Aberrant function of the salience network related to maltreatment experiences during thought–action fusion

doi:10.21203/rs.3.rs-2497824/v1

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Aberrant function of the salience network related to maltreatment experiences during thought–action fusion

https://doi.org/10.21203/rs.3.rs-2497824/v1

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published 03 Jan, 2024

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Childhood maltreatment (CM) causes early deviations in cognitive and affective processes, leading to future adaptation failures and psychopathology. Specifically, CM has been linked to cognitive distortions, and recent studies have focused on the impact of CM on the higher level of metacognitive beliefs. However, only a few studies have revealed the neural mechanisms underlying the association between altered metacognition and CM. Therefore, this functional magnetic resonance imaging (fMRI) study investigated the neural correlates of thought–action fusion (TAF) tendency and CM experiences. Overall, 40 young adults (21 men) participated in this study and underwent fMRI during the TAF task as well as psychological evaluation for CM, TAF tendency, anxiety, and depressive symptoms. During the TAF task, they were asked to read negative (Neg) or neutral (Neu) statements about neutral or close people (CP). Notably, significant activations were found in regions such as the bilateral anterior insula, dorsal anterior cingulate cortex (dACC), caudate, thalamus, medial prefrontal cortex, precuneus, and right amygdala in the NegCP > NeuCP contrast. Furthermore, anterior insula and dACC activities were significantly correlated with total scores of CM experiences and TAF. Exaggerated TAF tendency in CM victims was associated with increased response of the anterior insula and dACC, which are two core hubs of the salience network. Our results therefore seem to suggest insights for a better understanding of the neural mechanisms underlying metacognitive beliefs related to CM experiences.

childhood maltreatment

thought–action fusion

metacognition

emotional abuse

anterior insula

dorsal anterior cingulate cortex

Childhood maltreatment (CM), which includes sexual abuse, physical/emotional abuse, and neglect, is widespread and can have negative health consequences. Approximately one in three people reported experiencing maltreatment during their childhood (Hanlon et al., 2020; Kim et al., 2017; Scher et al., 2004). CM experiences are strong risk factors for psychiatric illnesses, such as mood and anxiety disorders (Kessler et al., 2010), and they can negatively affect the course of illness or treatment outcome of depression (Nanni et al., 2012). Additionally, CM could have a significant impact on the neurobiological changes underlying these impairments during development. Briefly, hyperactive response to negative threats have been reported in the relevant literature (Teicher and Samson, 2016). In cases of CM, several studies have reported that the response by the amygdala—an important area for emotion recognition—tends to be exaggerated against negative emotional stimuli (Dannlowski et al., 2013; Lee et al., 2015; Tottenham et al., 2011). The biological changes related to CM experiences could also increase susceptibility to mental illness (Teicher et al., 2022).

Furthermore, cognitive distortions can be influenced by CM experiences (Deguchi et al., 2021). For example, Briere’s self-trauma model reported an association between CM and three types of cognitive biases, such as security, controllability, and internal attribution (Briere, 1996). These cognitive distortions may be incorporated into the child’s cognitive schema, which affects themselves, their environment, and their future (Smucker et al., 1995). In addition, recent studies have started to elucidate the impact of CM on higher levels of metacognitive beliefs, such as negative beliefs about the uncontrollability, and the danger of thoughts (Mansueto et al., 2019). A study by Wells (2009) defines fusion beliefs as a special class of negative metacognitive beliefs (i.e., beliefs about thoughts) related to the potency and importance of negative thoughts, representing the belief that a single thought triggers an external event or that an event may have already occurred (e.g., the thought of a car crash may cause it). This idea was first introduced as likelihood thought–action fusion (TAF). In particular, TAF begins with two assumptions. First, certain thoughts can increase the likelihood of events (likelihood TAF). Second, thoughts can be morally equated with real action (moral TAF) (Rassin et al., 1999). TAF can be found not only in various psychiatric illnesses but also in the general population.

