Attachment style, affective loss and gray matter volume: A voxel‐based morphometry study

Abstract

Early patterns of infant attachment have been shown to be an important influence on adult social behavior. Animal studies suggest that patterns of early attachment influence brain development, contributing to permanent alterations in neural structure; however, there are no previous studies investigating whether differences in attachment style are associated with differences in brain structure in humans. In this study, we used Magnetic Resonance Imaging (MRI) and voxel‐based morphometry (VBM) to examine for the first time the association between attachment style, affective loss (for example, death of a loved one) and gray matter volume in a healthy sample of adults (n = 32). Attachment style was assessed on two dimensions (anxious and avoidant) using the ECR‐Revised questionnaire. High attachment‐related anxiety was associated with decreased gray matter in the anterior temporal pole and increased gray matter in the left lateral orbital gyrus. A greater number of affective losses was associated with increased gray matter volume in the cerebellum; in this region, however, the impact of affective losses was significantly moderated by the level of attachment‐related avoidance. These findings indicate that differences in attachment style are associated with differences in the neural structure of regions implicated in emotion regulation. It is hypothesized that early attachment experience may contribute to structural brain differences associated with attachment style in adulthood; furthermore, these findings point to a neuronal mechanism through which attachment style may mediate individual differences in responses to affective loss. Hum Brain Mapp, 2010. © 2010 Wiley‐Liss, Inc.

INTRODUCTION

The concept of attachment (Ainsworth, 1967; Bowlby, 1969, 1980]—the proposition that an infant's early dyadic experience with a caregiver shapes their internal working model of relationships—continues to be profoundly influential in the field of developmental research [Rutter et al., 2009]. Early attachment experiences are thought to influence subsequent social behavior and emotion regulation in adulthood [see Mikulincer and Shaver, 2003 for review]. For example, early attachment has been shown to both predict the quality of adult romantic relationships [Roisman et al., 2005] and influence the ability to cope with the loss of a close relationship, known as “affective loss” [Fraley and Shaver, 1998; Sbarra, 2006; Simpson et al., 1992]. Such loss may relate to separation, ending of a significant relationship or death of a loved one.

Although these findings provide some predictive validity for the attachment construct, longitudinal studies indicate only moderate stability of attachment security from infancy to adulthood [Fraley, 2002]. Traditionally attachment style has been categorized into three main categories [secure, anxious, and avoidant; Ainsworth et al., 1978]. Children with secure attachment use their adult caregivers as a safe base and feel able to depend on them; as adults they tend to be comfortable depending on others and having others depend on themselves. In contrast, children with anxious attachment are highly distressed and angered by separation from the caregivers and are ambivalent on their return; as adults they exhibit high levels of emotional expressiveness, worry and impulsiveness in their relationships. Finally children with avoidant attachment tend to avoid caregivers and show no preference between a caregiver and a complete stranger; as adults they view themselves as self‐sufficient and seek less intimacy with partners. More recently, a fourth category associated with later psychopathology (disorganized attachment) has been proposed [Main and Solomon, 1986]. Children and adults with disorganized attachment do not express consistent attachment behavior; rather, their responses appear to reflect a mix of anxiety and avoidance. Some theorists have argued that attachment style is best characterized dimensionally rather than categorically [Cummings, 1990; Fraley and Spieker, 2003].

In view of the primacy of human relationships for mental health it is not surprising that higher levels of attachment security are associated with higher levels of subjective well‐being and more effective coping [Mikulincer and Shaver, 2007, 2009]. One influential model of adult attachment characterizes individuals with an anxious attachment style as generally preoccupied with ideas of rejection or abandonment while individuals with an avoidant attachment style tend to avoid close relationships, remaining distant and detached from others [Fraley et al., 2000]. The link between high levels of either attachment related avoidance or anxiety and higher levels of psychological distress including greater levels of anxiety and depression is now well established [Blatt and Levy, 2003; Muris et al., 2001]. This is suggestive of poorer emotional regulation in these individuals. There is preliminary evidence that different mechanisms may mediate the link between each attachment style and psychological distress. For example, while hypersensitivity to emotional cues mediates the link between attachment anxiety and distress, refusal of social support appears to mediate the link with attachment avoidance [Wei et al., 2005]. These findings suggest that higher (and therefore less adaptive) levels of attachment related anxiety or avoidance may compromise an individual's ability to cope with a significant interpersonal stressor—namely the experience of an affective loss. In addition, an individual's attachment style may differentially mediate the experience of distress following such an event.

