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Selective amygdala hypoactivity to fear in boys with persistent conduct problems after parent training.

Open AccessPublished:October 08, 2022DOI:https://doi.org/10.1016/j.biopsych.2022.09.031

      Background

      Parenting interventions reduce antisocial behaviour (ASB) in some children with conduct problems (CP), but not others. Understanding the neural basis for this disparity is important because persistent ASB is associated with lifelong morbidity and places a huge burden on our health and criminal justice systems. One of the most highly replicated neural correlates of ASB is amygdala hypoactivity to another person’s fear. We aimed to assess whether amygdala hypoactivity to fear in CP children is remediated following reduction in ASB after successful treatment, and/or if it is a marker for persistent ASB.

      Methods

      We conducted a prospective, case-control, study of CP and typically developing (TD) boys. Both groups (aged 5-10 years) completed two MRI sessions (18±5.8 weeks apart) with ASB assessed at each visit. Participants included CP boys following referral to a parenting intervention group, and TD boys recruited from the same schools and geographical regions. Final functional MRI data was available for 36 TD and 57 CP boys. CP boys were divided into those whose ASB improved (n=27) or persisted (n=30) following the intervention. Functional MRI data assessing fear reactivity was then analysed using a longitudinal group (TD/improving CP/persistent CP) x timepoint (pre/post) design.

      Results

      Amygdala hypoactivity to fear was only observed in CP boys with persistent ASB and was absent in those whose ASB improved following intervention.

      Conclusions

      Our findings suggest amygdala hypoactivity to fear is a marker for ASB that is resistant to change following a parenting intervention, and a putative target for future treatments.

      Keywords

      INTRODUCTION:

      Conduct problems (CP), characterised by a persistent pattern of antisocial behaviour (ASB), are the most common psychiatric disorder in children(

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      ) However, the costs of severe CP extend beyond childhood, with a 5-10 fold increased risk of subsequent mental illness, substance abuse, criminality, unemployment and early death.(
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      Overview | Antisocial behaviour and conduct disorders in children and young people: recognition and management | Guidance | NICE (n.d.): Retrieved February 7, 2022, from https://www.nice.org.uk/guidance/cg158

      ) These aim to reduce the severity of CP by improving parenting skills using, for example, praise and rewards, and more positive forms of punishment(
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      ) As with many other psychiatric disorders, it is believed that heterogeneity in the brain mechanisms underpinning CP may partially explain the differential response profile.(
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      One of the most widely reported neurocognitive associates of CP is reduced amygdala activity to affective stimuli; particularly others’ distress.(

      Raschle NM, Menks M, Fehlbaum LV, Tshomba E, Stadler C (2015): Structural and Functional Alterations in Right Dorsomedial Prefrontal and Left Insular Cortex Co-Localize in Adolescents with Aggressive Behaviour: An ALE Meta-Analysis. https://doi.org/10.1371/journal.pone.0136553

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      ) The clinical importance of this deficit has been supported by recent evidence suggesting a role of amygdala hypoactivity in: i) CP youths with co-occurring callous-unemotional traits(
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      ) – a putative risk factor for persistent ASB(7,20) and poor treatment response,(
      • Hawes D.J.
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      The treatment of conduct problems in children with callous-unemotional traits.
      ) and ii) adult ASB(
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      ) and psychopathy.(
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      ) Consequently, it has been proposed that reduced amygdala activity is associated with lack of guilt, lack of empathy and increased instrumental aggression.(
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      ) Amygdala hypoactivity is therefore a compelling candidate marker of treatment resistant ASB in children. However, to date there has been an absence of longitudinal treatment data assessing this.
      Therefore, in the current study, we compared changes in brain and behaviour in a group of CP children, (pre and post the ‘gold-standard’ treatment for CP) in comparison to a typically developing (TD) control group (at two equivalent time points). Boys were assessed before and after the intervention, to characterise patterns of amygdala reactivity and persistence of ASB. CP boys were divided into those whose ASB persisted following the intervention, and those whose ASB improved (see methods for details). These groups were then compared in a longitudinal design (3 groups x 2 timepoints).
      We tested two competing hypotheses:
      • (i)
        Amygdala hypoactivity to fear would be observed in CP boys, and ‘normalise’ (i.e. in the direction of TD controls) in CP children whose ASB improves, but not in those whose ASB persists (i.e. a group x time effect driven by the ‘improving group’).
      • (ii)
        Amygdala hypoactivity to fear would be selectively observed in CP children with persistent ASB (i.e. not in those whose ASB improves) and would not change during the course of the intervention (i.e. a group effect driven by the ‘persistent’ group).
      Finally, as the presence of CU traits has been shown to be a reported risk factor for persistent ASB,(
      • Blair R.J.R.
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      • Pine D.S.
      Conduct disorder and callous-unemotional traits in youth.
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      • Frick P.J.
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      ) and poor treatment response,(
      • Hawes D.J.
      • Dadds M.R.
      The treatment of conduct problems in children with callous-unemotional traits.
      ) we examined the influence of callous-unemotional traits on amygdala hypoactivity and treatment responsivity.

