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Familial risk for distress and fear disorders and emotional reactivity in adolescence: an event-related potential investigation

Published online by Cambridge University Press:  08 April 2015

B. D. Nelson*
Affiliation:
Department of Psychology, Stony Brook University, Stony Brook, NY 11794, USA
G. Perlman
Affiliation:
Department of Psychology, Stony Brook University, Stony Brook, NY 11794, USA
G. Hajcak
Affiliation:
Department of Psychology, Stony Brook University, Stony Brook, NY 11794, USA
D. N. Klein
Affiliation:
Department of Psychology, Stony Brook University, Stony Brook, NY 11794, USA
R. Kotov
Affiliation:
Department of Psychology, Stony Brook University, Stony Brook, NY 11794, USA
*
*Address for correspondence: B. D. Nelson, Department of Psychology, Stony Brook University, Stony Brook, NY 11794, USA. (Email: brady.nelson@stonybrook.edu)

Abstract

Background

The late positive potential (LPP) is an event-related potential component that is sensitive to the motivational salience of stimuli. Children with a parental history of depression, an indicator of risk, have been found to exhibit an attenuated LPP to emotional stimuli. Research on depressive and anxiety disorders has organized these conditions into two empirical classes: distress and fear disorders. The present study examined whether parental history of distress and fear disorders was associated with the LPP to emotional stimuli in a large sample of adolescent girls.

Method

The sample of 550 girls (ages 13.5–15.5 years) with no lifetime history of depression completed an emotional picture-viewing task and the LPP was measured in response to neutral, pleasant and unpleasant pictures. Parental lifetime history of psychopathology was determined via a semi-structured diagnostic interview with a biological parent, and confirmatory factor analysis was used to model distress and fear dimensions.

Results

Parental distress risk was associated with an attenuated LPP to all stimuli. In contrast, parental fear risk was associated with an enhanced LPP to unpleasant pictures but was unrelated to the LPP to neutral and pleasant pictures. Furthermore, these results were independent of the adolescent girls’ current depression and anxiety symptoms and pubertal status.

Conclusions

The present study demonstrates that familial risk for distress and fear disorders may have unique profiles in terms of electrocortical measures of emotional information processing. This study is also one of the first to investigate emotional/motivational processes underlying the distress and fear disorder dimensions.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2015 

