Short- and long-range functional connectivity density alterations in adolescents with pure conduct disorder at resting-state

Accepted Manuscript Short- and long-range functional connectivity density alterations in adolescents with pure conduct disorder at resting-state Feng-Mei Lu, Jian-Song Zhou, Xiao-Ping Wang, Yu-Tao Xiang, Zhen Yuan PII: DOI: Reference:

S0306-4522(17)30206-3 http://dx.doi.org/10.1016/j.neuroscience.2017.03.040 NSC 17684

To appear in:

Neuroscience

Received Date: Revised Date: Accepted Date:

29 November 2016 15 March 2017 26 March 2017

Please cite this article as: F-M. Lu, J-S. Zhou, X-P. Wang, Y-T. Xiang, Z. Yuan, Short- and long-range functional connectivity density alterations in adolescents with pure conduct disorder at resting-state, Neuroscience (2017), doi: http://dx.doi.org/10.1016/j.neuroscience.2017.03.040

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

1

Short- and long-range functional connectivity density alterations in adolescents with pure conduct disorder at resting-state Feng-Mei Lua, Jian-Song Zhoub, Xiao-Ping Wangb, Yu-Tao Xianga, Zhen Yuana,*

a

Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, China.

b

Mental Health Institute, Second Xiangya Hospital, Central South University; Hunan Province

Technology Institute of Psychiatry; Key Laboratory of Psychiatry and Mental Health of Hunan Province, Changsha, Hunan 410011, China

*

Corresponding author: Prof. Zhen Yuan, Bioimaging Core, Faculty of Health Sciences,

University of Macau, Macau SAR China. Email: [email protected].

2

Abstract Conduct disorder (CD) is a developmental disorder defined by a repetitive and persistent display of antisocial and aggressive behaviors that violates the rights of others or basic social rules. Recently, resting-state functional magnetic resonance imaging (rsfMRI) has been widely adopted to investigate the altered intrinsic neural activities and the disrupted endogenous brain connectivity of CD. In this study, functional connectivity density (FCD) mapping, a newly developed ultrafast voxel-wise method based on rsfMRI, was applied for the first time to examine the changes in the brain functional connectivity in CD at the voxel level. We assessed the differences in FCD between eighteen male adolescents with CD and eighteen typicallydeveloping (TD) individuals. Then, the identified brain regions in which CD patients and healthy controls exhibited significant difference in FCD were extracted to calculate the correlations between measures of FCD values and clinical data. We discovered that compared to healthy controls, CD patients showed increased short-range FCD in the default-mode network including the bilateral posterior cingulate cortex (PCC) and the bilateral precuneus (PCUN). More importantly, increased short-range FCD values in the bilateral PCC, the bilateral PCUN, and increased long-range FCD values in the left MCC showed significant correlations with the impulsivity. Overall, these results suggested that the FCD abnormalities in CD patients occurred in brain regions known to be involved in cognition, emotion and visual perception.

Abbreviations CD, conduct disorder; TD, typically-developing; rsfMRI, resting-state functional magnetic resonance imaging; FCD, functional connectivity density; DMN, default-mode network; PCC, posterior cingulate cortex; PCUN, precuneus; MCC, middle cingulate cortex; CAL, calcarine

3 fissure; ICA, independent component analysis; rsFCD, resting-state functional connectivity density; K-SADS-PL, Schedule for Affective Disorder and Schizophrenia for School-Age Children-Present and Lifetime; BIS-11, Barratt Impulsivity Scale; FD, frame-wise displacement; MNI, Montreal Neurological Institute; FWHM, full-width at half-maximum; ODD, oppositional defiant disorder; substance use disorder (SUD), obsessive-compulsive disorder (OCD); ADHD, attention deficit/hyperactivity disorder

Keywords conduct disorder; resting-state fMRI; functional connectivity density; default-mode network

4

Introduction Conduct disorder (CD) is typically characterized by a repetitive and persistent pattern of antisocial and aggressive behaviors that entails the violation of the rights of others or basic social rules (DSM-5, Diagnostic and Statistical Manual of Mental Disorders) (Association, 2013). According to the DSM-5, CD has the subtypes of childhood onset (prior to 10 years old) and adolescent onset. Importantly, a meta-analysis of epidemiological study indicated that CD has a very high worldwide prevalence of 3.2% during aged from 6 to 18 years (Canino et al., 2010), and particularly males are more likely to develop CD compared with females (Berkout et al., 2011). Among the adolescents with CD, 46% of the males and 39% of the females exhibited the comorbidity with other disorders such as oppositional defiant disorder (ODD), attentiondeficit/hyperactive disorder (ADHD), anxiety disorders, and mood disorders (Maughan et al., 2004, Olsson, 2009). Additionally, patients with CD also present a very high risk of developing new and various psychopathologic disorders such as substance abuse, depression, antisocial personality disorder and suicide (Colman et al., 2009). More importantly, rising fees on multiple services for CD individuals including the social, education, health and juvenile justice services have hit all families hard (Baker, 2013). Given the severe impacts of CD on affected individuals and costs of medical care, it is essential to examine whether the altered resting-state activity in FCD is an important biomarker for CD. Recent work using task-based or resting-state functional magnetic resonance imaging (rsfMRI) has revealed the cortical and subcortical dysfunctions in patients with CD, in which the involved brain regions include the insula (Rubia et al., 2009b, Sebastian et al., 2012, Zhou et al., 2015b), anterior cingulate cortex (Rubia et al., 2009b), amygdala (Jones et al., 2009, Sebastian et al., 2012), fusiform gyrus (Zhou et al., 2015b), and orbitofrontal cortex (Finger et al., 2011). In

5 addition, recent results also showed that CD is strongly associated with the abnormalities of the functional connectivity brain networks including the default-mode network (DMN), the somatosensory network, and the visual network (Dalwani et al., 2014, Lu et al., 2015). To date, the most used technique for the functional connectivity analysis of the brain network based on rsfMRI is the seed-based correlation method (Biswal et al., 1995, Uddin et al., 2009, Guo et al., 2013). It is a hypothesis-driven approach which requires a priori selection of a specific seed region (Cole et al., 2010). Another data-driven based method for mapping the brain connectivity networks is the independent component analysis (ICA), which does not need to define an a priori time course or a specific seed region (McKeown et al., 1998, van de Ven et al., 2004, Beckmann et al., 2005). However, neither the seed-based method nor the ICA can effectively characterize the brain functional connectomes since they only provide the global measures of brain connectivity rather than local ones. In particular, changes in the number of connections at the voxel level within the whole brain, which are essential for the investigation of the underlying causes and mechanisms of development for CD, remain largely unclear. By contrast, resting-state functional connectivity density (rsFCD) mapping has been developing into an ultrafast and voxel-wise graph theory method, which has the capability for measuring the number of functional connections between a given voxel and all the other remaining brain voxels (Tomasi and Volkow, 2010). Consequently, FCD mapping can fully exhibit the altered cortical and subcortical functional hubs (regions that are densely connected) underlying the brain’s intrinsic functional organization. More importantly, rsFCD mapping has also shown its unbeatable advantages in generating the local and global FCD distributions at the voxel level with unprecedented sensitivity and discrimination at 3-mm isotropic spatial resolution (Tomasi and Volkow, 2012b, a). Interestingly, a specific voxel with the high rsFCD

