Modulation of Emotional Reactivity through Self-Administered Bilateral Stimulation Indexed by Neurophysiological Measures

Modulation of Emotional Reactivity through Self-Administered Bilateral Stimulation Indexed by Neurophysiological Measures | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 13 February 2026 V1 Latest version Share on Modulation of Emotional Reactivity through Self-Administered Bilateral Stimulation Indexed by Neurophysiological Measures Authors : Margherita Filosa 0009-0000-7078-2659 [email protected] , Camilla Panacci 0009-0008-2157-2004 , Luca Boccacci , BiancaMaria Di Bello 0009-0006-6784-9713 , Andrea Casella 0009-0009-0886-0439 , Merve Aydin , Francesca Strappini , Sabrina Pitzalis , and Francesco Di Russo 0000-0002-3127-9433 Authors Info & Affiliations https://doi.org/10.22541/au.177099141.10864120/v1 237 views 65 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This study aimed to investigate the effects of a single session of Butterfly Tapping (BT), a self-administered form of alternating bilateral stimulation, on emotional reactivity and its neurophysiological correlates. Thirty-two young healthy participants were randomly assigned to an experimental (Exp) or control (Con) group. The Exp group performed a 15-minute session of BT. Emotional reactivity was assessed before and after the stimulation using a detection task with emotional visual stimuli, presented during electroencephalographic (EEG) recording. EEG analyses were conducted using the event-related potential (ERP) method, specifically focusing on the differential amplitude (negative minus neutral) of the Late Positive Potential (LPP), a centro-parietal component associated with sustained processing of emotionally salient stimuli. Results revealed a significant LPP reduction in the Exp group at T1 compared to T0, whereas no change emerged in the Con group. The topographical distribution of the modulation was predominantly central, consistent with models implicating the LPP in higher-order integrative and evaluative processes. These findings provide preliminary neurophysiological evidence that BT may reduce cortical reactivity to negative emotional stimuli in young non-clinical populations, supporting its potential as a simple and accessible strategy capable of modulating affective responsiveness. Introduction Emotional responses to salient events vary widely in their intensity, duration, and persistence. This variability, commonly referred to as emotional reactivity, describes the magnitude and temporal dynamics of neural, physiological, and experiential responses elicited by emotionally salient stimuli, and represents a core dimension of affective functioning. Emotional reactivity reflects how strongly and how long affective systems remain engaged when confronted with emotionally relevant events, encompassing parameters such as response intensity, duration, and recovery dynamics (Davidson, 1998). Converging evidence indicates that elevated emotional reactivity is linked to a wide spectrum of internalizing symptoms, including anxiety and depression, across developmental stages and populations (McLaughlin et al., 2010; Shapero et al., 2016). Conversely, lower levels or more rapid attenuation of emotional reactivity have been linked to greater psychological resilience and reduced distress, suggesting that the degree to which emotional responses are shaped by contextual and experiential factors is relevant for overall well-being (Richard-Sephton et al., 2024). Together, these findings highlight emotional reactivity as a fundamental target for understanding affective vulnerability and resilience, independently of the specific processes that may later influence or shape emotional responding. Importantly, modulation of emotional reactivity does not necessarily imply the engagement of an explicit regulatory control system in a strict control-theoretic sense since changes in affective response may arise from multiple mechanisms operating at different levels (Davidson, 1998; Payne et al., 2015). While traditional approaches to emotional responding have primarily emphasized top-down strategies, such as cognitive reappraisal, mindfulness, and behavioral activation, emerging evidence has highlighted the potential of bottom-up methods, that operate through direct engagement of physical processes, particularly in conditions where affective load is high, limiting the applicability of cognitively mediated techniques (e.g., Payne et al., 2015; Webb et al., 2012). Within this context, a class of interventions that may influence emotional reactivity through bottom-up mechanisms is the alternating bilateral stimulation, used within the framework of the Eye Movement Desensitization and Reprocessing (EMDR) protocol, widely used in psychotherapy (Shapiro, 2001). In the EMDR, the most common bilateral stimulation involves alternating horizontal