[Skip to Content]
Sign In
Individual Sign In
Create an Account
Institutional Sign In
OpenAthens Shibboleth
[Skip to Content Landing]
Figure 1.  Associations of Total Child Trauma Questionnaire (CTQ) Score × Task Condition and Abuse × Task Condition
Associations of Total Child Trauma Questionnaire (CTQ) Score × Task Condition and Abuse × Task Condition

A and B, Increased total CTQ scores were associated with decreased differential responsiveness to incongruent task trials compared with view trials in the right midcingulate cortex (x = 7.5; y = −22.5; z = 47.5) (A) and the right postcentral gyrus (x = 40.5; y = −25.5; z = 56.5) (B). C and D, Increased amounts of abuse were associated with decreased differential responsiveness to incongruent task trials compared with view trials in the right midcingulate cortex (x = 7.5, y = −22.5; z = 47.5) (C) and the right postcentral gyrus and inferior parietal lobule (x = 31.5; y = −37.5; z = 53.5) (D). E, Increased amounts of abuse were associated with increased differential responsiveness to view trials compared with incongruent task trials in the left rostromedial prefrontal cortex (x = −16.5; y = 49.5; z = 26.5). A-E, Scatterplots depict the correlations (A and B) and partial correlations (C-E) with adjusted residuals for each of the brain regions. Adjusted residuals for the Blom-transformed z-scored CTQ scores (x-axis: A and B) or abuse subscores (x-axis: C-E) are plotted against adjusted residuals for the mean blood oxygen level–dependent (BOLD) response difference in incongruent trials and view trials.

Figure 2.  Associations of Emotional Abuse (EA) × Task Condition and Physical Abuse (PA) × Task Condition
Associations of Emotional Abuse (EA) × Task Condition and Physical Abuse (PA) × Task Condition

A, Increased EA scores were associated with decreased differential responsiveness to incongruent task trials compared with view trials in the right inferior parietal lobule (x = 31.5; y = −37.5; z = 53.5). B and C, Increased PA scores were associated with increased differential responsiveness to negative compared with positive trials in the right dorsomedial prefrontal cortex (x = 7.5; y = 31.5; z = 56.5) (B) and the right dorsolateral frontal gyrus (x = 31.5; y = 40.5; z = 32.5) (C). A-C, Scatterplots depict the partial correlations and adjusted residuals for each of the regions. Adjusted residuals for the Blom-transformed z-scored EA (x-axis: A) or PA scores (x-axis: B and C) are plotted against adjusted residuals for the mean blood oxygen level–dependent (BOLD) responses to incongruent compared with view trials (y-axis: A), and negative compared with positive trials (y-axis: B and C).

Figure 3.  Interactions of Sexual Abuse (SA) × Task Condition
Interactions of Sexual Abuse (SA) × Task Condition

A-C, Increased SA scores were associated with increased differential responsiveness to view compared with incongruent task trials in the right postcentral gyrus (x = 43.5; y = −22.5; z = 44.5) (A), the right anterior cingulate cortex and rostromedial prefrontal cortex (x = 10.5; y = 31.5; z = 2.5) (B), and the right insula (x = 34.5; y = 7.5; z = 5.5) (C). Scatterplots depict the partial correlations and adjusted residuals for each of the regions. Adjusted residuals for the Blom-transformed z-scored SA scores (x-axis) are plotted against adjusted residuals for the mean blood level–dependent (BOLD) responses to view compared with incongruent task trials.