6 value indicates a large number of functional connections between this voxel and the surroundings, suggesting that this voxel plays a more essential role in the information processing than those with low rsFCD values. Meanwhile, the rsFCD technique has two categories: the short-range (intraregional) and long-range (interregional) FCD mapping of the brain that are determined by the neighboring relationships between brain voxels (Tomasi and Volkow, 2012a, b). For instance, the short-range FCD is equivalent to the local FCD that mainly manifest the number of voxels in the local cluster whereas the global FCD illustrates the number of functional connections between this voxel and all the other voxels in the whole brain including both local and distant functional connections. In contrast, the long-range FCD is denoted as the difference between the global FCD and local FCD in order to eliminate all connected voxels belonging to the local cluster. Based on previous findings and methods mentioned above in the investigation of CD, it is rational to hypothesize that patients with CD might be characterized by the aberrant rsFCD in specific brain regions including the precuneus, posterior cingulate gyrus, occipital gyrus, and fusiform gyrus, which ultimately can cause the cognitive deficits in default-mode network, and the impaired perception in visual systems. In this study, we aim to quantify the resting-state neural brain activation patterns using FCD mapping, and compare the short-range and long-range FCD differences between the two groups. Notably, only “pure” CD patients without any comorbid psychiatric disorders such as ADHD, substance use disorder (SUD), anxiety, depression, affective disorders, alcohol- and drug-use disorder, obsessive-compulsive disorder (OCD), ODD, or mental retardation were recruited to participate in this study largely due to the significant differences between pure CD patients and healthy controls (Rubia et al., 2009a, Rubia et al., 2009b, Rubia et al., 2010, Stevens and Haney-Caron, 2012). In particular, only male

7 participants with pure CD were scanned using fMRI since previous studies exhibited substantial differences in brain activation patterns between male and female subjects (Tiet et al., 2001, Bao and Swaab, 2010). Consequently, we determine to examine the hypothesis that altered restingstate FCD is an essential biomarker for CD. We believe that the FCD changes in male adolescents with pure CD could provide us the new tool to reveal the complex neural mechanism underlying CD according to the alteration in the importance of a particular voxel in information processing.

Materials and Methods Participants Participants were eighteen right-handed adolescents with pure CD (mean aged 16.1 ± 0.5 years, age range 15~17 years) and eighteen precisely age-, handedness-, and gender-matched healthy controls (Lu et al., 2015, Zhou et al., 2015a, Zhou et al., 2015b). The CD adolescents were recruited from the Hunan province Youth Detection Centre, whereas the healthy controls were recruited from schools in the local community. The CD patients in our study were subjects with childhood-onset CD, who were less than 10 years old at the time of symptom onset (Association, 2013). It’s noted that only male subjects were included for both CD and TD groups. The oral and written information about the aims, content, duration of interviews, and scanning procedures were presented to all the CD and TD individuals and their parents or their legal guardians. Written informed assents for study participation and parental permission were then obtained by all the participants as well as their parents or legal guardians prior to our research. The present study was approved by the Biomedical Ethics Board of the Second Xiangya Hospital, China Central South University and the Biomedical Ethics Board with Faculty of Health Sciences at the University of Macau (Macao SAR, China).

8

Clinical measurements The present and lifetime histories of psychiatric diagnoses were assessed for all the participants by a professionally trained child psychiatrist using the Schedule for Affective Disorder and Schizophrenia for School-Age Children-Present and Lifetime (K-SADS-PL; Chinese version) (Kaufman et al., 1997, Shanee et al., 1997, Zhou et al., 2012). The K-SADS-PL is a standard semi-structured diagnostic interview questionnaire, which is widely adopted to diagnose the psychopathology in children and adolescents aged 6~18 years in accordance with the DSM-IV criteria (Association and Association, 1994). It consists of six sections: 1) the Unstructured Introductory Interview; 2) the Diagnostic Screening Interview; 3) the Supplement Completion Checklist; 4) the Appropriate Diagnostic Supplements; 5) the Summary Lifetime Diagnoses Checklist; and 6) the Children's Global Assessment Scale (Kaufman et al., 1997). Each individual symptoms is scored on a 0~3 rating scale, in which 0 means no information, 1 represents the symptom is not present, 2 implies subthreshold levels of symptomatology, and 3 denotes threshold criteria. All CD subjects met the K-SADS-PL criteria for CD, who also satisfied the following criteria: (1) satisfying the DSM-V criteria for CD; (2) no histories of neurological disorders; (3) no histories of other psychiatric disorders (e.g., anxiety, depression, schizophrenia, bipolar disorder, ADHD, SUD, OCD, ODD, alcohol- and drug-use disorder); (4) right handedness; and (5) normal and corrected-to-normal vision. Healthy controls were screened using the same instrument, who were required to be free of any neurological disorders such as paralysis, loss of sensation, epilepsy, muscular weakness, seizures, chronic pain, confusion, and prolonged loss of consciousness due to head injury. Finally, all participants had no contraindications to the MRI environment, no histories of head trauma, and didn’t take any medicine for at least 3 months prior to participating in our study.

9

Impulsiveness assessment The Barratt Impulsivity Scale (BIS-11) is a questionnaire applied to assess the personality/behavioral trait of impulsiveness (Patton and Stanford, 1995). The current version of the BIS-11 consists of 30 items which denotes the impulsive or non-impulsive behaviors and preferences. Each item has four points scale, in which 1 stands for rarely or never, 2 denotes occasionally, 3 implies often, and 4 means almost always or always. In addition, it has three second-order factors of impulsivity: attentional, motor and non-planning.

Data acquisition Data acquisition was performed using a 3T MRI scanner (Siemens Allegra, located at the Magnetic Resonance Center of Hunan Provincial People’s Hospital) with an eight-channel head coil. Foam padding was used to minimize the head motion and earplugs were also utilized to minimize the effect of the scanning noise on brain activation for all subjects. During the restingstate scans, all participants were instructed to rest quietly with eyes closed, and to be relaxed without thinking of anything but to keep awake. Functional images were obtained using a single shot gradient-recalled Echo Planar Imaging (EPI) pulse sequences with the following parameters: TR/TE = 3 s/30 ms, flip angle = 90°, field of view (FOV) = 256 × 256 mm, in-plane matrix = 64 × 64, slice thickness = 3 mm, and no gap. For each subject, a total of 100 volumes (36 slices per volume) of images were collected requiring a total scan time of 300 s. For spatial normalization, three-dimensional T1-weighted images with high resolution were acquired with a standard fast spoiled gradient-echo (Magnetization Prepared Rapid Gradient Echo, MP-RAGE) sequence using the following parameters: TR/TE = 2 s/3.36 ms, flip angle = 9°, voxel size = 1 × 1 × 1 mm3, FOV = 256 × 256 mm, and number of slices = 144.

