Demystifying Love:
Modern Biological Techniques Measuring Attraction, Love And Relationships
Kyra Lubbers
University of Amsterdam
Name: Kyra Lubbers (6046223), MSc in Brain and Cognitive Sciences, Cognitive Science Track, University of Amsterdam
Date: 17-08-2015
Version: First version
Supervisor: Prof. dr. Jan Hindrik Ravesloot Co-assessor: Prof. dr. Cyriel Pennartz
Abstract
Love is an important motivator of human behavior. It drives partner selection, reproduction and motivates couples to stay together to care for their offspring; contributing to survival of the species. To measure love, most studies rely on questionnaires and self-reports, which are highly subjective. This thesis reviews the literature to investigate whether modern biological measurement techniques are able to quantify the strength of love and relationships objectively. Modern techniques appear to fall short in measuring compatibility between potential partners, as stimulus presentation is limited in both
quantity and quality. However, when it comes to measuring the quality and stability of love and relationship, several markers show potential. These markers include muscle activity, hormone levels and neural activation patterns. Most promising is the blurring of neural representations of the self and the other that seems to occur as relationships grow stronger. However, these measures are highly dynamic, and there are also large individual differences, which complicate the determination of the strength of love for a single individual. Therefore, we conclude that modern biological measurement techniques are unable to provide an objective measure of love.
Introduction
Throughout history love has been the inspiration for poets, writers, and philosophers. Around 385-310 BCE the Greek philosopher Plato described how Aristophanes explained the origin of love. According to this myth, humans originally had four arms, four legs, two faces and two sets of genitalia. They possessed an enormous strength, threatening to overpower the gods. To avoid this, Zeus used his lightning to split all humans, leaving them with two legs, two arms, one head and one set of genitalia. Even though their wounds healed, the humans became miserable, felt incomplete, and spent the rest of their lives searching for their other halves. It was said that if two halves found each other they would feel unified, and could find no greater joy than spending the rest of their lives together. Even though Aristophanes’ explanation of love is considered to be a satirical reference to creation myths present at that time, it shows that humans have been interested in the origin of love for a long time.
It took until 1992 for love to be recognized as a universal phenomenon, when Jankowiak & Fisher (1992) proved its presence in at least 88,5% of 166 studied human societies. Before that time, historians thought that love originated in 12th century Europe. It was assumed that only the fortunate elite had time to appreciate the feelings associated with love (Shaver, Morgan & Wu, 1996). The next obstacle for love as a research topic was its definition. According to the general public love is an emotion (Fehr & Russell, 1984). Even though some scholars attempted to define love as a basic emotion (Shaver, Morgan & Wu, 1996), love does not meet the criteria. Basic emotions are of short duration while love can last a lifetime, and love can lead to a variety of emotions rather than just one (Aron et al., 2005; Ekman & Cordaro, 2011). Rempel & Burris (2005) suggested that love should be defined as a motivational state, with the protection and preservation of the well-being of an object of value as goal. The idea that love is a motivation or drive that leads to different emotions has thus far been supported (Fisher et al., 2005; Cacioppo et al., 2012; Diamond and Dickenson, 2012; Song et al, 2015). Nowadays, different types of love are distinguished. Distinctions can be made based on the object of love, such as marital love, parental love, unconditional love, romantic love, and love towards a friend. Moreover, different stages of love have been described, such as short term passionate love,
which is related to the beginning of new relationships, and long term compassionate love, which best describes the love felt in long term romantic relationships (de Boer et al., 2012).
Many early studies on love and relationships relied on self-reports, which led to the
development of the first love-questionnaire in 1977 (Dion & Dion, 1973; Hatfield & Sprecher, 1986). According to the subscales of this questionnaire, the passionate love scale (PLS; Hatfield & Sprecher, 1986), love consists of emotional, cognitive and behavioral components. Emotional components include physiological arousal, feeling positive while together and negative while apart, and the longing for an exclusive relationship and intimacy. Cognitive components include increased and intrusive attention towards another, the idealization of the other and your relationship, and the desire to get to know each other. Finally, behavioral components are the desire to study the other person and to know what they feel, maintaining physical closeness to the other person, and serving or helping them. The PLS has been frequently used in love research and is still used today (Bartels & Zeki, 2000; Song et al., 2015; Langeslag et al., 2015), suggesting that these components of love are still relevant.
Even though the PLS appears to be a reliable questionnaire, it is highly subjective. Since the development of the PLS, many new biological techniques have been developed, such as
skin-conductance measurements and neuroimaging techniques. These measures enable us to study physical and neural correlates of love and relationships. Nowadays, love is studied in various scientific disciplines, including cognitive-, neuro- and behavioral science. These studies are of clear scientific importance, as they expand our knowledge about the biological and neural correlates of love and positive emotional states, important motivators of human behavior. Moreover, interdisciplinary research is important for understanding this complex construct, as changes on a chemical level are likely to influence behavior or neural activation patterns, and vice versa.
In this thesis, we will review literature on love and relationships to see whether modern biological techniques can objectively measure love. For each stage leading up to long term romantic relationships we will discuss the known psychological, biological, and neural love correlates. Firstly, we will focus on the main cause of falling in love; meeting another person we feel attracted to. We
will describe what characteristics determine attractiveness and what mechanisms are used to detect them. Secondly, we will investigate the effects of early stage passionate love, again on a
psychological, physical, chemical and neural level. Thirdly, we will focus our attention on long term relationships, to investigate what mechanisms allow romantic partners to form and maintain long lasting relationships. Subsequently, we will discuss whether biological measurement techniques can objectively measure the strength of love and relationships. Finally, we will cover the limitations of the literature, and provide future directions.
Partner selection
From an evolutionary perspective, successful reproduction is essential for species survival. At the same time, reproduction is costly, as resources have to be allocated to courtship, birth, and the care and protection of the offspring, which makes the parent more vulnerable to predation. It has been suggested that throughout evolution mammals have developed biological mechanisms that help select the optimal mating partner (Fisher et al., 2005). Following the main question of this thesis, we will review the literature on partner selection to see whether modern techniques could be used to measure interpersonal attraction objectively. We will describe what characteristics influence the attractiveness of an individual, which mechanisms allow us to select a good partner, and what factors influence our sensitivity to these, often subtle, cues. Afterwards, we will discuss how our attractiveness ratings relate to the actual partner choices individuals make in life.
Attractiveness characteristics
The genetic quality of a partner is important as genes are passed on during reproduction, influencing the offspring’s health. Some phenotypic characteristics provide clues about an individual’s genetic make-up. Body symmetry is such a characteristic, which is suggested to reflects embryo’s ability to cope with stressors during ontogeny. Good genes would allow all available resources to be allocated to reaching perfect bodily symmetry, instead of the correction of genetic deficiencies (Waddington, 1957). Fluctuating asymmetry (FA) is used to describe the extent to which one’s
physical features deviate from perfect symmetry, in which low FA represents high symmetry (Thornhill et al., 2003). Low FA values have been related to a cascade of health benefits (Thornhill et al., 2003).
