Understanding the intricate relationship between attachment style, emotional processing, and neural responses is crucial for comprehending variations in social and emotional functioning among individuals (Bowlby, 1969; Mikulincer et al., 2009). Previous research indicates that individuals with insecure attachment tend to display heightened emotional reactivity and encounter challenges in regulating their emotions when compared to those with secure attachment (Mikulincer et al., 2009). Specifically, anxious and avoidant attachment styles have been linked to increased emotional sensitivity, stronger negative emotional reactions, and diminished emotion regulation abilities (Mikulincer et al., 2003; Vrtička et al., 2012).

Existing studies have demonstrated that attachment styles impact emotional responses (Rognoni et al., 2008) and neural activity during social perception (Chavis and Kisley, 2012). However, the specific role of attachment style in the interplay between cognitive processing and emotional feedback has not been thoroughly investigated. Some studies have examined the relationship between attachment dimensions and brain activation during gaze interactions (Cecchini et al., 2015), as well as the connection between attachment classifications and frontal EEG asymmetry (Gander and Buchheim, 2015). Other research has explored the response of individuals with fearful-avoidant attachment orientation to emotional stimuli (Dan et al., 2020) and the relationship between defense mechanisms, attachment, and depression (Békés et al., 2021). Additionally, studies have investigated the neural correlates of attachment dimensions during Rorschach inkblot tests (Lai et al., 2022) and the association between attachment insecurity and the α-EEG anomaly during sleep (Sloan et al., 2007).

Thus, there is a notable research gap in the existing literature regarding the specific examination of the role of attachment style in the interaction between cognitive processing and emotional feedback. In our study, we aim to fill this gap by employing ERPs to investigate how attachment style influences emotional responses. Specifically, we will analyze electrophysiological indices, such as the P200 and P400 components, to capture precise neural markers associated with cognitive and emotional processes. By integrating attachment theory with ERPs, we can gain a deeper understanding of how attachment style shapes emotional responses within the cognitive processing framework (Mikulincer et al., 2003; Vrtička et al., 2012).

The P200 component typically observed around 200 ms after stimulus presentation, is associated with early attentional processes and has been linked to the evaluation of emotional stimuli (Carretié et al., 2001). It reflects the initial orienting of attention toward emotionally salient information and can provide insights into the early perceptual processing of emotional cues. The P400 component, occurring approximately 400 ms after stimulus onset, is thought to reflect cognitive evaluation and elaborative processing of emotional stimuli (Dien et al., 2010). It is sensitive to the motivational and affective significance of stimuli and has been linked to processes such as the evaluation of emotional meaning and contextual integration of emotional information (Kanske and Kotz, 2007). In the context of emotional feedback, the P400 component can capture the cognitive and emotional processing associated with the evaluation of the feedback’s relevance and implications.

Furthermore, we consider the findings of Etkin et al. (2011), which challenge the traditional dichotomy of the medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC) into cognitive and affective subdivisions. According to their research on negative emotions, including fear and anxiety, both dorsal-caudal and ventral-rostral regions of the ACC and mPFC contribute to emotional processing. Dorsal-caudal regions are involved in appraising and expressing negative emotions, while ventral-rostral regions regulate emotional responses generated by limbic regions. These insights support our investigation into the role of attachment style in cognitive-emotional interactions.

Additionally, previous research has shown that individuals high in avoidance, an insecure attachment style, may exhibit reduced Error-Related Negativity (ERN), which is associated with response-error monitoring (Simon-Dack et al., 2021). However, when it comes to emotional processing and cognitive engagement, we hypothesize that individuals with insecure attachment styles will exhibit larger P200 and P400 responses to emotional feedback compared to those with secure attachment. The rationale behind this hypothesis is that insecure individuals, due to their heightened emotional reactivity and difficulties in emotion regulation, may exhibit enhanced attentional processes (reflected in the P200) and heightened cognitive evaluation and elaborative processing of emotional stimuli (reflected in the P400). In contrast, individuals exhibiting secure attachment styles are anticipated to demonstrate regulated P200 and P400 responses, indicating effective emotion regulation strategies and an enhanced capacity to process emotional feedback within a cognitive framework.