eye movements, as well as auditory or tactile stimulation, administered by the psychotherapist while the patient focuses on recurrent distressing memories of an emotionally traumatic event. The EMDR has proved to be effective in the treatment of post-traumatic stress disorder (for a review see Schubert & Lee, 2009), and its clinical application has progressively extended to a broader spectrum of trauma-related and emotion dysregulation conditions. Specifically, the EMDR is grounded in the Adaptive Information Processing (AIP) model, developed by Shapiro (1995, 2001), which conceptualizes psychological distress as the result of dysfunctionally stored memories of adverse life experiences. According to this framework, when traumatic or highly stressful events overwhelm the brain’s natural information processing capacity, these experiences may become encoded in a fragmented and maladaptive manner, disconnected from more adaptive cognitive and emotional networks. The persistence of such unprocessed memories can lead to dysfunctional responses, negative self-perceptions, and emotional dysregulation (Shapiro & Laliotis, 2011). The EMDR facilitates the reprocessing of these memories through bilateral stimulation, allowing the integration of previously isolated information into more adaptive memory networks, promoting symptom relief and psychological resilience (Shapiro, 2001). Neurobiological evidence suggests that alternating bilateral stimulation facilitates emotional processing by promoting interhemispheric connectivity (Propper & Christman, 2008), modulating limbic activity (Pagani et al., 2017), and reducing physiological hyperarousal (Sack et al., 2008a, 2008b). Based on these principles, simplified variants of alternating bilateral stimulation have been developed for broader application beyond clinical settings. Among these, the Butterfly Tapping (BT), also known as the butterfly hug, is a self-administered form of alternating bilateral stimulation in which individuals cross their arms over the chest and rhythmically tap their hands on their shoulders in an alternating (left-right) pattern (e.g., Artigas et al., 2000; Boel, 1999; Parnell, 2008). Originally introduced as an emergency stabilization technique following large-scale trauma events (Artigas & Jarero, 2014), the BT facilitates affective processing without external devices or clinical supervision, making it particularly suitable for implementation in non-clinical contexts such as stress prevention and everyday settings. The bilateral stimulation used in the EMDR, together with the other EMDR techniques, are presumed to preserve the core regulatory system obtained by the psychotherapy, potentially supporting affective stabilization through mechanisms such as interhemispheric communication and modulation of fronto-limbic circuits (Sack et al., 2008a, 2008b; Pagani et al., 2017). While its theoretical foundations are derived from EMDR protocols, the BT has been widely used in humanitarian aid, education, and public health settings as an emotion regulation technique (e.g., Shapiro, 2001). A recent systematic review (Mahyuvi & Ramadhan, 2025) analyzed eight studies, highlighting consistent anxiety-reducing effects of the BT in various populations, including university students, adolescents, elderly individuals, and patients undergoing stressful medical procedures. However, despite its growing use, empirical validation of the neural basis of BT’s efficacy is limited. Emotional reactivity can be investigated by assessing responses to emotional stimuli using standardized affective image sets, and numerous studies have shown that emotional valence affects perception and attention. Specifically, these effects are supported by neuroimaging evidence identifying that emotional pictures may affect a distributed network of brain regions, including the amygdala, insula, medial prefrontal cortex, anterior cingulate cortex, as well as premotor, temporal, and occipital areas (e.g., Barrett & Wager, 2006). While neuroimaging techniques, such as fMRI, offer high spatial resolution, event-related potentials (ERPs) provide greater temporal resolution, making them well-suited measures for capturing the dynamics underpinning neural responses during emotional processing. ERPs are voltage deflections associated with stimuli and events, extracted from the continuous electroencephalographic (EEG) signal, that provide a valid index of the brain’s processing of sensory, cognitive, or emotional events (e.g., Hajcak et al., 2010; Luck & Kappenman, 2011). ERPs have been widely used to study affective reactivity, giving evidence that the brain reacts differently to emotionally salient stimuli compared to neutral stimuli, particularly in components associated with perceptual, attentional, and evaluative processes (for a review, Olofsson et al., 2008). Specifically, the results of a