Table 1.  Associations of Maltreatment and Forms of Maltreatment With Demographic Variables and Diagnosis Information
Associations of Maltreatment and Forms of Maltreatment With Demographic Variables and Diagnosis Information
Table 2.  Significant Areas of Activation From the Analysis Involving the CTQ Total Score
Significant Areas of Activation From the Analysis Involving the CTQ Total Score
1.
Bremne  JD, Vermetten  E.  Stress and development: behavioral and biological consequences.  Dev Psychopathol. 2001;13(3):473-489. doi:10.1017/S0954579401003042PubMedGoogle ScholarCrossref
2.
Shonkoff  JP, Garner  AS; Committee on Psychosocial Aspects of Child and Family Health; Committee on Early Childhood, Adoption, and Dependent Care; Section on Developmental and Behavioral Pediatrics.  The lifelong effects of early childhood adversity and toxic stress.  Pediatrics. 2012;129(1):e232-e246. doi:10.1542/peds.2011-2663PubMedGoogle ScholarCrossref
3.
McLaughlin  KA, Green  JG, Gruber  MJ, Sampson  NA, Zaslavsky  AM, Kessler  RC.  Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication II: associations with persistence of DSM-IV disorders.  Arch Gen Psychiatry. 2010;67(2):124-132. doi:10.1001/archgenpsychiatry.2009.187PubMedGoogle ScholarCrossref
4.
Green  JG, McLaughlin  KA, Berglund  PA,  et al.  Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication I: associations with first onset of DSM-IV disorders.  Arch Gen Psychiatry. 2010;67(2):113-123. doi:10.1001/archgenpsychiatry.2009.186PubMedGoogle ScholarCrossref
5.
McCrory  EJ, Gerin  MI, Viding  E.  Annual research review: childhood maltreatment, latent vulnerability and the shift to preventative psychiatry—the contribution of functional brain imaging.  J Child Psychol Psychiatry. 2017;58(4):338-357. doi:10.1111/jcpp.12713PubMedGoogle ScholarCrossref
6.
Pollak  SD.  Early adversity and mechanisms of plasticity: integrating affective neuroscience with developmental approaches to psychopathology.  Dev Psychopathol. 2005;17(3):735-752. doi:10.1017/S0954579405050352PubMedGoogle ScholarCrossref
7.
Toth  SL, Cicchetti  D.  Frontiers in translational research on trauma.  Dev Psychopathol. 2011;23(2):353-355. doi:10.1017/S0954579411000101PubMedGoogle ScholarCrossref
8.
Pollak  SD, Sinha  P.  Effects of early experience on children’s recognition of facial displays of emotion.  Dev Psychol. 2002;38(5):784-791. doi:10.1037/0012-1649.38.5.784PubMedGoogle ScholarCrossref
9.
Pine  DS, Mogg  K, Bradley  BP,  et al.  Attention bias to threat in maltreated children: implications for vulnerability to stress-related psychopathology.  Am J Psychiatry. 2005;162(2):291-296. doi:10.1176/appi.ajp.162.2.291PubMedGoogle ScholarCrossref
10.
Tottenham  N, Hare  TA, Millner  A, Gilhooly  T, Zevin  JD, Casey  BJ.  Elevated amygdala response to faces following early deprivation.  Dev Sci. 2011;14(2):190-204. doi:10.1111/j.1467-7687.2010.00971.xPubMedGoogle ScholarCrossref
11.
McCrory  EJ, De Brito  SA, Kelly  PA,  et al.  Amygdala activation in maltreated children during pre-attentive emotional processing.  Br J Psychiatry. 2013;202(4):269-276. doi:10.1192/bjp.bp.112.116624PubMedGoogle ScholarCrossref
12.
McLaughlin  KA, Peverill  M, Gold  AL, Alves  S, Sheridan  MA.  Child maltreatment and neural systems underlying emotion regulation.  J Am Acad Child Adolesc Psychiatry. 2015;54(9):753-762. doi:10.1016/j.jaac.2015.06.010PubMedGoogle ScholarCrossref
13.
Birn  RM, Roeber  BJ, Pollak  SD.  Early childhood stress exposure, reward pathways, and adult decision making.  Proc Natl Acad Sci U S A. 2017;114(51):13549-13554. doi:10.1073/pnas.1708791114PubMedGoogle ScholarCrossref
14.
Gerin  MI, Puetz  VB, Blair  RJR,  et al.  A neurocomputational investigation of reinforcement-based decision making as a candidate latent vulnerability mechanism in maltreated children.  Dev Psychopathol. 2017;29(5):1689-1705. doi:10.1017/S095457941700133XPubMedGoogle ScholarCrossref
15.
Harms  MB, Shannon Bowen  KE, Hanson  JL, Pollak  SD.  Instrumental learning and cognitive flexibility processes are impaired in children exposed to early life stress.  Dev Sci. 2018;21(4):e12596.PubMedGoogle ScholarCrossref
16.
Mueller  SC, Maheu  FS, Dozier  M,  et al.  Early-life stress is associated with impairment in cognitive control in adolescence: an fMRI study.  Neuropsychologia. 2010;48(10):3037-3044. doi:10.1016/j.neuropsychologia.2010.06.013PubMedGoogle ScholarCrossref
17.
Lim  L, Hart  H, Mehta  MA, Simmons  A, Mirza  K, Rubia  K.  Neural correlates of error processing in young people with a history of severe childhood abuse: an fMRI study.  Am J Psychiatry. 2015;172(9):892-900. doi:10.1176/appi.ajp.2015.14081042PubMedGoogle ScholarCrossref
18.
Mackiewicz Seghete  KL, Kaiser  RH, DePrince  AP, Banich  MT.  General and emotion-specific alterations to cognitive control in women with a history of childhood abuse.  Neuroimage Clin. 2017;16:151-164. doi:10.1016/j.nicl.2017.06.030PubMedGoogle ScholarCrossref
19.
Harms  MB, Birn  R, Provencal  N,  et al.  Early life stress, FK506 binding protein 5 gene (FKBP5) methylation, and inhibition-related prefrontal function: a prospective longitudinal study.  Dev Psychopathol. 2017;29(5):1895-1903. doi:10.1017/S095457941700147XPubMedGoogle ScholarCrossref
20.
Lim  L, Hart  H, Mehta  MA, Simmons  A, Mirza  K, Rubia  K.  Neurofunctional abnormalities during sustained attention in severe childhood abuse.  PLoS One. 2016;11(11):e0165547. doi:10.1371/journal.pone.0165547PubMedGoogle ScholarCrossref
21.
Marusak  HA, Martin  KR, Etkin  A, Thomason  ME.  Childhood trauma exposure disrupts the automatic regulation of emotional processing.  Neuropsychopharmacology. 2015;40(5):1250-1258. doi:10.1038/npp.2014.311PubMedGoogle ScholarCrossref
22.
McLaughlin  KA, Sheridan  MA.  Beyond cumulative risk: a dimensional approach to childhood adversity.  Curr Dir Psychol Sci. 2016;25(4):239-245. doi:10.1177/0963721416655883PubMedGoogle ScholarCrossref
23.
Pollak  SD, Cicchetti  D, Hornung  K, Reed  A.  Recognizing emotion in faces: developmental effects of child abuse and neglect.  Dev Psychol. 2000;36(5):679-688. doi:10.1037/0012-1649.36.5.679PubMedGoogle ScholarCrossref
24.
van Schie  CC, van Harmelen  AL, Hauber  K, Boon  A, Crone  EA, Elzinga  BM.  The neural correlates of childhood maltreatment and the ability to understand mental states of others.  Eur J Psychotraumatol. 2017;8(1):1272788. doi:10.1080/20008198.2016.1272788PubMedGoogle ScholarCrossref
25.
Dennison  MJ, Rosen  ML, Sambrook  KA, Jenness  JL, Sheridan  MA, McLaughlin  KA.  Differential associations of distinct forms of childhood adversity with neurobehavioral measures of reward processing: a developmental pathway to depression.  Child Dev. 2019;90(1);e96-e113.PubMedGoogle ScholarCrossref
26.
Sheridan  MA, Peverill  M, Finn  AS, McLaughlin  KA.  Dimensions of childhood adversity have distinct associations with neural systems underlying executive functioning.  Dev Psychopathol. 2017;29(5):1777-1794. doi:10.1017/S0954579417001390PubMedGoogle ScholarCrossref
27.
Lambert  HK, King  KM, Monahan  KC, McLaughlin  KA.  Differential associations of threat and deprivation with emotion regulation and cognitive control in adolescence.  Dev Psychopathol. 2017;29(3):929-940. doi:10.1017/S0954579416000584PubMedGoogle ScholarCrossref
28.
Blair  KS, Smith  BW, Mitchell  DG,  et al.  Modulation of emotion by cognition and cognition by emotion.  Neuroimage. 2007;35(1):430-440. doi:10.1016/j.neuroimage.2006.11.048PubMedGoogle ScholarCrossref
29.
Mitchell  DG, Nakic  M, Fridberg  D, Kamel  N, Pine  DS, Blair  RJ.  The impact of processing load on emotion.  Neuroimage. 2007;34(3):1299-1309. doi:10.1016/j.neuroimage.2006.10.012PubMedGoogle ScholarCrossref
30.
Mitchell  DGV, Luo  Q, Mondillo  K, Vythilingam  M, Finger  EC, Blair  RJR.  The interference of operant task performance by emotional distracters: an antagonistic relationship between the amygdala and frontoparietal cortices.  Neuroimage. 2008;40(2):859-868. doi:10.1016/j.neuroimage.2007.08.002PubMedGoogle ScholarCrossref
31.
White  SF, Costanzo  ME, Blair  JR, Roy  MJ.  PTSD symptom severity is associated with increased recruitment of top-down attentional control in a trauma-exposed sample.  Neuroimage Clin. 2014;7:19-27. doi:10.1016/j.nicl.2014.11.012PubMedGoogle ScholarCrossref
32.
Hwang  S, Nolan  ZT, White  SF, Williams  WC, Sinclair  S, Blair  RJ.  Dual neurocircuitry dysfunctions in disruptive behavior disorders: emotional responding and response inhibition.  Psychol Med. 2016;46(7):1485-1496. doi:10.1017/S0033291716000118PubMedGoogle ScholarCrossref
33.
Blair  KS, Vythilingam  M, Crowe  SL,  et al.  Cognitive control of attention is differentially affected in trauma-exposed individuals with and without post-traumatic stress disorder.  Psychol Med. 2013;43(1):85-95. doi:10.1017/S0033291712000840PubMedGoogle ScholarCrossref
34.
Blair  KS, Geraci  M, Smith  BW,  et al.  Reduced dorsal anterior cingulate cortical activity during emotional regulation and top-down attentional control in generalized social phobia, generalized anxiety disorder, and comorbid generalized social phobia/generalized anxiety disorder.  Biol Psychiatry. 2012;72(6):476-482. doi:10.1016/j.biopsych.2012.04.013PubMedGoogle ScholarCrossref
35.
Bernstein  DP, Ahluvalia  T, Pogge  D, Handelsman  L.  Validity of the Childhood Trauma Questionnaire in an adolescent psychiatric population.  J Am Acad Child Adolesc Psychiatry. 1997;36(3):340-348. doi:10.1097/00004583-199703000-00012PubMedGoogle ScholarCrossref
36.
Lang  PJ, Greenwald  MK.  International Affective Picture System Standardization Procedure and Initial Group Results for Affective Judgements: Technical Reports 1A & 1B. Gainesville: Center for Research in Psychophysiology, University of Florida; 1988.
37.
Cox  RW.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages.  Comput Biomed Res. 1996;29(3):162-173. doi:10.1006/cbmr.1996.0014PubMedGoogle ScholarCrossref
38.
Talairach  J, Tournoux  P.  Co-Planar Stereotaxic Atlas of the Human Brain. Stuttgart, Germany: Thieme Classics; 1988.
39.
Wagner  G, Sinsel  E, Sobanski  T,  et al.  Cortical inefficiency in patients with unipolar depression: an event-related fMRI study with the Stroop task.  Biol Psychiatry. 2006;59(10):958-965. doi:10.1016/j.biopsych.2005.10.025PubMedGoogle ScholarCrossref
40.
Krompinger  JW, Simons  RF.  Cognitive inefficiency in depressive undergraduates: Stroop processing and ERPs.  Biol Psychol. 2011;86(3):239-246. doi:10.1016/j.biopsycho.2010.12.004PubMedGoogle ScholarCrossref
41.
Gold  AL, Steuber  ER, White  LK,  et al.  Cortical thickness and subcortical gray matter volume in pediatric anxiety disorders.  Neuropsychopharmacology. 2017;42(12):2423-2433. doi:10.1038/npp.2017.83PubMedGoogle ScholarCrossref
42.
Gold  AL, Sheridan  MA, Peverill  M,  et al.  Childhood abuse and reduced cortical thickness in brain regions involved in emotional processing.  J Child Psychol Psychiatry. 2016;57(10):1154-1164. doi:10.1111/jcpp.12630PubMedGoogle ScholarCrossref
43.
Lim  L, Radua  J, Rubia  K.  Gray matter abnormalities in childhood maltreatment: a voxel-wise meta-analysis.  Am J Psychiatry. 2014;171(8):854-863. doi:10.1176/appi.ajp.2014.13101427PubMedGoogle ScholarCrossref
44.
Clithero  JA, Rangel  A.  Informatic parcellation of the network involved in the computation of subjective value.  Soc Cogn Affect Neurosci. 2014;9(9):1289-1302. doi:10.1093/scan/nst106PubMedGoogle ScholarCrossref
45.
De Pisapia  N, Barchiesi  G, Jovicich  J, Cattaneo  L.  The role of medial prefrontal cortex in processing emotional self-referential information: a combined TMS/fMRI study  [published online May 9, 2018].  Brain Imaging Behav. doi:10.1007/s11682-018-9867-3PubMedGoogle Scholar
46.
Bradley  RH, Corwyn  RF, McAdoo  HP, Coll  CG.  The home environments of children in the United States part I: variations by age, ethnicity, and poverty status.  Child Dev. 2001;72(6):1844-1867. doi:10.1111/1467-8624.t01-1-00382PubMedGoogle ScholarCrossref
47.
Pollak  SD, Vardi  S, Putzer Bechner  AM, Curtin  JJ.  Physically abused children’s regulation of attention in response to hostility.  Child Dev. 2005;76(5):968-977. doi:10.1111/j.1467-8624.2005.00890.xPubMedGoogle ScholarCrossref
48.
Norman  RE, Byambaa  M, De  R, Butchart  A, Scott  J, Vos  T.  The long-term health consequences of child physical abuse, emotional abuse, and neglect: a systematic review and meta-analysis.  PLoS Med. 2012;9(11):e1001349. doi:10.1371/journal.pmed.1001349PubMedGoogle ScholarCrossref
49.
Lansford  JE, Miller-Johnson  S, Berlin  LJ, Dodge  KA, Bates  JE, Pettit  GS.  Early physical abuse and later violent delinquency: a prospective longitudinal study.  Child Maltreat. 2007;12(3):233-245. doi:10.1177/1077559507301841PubMedGoogle ScholarCrossref
50.
Jaffee  SR, Caspi  A, Moffitt  TE, Taylor  A.  Physical maltreatment victim to antisocial child: evidence of an environmentally mediated process.  J Abnorm Psychol. 2004;113(1):44-55. doi:10.1037/0021-843X.113.1.44PubMedGoogle ScholarCrossref
51.
Briggs-Gowan  MJ, Carter  AS, Clark  R, Augustyn  M, McCarthy  KJ, Ford  JD.  Exposure to potentially traumatic events in early childhood: differential links to emergent psychopathology.  J Child Psychol Psychiatry. 2010;51(10):1132-1140. doi:10.1111/j.1469-7610.2010.02256.xPubMedGoogle ScholarCrossref
Limit 200 characters
Limit 25 characters
Conflicts of Interest Disclosure