Humans seem to be highly sensitive to body symmetry, as multiple studies have confirmed that individuals with low FA are rated more attractive compared to individuals with higher FA (Grammer et al., 1994; Perret et al., 1999; only for female faces: Penton-Voak et al., 2001; Abend et al., 2015). Interestingly, a study by Scheib et al (1999) found that symmetrical faces were even rated more attractive when every indication of facial symmetry was eliminated, and only the left or right half of the face was shown. Facial masculinity or femininity, known as sexual dimorphism, was considered as a cause of this effect (Penton-Voak et al., 2001). As sexual dimorphism remains constant when faces are halved, it could explain the persistent attractiveness of halved stimuli of symmetrical faces. However, in their study they did not find a correlation between symmetry and masculinity, suggesting that symmetric faces possess additional cues supporting their attractiveness (Penton-Voak et al., 2001).
On a whole body level attractiveness is predominantly influenced by body shape and body weight, which is sometimes measured relative to body size in the body mass index (BMI, body weight divided by body length in meters squared). While men prefer women a low waist-to-hip ratio (WHR), equaling a more curvaceous body type, women seem to be attracted to a low waist-to-chest ratio (WCR), representing broad shoulders and chest and a narrow waist (Singh, 1993; Tovée et al., 1999; Tovée & Cornelissen, 2001). In addition, Swami and colleagues (2007) found that body weight was a strong predictor of an individual’s overall attractiveness ratings. In general, women with a BMI of 18-20 are rated most attractive, which is also the BMI value that is suggested to be the healthiest and optimal for female fertility (Tovée & Cornelissen, 2001). The relative importance of body shape and body weight as attractiveness measures is largely gender dependent. Studies have shown that in women 80% of variance in attractiveness could be explained by BMI, irrespective of whether images were rated by males or females (Swami & Tovée, 2006; Tovée & Cornelissen, 2001). In men on the other hand, shape seems to be most important, as the WCR explains more variance in attractiveness ratings than BMI (Tovée et al., 1999).
Attractiveness cannot only be perceived visually, it can even be smelled. Several studies have shown that the body odor of symmetrical men is rated as more attractive compared to asymmetrical men, especially by fertile women (Gangestad & Thornhill, 1998b; Rikowski & Grammer, 1999; Thornhill & Gangestad, 1999b; Thornhill et al., 2003). Body odor is not only related to symmetry, but also contains information about the major histocompatibility complex (MHC), a DNA sequence that codes for cell-surface receptors that help trigger immune responses when confronted with foreign molecules, such as pathogens (Wedekind et al., 1995). Heterozygosity in the MHC complex can be considered a health benefit, as it enables the immune system to recognize a larger variety in foreign molecules. Furthermore, selecting a partner with dissimilar MHC alleles is beneficial for reproduction as it heightens the chance of heterozygous progeny. Studies have shown that body odors of individuals with dissimilar MHC alleles, or body odors of heterozygotes, are rated more attractive compared to body odors of individuals with MHC alleles similar to the rater (Wedekind et al., 1995; Wedekind & Füri, 1997; Thornhill et al., 2003, but see also Hedrick & Black, 1997; Ihara et al., 2000).
Interestingly, participants in the study by Wedekind & Füri (1997) reported that the odor of
MHC-dissimilar individuals reminded them of their (ex)partners, suggesting that this attractiveness characteristic could influence partner choice outside of laboratory environments. In addition to its potential health benefits, the attraction to dissimilarity might be explained by an avoidance of similarity and the scent of self, as to avoid inbreeding (Wedekind & Füri, 1997).
Our auditory system also appears to be able to detect attractiveness. The effort put into achieving bodily symmetry during ontogeny appears to go beyond our external visual appearance, and is presumed to affect our inner organs as well. It has been suggested that our vocal chords, which are of vital importance for our social development, can be influenced by prenatal stress. Studies have shown that voice qualities influence attractiveness ratings, and that vocal attractiveness is negatively related to FA (Hughes et al., 2002). In a recent study by Abend et al. (2015), men rated both faces and voices of women separately, and found that the voices of attractive women were also rated to be more attractive. Additionally, he found that these attractiveness ratings were related to the women’s FA.
Even though appearance seems to be very important in partner selection, the desirability of a potential partner might depend even more on their personality traits. In a study by Todosijević et al. (2003) participants rated the desirability of many personality traits as well as physical characteristics. Most desirable traits among men and women were found to be: sincerity, faithfulness, tenderness, passion, reliability, maturity, and intelligence. On the other hand, conceitedness, selfishness,
insecurity, aggressiveness, fearfulness, and introversion were deemed most undesirable (Todosijević et al., 2003). Interestingly, none of the physical attractiveness characteristics that were taken up in the rankings were listed as highly desirable, but all were scored as moderately desirable.
Detection mechanisms
As shown previously, numerous sensory characteristics influence attractiveness. These characteristics seem to be interrelated; visual cues can be related to auditory and olfactory cues and vice versa. According the redundant signaling hypothesis, humans use multiple mechanisms to convey their attractiveness, sending redundant information to potential partners, serving as a back-up and minimizing the chance of erroneous attractiveness estimations (Abend et al., 2015). Following this hypothesis, attractiveness characteristics can be detected independently from one another, and specialized detection mechanisms might have evolved for specific cues.
To investigate the neural correlates of visual attractiveness, O’Doherty et al. (2003) contrasted brain activity of participants viewing either attractive or unattractive faces using functional magnetic resonance imaging (fMRI). In contrast to unattractive faces, attractive faces caused increased activation in the medial orbitofrontal cortex (mOFC), the bilateral posterior cingulate cortex, and the medial prefrontal cortex (mPFC). The reversed contrast showed that the inferior frontal gyrus (IFG), the bilateral insula, the dorsal para-cingulate cortex, and the right ventral prefrontal cortex were more active when unattractive faces were viewed compared to attractive faces. Aharon and colleagues (2001) showed that the faces of beautiful women can act as a reward to heterosexual men. Men were willing to work to see pictures of beautiful women, and fMRI results showed increased activation in the nucleus accumbens (NAcc), the sublenticular extended amygdala and the ventral tegmental area
(VTA) while viewing beautiful women, but not beautiful men (Aharon et al., 2001). The role of the amygdala was nuanced by Winston et al. (2007) who found a non-linear relationship between facial attractiveness and amygdala activation, in which the amygdala was more active for both highly attractive and unattractive faces, but not for faces with average attractiveness.
A study by Bestelmeyer and colleagues (2012) investigated the neural correlates of vocal attractiveness using fMRI, and found that activity in inferior frontal gyrus (pars triangularis) is related to the attractiveness of a woman’s voice. More specifically, they found a negative correlation between vocal attractiveness and activity in the IFG, meaning that more attractive faces were related to
decreased IFG activity (Bestelmeyer et al., 2012), which corresponds to the decreased activation found in the IFG in relation to visual attractiveness (O’Doherty et al., 2003).