10

Image preprocessing The rsfMRI data was preprocessed using the Data Processing Assistant for Resting-State fMRI (DPARSF) software package (Chao-Gan and Yu-Feng, 2010). The first five volumes were discarded from each subject to allow for the magnetization equilibrium and saturation effects. Then slice timing correction and head motion correction were performed for the remaining 95 consecutive volumes. During realignment step, we first computed the 3 translational and 3 rotational motion parameters. Then the mean frame-wise displacement (FD) was generated, which reflected the volume-to-volume changes in head position (Power et al., 2012, Power et al., 2013). For the present work, we only investigated cerebral alterations in adolescents with CD, in which all voxels’ time series within the gray matter were extracted for further analysis. Because the gross head motions can significantly affect the accuracy of the functional connectivity evaluation (Power et al., 2012, Ding et al., 2014, Qin et al., 2014), the following steps were adopted and implemented to eliminate the head motion effects: 1) the data with translational or rotational parameters exceeded ± 1 mm or ± 1° were excluded; 2) the data were also discarded when the mean FD was larger than 0.3; 3) the mean FDs were regressed out as nuisance covariates in the statistical analyses. Two-sample t-tests yielded no significant group difference (p = 0.8761) regarding mean FD between the CD group (0.107 ± 0.011) and TD group (0.109 ± 0.009). In addition, the individuals' high resolution structural images were co-registered to the functional data using a linear transformation. They were then segmented into grey matter, white matter and cerebrospinal fluid in MNI space by using "New Segment + DARTEL" in DPARSF. The DARTEL procedure (Ashburner, 2007) was applied to generate a study-specific template. After spatial normalization, the voxel size was 3 × 3 × 3 mm3, and then several sources of nuisance covariate including six head motion parameters, global signal of the whole brain,

11 averaged signals from the cerebrospinal fluid and white matter were regressed out from the data (Guo et al., 2013). Finally, the functional images were first detrended to remove the linear trend, and then temporally band-pass filtered in a frequency range of 0.01~0.10 Hz to reduce the effect of low-frequency machine magnetic field drifts and high-frequency respiratory and cardiac noise. No spatial smoothing was performed to avoid introducing of the artificial local spatial correlation (Liu et al., 2014, Liu et al., 2015, Pang et al., 2015).

Reconstruction of rsFCD maps The preprocessed data was then utilized to reconstruct the global FCD (gFCD) and the local FCD (lFCD) maps based on the method proposed by Tomasi and Volkow (Tomasi and Volkow, 2010, 2011). In brief, the Pearson’s correlation analysis was performed to access the strength of functional connectivity between the preprocessed time series of a given voxel and that from all the other voxels. A correlation threshold 0.6 was set as the optimal threshold to calculate the binary rsFCD values (Tomasi and Volkow, 2010). For a given voxel, the gFCD was calculated as the total number of functional connectivity between this specific voxel and each of the other voxels from the whole brain. This procedure was repeated until the operation for all cerebral gray matter voxels from each subject was completed. Meanwhile, the generation of lFCD at voxel
 was very similar with that of gFCD although the operation was restricted within its local cluster. The lFCD was defined as the number of functional connectivity between a given voxel
 and its direct and indirect neighbor voxels (Tomasi and Volkow, 2010). Consequently, the functional connectivity was first computed between the voxel
 and each voxel
 that was directly adjacent to
 . The voxel
 could be added to the lists of neighboring voxels that was functionally connected with voxel
 if and only if the Pearson correlation coefficient was larger than 0.6. Then, the functional connectivity between
 and each voxel
 that was direct

12 neighbors with
 but not with
 was also computed. If the Pearson correlation coefficient was larger than 0.6 as well, the voxel
 can also be counted as a neighbor voxel that was functionally connected with
 . This “growing” algorithm was developed in Interactive Data Language (IDL) (Tomasi and Volkow, 2010). The calculation procedure was repeated in an iterative manner for the next voxel that was adjacent to the voxels belong to the neighbors list until no further new voxels could be identified in the list of neighbors of voxel
 . Further, we also calculated the voxel signal-to-noise ratio (SNR, the voxel-wise mean of the signal over time divided by the standard deviation of the time series of data) of each subjects. Then all the FCD calculations were performed again, which was restricted to voxels within the grey matter region with all of the SNR > 50 voxels in order to minimize unwanted effects from susceptibility-related signalloss artifacts (Tomasi et al., 2014).

Quantification of short- and long-range FCD According to the neighboring relationship among voxels, the short-range FCD was considered to be equal to the lFCD which predominantly represented the functional connectivity of the local cluster inside the neighborhood. In contrast, the long-range FCD was defined as: gFCD-lFCD, which only considered the voxels outside the neighborhood (Tomasi and Volkow, 2012a, b). The grand mean scaling of short- and long-range FCD maps were generated by dividing the FCD value of each voxel by the mean value of FCDs from all brain voxels so that all rsFCD maps can be averaged and compared across all subjects. Finally, those normalized short- and long-range FCDs were spatially smoothed using an 8 × 8 × 8 mm full-width at half-maximum (FWHM) Gaussian kernel prior to group-level analyses.

Statistical analysis For group-level analyses, we adopted the Statistical Parametric Mapping software (SPM8,

13 http://www.fil.ion.ucl.ac.uk/spm/software/spm8/) in this study. Two-sample t-tests were performed to evaluate the between-group FCD differences for each threshold, controlling for the effects of age and mean FD. Data were corrected using Monte Carlo simulation, resulting in a corrected threshold of p < 0.05 (AlphaSim program based on the REST toolbox (http://www.restfmri.net/forum/REST_V1.8)), in which parameters used were: single voxel p = 0.005, 1000 simulations, FWHMx = 16.666 mm, FWHMy = 15.502 mm, and FWHMz = 15.964 mm for short-range FCDs; single voxel p = 0.05, 1000 simulations, FWHMx = 14.396 mm, FWHMy = 13.230 mm, and FWHMz = 14.029 mm for long-range FCDs; cluster connection radius r = 5 mm and an AAL mask without the cerebellum with the resolution of 3 × 3 × 3 mm3. Further, the mean values of short- and long-range FCDs in brain regions with significant difference between the two groups were extracted from each subject. The relationship between the extracted FCD values of CD group and the BIS-11 scores was then generated by using the Pearson’s correlation analysis, controlling for age and mean FD.

Results Demographic and clinical features Demographic and clinical characteristics of the CD and TD group were summarized in Table 1. No significant differences between the two groups were identified in terms of age and education level. Compared to TD subjects, CD patients showed significantly higher BIS-11 scores including the BIS Total, the BIS Attentional, the BIS Motor, and the BIS Non-planning scores.

