence-exposed youth had reduced activation in the left middle frontal gyrus and right intraparietal sulcus during encoding and the left superior temporal sulcus and temporal–parietal junction during retrieval compared to control youth. Reduced activation in the left middle frontal gyrus during encoding and the left superior temporal sulcus during retrieval mediated the association between violence exposure and task performance. Violence exposure influences the frontoparietal network that supports working memory as well as regions involved in facial processing during working memory for emotional stimuli. Reduced neural recruitment in these regions may explain atypical patterns of cognitive processing seen among violence-exposed youth, particularly within emotional contexts.

Type
Regular Articles
Information
Development and Psychopathology , Volume 30 , Issue 4 , October 2018 , pp. 1517 - 1528
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

This research was supported by National Institute of Child Health and Human Development Grant T32-HD057822 and National Institute of Mental Health Grants K01-MH092526, R01-MH103291, and R01-MH106482.

References

Achenbach, T. M. (1991). Manual for the Child Behavior Checklist/4–18 and 1991 profile. Burlington, VT: University of Vermont, Department of Psychiatry.Google Scholar
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5). Washington, DC: Author.Google Scholar
Askren, M. K., McAllister-Day, T. K., Koh, N., Mestre, Z., Dines, J. N., Korman, B. A., … Madhyastha, T. M. (2016). Using make for reproducible and parallel neuroimaging workflow and quality-assurance. Frontiers in Neuroinformatics. Advance online publication.Google Scholar
Augusti, E.-M., & Melinder, A. (2013). Maltreatment is associated with specific impairments in executive functions: A pilot study: Executive functions in maltreated children. Journal of Traumatic Stress, 26, 780–783. doi:10.1002/jts.21860Google Scholar
Avants, B. B., Tustison, N. J., Song, G., Cook, P. A., Klein, A., & Gee, J. C. (2011). A reproducible evaluation of ANTs similarity metric performance in brain image registration. NeuroImage, 54, 2033–2044.Google Scholar
Barrett, L. F., Tugade, M. M., & Engle, R. W. (2004). Individual differences in working memory capacity and dual-process theories of the mind. Psychological Bulletin, 130, 553.Google Scholar
Behzadi, Y., Restom, K., Liau, J., & Liu, T. T. (2007). A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. NeuroImage, 37, 90–101.Google Scholar
Bernstein, D. P., Ahluvalia, T., Pogge, D., & Handelsman, L. (1997). Validity of the Childhood Trauma Questionnaire in an adolescent psychiatric population. Journal of the American Academy of Child & Adolescent Psychiatry, 36, 340–348.Google Scholar
Bifulco, A., Brown, G. W., Lillie, A., & Jarvis, J. (1997). Memories of childhood neglect and abuse: Corroboration in a series of sisters. Journal of Child Psychology and Psychiatry, 38, 365–374.Google Scholar
Braunlich, K., Gomez-Lavin, J., & Seger, C. A. (2015). Frontoparietal networks involved in categorization and item working memory. NeuroImage, 107, 146–162.Google Scholar
Cicchetti, D., Rogosch, F. A., Maughan, A., Toth, S. L., & Bruce, J. (2003). False belief understanding in maltreated children. Development and Psychopathology, 15, 1067–1091.Google Scholar
Cromheeke, S., Herpoel, L.-A., & Mueller, S. C. (2014). Childhood abuse is related to working memory impairment for positive emotion in female university students. Child Maltreatment, 19, 38–48. doi:10.1177/1077559513511522Google Scholar
Curtis, C. E., & D'Esposito, M. (2003). Persistent activity in the prefrontal cortex during working memory. Trends in Cognitive Sciences, 7, 415–423.Google Scholar
Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis: I. Segmentation and surface reconstruction. NeuroImage, 9, 179–194.Google Scholar
Deen, B., Koldewyn, K., Kanwisher, N., & Saxe, R. (2015). Functional organization of social perception and cognition in the superior temporal sulcus. Cerebral Cortex, 25, 4596–4609.Google Scholar
Dennis, M., Francis, D. J., Cirino, P. T., Schachar, R., Barnes, M. A., & Fletcher, J. M. (2009). Why IQ is not a covariate in cognitive studies of neurodevelopmental disorders. Journal of the International Neuropsychological Society, 15, 331. doi:10.1017/S1355617709090481Google Scholar