Several studies have suggested that early life experiences can influence the development of TAF. Salkovskis et al. (1999) proposed that early life experiences, such as an incident that appeared to be related to one’s thoughts or extreme rules for duty, could be induced by an inflated sense of responsibility related to TAF. Berman et al. (2013a) used an empirical study design to test this concept; in their study, parenting strategies, such as guilt induction or psychological control, significantly predicted an increased tendency of likelihood TAF (Berman et al., 2013a). Furthermore, emotional abuse as well as physical neglect/abuse were found to be significant predictors of likelihood and moral TAFs, respectively, in self-report questionnaires but not in the in vivo behavioral assessment (Berman et al., 2013b). Taken together, CM experiences during development may contribute to an exaggerated TAF bias.

The present study aimed to validate the underlying neural correlates explaining the relationship between metacognitive beliefs (such as TAF) and CM experiences using fMRI and the TAF induction task. Previous fMRI studies have revealed that salience network (SN) and cortico-striatal-thalamo-cortical (CSTC) elements were involved in the processing of TAF stimuli (Lee et al., 2019; Lee et al., 2020). Furthermore, significant evidence suggested that the victims of CM experience hyperactive reactions to negative emotional threats (Teicher and Samson, 2016). Therefore, the hypotheses of the present study were 1) CM experiences are associated with increased responses to the elements of SN, such as the insula, dorsal anterior cingulate cortex (dACC), and amygdala, during the TAF task, and 2) hyperactivity of SN elements is a potential predictor of an increased TAF tendency.

Participants

In the present study, 40 healthy participants (including 21 men) were recruited via subway advertisements. Two experienced psychiatrists performed psychiatric interviews to rule out pre-existing psychiatric illnesses, such as psychotic/mood/anxiety disorders, mental retardation, or acute medical/neurological disease, or a history of head injury. The mean age of the participants was 28.6 ± 6.4 years. All participants signed written informed consent forms approved by the Institutional Review Board of Kyungpook National University Hospital (2021-04-032).

Psychological measurements

TAF tendency was assessed using the Thought–Action Fusion Scale (TAFS), which is a self-reported scale comprising 19-items (7 for likelihood TAF), on a 5-point scale (Shafran et al., 1996), and it is validated in Korean (Lee and Lee, 2021). The Early Trauma Inventory Self Report-Short form (ETISR-SF) is a 27-item questionnaire that assesses four types of traumatic experiences before the age of 18 years; these include general trauma, physical, emotional, and sexual abuse (Bremner et al., 2007). In the present study, we used the Korean version of ETISR-SF (Jeon et al., 2012). Moreover, the Center for Epidemiologic Studies Depression (CES-D) Scale, which comprises 20 items, was used to assess depressive symptoms in the participants (Radloff, 1977). The validated Korean version of CES-D was used (Cho and Kim, 1993). Anxiety symptoms were assessed using the Generalized Anxiety Disorder-7 (GAD-7) scale validated in the Korean language; this scale comprises seven questions on a 4-point scale (Seo and Park, 2015; Spitzer et al., 2006).

TAF induction task

Based on the previous TAF induction fMRI studies (Lee et al., 2019), we modified the TAF task in this study including additional neutral sentences. The names of two close people (CPs) and two neutral people (NPs) were gathered before the fMRI scan. Further, the participants were asked to imagine the person based on the name (CP or NP) displayed on the screen for 4 seconds (name condition). After the name condition task, the participants were instructed to silently read the displayed negative or neutral sentence for 10 seconds (sentence condition). Notably, the participants were shown negative sentences (Neg), such as “I hope that the person (CP or NP) will soon be injured in a car accident” as target stimuli or neutral sentences (Neu), such as “I hope that the person (CP or NP) will have coffee in the cafeteria” as control stimuli. Following the sentence condition task, all participants were requested to rate their negative feelings on a scale of 1 (very little) to 4 (very much) using an MR convertible button box for 4 seconds (evaluation condition). After the evaluation, a cross was displayed on the center of the screen for 10 seconds (resting condition). The CP, NP, Neg, and Neu conditions were presented in a pseudorandomized order, and the total task paradigm time was 14 minutes and 56 seconds.

