Psychological Medicine (2013), 43, 401–411. f Cambridge University Press 2012
doi:10.1017/S003329171200116X
O R I G I N A L AR T I C LE
Frontotemporal white-matter microstructural
abnormalities in adolescents with conduct disorder:
a diffusion tensor imaging study
S. Sarkar1,3*#, M. C. Craig1,2,3#, M. Catani1,2,3, F. Dell’Acqua1,2,3, T. Fahy1,2, Q. Deeley1,2$
and D. G. M. Murphy1,2$
1
Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, King’s College London, London, UK
NIHR Biomedical Research Centre for Mental Health at South London and Maudsley NHS Foundation Trust and Institute of Psychiatry, King’s
College London, UK
3
Natbrainlab, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, King’s College London, London, UK
2
Background. Children with conduct disorder (CD) are at increased risk of developing antisocial personality disorder
(ASPD) and psychopathy in adulthood. The biological basis for this is poorly understood. A preliminary diffusion
tensor magnetic resonance imaging (DT-MRI) study of psychopathic antisocial adults reported significant differences
from controls in the fractional anisotropy (FA) of the uncinate fasciculus (UF), a white-matter tract that connects the
amygdala to the frontal lobe. However, it is unknown whether developmental abnormalities are present in the UF of
younger individuals with CD.
Method. We used DT-MRI tractography to investigate, for the first time, the microstructural integrity of the UF in
adolescents with CD, and age-related differences in this tract. We compared FA and perpendicular diffusivity of the
UF in 27 adolescents with CD and 16 healthy controls (12 to 19 years old) who did not differ significantly in age, IQ
or substance use history. To confirm that these findings were specific to the UF, the same measurements were
extracted from two non-limbic control tracts. Participants in the CD group had a history of serious aggressive and
violent behaviour, including robbery, burglary, grievous bodily harm and sexual assault.
Results. Individuals with CD had a significantly increased FA (p=0.006), and reduced perpendicular diffusivity
(p=0.002), in the left UF. Furthermore, there were significant age-related between-group differences in perpendicular
diffusivity of the same tract (Zobs=2.40, p=0.01). Controls, but not those with CD, showed significant age-related
maturation. There were no significant between-group differences in any measure within the control tracts.
Conclusions. Adolescents with CD have significant differences in the ‘ connectivity ’ and maturation of UF.
Received 3 January 2012 ; Revised 24 April 2012 ; Accepted 25 April 2012 ; First published online 23 May 2012
Key words : Conduct disorder, diffusion tensor imaging, neuroimaging, psychopathy, uncinate fasciculus, white
matter.
Introduction
Conduct disorder (CD) has been reported to occur in
up to 16 % of school-aged children (Olsson, 2009). It is
defined by a persistent display of antisocial behaviour
such as deception, theft, vandalism and violence
within a 6–12-month period prior to age 18 years
(APA, 2000). Importantly, children with severe CD
cost society 10 times more to support into adulthood
* Address for correspondence : Ms. S. Sarkar, King’s College
London, Institute of Psychiatry, Department of Forensic and
Neurodevelopmental Science, PO Box 50, De Crespigny Park, London
SE5 8AF, UK.
(Email : [email protected])
# These authors contributed equally to this work.
$ These authors contributed equally to this work.
than those without (Scott et al. 2001). Furthermore,
there is a strong association between CD and other
psychiatric disorders, for example substance use
(Kessler et al. 1996) and mood disorders (Vloet et al.
2008), and persistent antisocial behaviour in adulthood. For instance, up to 75 % of children with CD
grow up to have adult antisocial personality disorder
(ASPD) (Gelhorn et al. 2007). Current treatment interventions are not effective in the majority of children
with CD (Kazdin, 1995). Despite the significant impact
on individuals and society as a whole, the biological
determinants of CD are poorly understood.
It is unlikely that CD can be explained by differences in the development of a single brain region.
Nevertheless, increasing evidence suggests that childhood CD and adulthood antisocial behaviour are
402
S. Sarkar et al.
associated with abnormalities in the anatomy and
function of brain regions associated with the limbic
system, and particularly the orbitofrontal cortex (OFC)
and amygdala (Sterzer & Stadler, 2009 ; Fairchild et al.