Identify all potential conflicts of interest that might be relevant to your comment.

Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

Err on the side of full disclosure.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.

Not all submitted comments are published. Please see our commenting policy for details.

Limit 140 characters
Limit 3600 characters or approximately 600 words
    Original Investigation
    Psychiatry
    May 24, 2019

    Association of Different Types of Childhood Maltreatment With Emotional Responding and Response Control Among Youths

    Author Affiliations
    • 1Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, Nebraska
    • 2Department of Psychiatry, University of Nebraska Medical Center, Omaha
    • 3Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, Charleston
    • 4Target Holding, Groningen, the Netherlands
    • 5Department of Neurological Sciences, University of Nebraska Medical Center, Omaha
    • 6Department of Psychiatry, Creighton University, Omaha, Nebraska
    • 7Department of Psychology, University of Wisconsin, Madison
    JAMA Netw Open. 2019;2(5):e194604. doi:10.1001/jamanetworkopen.2019.4604
    Key Points español 中文 (chinese)

    Question  Are the amount and type (abuse vs neglect) of childhood maltreatment differentially associated with the responsiveness of regions of the brain implicated in emotional responding and response control?

    Findings  In this cross-sectional study including 116 youths aged 10 to 18 years, the amount of childhood maltreatment was inversely associated with the responsiveness of regions of the brain involved in response control and positively associated with emotional responding. This association was also found specifically for abuse but not for neglect.

    Meaning  Different types of childhood maltreatment may have different associations with atypical neural responses; therefore, they may have different associations with different forms of psychiatric neurobiology.

    Abstract

    Importance  Childhood maltreatment is associated with serious developmental consequences that may be different depending on the form of maltreatment. However, relatively little research has investigated this issue despite implications for understanding the development of psychiatric disorders after maltreatment.

    Objective  To determine the association of childhood maltreatment and potential differential associations of childhood abuse or neglect with neural responsiveness within regions of the brain implicated in emotional responding and response control.

    Design, Setting, and Participants  In this cross-sectional study, participants aged 10 to 18 years with varying levels of prior maltreatment as indexed by the Childhood Trauma Questionnaire (CTQ) were recruited from a residential care facility and the surrounding community. Blood oxygen level–dependent response data were analyzed via 2 analyses of covariance that examined 2 (sex) × 3 (task condition [view, congruent, incongruent]) × 3 (valence [negative, neutral, positive]) with Blom-transformed covariates: (1) total CTQ score; and (2) abuse and neglect subscores. Data were collected from April 1, 2016, to June 30, 2018. Data analyses occurred from June 10, 2018, to October 31, 2018.

    Main Outcomes and Measures  Blood oxygenation level–dependent signals in response to an Affective Stroop task were measured via functional magnetic resonance imaging.

    Results  The sample included 116 youths (mean [SD] age, 15.0 [2.2] years; 70 [60.3%] male). Fifteen participants reported no prior maltreatment. The remaining 101 participants (87.1%) reported at least some prior maltreatment, and 55 (54.5%) reported significant maltreatment, ie, total CTQ scores were greater than the validated CTQ score threshold of 40. There were significant total CTQ score × task condition associations within the bilateral postcentral gyrus, left precentral gyrus, midcingulate cortex, middle temporal gyrus, and superior temporal gyrus (left postcentral gyrus: F = 11.73; partial η2 = 0.14; right postcentral and precentral gyrus: F = 9.81; partial η2 = 0.10; midcingulate cortex: F = 12.76; partial η2 = 0.12; middle temporal gyrus: F = 13.24; partial η2 = 0.10; superior temporal gyrus: F = 10.33; partial η2 = 0.11). In all examined regions of the brain, increased maltreatment was associated with decreased differential responsiveness to incongruent task trials compared with view trials (left postcentral gyrus: r = −0.34; 95% CI, −0.17 to −0.51; right postcentral and precentral gyrus: r = −0.31; 95% CI, −0.14 to −0.49; midcingulate cortex: r = −0.36; 95% CI, −0.18 to −0.53; middle temporal gyrus: r = −0.35; 95% CI, −0.17 to −0.52; superior temporal gyrus: r = −0.37; 95% CI, −0.20 to −0.55). These interactions were particularly associated with level of abuse rather than neglect. A second analysis of covariance revealed significant abuse × task condition (but not neglect × task) interactions within the midcingulate cortex (F = 13.96; partial η2 = 0.11), right postcentral gyrus and inferior parietal lobule (F = 15.21; partial η2 = 0.12), left postcentral and precentral gyri (F = 11.16; partial η2 = 0.12), and rostromedial frontal cortex (F = 10.36; partial η2 = 0.08)). In all examined regions of the brain, increased abuse was associated with decreased differential responsiveness to incongruent task trials compared with view trials (midcingulate cortex: partial r = −0.33; P < .001; right postcentral gyrus and inferior parietal lobule: partial r = −0.41; P < .001; left postcentral and precentral gyri: partial r = −0.40; P < .001; and rostromedial frontal cortex: partial r = −0.40; P < .001).

    Conclusions and Relevance  These data document associations of different forms of childhood maltreatment with atypical neural response. This suggests that forms of maltreatment may differentially influence the development of psychiatric pathology.