      METHODS

      Sample

      The sample included 83 boys with CP, and 47 TD boys, aged 5-10 years old. CP boys were recruited from two parenting programmes (i.e. Incredible Years (IY) and Triple P). Each required parents to attend facilitated, weekly group sessions, over 10-12 weeks, and to complete 'homework' between meetings. CP was assessed at the beginning (i.e. <3 weeks after enrolment into the parenting programme), and after completion of the programme (18.5 ± 7.0 weeks from baseline assessment). Families were referred to parenting groups from Child and Adolescent Mental Health Services (CAMHS), Local Authorities, Charities, & Social Enterprises and attended weekly group training sessions. Boys were included if they met a pre-defined threshold of ≥ 3 on the CP scale of the Strengths and Difficulties Questionnaire (SDQ)(
      • Goodman R.
      The strengths and difficulties questionnaire: A research note.
      ). Typically developing (TD) boys were recruited from the same schools and geographical areas as CP boys and scanned at two equally spaced timepoints (17.6 ± 4.3 weeks). Inclusion criteria to the TD group required a score of <3 on the SDQ. TD boys and their families did not participate in the parenting programmes. For both groups boys with a clinical diagnosis of an autism spectrum disorder, neurological abnormality, or MRI contraindication were excluded from the study.

      Behavioural and clinical assessments

      At each timepoint, the Parent Account of Childhood Symptoms (PACS) interview was used to assess CP symptoms as the primary outcome measure. This semi-structured clinical interview uses specific investigator-based criteria to assess both the frequency and severity of ASB (e.g. aggression, destruction of property, disobedience etc.) and is highly predictive of later psychosocial outcomes.(
      • Taylor E.
      • Chadwick O.
      • Heptinstall E.
      • Danckaerts M.
      Hyperactivity and conduct problems as risk factors for adolescent development.
      ) The PACS interview was administered by a member of the research team who was trained to use the instrument by a fully qualified clinician. To discern a clinically meaningful level of symptom improvement, a minimally important clinical difference (MICD) approach was employed.(
      • Jaeschke R.
      • Singer J.
      • Guyatt G.H.
      Measurement of health status. Ascertaining the minimal clinically important difference.
      ,
      • Norman G.R.
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      • Wyrwich K.W.
      Interpretation of Changes in Health-related Quality of Life.
      ) Meta-analysis of parent training indicates a mean change in symptoms of approximately 0.6 standard deviations (SD), associated with a high user reported satisfaction (∼92%).(

      Overview | Antisocial behaviour and conduct disorders in children and young people: recognition and management | Guidance | NICE (n.d.): Retrieved February 7, 2022, from https://www.nice.org.uk/guidance/cg158

      ) Therefore, to ascertain an MICD, we used a cut-off of 2/3 of this (0.4 SD) to reflect successful treatment. In our study, SD was measured as a function of baseline CP PACS scores across the entire clinical cohort (i.e. CP children whose CP scores improved by 0.4 SD or higher following the intervention were classed as ‘improving’ and those whose CP scores did not improve by 0.4 SD were classed as ‘persistent’).
      At both timepoints, clinical symptoms were additionally assessed using the parent forms of the SDQ,(
      • Goodman R.
      The strengths and difficulties questionnaire: A research note.
      ) Inventory of Callous-Unemotional Traits (ICU),(
      • Kimonis E.R.
      • Frick P.J.
      • Skeem J.L.
      • Marsee M.A.
      • Cruise K.
      • Munoz L.C.
      • et al.
      Assessing callous-unemotional traits in adolescent offenders: Validation of the Inventory of Callous-Unemotional Traits.
      ) and the Conners 3 Short form ADHD assessment report.(
      • Conners C.K.
      Conners 3rd Edition (Conners 3).
      ) Parents also completed the Alabama Parenting Questionnaire(
      • Essau C.A.
      • Sasagawa S.
      • Frick P.J.
      Psychometric properties of the Alabama parenting questionnaire.
      ) at both timepoints. Boys completed the Wechsler Abbreviated Scale of Intelligence (WASI)(

      Wechsler D (1999): Manual for the Wechsler abbreviated intelligence scale (WASI). WASI.

      ) and parents completed sociodemographic measures at baseline only. Maternal education was used as a measure of Socioeconomic Status (SES). Children’s ethnicity was also reported by parents.