DePrince, A. P., Weinzierl, K. M., & Combs, M. D. (2009). Executive function performance and trauma exposure in a community sample of children. Child Abuse and Neglect, 33, 353–361.Google Scholar
Eklund, A., Nichols, T. E., & Knutsson, H. (2016). Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates. Proceedings of the National Academy of Sciences. Advance online publication.Google Scholar
Finkelhor, D., Ormrod, R. K., & Turner, H. A. (2009). The developmental epidemiology of childhood victimization. Journal of Interpersonal Violence, 24, 711–731.Google Scholar
Finn, A. S., Minas, J. E., Leonard, J. A., Mackey, A. P., Salvatore, J., Goetz, C., … Gabrieli, J. D. (2016). Functional brain organization of working memory in adolescents varies in relation to family income and academic achievement. Developmental Science. Advance online publication. doi:10.1111/desc.12450/fullGoogle Scholar
Geier, C. F., Garver, K., Terwilliger, R., & Luna, B. (2009). Development of working memory maintenance. Journal of Neurophysiology, 101, 84–99.Google Scholar
Ghosh, S. S., Kakunoori, S., Augustinack, J., Nieto-Castanon, A., Kovelman, I., Gaab, N., … Fischl, B. (2010). Evaluating the validity of volume-based and surface-based brain image registration for developmental cognitive neuroscience studies in children 4 to 11 years of age. NeuroImage, 53, 85–93.Google Scholar
Gold, A. L., Sheridan, M. A., Peverill, M., Busso, D. S., Lambert, H. K., Alves, S., … McLaughlin, K. A. (2016). Childhood abuse and reduced cortical thickness in brain regions involved in emotional processing. Journal of Child Psychology and Psychiatry, 57, 1154–1164.Google Scholar
Gould, F., Clarke, J., Heim, C., Harvey, P. D., Majer, M., & Nemeroff, C. B. (2012). The effects of child abuse and neglect on cognitive functioning in adulthood. Journal of Psychiatric Research, 46, 500–506.Google Scholar
Hanson, J. L., Chung, M. K., Avants, B. B., Shirtcliff, E. A., Gee, J. C., Davidson, R. J., & Pollak, S. D. (2010). Early stress is associated with alterations in the orbitofrontal cortex: A tensor-based morphometry investigation of brain structure and behavioral risk. Journal of Neuroscience, 30, 7466–7472.Google Scholar
Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. (2000). The distributed human neural system for face perception. Trends in Cognitive Sciences, 4, 223–233.Google Scholar
Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. (2002). Human neural systems for face recognition and social communication. Biological Psychiatry, 51, 59–67.Google Scholar
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: Guilford Press.Google Scholar
Hein, G., & Knight, R. T. (2008). Superior temporal sulcus—It's my area: Or is it? Journal of Cognitive Neuroscience, 20, 2125–2136.Google Scholar
Holt, M. K., Finkelhor, D., & Kantor, G. K. (2007). Multiple victimization experiences of urban elementary school students: Associations with psychosocial functioning and academic performance. Child Abuse and Neglect, 31, 503–515.Google Scholar
Jenkinson, M., Beckmann, C. F., Behrens, T. E., Woolrich, M. W., & Smith, S. M. (2012). NeuroImage, 62, 782–790.Google Scholar
Lambert, H. K., Sheridan, M. A., Sambrook, K. A., Rosen, M. L., Askren, M. K., & McLaughlin, K. A. (2017). Hippocampal contribution to context encoding across development is disrupted following early-life adversity. Journal of Neuroscience, 37, 1925–1934.Google Scholar
Lipina, S., Segretin, S., Hermida, J., Prats, L., Fracchia, C., Camelo, J. L., & Colombo, J. (2013). Linking childhood poverty and cognition: Environmental mediators of non-verbal executive control in an Argentine sample. Developmental Science, 16, 697–707.Google Scholar
LoPresti, M. L., Schon, K., Tricarico, M. D., Swisher, J. D., Celone, K. A., & Stern, C. E. (2008). Working memory for social cues recruits orbitofrontal cortex and amygdala: A functional magnetic resonance imaging study of delayed matching to sample for emotional expressions. Journal of Neuroscience, 28, 3718–3728.Google Scholar
Lupien, S. J., McEwen, B. S., Gunnar, M. R., & Heim, C. (2009). Effects of stress throughout the life span on the brain, behaviour and cognition. Nature Reviews Neuroscience, 10, 434–445.Google Scholar