    Introduction

    Childhood maltreatment is associated with neurodevelopmental disruption,1 psychopathology2-5 (ie, heightened threat sensitivity6-9), heightened amygdala responsiveness,10-12 and disrupted reinforcement-based decision making.13-15 Maltreatment may also be associated with executive dysfunction, although there is some inconsistency in the findings.16-19 Two studies examining response control reported increased responsiveness within the dorsal cingulate cortex and midcingulate cortex and precentral and postcentral gyri during response control in maltreated children and adolescents.16,17 However, 2 other studies using similar tasks reported that a history of childhood maltreatment in women18 and a history of exposure to childhood stress in adults19 were associated with decreased responsiveness in the frontal or frontal-parietal regions of the brain. Moreover, a 2016 study20 reported a history of childhood maltreatment was associated with significantly reduced activation during sustained attention within regions of the brain in adults, including the left inferior cortex, dorsolateral prefrontal cortex, insula, and temporal cortex, compared with healthy controls.

    This inconsistency in the association of maltreatment with executive function might reflect differences in the forms of maltreatment experienced by participants. To our knowledge, much of the previous literature has either grouped together participants who have experienced different forms of maltreatment11,21 or only considered 1 form of maltreatment, eg, deprivation.10 However, different forms of childhood maltreatment may have distinct consequences for development (even if many individuals who have experienced maltreatment experienced multiple forms of maltreatment).22-27 In particular, the literature suggests that threatening contexts (eg, physical abuse [PA] or sexual abuse [SA]) increase threat responsiveness while deprivation (eg, physical neglect [PN] or emotional neglect [EN]) disrupts aspects of learning, memory, and executive function.22,26,27

    The goal of this study was to examine the association of childhood maltreatment and childhood abuse or neglect with the responsiveness of neural regions implicated in emotional responding and response control via the Affective Stroop task.28 We chose an emotion-based response control task rather than one that was affectively neutral because of previous research indicating that maltreatment disrupts emotional regulation, which might in turn disrupt response control or other forms of executive function.28-30 In the Affective Stroop task, participants either perform a goal-directed activity (ie, counting the number of numerals) in the context of emotional and neutral distracter images (eFigure, A and B, in the Supplement) or simply view the emotional and neutral images (eFigure, C, in the Supplement). The task indexes systems engaged in response control via the main effect of task condition. Regions of the brain implicated in response control or the organization of motor responses show increased responses to number task trials compared with view trials (eg, dorsomedial frontal cortex and lateral frontal lobe, anterior insula, parietal lobe, premotor cortex, and motor cortex). In contrast, regions of the brain implicated in distracter representation show increased responses to view trials compared with task trials (eg, temporal cortex, ventromedial frontal cortex, rostromedial frontal cortex [rmFC], and amygdala). Impaired goal-directed emotional regulation manifests as reduced suppression of activity within regions of the brain involved in distracter representation on number task trials.28-34

    Therefore, we hypothesized first that maltreatment would be positively associated with responsiveness to distracters and inversely associated with the responsiveness of regions of the brain involved in response control. Second, we hypothesized that abusive forms of maltreatment (ie, SA, emotional abuse [EA], and PA) and neglectful forms of maltreatment (ie, EN and PN) would differ in their associations with atypical neural functioning.23 Specifically, on the basis of previous suggestions,22 we hypothesized that abuse would be positively associated with responsiveness to distracters while neglect would be negatively associated with the responsiveness of regions of the brain involved in response control. In addition to these hypotheses, we conducted exploratory analyses to examine the extent to which different subforms of abuse and neglect might be associated in different ways with the responsiveness of regions of the brain implicated in emotional responding and response control. Given the exploratory nature of this last goal, we did not make specific predictions a priori.

    Methods
    Participants

    Participants included 116 youths aged 10 to 18 years (Table 1). Participants were recruited either within 1 week of their arrival at a residential care facility (n = 70) or from the surrounding community (n = 46). Participants recruited from the care facility had been referred for behavioral and mental health problems. Participants from the community were recruited through flyers.

    Clinical characterizations were performed through psychiatric interviews by 2 authors who are licensed and board-certified child and adolescent psychiatrists (M.D. and K.P.) with the participants and separately with their parents or guardians to adhere closely to common clinical practice. Written informed consent from the parents or guardians and written assent from the participants were obtained. In all cases, youths had the right to decline participation at any time before or during the study. Consent documents were reviewed with the parents or legal guardians and written permission was obtained at the initial visit for community participants or at the time of intake for youths placed in Boys Town programs (eAppendix 1 in the Supplement). Assent was obtained from the youth from the community in a separate session. The Boys Town National Research Hospital institutional review board approved this study.

    Data for this study were collected from April 1, 2016, to June 30, 2018. Data analysis occurred from June 10, 2018, to October 31, 2018. This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

    Childhood Trauma Questionnaire

    Child maltreatment was assessed using the Childhood Trauma Questionnaire (CTQ), a 28-item self-reported measure containing 5 subscales indexing EA, PA, SA, EN, and PN. The CTQ has excellent psychometric properties, including internal consistency, test-retest reliability, and convergent and discriminant validity with interviews and clinician reports of maltreatment.35 Individuals respond to each item using a 5-point Likert scale, and scores range from 25 (no history of abuse or neglect) to 125 (extreme abuse or neglect).

    Functional Magnetic Resonance Imaging Task

    The Affective Stroop task was adapted from a 2007 study by Blair et al28 and a 2016 study by Hwang et al32 (eAppendix 2 and eFigure in the Supplement). In brief, on congruent and incongruent trials, participants responded using buttons to indicate the number of numerals (3, 4, 5, or 6) presented temporally between picture images (eFigure in the Supplement). In view trials, participants received a blank between the display of the picture images (no response required). Sixteen images for each affect (negative, neutral, and positive) were selected from the International Affective Picture System.36

    Each participant underwent 2 rounds of testing. Each round included 16 presentations of each valence × condition combination throughout the round. In addition, forty 2500-millisecond fixation points were randomly presented throughout each round. Thus, each participant was presented with a total of 32 trials of each valence × task condition.

    Functional Magnetic Resonance Imaging Parameters

    Whole-brain blood oxygen level–dependent functional magnetic resonance imaging data were acquired using a MAGNETOM Skyra magnetic resonance scanner (Siemens Medical Solutions) (eAppendix 3 in the Supplement). Data were analyzed with a random-effects general linear model using Analysis of Functional NeuroImages functional magnetic resonance imaging software (National Institute of Mental Health Scientific and Statistical Computing Core).37

    Ten regressors depicting each of the response types were created: negative view, negative congruent, negative incongruent, neutral view, neutral congruent, neutral incongruent, positive view, positive congruent, positive incongruent, and error or missed responses. Voxelwise group analyses involved transforming single-subject β coefficients into the 3-dimensional standard coordinate system of Talairach space.38 Generalized linear model fitting was performed with the 10 regressors, 6 motion regressors (rotation around the inferior-superior axis, rotation around the right-left axis, rotation around the anterior-posterior axis, displacement in the superior direction, displacement in the left direction, and displacement in the posterior direction), and a regressor modeling a first-order baseline drift function.

    Statistical Analysis

    To reduce skewness and kurtosis, a Blom transformation was applied to participants’ total CTQ and CTQ subscale scores. Posttransformation, skewness and kurtosis values for CTQ and all subscores were between −1 and 1.

    Clinical Correlations

    Pearson correlation analyses were conducted to determine the associations among Blom-transformed CTQ total scores, abuse (EA + SA + PA) score, neglect (EN + PN) score, age, IQ score, sex, and whether the individual had received 1 or more of 6 psychiatric diagnoses (conduct disorder, attention-deficit/hyperactivity disorder, major depressive disorder, generalized anxiety disorder, social anxiety disorder, or posttraumatic stress disorder) or not (scored 1 or 0, respectively). Steiger z tests were performed to determine whether there were significant differences in correlation strengths between amount of abuse or neglect and any of the psychiatric diagnoses. For all these analyses, P values were 2-tailed and considered significant at less than .05.