systematic review (Schupp et al., 2006) highlighted that early components, such as the P1 and the N1, show greater amplitude in response to emotional compared to neutral stimuli, suggesting a facilitation in automatic attentional orienting and perceptual encoding of emotional cues (Carretié et al., 2004). However, since affective processing is a temporally extended process, later components, in particular the Late Positive Potential (LPP), reflect more closely the sustained evaluation of emotional stimuli and the engagement of higher-order cognitive-affective processes (e.g., Hajcak & Olvet, 2008). The LPP is a positive deflection, typically emerging around 300 ms following stimulus onset that may persist for a long time (e.g., up to six seconds in duration; Foti & Hajcak, 2008). The LPP shows greater amplitude in response to emotionally salient stimuli, whether with positive or negative valence, compared to neutral content, independently of factors such as stimulus novelty or task relevance (Cuthbert et al., 2000; Schupp et al., 2000). While early phases of the LPP, typically between 300 and 600 ms, are particularly sensitive to the arousal dimension of stimuli, later peaks appear more closely associated with the processing of emotional valence and the engagement of evaluative and motivational systems (Pastor et al., 2008; Weinberg & Hajcak, 2010). Topographically, the LPP originates over parietal-occipital regions and extends anteriorly over time, involving centro-parietal, frontal, and prefrontal areas. This spatiotemporal progression has been interpreted as reflecting a shift from early perceptual encoding to higher-order integration processes involving attentional and motivational systems (Keil et al., 2005; Sabatinelli et al., 2007). Specifically, the parietal LPP peak has been positively correlated with subjective emotional arousal, whereas the frontal LPP activity has been associated with the allocation of cognitive resources required for evaluative or regulatory processes (MacNamara et al., 2009). This dynamic distribution supports the idea of reciprocal influences between posterior sensory areas and anterior control regions, highlighting the interplay of bottom-up and top-down mechanisms in the elaboration of emotionally relevant stimuli. Importantly, the LPP is not only modulated by the intrinsic emotional salience of stimuli, but also by contextual and task-related factors that influence sustained affective engagement. A growing body of evidence demonstrates that top-down techniques, such as cognitive reappraisal (i.e., reinterpretation of the meaning of an emotional stimulus), lead to a significant reduction in the LPP amplitude, particularly in response to images with negative valence (e.g., Hajcak & Nieuwenhuis, 2006; MacNamara et al., 2009). Similarly, other techniques such as attentional distraction and expressive suppression seem to reduce LPP responses relative to passive viewing conditions (Foti & Hajcak, 2008; Moser et al., 2006). In contrast, when participants are instructed to maintain or intensify their emotional responses, LPP amplitudes remain elevated (Dennis & Hajcak, 2009), reflecting persistent affective engagement. Overall, the LPP offers a reliable and sensitive neural index of affective emotional reactivity, reflecting the magnitude and persistence of sustained neural engagement elicited by emotionally salient stimuli. Therefore, variations in LPP amplitude can serve as an objective, temporally precise marker of the degree to which an emotional response has been successfully modulated by a given strategy. For these reasons, the modulation of emotional responsiveness can be represented by the amplitudes of LPP difference waves, which are the absolute difference between the LPP evoked by negative and neutral pictures (e.g., Foti & Hajcak, 2008; Hajcak, MacNamara, & Olvet, 2010). Based on these findings, the present study aimed to investigate the neural correlates underpinning the alternating bilateral stimulation of the BT, through a comparison of the LPP before and after this self-stimulation in a non-clinical population. To do this, participants were divided into two groups and were exposed to negative and neutral images before and after the stimulation. While the experimental group performed the BT, the control group maintained an identical but static posture. By comparing pre- and post-stimulation LPP responses across conditions, we aimed to determine if the BT produces measurable changes in the neural responsiveness to emotionally salient stimuli. We hypothesized that the experimental group would exhibit a reduction in LPP amplitude in response to negative images after the BT session, reflecting a decrease in emotional arousal. No comparable modulation was expected in the control group. Such findings would provide evidence supporting BT as a feasible, self-administered intervention