Image and statistical analyses

All brain images were obtained using a GE SIGNA architect 3.0 Tesla MR Scanner with a 48-channel head coil (GE Healthcare, Milwaukee, WI). A T2* weighted gradient echo planar imaging pulse sequence with an echo time (TE) of 30 ms, repetition time (TR) of 2000 ms, and a total time-series volume of 448 was used to obtain all functional data. A T1 weighted 3D brain volume image pulse sequence with TE of 3.2 ms, TR of 8.5 ms, a field of view of 25.6 cm, and the iso-voxel of 1 mm was used. A statistical parametric mapping (SPM12; http://www.fil.ion.ucl.ac.uk/spm) was used to reprocess all functional images including slice-time correction and realignment. Anatomical brain tissues were segmented using a computational anatomy toolbox (https://www.nitrc.org/projects/cat). Further, the realigned functional images were smoothened to full-width at half-maximum of 6 mm and normalized to Montreal Neurological Institute space using a computed deformation field map. Moreover, artifact detection tools (https://www.nitrc.org/projects/artifact_detect) were used to detect head movements and significant outlier factors on acquired functional images. In the first-level analysis, the detected movement effects were regressed out. Additionally, we performed a convolution of all individual time-series data via a hemodynamic response function and regression via a TAF task design model. We used NegCP > NeuCP as the main contrast associated with classical TAF (higher negative affective load) in the present study; moreover, we evaluated NegNP > NeuNP contrast as TAF (lower negative affective load). The threshold for brain activation maps was set at p < 0.01, and FDR was corrected for the entire brain region. All beta values were calculated by averaging intensity on ROIs with 5-mm radius spheres on coordinates at the maximum t value. Kendall’s tau coefficient was calculated by performing a partial correlation analysis among the measurements after controlling for depression effects as a covariate factor using the Jeffrey’s Amazing Statistics Program (https://jasp-stats.org).

Psychological characteristics

Table 1 presents the overall psychological characteristics of the participants. According to the baseline mean scores of CES-D and GAD-7, our study participants reported no clinically significant depressive or anxiety symptoms. Moreover, mean ETISR-SF score of the study participants was 4.6, indicating a value between the mean of clinical and nonclinical Korean samples (Jeon et al., 2012; Park, 2018). Supplementary materials showed results of statistical analyses provided in Table 1.

The relationship between CM experiences, psychological measures, and behavioral data

After controlling for depressive symptoms, we found a significant positive relationship between the TAFS likelihood score and the general trauma (τ = 0.252, p = 0.024), and emotional abuse (τ = 0.298, p = 0.008) scores of ETISR-SF.

CM has been reported to be associated with underrated emotional intensity and delayed response during TAF stimuli. Moreover, emotional intensity in the NegCP condition was found to be negatively related to general trauma (τ=−0.337, p = 0.003) and emotional abuse (τ=−0.265, p = 0.018) scores on ETISR-SF. Furthermore, in the NegCP condition, reaction time was positively correlated with physical abuse (τ = 0.376, p < 0.001) and emotional abuse (τ = 0.275, p = 0.014) scores on ETISR-SF. Table 2 contains detailed information.

TAF stimulated brain activity

A significant activity was noted in various brain regions in the NegCP > NeuCP contrast, including the bilateral anterior insular, dACC, caudate, thalamus, medial prefrontal cortex, precuneus, and right amygdala (FDR corrected p < 0.01, Fig. 1). Also, the NegNP > NeuNP contrast was activated in nearly the same regions (FDR corrected p < 0.01). Table 3 shows details of the activated regions.

The relationship between brain activity in SN, CM experiences, and psychological measures

The cortical hubs of SN—the bilateral anterior insula and dACC—were chosen as ROIs (Seeley, 2019). Furthermore, the right amygdala, which is involved in emotion processing and is a component of SN, was chosen based on our hypotheses.

Among these ROIs, bilateral anterior insula and dACC exhibited a significant positive correlation with total ETISR-SF scores in the NegCP > NeuCP contrast (all ps < 0.05, Fig. 2). In addition, emotional abuse was significantly associated with activities in the right anterior insula (τ = 0.304, p = 0.006), left dACC (τ = 0.279, p = 0.012), and right dACC (τ = 0.313, p = 0.005) on ETISR-SF scores. Sexual (τ = 0.255, p = 0.022) and physical (τ = 0.220, p = 0.049) abuses were associated with the right anterior insula activity; general trauma was associated with activities in the left (τ = 0.265, p = 0.018) and right (τ = 0.266, p = 0.017) anterior insula. Notably, only the right anterior insular activity (τ = 0.295, p = 0.008) exhibited a positive relationship with GAD-7 scores. Furthermore, the TAFS likelihood scores were associated with activities in the left (τ = 0.251, p = 0.024) and right anterior insula (τ = 0.260, p = 0.020). Conversely, there was no significant correlation between the right amygdala activity in the NegCP > NeuCP contrast and CM experiences or psychological measures.