    Blood Oxygen Level–Dependent Response Data

    Two core analyses of covariance (ANCOVAs) were performed on the blood oxygen level–dependent response data. Both had the same basic model structure. Specifically, because of sex differences in total CTQ scores and EA and SA subscores, full 2 (sex) × 3 (task condition [view, congruent, incongruent]) × 3 (valence [negative, neutral, positive]) ANCOVAs were conducted.

    The first ANCOVA, focusing on the association of maltreatment with atypical brain function, involved 1 covariate, total CTQ score. The second ANCOVA, focusing on differential associations of abuse compared with neglect with atypical neural functioning, involved 2 covariates, abuse (EA + PA + SA) subscore and neglect (EN + PN) subscore.

    Correction for multiple comparisons was performed using 3dClustSim, a spatial clustering operation in the Analysis of Functional NeuroImages software, using the autocorrelation function (−acf) with 10 000 Monte Carlo simulations for the whole-brain analysis. The initial threshold for P value was set at .001. This process resulted in an extant k threshold of 24 voxels for the whole brain (multiple comparison–corrected, P < .05). To facilitate future meta-analytic work, effect sizes (partial η2) for all clusters are reported in Table 2.

    Associations of covariates with task variables identified via the ANCOVAs were interpreted via correlational analyses using SPSS statistical software version 22.0 (IBM), and significance was set at P less than .05. For the results of the second (2-covariate) ANCOVA, these correlations controlled for the second covariate.

    Our exploratory goal—examining the extent to which different subforms of abuse are associated with different neural response—was examined by 3 exploratory 2 (sex) × 3 (task condition) × 3 (valence) ANCOVAs. Covariates were (1) EA and PA, (2) SA and all other forms of abuse combined (given the very small number of male participants reporting SA in this sample, the association with SA was examined only among the female participants), and (3) EN and PN.

    Results
    Levels of Maltreatment and Clinical Correlations

    There were 116 youths included in the study (mean [SD] age, 15.0 [2.2] years; 70 [60.3%] male participants). The mean (SD) IQ score was 103.1 (12.2). Fifteen youths reported no prior maltreatment (total CTQ score = 25). The remaining 101 youths reported at least some prior maltreatment, with 55 (54.5%) reporting significant amounts of maltreatment (ie, their CTQ scores were greater than validated thresholds [total CTQ score, ≥40; EA subscore, ≥10; SA subscore, ≥8; PA subscore, ≥8; EN subscore, ≥15; or PN subscore, ≥8]).11,36 All participants reporting significant SA or PA were discussed by 1 of 3 of us (K.C., P.M.T., or M.D.) with the participants’ consultants to confirm that this had been previously identified and was followed up.

    There were no significant associations of total CTQ score or CTQ subscore with age or IQ score. However, compared with male participants, female participants had a significantly greater mean total CTQ score (F = 8.68; P = .01), mean EA subscore (F = 6.36; P = .004), and mean SA subscore (F = 17.87; P < .001) (Table 1). In addition, there were significant positive correlations of both amount of abuse and amount of neglect with all 6 psychiatric diagnoses assessed and with the self-report measures (eTable 1 in the Supplement). There were no significant differences in correlation strengths between amount of abuse or neglect and any of the psychiatric diagnoses or self-report measures except posttraumatic stress disorder. Among patients who had received diagnoses of posttraumatic stress disorder, the amount of abuse showed a significantly greater correlation with diagnosis compared with amount of neglect (Steiger z = 2.62; P < .05).

    Association of Maltreatment With Atypical Neural Functioning

    Details on the measurement and calculation of behavior and movement data can be found in eTable 4 in the Supplement. Our first ANCOVA revealed regions showing several significant interactions (Table 2).

    There were significant total CTQ score × task condition interactions in regions of the brain implicated in response control and motor responding (left postcentral gyrus: F = 11.73; partial η2 = 0.14; right postcentral and precentral gyri: F = 9.81; partial η2 = 0.10; midcingulate cortex: F = 12.76; partial η2 = 0.12; middle temporal gyrus [mTG]: F = 13.24; partial η2 = 0.10; sTG: F = 10.33; partial η2 = 0.11) and in regions of the brain implicated in distracter representation (left mTG, and right superior temporal gyrus [sTG]) (Table 2). Within all examined regions, increased maltreatment was associated with decreased differential responsiveness to both incongruent task trials (left postcentral gyrus: r = −0.34; 95% CI, −0.17 to −0.51; right postcentral and precentral gyri: r = −0.31; 95% CI,−0.14 to −0.49; midcingulate cortex: r = −0.36; 95% CI, −0.18 to −0.53; mTG: r = −0.35; 95% CI, −0.17 to −0.52; sTG: r = −0.37; 95% CI, −0.20 to −0.55) and congruent task trials (left postcentral gyrus: r = −0.42; 95% CI, −0.25 to −0.59; right postcentral and precentral gyri: r = −0.39; 95% CI, −0.22 to −0.56; midcingulate cortex: r = −0.38; 95% CI, −0.20 to −0.55; mTG: r = −0.45; 95% CI, −0.28 to −0.61; sTG: r = −0.43; 95% CI, −0.26 to −0.60) compared with view trials (Figure 1A and B). All other statistically significant results are presented in eTable 2 in the Supplement.

    Differential Associations of Abuse Compared with Neglect With Atypical Neural Functioning

    Our second ANCOVA revealed statistically significant abuse × task condition interactions in regions of the brain implicated in response control and motor responding (eg, midcingulate cortex: F = 13.96; partial η2 = 0.11 [Figure 1C]; right postcentral gyrus and inferior parietal lobule: F = 15.21; partial η2 = 0.12 [Figure 1D]; left postcentral and precentral gyri: F = 11.16; partial η2 = 0.12) and those implicated in distracter representation that was suppressed by goal-directed activity (eg, rmFC: F = 10.36; partial η2 = 0.08) (Table 2 and Figure 1E). Within the regions of the brain implicated in response control and motor responding, after adjusting for covariates, the amount of abuse was negatively correlated with differential responsiveness to incongruent trials (midcingulate cortex: partial r = 0.33; P < .001; right postcentral gyrus and inferior parietal lobule: partial r = −0.41; P < .001; left precentral and postcentral gyri: partial r = −0.40; P < .001) and congruent trials (right inferior parietal lobule and postcentral gyrus: partial r = −0.37; P < .001) compared with view trials (Figure 1C and D). Within the rmFC, the amount of abuse was positively correlated with differential responsiveness to view relative to both incongruent trials (rmFC: partial r = −0.40; P < .001) and congruent trials (partial r = −0.30; P = .002).

    There were significant neglect × task condition interactions within cuneus (Table 2). After adjusting for covariates, the amount of neglect was negatively correlated with differential responsiveness to congruent trials compared with view trials (r = −0.38; P < .001). All other significant results are presented in eTable 3 in the Supplement.

    Examining Potential Confounders of Recruitment Strategy and Diagnosis

    Given that participants were recruited from both a residential treatment center and from the community, we examined whether this variable could have critically influenced our results. We repeated our 2 core ANCOVAs by adding residential care facility vs community as a covariate. This added covariate was associated with minor changes to the results reported in Table 2. eTable 4 and eTable 5 in the Supplement present the full overview of these analyses.

    We examined diagnostic status as a potential confounder via a series of ANCOVAs involving an additional covariate coding each psychiatric condition (present vs not present). In all cases, the added covariate was associated with minor changes to the results reported in Table 2. eTable 4 and eTable 5 in the Supplement present the full overview of these analyses.

    Exploring Associations of Different Subforms of Abuse With Atypical Neural Functioning
    Emotional Abuse × Task Condition Interactions

    There were significant EA × task condition interactions in the inferior parietal lobule and culmen (eTable 6 in the Supplement). Within the inferior parietal lobule and culmen, amount of EA was negatively correlated with differential responsiveness to both incongruent task trials (inferior parietal lobule: partial r = −0.31, P = .001; culmen: partial r = −0.34, P < .001) and congruent task trials (inferior parietal lobule: partial r = −0.23, P = .01; culmen: partial r = −0.29, P = .002) relative to view trials (Figure 2A).

    Physical Abuse × Valence Interactions

    There were significant PA × valence associations in the dorsomedial prefrontal and lateral frontal cortices (eTable 6 in the Supplement). Within both regions, amount of PA was positively correlated with differential responsiveness to negative stimuli compared with positive stimuli (prefrontal cortex: partial r = 0.30, P = .001; lateral frontal cortex: partial r = 0.34, P < .001) (Figure 2B and C).