Importantly, the observed reduction in ERN among insecure individuals (Simon-Dack et al., 2021) specifically pertains to error processing, while the expectation of larger P200 and P400 responses in insecure individuals relates to their processing of emotional feedback. These variations in neural responses underscore the intricate relationship between attachment style and the diverse cognitive and emotional processes at play. Attaining a comprehensive understanding of the precise neural mechanisms associated with attachment style and emotional feedback within a cognitive context can offer valuable insights into individual differences in emotional reactivity and regulation. Moreover, such knowledge holds potential for informing clinical interventions and therapeutic approaches aimed at fostering emotional wellbeing and nurturing positive interpersonal relationships.

In conclusion, our study addresses a significant gap in the existing literature by examining the influence of attachment style on the interplay between emotional feedback and cognitive processing. By focusing on the P200 and P400 components of ERPs, we aim to uncover the differential neural responses of secure and insecure individuals to emotional feedback within a cognitive framework. Through this investigation, we seek to shed light on the underlying mechanisms through which attachment style influences emotional processing and contribute to a more comprehensive understanding of the complex dynamics between attachment, cognitive processes, and emotional experiences.

In all the subsections below, ERP components (P200 and P400) were analyzed using a Welch ANOVA with a 2 (Attachment Style: Secure vs. Insecure) × 2 (Feedback Valence: Positive vs. Negative) design.

The primary objective of this study was to investigate how attachment style and feedback valence impact ERP components, specifically the P200 and P400. Our hypotheses were partially supported, as we observed significant effects of both attachment style and feedback valence on these components. Insecure individuals displayed noticeable changes in relative energy when transitioning from negative to positive feedback for both the P200 and P400 (Pan et al., 2019). Conversely, secure individuals demonstrated minimal to moderate variations in relative energy and maintained consistently lower levels of P200 energy. Numerous studies have indicated that individuals who feel secure exhibit reduced amygdala reactivity when exposed to negative or threatening emotional stimuli. This diminished amygdala response suggests that secure individuals may possess a more adaptable and regulated style of emotional processing (Gillath et al., 2005; Dannlowski et al., 2011; Vrtička et al., 2012). Secure individuals may also demonstrate enhanced functional connectivity between prefrontal and limbic regions involved in emotional processing, such as the amygdala and hippocampus. This heightened connectivity could facilitate the top-down regulation of emotions and foster a more balanced and adaptive emotional response (Tidwell et al., 1996; Coan et al., 2006; Kim et al., 2014).

Our findings show that insecure attachment is associated with heightened emotional reactivity, whereas secure attachment is characterized by effective strategies for regulating emotions. Our study’s examination of neural responses reveals distinct differences that shed light on how attachment style influences emotional processing. Specifically, the processing patterns associated with negative feedback demonstrate notable distinctions in both the P200 and P400 components. In the case of insecure individuals, a pronounced P200 response to negative feedback indicates heightened sensitivity to negative emotional stimuli. This heightened response suggests that insecure individuals are more attuned to negative feedback and may experience stronger negative emotional reactions. It is possible that their increased vigilance for potential threats, coupled with a tendency to interpret negative feedback as personally meaningful or impactful, contribute to this heightened sensitivity (Meyer et al., 1999; Liu et al., 2011; Weinberg et al., 2012).

Conversely, secure individuals exhibit a regulated P200 response to negative feedback, indicating effective emotion regulation strategies or a greater ability to reinterpret negative feedback in a less threatening manner. The significantly lower amplitude of the P200 response observed in our study highlights their emotional resilience and adaptive coping mechanisms associated with secure attachment. Secure individuals may employ strategies such as reappraisal or cognitive reframing to maintain emotional stability despite negative feedback (Wei et al., 2005; Coan et al., 2006).

In addition to the P200 component, the P400 component also demonstrates differential patterns in response to feedback valence based on attachment style. Both secure and insecure individuals showed increased intensity in the P400 component for positive feedback (Gentzler et al., 2010). However, insecure individuals display a significant decrease in the P400 component in response to negative feedback, reflecting a heightened negative emotional response. This suggests that they are more sensitive to negative feedback compared to secure individuals. The pronounced P400 response in insecure individuals aligns with their tendency to perceive negative feedback as more threatening or personally meaningful, leading to a stronger emotional reaction. On the other hand, secure individuals exhibit a more moderate decrease in the P400 component, indicating regulated emotional responses even in the face of negative feedback. This finding underscores the emotional resilience and adaptive coping mechanisms associated with secure attachment (Karreman and Vingerhoets, 2012; Kural and Kovacs, 2021).