Spatial distributions of short- and long-range FCDs It was observed from Figs. 1 and 2 that both CD and TD groups exhibited very similar FCD spatial distributions. In particular, brain regions located in the bilateral fusiform gyrus, the

14 occipital gyrus, the lingual gyrus, the calcarine fissure, the cuneus, the precuneus, and the superior frontal gyrus showed the densest distribution of short-range FCD (Figs. 1A&1B). In addition, Figs. 2A and 2B displayed the averaged distribution of the long-range FCD for the CD and TD group, respectively, in which the brain regions with high long-range FCD were preferentially located in the bilateral posterior cingulate cortex/precuneus, the superior and the inferior parietal lobules, the temporal cortex, the precentral, and the dorsolateral prefrontal cortex. Interestingly, those brain regions with high FCD were considered as brain hubs, which showed good agreement with the brain activation patterns revealed by previous results (Tomasi and Volkow, 2010, Ding et al., 2014).

Group differences in the short- and long-range FCDs Compared to healthy controls, CD patients showed increased short-range FCD in the bilateral PCC and the bilateral PCUN whereas decreased short-range FCD in the bilateral calcarine fissure and the right cuneus (Figs. 1C&1D, Table 2, p < 0.05, AlphaSim corrected). Meanwhile, relative to TD subjects, CD patients exhibited higher long-range FCD in the right fusiform gyrus, the left MCC and the right PCUN whereas lower long-range FCD in the bilateral lingual gyrus, the bilateral middle occipital gyrus, the right calcarine fissure, and the left superior occipital gyrus (Figs. 2C&2D, Table 3, p < 0.05, AlphaSim corrected). Those results were visualized by using BrainNet Viewer (Xia et al., 2013) (http://www.nitrc.org/projects/bnv/). Moreover, the group comparison according to measures of short- and long-range FCDs within the SNR (SNR > 50) masks was also performed and the results were provided in Figs. 4&5. It was observed from Figs. 4 and 5 that the main brain regions that showed significant differences between the two groups were also located in the calcarine fissure, the cuneus, the fusiform gyrus, the MCC, the PCUN, the lingual gyrus, the middle occipital gyrus and the superior occipital gyrus. As such,

15 the analysis results based on measures of short- and long-range FCDs within the SNR masks were consistent with that generated from the whole-brain FCDs.

Correlations between short- and long-range FCD values with BIS-11 score Pearson’s correlation analyses were performed between the significantly altered brain regions and BIS-11 score, controlling for the nuisance variance of age and mean FD after removing potential outliers (Schwarzkopf et al., 2012). According to the measure of short-range FCD, seven brain regions (bilateral PCC, bilateral PCUN, bilateral calcarine fissure, and the right cuneus) were revealed to be significantly altered in the CD group, while for the long-range FCD case, nine altered brain areas (right fusiform gyrus, the left MCC, the right PCUN, the bilateral lingual gyrus, the bilateral middle occipital gyrus, the right calcarine fissure, and the left superior occipital gyrus) were identified for CD patients. We further extracted the FCD values of those aberrant sixteen regions to calculate the correlations between them with the BIS Total score, BIS Motor score and BIS Non-planning score, respectively. The left PCC with increased short-range FCD were found to be significantly and positively associated with BIS Total scores (p < 0.05) for the CD group as plotted in Fig. 3A. In addition, as shown in Figs. 3B~3E, four brain regions with increased short-range FCD in the CD group were shown to be significantly and positively correlated with BIS Motor scores (p < 0.05), which included the bilateral PCC, the bilateral PCUN, and the key regions of DMN. Likewise, the left MCC with increased long-range FCD was identified to be significantly and positively correlated with BIS Motor scores for the CD group (Fig. 3F). In contrast, no significant correlations were revealed between regions with altered FCDs and BIS Non-planning scores in the patient group.

Discussion To the best of our knowledge, this is the first work that employs the FCD mapping to investigate

16 the cortical changes in brain functional connectivity in adolescents with pure CD at rest. Our preliminary results indicated that the short-range FCD that is associated with the strength of the intraregional functional connectivity, showed to be significantly altered for the CD group in brain regions including the PCC, the PCUN, the calcarine fissure and the cuneus as compared to that from the TD group. Meanwhile, the long-range FCD, which reflects the strength of interregional functional connectivity, was found to be changed in the fusiform gyrus, the MCC, the PCUN, the lingual gyrus, the middle occipital gyrus, the calcarine fissure, and the superior occipital gyrus for CD subjects. The identified brain regions with abnormal rsFCD were mainly involved in DMN and visual-related nervous systems (McCarthy et al., 1999, Rubia et al., 2009b, Said et al., 2011, Štillová et al., 2013), suggesting that the CD patients have impairments in cognitive, emotional and visual perception functions. In particular, the FCD values of altered regions in the CD group, including the PCC, the PCUN, and the MCC, showed significant correlations with BIS-11 scores. The identified brain regions with altered FCD implied an abnormality of total number of functional connections between those regions and all other voxels across the entire brain, which revealed an aberrant information processing in those regions. Thus, the present study will pave a new path for better understanding the pathophysiological mechanism underlying CD by exploring the regional abnormalities of brain, in terms of both increased and decreased short- and long-range FCDs.

Altered short-range FCD in patients with CD In this study, the PCC and the PCUN of the CD patients were found to have increased number of short-range connections compared with healthy controls. It is widely recognized that the PCUN and the PCC are the essential regions of the DMN, which are engaged in the self-referential mental thoughts when a person is free from a task (Fransson and Marrelec, 2008). In particular,

17 the PCC is linked to neural cognitive functions such as working memory, attention, visuospatial cognitions (Olson et al., 1993, Sutherland and Hoesing, 1993), and emotional processing (Maddock et al., 2003). Meanwhile, the PCUN is implicated in a wide range of cognitive processes which include self-related processing (Lou et al., 2004), awareness and consciousness (Vogt and Laureys, 2005), episodic memory (Lundstrom et al., 2005, Dörfel et al., 2009), and visuospatial imagery (Kawashima et al., 1995, Wenderoth et al., 2005). Previous task-based fMRI studies suggested that CD patients showed increased brain activation in the PCC and PCUN during a reward continuous performance task relative to healthy controls (Rubia et al., 2009b). Our findings on increased short-range FCD in the PCC and PCUN indicate that the hyperactivity in these two regions is a pathological mechanism of CD from a new perspective of the number of functional connectivity. More importantly, the PCC only showed increased shortrange FCD while the PCUN showed both increased short-range and long-range FCDs in CD patients relative to that of the TD subjects, suggesting the differences between the functional components of the PCC and PCUN between the CD and TD groups (Stevens et al., 2009, Thomas Yeo et al., 2011, Yang et al., 2014). Regardless of the structural proximity of these two regions, previous studies have revealed the differences between CD patients and healthy controls regarding the PCC and PCUN-based networks (Margulies et al., 2009, Zuo et al., 2010, Zhang and Chiang-shan, 2012). Our findings using FCD mapping provided us additional evidence to show the difference in functional roles of the PCUN and the PCC between the two groups. In addition, the calcarine fissure and the cuneus in patients with CD showed weaker shortrange FCD as compared with that of healthy controls. The calcarine fissure and cuneus gyrus are widely recognized to be involved in visual perception and face memory (Štillová et al., 2013). The decreased short-range FCD in calcarine fissure and cuneus identified by the present work

18 was consistent with our previous findings that lower amplitude of low-frequency fluctuations was identified in cuneus for the CD group. Both the present and previous neural features identified implied decreased spontaneous neuronal activities with respect to visual processing at resting state (Zhou et al., 2015b).