    Sexual Abuse × Task Condition Interactions

    There were significant SA × task condition associations in the anterior cingulate cortex, rmFC, and bilateral postcentral gyrus that overlapped with regions of the brain showing abuse × task condition associations in the main analysis (eTable 7 in the Supplement). Within all regions examined, amount of SA was positively correlated with differential responsiveness to view trials compared with incongruent task trials (anterior cingulate cortex and rmFC: partial r = 0.51; P < .001; right postcentral gyrus: partial r = 0.65; P < .001; left postcentral gyrus: partial r = 0.56; P < .001) (Figure 3). Other associations of subforms of abuse with atypical neural functioning analyses are listed in eTables 6-8 in the Supplement.

    Discussion

    The goals of this study were to determine the extent to which maltreatment, abuse, and neglect may be differentially associated with atypical neural functioning. We found that maltreatment was associated with reduced responsiveness of regions of the brain implicated in response control and increased responsiveness of regions of the brain implicated in responding to and representing affective information. We also found that the amount of abuse, but not the amount of neglect, was associated with increased responsiveness of regions of the brain implicated in responding to and representing affective information (rmFC, mTG, and sTG). Additionally, and in contrast with predictions, we found that the amount of abuse, but not the amount of neglect, was associated with decreased responsiveness of regions of the brain implicated in response control and motor responding (inferior parietal lobule and postcentral gyrus). Exploratory analyses of different subforms of abuse and neglect also found an association of amount of PA with enhanced responsiveness to threat information within regions of the brain implicated in attentional processing (dorsomedial frontal cortex and lateral frontal cortex). There was also an association of SA with enhanced processing of salient visual stimuli in regions of the brain involved in the representation of emotional valence.

    Additionally, we found that the amount of maltreatment was inversely associated with responsiveness of regions of the brain involved in response control. Notably, our findings related to the postcentral gyrus and midcingulate cortex are similar to 2 previous studies examining response control and behavioral inhibition in maltreated children and adolescents.16,17 These studies found maltreatment increased responsiveness within these regions of the brain during response inhibition, although decreased responsiveness as a function of maltreatment has also been previously reported.18-20 Potentially, maltreatment disrupts the functional efficiency of regions of the brain implicated in response control and behavioral inhibition, and the disruption may be expressed as increased or decreased responsiveness as a function of task parameters. A similar argument has been made for similarly inconsistent findings in patients with depression.39,40

    We also found that maltreatment was positively associated with responsiveness to distracters and emotional stimuli within the rmFC, ventromedial frontal cortex, mTG, and sTG. Previous structural imaging studies have reported that these regions of the brain are smaller in individuals exposed to prior maltreatment.41-43 The rmFC and ventromedial frontal cortex have been implicated in the representation of valence44 and, for the rmFC in particular, affect-based self-referential processing.45 Therefore, our data are consistent with suggestions that the amount of maltreatment (particularly abuse) is associated with enhanced processing of salient stimuli.6-9

    We found that amount of abuse was associated with increased responsiveness of regions of the brain implicated in responding to and representing affective information (rmFC, mTG, and sTG). Amount of neglect was also associated with a heightened responsiveness to salient visual stimuli, albeit only within visual cortices. In short, amount of maltreatment may generally increase responsiveness to salient visual stimuli. However, it is possible that abuse may increase responsiveness to affect-based stimuli (consistent with hypervigilance to threat) while neglect does so to general environmental stimuli (consistent with emotional numbing).

    We found no association of amount of neglect with decreased responsiveness in regions of the brain implicated in response control and motor responding. Instead, amount of abuse was associated with decreased responsiveness in these regions (inferior parietal lobule, postcentral gyrus, and midcingulate cortex). In their 2017 article, McLaughlin and Sheridan22 hypothesized that cognitive deprivation disrupts aspects of learning, memory, and executive function. While our study does not support that hypothesis, it is possible that PN and EN, as indexed by the CTQ, do not equate to cognitive deprivation.46 Future work will require more precise indices of cognitive deprivation to test the hypothesis.

    Our analysis of potential differential associations of specific forms of abuse and neglect with atypical neural functioning must be considered to be exploratory. However, there are several features of interest. First, PA was the only form of maltreatment shown to demonstrate an exaggerated response to threat on this task. This agrees with a 2000 study23 and a 2005 study47 suggesting that PA is, compared with other forms of maltreatment, particularly associated with an attentional threat bias. Second, there were notable overlaps in regions of the brain disrupted by both EA and SA, which supported the findings related to abuse generally compared with neglect. It is possible that both have profound impacts on development, perhaps by disrupting capacities to form relationships with others.

    Limitations

    There are several limitations that should be noted with respect to our results. First, the forms of neglect measured by the CTQ are indirect measures of cognitive deprivation. As such, our data do not provide a direct test of the cognitive deprivation hypothesis.22 Second, consistent with considerable previous work,2-4,48-51 increasing amount of maltreatment was associated with increasing severity of psychopathology. Accordingly, our results might reflect psychopathology rather than maltreatment. Ameliorating this concern is the fact that there were no significant differences in correlation strengths between amount of abuse or amount of neglect with any of the psychiatric diagnoses except posttraumatic stress disorder. Further, the follow-up analyses that we conducted with psychiatric diagnosis as separate covariates for our 2 main analyses did not significantly change our results (eTable 4 and eTable 5 in the Supplement), suggesting that psychiatric diagnostic status did not significantly confound the results. Third, our study involved participants from a residential care facility and from the community, and it is possible that this recruitment strategy could have influenced our results. However, the results from follow-up analyses with recruitment strategy as a covariate were in line with the results reported without this covariate (eTable 4 and eTable 5 in the Supplement). Thus, recruitment strategy does not appear to have been a prime determinant of the results. Fourth, most participants who had experienced abuse had also experienced neglect, potentially making the associations of these different forms of maltreatment difficult to untangle. Importantly, though, the regions of the brain showing significant abuse × task associations showed these associations whether the neglect covariate was present in the ANCOVA (Table 2) or not (eTable 9 in the Supplement). Moreover, none of these revealed neglect × task associations even at very low initial thresholds (eTable 10 in the Supplement). Fourth, our sample identified very few male participants who reported experiences of SA. As such, the conclusions regarding the neural associations of SA are based on female participants only.

    Conclusions

    In conclusion, this study found that amount of childhood maltreatment was inversely associated with the responsiveness of regions of the brain involved in response control and positively associated with responsiveness to emotional stimuli and distractors. This association was statistically more significant for abuse compared with neglect. Moreover, exploratory analyses suggested that SA was associated with widespread disruptions of neural systems involved in emotional responding, while PA was associated with heightened processing of threat. It is plausible that these potentially differential associations could underpin potentially differential risks of specific forms of psychiatric sequelae as functions of form and amount of abuse.

    Back to top
    Article Information

    Accepted for Publication: April 3, 2019.

    Published: May 24, 2019. doi:10.1001/jamanetworkopen.2019.4604

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Blair KS et al. JAMA Network Open.

    Corresponding Author: Karina S. Blair, PhD, Center for Neurobehavioral Research, Boys Town National Research Hospital, 14100 Crawford St, Boys Town, Nebraska 68010-7520 (karina.blair@boystown.org).

    Author Contributions: Dr K. S. Blair had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: K. S. Blair, Meffert, Abdel-Rahim, Lukoff, Pope, R. J. Blair.

    Acquisition, analysis, or interpretation of data: K. S. Blair, Aloi, Crum, Meffert, White, Taylor, Leiker, Thornton, Tyler, Shah, Johnson, Abdel-Rahim, Dobbertin, Pope, Pollak, R. J. Blair.

    Drafting of the manuscript: K. S. Blair, Leiker, Pollak, R. J. Blair.

    Critical revision of the manuscript for important intellectual content: K. S. Blair, Aloi, Crum, Meffert, White, Taylor, Leiker, Thornton, Tyler, Shah, Johnson, Abdel-Rahim, Lukoff, Dobbertin, Pope, R. J. Blair.

    Statistical analysis: K. S. Blair, Aloi, Crum, Tyler.

