Association Between Nonparenting Adult’s Attachment Patterns and Brain Structure and Function

Adult Attachment

While attachment patterns established in childhood can change over the life course, attachment patterns in childhood are relatively stable over time, especially under conditions of low stress and high social support (Sroufe, 2005). Adult attachment patterns are assumed to be learned in childhood via the emotional bonds that are developed between parents and their children (Feldman & Downey, 1994). There are a number of psychometrically sound approaches to measuring and classifying adult attachment patterns, with all instruments differentiating between security and insecurity and subtypes (Ravitz, Maunder, Hunter, Sthankiya, & Lancee, 2010). A recent 25-year review of adult attachment measures reported that of the 29 instruments typically used to assess adult attachment, 11 demonstrated strong psychometric properties (Ravitz et al., 2010). We will comment on the two most common measures.

Considered the gold standard, the Adult Attachment Interview (AAI) is a narrative-based interview that is used to classify adult attachment via psycholinguistic qualities that reveal interviewees’ state of mind, for example, coherence versus noncoherence when adults are asked to describe how their parents behaved toward them as young children (Main, Kaplan, & Cassidy, 1985). Three main adult attachment patterns can be yielded, including secure or autonomous (George, Kaplan, & Main, 1984, 1988, 1996; Pearson, Cohn, Cowan, & Cowan, 1994), dismissing, and preoccupied, which are analogous to the childhood attachment patterns (i.e., secure Type B, anxious avoidant Type A, and anxious resistant Type C respectively; Ainsworth et al., 1978). A fourth pattern called unresolved, parallels disorganization (i.e., Type D). Adults classified as secure (continuous or earned; Type B) provide clear, direct, balanced (i.e., positive and negative accounts of their early childhood experiences with their parents), and coherent responses regarding their childhood attachment experiences, whereas adults classified as dismissing (Type A) undervalue attachment relationships and provide restricted and avoidant responses; adults classified as preoccupied (Type C) ruminate extensively over past attachment experiences and respond with psychological jargon, nonsense words, and childlike speech (Paley, Cox, Burchinal, & Payne, 1999; Westen, Nakash, Thomas, & Bradley, 2006). A significant relationship exists between early experiences with primary caregivers and later attachment-related representations (Steele et al., 2014).

Attachment patterns in childhood are linked with the quality of intimate relationships in adulthood (Bartholomew, 1993). Adults who are classified as having a secure pattern of attachment are more satisfied in their romantic relationships when compared with their insecure counterparts (Gleeson & Fitzgerald, 2014). Secure attachment is also negatively correlated with perceptions of stress, and positively correlated with resiliency, proactive coping strategies (Marriner, Caciolli, & Moore, 2014), self-reliance, self-regulation, and social competence in adulthood (Sroufe, 2005). Additionally, individuals who adopt a secure attachment pattern display fewer signs of emotional and behavioral disorders and are less likely to suffer from depression, anxiety, or excessive aggression in adulthood (Steele & Steele, 2013).

In contrast, insecure attachment strategies in adulthood are associated with problems in social, emotional, and mental domains (Fraley, 2002; Madigan, Atkinson, Laurin, & Benoit, 2013; van Ijzendoorn et al., 1999a), as well as health problems, especially inflammatory conditions over the life span (Puig, Englund, Simpson, & Collins, 2013). Insecurely attached adults are disproportionately more likely to exhibit an array of internalizing and externalizing behavioral problems including depression, anxiety, aggression, and attention-deficit hyperactivity disorder (Steele & Steele, 2013), which appear to also have negative consequences for adult intimate relationships (Paetzold, Rholes, & Kohn, 2015). These findings are in accordance with past research that indicates insecure attachment in adulthood is linked with a host of problems including the inability to establish long-term trusting relationships (Barlow, 2013).

Attachment and Neurodevelopment

During the period of establishment of the initial attachment pattern (typically, first 3 to 6 years of life), the human brain generates as many as 2 million synapses per second. This prolific production of synaptic connections enables the child’s brain to be especially adaptive to experience (Huttenlocher, 2009). Gradually, neuronal connections undergo systematic organization associated with experience including caregiving, wherein the most used pathways are retained and strengthened and the least used ones are eliminated or weakened (Pascual-Leone, Amedi, Fregni, & Merabel, 2005). Given the primary role of experiences with parents in infancy and indeed the evolutionary role of attachment in promoting infants’ survival (Strathearn, Fonagy, Amico, Montague, 2009), social-emotional and behavioral adjustment, experiences with parents are likely to contribute significantly to retention and elimination of synaptic connections across many brain regions. Indeed, we conjecture that the attachment patterns that children and adults demonstrate (secure vs. insecure) likely correlate with underlying changes to brain structure and function that arise from early formative experiences that may be observed in adulthood.