As reviewed by Pause (2012), the processing of body odor involves a specialized network related to social signal processing, including the fusiform cortex, the insula, the cingulate cortex, the medial prefrontal cortex (mPFC) and the amygdala. Similar to the non-linear relationship between amygdala activation and facial attractiveness, a non-linear relationship has been found between the intensity and valance of odors and amygdala activation (Winston et al., 2005). Increased amygdala activation was only found for high intensity odors with an emotional value. However, only four odors were tested in this study and none of them were related to human scent. It is plausible that the
amygdala is also involved in determining the emotional valance of human odors, and determining their attractiveness, but further research is needed to confirm this hypothesis. Lundström et al. (2008) studied olfactory processing using positron emission tomography (PET) and showed that body odors are processed differently in the brain compared to other common odors. Additionally, they compared the neural response to odors of a friend to the response to the odor of a stranger, and found activation in a network consisting of the central sulcus, the occipital cortex and the posterior part of the
retrosplenial cortex and the pre-supplementary motor area (preSMA; Lundström et al., 2008). They relate these findings to previous research suggesting that these areas, the retrosplenial cortex and the preSMA in particular, code for familiarity of stimuli, independent of modality (Shah et al., 2001; Lundtröm et al., 2008).
Less is known about the mechanisms involved in detecting personality characteristics, even though they have been rated as more important in partner selection than physical attractiveness (Todosijević et al., 2003). It is suggested that our partner personality preferences are influenced by our early life experiences. Gyuris et al. (2010) suggest that individuals are likely to select a partner with personality traits that differ from those of their own close relatives, an acquired mechanism thought to prevent inbreeding. However, to our knowledge, the biological or neural correlates of the detection of desirable personality traits in strangers have not been studied. Personality detection is highly complex and studying this process would require complex multimodal stimuli, which are likely to contain a large number of confounding variables for which neuroimaging techniques cannot control. However, some studies have looked at the way third party judgments (e.g. reputation or compatibility) influence attractiveness ratings. In an fMRI study by Cartmell et al. (2014) participants were presented with pictures of potential partners together with compatibility scores, which they believed were based on their own and the presented individuals’ personality questionnaire scores. A behavioral analysis showed that both facial attractiveness, and compatibility scores predicted how participants responded to the presented individual. In correspondence with previous fMRI research on facial attractiveness, this study found that the NAcc and the mOFC responded to attractive faces. Additionally, similar to financial decision making studies, they found that activity in the NAcc and the anterior insula predicted choice behavior (Cartmell et al., 2014). Even though this study provides insight into the decision making process related to partner choice, predicting choice behavior is not the same as measuring optimal partner choices.
Sensitivity to attractiveness characteristics.
There are several factors that influence an individuals’ sensitivity to these attractiveness characteristics. On the one hand, the sensitivity of attractiveness detection mechanisms can be influenced by internal factors, such as genetics or hormones. For example, a study showed that blue-eyed men in particular prefer blue-eyed women (Laeng et al., 2007). Additionally, we have shown that individuals prefer genetically dissimilar partners (Wedekind et al.,1995). Hormones appear to influence these preferences, as the preference for dissimilarity was not present in women that used
the pill (Wedekind et al., 1995; Wedekind & Füri, 1997). The use of oral contraceptives can also cause women to prefer men with less masculine facial characteristics (Little et al., 2013). Furthermore, the body odor of symmetrical males were only more attractive for women that were in a fertile stage of their menstrual cycle (Thornhill et al., 2003). On the other hand, external factors can influence sensitivity to attractiveness, such as social economic status (SES) and culture. Studies have for example shown that WCR is more important in urban communities while BMI is more important in rural communities (Swami & Tovée, 2005; Swami et al., 2007). Additionally, women’s attractiveness ratings of male faces were higher when the male faces were presented in a high SES context compared to a low SES context (Dunn & Searle, 2010). The specificity and flexibility of these factors complicate the search for an optimal partner, especially one that will remain attractive throughout a relationship.
Actual partner choice
Attractiveness is predominantly studied under laboratory settings, in which participants are asked to reveal their personal preferences for potential partners. However, partner preferences do not always directly correspond to actual partner choices (Regan et al., 1998; Wincenciak et al., 2014). Regan et al. (1998) describe partner choice as a stock market, in which an individual’s own market value determines the optimal mate quality. In this context, seeking a lower-status partner is relatively cost-efficient but unprofitable in the long run, while seeking a higher-value partner is considered profitable, but at the same time costly and risky. They hypothesize that individuals weigh the costs and benefits of potential partners relative to their own market value in order to select the optimal partner. Correspondingly, they found that participants with high self-reported market value were less willing to compromise on partner qualities.
In a study by Wincenciak and colleagues (2014) partner preferences were related to the appearance of participants’ actual partners, and the correspondence between these two variables was in turn related to the participants’ own attractiveness. They found that in more attractive women the partners appearance corresponds more to the women’s preference than in less attractive women. They explain this finding by suggesting that women with a higher market value are better able to find a partner matching their preferences. Earlier study also found that more attractive women have higher
preferences for male masculinity and symmetry (Little et al., 2001), and seem more concerned with the interestingness of potential partners, reflected by high desirability for education, talkativeness, interesting profession and passion (Todosijević et al., 2003). The effect of physical attractiveness on partner preferences was not found for men, which could be explained by the idea that men’s
attractiveness is not solely determined by their looks but also by their resources for example (Wincenciak et al., 2014).
Across species, females usually have to invest more of their resources in their offspring compared to males. While males can increase their reproduction success by mating with multiple females, females are limited by gestation and optimize their reproductive success by selecting males with high genetic quality. This argument is often used to explain why women seem to be more selective in partner choice compared to men. For example, women are found to be more selective compared to men when it comes to potential partners’ social status, income, education, intelligence and self-confidence (Regan et al., 1998; Buunk et al., 2002). However, in modern day human society men are required to make large investments as well. Therefore, Kenrick et al. (1990) formulated the ‘parental investment model’, which states that selectivity depends on the anticipated investment required in the relationship. For example, selectivity decreases if the relationship anticipated to be of short duration or purely sexual. In agreement with this theory, a study by Buunk et al (2002) found that the lower the relationship involvement, the more participants were willing to compromise on their partner preferences, especially men (Regan et al., 1998; Buunk et al., 2002). On the other hand, preference levels for physical attractiveness were found to be higher in both men and women for sexual fantasies compared to real life partners (Buunk et al., 2002). Partner preferences seem to be stable across age groups, except that in participants over 40 years old the preference for a partner with a higher education compared to their own increased (Buunk et al., 2002).
In short, attractiveness can be measured on multiple levels, ranging from sensory observable characteristics, to psychological and cultural factors, which are relatively more complex to study. Even though humans are highly capable of detecting attractiveness in potential partners, especially in the visual domain, detection mechanisms are highly dynamic. The relative importance of these
hormone levels and social economic status. Therefore, complex calculations are necessary to compare costs and benefits of potential partners, taking into account all possible factors. Before discussing how these studies on partner selection contribute to the objective measurement of compatibility, we will investigate what mechanisms are involved in early stage romantic love, and long term romantic relationships and marriage respectively.
Passionate love
Next we will focus on the phase that occurs after a potential partner has been found: falling in love. Novels, movies, poems, love songs and the like all agree that falling in love can have an huge influence on human lives. This is supported by the literature, which shows that love-related effects can be found on many different levels. This chapter will cover the psychological, physiological, chemical, and neural changes that have been associated with early stage passionate love. Hereby, we provide a basis for our discussion, in which we will debate whether modern measurement techniques, including neuroimaging, can be used to objectively quantify the strength love.