Secure individuals tend to exhibit increased activation in prefrontal regions of the brain, such as the dorsolateral prefrontal cortex (DLPFC) and the ventromedial prefrontal cortex (vmPFC), during the processing of emotional stimuli which may explain the more moderate decrease in the P400 component in response to negative feedback. These regions are associated with cognitive control, emotion regulation, and the integration of emotional and cognitive information. Eppinger et al. (2009) examined developmental differences in learning and error processing using event-related potentials (ERPs), including the P400 component. The results suggested that the DLPFC is involved in the regulation of cognitive control processes, specifically in the late positive component (LPC), which overlaps with the P400 component. These findings highlight the role of attachment style in modulating early neural processing of negative feedback, with insecure individuals showing heightened sensitivity in both P200 and P400 responses, possibly due to increased vigilance for threats and a tendency to perceive negative feedback as personally meaningful. In contrast, secure individuals display more regulated responses in both P200 and P400 components, indicating emotional resilience and effective emotion regulation strategies. This unravels how attachment-related factors influence emotional reactivity and regulation, shedding light on their connection to defense mechanisms.

The results of this study have important implications for clinical interventions and therapeutic approaches aimed at improving emotional wellbeing and interpersonal relationships. For example, brain-computer interface (BCI) and biofeedback techniques can focus on enhancing emotional regulation, increasing defense mechanism awareness, and utilizing electrophysiological markers such as P200 and P400 responses to guide treatment progress (Lim et al., 2012; Friedrich et al., 2014; Kural and Kovacs, 2021). Future research should explore the association between attachment and defense mechanisms in clinical or treatment samples to provide a more comprehensive understanding of the implications for psychopathology and therapeutic interventions (Ciocca et al., 2020; Békés et al., 2021). Understanding the influence of attachment style on neural processing can inform the development of tailored interventions that address individuals’ attachment-related needs. By targeting specific neural mechanisms involved in emotional processing, interventions can potentially enhance emotional regulation skills and promote more secure attachment styles.

Despite the insights provided by this study, several limitations should be acknowledged. The study focused on a specific age group and may not generalize to other populations or developmental stages both cognitively and emotionally. Our caution about generalizability pertains to individuals outside the young adulthood age range and encompasses various cognitive and emotional developmental stages that may exhibit different attachment patterns and neural processing of emotional information.

Self-report measures were used to assess attachment style, which can introduce biases and limitations. Future research should include more diverse samples to account for different cognitive and emotional stages such as adolescence, middle adulthood, or late adulthood. Moreover it is needed to utilize objective measures of attachment, and consider longitudinal designs to examine the stability and developmental trajectories of attachment-related neural processes. Moreover, it is important to consider the relatively small sample size of the attachment classes. Therefore, conducting future research with a larger and more diverse participant pool would be beneficial in confirming and further enhancing the validity of our findings.

In conclusion, this study deepens our understanding of how attachment style influences defensive responses and the role of defense mechanisms as moderators of the attachment system. It contributes to our knowledge of the impact of attachment style and feedback valence on neural processing, specifically the P200 and P400 components. These findings underscore the significance of attachment style in shaping emotional reactivity and regulation, highlighting the relevance of attachment theory for comprehending individual differences in social and emotional functioning. Further research in this area will offer valuable insights into the intricate interplay among attachment, neural processes, and emotional experiences.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by the Ariel University IRB Committee. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

DM responsible for visualization and implementation of supporting algorithms. IZ and IL supervised the research activity. All authors carried out the stages of conceptualization, design of methodology, data curation, formal analysis, data modeling, model validation, writing, drafting and editing, discussed the results, read and approved the final manuscript and are accountable for all aspects of the work, read, and agreed to the published version of the manuscript.

The authors would like to acknowledge the assistance of OpenAI’s ChatGPT model, version 3.5, for proofreading and grammar corrections of this manuscript. It is emphasized that the ChatGPT tool was solely utilized for the purpose of enhancing the grammatical accuracy and readability of the text. The entirety of the manuscript’s content was originally conceived and authored by human contributors without the generative assistance of AI in the creation or modification of the academic content.