2011 ; Sarkar et al. 2011). Studies of cognitive processing in children and adults with antisocial behaviour
have reported impairments in neuropsychological
tasks sensitive to differences in function of the OFC
and amygdala, for example in reversal learning
(Budhani et al. 2005 ; Budhani et al. 2006) and emotion
processing, respectively (Levenston et al. 2000 ; Blair
et al. 2001, 2006). Damage to these brain regions is associated with CD (Ishikawa & Raine, 2003) and adult
antisocial behaviour (see Brower & Price, 2001),
and with impaired perception of fear and anger
(Scott et al. 1997 ; Adolphs et al. 1998). In vivo functional
brain imaging studies, from our group and others,
also report significant differences in activation of
these regions, and/or regions modulated by them, in
children with CD (Finger et al. 2008 ; Marsh et al. 2008)
and adult criminal psychopaths (Raine et al. 1997 ;
Kiehl et al. 2001 ; Deeley et al. 2006). There is also
initial evidence that adolescents with CD have
reduced functional ‘ connectivity ’ between the amygdala and OFC (Marsh et al. 2008, 2011). However,
little is known about the anatomy of limbic brain
regions, or the connections between them, in children
with CD.
Some structural magnetic resonance imaging (MRI)
studies have reported that adults with antisocial behaviour have significantly reduced volumes of the
amygdala (Yang et al. 2009) and OFC/prefrontal cortex (PFC) grey matter (Raine et al. 2000 ; de OliveiraSouza et al. 2008). Only nine structural MRI studies
have been published to date on children/adolescents
with CD (Bussing et al. 2002 ; Kruesi et al. 2004 ; Sterzer
et al. 2007 ; Huebner et al. 2008 ; De Brito et al. 2009,
2011 ; Fahim et al. 2011 ; Fairchild et al. 2011 ; Hyatt et al.
2011). These reported that young people with CD have
significantly reduced grey-matter volume in the temporal lobes (Kruesi et al. 2004 ; Huebner et al. 2008 ;
Hyatt et al. 2011) and anterior insula (Sterzer et al.
2007) bilaterally, and left (Sterzer et al. 2007 ; Huebner
et al. 2008) or bilateral (Fairchild et al. 2011) amygdala.
However, evidence for differences within other regions, such as the PFC, is less consistent. For example,
grey-matter volume and/or concentration of the PFC
has been reported as no different (Sterzer et al. 2007),
reduced (Huebner et al. 2008 ; Fahim et al. 2011) and
increased (De Brito et al. 2009). This variability probably arises because most studies were of relatively
small heterogeneous samples that differed in several
key respects, such as the age ranges of people studied
(e.g. older adolescents frequently engage in higher
levels of substance misuse than younger children).
In addition, some did not control for potential
confounding factors such as overall cognitive ability
(Bussing et al. 2002) and co-morbid attention-deficit/
hyperactivity disorder (ADHD) (Bussing et al. 2002 ;
Huebner et al. 2008). Importantly, studies have not
considered the presence of callous–unemotional (CU)
traits, often referred to as psychopathic tendencies.
These are a constellation of interpersonal and
emotional characteristics that accompany disruptive
or antisocial behaviour in approximately 25 % of children with childhood-onset CD (Frick, 1998). Traits
include low fearfulness, impulsivity, shallow affect,
poor empathy and an absence of guilt (Hare, 1991 ;
Christian et al. 1997). Children with CU traits show a
pattern of neuropsychological deficits that implicate
limbic/prefrontal dysfunction (Blair et al. 2006 ; Dadds
et al. 2006 ; Finger et al. 2008 ; Marsh et al. 2008). Thus,
CU traits delineate a distinct subset within CD that
require consideration in research.
Brain regions do not function in isolation ; they form
part of brain ‘ systems ’. Hence it is crucial to investigate the white-matter connections linking brain regions putatively implicated in CD. We previously
reported that adults with ASPD and psychopathy had
a significant reduction in fractional anisotropy (FA) of
the uncinate fasciculus (UF), a white-matter tract connecting the amygdala and OFC (Craig et al. 2009). A
recent study also reported reduced FA of the UF
alongside several other tracts (Sundram et al. 2012). FA
value is derived from diffusion tensor MRI scanning
(DT-MRI), and is an indicator of white-matter microstructural integrity through the quantification of
directional differences in the diffusion of water
molecules inside tissues. FA is derived from the difference between two absolute values, parallel/axial
diffusivity (Dparr) and perpendicular/radial diffusivity (Dperp), the rates of diffusion observed along versus
across fibre tracts, respectively. FA values range from
0 (perfectly isotropic diffusion) to 1 (perfectly anisotropic diffusion), providing a proxy measure of tissue
integrity (Horsfield & Jones, 2002). The microstructural basis for FA value is thought to lie with properties such as the organization within and between
fibres, axonal diameter, and myelination (Beaulieu,
2009 ; Paus, 2010). By contrast, Dperp is considered a
marker for reduced membrane integrity, which has
its basis in reduced myelin content, and intraaxonal factors (see Beaulieu, 2009), based on the observation that increased Dperp occurs with demyelination. Reduced Dperp is also seen in typical brain
maturation and is associated with increasing FA
(Lebel et al. 2008).