Psychological and physiological effects
Many behavioral and psychological reactions have been related to falling in love, such as increased feelings of euphoria and depression, difficulty sleeping, increased daydreaming, agitation, restlessness, and a decreased ability to concentrate (Dion & Dion, 1973). While reciprocated love can lead to feelings of fulfillment and ecstasy, rejection or separation can lead to feelings of emptiness, anxiety and despair (Hatfield & Sprecher, 1986). Dion and Dion (1973) already showed that personality influences if and how you experience love. They found that ‘externals’, people who attribute control over life events that affect them to external forces, are more likely to experience falling in love as mysterious and volatile compared to ‘internals’, who attribute control over these events to themselves. Additionally, gender differences were found, as women reported to experience love more intensely compared to men (Dion & Dion, 1973). These findings show that love can have various effects, and that there are large individual differences in the way love is experienced.
As love elicits such intense feelings, it is no wonder that the effects of love are also found in physiological measurements. Several studies have compared physiological responses that are elicited by lovers or control stimuli. In a study by Vico et al. (2010) participants passively viewed pictures of their lovers, babies, family members and strangers while their heart rate and skin conductance levels were recorded. In addition, electromyography (EMG) of the zygomatic muscle was recorded,
measuring activity in the muscle that mediates smiling. When comparing responses to lovers to those related to the control stimuli, increased signals were found for all these physiological measures (Vico et al., 2010). Even though this study showed that love-related stimuli evoke increased physiological responses, this effect does not seem to be exclusively related to romantic love. Using a similar design, Guerra and colleagues (2011) showed that increased heart rate and skin conductance levels can be elicited not only by pictures of participants’ lovers, but also by pictures of participants’ fathers, showing that these measures might respond to love in general. However, they did find differences in EMG of the zygomatic muscle, with boyfriend pictures eliciting a larger EMG signal compared to father pictures as well as all other control stimuli (Guerra et al., 2011). Previous studies have shown that zygomatic responses are related to the pleasurableness of facial stimuli (Lang et al., 1993), and that the number of Duchenne smiles (which involve both the zygomatic and orbicularis oculi muscles) that occurs during couple interactions, accurately predict self-reported love (Gonzaga et al., 2001). Therefore, responses of the zygomatic muscle could be considered as a specific measure for love.
Chemical effects
Cells in our bodies have various communication mechanisms, one of which involves the release of neurotransmitters. Studying the distribution of neurotransmitters and their receptors in the brain can help unravel the neural networks underlying love. Two neurotransmitters of which levels are found to be elevated in passionate love are oxytocin (OT) and vasopressin (VP). These neuropeptides have been linked to social attachment, such as mother-infant bonding and parental bonding, and to reproduction-related behavior, such as childbirth, sexual pleasure, and competitive aggression among males (Insel & Young, 2000; Dębiec et al., 2007; Murphy et al., 1987; Zeeman et al., 1997; Meston & Frohlich, 2000; Zeki et al., 2007; Dębiec et al., 2007). After production in the hypothalamus, OT and
VP and stored in the pituitary gland, from which they are released into the blood. Receptors of OT and VP can be found in brain areas involved in social attachment, reward, and emotional processing (e.g. the nucleus accumbens, the VTA, the hippocampus and the amygdala; Insel & Young, 2001; Esch & Stefano, 2005; Meyer-Lindenberg et al., 2011). OT and VP seem to be closely linked, as both neurotransmitters can bind to each other’s receptors (Esch & Stefano, 2005).
Individuals that experience passionate love have also shown to have increased levels of neurotrophines. For example, Emanuele et al. (2006) found increased levels of nerve growth factor (NGF) in individuals experiencing early stage passionate love, compared to individuals that were single as well as participants that were in established romantic relationships. NGF levels were additionally found to be related to participants PLS scores, with higher PLS scores for participants with higher NGF levels (Emanuele et al., 2006). Neurotrophins such as NGF have various functions, such as the regulate vasopressin levels, but also the activation of the
hypothalamic-pituitary-adrenocortical axis (HPA-axis), which is, among other functions, involved in regulating cortisol levels (Emanuele et al., 2006; Angelucci, 1994). Several studies have shown that early stage passionate love activates the HPA-axis, as represented by increased cortisol levels (Marazziti & Canale, 2004; Loving et al., 2009). In a study by Loving et al. (2009) the increased cortisol levels were recorded in women when they were asked to think about their relationships. Moreover, this effect was found to be prolonged specifically in women think about their relationships more frequently in general (Loving et al., 2009). These cortisol changes could be related to the excitement and uncertainty that co-occurs with the start of new romantic relationships, and could promote social attachment, especially in combination with increased OT levels (Marazziti & Canale, 2004; Esch & Stefano, 2005; Loving et al., 2009).
Besides changes in stress hormones, Marazziti and Canale (2004) found that passionate love was related to increased testosterone levels in women and decreased testosterone and follicle
stimulating hormone (FSH) in men. The changes in these hormone levels seem to be specific to this stage of love specifically, as they have been found to diminish within 12 to 24 months of being in a relationship (Marazziti & Canale, 2004). Gender differences in the response to early stage passionate love were also found in serotonin levels, which increased in women and decreased in men
experiencing passionate love (Langeslag et al., 2015). Similar to Loving et al. (2009), this study showed that changes in hormone levels were related to lovers’ amounts of obsessive thinking about their partner. Thinking about a partner has even been related to increased blood glucose levels (Stanton et al., 2014). The authors suggest that love evokes ‘eustress’, a good type of stress that is related to positive affect, and that it makes you feel energized.
Neural effects
In the past two decades various neuroimaging techniques have been applied to investigate the neural correlates of love and romantic relationships. The most frequently used techniques are
electroencephalogram (EEG) recordings and functional magnetic resonance imaging (fMRI). Both measures provide an indirect measure of brain activity, as EEG measures voltage changes at the scalp, and fMRI measures the hemodynamic response (blood flow and oxygenation) following brain
activation.
Previously we described that Vico et al. (2010) found that women had increased physiological responses to pictures of lovers, compared to faces of celebrities, babies, family members and strangers. In addition to these measures, event related potentials (ERPs) were recorded, which are changes in the EEG signal that are time locked to a certain event, such as stimulus presentation. Again, the results showed increased responses to pictures of lovers, specifically in the P3 component of the ERP, which is the positive peak in the signal that occurs around 300 ms after stimulus presentation. In a study with a similar design, Langeslang et al. (2007) also found an increased P3 response to pictures of lovers, in this case compared to a picture of their friend or an unknown beautiful person. While EEG measures the voltage changes on the scalp that are related to brain activity, magneto encephalogram (MEG) measures the changes in magnetic field strengths. A recent study showed that viewing pictures lovers compared to friends evoked an increased MEG signal at approximately 300 ms after stimulus
presentation, which corresponds to the increased P3 signal measured in EEG studies. Interestingly, this effect was only found in women in the left lateralized electrodes (Tiedt et al., 2014).