Improvements in neuroimaging technology have allowed researchers to explore correlations between attachment patterns and changes in brain structure (morphology) and function (physiology) in great detail. Several prominent procedures exist for monitoring brain activity, but the most common for attachment studies has been functional magnetic resonance imaging (fMRI). A high resolution and noninvasive procedure, fMRI uses the differing magnetic signals of oxygenated and nonoxygenated hemoglobin to map brain activity localized to the nearest millimeter. By monitoring this activity while exposing participants to certain stimuli, researchers can determine the importance of different brain regions in reacting to and processing different types of information. Thus, neuroimaging technologies, with fMRI chief among them, have been used by researchers to develop a far more detailed understanding of the effects of attachment behaviors on specific regions of the brain than in the past (Ulmer & Jansen, 2013). Another technique used to assess brain structure (not function) is called voxel-based morphometry (VBM), used to assess whole brain structural brain differences by quantifying gray matter concentrations in the whole brain (Ashburner & Friston, 2000; Mechelli, Price, Friston, & Ashburner, 2005).

The lobes of the brain, including frontal, parietal, occipital, temporal, and limbic regions, were originally a purely anatomical classification but have been shown to be related to different brain functions (Martin, 2008). Key brain areas of interest include those associated with executive (cortical) function, affective (emotion) processing and arousal, reward, sensory, social and cerebral functions, and stress. While no single brain region is solely responsible for a specific function, various brain regions do moderate functions, specifically:

Executive function is centered in the frontal lobes, including the right and left inferior frontal cortices, orbitofrontal cortex, superior frontal gyrus, dorsolateral prefrontal cortex, anterior cingulate cortex, medial frontal gyrus, left lateral orbital gyrus, left anterior gyrus, right middle frontal gyrus, prefrontal cingulated, and supplementary motor area. This region is the last to develop and is the most influenced by the environment.

Animal and Human Attachment Behaviors and Neurodevelopment

Although animal studies do not directly correlate with human experience, reviews of research have shown strong links between rodent and human maternal caregiving behaviors, linked to attachment and brain structure and function (Swain, Loberbaum, Kose, & Strathearn, 2007; Swain, 2008, 2011). Both humans and rodent species calibrate their HPA axes, an endocrine system responsible for regulating their response to stressful stimuli, through qualities of early maternal caregiving behavior and many neural regions affected by maternal behaviors in mice have human counterparts shown to react in a similar fashion (Swain, 2008). Likewise, the detrimental effect of poor early maternal caregiving behavior on emotional and behavioral development—particularly involving the HPA stress response system has been well documented in both rodent (Caldji, Diorio, & Meaney, 2000; Szyf, Weaver, Champagne, Diorio, & Meaney, 2005; Weaver et al., 2005; Weaver, Diorio, Seckl, Szyf, & Meaney, 2004) and human cases (Kidd, Hamer, & Steptoe, 2011; McGowan et al., 2009).

Numerous rodent studies have observed a clear connection between the frequency at which dams engage in affectionate maternal behaviors, linked to attachment, and the development of their pups’ HPA axis. Rodent pups whose mothers perform more nurturing behaviors (licking, grooming, and arched-back nursing) demonstrate a more moderate endocrinal response to stress and return more promptly to a prestress state than do their less nurtured peers (Szyf et al., 2005). Further, reviews of nonhuman animal research has also provided evidence of associations between attachment behaviors and neural development, particularly in basal forebrain structures, which are located to the front of and below the striatum, include the nucleus accumbens and link to reward (Swain et al., 2007). Damage to these forebrain structures, associated with reward, is linked to elimination of attachment behaviors among rodents, including nursing, breastfeeding, and nest building (Numan & Insel, 2003). Other areas involved in regulating rodent maternal behavior include the medial preoptic area of the hypothalamus, the ventral part of the bed nucleus of the stria terminalis (serves as major output pathway for the amygdala associated with affective processing), and the lateral septum (connected to the hippocampus, amygdala, hypothalamus, and cingulate gyrus linked to executive function, and affective and stress processing) (Leckman & Herman, 2002; Numan, 2007; Numan & Stolzenberg, 2009; Swain, 2008, 2011). With the exception of evidence from animal models on associations between early maternal behavior and offspring HPA axis function, much of the extant literature focuses on associations between brain structure or function and maternal behavior. Perhaps in animals, it is difficult to assess attachment behavior linked to neuroanatomic function, in the absence of parenting. Nonetheless, we require a review of evidence of associations between brain structure or function and nonparenting adults’ attachment behavior, linked to their own early maternal caregiving experience.