Altered long-range FCD in patients with CD Patients with CD were identified to have higher long-range FCD than healthy controls in the brain regions such as the fusiform gyrus, the MCC and the PCUN. The fusiform gyrus is recognized to play a pivotal role in facial identity processing and facial expression perception (Said et al., 2011). Previous tasked-based fMRI studies in CD reported compound results of the brain activation in the fusiform gyrus (Deeley et al., 2006, Qiao et al., 2012, Fairchild et al., 2014), which might be attributed to the difference in the cognitive load or difficulty among different tasks. To the best our knowledge, this study is the first to investigate the FCD changes in adolescents with CD at resting state, which can effectively exhibit baseline functions relative to task-related activities. Importantly, in relation to the healthy controls, several brain regions were identified for the CD patients, which showed reduced number of long-range connections primarily in the visual areas including lingual gyrus, middle occipital gyrus, calcarine fissure, and superior occipital gyrus. It is well-known that the calcarine fissure plays an important role in visual processing. Additionally, the lingual gyrus is implicated in visual processing (McCarthy et al., 1999), logical reasoning (Takeuchi et al., 2013), and visual memory encoding (Roland and Gulyás, 1995). Recently, a task-based study showed that brain activation in lingual gyrus was correlated inversely with risk-taking in CD patients (Dalwani et al., 2014). Another work reported that a significantly negative relationship between the severity of hyperactive/impulsive symptoms and

19 the reduction in gray matter volume in the bilateral occipital cortex was identified for CD patients (Huebner et al., 2008). More recently, Rubia et al. also demonstrated that CD patients showed decreased activation in the occipital cluster compared with healthy controls (Rubia et al., 2009c). Altered long-range FCD could implicate the weak functional connectivity during resting state, suggesting that CD patients might need more reserve for the demands of tasks involving visual processing and memory. Our findings on the hypoconnectivity of the visual networks regions may also reflect the insufficient top-down processing in visual and memory functions for the CD group.

Impulsivity is associated with hyperconnectivity in DMN Our finding indicated that a positive relationship between the BIS Total score and the short-range FCD of the left PCC was identified. In addition, the short-range FCD values in the bilateral PCC and the PCUN exhibited positive relationships with the BIS Motor score in the CD group. Interestingly, the BIS Motor score was significantly and positively correlated with increased long-range FCD in the left MCC for the CD group. Considering the positive relationships between short- and long-range FCD values and BIS-11 scores, our results implied that a patient with CD exhibited higher impulsivity, who needs more functional connections to satisfy the requirements of efficient information processing. Since the PCC and the PCUN are the central nodes of the DMN, our results also implied that the hyperconnectivity in DMN is closely related to the impulsivity in CD patients, which may serve as the neural mechanisms underlying CD.

Limitations Several limitations should be mentioned for the present study. First of all, a relatively weak correction strategy was used since the sample size of CD adolescents in this study limited the statistical power of our FCD analysis. Second, the duration or severity of CD symptoms and

20 other personality traits associated with CD including the callous-unemotional traits were not inspected for the patients. Consequently, large sample size is required to further confirm the present findings. More specifically, work should be guaranteed to inspect the relationship between the brain functional connectivity abnormalities and the symptoms or some traits in CD. Finally, we caution against overgeneralization of our results. Evidence has shown that many adolescents suffered from CD also exhibit comorbid diagnoses (i.e., ODD and ADHD). Therefore, we cannot determine whether our findings can be extended to those affected by more comorbid conditions. For this reason, to compare our CD group to a group of male adolescents with comorbid symptoms should be desirable for the future work.

Conclusions In summary, we employed an unbiased voxel-based analysis method to investigate the short- and long-range FCDs in patients with pure CD. The fusiform gyrus and the key hubs of the DMN which are associated with BIS-11 scores predominately showed increased powerful rsFCD in the CD group. More interestingly, the posterior brain regions which dominated in the occipital cortex exhibited decreased rsFCD for CD patients. The rsFCD alterations in patients with CD occurred in widely distributed brain regions known to be involved in cognition, emotion and visual perception functions. The abnormalities may facilitate understanding of the neural mechanisms in the disease.

Acknowledgments This study was supported by MYRG2014-00093-FHS and MYRG 2015-00036-FHS grants from the University of Macau in Macau, and FDCT 026/2014/A1 and FDCT 025/2015/A1 grants from Macao government and the National Natural Science Foundation of China (NSFC, 81571341

21 and 81371500).

22

Tables Table 1. Demographic features and clinical data of CD patients and TD subjects. CD (n = 18)

TD (n = 18)

t-value

p-value

16.1 ± 0.54

15.9 ± 0.32

1.124

0.27

Education (yrs)

9.4 ± 2.0

9.2 ± 1.9

0.7

0.47

Mother’s education (yrs)

8.2 ± 4.1

10.1 ± 3.5

-1.6

0.13

Father’s education (yrs)

8.8 ± 2.6

10.4 ± 2.2

-1.9

0.07

Total score

76.06 ± 8.26

64.89 ± 11.14

3.417

< 0.001

Attention score

18.39 ± 2.06

17.83 ± 3.67

0.560

0.58

Motor score

26.89 ± 4.76

20.61 ± 4.16

4.211

< 0.001

Non-planning score

30.78 ± 4.43

26.44 ± 5.24

2.681

0.01

Age (yrs)

BIS-11

Values are presented as mean ± SD. The p value was obtained by two-sample t-test. CD, conduct disorder; TD, typically developing; SD, standard deviation; BIS-11, Barratt Impulsivity Scale11; yrs, years.

23 Table 2. Statistical significance of short-range FCD differences between CD and TDs. Peak MNI, mm

Cluster size Brain regions

BA

Peak T value (voxels)

x

y

z

Short-range FCD increased regions PCC_R

30

71

+3.27

3

-45

21

PCUN_L

23

70

+3.53

-3

-54

21

PCC_L

26

54

+3.24

-3

-42

21

PCUN_R

30

37

+3.37

4

-45

18

Short-range FCD decreased regions CAL_R

17

86

-3.76

9

-75

15

CUN_R

18

50

-3.51

6

-78

21

CAL_L

17

38

-3.17

-4

-69

12

R, right; L, left; BA, Brodmann’s area; MNI, Montreal Neurological Institude. The threshold was set p < 0.05 using Alphasim corrected. PCC, posterior cingulate cortex; PCUN, precuneus; CAL, calcarine fissure; CUN, cuneus.