In summary, there is preliminary evidence that
microstructural integrity of the UF (as measured using
DT-MRI) is reduced in antisocial adults. However, it is
White-matter microstructural abnormalities in conduct disorder
403
Table 1. Description of the cohort
Conduct disorder
(n=27)
Healthy controls
(n=16)
p value
16 (2)
99 (8)
6 (2)
7 (2)
18 (5)
7 (2)
25 (7)
16 (2)
103 (10)
3 (1)
6 (2)
12 (5)
5 (2)
19 (6)
0.858
0.098
0.000**
0.375
0.000**
0.012*
0.005**
x2
Age (years)
Mean FSIQ
Conduct problems (SDQ)
Hyperactivity (SDQ)
Total problems (SDQ)
Callous–unemotional traits (APSD)
Total score (APSD)
Ethnicity
White
Black/African-Caribbean
Other
52
33
15
63
25
13
0.717
0.735b
1.000b
Substance use
Cannabis – ever used
Cannabis – used in past month
Alcohol – ever used
Alcohol – used in past month
Cocaine – ever used
Amphetamine – ever used
Any other druga – ever used
60
50
75
73
10
10
15
40
67
100
67
0
0
7
0.407
0.638b
0.057b
1.000b
0.496b
0.496b
0.619b
FSIQ, Full-Scale Intelligence Quotient ; SDQ, Strengths and Difficulties Questionnaire ; APSD, Antisocial Process Screening
Device.
Values given as percentage or mean (standard deviation).
a
Excluding alcohol and cannabis.
b
Fisher’s exact probability test.
* Significant p value f0.05. ** Significant p value f0.005.
unknown whether children with CD have similarly
abnormal anatomy, or maturation, of this same tract as
compared to their non-CD peers.
Therefore, we extended our prior work and investigated white-matter tract anatomical ‘ connectivity ’ within the limbic system of children with CD
and healthy controls who did not differ significantly in
age or IQ. As brain anatomy is modulated by chronic
exposure to factors such as alcohol and substance
misuse, which are frequently found in these populations (Versace et al. 2008), we additionally assessed
self-reported substance use history. We tested the
main hypothesis that children with CD have significant differences in the microstructural integrity of the
UF, as indexed by reduced FA, and increased Dperp. To
confirm that any differences we found were specific
to the limbic amygdala–OFC network, the same measurements were extracted from two non-limbic control
tracts : the inferior fronto-occipital fasciculus (IFOF)
and the inferior longitudinal fasciculus (ILF). We also
tested the subsidiary hypotheses that : (1) individuals
with CD and controls have significant age-related differences in the FA and Dperp of the UF ; and (2) the
degree of white-matter abnormality is related to
severity of antisocial behaviour and CU traits.
Method
This study was approved by the Joint South London
and Maudsley Research Ethics Committee (243/00).
Participants
Twenty-seven CD participants aged between 12 and
19 years were recruited from : (i) an Institute of
Psychiatry database of adolescents with conduct problems (CPs) ; (ii) three Youth Offending Teams ; (iii) five
Pupil Referral Units (PRUs ; facilities providing education to children who cannot attend mainstream
schools, e.g. following school exclusion) ; (iv) four
youth projects ; and (v) two mainstream educational
institutions. A further 16 right-handed males were recruited as controls from the general public, through
schools and youth services (i.e. youth clubs,
‘ Connexions ’ and several youth charities) within the
same geographical areas (deprived and inner city) as
the CD group. Groups did not differ significantly in
age, full-scale IQ (FSIQ), ethnicity and self-reported
history of alcohol or cannabis use (Table 1). Although
more CD individuals (n=2) than controls (n=0) had
previously used amphetamines and cocaine, this difference was not statistically significant. Furthermore,
404
S. Sarkar et al.
measures of current hyperactivity and the number
of boys who had ever received a diagnosis of
ADHD (Table 1) did not differ significantly between
groups.