capable of producing measurable effects on both neurophysiological and subjective affective processing. Materials and Methods Participants Using the G*Power 3.1.9.7 program (Faul et al., 2009), the sample size was determined a priori. The present mixed 2×2 ANOVA design was based on Cohen’s f statistic. The expected effect size (f = 0.306) was derived from prior studies using emotional ERP paradigms targeting the LPP component (Bianco et al., 2024). The desired statistical power (1 – β) was set at 0.90, with an alpha level of 0.05. Under these conditions, the estimated sample size was 32 participants. Therefore, a total of 32 university students and staff were recruited. Participants were healthy, aged between 18 and 40 years (mean age = 24.6 years; SD = 2.8) (59% of females) with normal or corrected-to-normal vision. Inclusion criteria required full right-handedness as self-reported (Edinburgh Handedness Inventory; Oldfield, 1971), no history of neurological or psychiatric disorders, and no current use of psychoactive medications. All participants were naïve to the purpose of the study. Data was collected between July 2024 and February 2025. Participants were pseudo-randomly assigned to the experimental (Exp) or control (Con) group, which were balanced for sex and age. The present study was approved by the local ethics committee of the University of Rome “Foro Italico” (protocol number: CARD-74/2023), and conducted in accordance with the ethical standards of the Declaration of Helsinki. Written informed consent was obtained from each participant before participation. Self-Report Measures To verify the comparability of the two groups, participants completed the trait subscale of the State-Trait Anxiety Inventory (STAI-Y2; Spielberger et al., 1971) at the beginning of the experimental session. This 20-item self-report questionnaire evaluates stable personality-related tendencies to experience anxiety across time and situations. Independent samples t-tests confirmed no significant differences between groups ( t < 1). To capture transient emotional responses associated with the experimental manipulation, participants completed two tests, the State subscale of the STAI (STAI-Y1; Spielberger et al., 1971) and the Visual Analogue Scale (VAS; Gift, 1989), immediately after the Tasks described below. Specifically, the STAI-Y1 consists of 20 items assessing how anxious the participant feels “at the moment”, rated on a 4-point Likert scale ranging from 1 (”not at all”) to 4 (”very much so”). It provides a reliable index of momentary anxiety and is sensitive to situational changes, making it well-suited to evaluating the effects of affective processing interventions. Furthermore, the VAS was used to quantify subjective emotional discomfort related to the negative emotional content of the task. Participants were asked to indicate the intensity of discomfort experienced while viewing the negative images, with endpoints labeled “no discomfort” (0) and “extreme discomfort” (100). The VAS is a well-validated tool for capturing subtle affective changes in a fast and intuitive manner and is particularly useful in protocols involving repeated measures. Stimuli A total of 240 images were selected from the Nencki Affective Picture System (NAPS; Marchewka et al., 2014), a standardized database widely used for emotion research. Specifically, this database includes realistic photographs categorized by five content types: people, faces, animals, objects, and landscapes, each rated along three affective dimensions: valence (from 1 = very negative to 9 = very positive), arousal (from 1 = very calm to 9 = highly arousing), and approach/avoidance motivation (from 1 = strong tendency to avoid to 9 = strong tendency to approach). In the present study, the images used were divided into two emotional categories (negative and neutral), and each category was presented across two separate tasks (Task 1 and Task 2). Each task included 60 images of the same emotional valence, resulting in 60 negative images in Task 1, 60 negative images in Task 2, 60 neutral images in Task 1, and 60 neutral images in Task 2. Importantly, the image sets used in Task 1 and Task 2 were not repeated across time points. Specifically, each participant viewed one set at T0 and the other at T1, with the set assignment randomized across participants. This design allowed us to evaluate the generalizability of any observed effects to novel, previously unseen stimuli. All images were selected based on normative valence ratings, approach–avoidance motivation, and arousal, ensuring internal consistency within emotional categories (see Table 1). Negative – Task 1 2.57 2.86 6.86 Negative – Task 2 2.66 2.87 6.73 Neutral – Task 1 5.53 5.49 4.67 Neutral – Task 2 5.54 5.44 4.72 Table 1 : Mean ratings of valence, avoidance/approach motivation (Av/Ap), and arousal of the 240 images included