    Obtained funding: K. S. Blair, Pope, R. J. Blair.

    Administrative, technical, or material support: Aloi, Meffert, White, Taylor, Leiker, Thornton, Johnson, Lukoff, Dobbertin.

    Supervision: Dobbertin, Pope, R. J. Blair.

    Conflict of Interest Disclosures: None reported.

    Funding/Support: This research was in part supported by the National Institute of General Medical Sciences of the National Institutes of Health (Dr K. S. Blair) and the National Institute of Mental Health (Dr R. J. Blair).

    Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    References
    1.
    Bremne  JD, Vermetten  E.  Stress and development: behavioral and biological consequences.  Dev Psychopathol. 2001;13(3):473-489. doi:10.1017/S0954579401003042PubMedGoogle ScholarCrossref
    2.
    Shonkoff  JP, Garner  AS; Committee on Psychosocial Aspects of Child and Family Health; Committee on Early Childhood, Adoption, and Dependent Care; Section on Developmental and Behavioral Pediatrics.  The lifelong effects of early childhood adversity and toxic stress.  Pediatrics. 2012;129(1):e232-e246. doi:10.1542/peds.2011-2663PubMedGoogle ScholarCrossref
    3.
    McLaughlin  KA, Green  JG, Gruber  MJ, Sampson  NA, Zaslavsky  AM, Kessler  RC.  Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication II: associations with persistence of DSM-IV disorders.  Arch Gen Psychiatry. 2010;67(2):124-132. doi:10.1001/archgenpsychiatry.2009.187PubMedGoogle ScholarCrossref
    4.
    Green  JG, McLaughlin  KA, Berglund  PA,  et al.  Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication I: associations with first onset of DSM-IV disorders.  Arch Gen Psychiatry. 2010;67(2):113-123. doi:10.1001/archgenpsychiatry.2009.186PubMedGoogle ScholarCrossref
    5.
    McCrory  EJ, Gerin  MI, Viding  E.  Annual research review: childhood maltreatment, latent vulnerability and the shift to preventative psychiatry—the contribution of functional brain imaging.  J Child Psychol Psychiatry. 2017;58(4):338-357. doi:10.1111/jcpp.12713PubMedGoogle ScholarCrossref
    6.
    Pollak  SD.  Early adversity and mechanisms of plasticity: integrating affective neuroscience with developmental approaches to psychopathology.  Dev Psychopathol. 2005;17(3):735-752. doi:10.1017/S0954579405050352PubMedGoogle ScholarCrossref
    7.
    Toth  SL, Cicchetti  D.  Frontiers in translational research on trauma.  Dev Psychopathol. 2011;23(2):353-355. doi:10.1017/S0954579411000101PubMedGoogle ScholarCrossref
    8.
    Pollak  SD, Sinha  P.  Effects of early experience on children’s recognition of facial displays of emotion.  Dev Psychol. 2002;38(5):784-791. doi:10.1037/0012-1649.38.5.784PubMedGoogle ScholarCrossref
    9.
    Pine  DS, Mogg  K, Bradley  BP,  et al.  Attention bias to threat in maltreated children: implications for vulnerability to stress-related psychopathology.  Am J Psychiatry. 2005;162(2):291-296. doi:10.1176/appi.ajp.162.2.291PubMedGoogle ScholarCrossref
    10.
    Tottenham  N, Hare  TA, Millner  A, Gilhooly  T, Zevin  JD, Casey  BJ.  Elevated amygdala response to faces following early deprivation.  Dev Sci. 2011;14(2):190-204. doi:10.1111/j.1467-7687.2010.00971.xPubMedGoogle ScholarCrossref
    11.
    McCrory  EJ, De Brito  SA, Kelly  PA,  et al.  Amygdala activation in maltreated children during pre-attentive emotional processing.  Br J Psychiatry. 2013;202(4):269-276. doi:10.1192/bjp.bp.112.116624PubMedGoogle ScholarCrossref
    12.
    McLaughlin  KA, Peverill  M, Gold  AL, Alves  S, Sheridan  MA.  Child maltreatment and neural systems underlying emotion regulation.  J Am Acad Child Adolesc Psychiatry. 2015;54(9):753-762. doi:10.1016/j.jaac.2015.06.010PubMedGoogle ScholarCrossref
    13.
    Birn  RM, Roeber  BJ, Pollak  SD.  Early childhood stress exposure, reward pathways, and adult decision making.  Proc Natl Acad Sci U S A. 2017;114(51):13549-13554. doi:10.1073/pnas.1708791114PubMedGoogle ScholarCrossref
    14.
    Gerin  MI, Puetz  VB, Blair  RJR,  et al.  A neurocomputational investigation of reinforcement-based decision making as a candidate latent vulnerability mechanism in maltreated children.  Dev Psychopathol. 2017;29(5):1689-1705. doi:10.1017/S095457941700133XPubMedGoogle ScholarCrossref
    15.
    Harms  MB, Shannon Bowen  KE, Hanson  JL, Pollak  SD.  Instrumental learning and cognitive flexibility processes are impaired in children exposed to early life stress.  Dev Sci. 2018;21(4):e12596.PubMedGoogle ScholarCrossref
    16.
    Mueller  SC, Maheu  FS, Dozier  M,  et al.  Early-life stress is associated with impairment in cognitive control in adolescence: an fMRI study.  Neuropsychologia. 2010;48(10):3037-3044. doi:10.1016/j.neuropsychologia.2010.06.013PubMedGoogle ScholarCrossref
    17.
    Lim  L, Hart  H, Mehta  MA, Simmons  A, Mirza  K, Rubia  K.  Neural correlates of error processing in young people with a history of severe childhood abuse: an fMRI study.  Am J Psychiatry. 2015;172(9):892-900. doi:10.1176/appi.ajp.2015.14081042PubMedGoogle ScholarCrossref
    18.
    Mackiewicz Seghete  KL, Kaiser  RH, DePrince  AP, Banich  MT.  General and emotion-specific alterations to cognitive control in women with a history of childhood abuse.  Neuroimage Clin. 2017;16:151-164. doi:10.1016/j.nicl.2017.06.030PubMedGoogle ScholarCrossref
    19.
    Harms  MB, Birn  R, Provencal  N,  et al.  Early life stress, FK506 binding protein 5 gene (FKBP5) methylation, and inhibition-related prefrontal function: a prospective longitudinal study.  Dev Psychopathol. 2017;29(5):1895-1903. doi:10.1017/S095457941700147XPubMedGoogle ScholarCrossref
    20.
    Lim  L, Hart  H, Mehta  MA, Simmons  A, Mirza  K, Rubia  K.  Neurofunctional abnormalities during sustained attention in severe childhood abuse.  PLoS One. 2016;11(11):e0165547. doi:10.1371/journal.pone.0165547PubMedGoogle ScholarCrossref
    21.
    Marusak  HA, Martin  KR, Etkin  A, Thomason  ME.  Childhood trauma exposure disrupts the automatic regulation of emotional processing.  Neuropsychopharmacology. 2015;40(5):1250-1258. doi:10.1038/npp.2014.311PubMedGoogle ScholarCrossref
    22.
    McLaughlin  KA, Sheridan  MA.  Beyond cumulative risk: a dimensional approach to childhood adversity.  Curr Dir Psychol Sci. 2016;25(4):239-245. doi:10.1177/0963721416655883PubMedGoogle ScholarCrossref
    23.
    Pollak  SD, Cicchetti  D, Hornung  K, Reed  A.  Recognizing emotion in faces: developmental effects of child abuse and neglect.  Dev Psychol. 2000;36(5):679-688. doi:10.1037/0012-1649.36.5.679PubMedGoogle ScholarCrossref
    24.
    van Schie  CC, van Harmelen  AL, Hauber  K, Boon  A, Crone  EA, Elzinga  BM.  The neural correlates of childhood maltreatment and the ability to understand mental states of others.  Eur J Psychotraumatol. 2017;8(1):1272788. doi:10.1080/20008198.2016.1272788PubMedGoogle ScholarCrossref
    25.