In humans, research has focused largely on brain structure and function and adult attachment behaviors in parents, but also among romantic partners. In addition to influencing the development of the HPA axis, attachment patterns have been associated with reward regions of the brain (including the basal ganglia, ventral striatum or nucleus accumbens, amygdala, hypothalamus, and hippocampus) and emotional and sensory processing (including the anterior cingulate, insula medial frontal, and orbitofrontal cortices) in parents (Swain, 2011). Further, reviews of the extant research has focused on the influence of becoming a parent on both attachment and brain structure and function (Strathearn et al., 2009; Strathearn, Li, Fonagy, & Montague, 2008), revealing the role of various reward circuits in reinforcing feelings of both romantic and maternal love (Vrtička, Sander, & Vuilleumier, 2012; Weisman, Feldman, & Goldstein, 2012). These feelings are associated with heightened functional responses in reward centers to various attachment stimuli (e.g., an image of a newborn baby, the sound of infant crying) among new parents, romantic partners, or other individuals experiencing strong attachment bonds (Swain, 2008; Weisman et al., 2012). While informative, well described brain structural and functional changes associated with the onset of pregnancy and parenthood (Strathearn et al., 2009; Strathearn et al., 2008) confound the evidence of linkages between attachment pattern and adult brain structure and function.

In summary, the association between human nonparenting adults’ attachment patterns and brain structure and function has not been systematically reviewed. Moreover, as changes have been observed coincident with becoming a parent (Leuner, Glasper, & Gould, 2010; Mayes, Swain, & Leckman, 2005), it is surprising that reviews have not examined the influence of early attachment experiences on nonparents’ brain structures and functions, as a baseline.

Attachment Classification

As previously mentioned, the original attachment categories established by Ainsworth et al. (1973) are secure (Type B) and insecure with two subcategories, namely insecure anxious avoidant (Type A) and insecure anxious resistant or ambivalent (Type C). Over the years, nomenclature relating to attachment research has expanded. For example, some researchers use the term anxious to describe either a specific type of insecure attachment (e.g., avoidant or dismissing or resistant/ambivalent) or both forms of insecure attachment, which can cause confusion when attempting to review attachment research. Originally, Ainsworth et al. (1978) described both subcategories of insecure attachment as “anxious,” (e.g., avoidant or dismissing and resistant or preoccupied); however, many refer to avoidant and anxious types, suggesting that anxious refers to the resistant category. Thus, for the purposes of this review, any study referring to insecure attachment as only “anxious” can be viewed as being interchangeable with Ainsworth’s “anxious resistant/ambivalent” classification or preoccupied in adults. The reason for this is that researchers’ descriptions of “anxious” attachment typically resemble similar descriptions Ainsworth provided for “anxious resistant/ambivalent” insecure attachment. That said, in order to preserve the integrity of this review article, the language used in each individual study as it relates to attachment will not be altered.

Reviewed studies employed participants’ category of attachment security as a variable with which to analyze brain structure and function. Seven studies treated “avoidant/dismissing” and “resistant/preoccupied” (anxious) attachment categories as separate variables (Benetti et al., 2010; DeWall et al., 2012; Gillath et al., 2005; Quirin et al., 2010; Vrtička et al., 2008; Vrtička, Bondolfi, et al., 2012) with two of those studies including an additional variable representing secure attachment (Quirin et al., 2010; Vrtička et al., 2008). Five studies used a continuous scale to assess degrees of security or insecurity, thus insecure attachment is represented as only one primary category not two (Buchheim et al., 2006; Galynker et al., 2012; Lemche et al., 2006; Riem et al., 2012; Warren et al., 2010). Two studies focused solely on participants’ levels of attachment avoidance or dismissing (Lenzi et al., 2013; Suslow et al., 2009), and another focused solely on attachment anxiety, that is insecurity (Donges et al., 2012). None focused on attachment disorganization (Type D) or A/C mixed attachment patterns.