There was no significant correlation between TAFS or ETISR-SF and activities in right amygdala, bilateral anterior insula, and dACC in the NegNP > NeuNP contrast.

In the present study, CM experiences—particularly emotional abuse—were found to be associated with increased likelihood TAF. Enhanced responses in the anterior insula and dACC, which are the two core hubs of SN, were associated with CM experiences and TAF tendency during the fMRI TAF task. To the best of our knowledge, this is the first study to demonstrate a link between neural correlates of TAF tendency and CM experiences.

Consistent with the findings of a previous study (Berman et al., 2013b), our study found a significant relationship between emotional abuse and TAF likelihood. Briefly, victims of emotional abuse may believe that certain negative thoughts cause or increase the likelihood of certain negative events. Although the evidence that directly links emotional abuse to TAF is limited, several studies including a meta-analysis have reported that the emotional type of CM has more negative effects on depressive symptoms (Gibb et al., 2007; Spertus et al., 2003; Humphreys et al., 2020). Furthermore, compared with healthy controls, people with depression exhibited higher total score of TAFS (Berle and Starcevic, 2005). Similar to TAF, ruminative cognitive style—a type of metacognition—acts as a moderator in the relationships between emotional abuse and depressive symptoms or emotional dysregulation (Li et al., 2020; Raes and Hermans, 2008). Our findings suggest that emotional abuse, increased metacognitive belief in the likelihood of negative events, and negative affect, such as depression or anxiety, may closely influence each other.

The current fMRI study revealed that the TAF task activated several brain regions, including the anterior insula, dACC, caudate, medial prefrontal cortex, precuneus, and amygdala. Although our previous fMRI study using the TAF task reported activation in the caudate, medial prefrontal cortex, precuneus, and anterior insula (Lee et al., 2019), the current TAF task activated a broader and greater number of brain regions. Our previous TAF task did not include neutral sentences as control stimuli, and the anticipated effects of the name phase were identified as a limitation (Lee et al., 2019). In the present study, the TAF task using neutral sentence stimuli demonstrated increased activity in brain regions. The present study therefore supports the reliability of the TAF task, and the current task was improved in this study with more acceptable contrast.

Furthermore, CM experiences were related to anterior insula activities during the TAF task. Our stimuli elicited interoceptive awareness of negative affect (e.g., serious injury from a car accident), prediction of self and other-related affects, and decision-making in uncertain context (e.g., I wish my mother would); there were pieces of evidence that the anterior insula could play central roles in these functions. First, increased activity in the anterior insular cortex is observed during high physiological arousal and awareness of changes in bodily states (Critchley, 2005). The insula computes an interceptive prediction error, which signals a mismatch between expected and actually experienced bodily arousal to a potentially aversive stimulus (Paulus and Stein, 2006). In the present study, increased anterior insular activation showed significant relationships with CM and anxiety scores, which was consistent with previous observations of increased insular activation in anxiety-prone individuals during emotion processing (Stein et al., 2007). Second, the anterior insula serves as the neural basis of empathy by performing predictive simulations of self- and other-related affects. In a previous study using TAF task, we found that the anterior insula was more active when thinking of a tragic accident happening to a loved one than when thinking of a neutral person (Lee et al., 2019). Third, when the anticipation involves uncertainty, the anterior insula’s response to aversive stimuli could be amplified in anxiety-prone subjects (Simmons et al., 2006). Taken together, we speculate that the hyper-reactivity of the insula may result in incorrect simulation and predictions about adverse events occurring, which in turn lead to maladaptive behaviors, such as avoidance, or drug use (Lin et al., 2016).