The P3 component, also known as the late positive potential (LPP), has been related to emotional processing as well as attention (Schupp et al., 2006). There are two main types of attention:
task-related attention and motivated attention, of which the latter has for example been related to the increase in attention directed towards another when one falls in love. In both previously mentioned studies, participants passively watched the pictures, and could have been aware of the aim of the study. Therefore, in a follow up study an oddball paradigm was used to eliminate task effects
(Langeslag et al., 2008). Besides replicating the increased P3 amplitude to the picture of the lover, this study showed task-related and love-related attention were uncorrelated, confirming that love related stimuli elicit a distinct form of attention (Langeslag et al., 2008). Even though EEG results cannot be directly related to brain areas, motivated attention is thought to be regulated by the amygdala, and the ventromedial and dorsolateral prefrontal cortices, as these areas are suggested to encode the emotional valance of stimuli and exercise bottom-up control on the attention directed to emotional stimuli (Compton, 2003).
The first functional magnetic resonance imaging (fMRI) study to focus on the neural
correlates of love was performed by Bartels & Zeki (2000), which was later replicated by Aron et al. (2005). These two studies contrasted participants’ brain activity while watching a picture of their lover to their brain activity while watching a picture of one of their friends. Increased activation was found in the anterior cingulate cortex (ACC), the caudate, the VTA, the putamen, the insula, the cerebellum and the posterior hippocampus (both studies), as well as the posterior cingulate (PCC; only found by Aron et al., 2005). On the other hand, love-related deactivation was found in both studies in the amygdala (both studies), but also in the prefrontal cortex (PFC), the parietal cortex and the middle temporal cortex (only Bartels & Zeki, 2000). This network was unique to other networks previously found in studies on other emotional states. These two studies differed in three aspects. First, the length with which participants reported to be in a relationship, which was longer for study by Bartels & Zeki (2000) (M = 2.4 years, versus M = 7,4 months in Aron et al. (2005)). Second, Bartels & Zeki (2000) presented their stimuli for 17.36 seconds while Aron et al. (2005) presented them for 30 seconds. Third, Aron et al. (2005) used a region of interest (ROI) analysis, in which analyses are focussed on pre-selected brain regions, which might ignore activation in other brain regions. While Bartels & Zeki found increased activation in the cingulate cortex in their main contrast and Aron and colleagues
(2005) did not, Aron et al. (2005) did show that activity in the ACC and PCC was positively correlated to the length with which participants were in a relationship. These findings together suggest that the activity levels in these areas vary over the course of development of a relationship, and that our brain flexibly adjusts to being in a relationship (Fisher et al., 2005). Furthermore, only Aron et al. (2005) found that increased activity in the caudate was related to increased feelings of passionate love as measured by the PLS. Interestingly, deactivations in this study affected the right hemisphere more than the left (Bartels & Zeki, 2000, 2004), which corresponds to the left lateralized activity found in the EEG and MEG studies (Tiedt et al., 2014).
Using again a similar design, Zeki and Romaya (2010) compared activity patterns between heterosexual and homosexual men and women. This study again replicated previous findings, showing increased activation in in the hippocampus, the head of the caudate, the vermis, the hypothalamus, the cerebellum, and the superior parietal lobe (and nearly significant activation in the tegmentum, the anterior cingulate and the caudate nucleus body), and deactivation in the superior frontal gyrus, the parietal cortex, the middle temporal gyrus, the middle orbital gyrus, the rolandic operculum, the precuneus, the superior frontal gyrus, the angular gyrus and the insula. However, in contrast to the study by Aron et al. (2005), they did not find a correlation between love-related brain activation and the PLS, nor did they find a relationship between brain activity and the length of participants’ relationships.
So far, all of the discussed studies have used pictures of loved ones that were consciously processed by participants. However, Ortigue et al (2007) investigated whether subliminal presentation of the name of a romantic partner compared to a friend would cause the same activation pattern. In this study participants performed a lexical task in which trials were primed with a ‘passion’ prime,
consisting of one word describing their passion in life, or a ‘love’ or ‘friend’ prime, consisting of the name of their lover or friend respectively. Both the passion and the love primes resulted in faster response times on the lexical task. Subsequently, fMRI results showed that the love prime elicited an activation pattern that was very similar to the activation pattern found in previous studies (Bartels & Zeki, 2000, 2004; Aron et al., 2005). However, comparing activation related to the love and passion
primes, similar activation patterns were found, consisting of the caudate, the insula, the fusiform gyrus, the parahippocampal gyrus, the right angular gyrus and cerebellum. However, two areas were specifically activated for love primes, namely the lateral angular gyri and the bilateral fusiform regions (Ortigue et al., 2007). This finding seems to conflict with Zeki & Romaya (2010), showing
deactivation of the angular gyri in response to love-related stimuli. Even though these areas are found to be active specifically in relation to romantic stimuli, in correspondence with the study by Aron and colleagues (2005), these brain areas were unrelated to relationship length. In this study the strength of life passion was not measured, which makes it impossible to relate this variable to PLS scores.
The aforementioned studies showed that the activation pattern related to romantic love changes in relation to the length of the romantic relationship. However, these studies did not demonstrate what the cause of these changes in brain activity might be. A study using resting state functional magnetic resonance imaging (rsfMRI) showed that falling in love can cause changes in connectivity between brain regions (Song et al., 2015). In this study both functional connectivity (FC) and regional homogeneity (REHO) were measured, showing the communication between spatially separated brain regions, and short-distance communication within a brain area respectively. These measures were compared for participants that i) were in love at the moment, ii) were not in love at the moment but had been previously, and iii) participants that reported never to have been in love. The PLS (Hatfield and Sprecher, 1986) was used to measure the status of passionate/romantic love in participants that were in love. Results showed that participants that were in love during the experiment showed increased REHO in the dorsal anterior cingulate cortex (dACC), and reduced REHO in the bilateral caudate (compared to participants that were not in love or had never been in love). The REHO in the dACC was related to relationship length in participants that were in love, and negatively correlated to the length of time since the break up in participants that had been in love. Furthermore, REHO in the caudate was decreased in participants that had been in love previously, and this decrease was related to the time since their break up. Additionally, functional connectivity was increased in participants that were in love compared to those that had ended their relationships in multiple networks (Song et al., 2015).
Romantic-love specific activation
In order to determine whether love can be objectively measured using the found activation patterns, it is important to consider the specificity of these findings to romantic love. If other stimuli can evoke similar activation patterns, the certainty with which we can attribute measured activity to love decreases substantially. Regarding EEG findings, larger P3 components cannot be exclusively related to romantic love. Guerra et al. (2011) performed a study similar to those of Langeslag et al. (2007) and Vico et al. (2010), and compared ERP’s in response to images of participants’ boyfriends to those in response to images of their fathers. This study found that the P3 response was larger for fathers compared to boyfriends, and that both physiological and electrophysiological responses were higher for loved faces compared to unknown faces (Guerra et al., 2011). This finding suggests that love in general affects P3 magnitude, and illustrates the importance of using adequate control images.