Stimuli and Design

Studies included used varying stimuli to trigger neural regions associated with attachment. The majority of studies measured participants’ response to evocative images, most commonly faces expressing positive or negative emotions and masked by neutral expressions (Donges et al., 2012; Galynker et al., 2012; Suslow et al., 2009). Faces were typically of strangers (Donges et al., 2012; Galynker et al., 2012; Suslow et al., 2009), although one study used faces of individuals familiar to the participants (e.g., mother, close friend) as well as those of strangers (Galynker et al., 2012). Two studies (Donges et al., 2012; Suslow et al., 2009) employed standardized faces such as Ekman’s (Ekman & Friesen, 1976). Participants were asked to rank images by pressing buttons (Donges et al., 2012; Suslow et al., 2009). Other images besides faces were sometimes used. One study used images of children aged 6 to 12 months and asked participants at various points to either imitate the children’s expression or attempt to empathize with them (Lenzi et al., 2013). Two studies had participants view images of scenes with connotations considered positive (e.g., a mother playing with her baby, a tropical island scene), negative (e.g., a couple arguing, a bird covered in oil), or neutral (e.g., children playing in a sandbox; Buchheim et al., 2006; Vrtička, Bondolfi, et al., 2012). Participants were asked to rank images as positive or negative on a 4-point scale (Vrtička, Bondolfi, et al., 2012) or create a narrative based on the image displayed (Buchheim et al., 2006).

Four studies used alternative means of aural or visual stimuli (Gillath et al., 2005; Lemche et al., 2006; Riem et al., 2012; Warren et al., 2010). Gillath et al. (2005) described relationship scenarios to participants and asked them to either reflect on or suppress thoughts of these scenarios according to visual cues rendered in the form of a traffic light. Lemche et al. (2006) showed participants a series of subliminal sentences containing either nonsense or descriptions of unpleasant attachment experiences, followed by plainly displayed statements to which the participants responded by agreeing or disagreeing. Riem et al. (2012) measured the neural response of participants to sounds of infant crying. Finally, Warren et al. (2010) showed patients a series of pleasant and unpleasant words, each written in one of four colors, and had them indicate which color they saw via a control pad.

Two studies used simulations in which the participants thought they were playing a game with or against other players (DeWall et al., 2012; Vrtička et al., 2008). The games’ outcomes were manipulated to trigger attachment responses. In DeWall (2012), participants took part in a virtual ball-tossing game. Three players passed a “cyberball” back and forth. Unbeknownst to the participant, the other two “players” were part of the computer program. After the first round, the participant was excluded from the game by the other players, triggering feelings of social distress. In Vrtička’s et al. (2008), participants played a counting game. The program actively calibrated the game’s difficulty to the player’s level of success, assuring that each player both won and lost some rounds. The results of each round were followed by the words “won” or “lost” and an image of a smiling or frowning face, symbolizing an opponent. Both smiling and frowning faces could appear over either “won” or “lost” captions, allowing for a wider variety of emotional stimuli. Finally, two studies that were not fMRI studies, but rather VBM studies of brain structure, did not have participants engage in any sort of activity (Benetti et al., 2010; Quirin et al., 2010). Instead, they assessed participants’ attachment pattern (i.e., secure, avoidant, or anxious) and examined results for attachment-based differences in neural structure.

fMRI or VBM Data Acquisition

Five studies employed 1.5 Tesla scanners (Benetti et al., 2010; Buchheim et al., 2006; Gillath et al., 2005; Lemche et al., 2006; Vrtička et al., 2008) with Buchheim et al. (2006) using a Magnetom Symphony Scanner, Lemche et al. (2006) and Gillath et al. (2005) using a General Electric Neurovascular Signa MRI. Benetti et al. (2010) used a General Electric MRI. Gillath et al. (2005) indicate the use of a birdcage head-coil T2-weighted gradient with echo-planar imaging procedure and Lemche et al. (2006) reported using whole brain T1-weighted structural imaging. Vritikca et al. (2008) reported using whole-body INTERA system using standard head coil.