A characterization of the neural structure associated with anxious and avoidant attachment styles may help elucidate their robust association with psychological distress and provide a preliminary understanding of those brain regions implicated in poor affect‐ or emotion‐regulation. In addition, such an investigation may shed light on individual differences in the ability to cope with affective loss. Animal models suggest that early attachment experiences may influence brain development resulting in permanent structural and functional alterations, particularly within the limbic system [Fish et al., 2004; Insel and Young, 2001; Moriceau and Sullivan, 2005; Zimmerberg et al., 2003]; such alteration are thought to account for individual differences in cognitive performance and social behavior [Fish et al., 2004; Zimmerberg et al., 2003]. For example, variations in the amounts of maternal arched‐back nursing and liking/grooming in rat pups influence synaptogenesis and neuronal survival in the hippocampus and results in phenotypic differences in learning, memory, object recognition, and response to stress [Fish et al., 2004].

So far, however, there have been only few studies that have examined the neural correlates of attachment in humans [Dawson et al., 2001; Gillath et al., 2005; Vrtic̆ka et al., 2008]. These functional imaging studies have reported that differences in attachment style are associated with different responses in brain regions implicated in reward and threat processing [Vrtic̆ka et al., 2008]. Extant studies, however, have not investigated the structural correlates of attachment style; it is therefore unclear whether differences in attachment style are associated with gray matter alterations in humans. Furthermore, prior studies have not examined the interaction between attachment style and affective loss on brain structure; thus, at present little is known about the neuronal mechanism through which attachment style moderates the ability to cope with affective loss.

Here we used voxel‐based morphometry (VBM), a whole‐brain semi‐automated technique for characterizing structural brain differences in vivo [Ashburner and Friston, 2000; Mechelli et al., 2005], to examine for the first time the association between attachment style, the number of affective losses an individual has experienced and brain structure in a clinically healthy sample. In particular, we: (i) identified the structural correlates of anxious and avoidant attachment style; (ii) characterized the structural correlates of affective loss (including separation, ending of a relationship and death of a loved one); and (iii) tested the hypothesis that the impact of affective losses on gray matter volume is moderated by attachment style. In view of the association between symptoms of depression and anxiety and attachment‐related anxiety and avoidance traits, we hypothesized that differences in these traits would be associated with differences in gray matter volume in regions implicated in emotion regulation, particularly the amygdala, anterior cingulate cortex, orbitofrontal cortex, insula and inferior temporal pole [see Phan et al., 2004 for a review]. Furthermore, we expected that the impact of affective loss would moderated by individual differences in attachment style, consistent with the results of behavioral studies [Sbarra, 2006].

METHODS

Participants

Thirty‐two healthy volunteers without a history of psychiatric or neurological illness were recruited through local advertising. The sample comprised 17 females and 15 males with a mean age of 25.2 and a standard deviation of 4.3.

