FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2933229968> ?p ?o ?g. }

• W2933229968 endingPage "752" @default.
• W2933229968 startingPage "742" @default.
• W2933229968 abstract "Loss and abuse in children can lead to unresolved–disorganized (UD) attachment. How this condition relates to brain structure and functional connectivity (FC) is unknown. We therefore aimed to investigate gray matter volume (GMV) and resting state functional connectivity (RSFC) correlates of UD attachment in adolescents. Based on previous neuroimaging studies of trauma effects, we hypothesized that the structure of the amygdala and hippocampus and the FC of the latter would be linked to UD attachment. Anatomical and RSFC data were collected from a mixed group of adolescents (N = 74) with symptoms of posttraumatic stress disorder (PTSD) related to childhood sexual abuse (CSA), anxiety/depressive symptoms, and without psychiatric disorder as part of the Emotional Pathways’ Imaging Study in Clinical Adolescents (EPISCA). Bilateral volumes of the amygdala and hippocampus were measured using the FMRIB Software Library, and RSFC of the hippocampus was assessed using seed-based correlation. UD attachment was measured using the Adult Attachment Interview. Hierarchical regression and correlation were used to assess the associations between UD status (continuous and categorical), brain structure, and FC, adjusting for a general psychopathology factor, puberty stage, gender, age, and IQ. UD attachment was associated with a smaller left hippocampal volume, R2 = .23, and a higher level of FC between the hippocampus and the middle temporal gyrus and lateral occipital cortex. The associations among UD attachment, specific brain structure, and FC across psychopathological classifications shows promise for dimensional complements to the dominant classificatory approach in clinical research and practice. Spanish Abstracts by Asociación Chilena de Estrés Traumático (ACET) El apego desorganizado no resuelto asociado con un menor hipocampo y un incremento de la conectividad funcional más allá de la psicopatología APEGO, HIPOCAMPO Y CONECTIVIDAD FUNCIONAL. Las pérdidas y el abuso en niños pueden conllevar a un apego desorganizado no resuelto (DN). La forma en que esta condición se relaciona con la estructura cerebral y conectividad funcional (CF) es desconocida. Por lo tanto, nuestro objetivo fue investigar el volumen de materia gris (VMG) y los correlatos de la conectividad funcional en estado de reposo (CFER) de DN en adolescentes. Basado en estudios previos de neuroimágenes sobre los efectos del trauma, hipotetizamos que la estructura de la amígdala e hipocampo y la CF de este último podría estar relacionado con DN. Los datos anatómicos y de CFER fueron recolectados de un grupo mixto de adolescentes (N = 74) con síntomas de trastorno de estrés postraumático (TEPT) relacionado con abuso sexual infantil (ASI), síntomas de ansiedad/depresión, y sin trastornos psiquiátricos, como parte del Estudio de Imágenes de Vías Emocionales en Clínica Adolescente (EPISCA en su sigla en inglés). Volúmenes bilaterales de la amígdala e hipocampo fueron evaluados usando el software de biblioteca FMRIB, y la CFER del hipocampo fue evaluada usando la correlación basada en semillas. La DN fue medido utilizando la Entrevista de Apego Adulto. Regresiones jerárquicas y correlaciones fueron utilizadas para evaluar las asociaciones entre DN (continuo y categórico), estructura cerebral, y CF, ajustando un factor general de psicopatología, etapa de pubertad, género, edad y CI. DN fue asociado con un menor volumen del hipocampo izquierdo, R2 = .23, y altos niveles de CF entre el hipocampo y giro temporal medio y la corteza occipital lateral. La asociación de DN con una estructura cerebral especifica y CF a través de clasificaciones psicopatológicas es prometedora como complementos dimensionales al enfoque clasificatorio dominante en la investigación y práctica clínica. Traditional and Simplified Chinese Abstracts by the Asian Society for Traumatic Stress Studies (AsianSTSS) 簡體及繁體中文撮要由亞洲創傷心理研究學會翻譯 Unresolved-disorganized attachment associated with smaller hippocampus and increased functional connectivity beyond psychopathology Traditional Chinese 標題: 未解決和錯亂依附跟海馬體較小和功能連結性提升有關, 程度超於心理疾病所致 撮要: 兒童經歷失落與虐待, 可導致有未解決和錯亂依附(UD)。可是, 我們仍不清楚這種狀況跟腦部結構與功能連結性有何關連。因此, 我們旨在探查青少年中, 作為UD的關連因素的灰質體積(GMV)及靜息態功能連結性(RSFC)。