BMe Research Grant


Suri Karolin



BMe Research Grant - 2020


Doctoral School of Psychology/Cognitive Sciences  

BME Faculty of Natural Sciences, Department of Cognitive Science

Supervisor: Dr. Németh Kornél

Behavioral, psychophysiological, eye-tracking and electrophysiological studies of the relationship between adult attachment and facial perception

Introduction of the research area

In the research project, we examine the correlations between adult attachment and different attachment styles with facial perception mechanisms, through which it may be possible to understand the different cognitive processes behind the attachment styles more accurately. We use questionnaires, conduct behavioral tests, and eye movement and EEG registration to examine the differences in facial perceptions between individuals of different attachment styles in a neurotypical adult population, and to assess possible behavioral changes following intranasal oxytocin administration.


Brief introduction of the research site

The research takes place at the Department of Cognitive Science of BUTE (for detailed information see Our experiments involve questionnaires, behavioral, psychophysiological and electrophysiological (EEG) methods, as well as eye-tracking to examine the neurotypical population. Our investigations aim to explore the relationship between attachment and facial perception mechanisms.


History and context of the research

Attachment theory is one of the most important doctrines of modern psychology. Early studies of attachment described 4 attachment styles: a relatively well-functioning attachment system indicates secure, hyperactive attachment system indicates anxious, while deactivated attachment system results in avoidant attachment. Individuals who score high on both anxiety and avoidance scales can be characterized as disorganized-disoriented (Bowlby, 1969/1982; Ainsworth, 1978; Main & Solomon, 1990). The classifications originally introduced to describe mother-child relationships are now used in the study of adult attachment as well. Data from previous literature suggest that faces play a prominent role as key stimuli in attachment related experiments (e.g. Meyer et al, 2004; Zheng et al., 2015; Tang et al, 2017). This is not surprising given that faces are one of the most important sources of emotional information for humans, since most often we are informed about the emotional state of our peers by their facial expressions (for example, during a conflict). Based on this, my doctoral research focuses on the relationship of different attachment styles to facial perception mechanisms, which may be used to gain a more accurate understanding of our social relationships.


Aim of the research

The scanning patterns of facial stimuli may be different in individuals, or even different emotional facial expressions can influence fixation patterns; eye movement registration can be used to examine these processes (e.g. Schurgin et al., 2014). Understanding the relationship between attachment and facial perception can also be aided by understanding the processes in the brain, therefore, studies using EEG are an important part of my research plan to gain information about the temporal (and spatial) neural patterns of these processes.

It is also known from previous research that the neurohormone oxytocin can increase the sense of trust, facilitate emotion recognition, and increase the amount of fixations to the eye region (e.g. Guastella et al., 2008). Oxytocin has been associated with the development of attachment (e.g. Tops et al., 2014), and there are results indicating that oxytocin treatment may increase the sense of attachment security as well (e.g. Buchheim et al., 2009). Based on these results, my plans include combining the eye-tracking paradigm we developed with oxytocin treatment, which could help to better understand the role of oxytocin in attachment and facial perception.



Research subjects are usually recruited through an online questionnaire, where respondents can also provide their contact information at the end of the questionnaire if they wish to participate in our experiments.

At the beginning of each experiment, we assess the attachment style of the subjects using the ECR (Experiences in Close Relationships; Brennan et al., 1998) questionnaire. (By clicking the link and filling out the questionnaire, you will also receive a short evaluation and explanation of the score achieved). Based on the ECR scores, subjects can be divided into groups along the dimensions of attachment anxiety and attachment avoidance, which division is necessary to interpret the results of the experiment in the context of attachment. Two types of division are typically used in the literature: on the one hand, we can divide subjects into secure, anxious and avoidant categories along the dimensions of anxiety and avoidance, or, alternatively, as a fourth group we can separate individuals who score high on both the anxiety and avoidance scales: they can be characterized as “disorganized-disoriented” regarding their attachment style. In our previous studies, we used the latter 4-category subdivision to more accurately distinguish patterns characteristic of different attachment styles.