      MRI acquisition

      All participants underwent MRI scanning at each timepoint at the Centre for Neuroimaging Sciences, King’s College London, providing T1-weighted, T2-weighted, diffusion MRI, and functional MRI data with a total scan time of one hour. Prior to scanning, children were introduced to a mock scanning environment, where they were familiarized with the sounds of the MRI scanner, practiced entering the scanner and lying still, and were familiarized with the emotion processing task detailed below. Several studies have suggested the importance of these procedures for enhancing data quality in pediatric cohorts.(
      • de Bie H.M.A.
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      • et al.
      Preparing children with a mock scanner training protocol results in high quality structural and functional MRI scans.
      ,
      • Pua E.P.K.
      • Barton S.
      • Williams K.
      • Craig J.M.
      • Seal M.L.
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      )
      Task based functional data was acquired using 218 volumes of T2* weight echo-planar imaging (EPI) data with 41 near-contiguous slices (3mm3 voxels, Matrix 64X64, slice gap = 3.3mm, FOV = 240mm), TE = 30ms, TR = 2000ms and Flip angle = 75°. In addition, T1-weighted MPRAGE structural imaging data acquired on a 3T GE Signa HDx with a 12-channel head coil located at the Centre for Neuroimaging Sciences at King’s College London, with a resolution of 1x1x1.2mm, matrix size of 256x256x196, flip angle of 11°, TE of 3016ms, TR of 7312ms, FOV of 270mm, and inversion time of 400ms.

      fMRI: Emotion processing task

      The fMRI paradigm employed was an implicit emotion processing task, which was modelled as an event-related design. The task consisted of 140 trials for a duration of 7 minutes and 36 seconds, where they were presented with a male or female face with either a fearful (60 trials), happy (60 trials) or neutral (20 trials) expression(
      • Leiker E.K.
      • Meffert H.
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      • Taylor B.K.
      • Aloi J.
      • Abdel-Rahim H.
      • et al.
      Alcohol use disorder and cannabis use disorder symptomatology in adolescents are differentially related to dysfunction in brain regions supporting face processing.
      ) for 1.5s in a randomised order. Faces expressing emotion were additionally morphed (50%, 100% or 150%) to display a range of intensities. During each trial, participants were asked to indicate whether the face belonged to a male or female individual by pressing a button with their index or middle finger when the image appeared on the screen. Each trial was followed by a variable intertrial interval of between 1 and 2s (mean 1.5s).

      MRI processing

      FMRI data were preprocessed using fMRIPrep 1.5.1rc1(
      • Esteban O.
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      fMRIPrep: a robust preprocessing pipeline for functional MRI.
      ,

      Esteban O, Markiewicz CJ, Burns C, Goncalves M, Jarecka D, Ziegler E, et al. (2020): nipy/nipype: 1.5.1. https://doi.org/10.5281/ZENODO.4035081

      ) (RRID:SCR_016216), which is based on Nipype 1.3.0-rc1(

      Esteban O, Markiewicz CJ, Burns C, Goncalves M, Jarecka D, Ziegler E, et al. (2020): nipy/nipype: 1.5.1. https://doi.org/10.5281/ZENODO.4035081

      ,
      • Gorgolewski K.
      • Burns C.D.
      • Madison C.
      • Clark D.
      • Halchenko Y.O.
      • Waskom M.L.
      • Ghosh S.S.
      Nipype: A flexible, lightweight and extensible neuroimaging data processing framework in Python.
      (39,40) (RRID:SCR_002502). Details of the pre-processing pipeline can be found within eMethods 1 and eMethods 2 of the Supplementary Materials.