Psychological Assessment

IQ was assessed using the Wechsler Abbreviated Scale of Intelligence [Wechsler, 1999]. Attachment style was assessed in terms of anxiety and avoidance traits using the revised version of the Experiences in Close Relationships inventory [ERC‐R; Fraley et al., 2000]. This 36‐item questionnaire is specifically designed to assess individual differences in attachment style. The Anxiety subscale (attachment‐related anxiety, AR‐Anx) relates to the extent to which people are insecure vs. secure about their partner's availability and responsiveness and taps fears of rejection or abandonment; the Avoidance subscale (attachment‐related avoidance, AR‐Avd) relates to the extent to which people are uncomfortable vs. secure being in close proximity to others and taps fear of intimacy and discomfort with closeness or dependence. Each item is rated on a scale ranging from 1 (strongly disagree) to 7 (strongly agree); higher scores indicate higher levels of attachment anxiety and attachment avoidance. For both scales, reliability is estimated to be 0.90 or higher [Sibley and Liu, 2004] and normative values are available (attachment‐related anxiety: mean = 3.64; SD = 1.33; attachment‐related avoidance: mean = 2.93; SD = 1.18). Affective losses were assessed using a subset of questions from the List of Threatening Experiences Questionnaire (LTE‐Q) [Brugha and Cragg, 1990]. Specifically, we used items 3, 4, and 5 to establish the number of affective losses in relation to loss of a relative, loss of a close friend or separation from a spouse within the previous five years. Analyses were performed using SPSS 15.0 software.

Magnetic Resonance Imaging

A whole brain T1‐weighted structural brain image comprising of 180 sagittal slices was acquired from each participants using a 1.5T GE (General Electronics, Milwauke, USA) magnetic resonance imaging scanner at the Institute of Psychiatry. Image matrix was 256 × 180 (Read x Phase) resulting in a final resolution of 0.93 × 0.93 × 1.2 mm³, a repetition time (TR) of 8.592 ms and an echo time (TE) of 3.8 ms.

Data Analysis

VBM was performed using SPM8 software [Friston, 2003] running under Matlab 7.0. First, all structural images were manually reoriented to place the anterior commissure at the origin of the three‐dimensional Montreal Neurological Institute (MNI) coordinate system. The images were then segmented into gray and white matter partitions using the unified segmentation procedure described in Ashburner and Friston [ 2005]. The Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL) algorithm [Ashburner, 2007] was used to spatially normalize the segmented images; this procedure maximizes sensitivity and accuracy of localization by registering individual structural images to an asymmetric custom T1‐weighted template derived from the participants' structural images rather than a standard T1‐weighted template based on a different sample [Ashburner, 2007]. Because this procedure generated a template from our group of individuals, the resulting images of average size were spatially normalized to MNI space using an affine spatial normalization. An additional “modulation” step consisted of multiplying each spatially normalized gray matter image by its relative volume before and after normalization; this ensured that the total amount of gray matter in each voxel was preserved. Finally, the resulting gray matter images were smoothed using a 8‐mm isotropic kernel at full width half maximum (FWHM) in order to ensure normal distribution of the data as required by subsequent parametric tests. An interaction term was computed which encoded the interaction between AR‐Anx and AR‐Avd, by multiplying the AR‐Anx and AR‐Avd vectors after mean‐centering them; using the same procedure, two additional interaction terms were computed which encoded the interaction between AR‐Anx and number of affective losses and the interaction between AR‐Anx and number of affective losses respectively. A multiple regression analysis was then performed to examine the extent to which gray matter volume was associated with (i) AR‐Anx; (ii) AR‐Avd; (iii) number of affective losses during the previous 5 years; (iv) interaction between AR‐Anx and AR‐Avd; (v) interaction between AR‐Anx and number of affective losses; (vi) interaction between AR‐Avd and number of affective losses. Age and gender were modeled as covariates of no interest; this resulted in a total of 8 covariates including three main effects, three interaction terms, and two covariates of no interest. In addition, the proportional normalization option was used to discard global nuisance effects due to individual variability in overall brain size. Inferences were made at P < 0.05 after false‐rate‐discovery (FDR) correction for multiple comparisons across the whole brain. When significant effects were not detected, we report trends significant at P < 0.001 (uncorrected) for completeness but in the discussion we focus on effects significant at corrected level.