In addition to determining their attachment style, subjects are also assessed for state and trait anxiety (State-Trait Anxiety Inventory, STAI-S and STAI-T questionnaires; Spielberger et al., 1983) and depression (Beck Depression Inventory, BDI questionnaire; Beck & Beck, 1972), which may be influencing factors (cofactors) in the interpretation of experimental results.

The SMI RED500 (SensoMotoric Instruments GmbH) and the accompanying iViewX program are used to record eye movement, and BeGaze 2.1.152 and MATLAB 2014a (Mathworks, Natick, MA, USA) are used for fixation analysis. Stimulus presentation is provided by MATLAB 2008a (Mathworks, Natick, MA, USA), using Psychtoolbox 3.0.9 (Brainard, 1997; Pelli, 1997) and custom scripts.

The combination of our eye-tracking experimental paradigm (see in the Current results section) with EEG measurement and oxytocin treatment is still in progress; I would like to implement this during the first 2 years of my doctoral studies.

Statistical analysis of our results is conducted with IBM SPSS Statistics 20.0.0 (IBM Co.).


Current results

Our previous studies have examined the relationship between attachment styles and perception of emotional stimuli and facial memory performance using a self-developed experimental paradigm involving behavioral tests and eye movement registration.

After completing the questionnaires presented above, subjects performed an emotion recognition task, which consisted of a simple decision: a face with reduced emotional valence (composed of a neutral and emotional face) appeared on the screen, and the subject had to make a decision whether they considered it happy or sad.

Figure 1: Facial stimuli used in the experiments (example). The image shows the two endpoints (20% sad, 20% happy) and the transitions between them, with the neutral element in the middle. Face stimuli were derived from the Radboud Faces Database (Langner et al., 2010).


In the second part of the test, 20 new identities (new condition) appeared beyond the identities seen earlier (old condition), and the subject had to decide whether they had seen the given face during the first part (face-memory task). Eye movements of the subjects were also recorded during the tests.

Based on our results, it seems that making the right emotional decisions does not depend on attachment style; all attachment subgroups showed similar performance during the first task. However, this may also have been influenced by the emotional valence of facial stimuli: although the images in our stimulus material created with morph-technique (Abrosoft Fantamorph Deluxe 5.3.8 program; Abrosoft Co.) had reduced emotional valence, using an even higher neutral ratio could have made the task so difficult that sensitivity (or lack thereof) to emotional signals characteristic of people with different attachment styles would have been more evident in performance. To confirm this, further studies are needed for the assessment of emotion recognition ability in the case of stimuli containing even less emotional information.

Performance and response time in the memory test were also unrelated to subjects' attachment style, however, the response time measured during correct responses was overall faster for old (previously seen) faces. The response time measured for old faces was also positively correlated with the avoidance subscale of the ECR questionnaire, suggesting that people with avoidant attachment style needed more time to recognize the faces they had already seen. This subgroup was also characterized by an increased time of fixations to the right eye region of the facial stimuli compared to the other attachment-style groups. One possible explanation for this is the theory of increased use of cognitive resources, according to which avoidant people invest more energy in processing emotional stimuli so that they can later filter out these “unwanted” stimuli more effectively using postemptive defense mechanisms (pl. Zheng et al., 2015).


Possible impact, further plans

Based on our results so far, it can be said that there are some correlations between attachment styles and emotion recognition and facial memory performance,however, a more accurate understanding of these relationships requires further studies (e.g., the EEG and oxytocin studies already mentioned above), which may enrich the existing knowledge on attachment with additional results. A more accurate understanding of the cognitive mechanisms behind attachment and the behavioral characteristics of attachment styles may provide a useful theoretical background for the development of other applied (therapeutic) psychological methods in the future.


Own publications, external links, references

Presentations at conferences:

Suri, K., Németh, K. (2020) A kötődési stílusok és az érzelmi arc-emlékezet kapcsolatának vizsgálata neurotipikus felnőtt mintán. (Magyar Pszichiátriai Társaság XXIII. Jubileumi Vándorgyűlése, Budapest, 2020. 01. 22–25.) - presentation


External links:

Department of Cognitive Science of BUTE

EEG (Electroencephalography)

Eye tracking

Attachment theory

Fixation patterns


ECR (Experiences in Close Relationships questionnaire)

STAI-S és STAI-T (State-Trait Anxiety Inventory questionnaire)

BDI (Beck Depression Inventory questionnaire)

Morph-technique (Abrosoft FantaMorph)


Reference list:

       Ainsworth, M. D. S., Blehar, M. C., Waters, E., & Wall, S. (1978). Patterns of attachment: Assessed in the Strange Situation and at home. Hillsdale, NJ: Erlbaum.