      fMRI analysis

      Regressors for each condition of interest (Fear, Happy, Neutral) were entered into a single subject General Linear Model (GLM; SPM12). A parametric modulator encoding the intensity of the emotion was included in the conditions containing emotional valence (i.e. Fear and Happy). In addition, following Pruim et al.,(
      • Pruim R.H.R.
      • Mennes M.
      • van Rooij D.
      • Llera A.
      • Buitelaar J.K.
      • Beckmann C.F.
      ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data.
      ) mean signal for CSF and WM were included as nuisance variables. Scans with framewise displacement (FD) exceeding 1mm were also deweighted in the model, (
      • Siegel J.S.
      • Power J.D.
      • Dubis J.W.
      • Vogel A.C.
      • Church J.A.
      • Schlaggar B.L.
      • Petersen S.E.
      Statistical improvements in functional magnetic resonance imaging analyses produced by censoring high‐motion data points.
      ) with the scans themselves interpolated from the surrounding volumes to mitigate the effects of residual motion artifacts on the data.
      After this the regressors of interest for each analysis (parametric modulation of fear by intensity and parametric modulation of happy by intensity [hereafter, simply ‘Fear’ and ‘Happy’ respectively]) were entered into separate Linear Mixed Models (LMM) using 3dLME (AFNI)(
      • Chen G.
      • Saad Z.S.
      • Britton J.C.
      • Pine D.S.
      • Cox R.W.
      Linear mixed-effects modeling approach to FMRI group analysis.
      ) using a 3 x 2 design modelling ‘group’ (improving, persistent, TD) and ‘time’ (pre-intervention, post-intervention) and a random subjects factor. Of particular interest, significant Time-by-Group effects were examined to assess for any changes in brain activity over time that differed according to clinical response profile i.e. improving, persistent, TD controls (Hypothesis 1). Secondly, significant group effects were examined to assess for any overall differences in amygdala activity between the groups (Hypothesis 2). Age, IQ, SES, child ethnicity, and ADHD symptoms were included as covariates.
      In addition, to ensure that any remaining effects of motion did not influence the data, mean FD at each timepoint was included as a within-subjects covariate.(
      • Yan C.G.
      • Cheung B.
      • Kelly C.
      • Colcombe S.
      • Craddock R.C.
      • di Martino A.
      • et al.
      A Comprehensive Assessment of Regional Variation in the Impact of Head Micromovements on Functional Connectomics.
      ) Following exclusions, no differences in the number of volumes censored or mean FD were observed between groups (Volumes: F(2,77.5)=1.1, p=0.338; FD: F(2,93.0)=0.8, p=0.462), timepoints (Volumes: F(1,63.7)=0.3; p=0.582, FD: F(1,65.6)=1.8, p=0.189), or their interaction (Volumes: F(2,63.4)=0.6, p=0.544; FD: F(2,65.4)=0.4, p=0.651). Resulting statistical maps were initially thresholded at an uncorrected threshold of punc < 0.001. Simulations using 3dClustSim (NN = 2, 2-sided clustering) assuming a mixed autocorrelation function(
      • Cox R.W.
      • Chen G.
      • Glen D.R.
      • Reynolds R.C.
      • Taylor P.A.
      FMRI Clustering in AFNI: False-Positive Rates Redux.
      ) suggested a clustering threshold of 167 voxels for whole brain analysis. Due to the hypothesised importance of the amygdala, a small volume correction (SVC) approach was used here for our region of interest, with simulations recommending a cluster threshold of 2.1 voxels within this region. Finally, behavioural parameters of the task (% accuracy for gender discrimination and reaction time) were analysed using identical LMMs to the fMRI data, excepting exclusions and covariates for motion.

      RESULTS

      Demographic and clinical data

      Groups did not differ significantly in age, and time to follow-up (Table 1). Also, no significant between group differences were observed in ethnicity (Fisher’s Exact Test p=0.441). Individuals whose ASB improved during the intervention (Improved ASB) and those whose ASB persisted (Persistent ASB) differed from controls on IQ and SES (Table 1); but there were no significant differences between ‘improvers’ and ‘persisters’.
      Table 1Key Demographic Data
      Mean (SD)
      MeasureControlImprovedPersistentOmnibus TestCtrl Vs Imp pCtrl Vs Pers pImp Vs Pers p
      n362730--------
      Age8.5 (1.5)8.7 (1.4)9.1 (1.2)F(2,90)=1.2, p=0.3130.1290.5090.395
      Followup time (Weeks)17.3 (4.4)19.8 (7.3)17.5 (5.2)F(2,86)=1.7, p=0.1800.9400.0910.141
      ADHD (Conners)17.0 (10.7)53.7 (12.6)53.7 (18.8)F(2,90)=75.2, p=0.001*<0.001<0.0010.997
      IQ109.2 (15.1)101.6 (13.8)99.6 (12.1)F(2,90)=4.3, p=0.016*0.0080.0300.586
      SES5.7 (2.2)3.8 (2.5)3.6 (2.3)F(2,90)=8.0, p=0.001*0.0010.0010.778
      Ctrl=controls; Imp=Improved; Pers=Persisters; ADHD (Conners)= attention deficit hyperactivity disorder (Conners' ADHD Rating Scales); IQ= intelligent quotient; CU= callous-unemotional; PACS= parental accounts of childrens symptoms; SDQ=Strength and difficulties questionnaire;.
      The CP group overall showed a significant response to the intervention, showing reduced (Pre: 1.60±0.42, Post: 1.34±0.46; F(1,55.3)=17.9, p<0.001) ASB scores. A reduction in ADHD (Pre: 53.7±15.7, Post: 49.3±18.3; F(1,51.9)=5.4, p=0.024) and CU scores (Pre: 39.0±12.0, Post: 35.7±12.4; F(1,47.1)=6.1, p=0.017) was also observed, but no difference in internalising symptoms between the two timepoints was detected (Pre: 7.9±3.9, Post: 7.5±4.6; F(1,51.0)=1.1, p=0.307).
      Next, we examined any differences in symptoms across timepoints (i.e. ASB, CU traits, ADHD and internalising symptoms) or symptom change between the improved and persistent CP groups. Apart from the differences in ASB observed following treatment (GroupxTime: F(1,47.7)=63.1, p<0.001), symptom levels (i.e. no Group effect. ASB: F(1,64.7)=0.2, p=0.656, ADHD: F(1,66.3)<0.1, p=0.994, ICU: F(1,62.9)=0.3, p=0.596, Internalising: F(1,65.1)<0.1, p=0.924) and changes in symptoms (i.e. no GroupxTime interaction. ADHD: F(1,51.3)=0.1, p=0.779, ICU: F(1,49.1)=1.0, p=0.319, Internalising: F(1,50.2)<0.1, p=0.945) did not differ according to CP clinical response group. Means and standard deviations for all symptoms pre and post treatment are shown in Table 2.
      Table 2Key behavioural data at baseline and follow-up.
      ControlImprovedPersistentOmnibus Test
      The omnibus tests were run on the improving versus persisting groups only.
      :