24 Table 3. Statistical significance of long-range FCD differences between CD and TDs. Peak MNI, mm

Cluster size Brain regions

BA

Peak T value (voxels)

x

y

z

Long-range FCD increased regions FFG_R

20

160

+2.07

39

-18 -27

MCC_L

23

140

+2.71

-3

-45

33

PCUN_R

30

119

+1.95

4

-45

18

Long-range FCD decreased regions LING_L

17

234

-2.26

-3

-69

6

MOG_R

18

210

-1.95

38

-90

9

MOG_L

18

202

-2.62

-18

-90

12

LING_R

18

196

-3.09

18

-63

-3

CAL_R

18

179

-2.92

9

-75

18

SOG_L

18

142

-3.06

-15

-90

21

R, right; L, left; BA, Brodmann’s area; MNI, Montreal Neurological Institude. The threshold was set p < 0.05 using Alphasim corrected. FFG, fusiform gyrus; MCC, median cingulate cortex; PCUN, precuneus; LING, lingual gyrus; MOG, middle occipital gyrus; CAL, calcarine fissure; SOG, superior occipital gyrus.

25

Figure legends Fig. 1. Spatial distribution of short-range FCD in the brain in patients with CD (A) and TD individuals (B) and statistical differences between the two groups (C)-(D). Patients with CD showed (C) increased short-range FCD in the bilateral posterior cingulate cortex (PCC) and the bilateral precuneus (PCUN) and (D) decreased short-range FCD in the bilateral calcarine fissure (CAL) and the right cuneus (CUN) as compared with TD individuals (p < 0.05, AlphaSim corrected). Those images are visualized in BrainNet Viewer. More details about those regions are described in Table 2. FCD, functional connectivity density; CD, conduct disorder; TD, typically developing; L, left; R, right. Fig. 2. Spatial distribution of long-range FCD in the brain in patients with CD (A) and TD individuals (B) and statistical differences between the two groups (C)-(D). Patients with CD showed (C) increased long-range FCD mainly in the right fusiform gyrus (FFG), the left middle cingulate cortex (MCC) and the right precuneus (PCUN) and (D) decreased long-range FCD in the bilateral lingual gyrus (LING), the bilateral middle occipital gyrus (MOG), the right calcarine fissure (CAL) and the left superior occipital gyrus (SOG) as compared with TD individuals (p < 0.05, AlphaSim corrected). Those images are visualized in BrainNet Viewer. More details about those regions are described in Table 3. FCD, functional connectivity density; CD, conduct disorder; TD, typically developing; L, left; R, right. Fig. 3. Positive relationships between clinical data and significantly altered regions in short- and long-range FCD in patients with CD (p < 0.05). Pearson’s correlation analysis was performed over the data after removing the outliers which marked by white circles. The short- and longrange FCD values were extracted from the significant clusters after the age and mean FD were regressed out. (A) represents that the BIS Total score was positively correlated with abnormal

26 short-range FCD in the left PCC. (B)-(E) denote that the BIS Motor score was positively associated with short-range FCD in bilateral PCC and bilateral PCUN. (F) indicates that the BIS Motor score was positively correlated with long-range FCD in the left MCC. More details about those regions are described in Table 2 and 3. FCD, functional connectivity density; CD, conduct disorder; BIS, Barratt Impulsivity Scale; PCC, posterior cingulate cortex; PCUN, precuneus; MCC, middle cingulate cortex; L, left; R, right. Fig. 4. Statistical differences of short-range FCD between the patients with CD (A) and TD individuals (B). Patients with CD showed (A) increased short-range FCD in the right fusiform gyrus (FFG), the right parahippocampus and the right thalamus and (B) decreased short-range FCD in the bilateral calcarine fissure (CAL) and the bilateral cuneus (CUN) as compared with TD individuals (p < 0.05, AlphaSim corrected). Those images are visualized in BrainNet Viewer. FCD, functional connectivity density; CD, conduct disorder; TD, typically developing; L, left; R, right. Fig. 5. Statistical differences of long-range FCD between the patients with CD (A) and TD individuals (B). Patients with CD showed (A) increased long-range FCD mainly in the right fusiform gyrus (FFG), the left middle cingulate cortex (MCC) and the right precuneus (PCUN) and (B) decreased long-range FCD in the bilateral lingual gyrus (LING), the bilateral cuneus (CUN), the bilateral middle occipital gyrus (MOG), the bilateral calcarine fissure (CAL) and the left superior occipital gyrus (SOG) as compared with TD individuals (p < 0.05, AlphaSim corrected). Those images are visualized in BrainNet Viewer. FCD, functional connectivity density; CD, conduct disorder; TD, typically developing; L, left; R, right.

27

References Ashburner J (2007) A fast diffeomorphic image registration algorithm. Neuroimage 38:95-113. Association AP (2013) Diagnostic and statistical manual of mental disorders, (DSM-5®): American Psychiatric Pub. Association AP, Association AP (1994) Diagnostic and statistical manual of mental disorders (DSM). Washington, DC: American psychiatric association 143-147. Baker K (2013) Conduct disorders in children and adolescents. Paediatrics and Child Health 23:24-29. Bao A-M, Swaab DF (2010) Sex differences in the brain, behavior, and neuropsychiatric disorders. The Neuroscientist 16:550-565. Beckmann CF, DeLuca M, Devlin JT, Smith SM (2005) Investigations into resting-state connectivity using independent component analysis. Philosophical Transactions of the Royal Society of London B: Biological Sciences 360:1001-1013. Berkout OV, Young JN, Gross AM (2011) Mean girls and bad boys: Recent research on gender differences in conduct disorder. Aggression and Violent Behavior 16:503-511. Biswal BB, Yetkin FZ, Haughton VM, Hyde JS (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Canino G, Polanczyk G, Bauermeister JJ, Rohde LA, Frick PJ (2010) Does the prevalence of CD and ODD vary across cultures? Social psychiatry and psychiatric epidemiology 45:695704. Chao-Gan Y, Yu-Feng Z (2010) DPARSF: a MATLAB toolbox for “pipeline” data analysis of resting-state fMRI. Frontiers in systems neuroscience 4. Cole DM, Smith SM, Beckmann CF (2010) Advances and pitfalls in the analysis and interpretation of resting-state FMRI data. Frontiers in systems neuroscience 4. Colman I, Murray J, Abbott RA, Maughan B, Kuh D, Croudace TJ, Jones PB (2009) Outcomes of conduct problems in adolescence: 40 year follow-up of national cohort. BMJ 338. Dörfel D, Werner A, Schaefer M, Von Kummer R, Karl A (2009) Distinct brain networks in recognition memory share a defined region in the precuneus. European Journal of Neuroscience 30:1947-1959. Dalwani MS, Tregellas JR, Andrews-Hanna JR, Mikulich-Gilbertson SK, Raymond KM, Banich MT, Crowley TJ, Sakai JT (2014) Default mode network activity in male adolescents with conduct and substance use disorder. Drug and Alcohol Dependence 134:242-250. Deeley Q, Daly E, Surguladze S, Tunstall N, Mezey G, Beer D, Ambikapathy A, Robertson D, Giampietro V, Brammer MJ (2006) Facial emotion processing in criminal psychopathy Preliminary functional magnetic resonance imaging study. The British Journal of Psychiatry 189:533-539. Ding J, An D, Liao W, Wu G, Xu Q, Zhou D, Chen H (2014) Abnormal functional connectivity density in psychogenic non-epileptic seizures. Epilepsy research 108:1184-1194. Fairchild G, Hagan CC, Passamonti L, Walsh ND, Goodyer IM, Calder AJ (2014) Atypical neural responses during face processing in female adolescents with conduct disorder. Journal of the American Academy of Child & Adolescent Psychiatry 53:677-687. e675. Finger EC, Marsh AA, Blair KS, Reid ME, Sims C, Ng P, Pine DS, Blair RJR (2011) Disrupted Reinforcement Signaling in the Orbitofrontal Cortex and Caudate in Youths With Conduct Disorder or Oppositional Defiant Disorder and a High Level of Psychopathic Traits. American Journal of Psychiatry 168:152-162.