我們基於過往檢視創傷效應的神經成像研究, 假設杏仁核與海馬體的結構和後者的FC會跟UD有關。混合的青少年樣本(N = 74) 來自青少年臨床情緒路徑成像研究(EPISCA)。他們有童年性虐(CSA)相關、焦慮症/抑鬱症狀相關的創傷後壓力症(PTSD)症狀, 但無精神疾病。我們收集樣本的解剖數據和RSFC數據, 採用FMRIB Software Library來測量杏仁核與海馬體的雙邊體積, 用種子相關分析來評估海馬體的RSFC, 並以成人依附面談來測量UD。層次迴歸及相關分析用以評估UD(連續與明確的)、腦部結構、FC之間的關連;我們亦因應以下因素作調節:一個普遍的心理疾病因素、青春期、性別、年齡、IQ。UD跟左邊海馬體體積較小有關(R2 = .23), 亦跟海馬體與顳中迴與外側枕葉之間的FC水平較高有關。在不同的心理疾病類別中, UD跟特殊的腦部結構和FC的關連反映, 現時臨床研究和實踐的主流分類法有多維度的替代可能。 Simplified Chinese 标题: 未解决和错乱依附跟海马体较小和功能链接性提升有关, 程度超于心理疾病所致 撮要: 儿童经历失落与虐待, 可导致有未解决和错乱依附(UD)。可是, 我们仍不清楚这种状况跟脑部结构与功能链接性有何关连。因此, 我们旨在探查青少年中, 作为UD的关连因素的灰质体积(GMV)及静息态功能链接性(RSFC)。我们基于过往检视创伤效应的神经成像研究, 假设杏仁核与海马体的结构和后者的FC会跟UD有关。混合的青少年样本(N = 74) 来自青少年临床情绪路径成像研究(EPISCA)。他们有童年性虐(CSA)相关、焦虑症/抑郁症状相关的创伤后压力症(PTSD)症状, 但无精神疾病。我们收集样本的解剖数据和RSFC数据, 采用FMRIB Software Library来测量杏仁核与海马体的双边体积, 用种子相关分析来评估海马体的RSFC, 并以成人依附面谈来测量UD。层次回归及相关分析用以评估UD(连续与明确的)、脑部结构、FC之间的关连;我们亦因应以下因素作调节:一个普遍的心理疾病因素、青春期、性别、年龄、IQ。UD跟左边海马体体积较小有关(R2 = .23), 亦跟海马体与颞中回与外侧枕叶之间的FC水平较高有关。在不同的心理疾病类别中, UD跟特殊的脑部结构和FC的关连反映, 现时临床研究和实践的主流分类法有多维度的替代可能。 The loss of an attachment figure or the abuse within an attachment relationship are adverse childhood events that may have lifelong somatic, psychiatric, and psychosocial consequences for the individual (Anda et al., 2006; Felitti et al., 1998). From an attachment theory perspective (Bowlby, 1969, 1980; Hesse, 2016), loss and abuse increase the likelihood of unresolved–disorganized (UD) attachment: The child may show signs of current mental impact from loss of loved ones or abuse, or the child may apply contradictory approach–avoidance strategies to relationships with parents or other attachment figures. For example, the child may simultaneously display proximity-seeking and avoidant behaviors. This UD attachment is considered a (momentary) breakdown of an organized strategy to deal with stressful situations. It results from abuse or another traumatic experiences within the attachment relationship, thus confronting the child with a paradox, as the parent is both a source of comfort and fear at the same time for the child (Lyons-Ruth & Jacobvitz, 2016). Not all children are able to resolve these traumatic attachment experiences. Some adolescents show signs of disorientation and disorganization while discussing early traumatic attachment events, indicating that they are still overwhelmed by the trauma or loss experience (Hesse, 2016; Lyons-Ruth & Jacobvitz, 2016). This UD mental representation may negatively impact current and future attachment relationships and the transition to adult functioning (Hesse & Main, 2000). Previous research has indicated that experiences of loss and abuse increase an individual's risk for psychopathology, including posttraumatic stress disorder (PTSD) as well as anxiety or depressive disorders (Cloitre et al. 2009; Gospodarevskaya, 2013; McLaughlin, Sheridan, & Lambert, 2014). This may be at least partially attributable to the profound adverse effects of early life stress on brain development, particularly the hippocampus, a stress-sensitive brain region that plays a role in the regulation of the hypothalamic–pituitary–adrenal (HPA) axis. Previous studies have found evidence for a smaller hippocampal volume in healthy adults who report experiences of abuse but not in children who have experienced abuse (Calem, Bromis, McGuire, Morgan, & Kemptona, 2017; Hart & Rubia, 2012; Riem, Alink, Out, Van IJzendoorn, & Bakermans-Kranenburg, 2015; Rinne-Albers, Van der Wee, Lamers-Winkelman, & Vermeiren, 2013). A reduced hippocampal volume has also been found in adults with PTSD (Chen & Etkin, 2013). Studies examining brain structure in patients with anxiety and depressive disorders have shown diverging results, from a larger amygdala volume to a smaller left hippocampal volume (DeBellis et al., 2000; Koolschijn, Van IJzendoorn, M. H., Bakermans-Kranenburg, & Crone, 2013; MacMillan et al., 2003; Pechtel, Lyons-Ruth, Anderson, & Teicher, 2014; Schmaal et al., 2016). It is, however, possible that experiences of trauma account for hippocampal abnormalities in patients with PTSD, anxiety, and depressive disorders, as a reduced hippocampal volume has been found in maltreated individuals regardless of psychopathology. In addition to structural differences, abnormalities in resting-state functional connectivity (RSFC) of the hippocampus have been found in individuals with childhood adversity (Philip et al., 2013) and