      Group
      Omnibus Test
      The omnibus tests were run on the improving versus persisting groups only.
      :

      Time
      Omnibus Test
      The omnibus tests were run on the improving versus persisting groups only.
      : Group*Time
      CP symptoms T1 (PACS)0.63 (0.34)1.74 (0.37)1.44 (0.42)--F(1,169)=253.71, p<0.001*
      CP symptoms T2 (PACS)0.56 (0.36)1.20 (0.45)1.59 (0.44)
      CP symptoms T1 (SDQ)1.00 (1.28)5.50 (1.95)6.07 (2.33)--F(1,159.72)=14.11, p<0.001*
      CP symptoms T2 (SDQ)0.86 (0.86)3.93 (2.50)5.48 (2.58)
      CU traits T114.94 (6.82)34.82 (9.24)35.28 (14.19)F(1,54.08)=

      0.08, p=0.775
      F(1,159.15)=

      16.56, p<0.001*
      F(1,159.15)=2.66, p=0.105
      CU traits T216.13 (7.85)31.69 (12.45)33.09 (10.30)
      APQ (Pos P) T113.55 (1.90)13.02 (2.25)13.04 (2.09)F(1,53.38)=

      0.40, p=0.530
      F(1,159.45)=

      16.39, p<0.001*
      F(1,159.45)=0.937, p=0.334
      APQ (Pos P) T213.77 (1.77)13.93 (1.53)13.68 (1.79)
      APQ (Incon Dis) T17.38 (2.29)8.68 (2.49)8.56 (1.85)F(1,52.70)=

      0.40, p=0.863
      F(1,161.25)=29.94, p<0.001*F(1,161.25)=0.018, p=0.894
      APQ (Incon Dis) T27.61 (2.62)7.34 (2.25)7.40 (1.73)
      APQ (Poor Sup) T13.41 (0.88)4.18 (1.81)4.27 (1.99)F(1,52.15)=

      1.79, p=0.186
      F(1,144.39)=2.75, p=0.099F(1,144.39)=1.09, p=0.297
      APQ (Poor Sup) T23.37 (1.03)3.80 (1.38)4.43 (2.03)
      APQ (Involv) T112.64 (1.63)12.51 (1.63)12.40 (1.63)F(1,54.14)=

      0.086, p=0.771
      F(1,158.86)=0.489, p=0.486F(1,158.86)=0.416, p=0.520
      APQ (Involv) T212.64 (1.63)12.44 (1.74)12.30 (1.73)
      APQ (Corp Pun) T13.97 (1.26)4.17 (1.51)4.42 (1.15)F(1,52.31)=

      1.28, p=0.262
      F(1,157.89)=22.97, p<0.001*F(1,157.89)=0.494, p=0.483
      APQ (Corp Pun) T23.88 (1.32)3.41 (0.94)4.00 (1.61)
      CP = conduct problems; PACS= parental accounts of children’s symptoms; SDQ=Strength and difficulties questionnaire; CU= callous-unemotional; APQ = Alabama Parenting Questionnaire; Pos P = Positive Parenting; Incon Dis = Inconsistent Discipline; Poor Sup = Poor supervision; Involv = Involvement; Corp Pun = Corporal Punishment.
      1 The omnibus tests were run on the improving versus persisting groups only.