Regarding the large-scale network, the anterior insula and dACC were critical SN hubs (Seeley, 2019). Within SN, the anterior insula integrates the responses aroused by sensory, affective, and visceral systems (Menon and Uddin, 2010); moreover, dACC was closely related to response selection and conflict monitoring (Ide et al., 2013). These areas are also involved in determining the salience of stimuli and identifying the homeostatically relevant internal or external response (Menon, 2011). Notably, the SN coherence was increased on threatening stimuli (Carlson et al., 2013), and it was related to higher levels of anxiety (Seeley et al., 2007). In post-traumatic stress disorder, hyperactivity and hyperconnectivity of SN can be linked to increased threat detection (Akiki et al., 2017). Therefore, increased TAF tendency associated with CM experiences could be a result of sensitivity to threatening stimuli mediating SN. In the current study, ETISR-SF scores, particularly emotional abuse and TAFS likelihood, were significantly correlated to components of SN activities in the NegCP > NeuCP contrast, indicating high affective loads, but not in the NegNP > NeuNP contrast, indicating low affective loads. In a previous study, it was found that negative TAF activates more brain regions than positive TAF (Lee et al., 2021). Our findings therefore suggest that CM experiences increase negative affective loads, making TAF stimuli more salient.

TAF is representative of cognitive distortion related to OCD symptoms (Salkovskis, 1985), and previous studies have indicated that patients with OCD have an exaggerated TAF tendency (Berle and Starcevic, 2005; Shafran et al., 1996). However, our findings suggest some differences in the factors that contribute to a higher TAF tendency in patients with OCD versus CM victims. In case of OCD, increased activities and connectivities in the components of CSTC circuits during TAF stimuli exhibited associations with OCD symptoms during TAF stimuli (Lee et al., 2019; Lee et al., 2020). We found that OCD patients seem to attempt to avoid unpleasant affective stimuli elicited by negative TAF, in contrast to hypersensitive reactions to negative stimuli in CM victims. Both hyper-reactivity in patients with CM and avoidance in patients with OCD may have made them susceptible to TAF stimuli. Our past and current results suggest that staying within an acceptable range of emotional responses, e.g., feeling but not being overwhelmed, in order to adequately process the TAF stimuli.

This study has some limitations. First, this was a cross-sectional study, and CM experiences were compiled from participants’ memories. Thus, recall bias may have influenced our results. Second, our sample was relatively small, with only one institution. Therefore, our results cannot be generalized to the entire population. A multicenter study with a prospective design is required to confirm our preliminary results.

The current fMRI study revealed the possible relationships between increased SN activity and TAF tendency related to CM. Our findings therefore could provide valuable clues for aunderstanding of the biological and psychological vulnerability associated with CM experiences.

Acknowledgements

We thanks to Mina Choi and members involved in BMRlab to support our experiments.

Author contributions

Conception and study design (S.W.L., S.L., Y.C., S.J.L); data acquisition and design statistical analysis (S.W.L., S.L., Y.J.K., Y.C., S.J.L); recruitment (S.W.L., S.J.L); data collection (S.L., Y.J.K); interpretation of results (all authors); drafting the manuscript and revision of subsequent drafts (all authors)

Funding This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2021R1F1A1049460 and 2021R1A2C2004720).

This work was also supported by the basic research program through the Korean Brain Research Institute, funded by the Ministry of Science and Information Communications Technology (ICT) (22-BR-03-01)

Data Availability The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflict of interest The authors declare that there was no potential conflict of interest.

Ethical approval The present study was performed in agreement with the Declaration of Helsinki and its further amendments. The study is approved by the Institutional Review Board of Kyungpook National University Hospital (2018–04-029)

Informed consent Informed consent was obtained from all individual participant included in the study