in a variety of neuropsychiatric disorders known to be related to childhood adversity, such as PTSD (Tursich et al., 2015), depression, and anxiety (Veer et al., 2010). More specifically, individuals who have experienced childhood adversity with or without psychopathology show aberrant resting-state connectivity between the amygdala and frontal regions (for a review, see Teicher, Samson, Anderson, & Ohashi, 2016; Teicher & Samson, 2016). However, there is a lack of research examining the role of attachment in structural and functional brain abnormalities in adolescents with psychopathology, possibly because simultaneous assessment of psychopathology and attachment representations in adolescents is scarce (Van Hoof, van Lang, Speekenbrink, van IJzendoorn, & Vermeiren, 2015). Attachment is best described as the innate system that motivates humans to develop an affective bond with a protective caregiver as a secure haven and a safe base to explore the environment (Bowlby, 1969). Caregiver protection against dangers and stresses along with stimulation of exploration shape the child's emotion regulation and the ability to build trusting relationships with others (Cassidy, 2016). According to attachment theory, interactions with attachment figures in childhood develop into inner-working models of the self and others (Bretherton & Munholland, 2016). Attachment in adolescents and adults can be assessed with the well-validated Adult Attachment Interview (AAI; Hesse, 2016; Main, Kaplan, & Cassidy, 1985), which asks respondents for current mental representations of childhood attachment experiences. In the case of adversity such as loss of an attachment figure or the experience of child abuse, attachment representations may be characterized as UD (Hesse, 2016; Lyons-Ruth & Jacobvitz, 2016), indicated by incoherent (i.e., disoriented and disorganized) speech in response to questions about losses or other potentially traumatic events, independent from assessed psychopathology. This UD representation is considered a transdiagnostic risk factor that may increase vulnerability to a range of psychiatric disorders. Indeed, the authors of a meta-analysis found UD attachment had a prevalence of 43% in combined clinical samples, with elevated rates of unresolved loss and trauma in all clinical groups (Bakermans-Kranenburg & van IJzendoorn, 2009). Some studies point to an association between disorganized attachment and structural brain abnormalities. For example, maltreatment reported in the AAI was associated with smaller hippocampal volume in a study that used female adult twin pairs (Riem et al., 2015). Recently, Lyons-Ruth, Pechtel, Yoon, Anderson, and Teicher (2016) showed that both maternal and infant components of disorganized attachment interaction in infancy were associated with increased left amygdala volume later in adulthood in a sample of impoverished, highly stressed families. However, it is yet unknown whether attachment representation as assessed with the “gold standard” AAI (Hesse, 2016; Main et al., 1985) is associated with structural brain abnormalities. Moreover, whereas there is sparse literature on the association between attachment and brain morphology, studies on attachment representation and functional connectivity in the brain are lacking. Examining how UD attachment relates to brain structure and functional connectivity will extend previous neuroimaging research on childhood trauma as previous studies have assessed trauma retrospectively and have not examined whether or not it matters if the trauma has been resolved. Unresolved–disorganized attachment represents a current state of mind with respect to childhood attachment experiences. It is yet unknown how this current state relates to brain measures. Although there is evidence that UD attachment increases vulnerability to psychopathology in general, it is unknown how unresolved trauma relates to the abnormalities in brain structure and function that are commonly found in patients with psychopathology (Caspi et al., 2014; Lahey et al., 2017). In the current study, we therefore examined whether UD attachment is related to brain abnormalities across multiple psychiatric diagnoses. Thus, we applied a dimensional approach to examine gray matter and resting-state abnormalities related to UD attachment across different psychopathological conditions. Although traditionally