RESULTS

Average IQ was 120.1 (Standard Deviation, 8.4; Range, 102–135). Participants reported an average of 1.34 (standard deviation, 1.21; range, 0–‐4) affective losses within the previous five years. The average AR‐Anx and AR‐Avd scores were 3.07 (standard deviation, 1.22; range, 1.22–5.83) and 3.23 (standard deviation, 0.96; range, 1.05–5.00) respectively. These values are comparable to existing norms (see Methods). A significant positive association was found between AR‐Anx and AR‐Avd (Pearson Correlation = 0.453; P‐value = 0.009). Correlation analyses also indicated that the number of affective losses was positively associated with AR‐Anx (Pearson Correlation = 0.478; P‐value = 0.006) but not with AR‐Avd (Pearson Correlation = 0.185; P‐value = 0.309). Finally, AR‐Avd, AR‐Anx, and number of affective events were not significantly associated with age, gender or IQ (P > 0.05).

Main Effect of Attachment‐Related Anxiety

AR‐Anx was positively associated with gray matter volume in the left lateral orbital gyrus (x = −43; y = 26; z = −11; z‐score = 4.66; cluster size: 293) and negatively associated with gray matter volume in the right middle and inferior temporal gyrus of the anterior temporal pole (x = 50; y = −26; z = −26; z‐score = 4.05 cluster size: 488) (see Fig. 1).

Figure 1.

Regions where gray matter volume was significantly associated with attachment‐related anxiety (AR‐Anx) at P < 0.05 (after FDR correction across the whole brain). The left lateral orbital gyrus (top) showed a positive correlation with AR‐Anx; in contrast, the right anterior temporal pole (bottom) expressed a negative correlation with AR‐Anx. Plotted values are adjusted for age and gender of participants. GMV = gray matter volume measured in terms of mm³ of gray matter per voxel. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Main Effect of Attachment‐Related Avoidance

There were no regions positively or negatively associated with attachment‐related avoidance after correction for multiple comparisons across the whole brain. When we lowered the statistical threshold to P < 0.001 (uncorrected), we detected a positive association at trend level in the superior temporal gyrus of the left anterior temporal pole (x = −27; y = 5; z = −23; z‐score = 3.9 cluster size: 135) and the left inferior semilunar lobule of the cerebellum (x = 24; y = −75; z = −49; z‐score = 3.6 cluster size: 125).

Interaction Between Attachment‐Related Anxiety and Avoidance

No regions showed a significant interaction between AR‐Anx and AR‐Avd after correction for multiple comparisons across the whole brain. However, when lowering the statistical threshold to P < 0.001 (uncorrected), we detected a trend for an interaction in the left cerebellum (x = −44; y = −75; z = −34; z‐score = 3.9 cluster size: 331); in this region the positive association between AR‐Avd and gray matter volume was more pronounced in individuals with high AR‐Anx than those with low AR‐Anx.

Main Effect of Affective Losses

The number of affective losses was positively associated with gray matter volume in the cerebellum (−x = −36; y = −75; z = −29; z‐score = 4.7 cluster size: 835). No negative correlation between number of affective losses and gray matter volume was detected after correction for multiple comparisons. However, when lowering the statistical threshold to P < 0.001 (uncorrected), we detected a trend for a negative association in the left precuneus (x = −31; y = −80; z = −11; z‐score = 4.0 cluster size: 131) and the left lateral orbital gyrus (x = −43; y = 26; z = −11; z‐score = 3.8 cluster size: 53). In other words, greater experience of affective losses tended to be associated with reduced gray matter volume in these regions.

Moderation of the Main Effect of Affective Losses by Attachment Style

We tested the hypothesis that the impact of affective loss would be moderated by individual differences in attachment style. The main effect of affective losses in the left cerebellum was significantly moderated by the level of AR‐Avd (x = −39; y = −75; z = −30; z‐score = 5.3 cluster size: 1995). To best illustrate this interaction, we plotted the relationship between number of affective losses and gray matter volume for individuals with AR‐Avd lower and higher than the sample average separately (see Fig. 2); this showed that the number of affective losses and gray matter volume were positively associated in the subsample of individuals with lower than average AR‐Avd but negatively associated in the subsample of those with higher than average AR‐Avd. In contrast, the main effect of affective losses in the left cerebellum was not significantly moderated by the level of AR‐Anx.

Figure 2.