There are also studies that have compared love-related fMRI activation patterns to patterns evoked by other types of stimuli. One example is a follow up study performed by Bartels & Zeki (2004), in which they compared the activation pattern of romantic-love from their previous study (Bartels & Zeki, 2000) to the activation evoked by maternal love. This comparison revealed that activity patterns for both stimuli overlapped substantially. However, they did find activation that was specific to romantic love. Activation in the VTA, the hippocampus, and the hypothalamus was specifically related to romantic love but not to maternal love. No differences were found in the deactivation patterns of romantic and maternal love (Bartels & Zeki, 2004). Interestingly, similarities in activation patterns have also been found when responses of mothers watching their child were compared to responses of the same mothers watching their own dogs (Stoeckel et al., 2014). Both stimuli evoked activation of the hippocampus, the amygdala, the medial OFC, the dorsal putamen and the thalamus. In this study, activation of the VTA and the substantia nigra was specifically found when mothers watched their own child, and hippocampal activation was found for both child and dog images. These findings do not seem to correspond to the findings of Bartels & Zeki (2004) in which VTA and hippocampal activation was found specifically for romantic love but not for maternal love.
Romantic love has not only been compared to other types of love. Previously we described the behavioral, psychological and chemical effects of love, and many of the described characteristics of love could be compared to being addicted. For example, similar to addiction, love involves obsessive thinking, approach behavior, and feelings of euphoria. Moreover, both love and addition are related to the dopamine system and the release of OT (Insel & Young, 2001; Reynaud et al., 2010). On a neural level, Reynaud and colleagues (2010) compared activation patterns from studies on romantic love, as described above, to those acquired in addition studies and found that these patterns were very similar, involving the VTA, the caudate, the ventral striatum, the insula, the ACC and the hypothalamus.
In summary, both P3 magnitudes and fMRI activation patterns can be related to romantic love, but the relationship between these measured responses is not likely to be exclusive. Even though the P3 component is not specific to romantic love, it could still be considered as a measure of the strength of love in general. The same applies to the fMRI activation patterns, which show substantial overlap when comparing different types of love. However, even though these measurement techniques seem to be able to provide us with some information about the type and strength of love, further research is necessary to investigate whether there are any more stimuli types that elicit similar activation.
Compassionate love, romantic relationships, and marriage
Besides its role in partner selection, relationship formation, and procreation, love is suggested to keep couples together in order to care for their offspring (Gonzaga et al., 2001; Fletcher et al., 2015). In human society it is common for romantic partners to form exclusive relationships, in some cases legally defined by marriage. So far we have described the biological mechanisms involved in partner selection and short term passionate love. Subsequently, we will cover the biological correlates of long term relationships, in which passionate love evolves into compassionate love (de Boer et al., 2012). Hence, we will address the following questions: ‘What role does love play in relationships and marriage?’, ‘How do romantic relationships affect couples?’, and finally ‘What neural networks are related to long term love, and romantic relationships?’.Relationships and love
Quite frequently, love is linked to romantic relationships and marriage almost effortlessly. However, love is not the only factor that stimulates lovers to form relationships. An indication of the factors considered to be important in relationships can be derived from subscales of the questionnaires that are used to measure relationship quality. The Dyadic Adjustment Scale (DAS; Spanier, 1976) for example shows four components related to marriage quality: satisfaction, cohesion, consensus and affectionate expression. The Perceived Relationship Quality Component (PRQC) on the other hand measures six relationship quality components: relationship satisfaction, commitment, intimacy, trust, passion, and love (Fletcher et al., 2000). Relationships can also be investigated by measuring the frequency of physical contact between couples, such as hand holding, embraces and kissing, which can be assessed using the Physical Affection Scale (PAS; Diamond, 2000). Marriage quality has furthermore been related to the occurrence and frequencies of negative events in the relationship, which can be measured by the marital attribution scale (MAS; Bradbury & Fincham, 1992).
These questionnaires not only show that relationships are based on more factors than love alone, they show that sometimes love is not even directly named as a factor. The perceived importance of love in relationships and marriage appears to depend on socioeconomic status, gender roles, and female emancipation, is in agreement with studies on the influence of socioeconomic factors on partner selection (Swami & Tovée, 2005; Swami et al., 2007; Dunn & Searle, 2010). In 1967, American college students were asked the following question: “If a boy (girl) had all the other
qualities you desired, would you marry this person if you were not in love with him (her)?”. While the
majority of men (64%) refused to marry someone they did not love, the majority of women was undecided (71,7%). Only 24% of the women refused to marry a man they did not love (Kephart, 1967). These responses were explained by the existing gender roles, which led women to be less educated, largely unemployed, and economically dependent on either their family or husband
(Kephart, 1967; Simpson et al., 1986). In the following two decades, Simpson and colleagues repeated Kephart’s question on subsequent generations of college students. These studies showed that the perceived importance of love in marriage increased dramatically over time, especially in women. By 1984 more than 84% of both male and female college students refused a loveless marriage, which the
authors related to the changes in gender roles and emancipation over the years (Simpson et al., 1986). Throughout history many cases are known in which marriages are arranged for religious, political or economic reasons (Allendorf, 2013; Bunkanwanicha et al., 2013; Shafer & James, 2013). Nowadays there are still many cultures in which marriages are primarily arranged or economically motivated. However, love-marriages are currently most common in western cultures (Allendorf, 2013).
Chemical changes
As with passionate love, multiple studies linked long term romantic relationships and marriage to chemical and physiological changes. Similar to passionate love, oxytocin (OT) and vasopressin (VP) levels are found to be elevated in individuals in high quality romantic relationships (Light et al., 2004). High levels of these neurotransmitters have been related to improved couple communications; high OT levels were related to increased positive communication behavior while high VP levels were related to decreased negative couple interactions (Gouin et al., 2010). Additionally, OT is known to downregulate the HPA-axis, which is responsible for stress responses. As the novelty and excitement of new relationships fade, OT levels seem to remain elevated while cortisol levels decrease (Ditzen et al., 2007). In spite of these stress reducing effects, couples can experience increased stress levels, for example in response to relationship changes, such as marriage. In a study by Kiecolt-Glaser et al (2003) stress hormone levels were measured in newlyweds, and hormone levels were used to predict marital outcome 10 years later. Acetylcholine (ACTH), cortisol, epinephrine (EPI) and norepinephrine (NEPI) levels were measured when newlyweds performed a conflict resolution task. After 10 years, the marital status of these couples was evaluated and hormone levels of couples that were still married were compared to hormone levels of divorced couples. The results of this study showed that couples that remained married had lower levels of EPI and NEPI as newlyweds compared to couples that ended up in divorce. Hormone levels were also related to marital satisfaction, as couples with high satisfaction had lower NEPI and ACTH levels. Even though married and divorced couples differed in their hormone levels, they did not differ in their self-reports about their relationships, suggesting that hormone levels are not only more objective but also a more reliable predictor of relationship outcome
(Kiecolt-Glaser et al., 2003). Interestingly however, unlike its large effects in early love, no differences were found in married and divorced newlyweds’ cortisol levels.