All study participants satisfied MRI safety requirements and were medication free, did not have a psychiatric history (other than CD, ADHD or referrals
for anger management), spoke English as their first
language and were right-handed as assessed by the
Edinburgh Handedness Inventory (Oldfield, 1971).
FSIQ was measured using the vocabulary and matrix
reasoning subtests of the Wechsler Abbreviated Scale
of Intelligence (WASI ; Wechsler, 1999). We excluded
individuals with an FSIQ <80.
Measures
Questionnaires
Parent and self-report versions of the Strengths and
Difficulties Questionnaire (SDQ ; Goodman, 1999) and
Antisocial Process Screening Device (APSD ; Frick &
Hare, 2001) were administered. The SDQ was used to
obtain CP and hyperactivity measures whereas the
APSD assessed CU traits. Following methods of
other groups, accepted subscales for both measures
comprised the higher rater’s score for each item (Jones
et al. 2009).
Interviews
CD and oppositional defiant disorder (ODD) subsections of the Kiddie Schedule for Affective Disorders
and Schizophrenia – Present and Lifetime Version
(K-SADS-PL ; Kaufman et al. 1997) were used to obtain
a research diagnosis of CD. Screening interviews for
these disorders were administered to all participants,
with those meeting criteria for CD or ODD given
complete interviews for both disorders. No participants met criteria for ODD in the absence of CD.
Finally, participants meeting CD criteria who additionally scored o20 on the APSD parent or selfreport questionnaire were then interviewed using the
Psychopathy Checklist Youth Version (PCL-YV ; Forth
et al. 2003). Scores o20 were used to indicate the
presence of psychopathic traits (Finger et al. 2008).
Interviews were conducted by a research psychologist
(S.S.) trained and supervised by a psychiatrist (Q.D.).
Additional information about antisocial behaviour
was gathered from teachers, youth club workers,
social workers and parents.
Participants in the CD group had a history of
serious aggressive and violent behaviour, including
robbery, burglary, grievous bodily harm and sexual
assault.
Procedure
Full written informed consent was taken from participants, and additionally from a parent/guardian where
boys were aged <16 years. Postal versions of parent
questionnaires were obtained where older participants
attended their test session unaccompanied.
DT-MRI acquisition
Each DT-MRI image was acquired using a GE Signa
HDx 3.0-T MR scanner (General Electric, USA), with
actively shielded magnetic field gradients (maximum
amplitude 40 mT/m). The body coil was used for RF
transmission, and an eight-channel head coil for signal
reception, allowing a parallel imaging (Array Spatial
Sensitivity Encoding Technique ; ASSET) speed-up
factor of two. Head movement was minimized by fitting extra padding beside the participant’s head. Each
volume was acquired using a multi-slice peripherally
gated doubly refocused spin–echo echo planar imaging (EPI) sequence, optimized for precise measurement of the diffusion tensor in parenchyma, from 60
contiguous near-axial slice locations with a voxel size
of 1.85r1.85r2.4 mm. The echo time was 104.5 ms
and the effective repetition time varied between subjects in the range 12 and 20 RR intervals. Based on the
recommendations of Jones et al. (2002), the maximum
diffusion weighting was 1300 s mmx2 and, at each
slice location, four images were acquired with no diffusion gradients applied, together with 32 diffusionweighted images in which gradient directions were
distributed uniformly in space. The sequence ran for
approximately 15 min.
DT-MRI data preprocessing
All data were first converted to NIfTI format and then
each raw diffusion dataset underwent a full quality
control check where all B0 values and diffusionweighted volumes were inspected visually for image
corruption, motion artefacts and signal drop-out effects
using the light-box function available inside fslview
(part of FSL software; www.fmrib.ox.ac.uk/fsl). Datasets showing more than two motion artefacts in different volumes on the same slice were removed from the
study. Datasets showing significant head movements
(>1 cm) were removed. No participant data acquired
in this study required removal due to motion
artefacts. Data were eddy current and motion corrected
using ExploreDTI (Leemans et al. 2009). The diffusion
tensor was estimated following removal of outlier
data (RESTORE function ; Chang et al. 2005) and
whole-brain tractography was performed on the data.