Six studies employed three Tesla scanners (DeWall et al., 2012; Galynker et al., 2012; Quirin et al., 2010; Riem et al., 2012; Vrtička, Bondolfi, et al., 2012; Warren et al., 2010), with Vrtička, Sander, et al. (2012) employing whole-body scanner and standard head coil and Quirin et al. (2010) indicated the use of a birdcage head coil. Warren et al. (2010) and Quirin et al. (2010) employed Siemens Allegra head-only scanner and Galynker (2012) used Phillips Intera and SENSE head coil. Riem et al. (2012) employed Phillips Achieva MRI and Dewall et al. (2012) employed Siemens Trio scanner. Three additional studies (Donges et al., 2012; Lenzi et al., 2013; Suslow et al., 2009) did not indicate the nature of their three Tesla MRI; however, Donges et al. (2012) and Suslow et al. (2009) reported using a single shot echo-planar sequence with parameter selection to minimize distortion and retain adequate signal to noise ratio and T2 sensitivity. Lenzie et al. (2013) only indicated that T2 functional data were collected, while Dewall et al. (2012) reported using T2-weighted graduated echo. Riem et al. (2012) reported T1-weighted anatomicals. Finally, T1 weighted three dimensional magnetization prepared rapid gradient echo were reported by Quirin et al. (2010). When indicated, the number of slices varied with 16 (Lemche et al., 2006), 24 (Gillath et al., 2005), 25 (Buchheim et al., 2006), 30 (Vrtička et al., 2008), 32 (Lenzi et al., 2013), 34 (Donges et al., 2012), 38 (Riem et al., 2012; Warren et al., 2010), 40 (DeWall et al., 2012; Suslow et al., 2009), and 180 in their VBM study (Benetti et al., 2010).

Neural Outcomes

All studies provided neuroimaging data describing the effects of attachment on brain structures and function. However, inconsistencies in attachment terminology were problematic. Although avoidant and anxious attachment behaviors are overlapping subsets of insecure attachment, several articles treated them as distinct categories. As such, the results of this study have been divided into overall insecure, avoidant, and anxious (resistant or ambivalent) attachment strategies. Again, neither disorganized attachment (Type D) nor A/C mixed patterns were mentioned in any of the studies that met inclusion criteria, so these categories were ignored. In brackets after brain areas, we indicate the associated function.

Anxious (resistant or ambivalent) attachment

Anxious attachment was correlated with heightened activity in the left anterior, middle, and medial frontal gyrus (executive), the left claustrum (reward), the left globus pallidus (reward), the right cerebellum (cerebral), the dorsal anterior cingulate cortex (executive), and the anterior insula (social; DeWall et al., 2012; Donges et al., 2012). When reflecting on negative attachment scenarios such as conflict in an emotional relationship, a breakup, or the death of a partner, participants with an anxious attachment strategy displayed heightened activity in the left anterior temporal pole (affect) and left hippocampus (affect), and low levels of activation in the orbitofrontal cortex (executive; Gillath et al., 2005). Participants displaying an anxious attachment strategy experienced increases in activity in the right amygdala (affect) and left parahippocampal cortex (affect) when responding to negative and positive social stimuli, but only while instructed to make spontaneous emotional judgments (Vrtička, Bondolfi, et al., 2012). Social cues signifying reproach or punishment (i.e., an angry face) evoked a particularly strong response in the left amygdala (affect) of participants with attachment anxiety, suggesting an increased sensitivity to social punishment (Vrtička et al., 2008). Compared with securely attached individuals, those who displayed anxious attachment strategies possessed increased gray matter in the left lateral orbital gyrus (executive; Benetti et al., 2010), and decreased gray matter in the anterior temporal pole (affect; Benetti et al., 2010) and left hippocampus (affect; Quirin et al., 2010). Table 1 summarizes the findings.

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Table 1.

Association between brain regions, functions and attachment pattern.