Mackey, A. P., Finn, A. S., Leonard, J. A., Jacoby-Senghor, D. S., West, M. R., Gabrieli, C. F., & Gabrieli, J. D. (2015). Neuroanatomical correlates of the income-achievement gap. Psychological Science, 26, 925–933.Google Scholar
Marcus, D. S., Harms, M. P., Snyder, A. Z., Jenkinson, M., Wilson, J. A., Glasser, M. F., … others. (2013). Human Connectome Project informatics: Quality control, database services, and data visualization. NeuroImage, 80, 202–219.Google Scholar
Marusak, H. A., Zundel, C. G., Brown, S., Rabinak, C. A., & Thomason, M. E. (2016). Convergent behavioral and corticolimbic connectivity evidence of a negativity bias in children and adolescents. Social Cognitive and Affective Neuroscience. Advance online publication.Google Scholar
McLaughlin, K. A. (2016). Future directions in childhood adversity and youth psychopathology. Journal of Clinical Child and Adolescent Psychology, 45, 361–382.Google Scholar
McLaughlin, K. A., Busso, D. S., Duys, A., Green, J. G., Alves, S., Way, M., & Sheridan, M. A. (2014). Amygdala response to negative stimuli predicts PTSD symptom onset following a terrorist attack. Depression and Anxiety, 31, 834–842. doi:10.1002/da.22284Google Scholar
McLaughlin, K. A., Green, J. G., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., & Kessler, R. C. (2012). Childhood adversities and first onset of psychiatric disorders in a national sample of US adolescents. Archives of General Psychiatry, 69, 1151–1160.Google Scholar
McLaughlin, K. A., Koenen, K. C., Hill, E. D., Petukhova, M., Sampson, N. A., Zaslavsky, A. M., & Kessler, R. C. (2013). Trauma exposure and posttraumatic stress disorder in a national sample of adolescents. Journal of the American Academy of Child & Adolescent Psychiatry, 52, 815–830.Google Scholar
McLaughlin, K. A., & Lambert, H. K. (2016). Child trauma exposure and psychopathology: Mechanisms of risk and resilience. Current Opinion in Psychology, 14, 29–34.Google Scholar
McLaughlin, K. A., Peverill, M., Gold, A. L., Alves, S., & Sheridan, M. A. (2015). Child maltreatment and neural systems underlying emotion regulation. Journal of the American Academy of Child & Adolescent Psychiatry, 54, 753–762.Google Scholar
McLaughlin, K. A., Sheridan, M. A., & Lambert, H. K. (2014). Childhood adversity and neural development: Deprivation and threat as distinct dimensions of early experience. Neuroscience & Biobehavioral Reviews, 47, 578–591.Google Scholar
McLaughlin, K. A., Sheridan, M. A., Winter, W., Fox, N. A., Zeanah, C. H., & Nelson, C. A. (2014). Widespread reductions in cortical thickness following severe early-life deprivation: A neurodevelopmental pathway to attention-deficit/hyperactivity disorder. Biological Psychiatry, 76, 629–638.Google Scholar
Miller, G. A., & Chapman, J. P. (2001). Misunderstanding analysis of covariance. Journal of Abnormal Psychology, 110, 40.Google Scholar
Miyake, A., & Friedman, N. P. (2012). The nature and organization of individual differences in executive functions four general conclusions. Current Directions in Psychological Science, 21, 8–14.Google Scholar
Noble, K. G., Houston, S. M., Brito, N. H., Bartsch, H., Kan, E., Kuperman, J. M., … Sowell, E. R. (2015). Family income, parental education and brain structure in children and adolescents. Nature Neuroscience, 18, 773–778.Google Scholar
Nolte, T., Bolling, D. Z., Hudac, C. M., Fonagy, P., Mayes, L., & Pelphrey, K. A. (2013). Brain mechanisms underlying the impact of attachment-related stress on social cognition. Frontiers in Human Neuroscience, 7. doi:10.3389/fnhum.2013.00816Google Scholar
Pollak, S. D., Cicchetti, D., Hornung, K., & Reed, A. (2000). Recognizing emotion in faces: Developmental effects of child abuse and neglect. Developmental Psychology, 36, 679–688. doi:10.1037/0012-1649.36.5.679Google Scholar
Pollak, S. D., & Tolley-Schell, S. A. (2003). Selective attention to facial emotion in physically abused children. Journal of Abnormal Psychology, 112, 323.Google Scholar
Raschle, N., Zuk, J., Ortiz-Mantilla, S., Sliva, D. D., Franceschi, A., Grant, P. E., … Gaab, N. (2012). Pediatric neuroimaging in early childhood and infancy: Challenges and practical guidelines. Annals of the New York Academy of Sciences, 1252, 43–50.Google Scholar
Roche, A. (2011). A four-dimensional registration algorithm with application to joint correction of motion and slice timing in fMRI. IEEE Transactions on Medical Imaging, 30, 1546–1554.Google Scholar