    Dennison  MJ, Rosen  ML, Sambrook  KA, Jenness  JL, Sheridan  MA, McLaughlin  KA.  Differential associations of distinct forms of childhood adversity with neurobehavioral measures of reward processing: a developmental pathway to depression.  Child Dev. 2019;90(1);e96-e113.PubMedGoogle ScholarCrossref
    26.
    Sheridan  MA, Peverill  M, Finn  AS, McLaughlin  KA.  Dimensions of childhood adversity have distinct associations with neural systems underlying executive functioning.  Dev Psychopathol. 2017;29(5):1777-1794. doi:10.1017/S0954579417001390PubMedGoogle ScholarCrossref
    27.
    Lambert  HK, King  KM, Monahan  KC, McLaughlin  KA.  Differential associations of threat and deprivation with emotion regulation and cognitive control in adolescence.  Dev Psychopathol. 2017;29(3):929-940. doi:10.1017/S0954579416000584PubMedGoogle ScholarCrossref
    28.
    Blair  KS, Smith  BW, Mitchell  DG,  et al.  Modulation of emotion by cognition and cognition by emotion.  Neuroimage. 2007;35(1):430-440. doi:10.1016/j.neuroimage.2006.11.048PubMedGoogle ScholarCrossref
    29.
    Mitchell  DG, Nakic  M, Fridberg  D, Kamel  N, Pine  DS, Blair  RJ.  The impact of processing load on emotion.  Neuroimage. 2007;34(3):1299-1309. doi:10.1016/j.neuroimage.2006.10.012PubMedGoogle ScholarCrossref
    30.
    Mitchell  DGV, Luo  Q, Mondillo  K, Vythilingam  M, Finger  EC, Blair  RJR.  The interference of operant task performance by emotional distracters: an antagonistic relationship between the amygdala and frontoparietal cortices.  Neuroimage. 2008;40(2):859-868. doi:10.1016/j.neuroimage.2007.08.002PubMedGoogle ScholarCrossref
    31.
    White  SF, Costanzo  ME, Blair  JR, Roy  MJ.  PTSD symptom severity is associated with increased recruitment of top-down attentional control in a trauma-exposed sample.  Neuroimage Clin. 2014;7:19-27. doi:10.1016/j.nicl.2014.11.012PubMedGoogle ScholarCrossref
    32.
    Hwang  S, Nolan  ZT, White  SF, Williams  WC, Sinclair  S, Blair  RJ.  Dual neurocircuitry dysfunctions in disruptive behavior disorders: emotional responding and response inhibition.  Psychol Med. 2016;46(7):1485-1496. doi:10.1017/S0033291716000118PubMedGoogle ScholarCrossref
    33.
    Blair  KS, Vythilingam  M, Crowe  SL,  et al.  Cognitive control of attention is differentially affected in trauma-exposed individuals with and without post-traumatic stress disorder.  Psychol Med. 2013;43(1):85-95. doi:10.1017/S0033291712000840PubMedGoogle ScholarCrossref
    34.
    Blair  KS, Geraci  M, Smith  BW,  et al.  Reduced dorsal anterior cingulate cortical activity during emotional regulation and top-down attentional control in generalized social phobia, generalized anxiety disorder, and comorbid generalized social phobia/generalized anxiety disorder.  Biol Psychiatry. 2012;72(6):476-482. doi:10.1016/j.biopsych.2012.04.013PubMedGoogle ScholarCrossref
    35.
    Bernstein  DP, Ahluvalia  T, Pogge  D, Handelsman  L.  Validity of the Childhood Trauma Questionnaire in an adolescent psychiatric population.  J Am Acad Child Adolesc Psychiatry. 1997;36(3):340-348. doi:10.1097/00004583-199703000-00012PubMedGoogle ScholarCrossref
    36.
    Lang  PJ, Greenwald  MK.  International Affective Picture System Standardization Procedure and Initial Group Results for Affective Judgements: Technical Reports 1A & 1B. Gainesville: Center for Research in Psychophysiology, University of Florida; 1988.
    37.
    Cox  RW.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages.  Comput Biomed Res. 1996;29(3):162-173. doi:10.1006/cbmr.1996.0014PubMedGoogle ScholarCrossref
    38.
    Talairach  J, Tournoux  P.  Co-Planar Stereotaxic Atlas of the Human Brain. Stuttgart, Germany: Thieme Classics; 1988.
    39.
    Wagner  G, Sinsel  E, Sobanski  T,  et al.  Cortical inefficiency in patients with unipolar depression: an event-related fMRI study with the Stroop task.  Biol Psychiatry. 2006;59(10):958-965. doi:10.1016/j.biopsych.2005.10.025PubMedGoogle ScholarCrossref
    40.
    Krompinger  JW, Simons  RF.  Cognitive inefficiency in depressive undergraduates: Stroop processing and ERPs.  Biol Psychol. 2011;86(3):239-246. doi:10.1016/j.biopsycho.2010.12.004PubMedGoogle ScholarCrossref
    41.
    Gold  AL, Steuber  ER, White  LK,  et al.  Cortical thickness and subcortical gray matter volume in pediatric anxiety disorders.  Neuropsychopharmacology. 2017;42(12):2423-2433. doi:10.1038/npp.2017.83PubMedGoogle ScholarCrossref
    42.
    Gold  AL, Sheridan  MA, Peverill  M,  et al.  Childhood abuse and reduced cortical thickness in brain regions involved in emotional processing.  J Child Psychol Psychiatry. 2016;57(10):1154-1164. doi:10.1111/jcpp.12630PubMedGoogle ScholarCrossref
    43.
    Lim  L, Radua  J, Rubia  K.  Gray matter abnormalities in childhood maltreatment: a voxel-wise meta-analysis.  Am J Psychiatry. 2014;171(8):854-863. doi:10.1176/appi.ajp.2014.13101427PubMedGoogle ScholarCrossref
    44.
    Clithero  JA, Rangel  A.  Informatic parcellation of the network involved in the computation of subjective value.  Soc Cogn Affect Neurosci. 2014;9(9):1289-1302. doi:10.1093/scan/nst106PubMedGoogle ScholarCrossref
    45.
    De Pisapia  N, Barchiesi  G, Jovicich  J, Cattaneo  L.  The role of medial prefrontal cortex in processing emotional self-referential information: a combined TMS/fMRI study  [published online May 9, 2018].  Brain Imaging Behav. doi:10.1007/s11682-018-9867-3PubMedGoogle Scholar
    46.
    Bradley  RH, Corwyn  RF, McAdoo  HP, Coll  CG.  The home environments of children in the United States part I: variations by age, ethnicity, and poverty status.  Child Dev. 2001;72(6):1844-1867. doi:10.1111/1467-8624.t01-1-00382PubMedGoogle ScholarCrossref
    47.
    Pollak  SD, Vardi  S, Putzer Bechner  AM, Curtin  JJ.  Physically abused children’s regulation of attention in response to hostility.  Child Dev. 2005;76(5):968-977. doi:10.1111/j.1467-8624.2005.00890.xPubMedGoogle ScholarCrossref
    48.
    Norman  RE, Byambaa  M, De  R, Butchart  A, Scott  J, Vos  T.  The long-term health consequences of child physical abuse, emotional abuse, and neglect: a systematic review and meta-analysis.  PLoS Med. 2012;9(11):e1001349. doi:10.1371/journal.pmed.1001349PubMedGoogle ScholarCrossref
    49.
    Lansford  JE, Miller-Johnson  S, Berlin  LJ, Dodge  KA, Bates  JE, Pettit  GS.  Early physical abuse and later violent delinquency: a prospective longitudinal study.  Child Maltreat. 2007;12(3):233-245. doi:10.1177/1077559507301841PubMedGoogle ScholarCrossref
    50.
    Jaffee  SR, Caspi  A, Moffitt  TE, Taylor  A.  Physical maltreatment victim to antisocial child: evidence of an environmentally mediated process.  J Abnorm Psychol. 2004;113(1):44-55. doi:10.1037/0021-843X.113.1.44PubMedGoogle ScholarCrossref
    51.
    Briggs-Gowan  MJ, Carter  AS, Clark  R, Augustyn  M, McCarthy  KJ, Ford  JD.  Exposure to potentially traumatic events in early childhood: differential links to emergent psychopathology.  J Child Psychol Psychiatry. 2010;51(10):1132-1140. doi:10.1111/j.1469-7610.2010.02256.xPubMedGoogle ScholarCrossref
    ×