Whole-brain tractography parameters selected as seed
voxels all those with FA o0.2. Streamlines were propagated using Euler integration applying a b-spline
White-matter microstructural abnormalities in conduct disorder
Left
Right
0.50
0.49
0.48
0.47
0.46
0.45
0.44
0.43
0.42
0.41
0.40
0.39
0
Inferior fronto-occipital fasciculus
Fractional anisotropy
0.50
0.49
0.48
0.47
0.46
0.45
0.44
0.43
0.42
0.41
0.40
0.39
0
Inferior longitudinal fasciculus
*p = 0.006
Fractional anisotropy
Fractional anisotropy
Uncinate fasciculus
Left
Right
405
0.54
0.53
0.52
0.51
0.50
0.49
0.48
0.47
0.46
0.45
0.44
0.43
0
Left
Right
Fig. 1. Between-group differences in mean fractional anisotropy of the uncinate fasciculus and control tracts. , Conduct
disorder ; %, healthy controls.
interpolation of the diffusion tensor field (Basser et al.
2000), and the tractography algorithm step size of
0.5 mm. Where FA <0.2 or when the angle between
two consecutive tractography steps was larger than
30x, tractography stopped. Finally, diffusion tensor
maps (FA, mean diffusivity, FA-colour, Dparr, Dperp,
mean diffusion weighted image) were estimated and
exported to TrackVis (Wang & Wedeen, 2007). Full
details are given elsewhere (Jones et al. 2002).
DT imaging (DTI) tractography
TrackVis software was used to hand dissect in native
space. The tract of interest (UF) plus the two control
tracts IFOF and ILF were dissected in the same order
for all data by a trained and reliable operator (S.S.)
blind to clinical groupings. Dissection of the three
tracts was performed one hemisphere at a time using
the region of interest (ROI) approach described
elsewhere (Catani et al. 2002 ; Catani & Thiebaut
de Schotten, 2008) in the order (i) IFOF, (ii) UF and
(iii) ILF (see top of Fig. 1). The UF was defined with
the first ROI placed on the axial slice at the level of the
medial temporal lobe and the second ROI placed coronally slightly posterior to the external capsule. Short
fibres that did not enter either termination of the tract
were excluded, as were long fibres extending to regions
outside the frontal and temporal lobes. These fibres
were omitted through placement of exclusion ROIs.
Statistical analysis
All statistical analyses were carried out using
SPSS software (SPSS Inc., USA). Repeated-measures
analysis was used with the within-subjects variables of
tract (UF, IFOF, ILF) and hemisphere (left, right), and
CD as the between-subjects variable. This tested for
significant differences in FA and Dperp between CD
and control participants in the UF and the two control
tracts. Post-hoc analyses were carried out to identify
significantly differing tract values between boys with
CD and healthy controls using one-way analysis
of variance (ANOVA). Analyses were Bonferroni
corrected for multiple comparisons.
Where a significant FA/Dperp difference was detected, post-hoc analyses were carried out to examine
the relationship between these measures and age in
each group using Pearson’s correlations ; we then determined if there were significant between group differences in these relationships using Z-observation
analysis (Pallant, 2007). Finally, we examined whether
significant differences in DT-MRI parameters were
associated with greater severity of CPs or CU traits
within, first, the whole sample and, second, the CD
group only. Correlations were carried out between
DT-MRI measures and (i) total SDQ score, (ii) SDQ CP
score, (iii) total APSD score and (iv) APSD CU traits
score, controlling for age.
Results
Tractography
The CD group had significant differences from controls in the left UF, with a greater FA (CD 0.471 ;
control 0.451 ; p=0.006) and reduced Dperp (CD
0.583r10x3 mm2/s ; control 0.611r10x3 mm2/s ;
406
S. Sarkar et al.
Table 2. Results of the one-way ANOVA showing differences in DTI measures of the UF and control tracts between CD and healthy
controls
Tract
Parameter
Hemisphere
CD
Mean (S.D.)