psychiatric disorders have been viewed as categorical psychopathological conditions, recent research shows accumulating evidence for a dimensional approach of psychopathology and points to overarching features and transdiagnostic factors. This dimensional approach to the structure of psychopathology may explain high levels of comorbidity among mental disorders. However, clinical neuroscience has not kept pace with these advances (Zald & Lahey, 2017). Neuroimaging studies examining biomarkers for psychopathological conditions point to similar structural and functional brain abnormalities across psychopathological conditions (Zald & Lahey, 2017). These shared brain abnormalities may be explained by high levels of comorbidity or shared transdiagnostic risk factors, such as UD attachment. Therefore, the aim of the present study was to investigate whether UD attachment representation is associated with gray matter volume (GMV) of the hippocampus and amygdala in a sample of adolescents, after adjusting for psychiatric symptomatology. We chose the hippocampus and amygdala as regions of interest based on previous studies showing abnormalities in these regions in individuals with experiences of childhood trauma. In addition, we examined whether brain regions that show structural alterations related to UD attachment are also associated with different functional resting state connectivity. In sum, we examined the neural correlates of unresolved loss or trauma as assessed using the AAI (Main et al., 1985). Our hypothesis was that UD attachment would be correlated with a smaller hippocampal volume and a larger amygdala (Brenning & Braet, 2013; Brown & Morey, 2012) and that brain structures associated with UD attachment would also show alterations in functional connectivity. The current study involved 74 participants from the Emotional Pathways’ Imaging Study in Clinical Adolescents (EPISCA, N = 77; Van Hoof et al., 2015). They were recruited according to specified inclusion and exclusion criteria (Van den Bulk et al., 2013; Van Hoof et al., 2015; see Supplemental Material) and available coded AAIs (Main et al., 1985). Dropout was due to anomalous magnetic resonance imaging (MRI) findings (n = 2), technical scanning problems, or poor imaging data quality (n = 2). Within this group, there were 21 adolescents with PTSD related to childhood sexual abuse (CSA), 28 adolescents with anxiety and/or depressive disorders (DEP), and 25 nonclinical adolescents (CNTR). All adolescents with experiences of CSA had PTSD. Some adolescents in the DEP and CNTR group had been exposed to other types of trauma (see Supplemental Material) but not to CSA. Inclusion criteria for the CSA group were having experienced sexual abuse during their lifetime more than once by one or more perpetrators in- or outside the family, and being referred for treatment. See Van Hoof and colleagues (2015) for a detailed description. The sample was originally recruited based on whether they had experienced CSA, had an anxiety and/or depressive disorder, or had no clinical symptoms in order to be able to compare groups cross-sectionally (see Van den Bulk et al., 2013). In the current study, the CSA, DEP, and CNTR groups were analyzed together as the aim was to examine whether UD attachment was related to brain abnormalities across multiple psychiatric diagnoses. Power analysis using G*power (linear multiple regression) showed that the power needed to examine effects of UD and the general psychopathology factor (GPF) on brain structure was met with an alpha value set to .05 and a power of .80, with an expected medium effect size f = 0.15 (Calem et al., 2017) and two predictors (UD and GPF), with a required sample size of 68. The study sample comprised 63 females (85.1%), with 18 in the CSA group, 24 in the DEP group, and 21 in the CNTR group. Participants’ mean age was 15.42 years (SD = 1.67, range: 12–20), and they had a total mean IQ of 103.28 (SD = 8.89, range: 81–119). Regarding cultural background, 1.4% of participants were Asian (CSA, n = 1), 93.2% were Caucasian (CSA, n = 20; DEP, n = 25; CNTR, n = 24), 1.4% were Surinamese (DEP, n = 1), and 2.7% were Latin-American (DEP, n = 2). Four adolescents (5.4%; n = 2 CSA and n = 2 DEP) reported stable selective serotonin reuptake inhibitor use (n = 3 fluoxetine, n = 1 sertraline). Puberty stage was assessed using the Pubertal