in the tasks. Task Participants were comfortably seated in a dimly lit room, approximately 100 cm from a 32” 16:9 computer monitor. Visual stimuli were presented using Presentation Software (Neurobehavioral Systems, Albany, CA, USA). A small yellow fixation point (0.15×0.15° of visual angle) on a grey background remained visible at the center of the screen throughout the experiment to maintain gaze stability and minimize ocular artifacts. The experimental task was a variant of a simple detection task, where the participant had to respond as soon as possible to the visual stimuli described above using a response key with their right index finger, regardless of their emotional content. In each trial, images were presented in full-screen mode (subtending 35.4 x 31.7°) at the center of the display for 350 ms, then the fixation point remained for a randomized inter-stimulus interval ranging from 1200 to 3000 ms. The task was structured into 12 consecutive runs, alternating in emotional valence: 6 runs of negative images and 6 runs of neutral images. Each run contained 60 images of the same valence. The order of runs (starting with neutral or negative) was counterbalanced across participants to control for sequence effects. Each run lasted about 2 min and 30 sec, resulting in a recording session duration of approximately 35 min, including breaks. For each valence, 360 trials were collected, for a total of 720 trials per participant. This task has been executed during EEG recordings before and after the stimulation session described below. Stimulation Following the first task session, participants executed a 15-minute self-administered tactile stimulation session, which differed depending on group assignment. The Exp group performed the BT (Artigas & Jarero, 2014). The posture followed the traditional butterfly hug configuration (Figure 1): participants were seated on a chair and were instructed to cross their hands and rest their fingertips gently over the suprasternal notch, with thumbs crossed and hands positioned just below the clavicles. From this position, they had to alternate bilateral tapping with their fingertips while keeping their eyes closed and mentally focusing on the negative images previously viewed during the task to maintain affective engagement across the session and ensure continuity between the pre- and post-stimulation EEG recordings. This instruction was intended to prevent disengagement from the emotional context during the stimulation interval. The tapping rhythm was modelled on the original Butterfly Hug procedure (Artigas & Jarero, 2014), and was kept consistent across participants, approximating a rate of one tap per second for standardization purposes in the experimental setting. On the other hand, in the Con group, the posture and instructions were identical. However, instead of rhythmic alternate tapping, participants rested their hands in place without movement (static stimulation). The posture-matched static control condition was selected to provide a conservative baseline by maintaining identical posture, environmental setting, and task structure across conditions. This control was designed to minimize confounds related to body position, visual input, and general task demands. Importantly, the present control condition was not intended to function as an active motor or attentional control, but rather as a conservative comparison allowing assessment of whether observed changes in affective neural responsiveness exceeded those attributable to time-on-task or repeated exposure alone. The session was structured into four blocks of 3 minutes each, interleaved with one-minute pauses. This structure provides sufficient exposure to stimulation while minimizing muscular fatigue and maintaining attention. Before the stimulation, the participants rehearsed the alternating pattern until a consistent and relaxed tempo was achieved. No auditory pacing was used during the actual session to preserve a spontaneous rhythm. Experimental Procedure The participants were fitted with the EEG cap and received instructions for the upcoming tasks. The experiment followed a pre-post design with three consecutive phases (Figure 1): Baseline assessment (T0), a 15-minute stimulation session, and post-assessment (T1). At both T0 and T1, participants performed the task while the EEG was recorded and completed the STAI-Y1 and the VAS. Figure 1 : Schematic representation of experimental design. At T0, participants performed the task and the State-Trait Anxiety Inventory – State version (STAI-Y1) and the Visual Analogue Scale (VAS) for discomfort. Participants assigned to the experimental (Exp) group performed a 15-minute self-administered bilateral tapping session (Butterfly Tapping), while subjects of the control (Con) group adopted the same posture without performing any tapping (static position). At T1, participants