Controls
Mean (S.D.)
p value
UF
FA
Left
Right
Left
Right
Left
Right
Left
Right
Left
Right
Left
Right
0.47 (0.02)
0.47 (0.02)
0.58 (0.03)
0.59 (0.03)
0.51 (0.02)
0.52 (0.02)
0.55 (0.03)
0.54 (0.04)
0.48 (0.03)
0.48 (0.02)
0.57 (0.04)
0.57 (0.03)
0.45 (0.02)
0.46 (0.02)
0.61 (0.03)
0.60 (0.03)
0.50 (0.02)
0.51 (0.02)
0.57 (0.03)
0.56 (0.03)
0.47 (0.02)
0.48 (0.02)
0.59 (0.03)
0.58 (0.04)
0.006a
0.040
0.002a
0.306
0.321
0.281
0.115
0.159
0.101
0.454
0.062
0.093
Dperp
IFOF
FA
Dperp
ILF
FA
Dperp
DTI, Diffusion tensor imaging ; CD, conduct disorder ; S.D., standard deviation ; UF, uncinate fasciculus ; IFOF, inferior
fronto-occipital fasciculus ; ILF, inferior longitudinal fasciculus ; FA, fractional anisotropy ; Dperp, perpendicular diffusivity
value and S.D.r10x3 mm2/s.
a
Significant after Bonferroni correction.
p=0.002). They also had significantly greater FA in the
right UF (CD 0.468 ; control 0.455 ; p=0.040) but this
did not withstand Bonferroni correction. No significant differences were observed between groups in
either FA or Dperp within the two control tracts (IFOF,
ILF ; Table 2 ; Fig. 1).
UF and age
Within the CD group there was no significant association between left UF FA and Dperp and age. By contrast, there was a significant negative correlation
between age and Dperp of the left UF (r=x0.625,
t=0.01) within the control group, and this differed
significantly from the non-significant correlation seen
in CD (Zobs=2.40, p=0.01 ; Table 3, Fig. 2). DT-MRI
indices between high and low CU groups did not
differ significantly from one another (Zobs=0.55).
UF and antisocial behaviour measures
Significant correlations were found between left UF
FA/Dperp abnormality and severity of all SDQ/APSD
behavioural scores within the whole sample (Table 4).
There was also a strong trend, but this did not reach
statistical significance, between APSD scores in the CD
group alone (p=0.09 ; Fig. 3).
Discussion
We report, for the first time, that adolescents with CD
have significantly increased microstructural integrity
Table 3. Pearson’s correlations between left UF FA and Dperp
with age in CD group compared to healthy controls
Age–CD group
r/p
FA left
Dperp left
x0.06/0.75
0.09/0.64
Age–controls
r/p
0.45/0.08
x0.63/0.01*
Zobs
value
1.60
2.40*
UF, Uncinate fasciculus ; FA, fractional anisotropy ;
Dperp, perpendicular diffusivity ; r, correlation coefficient ; p,
significance level ; CD, conduct disorder ; Zobs, Z observation.
* Two-tailed significance level : p<0.05.
of the UF as compared to healthy controls. This
increase was tract specific, that is no between-group
differences were found in the ‘ control ’ tracts. Post-hoc
analysis found that the expected decline of Dperp with
age was not seen in the CD group as it was in controls.
We also found a significantly different relationship
between age and this measure in the two groups.
Moreover, post-hoc analysis found a significant relationship between microstructural abnormality and
severity of antisocial behaviour in the whole sample,
although not in the CD group alone. The significant
findings reported here were found in the left UF ;
however, there was a trend towards significance in the
right hemisphere.
These results support our a priori hypothesis that
antisocial behaviour is associated with specific abnormalities in limbic connections (i.e. as opposed to global
white-matter changes). However, the difference we
White-matter microstructural abnormalities in conduct disorder
0.52
FA of left uncinate fasciculus
0.51
0.50
0.49
0.48
0.47
0.46
0.45
0.44
0.43
0.42
0.41
0.40
130
170
210
Dperp of left uncinate fasciculus
(×10–3 mm2/s)
Age (months)
0.66
0.62
0.58
0.54
0.50
130
170
210
Age (months)
Fig. 2. Relationship between diffusion tensor magnetic
resonance imaging (DT-MRI) measures and age in the left
uncinate fasciculus of adolescents with conduct disorder (&)
compared to healthy controls ( ). FA, Fractional anisotropy ;
Dperp, perpendicular diffusivity.
found was in the opposite direction to what was
hypothesized (i.e. increased FA). The UF tract is the
major frontotemporal limbic tract and it connects the
amygdala and OFC. Damage to this tract leads to impairments of conditional associative learning in animals (Gaffan & Eacott, 1995 ; Gutnikov et al. 1997).