      fMRI

      Our first prediction, that improvement in ASB would be related to amygdala activity, was not supported and the group by time interaction was absent.
      However, our second prediction, that amygdala hypo-activity to fear would be associated with persistence of ASB following treatment was supported. We found a significant overall group effect across timepoints (cluster size[k] = 36, MNI coordinates = -32, 2, -22; F=11.06; Figure 1). Post hoc tests revealed that this was driven by reduced right amygdala responsivity to fear in the persistent ASB group when compared to the control group (cluster size[k] = 48, MNI coordinates = -32, 2, -22; Z=4.37; Figure 1).
      Figure thumbnail gr1
      Figure1Figure on the left represents a significant group effect (across the 3 groups) on fear processing in the right amygdala. The figure on the right represents post hoc tests between the Controls vs. Improving, Controls vs. Persistent and Improving vs. Persistent. Our findings show that children with persistent ASB have significantly reduced amygdala activity in response to modulated fear processing (across both timepoints), in comparison to the typically developing control group. There was no evidence of amygdala hypoactivity to fear in children whose ASB improved over time. *Significant at p=0.001. Figures reflects the raw means and standard deviations.
      When we additionally examined the effects of CU traits within the model, we found no main effect of CU or interaction with group, time, or group*time for either condition. Further, no significant effects were observed in the happy condition.
      For completeness, we also performed whole brain analyses for the above contrasts. Here, we observed a significant group by time interaction to fear in medial sensory motor regions (k = 214, MNI = 6, 18, 60; F=13.39; Supplementary eFigure 1). This was driven by a reduction over time in the improving ASB group compared to the others. Supplementary results can be found in eResults 1 and 2, and eFigure 2 in the Supplement.

      DISCUSSION

      In this study we compared changes in brain and behaviour in CP boys, pre and post parenting intervention, and compared these to TD boys assessed over equivalent timepoints. Consistent with prior studies in CP children; i) parenting intervention successfully reduced ASB, CU traits and ADHD symptoms,(
      • Scott S.
      • Briskman J.
      • O’Connor T.G.
      Early prevention of antisocial personality: Long-term follow-up of two randomized controlled trials comparing indicated and selective approaches.
      ,
      • Muratori P.
      • Milone A.
      • Manfredi A.
      • Polidori L.
      • Ruglioni L.
      • Lambruschi F.
      • et al.
      Evaluation of improvement in externalizing behaviors and callous-unemotional traits in children with disruptive behavior disorder: A 1-year follow up clinic-based study.
      ) and ii) a subgroup of CP boys did not improve following the intervention.(
      • Scott S.
      Do Parenting Programmes for Severe Child Antisocial Behaviour Work over the Longer Term, and for Whom? One Year follow-up of a Multi-Centre Controlled Trial.
      )
      In addition, we found amygdala hypoactivity to fear in CP boys with ASB that persisted following treatment, but not in CP boys whose ASB improved. This finding provides the first direct evidence for a widely held view(
      • Viding E.
      • Sebastian C.L.
      • Dadds M.R.
      • Lockwood P.L.
      • Cecil C.A.M.
      • de Brito S.A.
      • McCrory E.J.
      Amygdala response to preattentive masked fear in children with conduct problems: The role of callous-unemotional traits.
      ,
      • Blair R.J.J.
      The neurobiology of psychopathic traits in youths.
      ,
      • Marsh A.A.
      Understanding amygdala responsiveness to fearful expressions through the lens of psychopathy and altruism.
      ) that amygdala hypoactivity to fear underpins particularly stable forms of ASB, and suggests that more malleable forms of childhood ASB are underpinned by distinct neural mechanisms. We believe that these findings are important to our understanding of the neural correlates underlying treatment response in CP, but they also raise several significant questions that need to be addressed by future studies.
      Firstly, contrary to one of our a priori hypotheses, we found no evidence of reduced amygdala hypoactivity to fear in CP boys whose ASB improved following intervention. Although we observed an association between improvement in ASB and sensorimotor activity, it would be highly tenuous to offer any interpretation of a relationship based on a task designed to probe affective processing. It may be that improvement in ASB is underpinned by different mechanisms not probed by the current task. Specifically, previous work has highlighted the importance of reinforcement learning in CP,(
      • Blair R.J.R.
      • Veroude K.
      • Buitelaar J.K.
      Neuro-cognitive system dysfunction and symptom sets: A review of fMRI studies in youth with conduct problems.
      ,
      • Finger E.C.
      • Marsh A.A.
      • Mitchell D.G.
      • Reid M.E.
      • Sims C.
      • Budhani S.
      • et al.
      Abnormal ventromedial prefrontal cortex function in children with psychopathic traits during reversal learning.
      ,
      • White S.F.
      • Pope K.
      • Sinclair S.
      • Fowler K.A.
      • Brislin S.J.
      • Williams W.C.
      • et al.
      Disrupted expected value and prediction error signaling in Youths with disruptive behavior disorders during a passive avoidance task.
      ) and early interventions for CP implicitly target the restructuring of reward and punishment schedules.(