Region of the left cerebellum where the effect of number of affective losses was moderated by attachment‐related avoidance (AR‐Avd) at P < 0.05 (after FDR correction across the whole brain); blue circles and the solid line refer to individuals with lower than average levels of AR‐Avd (scores <3.23) whereas red triangles and the dashed line refer to individuals with higher than average levels of AR‐Avd (scores >3.23). Plotted values are adjusted for age and gender of participants. GMV = gray matter volume measured in terms of mm³ of gray matter per voxel. It should be noticed that participants were divided into two groups with lower and higher than average levels of AR‐Avd for visualization purposes only; the finding that the effect of number of affective losses was moderated by attachment‐related avoidance was based on a multiple regression analysis with the individual regressors and the interaction term rather than a group comparison. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

DISCUSSION

The aim of the present investigation was to examine for the first time the association between attachment style, affective loss, and brain structure in clinically healthy adults. We found that individual differences in attachment‐related anxiety are associated with differences in gray matter volume in the right temporal pole and left lateral orbitofrontal cortex. In addition, attachment style moderated the impact of affective losses on gray matter volume, particularly in the left cerebellum. Although we did not assess early attachment directly, early attachment experience may contribute to some of these structural brain differences associated with attachment‐related anxiety and avoidance in adulthood.

The right anterior temporal pole, where gray matter volume negatively correlated with attachment‐related anxiety, has long been considered part of a extended limbic system and is thought to be play a key role in emotional processing; a recent review proposes that this region might be responsible for binding complex, highly processed perceptual inputs to visceral emotional responses [Olson et al., 2007]. In patients with major depression, this region is part of a distributed network which shows decreased glucose metabolism at rest [Fujimoto et al., 2008] and increased activation during voluntary down‐regulation of sad feelings [Beauregard et al., 2006]; interestingly, these alterations were detected in the right but not the left anterior temporal cortex, suggesting a possible hemispheric lateralization which was also apparent in the present investigation. Functional alterations in the right anterior temporal cortex are not specific to major depression but have also been reported in individuals with social phobia anticipating making a public speech [Lorberbaum et al., 2004]. Our finding of a negative association between attachment‐related anxiety and gray matter volume in this region is therefore consistent with its implication in psychopathology, particularly depression and social anxiety.

The left lateral orbitofrontal gyrus, where gray matter volume positively correlated with attachment‐related anxiety, plays a critical role in the regulation of both positive and negative emotions [Mak et al., 2009] and has been consistently implicated in mood and anxiety disorders [Ballmaier et al., 2004]. In patients with obsessive compulsive disorder, which is classified as an anxiety disorder, this region shows hyperactivation during the processing of disgust‐inducing visual stimuli [Stein et al., 2006] and its resting state activation is positively correlated with symptom severity [Busatto et al., 2000]. Further evidence for the implication of left lateral orbitofrontal gyrus in obsessive compulsive disorder comes from a recent VBM investigation which reported reduced gray matter volume in this region in medication‐free patients relative to age‐matched controls [van den Heuvel et al., 2009]. In addition, a wealth of neuroimaging and post‐mortem studies have implicated the left lateral orbitofrontal gyrus in the neuropathology of major and bipolar depression [Blumberg et al., 1999; Cotter et al., 2005; Drevets 1999; Dunn et al., 2005; Haldane and Frangou, 2004; Monks et al., 2004]. In contrast with the increases typically found in obsessive compulsive disorder, patients with depression tend to express attenuated activation in this region [Altshuler et al., 2008]. Our finding of a positive association between attachment‐related anxiety and gray matter volume and gray matter volume in the left lateral orbitofrontal gyrus provides further support for the view that this region is implicated in emotion regulation and affective psychopathology.

The observation of both a positive and a negative association between attachment‐related anxiety and gray matter volume may be surprising; however, it is consistent with previous evidence that experience‐dependent neuroplasticity may be expressed in terms of reorganization of gray matter volume as opposed to either increases or decreases [Draganski et al., 2006; Maguire et al., 2000]. For instance, Maguire et al. [ 2000] reported that gray matter volume correlated with the amount of time spent as a taxi driver positively in the posterior but negatively in the anterior hippocampus. Further studies are required in order to better understand the behavioral consequences of increases and decreases respectively in the context of experience‐dependent neuroplasticity [Draganski and May, 2008].