Reversal learning, a form of conditional associative
learning, involves learning to ‘ reverse ’ responses that
were previously rewarded but are later punished.
Difficulties with reversal learning have been demonstrated in adults with antisocial behaviour and
psychopathy (Budhani et al. 2005, 2006). Furthermore,
children with CD and CU traits show abnormal blood
oxygen level-dependent (BOLD) activation in the
ventromedial PFC on reversal tasks during functional
MRI (Finger et al. 2008). It has been suggested that
reversal learning deficits contribute to the perseveration of antisocial behaviour in both young people
and adults, in which individuals fail to learn
to avoid behaviour that has negative consequences
407
for themselves and others (Sundram et al. 2012).
Our findings may help to explain the biological
basis of this issue, which will be a focus of our future
studies.
In addition, altered ‘ connectivity ’ of the OFC and
amygdala secondary to abnormal development of the
UF may contribute to impaired regulation of amygdala activity by the OFC, which in turn may contribute
to the abnormal emotional processing and behavioural
disinhibition observed in young people with CD and
adults with ASPD/psychopathy (Blair, 2008). For example, a prior study reported reduced functional
‘ connectivity ’ between the amygdala and ventromedial PFC in children with CD and CU traits during
an emotional processing task (Marsh et al. 2008).
Furthermore, a DTI-MRI study of healthy children reported that a measure of engagement in dangerous
and risky activities correlated positively with FA, and
negatively with Dperp, in frontal white-matter tracts
(Berns et al. 2009). It was also proposed that this may
be attributable to earlier maturation of these tracts in
high-scoring youngsters. Finally, the converse could
be posited : that abnormal development of limbic and
prefrontal grey matter may underlie the development
of abnormal limbic–prefrontal circuitry.
Our findings raise the question of how age, behaviour and disorder-related differences in FA relate to
the underlying biology and its developmental determinants. Our results show that, whereas in typical
children Dperp of the left UF decreases with age, in CD
it does not. Moreover, the relationship between this
DT-MRI measure and increasing age differed significantly between groups. As discussed previously,
myelination is one process thought to underlie the
decreasing Dperp values and increasing FA seen in
typical maturation (Song et al. 2003 ; Lebel et al. 2008),
alongside greater axonal calibre (Paus, 2010) and reduced neuronal branching (Silk et al. 2009). It is not
clear which of these factors makes the greater contribution to our findings. However, we also found significantly reduced Dperp in the left UF accompanied by
increased FA in CD, suggesting that these individuals
may differ from controls with respect to the myelination of this tract. It is known that myelination differs
by age and brain region (Lebel et al. 2008), and is
modulated by learning and environmental experience.
For example, increased myelination has been found to
accompany intensive practice of motor tasks, such as
piano playing (Bengetsson et al. 2005) and juggling
(Scholz et al. 2009). In addition, children with ADHD
showed increased FA in frontal tracts, which the authors speculated may arise from early myelin damage
that later triggers hypermyelination (Li et al. 2010).
Finally, FA changes are associated with social and
emotional experience. For example, children who
408
S. Sarkar et al.
Table 4. Correlations between UF DT-MRI measures and antisocial behaviour scores in the
whole sample
(i) SDQ total
(ii) SDQ CP
(iii) APSD total
(iv) APSD CU traits
Left UF FA
r/p
Right UF FA
r/p
0.32/0.019*
0.32/0.021*
0.40/0.005**
0.40/0.004**
0.33/0.018*
0.27/0.042*
0.32/0.019*
0.36/0.009**
Left UF Dperp
r/p
x0.38/0.007**
x0.37/0.008**
x0.39/0.005**
x0.37/0.008**
UF, Uncinate fasciculus ; DT-MRI, diffusion tensor magnetic resonance imaging ;
SDQ, Strengths and Difficulties Questionnaire ; APSD, Antisocial Process Screening
Device ; CP, conduct problems ; CU, callous–unemotional traits ; FA, fractional
anisotropy ; Dperp, perpendicular diffusivity ; r, correlation coefficient ; p, significance
level.
* p<0.05, ** p<0.01.