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References

Bar-Haim, Y, Lamy, D, Pergamin, L, Bakermans-Kranenburg, MJ, van IJzendoorn, MH (2007). Threat-related attentional bias in anxious and nonanxious individuals: a meta-analytic study. Psychological Bulletin 133, 124.Google Scholar
Behar, E, DiMarco, ID, Hekler, EB, Mohlman, J, Staples, AM (2009). Current theoretical models of generalized anxiety disorder (GAD): conceptual review and treatment implications. Journal of Anxiety Disorders 23, 10111023.CrossRefGoogle ScholarPubMed
Bittner, A, Egger, HL, Erkanli, A, Costello, EJ, Foley, DL, Angold, A (2007). What do childhood anxiety disorders predict? Journal of Child Psychology and Psychiatry 48, 11741183.CrossRefGoogle ScholarPubMed
Borkovec, TD, Inz, J (1990). The nature of worry in generalized anxiety disorder: a predominance of thought activity. Behaviour Research and Therapy 28, 153158.Google Scholar
Brown, TA (2006). Confirmatory Factor Analysis for Applied Research. Guilford Press: New York, NY.Google Scholar
Bylsma, LM, Morris, BH, Rottenberg, J (2008). A meta-analysis of emotional reactivity in major depressive disorder. Clinical Psychology Review 28, 676691.CrossRefGoogle ScholarPubMed
Carthy, T, Horesh, N, Apter, A, Gross, JJ (2010). Patterns of emotional reactivity and regulation in children with anxiety disorders. Journal of Psychopathology and Behavioral Assessment 32, 2336.Google Scholar
Cuthbert, B, Insel, T (2010). The data of diagnosis: new approaches to psychiatric classification. Psychiatry 73, 311314.CrossRefGoogle ScholarPubMed
Cuthbert, B, Schupp, H, Bradley, M, Birbaumer, N, Lang, P (2000). Brain potentials in affective picture processing: covariation with autonomic arousal and affective report. Biological Psychology 52, 95111.CrossRefGoogle ScholarPubMed
Dunning, JP, Hajcak, G (2009). See no evil: directed visual attention modulates the electrocortical response to unpleasant images. Psychophysiology 46, 2833.CrossRefGoogle ScholarPubMed
Eaton, NR, Krueger, RF, Markon, KE, Keyes, KM, Skodol, AE, Wall, M, Hasin, DS, Grant, BF (2013). The structure and predictive validity of the internalizing disorders. Journal of Abnormal Psychology 122, 8692.Google Scholar
Feeny, NC, Zoellner, LA, Fitzgibbons, LA, Foa, EB (2000). Exploring the roles of emotional numbing, depression, and dissociation in PTSD. Journal of Traumatic Stress 13, 489498.CrossRefGoogle ScholarPubMed
Ferri, J, Bress, JN, Eaton, NR, Proudfit, GH (2014). The impact of puberty and social anxiety on amygdala activation to faces in adolescence. Developmental Neuroscience 36, 239249.CrossRefGoogle ScholarPubMed
Ferri, J, Weinberg, A, Hajcak, G (2012). I see people: the presence of human faces impacts the processing of complex emotional stimuli. Social Neuroscience 7, 436443.Google Scholar
First, MB, Spitzer, RL, Gibbon, M, Williams, JBW (1996). Structured Clinical Interview for DSM-IV Axis I Disorders, Clinician Version. American Psychiatric Press: Washington, DC.Google Scholar
Foti, D, Olvet, DM, Klein, DN, Hajcak, G (2010). Reduced electrocortical response to threatening faces in major depressive disorder. Depression and Anxiety 27, 813820.Google Scholar
Gao, PX, Liu, HJ, Ding, N, Guo, DJ (2010). An event-related-potential study of emotional processing in adolescence. Acta Psychologica Sinica 42, 342351.Google Scholar
Goodman, SH, Rouse, MH, Connell, AM, Broth, MR, Hall, CM, Heyward, D (2011). Maternal depression and child psychopathology: a meta-analytic review. Clinical Child and Family Psychology Review 14, 127.Google Scholar
Gratton, G, Coles, MG, Donchin, E (1983). A new method for off-line removal of ocular artifact. Electroencephalography and Clinical Neurophysiology 55, 468484.Google Scholar
Hajcak, G, Dennis, TA (2009). Brain potentials during affective picture processing in children. Biological Psychology 80, 333338.Google Scholar