repeated the task, followed again by the STAI-Y1 and the VAS. During the task, EEG was continuously recorded. EEG recording and ERP analysis During the task, continuous EEG was recorded using BrainProducts GmbH (Gilching, Germany) equipment, including Recorder 1.2 software and three BrainAmp amplifiers. Two of the amplifiers were connected to a 64-channel ActiCap active electrode system, mounted according to the 10-10 International System. EEG data were sampled at 250 Hz and band-pass filtered offline using a second-order zero-phase Butterworth filter (0.01 – 60 Hz) with an additional 50 Hz notch filter. All signals were referenced to the average of M1 and M2 electrodes. Bipolar electrooculographic (EOG) activity was recorded using a third BrainAmp ExG amplifier, with electrodes placed at the outer canthi of left and right eyes (horizontal EOG), and above and below the left eye (vertical EOG). Electrode impedances were kept below 5 kΩ. On average, 6.7 ± 3.4 electrodes were interpolated in the Con group and 6.1 ± 4.2 in the Exp group. Ocular artifacts (blinks and movements) were removed using the Gratton and Coles algorithm (Gratton et al., 1983), and residual noise was excluded via semi-automatic artifact rejection, discarding epochs with amplitudes exceeding ± 70 μV. After artifact rejection, an average of 8.1% of trials were excluded from the Con group and 6.7% from the Exp group. To measure post-stimulus activity, 1200 epochs were extracted time-locked to stimulus onset, ranging from 200 ms before to 1000 ms after it. The 200 ms pre-stimulus interval served as the baseline. For each subject, ERP waveforms were averaged separately for negative and neutral stimuli. ERP components were identified using the ”collapsed localizer” approach (Luck & Gaspelin, 2017), averaging across all groups and conditions to identify the electrodes to include in statistical analysis. Furthermore, to define analysis intervals, the Global Field Power (GFP) was computed. Specifically, the GFP is a reference-free measure that summarizes the overall distribution of electrical activity across the scalp into a single waveform, providing a measure of the global strength of the ERP signal at each time point. It is computed as the root mean square of the voltage values recorded at all electrodes, simultaneously, across the scalp. The main GFP peaks were used to identify the most prominent ERP components, and the time windows were determined by including the intervals in which the GFP amplitude exceeded 80% of the local maximum. Similarly, corresponding electrodes showing at least 80% of the maximum amplitude within each interval were grouped into spatial pools. As shown in Figure 2 and Figure 3, two separate GFP waveforms were generated: one based on the grand average of all post-stimulus activity, and another based on the differential waveforms obtained by subtracting neutral from negative trials. While the first waveform displayed multiple peaks, including those corresponding to early and late visual components, the second one highlighted two time-windows with strong affective modulation: Frontal Positivity (188–228 ms) and central LPP (cLPP; 456–552 ms). For statistical analysis, we focused on the components extracted by the difference waves, capturing the emotion-related modulation of interest. The electrodes included in the analysis were selected according to the scalp distribution of maximal amplitude in this window, averaging all sites whose activity exceeded 80% of the GFP peak. This procedure identified two electrode pools: a frontal cluster including F1, Fz, F2, FC1, FCz, and FC2, and a centro-parietal cluster comprising Cz, C1, C2, CP1, CPz, and CP2, both consistent with the canonical distribution of the LPP component (Hajcak et al., 2010). Mean amplitudes in this time window and pool were extracted for each condition and used in subsequent statistical comparisons. Figure 2 : Global Field Power (GFP) of the collapsed localizer computed across all participants and conditions. The shaded areas highlight the time windows of interest (104–156 ms, 212–316 ms, 420–504 ms, 732–972 ms). Scalp topographies correspond to the main ERP components: pN1, P1, pN2, P2, central LPP (cLPP), and frontal LPP (fLPP). Figure 3 : Global Field Power (GFP) of the collapsed localizer computed on differential waves (negative - neutral) across all groups, with corresponding scalp topographies showing Frontal Positivity (188–228 ms) and central LPP (cLPP; 456–552 ms). Statistical Analysis Prior to statistical testing, the normality assumption for all variables was assessed using the Shapiro–Wilk test. None of the distributions deviated significantly from normality. The assumption of homogeneity of variance was tested using Levene’s test, which confirmed that the data met the criterion for homoscedasticity. The behavioral and psychological measures were