0.52
FA of left uncinate fasciculus
0.51
0.50
0.49
0.48
0.47
0.46
0.45
0.44
0.43
0.42
0.41
0.40
0
10
20
30
40
APSD total score
Fig. 3. Trend towards correlation between fractional
anisotropy (FA) of the left uncinate fasciculus and total
Antisocial Process Screening Device (APSD) score in the
conduct disorder group (r=0.271, p=0.09).
experience severe deprivation in early childhood have
significant decreases in FA of the left UF as compared
to control children (Eluvathingal et al. 2006). Similarly,
it was reported that young adults exposed to high
levels of verbal abuse from their parents during
childhood have significant reduction in FA of two left
hemisphere limbic tracts (cingulum and fornix) and
the arcuate fasciculus (Choi et al. 2009). Therefore,
changes in tract integrity seen in developmental psychopathologies, such as those observed in this study,
may have arisen from a complex mixture of social and
biological factors. This highlights both the need for
future studies of white-matter maturation to consider
(for example) environmental and social variables,
and the potential relevance of early interventions to
prevent or moderate the course of developmental
disorders.
Our post-hoc investigation revealed a significant
association between CD/CU traits and UF FA/Dperp
in the sample as a whole but only a trend to significance in the CD group alone. This preliminary finding
suggests that this tract may contribute towards the
generation of behavioural variation in adolescents,
perhaps through an increased ‘ connectivity ’ between
frontal and limbic systems, but further (larger) studies
are required.
Finally, the increased FA reported in CD adolescents was in the opposite direction to our a priori
hypothesis, which had been based on findings in
adults with antisocial behaviour (Craig et al. 2009).
One possible explanation for this may be that whitematter maturation of the UF in children with CD follows a different developmental trajectory to that of
healthy individuals, consistent with abnormal patterns of white-matter maturation in non-CD children
who indulge in extreme risk-taking behaviours (Berns
et al. 2009) ; that is, an initially increased rate of whitematter microstructural development in CD adolescents, with subsequent failure of typical development
across adolescence. Such a mechanism may contribute
towards a neurobiological explanation for the
high rates of recidivism and treatment resistance
found within persistently antisocial populations. For
example, abnormal/precocious white-matter maturation in children with CD may interfere with neural
mechanisms underpinning pro-social behaviour.
However, it is only possible to investigate such a hypothesis through future longitudinal studies and the
current study, like all previous published studies, was
limited by its cross-sectional design.
Our study has several limitations. First, we did not
find significant correlations between abnormalities in
UF and measures of antisocial behaviour in the CD
group alone (albeit we did find trends) ; this may have
White-matter microstructural abnormalities in conduct disorder
resulted from lack of power due to our sample size.
Second, we recruited antisocial children with CD
from predominantly non-forensic community samples. These children had carried out extremely serious
offences (e.g. robbery, grievous bodily harm and sexual assault). Nevertheless, if we had recruited from
juvenile detention centres and other forensic settings,
we would probably have identified children with
more severe antisocial behaviour. This in turn may
have highlighted greater differences in white-matter
measures between groups that may have associated
with behavioural measures. However, given the difficulty of recruiting from such settings, the current
study selected participants with the highest levels of
antisocial behaviour observable in community samples. Furthermore, our findings are more generalizable
to the wider population of children with CD, whose
antisocial behaviour does not cross the threshold for
incarceration within the criminal justice system.
Conversely, one of the strengths of the current study
lies in its recruitment of a healthy control group
who closely resemble the CD group in many respects,
such as FSIQ and ethnicity. One final caveat is that
two of our four behavioural measures have a
recommended upper age limit of 16 and 17 years,
namely the APSD and SDQ respectively. However, as
these were used only as screening measures prior to
grouping participants using the K-SADS-PL and
PCL-YV, this was not thought likely to affect our
results.
In summary, adolescents with CD have significant
differences from controls in the microstructural
anatomy, and maturation, of the UF. However, it is
not clear how these abnormalities arise, or if they
predict outcome. Studies of antisocial behaviour
within larger cohorts and across the lifespan are
required.
Declaration of Interest
None.
Acknowledgements
This work was generously funded by a private donation, together with infrastructure support from the
Medical Research Council (MRC, UK) AIMS Network
(G0400061/69344, D.G.M.M., PI), an ongoing MRCfunded study of brain myelination in neurodevelopmental disorders (G0800298/87573), and the National
Institute for Health Research (NIHR) Biomedical
Research Centre for Mental Health at King’s College
London, Institute of Psychiatry and South London and
Maudsley National Health Service (NHS) Foundation
Trust.
409
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