Hajcak, G, Dunning, JP, Foti, D (2009). Motivated and controlled attention to emotion: time-course of the late positive potential. Clinical Neurophysiology 120, 505510.Google Scholar
Hajcak, G, Dunning, J, Foti, D, Weinberg, A (2014). Temporal dynamics of emotion regulation. In Handbook of Emotion Regulation, 2nd edn. (ed. Gross, J.). Guilford Publications: New York, NY.Google Scholar
Hajcak, G, MacNamara, A, Foti, D, Ferri, J, Keil, A (2013). The dynamic allocation of attention to emotion: simultaneous and independent evidence from the late positive potential and steady state visual evoked potentials. Biological Psychology 92, 447455.Google Scholar
Hajcak, G, Olvet, DM (2008). The persistence of attention to emotion: brain potentials during and after picture presentation. Emotion 8, 250255.Google Scholar
Hankin, BL, Abramson, LY, Moffitt, TE, Silva, PA, McGee, R, Angell, KE (1998). Development of depression from preadolescence to young adulthood: emerging gender differences in a 10-year longitudinal study. Journal of Abnormal Psychology 107, 128140.Google Scholar
Kagan, J (2008). Behavioral inhibition as a risk factor for psychopathology. In Child and Adolescent Psychopathology (ed. Beauchaine, T. P. and Hinshaw, S. P.), pp. 157179. John Wiley & Sons Inc.: Hoboken, NJ.Google Scholar
Kaufman, J, Birmaher, B, Brent, D, Rao, U, Flynn, C, Moreci, P, Williamson, D, Ryan, N (1997). Schedule for Affective Disorders and Schizophrenia for School-age Children Present and Lifetime Version (K-SADS-PL): initial reliability and validity data. Journal of the American Academy of Child and Adolescent Psychiatry 36, 980988.Google Scholar
Kayser, J, Bruder, G, Tenke, C, Stewart, J, Quitkin, F (2000). Event-related potentials (ERPs) to hemifield presentations of emotional stimuli: differences between depressed patients and healthy adults in P3 amplitude and asymmetry. International Journal of Psychophysiology 36, 211236.Google Scholar
Kendler, KS, Prescott, CA, Myers, J, Neale, MC (2003). The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Archives of General Psychiatry 60, 929937.Google Scholar
Kendler, KS, Walters, EE, Neale, MC, Kessler, RC, Heath, AC, Eaves, LJ (1995). The structure of the genetic and environmental risk factors for six major psychiatric disorders in women. Phobia, generalized anxiety disorder, panic disorder, bulimia, major depression, and alcoholism. Archives of General Psychiatry 52, 374383.Google Scholar
Kessel, EM, Huselid, RF, DeCicco, JM, Dennis, TA (2013). Neurophysiological processing of emotion and parenting interact to predict inhibited behavior: an affective–motivational framework. Frontiers in Human Neuroscience 7, 326.Google Scholar
Kessler, RC, Chiu, WT, Demler, O, Walters, EE (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 62, 617627.Google Scholar
Kessler, RC, Walters, EE (1998). Epidemiology of DSM-III-R major depression and minor depression among adolescents and young adults in the National Comorbidity Survey. Depression and Anxiety 7, 314.3.0.CO;2-F>CrossRefGoogle Scholar
Keyes, KM, Eaton, NR, Krueger, RF, Skodol, AE, Wall, MM, Grant, B, Siever, LJ, Hasin, DS (2013). Thought disorder in the meta-structure of psychopathology. Psychological Medicine 43, 16731683.Google Scholar
Kotov, R (in press). The quantitative classification of mental illness: emerging solution to boundary problems. In Long-Term Outcomes in Psychopathology Research: Rethinking the Scientific Agenda (ed. Bromet, E.). Oxford University Press: New York, NY.Google Scholar
Kotov, R, Perlman, G, Gámez, W, Watson, D (2014). The structure and short-term stability of the emotional disorders: a dimensional approach. Psychological Medicine. Published online 12 December 2014. doi:10.1017/S0033291714002815.Google ScholarPubMed
Krueger, RF (1999). The structure of common mental disorders. Archives of General Psychiatry 56, 921926.Google Scholar
Krueger, RF, Markon, KE (2006). Reinterpreting comorbidity: a model-based approach to understanding and classifying psychopathology. Annual Review of Clinical Psychology 2, 111133.Google Scholar