Development Scale (PDS; Petersen, Crockett, Richards, & Boxer, 1988) according to the following categories: prepubertal (CSA, n = 1), midpubertal (CNTR, n = 5), late pubertal (CSA, n = 7; DEP, n = 11; CNTR, n = 12), postpubertal (CSA, n = 10; DEP, n = 9; CNTR, n = 5). Information about pubertal status was missing for 10 participants; for these participants, pubertal status was imputed using gender and age. Attachment and clinical characteristics of the original larger total sample (Van den Bulk et al., 2013; N = 77), not using imaging data, have been reported separately (Van Hoof et al., 2015). Written informed assent and consent was obtained from all adolescents and their parents. Participants received financial compensation, including travel expenses. The medical ethics committee of the Leiden University Medical Center approved this study. After adolescents and their parents gave assent and consent to participate in the EPISCA study, they filled out questionnaires (usually at home), and were tested for IQ and interviewed for classification of any disorder, according to the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), as well as attachment representation at the clinic in separate appointments. Scanning was usually performed separate from the aforementioned diagnostics, depending on availability of the scanner. The AAI (Main et al., 1985; see Supplemental Material) is a clinician-administered semistructured interview, validated for adolescents, that takes approximately 1 hr to administer. The AAI asks interviewees what and how they think about their relationship with parents or other primary caregivers in their youth, how these experiences have influenced them, how their actual relationship with parents or other primary caregivers is, and whether there were any experiences of illness, separation, fear, trauma, or loss. Interviewees are asked to give specific examples to support each evaluation. The coherence of the narrative rather than its autobiographical content is of most importance. After transcription and coding of the AAI according to the manual (Hesse, 2016) by a certified coder, an attachment representation classification can be given. In organized attachment representations, there is one coherent mental strategy regarding attachment figures, either secure–autonomous or insecure. In UD attachment representations, different mental strategies concerning attachment figures are used simultaneously or sequentially, often contradicting one another, which becomes apparent when coding the narrative. The AAI includes a dimensional subscale entitled Unresolved for Loss or Trauma; AAI narratives are assigned scores on this dimension between 1 and 9, with a score of 9 indicating verbal behavior with highly incoherent speech characteristics in the narrative around loss or trauma experiences. A scale score for Unresolved Loss or Trauma of 5.5 or above also renders an individual UD (see Supplemental Material). To control for the effects of psychopathology, we decided to use the GPF. The GPF represents the lesser-to-greater severity of psychopathology associated with negative emotionality (Tackett et al., 2013), compromised brain integrity (Caspi et al., 2014), lower IQ, higher levels of negative affectivity, and lower levels of effortful control shown in 1,954 children between 6 and 8 years of age from a birth cohort (Jaddoe et al., 2012; Neumann et al., 2016). The GPF shows a significant single nucleotide polymorphism (SNP) heritability of 38% (SE = 0.16), p = .008. The use of the GPF has also demonstrated validity in girls (Lahey et al., 2015) and in young adolescents (Patalay et al., 2015). In our sample, the GPF was estimated using parent and self-report measurements for behavioral and emotional problems in children and adolescents: the Youth Self Report (YSR; Achenbach, 1991a; Verhulst, Ende, & van der Koot, 1997), Child Behavior Checklist (CBCL; Achenbach, 1991b; Verhulst, Ende, & van der Koot, 1996), Revised Child Anxiety and Depression Scale (RCADS; Chorpita, Yim, Moffitt, Umemoto, & Francis, 2000; Oldehinkel, 2000), Trauma Symptom Checklist for Children (TSCC; Briere, 1996), Children's Depression Inventory (CDI; Kovačs, 1992), and Adolescent Dissociative Experiences Scale (A-DES; Armstrong, Putnam, Carlson, Libero, & Smith, 1997). Principal component analysis was performed using these scales and appropriate