      The incredible years parents, teachers and children training series: A multifaceted treatment approach for young children with conduct problems. - PsycNET (n.d.): Retrieved February 7, 2022, from https://psycnet.apa.org/record/2003-88002-012

      ) We anticipate that emerging techniques employing machine learning(
      • Siugzdaite R.
      • Bathelt J.
      • Holmes J.
      • Astle D.E.
      Transdiagnostic Brain Mapping in Developmental Disorders.
      ) will be better able to fractionate out these different neural subtypes and determine their value in predicting treatment response.
      Secondly, unlike some previous studies, we did not find an association between severity of CU traits with either treatment response,(
      • Frick P.J.
      • Viding E.
      Antisocial behavior from a developmental psychopathology perspective.
      ,

      Overview | Antisocial behaviour and conduct disorders in children and young people: recognition and management | Guidance | NICE (n.d.): Retrieved February 7, 2022, from https://www.nice.org.uk/guidance/cg158

      ,
      • Scott S.
      • Briskman J.
      • O’Connor T.G.
      Early prevention of antisocial personality: Long-term follow-up of two randomized controlled trials comparing indicated and selective approaches.
      ) or amygdala reactivity to fear.(
      • Viding E.
      • Sebastian C.L.
      • Dadds M.R.
      • Lockwood P.L.
      • Cecil C.A.M.
      • de Brito S.A.
      • McCrory E.J.
      Amygdala response to preattentive masked fear in children with conduct problems: The role of callous-unemotional traits.
      ,
      • Blair R.J.J.
      The neurobiology of psychopathic traits in youths.
      ,
      • Aggensteiner P.M.
      • Holz N.E.
      • Böttinger B.W.
      • Baumeister S.
      • Hohmann S.
      • Werhahn J.E.
      • et al.
      The effects of callous-unemotional traits and aggression subtypes on amygdala activity in response to negative faces.
      ,
      • Hawes D.J.
      • Dadds M.R.
      The treatment of conduct problems in children with callous-unemotional traits.
      ) This may have been due to several factors, including the younger age range of our cohort compared to most prior neuroimaging studies(
      • Viding E.
      • Sebastian C.L.
      • Dadds M.R.
      • Lockwood P.L.
      • Cecil C.A.M.
      • de Brito S.A.
      • McCrory E.J.
      Amygdala response to preattentive masked fear in children with conduct problems: The role of callous-unemotional traits.
      ,
      • Blair R.J.J.
      The neurobiology of psychopathic traits in youths.
      ,
      • Aggensteiner P.M.
      • Holz N.E.
      • Böttinger B.W.
      • Baumeister S.
      • Hohmann S.
      • Werhahn J.E.
      • et al.
      The effects of callous-unemotional traits and aggression subtypes on amygdala activity in response to negative faces.
      ) (although similar deficits have been observed in behavioural studies of younger age groups(
      • White S.F.
      • Briggs-Gowan M.J.
      • Voss J.L.
      • Petitclerc A.
      • McCarthy K.
      • Blair RJ R.
      • Wakschlag L.S.
      Can the Fear Recognition Deficits Associated with Callous-Unemotional Traits be Identified in Early Childhood?.
      )). Another, more likely, possibility is that CU traits can arise from more than one neurocognitive profile - consistent with recent observations in different ‘subtypes’ of psychopathy.(
      • Sethi A.
      • McCrory E.
      • Puetz V.
      • Hoffmann F.
      • Knodt A.R.
      • Radtke S.R.
      • et al.
      ‘Primary’ and ‘secondary’ variants of psychopathy in a volunteer sample are associated with different neurocognitive mechanisms.
      ) Finally, it is possible that the phenotype of CU traits indexed by the ICU differs somewhat to that indexed by other assessment tools used to measure CU traits. For instance, previous research has used a range of assessments to classify participants into those with high versus low CU traits (i.e. Youth Psychopathic Traits Inventory (YPI)(
      • Cohn M.D.
      • Popma A.
      • van den Brink W.
      • Pape L.E.
      • Kindt M.
      • van Domburgh L.
      • et al.
      Fear conditioning, persistence of disruptive behavior and psychopathic traits: an fMRI study.
      ,
      • Andershed H.
      • Hodgins S.
      • Tengström A.
      Convergent validity of the youth psychopathic traits inventory (YPI): Association with the psychopathy checklist: Youth version (PCL:YV).
      ) Antisocial Process Screening Device (APSD),(
      • Jones A.P.
      • Laurens K.R.
      • Herba C.M.
      • Barker G.J.
      • Viding E.
      Amygdala hypoactivity to fearful faces in boys with conduct problems and callous-unemotional traits.
      ,

      Frick PJ, Hare RD (2002): Antisocial Process Screening Device. [Database record] APA PsycTests.