28 Fransson P, Marrelec G (2008) The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis. Neuroimage 42:1178-1184. Guo W, Liu F, Xue Z, Gao K, Liu Z, Xiao C, Chen H, Zhao J (2013) Abnormal resting-state cerebellar–cerebral functional connectivity in treatment-resistant depression and treatment sensitive depression. Progress in Neuro-Psychopharmacology and Biological Psychiatry 44:51-57. Huebner T, Vloet TD, Marx I, Konrad K, Fink GR, Herpertz SC, Herpertz-Dahlmann B (2008) Morphometric brain abnormalities in boys with conduct disorder. Journal of the American Academy of Child & Adolescent Psychiatry 47:540-547. Jones AP, Laurens KR, Herba CM, Barker GJ, Viding E (2009) Amygdala hypoactivity to fearful faces in boys with conduct problems and callous-unemotional traits. American Journal of Psychiatry 166:95-102. Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, Williamson D, Ryan N (1997) Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): initial reliability and validity data. Journal of the American Academy of Child & Adolescent Psychiatry 36:980-988. Kawashima R, Roland PE, O'Sullivan BT (1995) Functional anatomy of reaching and visuomotor learning: a positron emission tomography study. Cerebral Cortex 5:111-122. Liu F, Guo W, Fouche J-P, Wang Y, Wang W, Ding J, Zeng L, Qiu C, Gong Q, Zhang W (2015) Multivariate classification of social anxiety disorder using whole brain functional connectivity. Brain Structure and Function 220:101-115. Liu F, Xie B, Wang Y, Guo W, Fouche J-P, Long Z, Wang W, Chen H, Li M, Duan X (2014) Characterization of post-traumatic stress disorder using resting-state fMRI with a multilevel parametric classification approach. Brain topography 28:221-237. Lou HC, Luber B, Crupain M, Keenan JP, Nowak M, Kjaer TW, Sackeim HA, Lisanby SH (2004) Parietal cortex and representation of the mental self. P Natl Acad Sci USA 101:6827-6832. Lu F-M, Zhou J-S, Zhang J, Xiang Y-T, Zhang J, Liu Q, Wang X-P, Yuan Z (2015) Functional Connectivity Estimated from Resting-State fMRI Reveals Selective Alterations in Male Adolescents with Pure Conduct Disorder. PloS one 10. Lundstrom BN, Ingvar M, Petersson KM (2005) The role of precuneus and left inferior frontal cortex during source memory episodic retrieval. Neuroimage 27:824-834. Maddock RJ, Garrett AS, Buonocore MH (2003) Posterior cingulate cortex activation by emotional words: fMRI evidence from a valence decision task. Human Brain Mapping 18:30-41. Margulies DS, Vincent JL, Kelly C, Lohmann G, Uddin LQ, Biswal BB, Villringer A, Castellanos FX, Milham MP, Petrides M (2009) Precuneus shares intrinsic functional architecture in humans and monkeys. Proceedings of the National Academy of Sciences 106:20069-20074. Maughan B, Rowe R, Messer J, Goodman R, Meltzer H (2004) Conduct disorder and oppositional defiant disorder in a national sample: developmental epidemiology. Journal of child psychology and psychiatry 45:609-621. McCarthy G, Puce A, Belger A, Allison T (1999) Electrophysiological studies of human face perception. II: Response properties of face-specific potentials generated in occipitotemporal cortex. Cerebral Cortex 9:431-444.

29 McKeown MJ, Jung T-P, Makeig S, Brown G, Kindermann SS, Lee T-W, Sejnowski TJ (1998) Spatially independent activity patterns in functional MRI data during the Stroop colornaming task. Proceedings of the National Academy of Sciences 95:803-810. Olson C, Musil S, Goldberg M (1993) Posterior Cingulate Cortex and Visuospatial Cognition: Properties of Single Neurons in the Behaving Monkey. In: Neurobiology of Cingulate Cortex and Limbic Thalamus (Vogt, B. and Gabriel, M., eds), pp 366-380: Birkhäuser Boston. Olsson M (2009) DSM diagnosis of conduct disorder (CD)—a review. Nordic Journal of Psychiatry 63:102-112. Pang Y, Cui Q, Duan X, Chen H, Zeng L, Zhang Z, Lu G, Chen H (2015) Extraversion modulates functional connectivity hubs of resting‐state brain networks. Journal of neuropsychology. Patton JH, Stanford MS (1995) Factor structure of the Barratt impulsiveness scale. Journal of clinical psychology 51:768-774. Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE (2012) Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59:2142-2154. Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE (2013) Steps toward optimizing motion artifact removal in functional connectivity MRI; a reply to Carp. Neuroimage 76:439-441. Qiao Y, Xie B, Du X (2012) Abnormal response to emotional stimulus in male adolescents with violent behavior in China. European child & adolescent psychiatry 21:193-198. Qin W, Xuan Y, Liu Y, Jiang T, Yu C (2014) Functional connectivity density in congenitally and late blind subjects. Cerebral Cortex bhu051. Roland P, Gulyás B (1995) Visual memory, visual imagery, and visual recognition of large field patterns by the human brain: functional anatomy by positron emission tomography. Cerebral Cortex 5:79-93. Rubia K, Halari R, Cubillo A, Mohammad AM, Scott S, Brammer M (2010) Disorder-specific inferior prefrontal hypofunction in boys with pure attention-deficit/hyperactivity disorder compared to boys with pure conduct disorder during cognitive flexibility. Human Brain Mapping 31:1823-1833. Rubia K, Halari R, Smith AB, Mohammad M, Scott S, Brammer MJ (2009a) Shared and disorder-specific prefrontal abnormalities in boys with pure attentiondeficit/hyperactivity disorder compared to boys with pure CD during interference inhibition and attention allocation. Journal of Child Psychology and Psychiatry and Allied Disciplines 50:669-678. Rubia K, Smith AB, Halari R, Matsukura F, Mohammad M, Taylor E, Brammer MJ (2009b) Disorder-specific dissociation of orbitofrontal dysfunction in boys with pure conduct disorder during reward and ventrolateral prefrontal dysfunction in boys with pure ADHD during sustained attention. The American Journal of Psychiatry 166:83-94. Rubia K, Smith AB, Halari R, Matsukura F, Mohammad M, Taylor E, Brammer MJ (2009c) Disorder-specific dissociation of orbitofrontal dysfunction in boys with pure conduct disorder during reward and ventrolateral prefrontal dysfunction in boys with pure ADHD during sustained attention. American Journal of Psychiatry 166:83-94. Said CP, Haxby JV, Todorov A (2011) Brain systems for assessing the affective value of faces. Philosophical Transactions of the Royal Society B: Biological Sciences 366:1660-1670.