subscales, and one component explaining 61.6% was extracted, all loadings > .56 (see Supplementary Table S3). Factor scores were calculated in order to estimate the GPF (Franke, 2016; Lahey et al., 2012; Lahey, Zald et al., 2017; Lahey, Krueger, Rathouz, Waldman, & Zald, 2017). See Supplemental Material for a detailed description of the questionnaires used to estimate the GPF. Images were acquired on a Philips 3T MRI system (Philips Healthcare; Best, the Netherlands), equipped with a SENSE-8 head coil. Scanning took place at the Leiden University Medical Center. Prior to scanning, all participants were prepared for scanning by lying in a dummy scanner and hearing scanner sounds. For each participant, a sagittal 3-dimensional gradient-echo T1-weighted image was acquired (repetition time = 9.8 ms; echo time = 4.6 ms; flip angle = 8°; 140 sagittal slices; no slice gap; field of view = 256 × 256 mm; 1.17 × 1.17 × 1.2 mm voxels; duration = 4:56 min) as part of a larger, fixed imaging protocol. Resting-state functional MRI (fMRI) data were acquired, using T2*-weighted gradient-echo echo-planar imaging (160 whole-brain volumes; repetition time 2,200 ms; echo time 30 ms; flip angle 80°; 38 transverse slices; no slice gap; field of view 220 mm; in-plane voxel size 2.75 × 2.75 mm; slice thickness 2.72 mm; total duration of the resting-state run = 6 min). Participants were instructed to lie still with their eyes closed and not to fall asleep. Volumes of the left and right hippocampus and amygdala were assessed using FMRIB's Integrated Registration and Segmentation Tool (FIRST; Patenaude, Smith, Kennedy, & Jenkinson, 2011), part of FSL FMRIB's Software Library (FMRIB, n.d.; Smith et al., 2004). Hippocampal volumes were extracted after affine registration to standard space and subcortical structure segmentation. Registrations and segmentations were visually inspected, and no errors were observed. After hippocampal volume extraction, the fslstats program was used to assess volumes of the left and right hippocampus and amygdala. Brain tissue volume, normalized for participant head size, was estimated with SIENAX (Smith, De Stefano, Jenkinson, & Matthews, 2001; Smith, 2002). Brain and skull images were extracted from the single whole-head input data (Jenkinson, Bannister, Brady, & Smith, 2002). The brain image was then affine-registered to MNI152 space (Jenkinson et al., 2002), after which tissue-type segmentation with partial volume estimation was carried out in order to calculate total brain volume, including separate estimates of volumes of gray matter, white matter, peripheral gray matter, and ventricular CSF (Zhang, Brady, & Smith, 2001). Volumes of the left and right hippocampus and amygdala and total brain volume (mm3) were exported to SPSS. First, four hierarchical regression analyses with left and right hippocampal volume and left and right amygdala volume were performed with the GPF, sex, composite score age/pubertal status (see Supplemental Material), total IQ score, and whole-brain volume in Step 1, and unresolved loss or trauma (categorical UD vs. non-UD and unresolved continuous scale in two separate models) in Step 2. All participants were included in the UD versus non-UD comparison, and analyses were performed with the clinical groups combined, as the aim of the study was to apply a dimensional approach. In addition to age, pubertal status was also included because variance in pubertal status may be related to different brain structures than variance in age. A composite score for age and pubertal status was calculated to control for multicollinearity (Giedd et al., 2006). Statistics indicated no multicollinearity, largest variance inflation factor ≤ 1.20, tolerance > .83. The four hierarchical regression analyses were repeated with the GPF as an additional covariate in the first step. Vertex analysis was performed using first_utils (Patenaude et al., 2011) in order to localize and visualize effects of unresolved status. Exploratory whole-brain VBM analyses were performed. Contrasts of interest were the parameter estimates corresponding to the regressor of the region that was significantly related to unresolved loss and trauma (a subregion of the left hippocampus; see Figure 2), which represents functional connectivity with that region. Thus, the left hippocampus was used as the seed region. After transforming the mask to