       Beck, A. T., & Beck, R. W. (1972). Screening Depressed Patients in Family Practice. Postgraduate Medicine, 52(6), 81–85. doi:10.1080/00325481.1972.11713319

       Bodford, J. E., Kwan, V. S. Y., & Sobota, D. S. (2017). Fatal Attractions: Attachment to Smartphones Predicts Anthropomorphic Beliefs and Dangerous Behaviors. Cyberpsychology, Behavior, and Social Networking, 20(5), 320–326. doi:10.1089/cyber.2016.0500

       Bowlby, J. (1969). Attachment and loss. New York: Basic Books. (2nd ed published in 1982)

       Brennan, K. A., Clark, C. L., & Shaver, P. R. (1998). Self-report measurement of adult romantic attachment: An integrative overview. In J. A. Simpson & W. S. Rholes (Eds.), Attachment theory and close relationships (pp. 46–76). New York: Guilford Press.

       Buchheim, A., Heinrichs, M., George, C., Pokorny, D., Koops, E., Henningsen, P., O’Connor, M-F., Gündel, H. (2009). Oxytocin enhances the experience of attachment security. Psychoneuroendocrinology, 34(9), 1417-1422. doi: 10.1016/j.psyneuen.2009.04.002

       Guastella, A. J., Mitchell, P. B., & Dadds, M. R. (2008). Oxytocin Increases Gaze to the Eye Region of Human Faces. Biological Psychiatry, 63(1), 3–5. doi: 10.1016/j.biopsych.2007.06.026

        Langner, O., Dotsch, R., Bijlstra, G., Wigboldus, D. H. J., Hawk, S. T., & van Knippenberg, A. (2010). Presentation and validation of the Radboud Faces Database. Cogn Emot, 24(8), 1377-1388. doi:10.1080/02699930903485076

       Main, M., & Solomon, J. (1990). Procedures for identifying infants as disorganized/disoriented during the Ainsworth Strange Situation. In M. T. Greenberg, D. Cicchetti, & M. Cummings (Eds.), Attachment in the preschool years: Theory, research, and intervention (pp. 121–160). Chicago: University of Chicago Press.

       Meyer, B., Pilkonis, P. A., & Beevers, C. G. (2004). What’s in a (Neutral) Face? Personality Disorders, Attachment Styles, and the Appraisal of Ambiguous Social Cues. Journal of Personality Disorders, 18(4), 320–336. doi:10.1521/pedi.2004.18.4.320

       Mikulincer, M., & Shaver, P. R. (2007). Attachment in adulthood: structure, dynamics, and change. New York: Guilford Press.

       Schurgin, M. W., Nelson, J., Iida, S., Ohira, H., Chiao, J. Y., & Franconeri, S. L. (2014). Eye movements during emotion recognition in faces. Journal of Vision, 14(13), 1–16. doi:10.1167/14.13.14

       Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R., & Jacobs, G. A. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press.

       Tang, Q., Chen, X., Hu, J., & Liu, Y. (2017). Priming the Secure Attachment Schema Affects the Emotional Face Processing Bias in Attachment Anxiety: An fMRI Research. Frontiers in Psychology, 8. doi: 10.3389/fpsyg.2017.00624

       Tops, M., Koole, S. L., IJzerman, H., Buisman-Pijlman, F. T. A. (2014). Why social attachment and oxytocin protect against addiction and stress: Insights from the dynamics between ventral and dorsal corticostriatal systems. Pharmacology, Biochemistry and Behavior (119), 39-48. doi: 10.1016/j.pbb.2013.07.015

Zheng, M., Zhang, Y., Zheng, Y. (2015). The effects of attachment avoidance and the defensive regulation of emotional faces: Brain potentials examining the role of preemptive and postemptive strategies. Attachment & Human Development 17(1), 96–110. doi: 10.1080/14616734.2014.995191