Region	Subregion	Function/Behavior	Attachment Pattern	References
Executive
Frontal Lobe	Right inferior frontal gyrus	Risk aversion.	Insecure	Gillath et al., 2005
	Left inferior frontal gyrus	Impulse control and risk aversion.	Insecure	Gillath et al., 2005
	Orbitofrontal cortex	Decision making and expectation; Integration of sensory information, emotion and reward. Associated with substance abuse, attention deficit hyperactivity disorder.	Secure Insecure Anxious	Gillath et al., 2005; Lenzi et al., 2013; Warren et al., 2010
	Superior frontal gyrus	Self-awareness in coordinating actions with the sensory system.	Insecure	Gillath et al., 2005; Warren et al., 2010
	Dorsolateral and bilateral-lateral prefrontal cortex	Planning, organization, and regulation of actions, working memory, risky and moral decisions, relationships.	Insecure Avoidant	Gillath et al., 2005; Vrticka et al., 2012; Warren et al., 2010
	Anterior cingulate cortex	Autonomic functions (e.g. regulation blood pressure and heart rate), reward anticipation, decision making, empathy, impulse control, and emotion. Associated with obsessive-compulsive disorder.	Secure Insecure Avoidant Anxious	Gillath et al., 2005; Lenzi et al., 2013; Vrticka et al., 2012; Warren et al., 2010
	Left posterior cingulate	Pain and episodic memory retrieval.	Insecure	Gillath et al., 2005; Vrticka et al., 2012
	Medial frontal gyrus	Decision making.	Anxious	Donges et al., 2012
	Left lateral orbital gyrus	Executive function and its link to reward (approach and withdraw).	Anxious	Benetti et al., 2010
	Left anterior gyrus	Emotion and behavior.	Anxious	Martin, 2008
	Right middle frontal gyrus	Attention.	Anxious Avoidant	Donges et al., 2012
	Prefrontal cingulate	Action monitoring (correcting errors in behavior).	Avoidant	Vrticka et al., 2012
	Supplementary motor area	Planning complex movements, coordinating movements involving both hands.	Avoidant	Lenzi et al., 2013
Affective Processing/Arousal
Temporal Lobe	Amygdala	Memory consolidation, emotional reactions. Left amygdala associated with social anxiety, obsessive-compulsive disorders, and posttraumatic stress.	Secure Insecure Avoidant Anxious	Lemche et al., 2006; Lenzi et al., 2013; Riem et al., 2012; Suslow et al., 2009; Vrticka et al., 2008; Vrticka et al., 2012
	Hippocampus	Consolidation of information from short-term to long-term memory, spatial navigation, stress response.	Insecure Avoidant Anxious	Gillath et al., 2005; Quirin et al., 2010
	Anterior temporal pole	Language, cognition.	Anxious	Gillath et al., 2005
	Left parahippocampal cortex	Memory encoding and retrieval, visual memory. Associated with schizophrenia.	Anxious	Vrticka et al., 2012
	Middle temporal gyri	Recognition of known faces, accessing meaning while reading.	Insecure	Lemche et al., 2006
Reward
Subcortical Structures	Ventral caudate	Learning and memory, feedback processing.	Avoidant Insecure	Riem et al., 2012; Vrticka et al., 2012
	Ventral putamen	Regulates movements and influences learning.	Insecure	Lemche et al., 2006
	Striatum	Visual working memory, evaluating rewards. Associated with risk-taking behavior.	Secure Avoidant	Lemche et al., 2006; Vrticka et al., 2008
	Ventral tegmental area	Motivation, cognition, processing emotion. Associated with drug addiction and psychiatric disorders (e.g. schizophrenia).	Avoidant	Vrticka et al., 2008
	Left claustrum	Communication between hemispheres of the brain.	Anxious	Donges et al., 2012
	Left globus pallidus	Voluntary movement. Associated with schizophrenia.	Anxious	Donges et al., 2012
Sensory
Occipital Lobe	Left occipital cortex	Visual processing.	Insecure	Buchheim et al., 2006
	Occipital-temporal areas	Visual processing and memory.	Avoidant	Buchheim et al., 2006
Parietal Lobe	Somatosensory cortices	Respond to surface or internal state of the body.	Avoidant	Suslow et al., 2009
Social
Insular Cortex	Insula	Consciousness, emotion, homeostasis, motor control, self-awareness, interpersonal experiences. Associated with addiction and emotional dysregulation.	Avoidant Anxious Insecure	Donges et al., 2012; Suslow et al., 2009, 2012
Cerebellum
	Right cerebellum	Coordination, balance and voluntary movement on right side of body, language, regulating fear and pleasure responses.	Anxious	Benetti et al., 2010; Donges et al., 2012