Akiki, T. J., Averill, C. L., & Abdallah, C. G. (2017). A network-based neurobiological model of PTSD: Evidence from structural and functional neuroimaging studies. Curr Psychiatry Rep, 19(11), 81. https://doi.org/10.1007/s11920-017-0840-4
Berle, D., & Starcevic, V. (2005). Thought-action fusion: review of the literature and future directions. Clin Psychol Rev, 25(3), 263-284. https://doi.org/10.1016/j.cpr.2004.12.001
Berman, N. C., Wheaton, M. G., & Abramowitz, J. S. (2013a). Rigid rules of conduct and duty: Prediction of thought-action fusion. J Cogn Psychother, 27(2), 83-95. https://doi.org/10.1891/0889-8391.27.2.83
Berman, N.C., Wheaton, M.G., & Abramowitz, J.S. (2013b). Childhood trauma and thought action fusion: A multi-method examination. J Obsess-Compuls Rel, 2(1), 43-47.
Bremner, J. D., Bolus, R., & Mayer, E. A. (2007). Psychometric properties of the Early Trauma Inventory-Self Report. J Nerv Ment Dis, 195(3), 211-218. https://doi.org/10.1097/01.nmd.0000243824.84651.6c
Briere, J. (1996). A self-trauma model for treating adult survivors of severe child abuse, The APSAC handbook on child maltreatment. Sage Publications.
Carlson, J. M., Cha, J., & Mujica-Parodi, L. R. (2013). Functional and structural amygdala - anterior cingulate connectivity correlates with attentional bias to masked fearful faces. Cortex, 49(9), 2595-2600. https://doi.org/10.1016/j.cortex.2013.07.008
Cho, M.J., & Kim, K.H. (1993). Diagnostic validity of the CES-D (Korean version) in the assessment of DSM-III-R major depression. J Korean Neuropsychiatr Assoc, 32(3), 381-399.
Critchley, H. D. (2005). Neural mechanisms of autonomic, affective, and cognitive integration. J Comp Neurol, 493(1), 154-166. https://doi.org/10.1002/cne.20749
Dannlowski, U., Kugel, H., Huber, F., Stuhrmann, A., Redlich, R., Grotegerd, D., Dohm, K., Sehlmeyer, C., Konrad, C., Baune, B. T., Arolt, V., Heindel, W., Zwitserlood, P., & Suslow, T. (2013). Childhood maltreatment is associated with an automatic negative emotion processing bias in the amygdala. Human Brain Mapping, 34(11), 2899–2909. https://doi.org/10.1002/hbm.22112
Deguchi, A., Masuya, J., Naruse, M., Morishita, C., Higashiyama, M., Tanabe, H., Inoue, T., & Ichiki, M. (2021). Rumination mediates the effects of childhood maltreatment and trait anxiety on depression in non-clinical adult volunteers. Neuropsychiatr Dis Treat, 17, 3439-3445. https://doi.org/10.2147/NDT.S332603
Gibb, B. E., Chelminski, I., & Zimmerman, M. (2007). Childhood emotional, physical, and sexual abuse, and diagnoses of depressive and anxiety disorders in adult psychiatric outpatients. Depress Anxiety, 24(4), 256-263. https://doi.org/10.1002/da.20238
Hanlon, P., McCallum, M., Jani, B. D., McQueenie, R., Lee, D., & Mair, F. S. (2020). Association between childhood maltreatment and the prevalence and complexity of multimorbidity: A cross-sectional analysis of 157,357 UK Biobank participants. Journal of Comorbidity, 10, 2235042X10944344. https://doi.org/10.1177/2235042x10944344
Humphreys, K. L., LeMoult, J., Wear, J. G., Piersiak, H. A., Lee, A., & Gotlib, I. H. (2020). Child maltreatment and depression: A meta-analysis of studies using the Childhood Trauma Questionnaire. Child Abuse Negl, 102, 104361. https://doi.org/10.1016/j.chiabu.2020.104361
Ide, J. S., Shenoy, P., Yu, A. J., & Li, C. S. (2013). Bayesian prediction and evaluation in the anterior cingulate cortex. J Neurosci, 33(5), 2039-2047. https://doi.org/10.1523/JNEUROSCI.2201-12.2013
Jeon, J. R., Lee, E. H., Lee, S. W., Jeong, E. G., Kim, J. H., Lee, D., & Jeon, H. J. (2012). The early trauma inventory self report-short form: psychometric properties of the korean version. Psychiatry Investig, 9(3), 229-235. https://doi.org/10.4306/pi.2012.9.3.229
Kessler, R. C., McLaughlin, K. A., Green, J. G., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., Aguilar-Gaxiola, S., Alhamzawi, A. O., Alonso, J., Angermeyer, M., Benjet, C., Bromet, E., Chatterji, S., de Girolamo, G., Demyttenaere, K., Fayyad, J., Florescu, S., Gal, G., Gureje, O., . . . Williams, D. R. (2010). Childhood adversities and adult psychopathology in the WHO World Mental Health Surveys. Br J Psychiatry, 197(5), 378-385. https://doi.org/10.1192/bjp.bp.110.080499