native space, the mean time series for each participant was extracted from the left hippocampus using fslmeants. The time series was then used as a regressor in the model. In addition, CSF, white matter, and the global signal (see Supplemental Material) were added as regressors to the model in order to reduce the influence of artifacts caused by physiological signal sources on the results (Fox & Raichle, 2007). The temporal derivative of each regressor was added to the model, which resulted in eight regressors in each model. Motion parameters were also added to the model. First-level analyses were performed in native space. These first-level contrast images and the corresponding variance images were transformed to standard space and submitted to second-level mixed-effects group whole-brain analyses. The positive and negative correlations between hippocampal connectivity and unresolved loss and trauma score were assessed as were the contrasts of (a) UD larger than non-UD and (b) UD smaller than non-UD. Thus, we contrasted UD with non-UD and applied a dimensional analysis of UD. We included the GPF, composite score for age and pubertal status, sex, and IQ as confound regressors in the model. The statistical images were corrected for multiple comparisons at the cluster level in FSL, with a cluster-forming threshold of Z > 2.3 and a cluster-corrected significance of p < .050 (Worsley, 2001). This threshold was chosen to balance Type I and Type II error, as has been recommended (Hopfinger, 2017; Slotnick, 2017). Harvard-Oxford cortical structural atlas was used to localize hippocampal connectivity. See Table 1 for the clinical sample characteristics. Based on the AAI (Cassidy, 2016), 36.5% of the adolescents in the sample were classified as secure (CNTR, n = 13; DEP, n = 11; CSA, n = 3), 41.9% as dismissive (CNTR, n = 11; DEP, n = 1; CSA, n = 9), and 21.6% as UD (CNTR, n = 1; DEP, n = 6; CSA, n = 9). Unresolved–disorganized attachment was found in 16 (21.6%) participants. Of these unresolved participants, six adolescents had anxiety and/or depressive disorders, and nine had CSA-related PTSD. See Supplementary Table S1 for psychopathology scores for the separate groups (CSA-PTSD, internalizing, control, and U vs. non-U). Hierarchical regression analyses showed a significant effect of UD versus non-UD on left hippocampal volume, F(5, 68) = 3.94, p = .003, R2 = .17, but not on right hippocampal volume or on amygdala volume (left or right; see Supplementary Table S2). Hierarchical regression analyses were repeated with the GPF as an additional covariate. Again, there was a significant effect of the categorical UD versus non-UD on left hippocampal volume beyond psychopathology, F(6, 67) = 3.37, p = .014, R2 = .23. Participants who were classified as UD showed a smaller left hippocampal volume (M = 3,574.33, SD = 510.99 for UD; M = 3,921.81, SD = 344.29 for non-UD). The effect of UD remained significant after excluding one control participant with UD status. Hierarchical regression analysis with the continuous variable unresolved for loss or trauma (U) as predictor did not show a significant effect of U on bilateral hippocampal volumes beyond psychopathology (see Table 2). No effect was found regarding UD versus non-UD on right hippocampal volume (see Table 2) or in the hierarchical regression analyses with the amygdala as the dependent variable (see Table 3). Vertex analysis to localize and visualize the effect of UD in specific subfields of the hippocampus did not reach conventional levels of statistical significance, p < .100, when corrected for multiple comparisons. The hippocampal region of interest is shown in Figure 1. An exploratory whole-brain analyses yielded no results. Analy" @default.
• W2933229968 created "2019-04-11" @default.
• W2933229968 creator A5007458836 @default.
• W2933229968 creator A5018808916 @default.
• W2933229968 creator A5034669793 @default.
• W2933229968 creator A5040046390 @default.
• W2933229968 creator A5057030584 @default.
• W2933229968 creator A5063131593 @default.
• W2933229968 creator A5090506891 @default.
• W2933229968 date "2019-07-30" @default.
• W2933229968 modified "2023-10-12" @default.
• W2933229968 title "Unresolved–Disorganized Attachment is Associated With Smaller Hippocampus and Increased Functional Connectivity Beyond Psychopathology" @default.
• W2933229968 cites W1550462067 @default.