The main effect of attachment‐related avoidance was significant only at trend level; however, attachment‐related avoidance was found to moderate the impact of affective losses in the left cerebellum. Although this region is not part of the limbic system, it is anatomically and functionally connected with prefrontal areas and subcortical limbic structures which regulate emotional processing [Schmahmann, 2000]. Consistent with this observation, structural and functional cerebellar abnormalities have been reported in many psychiatric disorders associated with dysregulation of affect, such as bipolar disorder, major depressive disorder, anxiety disorders, and attention deficit hyperactivity disorder [Baldacara et al., 2009; Schmahmann et al., 2007]. The role of the cerebellum in the regulation of affect is further supported by a recent report that inhibition of cerebellar function using repetitive transcranial magnetic stimulation (rTMS) results in emotional disturbance and negative mood [Schutter and van Honk, 2009]. Our investigation extends the results of previous studies by showing for the first time that the relationship between number of affective losses and cerebellar gray matter volume is significantly moderated by anxiety‐related avoidance; this aspect of our findings points to a neuronal mechanism through which attachment style may mediate individual differences in responses to affective loss.

Attachment‐related anxiety and avoidance were modestly correlated consistent with previous findings (e.g. [Wei et al., 2005]). However, we were able to assess any effect specific to either AR‐Anx or AR‐Avd by modeling the two variables independently within the same statistical model. The finding of different neural correlates for AR‐Anx and AR‐Avd corroborates psychological models postulating two affective dimensions to explain individual differences in attachment, and is consistent with the results of previous functional neuroimaging studies [Gillath et al., 2005; Vrtic̆ka et al., 2008].

Within our sample, we also found that the number of affective events was positively associated with attachment‐related anxiety (see Results). This association could reflect a causal relationship in either direction; equally, it may at least partly reflect difference in recall of affective information. It has been shown that autobiographical memory is associated with attachment style [Conway et al., 2004]. Specifically, individuals with higher levels of attachment anxiety have been shown to access more easily memories of negative experiences [Gillath et al., 2007]. As such, these individuals may be more prone to report the number of affective losses; by contrast, avoidant adults have been shown to have more difficulty recalling emotional experiences [Fraley et al., 2000]. Although this issue cannot be resolved on the basis of the present data, the observation of distinct main effects of attachment‐related anxiety and affective events at neuronal level indicates that these two variables are at least in part independent.

Within our sample, IQ did not significantly correlate with AR‐anxiety, AR‐avoidance or number of affective events; however, IQ is known to be associated with individual differences in brain structure [Haier et al., 2004] and has been shown to moderate behavioral responses to adversity [Sameroff and Rosenblum, 2006]. We therefore explored the impact of IQ on gray matter volume and its interaction with number of affective losses by performing an additional multiple regression analysis which included (i) number of affective losses; (ii) IQ; (iii) interaction between number of affective losses and IQ. This analysis did not detect any effects of IQ in regions modulated by attachment style or number of affective losses, even at trend level (P < 0.001 uncorrected); furthermore, we found no evidence that the impact of the number of affective losses on gray matter volume was moderated by individual differences in IQ (P < 0.001 uncorrected). This aspect of our findings might reflect the fact that intersubject variability in IQ was relatively small within our sample (see Methods).

This study has a number of limitations, most notably the use of a cross‐sectional design to assess the impact of affective losses on brain structure. Future studies would benefit from the use of a longitudinal design allowing the effects of attachment‐style and affective losses on gray mater volume to be estimated more accurately. In addition, affective losses were assessed over the previous five years only and the participant sample size was relatively small. Despite these limitations, this study demonstrates for the first time that individual differences in attachment style are associated with differences in brain structure, most notably in regions implicated in the regulation of emotion; furthermore, it points to a neuronal mechanism through which attachment style may mediate individual differences in responses to affective loss.