Kim, H., Wildeman, C., Jonson-Reid, M., & Drake, B. (2017). Lifetime Prevalence of Investigating Child Maltreatment Among US Children. Am J Public Health, 107(2), 274-280. https://doi.org/10.2105/AJPH.2016.303545
Lee, S. J., & Lee, S. (2021). Korean Version of the Thought-Action Fusion Scale: The Evidence for Its Psychometric Properties. Psychiatry Investig, 18(4), 348-356. https://doi.org/10.30773/pi.2020.0396
Lee, S. W., Cha, H., Chung, Y., Kim, E., Song, H., Chang, Y., & Lee, S. J. (2019). The neural correlates of thought-action fusion in healthy adults: A functional magnetic resonance imaging study. Depress Anxiety, 36(8), 732-743. https://doi.org/10.1002/da.22933
Lee, S. W., Cha, H., Jang, T. Y., Kim, E., Song, H., Chang, Y., & Lee, S. J. (2021). The Neural Correlates of Positive Versus Negative Thought-action Fusion in Healthy Young Adults. Clin Psychopharmacol Neurosci, 19(4), 628-639. https://doi.org/10.9758/cpn.2021.19.4.628
Lee, S. W., Song, H., Jang, T. Y., Cha, H., Kim, E., Chang, Y., & Lee, S. J. (2022). Aberrant functional connectivity of neural circuits associated with thought-action fusion in patients with obsessive-compulsive disorder. Psychol Med, 52(11), 2106-2115. https://doi.org/10.1017/S0033291720003980
Lee, S. W., Yoo, J. H., Kim, K. W., Lee, J. S., Kim, D., Park, H., Choi, J., & Jeong, B. (2015). Aberrant function of frontoamygdala circuits in adolescents with previous verbal abuse experiences. Neuropsychologia, 79(Pt A), 76-85. https://doi.org/10.1016/j.neuropsychologia.2015.10.029
Li, E. T., Luyten, P., & Midgley, N. (2020). Psychological mediators of the association between childhood emotional abuse and depression: A systematic review. Front psychiatry, 11, 559213. https://doi.org/10.3389/fpsyt.2020.559213
Lin, X., Li, L., Chi, P., Wang, Z., Heath, M. A., Du, H., & Fang, X. (2016). Child maltreatment and interpersonal relationship among Chinese children with oppositional defiant disorder. Child Abuse Negl, 51, 192-202. https://doi.org/10.1016/j.chiabu.2015.10.013
Mansueto, G., Caselli, G., Ruggiero, G. M., & Sassaroli, S. (2019). Metacognitive beliefs and childhood adversities: an overview of the literature. Psychol Health Med, 24(5), 542-550. https://doi.org/10.1080/13548506.2018.1550258
Menon, V. (2011). Large-scale brain networks and psychopathology: a unifying triple network model. Trends Cogn Sci, 15(10), 483-506. https://doi.org/10.1016/j.tics.2011.08.003
Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: a network model of insula function. Brain Struct Funct, 214(5-6), 655-667. https://doi.org/10.1007/s00429-010-0262-0
Nanni, V., Uher, R., & Danese, A. (2012). Childhood maltreatment predicts unfavorable course of illness and treatment outcome in depression: a meta-analysis. Am J Psychiatry, 169(2), 141-151. https://doi.org/10.1176/appi.ajp.2011.11020335
Park, S. (2018). Reliability and Validity of the Early Trauma Inventory Self Report-Short Form among Korean Adolescents. J Korean Acad Child Adolesc Psychiatry, 29(1), 2-6. https://doi.org/10.5765/jkacap.2018.29.1.2
Radloff, L.S. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Appl Psychol Meas, 1(3), 385-401. https://doi.org/10.1177/014662167700100306
Raes, F., & Hermans, D. (2008). On the mediating role of subtypes of rumination in the relationship between childhood emotional abuse and depressed mood: brooding versus reflection. Depress Anxiety, 25(12), 1067-1070. https://doi.org/10.1002/da.20447
Rassin, E., Merckelbach, H., Muris, P., & Spaan, V. (1999). Thought-action fusion as a causal factor in the development of intrusions. Behav Res Ther, 37(3), 231-237. https://doi.org/10.1016/s0005-7967(98)00140-5
Salkovskis, P., Shafran, R., Rachman, S., & Freeston, M. H. (1999). Multiple pathways to inflated responsibility beliefs in obsessional problems: possible origins and implications for therapy and research. Behav Res Ther, 37(11), 1055-1072. https://doi.org/10.1016/s0005-7967(99)00063-7