      ) Psychopathy Checklist: Youth Version (PCL:YV)(
      • Finger E.C.
      • Marsh A.A.
      • Mitchell D.G.
      • Reid M.E.
      • Sims C.
      • Budhani S.
      • et al.
      Abnormal ventromedial prefrontal cortex function in children with psychopathic traits during reversal learning.
      ,

      Forth A, Kosson D, Hare RD (2003): Hare Psychopathy Checklist: Youth Version: Multi-Health Systems.

      ) in addition to the ICU).(
      • Viding E.
      • Sebastian C.L.
      • Dadds M.R.
      • Lockwood P.L.
      • Cecil C.A.M.
      • de Brito S.A.
      • McCrory E.J.
      Amygdala response to preattentive masked fear in children with conduct problems: The role of callous-unemotional traits.
      )
      This, in combination with our finding of neurocognitive dissociation between persistent and improving ASB, supports growing evidence that there is substantial neurocognitive heterogeneity within this group that requires further investigation. These findings may also have significant utility for future research into novel treatments. For instance, amygdala hypoactivity to fear could be used as a biomarker to fractionate out a CP subgroup that are targeted with a treatment that upregulates amygdala activity to fear.
      Although the current study has several strengths, such as being the first longitudinal study to examine the effect of brain and behavioural change in CP, several limitations should be addressed.
      Firstly, the sample in this study consisted of male participants only. In recent years several studies have identified differences in brain structure and function between male and female youth with CP,(
      • Rogers J.C.
      • Gonzalez-Madruga K.
      • Kohls G.
      • Baker R.H.
      • Clanton R.L.
      • Pauli R.
      • et al.
      White Matter Microstructure in Youths With Conduct Disorder: Effects of Sex and Variation in Callous Traits.
      ,
      • Fairchild G.
      • Hagan C.C.
      • Walsh N.D.
      • Passamonti L.
      • Calder A.J.
      • Goodyer I.M.
      Brain structure abnormalities in adolescent girls with conduct disorder.
      ,
      • Cao W.
      • Sun X.
      • Dong D.
      • Yao S.
      • Huang B.
      Sex differences in spontaneous brain activity in adolescents with conduct disorder.
      ) therefore future longitudinal studies including both genders are warranted, to investigate if female children with treatment-resistant CP present a similar neurobiological profile to their male counterparts.
      Secondly, it should be acknowledged that although task-based fMRI studies are a major focus for biomarker development, recent reviews have highlighted the limited individual test-retest reliability observed in task-fMRI.(
      • Elliott M.L.
      • Knodt A.R.
      • Ireland D.
      • Morris M.L.
      • Poulton R.
      • Ramrakha S.
      • et al.
      What Is the Test-Retest Reliability of Common Task-Functional MRI Measures? New Empirical Evidence and a Meta-Analysis.
      ,
      • Blair R.J.R.
      • Mathur A.
      • Haines N.
      • Bajaj S.
      Future directions for cognitive neuroscience in psychiatry: recommendations for biomarker design based on recent test re-test reliability work.
      ) However, even though the ability to make individual-level predictions based on fMRI data is limited, there is still evidence to suggest that task-based fMRI is a well-validated tool for making group-level inferences(
      • Bennett C.M.
      • Miller M.B.
      How reliable are the results from functional magnetic resonance imaging?.
      ) (e.g. with regards to phenotypes associated with clinical response (improving, persistent)). Future work attempting to predict treatment response on the individual level could use alternative modalities that are reportedly more reliable predictors of disease biomarkers, such as multi-modal MRI.(
      • Tulay E.E.
      • Metin B.
      • Tarhan N.
      • Arıkan M.K.
      Multimodal Neuroimaging: Basic Concepts and Classification of Neuropsychiatric Diseases.
      )
      In conclusion, we have found an association between amygdala hypoactivity to fear in CP boys with more persistent ASB following parenting intervention. Further studies, using a wider range of imaging modalities,(
      • Venugopalan J.
      • Tong L.
      • Hassanzadeh H.R.
      • Wang M.D.
      Multimodal deep learning models for early detection of Alzheimer’s disease stage.
      ,
      • Lu D.
      • Popuri K.
      • Ding G.W.
      • Balachandar R.
      • Beg M.F.
      • Weiner M.
      • et al.
      Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images.
      ), are now needed to explore other neural correlates that predict behavioural improvement or persistence. It is hoped that this will enable us to better understand the CP phenotype and, ultimately, to develop and target more effective treatments.

      Disclosures

      The authors report no biomedical financial interests or potential conflicts of interest.

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      Acknowledgment

      We would like to thank the Medical Research Council (MRC) (MR/M013588) for funding the study. We would also like to acknowledge and thank Ms Raj Seraya Bhatoa, Ms Iruni Wanigasekara and Ms Laura Lennuyeux-Comnene for their assistance with the study.

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