Kujawa, A, Hajcak, G, Torpey, D, Kim, J, Klein, DN (2012 a). Electrocortical reactivity to emotional faces in young children and associations with maternal and paternal depression. Journal of Child Psychology and Psychiatry 53, 207215.Google Scholar
Kujawa, A, Klein, DN, Hajcak, G (2012 b). Electrocortical reactivity to emotional images and faces in middle childhood to early adolescence. Developmental Cognitive Neuroscience 2, 458467.Google Scholar
Ladouceur, CD, Dahl, RE, Birmaher, B, Axelson, DA, Ryan, ND (2006). Increased error-related negativity (ERN) in childhood anxiety disorders: ERP and source localization. Journal of Child Psychology and Psychiatry 47, 10731082.Google Scholar
Lang, PJ, Bradley, MM, Cuthbert, BN (2008). International Affective Picture System (IAPS): affective ratings of pictures and instruction manual. Technical Report A-8. University of Florida: Gainesville, FL.Google Scholar
Lewinsohn, PM, Rohde, P, Seeley, JR (1998). Major depressive disorder in older adolescents: prevalence, risk factors, and clinical implications. Clinical Psychology Review 18, 765794.Google Scholar
MacNamara, A, Ferri, J, Hajcak, G (2011). Working memory load reduces the late positive potential and this effect is attenuated with increasing anxiety. Cognitive, Affective and Behavioral Neuroscience 11, 321331.Google Scholar
MacNamara, A, Foti, D, Hajcak, G (2009). Tell me about it: neural activity elicited by emotional stimuli and preceding descriptions. Emotion 9, 531543.Google Scholar
MacNamara, A, Hajcak, G (2010). Distinct electrocortical and behavioral evidence for increased attention to threat in generalized anxiety disorder. Depression and Anxiety 27, 234243.Google Scholar
Marshall, WA, Tanner, JM (1969). Variations in pattern of pubertal changes in girls. Archives of Disease in Childhood 44, 291303.Google Scholar
Merikangas, KR, He, J, Burstein, M, Swanson, SA, Avenevoli, S, Cui, L, Benjet, SA, Georgiades, K, Swendsen, J (2010). Lifetime prevalence of mental disorders in U.S. adolescents: results from the National Comorbidity Survey Replication-Adolescent Supplement (NCS-A). Journal of the American Academy of Child and Adolescent Psychiatry 49, 980989.Google Scholar
Michalowski, JM, Melzig, CA, Weike, AI, Stockburger, J, Schupp, HT, Hamm, AO (2009). Brain dynamics in spider-phobic individuals exposed to phobia-relevant and other emotional stimuli. Emotion 9, 306315.Google Scholar
Miltner, WHR, Trippe, RH, Krieschel, S, Gutberlet, I, Hecht, H, Weiss, T (2005). Event-related brain potentials and affective responses to threat in spider/snake-phobic and non-phobic subjects. International Journal of Psychophysiology 57, 4352.Google Scholar
Mitchell, DGV, Richell, RA, Leonard, A, Blair, RJR (2006). Emotion at the expense of cognition: psychopathic individuals outperform controls on an operant response task. Journal of Abnormal Psychology 115, 559566.Google Scholar
Mogg, K, Bradley, BP (1998). A cognitive–motivational analysis of anxiety. Behaviour Research and Therapy 36, 809848.Google Scholar
Moser, JS, Huppert, JD, Duval, E, Simons, RF (2008). Face processing biases in social anxiety: an electrophysiological study. Biological Psychology 78, 93103.CrossRefGoogle ScholarPubMed
Muthén, LK, Muthén, BO (2011). Mplus User's Guide, 6th edn. Muthén & Muthén: Los Angeles, CA.Google Scholar
Nelson, CA III, McCleery, JP (2008). Use of event-related potentials in the study of typical and atypical development. Journal of the American Academy of Child and Adolescent Psychiatry 47, 12521261.Google Scholar
Pauli, P, Dengler, W, Wiedemann, G, Montoya, P, Flor, H, Birbaumer, N, Buchkremer, G (1997). Behavioral and neurophysiological evidence for altered processing of anxiety-related words in panic disorder. Journal of Abnormal Psychology 106, 213220.Google Scholar
Petersen, AC, Crockett, L, Richards, M, Boxer, A (1988). A self-report measure of pubertal status: reliability, validity, and initial norms. Journal of Youth and Adolescence 17, 117133.CrossRefGoogle ScholarPubMed