30 Schwarzkopf DS, de Haas B, Rees G (2012) Better ways to improve standards in brain-behavior correlation analysis. Frontiers in Human Neuroscience 6. Sebastian CL, McCrory EP, Cecil CM, et al. (2012) Neural responses to affective and cognitive theory of mind in children with conduct problems and varying levels of callousunemotional traits. Archives of General Psychiatry 69:814-822. Shanee N, Apter A, Weizman A (1997) Psychometric properties of the K-SADS-PL in an Israeli adolescent clinical population. Israel Journal of Psychiatry and Related Sciences. Stevens MC, Haney-Caron E (2012) Comparison of brain volume abnormalities between ADHD and conduct disorder in adolescence. Journal of Psychiatry and Neuroscience 37:389-398. Stevens MC, Pearlson GD, Calhoun VD (2009) Changes in the interaction of resting‐state neural networks from adolescence to adulthood. Human brain mapping 30:2356-2366. Štillová K, Jurák P, Chládek J, Halámek J, Telecká S, Rektor I (2013) The posterior medial cortex is involved in visual but not in verbal memory encoding processing: an intracerebral recording study. Journal of Neural Transmission 120:391-397. Sutherland R, Hoesing J (1993) Posterior Cingulate Cortex and Spatial Memory: A Microlimnology Analysis. In: Neurobiology of Cingulate Cortex and Limbic Thalamus (Vogt, B. and Gabriel, M., eds), pp 461-477: Birkhäuser Boston. Takeuchi H, Taki Y, Nouchi R, Sekiguchi A, Hashizume H, Sassa Y, Kotozaki Y, Miyauchi CM, Yokoyama R, Iizuka K (2013) Resting state functional connectivity associated with trait emotional intelligence. Neuroimage 83:318-328. Thomas Yeo BT, Krienen FM, Sepulcre J, Sabuncu MR, Lashkari D, Hollinshead M, Roffman JL, Smoller JW, Zöllei L, Polimeni JR, Fischl B, Liu H, Buckner RL (2011) The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology 106:1125-1165. Tiet QQ, Wasserman GA, Loeber R, McReynolds LS, Miller LS (2001) Developmental and sex differences in types of conduct problems. Journal of Child and Family Studies 10:181197. Tomasi D, Volkow ND (2010) Functional connectivity density mapping. Proceedings of the National Academy of Sciences 107:9885-9890. Tomasi D, Volkow ND (2011) Functional connectivity hubs in the human brain. Neuroimage 57:908-917. Tomasi D, Volkow ND (2012a) Abnormal functional connectivity in children with attentiondeficit/hyperactivity disorder. Biological psychiatry 71:443-450. Tomasi D, Volkow ND (2012b) Aging and functional brain networks. Molecular psychiatry 17:549-558. Tomasi D, Wang R, Wang G-J, Volkow ND (2014) Functional Connectivity and Brain Activation: A Synergistic Approach. Cerebral Cortex 24:2619-2629. Uddin LQ, Clare Kelly AM, Biswal BB, Xavier Castellanos F, Milham MP (2009) Functional connectivity of default mode network components: Correlation, anticorrelation, and causality. Human Brain Mapping 30:625-637. van de Ven VG, Formisano E, Prvulovic D, Roeder CH, Linden DEJ (2004) Functional connectivity as revealed by spatial independent component analysis of fMRI measurements during rest. Human Brain Mapping 22:165-178. Vogt BA, Laureys S (2005) Posterior cingulate, precuneal and retrosplenial cortices: cytology and components of the neural network correlates of consciousness. Progress in brain research 150:205-217.

31 Wenderoth N, Debaere F, Sunaert S, Swinnen SP (2005) The role of anterior cingulate cortex and precuneus in the coordination of motor behaviour. European Journal of Neuroscience 22:235-246. Xia M, Wang J, He Y (2013) BrainNet Viewer: a network visualization tool for human brain connectomics. PloS one 8:e68910. Yang Z, Chang C, Xu T, Jiang L, Handwerker DA, Castellanos FX, Milham MP, Bandettini PA, Zuo X-N (2014) Connectivity trajectory across lifespan differentiates the precuneus from the default network. Neuroimage 89:45-56. Zhang S, Chiang-shan RL (2012) Functional connectivity mapping of the human precuneus by resting state fMRI. Neuroimage 59:3548-3562. Zhou J, Chen C, Wang X, Cai W, Zhang S, Qiu C, Wang H, Luo Y, Fazel S (2012) Psychiatric disorders in adolescent boys in detention: a preliminary prevalence and case–control study in two Chinese provinces. Journal of Forensic Psychiatry & Psychology 23:664675. Zhou J, Yao N, Fairchild G, Cao X, Zhang Y, Xiang Y-T, Zhang L, Wang X (2015a) Disrupted default mode network connectivity in male adolescents with conduct disorder. Brain Imaging and Behavior 1-9. Zhou J, Yao N, Fairchild G, Zhang Y, Wang X (2015b) Altered Hemodynamic Activity in Conduct Disorder: A Resting-State fMRI Investigation. PloS one 10. Zuo X-N, Kelly C, Adelstein JS, Klein DF, Castellanos FX, Milham MP (2010) Reliable intrinsic connectivity networks: test–retest evaluation using ICA and dual regression approach. Neuroimage 49:2163-2177.

32

33

34

35

36

37

Highlights

⋅

Resting-state fMRI and FCD approach was combined to explore the voxel-wise functional connectivity changes in CD.

⋅

Increased FCD were found in the DMN regions, the fusiform gyrus, and the middle cingulate cortex (MCC) in CD.

⋅

Reduced FCD changes were mainly in the visual-related regions in the CD patients.

⋅

The regions involved in DMN and the MCC were considered to be significantly correlated with clinical data.

⋅

Altered FCD may be a biomarker for CD.