Salkovskis, P. M. (1985). Obsessional-compulsive problems: a cognitive-behavioural analysis. Behav Res Ther, 23(5), 571-583. https://doi.org/10.1016/0005-7967(85)90105-6
Scher, C. D., Forde, D. R., McQuaid, J. R., & Stein, M. B. (2004). Prevalence and demographic correlates of childhood maltreatment in an adult community sample. Child Abuse Negl, 28(2), 167-180. https://doi.org/10.1016/j.chiabu.2003.09.012
Seeley, W. W. (2019). The Salience Network: A Neural System for Perceiving and Responding to Homeostatic Demands. J Neurosci, 39(50), 9878-9882. https://doi.org/10.1523/JNEUROSCI.1138-17.2019
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci, 27(9), 2349-2356. https://doi.org/10.1523/JNEUROSCI.5587-06.2007
Seo, J. G., & Park, S. P. (2015). Validation of the Generalized Anxiety Disorder-7 (GAD-7) and GAD-2 in patients with migraine. J Headache Pain, 16, 97. https://doi.org/10.1186/s10194-015-0583-8
Shafran, R., Thordarson, D. S., & Rachman, S. (1996). Thought-action fusion in obsessive compulsive disorder. J Anxiety Disord, 10(5), 379-391. https://doi.org/https://doi.org/10.1016/0887-6185(96)00018-7
Simmons, A., Strigo, I., Matthews, S. C., Paulus, M. P., & Stein, M. B. (2006). Anticipation of aversive visual stimuli is associated with increased insula activation in anxiety-prone subjects. Biol Psychiatry, 60(4), 402-409. https://doi.org/10.1016/j.biopsych.2006.04.038
Smucker, M. R., Dancu, C., Foa, E. B., & Niederee, J. L. (1995). Imagery rescripting: A new treatment for survivors of childhood sexual abuse suffering from posttraumatic stress. J of Cogn Psychother, 9(1), 3–17.
Spertus, I. L., Yehuda, R., Wong, C. M., Halligan, S., & Seremetis, S. V. (2003). Childhood emotional abuse and neglect as predictors of psychological and physical symptoms in women presenting to a primary care practice. Child Abuse Negl, 27(11), 1247-1258. https://doi.org/10.1016/j.chiabu.2003.05.001
Spitzer, R. L., Kroenke, K., Williams, J. B., & Lowe, B. (2006). A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med, 166(10), 1092-1097. https://doi.org/10.1001/archinte.166.10.1092
Stein, M. B., Simmons, A. N., Feinstein, J. S., & Paulus, M. P. (2007). Increased amygdala and insula activation during emotion processing in anxiety-prone subjects. Am J Psychiatry, 164(2), 318-327. https://doi.org/10.1176/ajp.2007.164.2.318
Teicher, M. H., Gordon, J. B., & Nemeroff, C. B. (2022). Recognizing the importance of childhood maltreatment as a critical factor in psychiatric diagnoses, treatment, research, prevention, and education. Molecular Psychiatry, 27(3), 1331-1338. https://doi.org/10.1038/s41380-021-01367-9
Teicher, M. H., & Samson, J. A. (2016). Annual research review: Enduring neurobiological effects of childhood abuse and neglect. J Child Psychol Psychiatry, 57(3), 241-266. https://doi.org/10.1111/jcpp.12507
Tottenham, N., Hare, T. A., Millner, A., Gilhooly, T., Zevin, J. D., & Casey, B. J. (2011). Elevated amygdala response to faces following early deprivation. Dev Sci, 14(2), 190-204. https://doi.org/10.1111/j.1467-7687.2010.00971.x
Wells, A. (2009). Metacognitive therapy for anxiety and depression. Guilford Press.

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Aberrant function of the salience network related to maltreatment experiences during thought–action fusion

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Abstract

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Introduction

Methods

Participants

Psychological measurements

TAF induction task

Image and statistical analyses

Results

Psychological characteristics

The relationship between CM experiences, psychological measures, and behavioral data

TAF stimulated brain activity

The relationship between brain activity in SN, CM experiences, and psychological measures

Discussion

Conclusion

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Journal Publication

Version 1