• W2933229968 cites W1566415063 @default.
• W2933229968 cites W1642124290 @default.
• W2933229968 cites W1827978642 @default.
• W2933229968 cites W1890675559 @default.
• W2933229968 cites W1939000027 @default.
• W2933229968 cites W1970695058 @default.
• W2933229968 cites W1977385640 @default.
• W2933229968 cites W1979540844 @default.
• W2933229968 cites W1981459575 @default.
• W2933229968 cites W1992701656 @default.
• W2933229968 cites W1996963027 @default.
• W2933229968 cites W1999889452 @default.
• W2933229968 cites W2000469813 @default.
• W2933229968 cites W2003359649 @default.
• W2933229968 cites W2006096283 @default.
• W2933229968 cites W2013567602 @default.
• W2933229968 cites W2015671245 @default.
• W2933229968 cites W2027592978 @default.
• W2933229968 cites W2047843580 @default.
• W2933229968 cites W2052644075 @default.
• W2933229968 cites W2056105279 @default.
• W2933229968 cites W2058396187 @default.
• W2933229968 cites W2059380634 @default.
• W2933229968 cites W2063718349 @default.
• W2933229968 cites W2067962939 @default.
• W2933229968 cites W2068232820 @default.
• W2933229968 cites W207036172 @default.
• W2933229968 cites W2071881327 @default.
• W2933229968 cites W2074457142 @default.
• W2933229968 cites W2079348783 @default.
• W2933229968 cites W2081103329 @default.
• W2933229968 cites W2083480926 @default.
• W2933229968 cites W2084764358 @default.
• W2933229968 cites W2089940272 @default.
• W2933229968 cites W2092702461 @default.
• W2933229968 cites W2110290320 @default.
• W2933229968 cites W2114366984 @default.
• W2933229968 cites W2116839388 @default.
• W2933229968 cites W2120654343 @default.
• W2933229968 cites W2122741903 @default.
• W2933229968 cites W2133939965 @default.
• W2933229968 cites W2136573752 @default.
• W2933229968 cites W2137189967 @default.
• W2933229968 cites W2145025766 @default.
• W2933229968 cites W2151775239 @default.
• W2933229968 cites W2157465110 @default.
• W2933229968 cites W2160583614 @default.
• W2933229968 cites W2166372248 @default.
• W2933229968 cites W2169793721 @default.
• W2933229968 cites W2227994377 @default.
• W2933229968 cites W2264981027 @default.
• W2933229968 cites W2266560836 @default.
• W2933229968 cites W2322236442 @default.
• W2933229968 cites W2322696033 @default.
• W2933229968 cites W2503622982 @default.
• W2933229968 cites W2523665179 @default.
• W2933229968 cites W2528247382 @default.
• W2933229968 cites W2552731340 @default.
• W2933229968 cites W2561015403 @default.
• W2933229968 cites W2590133125 @default.
• W2933229968 cites W2590215596 @default.
• W2933229968 cites W2593657192 @default.
• W2933229968 cites W2607103049 @default.
• W2933229968 cites W2734517864 @default.
• W2933229968 cites W2760887448 @default.
• W2933229968 cites W4211197706 @default.
• W2933229968 cites W4235770099 @default.
• W2933229968 doi "https://doi.org/10.1002/jts.22432" @default.
• W2933229968 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6851754" @default.
• W2933229968 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31361352" @default.
• W2933229968 hasPublicationYear "2019" @default.
• W2933229968 type Work @default.
• W2933229968 sameAs 2933229968 @default.
• W2933229968 citedByCount "14" @default.
• W2933229968 countsByYear W29332299682019 @default.
• W2933229968 countsByYear W29332299682020 @default.
• W2933229968 countsByYear W29332299682021 @default.
• W2933229968 countsByYear W29332299682022 @default.
• W2933229968 countsByYear W29332299682023 @default.
• W2933229968 crossrefType "journal-article" @default.
• W2933229968 hasAuthorship W2933229968A5007458836 @default.
• W2933229968 hasAuthorship W2933229968A5018808916 @default.
• W2933229968 hasAuthorship W2933229968A5034669793 @default.
• W2933229968 hasAuthorship W2933229968A5040046390 @default.
• W2933229968 hasAuthorship W2933229968A5057030584 @default.

• next