The stress reducing function of romantic relationships could be related to the health benefits associated with high quality romantic relationship. For example, Gouin et al. (2010) showed that high OT and VP levels were related to faster wound healing. A study by Light et al. (2004) showed that women who report to be hugged more frequently by their partners have higher baseline OT levels, and both hugging frequencies and OT levels were related to decreased blood pressure (BP) and heart rate (HR) levels. Stress reduction can also occur through a partners touch, as women who received a shoulder massage prior to a stressor had lower cortisol and HR stress responses (Ditzen et al., 2007). The social support that high quality marriages provide can also contribute to higher recovery and survival chances when a spouse suffers from health problems. Coynbeckese et al. (2001) showed that high marriage quality was related to higher survival rates of patients with congestive heart failure. In general, marital satisfaction has been shown to be an important predictor of health self-ratings, as a relationship between marriage and health ratings is found in satisfied married couples, but not in dissatisfied couples (Chung & Kim et al., 2014). This study additionally showed that cultural
differences influence the importance of marital satisfaction in relationships, which causes differences in the predictive value of this measure.
Psychological and cognitive changes
The stress reducing function of relationships can also be seen in romantic couples psychological and cognitive functioning. An old proverb from the 15th century states that ‘love is blind’. This popular phrase, amongst others used by Shakespeare, has received scientific support. Multiple studies have shown that couples hold positive biases about their partners, and the quality of their relationships, also referred to as ‘positive illusions’ (Murray & Holmes, 1997; McNulty, O’Mara, & Karney, 2008; Barelds-Dijkstra & Barelds, 2008). These illusions are thought to serve as a
protection mechanism, by which negative experiences with partners can be overcome without damaging the relationship (Murray & Holmes, 1997; McNultry et al., 2008).
Couples are for example biased when it comes to their partners physical appearance. Both men and women seem to rate their partner as more attractive compared to how they rate themselves, and compared to how their partners rate themselves (Swami et al., 2007; Barelds-Dijkstra & Barelds, 2008). Moreover, a follow-up study showed that participants believed that their partners would rate them as more attractive compared to the participants’ self-rating, and that partners self-ratings would be lower than the participants’ partner-rating (Swami et al., 2009). These findings suggest that participants were aware of their positive bias towards their partners, and of the positive bias of their partners towards them. Physical appearance is not the only factor on which couples may hold positive biases. Couples are also likely to hold biases about their partners’ traits, such as dominance,
self-esteem, sociability, intelligence, and sense of humor, to name a few (Murray & Holmes, 1997). Murray and Holmes (1997) found that the presence of positive biases predicted greater love, trust, and relationship satisfaction in couples, and reduced conflict and ambivalence, making the relationships more stable overall. Therefore they suggested that positive illusions facilitate the maintenance of long term relationships. However, MuNulty et al. (2008) showed that weaker
marriages could suffer from positive illusions as they might dissuade couples from addressing marital problems directly, in which case the situation could worsen over time.
High quality relationships have also been found to influence perception. In a study by Schnall et al (2008) participants were asked to visually estimate the slope of a geographical slant. The authors showed that slope estimation did not only depend on participants age and physical fitness, but also on psychosocial factors, such as the presence of a friend. With a friend present, participants were
positively biased and made lower slope estimations compared to when participants estimated the slope as being by themselves. The authors attribute this effect to social support, and show that it is
modulated by the friendship quality, which makes it highly likely that this effect is also present in romantic couples. However, further research is necessary to confirm this hypothesis.
Neural changes
Besides psychological and chemical effects, neuroimaging studies have shown that long term relationships affect neural activation patterns. On a cognitive level, we showed that social support is
thought to cause a positive bias in the estimation of geographical slants (Schnall et al., 2008). On a neural level, social support has been shown to positively affect threat responses and pain processing. In an fMRI study by Coan and colleagues (2006), married women received a foot shock, or a threat of shock, while being alone or holding the hand of their spouse or an unseen stranger. Hand holding not only reduced self-reported unpleasantness ratings, but also the neural threat response, as measured by decreased activation in the ventral ACC, the posterior cingulate, the left supramarginal gyrus and the right postcentral gyrus, areas related to bodily arousal and affect related action (Coan et al., 2006). Furthermore, spousal hand holding alone led to reduced activation in the DLPFC and the caudate, areas that have been related to emotion regulation, suggesting that spousal hand holding is more effective at reducing stress than holding the hand of a stranger. The stress-reducing effect of hand holding was furthermore found to be stronger in women with high marriage quality, as higher marital quality was related to deceased activity in the anterior insula, the superior frontal gyrus, and the hypothalamus, reflecting improved stress regulation and pain processing (Coan et al., 2006). Interestingly however, a study by Allen et al (1991) already showed that stress reduction through social support is also visible in women when their dog is present, showing that this quality might be more related to familiarity, or love in general, instead of romantic love specifically.
In a follow up study, Beckes et al. (2014) again investigated threat responses in participants that were holding hands, but this time participants held the hand of friends instead of romantic
partners, and both the participant and their friend could receive electric shocks. This study showed that when participants experience threat towards themselves the neural activation patterns are highly similar to those recorded when threat is directed to their friend or a stranger. However, looking at inter-individual correlations, the activation patterns evoked when friends were threatened were far more similar to threat-to-self activation compared to threat-to-stranger activation, which the authors describe as a blurring of the neural representation of the self and your friend (Beckes et al., 2014). As the resemblance of activation pattern depends on familiarity, it could be that threat-related activation patterns are even more similar in romantic partners compared to friends. However, additional research is necessary to test this hypothesis.
Some evidence for the blurring neural representations of the self and other was provided by Kawamichi and colleagues (2013), who investigated couples responses to social judgments, which could be directed to participants themselves, their romantic partners or a stranger. During an fMRI task participants would see a picture of themselves, their partner, or a stranger, which was coupled to a reputation adjective that judges had used to describe them in an earlier task. The imaging results showed that the mPFC was specifically activated when participants processed reputations of themselves or their partners, but not for the processing of the reputations of strangers (Kawamichi et al., 2013). As the mPFC is suggested to be involved in self-image, the authors suggest that in a relationship your self-image is extended in such a way that it includes your partner.
Long term stability
Several mechanisms have been proposed to help romantic couples stay together. Earlier we described that couples form positive biases about their partners, which improves their conflict resolution. Also, we have described that people in love direct more attention towards their lover. However, it might also be true that lovers direct attention away from anyone other than their lover. A similar effect was found in a study by Lundström & Jones-Gotman (2009), who found that romantic love modulates women’s ability to identify men’s body odors, which is important in attractiveness and partner selection.
Discussion
The aim of this thesis was to investigate whether modern biological measurement techniques are able to objectively quantify attraction, love or relationships. We discussed what biological, psychological and neural correlates are involved in partner selection, falling in love and maintaining a romantic relationship or marriage. Now, we will discuss the extent to which these techniques are able to provide an objective measure these three phases of love.