Pine, DS, Cohen, P, Gurley, D, Brook, J, Ma, Y (1998). The risk for early-adulthood anxiety and depressive disorders in adolescents with anxiety and depressive disorders. Archives of General Psychiatry 55, 5664.Google Scholar
Rottenberg, J, Gross, J, Gotlib, I (2005). Emotion context insensitivity in major depressive disorder. Journal of Abnormal Psychology 114, 627639.Google Scholar
Ruscio, AM, Weathers, FW, King, LA, King, DW (2002). Male war-zone veterans’ perceived relationships with their children: the importance of emotional numbing. Journal of Traumatic Stress 15, 351357.Google Scholar
Sanislow, CA, Pine, DS, Quinn, KJ, Kozak, MJ, Garvey, MA, Heinssen, RK, Wang, PS, Cuthbert, BN (2010). Developing constructs for psychopathology research: research domain criteria. Journal of Abnormal Psychology 119, 631639.CrossRefGoogle ScholarPubMed
Schmitz, A, Grillon, C, Avenevoli, S, Cui, L, Merikangas, KR (2014). Developmental investigation of fear-potentiated startle across puberty. Biological Psychology 97, 1521.Google Scholar
Silk, JS, Davis, S, McMakin, DL, Dahl, RE, Forbes, EE (2012). Why do anxious children become depressed teenagers? The role of social evaluative threat and reward processing. Psychological Medicine 42, 20952107.Google Scholar
Slade, TIM, Watson, D (2006). The structure of common DSM-IV and ICD-10 mental disorders in the Australian general population. Psychological Medicine 36, 15931600.Google Scholar
Sullivan, PF, Neale, MC, Kendler, KS (2000). Genetic epidemiology of major depression: review and meta-analysis. American Journal of Psychiatry 157, 15521562.Google Scholar
Thom, N, Knight, J, Dishman, R, Sabatinelli, D, Johnson, DC, Clementz, B (2014). Emotional scenes elicit more pronounced self-reported emotional experience and greater EPN and LPP modulation when compared to emotional faces. Cognitive, Affective and Behavioral Neuroscience 14, 849860.Google Scholar
Van Leijenhorst, L, Zanolie, K, Van Meel, CS, Westernberg, PM, Rombouts, SARB, Crone, EA (2010). What motivates the adolescent? Brain regions mediating reward sensitivity across adolescence. Cerebral Cortex 20, 6169.Google Scholar
Vollebergh, WAM, Iedema, J, Bijl, RV, de Graaf, R, Smit, F, Ormel, J (2001). The structure and stability of common mental disorders: the NEMESIS study. Archives of General Psychiatry 58, 597603.CrossRefGoogle ScholarPubMed
Watson, D (2005). Rethinking the mood and anxiety disorders: a quantitative hierarchical model for DSM-V. Journal of Abnormal Psychology 114, 522536.Google Scholar
Watson, D, O'Hara, MW, Naragon-Gainey, K, Koffel, E, Chmielewski, M, Kotov, R, Stasik, SM, Ruggero, CJ (2012). Development and validation of new anxiety and bipolar symptom scales for an expanded version of the IDAS (the IDAS-II). Assessment 19, 399420.Google Scholar
Weinberg, A, Ferri, J, Hajcak, G (2013). Bottom-up and top-down contributions to emotion: Reflections from ERP research. In Handbook of Cognition and Emotion (ed. Robinson, M., Watkins, E. and Harmon-Jones, E.), pp. 3554. Guilford Publications: New York, NY.Google Scholar
Weinberg, A, Hajcak, G (2011 a). Electrocortical evidence for vigilance-avoidance in generalized anxiety disorder. Psychophysiology 48, 842851.Google Scholar
Weinberg, A, Hajcak, G (2011 b). The late positive potential predicts subsequent interference with target processing. Journal of Cognitive Neuroscience 23, 29943007.Google Scholar
Weinberg, A, Hilgard, J, Bartholow, B, Hajcak, G (2012). Emotional targets: evaluative categorization as a function of context and content. International Journal of Psychophysiology 84, 149154.Google Scholar
Wright, AGC, Krueger, RF, Hobbs, MJ, Markon, KE, Eaton, NR, Slade, T (2013). The structure of psychopathology: toward an expanded quantitative empirical model. Journal of Abnormal Psychology 122, 281294.CrossRefGoogle ScholarPubMed
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