Sarsour, K., Sheridan, M., Jutte, D., Nuru-Jeter, A., Hinshaw, S., & Boyce, W. T. (2011). Family socioeconomic status and child executive functions: The roles of language, home environment, and single parenthood. Journal of the International Neuropsychological Society, 17, 120–132.Google Scholar
Scherf, K. S., Sweeney, J. A., & Luna, B. (2006). Brain basis of developmental change in visuospatial working memory. Journal of Cognitive Neuroscience, 18, 1045–1058. doi:10.1162/jocn.2006.18.7.1045Google Scholar
Shackman, J. E., Shackman, A. J., & Pollak, S. D. (2007). Physical abuse amplifies attention to threat and increases anxiety in children. Emotion, 7, 838.Google Scholar
Sheridan, M. A., & McLaughlin, K. A. (2014). Dimensions of early experience and neural development: Deprivation and threat. Trends in Cognitive Sciences, 18, 580–585.Google Scholar
Sheridan, M. A., Peverill, M. A., Finn, A. S., & McLaughlin, K. A. (2017). Dimensions of childhood adversity have distinct associations with neural systems underlying executive functioning. Development and Psychopathology. Advance online publication.Google Scholar
Shonk, S. M., & Cicchetti, D. (2001). Maltreatment, competency deficits, and risk for academic and behavioral maladjustment. Developmental Psychology, 37, 3.Google Scholar
Soto, D., Rotshtein, P., & Kanai, R. (2014). Parietal structure and function explain human variation in working memory biases of visual attention. NeuroImage, 89, 289–296.Google Scholar
Steinberg, A. M., Brymer, M. J., Decker, K. B., & Pynoos, R. S. (2004). The University of California at Los Angeles Post-Traumatic Stress Disorder Reaction Index. Current Psychiatry Reports, 6, 96–100.Google Scholar
Swartz, J. R., Graham-Bermann, S. A., Mogg, K., Bradley, B. P., & Monk, C. S. (2011). Attention bias to emotional faces in young children exposed to intimate partner violence. Journal of Child and Adolescent Trauma, 4, 109–122. doi:10.1080/19361521.2011.573525Google Scholar
Thomas, K. M., Drevets, W. C., Whalen, P. J., Eccard, C. H., Dahl, R. E., Ryan, N. D., & Casey, B. J. (2001). Amygdala response to facial expressions in children and adults. Biological Psychiatry, 49, 309–316.Google Scholar
Tibu, F., Sheridan, M. A., McLaughlin, K. A., Nelson, C. A., Fox, N. A., & Zeanah, C. H. (2016). Disruptions of working memory and inhibition mediate the association between exposure to institutionalization and symptoms of attention deficit hyperactivity disorder. Psychological Medicine, 46, 529–541.Google Scholar
Tottenham, N., Tanaka, J. W., Leon, A. C., McCarry, T., Nurse, M., Hare, T. A., … Nelson, C. (2009). The NimStim set of facial expressions: Judgments from untrained research participants. Psychiatry Research, 168, 242–249.Google Scholar
Twamley, E. W., Hami, S., & Stein, M. B. (2004). Neuropsychological function in college students with and without posttraumatic stress disorder. Psychiatry Research, 126, 265–274. doi:10.1016/j.psychres.2004.01.008Google Scholar
Vasilevski, V., & Tucker, A. (2016). Wide-ranging cognitive deficits in adolescents following early life maltreatment. Neuropsychology, 30, 239–246. doi:10.1037/neu0000215Google Scholar
Vul, E., Harris, C., Winkielman, P., & Pashler, H. (2009). Puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition. Perspectives on Psychological Science, 4, 274–290.Google Scholar
Walker, E. A., Unutzer, J., Rutter, C., Gelfand, A., Saunders, K., VonKorff, M., … Katon, W. (1999). Costs of health care use by women HMO members with a history of childhood abuse and neglect. Archives of General Psychiatry, 56, 609–613.Google Scholar
Woolrich, M. (2008). Robust group analysis using outlier inference. NeuroImage, 41, 286–301.Google Scholar
Supplementary material: File

Jenness et al supplementary material

Jenness et al supplementary material 1

Download Jenness et al supplementary material(File)
File 24.1 KB
Supplementary material: Image

Jenness et al supplementary material

Jenness et al supplementary material 2

Download Jenness et al supplementary material(Image)
Image 131.8 KB
Supplementary material: File

Jenness et al supplementary material

Jenness et al supplementary material 3

Download Jenness et al supplementary material(File)
File 20.7 KB