First we looked partner selection, and found that attractiveness can be influenced by physical appearance, but appears to depend most on personality characteristics. So far studies have mainly focus on physical attractiveness, which can be detected through visual, auditory and olfactory mechanisms. Complex detection mechanisms appear to have evolved for the purpose of partner selection, which seem automated and effortless. For example, we seem to be able to detect genetic information in potential partners body odors without us even being aware of the presence of these markers. On a neural level, attractive faces seem to activate the brains reward regions (mOFC, NAcc, VTA; Aharon et al., 2001; O’Doherty et al., 2003), while seeing attractive faces and hearing attractive voices causes decreased activity in the IFG (O’Doherty et al., 2003; Bestelmeyer et al., 2012). One potential function of this activation pattern is that it could facilitate approach behavior. Using neuroimaging techniques, such as fMRI, even enables us to predict partner choices in forced choice paradigms (Cartmell et al., 2014).
However, partner choices are not solely determined by appearance, but also depends on personality characteristics (Cartmell et al., 2014).
In order to be able to objectively measure attraction, an individuals’ responses should be measured to stimuli of potential partners that include both appearance and personality information. Subsequently, the physical or neural responses should be analyzed to see which of the presented potential partners evoked the optimal response. However, there are several substantial drawbacks to this proposal. The first main drawback is that it is unclear what responses to potential partners should be compared to. Due to the large number of attractiveness characteristics, and the even larger amount of possible combinations, it is almost impossible present participants with enough potential partners to control for all of these variables. Secondly, biological measurement techniques only allow for sensory stimuli. These stimuli are unlikely to provide sufficient information for the detection of personality traits, especially considering that these stimuli have to be of short duration in order to present as many potential partners as possible. The number of stimuli that can be presented is especially low in fMRI studies, which measure the relatively slow and imprecise hemodynamic response function. Moreover, as the BOLD response is an exaggerated compensation response to oxygen uptake in a brain region, it is unknown how sensitive this measure is to small differences in attractiveness. And finally,
attractiveness studies seem to neglect the fact that successful matchmaking relies on two individuals being mutually attracted to one another, and that attractiveness preferences rely heavily on an
individuals’ own attractiveness, their gender, and their desired relationship commitment, factors which so far have not been included in neuroimaging studies (Wincenciak et al., 2014; Kenrick et al., 1990; Buunk et al., 2002). Taken together, the limitations in stimulus presentation and the absence of adequate control stimuli show that at present neuroimaging techniques cannot objectively measure attraction.
Next, we investigated what biological, psychological and neurological factors correlate with early stage passionate love. Activity of the zygomatic muscle, which is necessary for smiling, could be considered the most robust physiological correlate of romantic love. Unlike skin conductance and heart rate levels, zygomatic activity levels were highest in response to images of lovers compared to all other stimuli types, including images high in familiarity and love like those of participants fathers (Vico et al., 2010). On a chemical level passionate love can be related to increased levels of OT, VP, NGF, cortisol, and blood glucose, and to changes in testosterone and serotonin levels (Zeki et al., 2007; Emanuele et al., 2006; Marazzitti & Canale, 2004; Langeslag et al., 2015; Stanton et al., 2014). As NGF levels seem to be related to the experience of love as measured by the PLS, this measure could potentially be used as a measure of love. But one could also consider to measure a combination of these substances. However, more research is necessary to see whether combining measures would provide a stronger measure of the strength of love. On a neural level we did not find convincing evidence for passionate love specific neural activation patterns, as there was great overlap between different types of love, and even between love and addiction (Guerra et al., 2011; Stoeckel et al., 2014; Bartels & Zeki, 2004). However, resting state analyses did show that passionate love changed
connectivity between brain regions, in which stronger self-reported love was related to increased REHO in the bilateral caudate and the dACC (Song et al., 2015).
In contrast to partner selection, for individuals in love one stimulus of interest remains. However, if we want to measure the strength of love of a single individual, it is still unclear should make up the control condition. Large individual differences in the way we experience love prevent us
from comparing neural or physiological responses between individuals. Another potential control is a baseline measurement from the individual itself. However, this would mean that these baseline measurements have to be acquired before individual falls in love. Still, this would only show whether levels are increased or decreased, but not what these changes actually mean. Hormone levels and brain activity may fluctuate over time, making future references unreliable.
Finally, we looked at the neural correlates of long term relationships and marriage. Several mechanisms seem to have evolved that promote long term bonding between romantic lovers. Positive illusions are formed to prevent conflict and increase satisfaction, and spouses become less sensitive to the attractiveness of others. Chemically, long term relationships have been related to increased OT and VP levels. These chemical changes relate well to the stress-reducing qualities that have been attributed to marital quality. Stress reduction however does not seem to be specific to romantic relationships, as the stress reduction could be explained by social support which can also be provided by close friends and even family pets (Alan et al., 1991). Interestingly enough, stress hormone levels in newlyweds have been found to predict relationship stability ten years later. This finding suggests that marriages with a troubled start are less likely to last. However, there are many confounding variables imaginable that would affect stress hormone levels, including family- or work-related stress, the length of the relationship before marriage, changes in living situations and whether or not they had children. A factor that shows more potential is the blurring of neural representations of the self and others, which seems to occur in close relationships (Beckes et al., 2014). Even though this study has not yet been replicated in romantic couples, the blurring effect has been related to familiarity, which is likely to be high in romantic lovers with high quality relationships or high marriage satisfaction. One substantial benefit of this measure as opposed to previously potential measures of love, is that it does not require external control groups or control stimuli. The neural representations of others can simply be
compared to the neural presentations of the self within an individual, at one point in time. Therefore, from all of the abovementioned potential measures of love, the increased similarity between neural representations of the self and partner seems to be the most promising measure of the strength of love. Further research is needed to first determine whether this effect is in fact stronger in romantic partners
compared to friends, and whether this effect is related to relationship quality, as measured by self-report measures, or as established by the long term stability of the relationship.
Conclusion
The studies described in this thesis show that a lot of progress has been made over the last two decades in unraveling the biological correlates of attraction, love and relationships. One of the most striking characteristics of these mechanisms is their flexibility. Hormone levels and even connectivity between brain regions have been found to rise and fall with the beginning and ending of relationships. Furthermore, all love-related measures seem to be highly dependent on individual differences, in biological and psychological factors, but also on differences in the culture and society we live in. Unfortunately, the flexibility of these love-related measures complicates the estimation if the strength of love in a single individual. Nevertheless, some of the measures we considered as objective
measures of the strength of love show potential. One of these factors is activity in the zygomatic muscle, which is related to the way couples smile to each other in high quality relationships. Or the levels of stress hormones in newlyweds, which have been shown to predict whether marriages will last ten years later. Unfortunately, at present there are no appropriate control conditions to reliably
compare measurements. Therefore, the most promising technique to measure love objectively is the increased similarity in neural activation patterns of the self and another person that has been found in relation to increased familiarity (Beckes et al., 2014). However, more research is necessary to replicate the findings of this study in romantic couples, and to relate these measurements to self-report measures to compare the reliability of these techniques. Hence, we conclude that at present biological
measurement techniques are unable to measure the strength of attraction, love and relationships objectively.
Further research is also necessary to elucidate limitations present in the literature, and potentially reinforce previous findings. A limitation that can be noticed throughout this thesis, is that many studies do not take into account gender differences. Some studies choose not to confront them,