analyzed using a 2×2×2 ANOVA, with Group (Exp vs. Con) as a between-subjects factor and Time (T0 vs. T1) and Valence (Negative vs. Neutral) as a within-subjects factor. Furthermore, a 2×2 ANOVA was conducted on the mean amplitudes of the Frontal Positivity and cLPP difference waves, with Group and Time as factors. Effect sizes were reported using partial eta squared (ηp²). Where significant main effects or interactions were found, Bonferroni-corrected post-hoc tests were applied. All tests adopted an α threshold of 0.05. Analyses were performed using Statsoft Statistica 12.0 (StatSoft Inc., Tulsa, OK, USA). Transparency and Openness We report how we determined our sample size, all data exclusions (if any), all manipulations, and all measures in the study. All materials and data used in this study will be available in a timely manner to other researchers upon request to the corresponding author. This study was not preregistered. Self-report scales As shown in Figure 4, anxiety and discomfort in T1 increased in the Con group and decreased in the Exp group. The ANOVA on state anxiety found non-significant effects of Group and Time (F < 1). However, the Group x Time interaction was significant (F (1,30) = 9.0, p < 0.01, η p ² = 0.231). Post-hoc comparisons showed that at T1, the STAI-Y1 score of the Exp group (17.9 ± 3.4) was significantly lower ( p < 0.05) compared to T0 (20.1 ± 3.9). In the Con group, the T1 score (20.2 ± 4.4) did not differ significantly from the T0 score (19.1 ± 3.7). The ANOVA on the discomfort score found non-significant effects of Group and Time (F < 1). However, the Group x Time interaction was significant (F (1,30) = 11.1, p < 0.01, η p ² = 0.277). Post-hoc comparisons showed that at T1, the VAS score of the Con group (45.0 ± 9.1) was significantly higher ( p < 0.05) compared to T0 (36.9 ± 7.5). In the Exp group, the T1 score (33.5 ± 7.1) did not differ significantly from the T0 score (38.5 ± 8.2). Figure 4 : Interaction between Group and Time in the self-report scales. State anxiety scores from the State-Trait Anxiety Inventory (STAI-Y1); intensity of discomfort experienced from viewing the negative images. The vertical lines represent the 0.95 confidence interval. * p < 0.05. Behavioral data ANOVA on the Response Time (RT) showed a significant effect of Valence (F (1,30) = 54.6, p < 0.01, η p ² = 0.646), with larger RTs for negative (253 ms, SD = 19) than neutral images (244 ms, SD = 18) as presented in Figure 5a. The Group (F (1,30) = 3.4, p = 0.07) and the Time (F (1,30) = 1.4, p = 0.25) factors did not reach statistical significance. The interactions between factors were not significant (F < 1). ANOVA on the Omission rate revealed a significant effect of Valence (F (1,30) = 15.1, p < 0.01, η p ² = 0.335), with less omission for negative images (Figure 5b). The Time effect was also significant (F (1,30) = 6.9, p = 0.02, η p ² = 0.169), with less omissions in T1 than T0. The Group effect (F < 1) was not significant. The interactions between factors were not significant (F < 1). Figure 5 : Results of the behavioral measures of the task. a) Response Time (RT); b) Omission rate. The vertical lines represent the 0.95 confidence interval. ** p < 0.01. ERP data Figure 6 shows the ERP waveforms separately for the Exp and Con groups, before and after the stimulation session, and both emotional valences, allowing a detailed inspection of raw waveform morphology and group-wise evolution over time. In contrast, Figure 7 presents the difference waves (Negative minus Neutral) to highlight the selective modulation of affective processing. In both figures, the components of interest are labeled near their respective peaks. Figure 6 : ERP waveform of the experimental (Exp) and control (Con) groups, before (T0) and after (T1) the stimulation. The head representation on the left indicates the electrode included in the two spatial pools considered. Figure 7 : ERP Difference waves of the experimental (Exp) and control (Con) groups, recorded before (T0) and after (T1) the stimulation. The top panel shows the Frontal Positivity, and the bottom panel shows the central LPP. The head maps on the left illustrate the electrode sites included in the two spatial pools used for statistical analysis. Although the amplitude tended to increase in the Con group and decrease in the Exp group, ANOVA on the Frontal Positivity showed no significant effect (F < 1). The interaction between Group and Time is reported in the upper panel of Figure 8. ANOVA on the cLPP showed a marginally significant effect of Group (F (1,30) = 4.2, p = 0.05, ηp ² = 0.123), while the effect of Time was not significant (F < 1). The interaction Time × Group (F (1,30) = 6.3, p = 0.02, η p ² = 0.174) was significant. Post-hoc comparisons showed that at T1, the cLPP differential amplitude of the Exp group (2.05 µV ± 0.73) was significantly reduced ( p = 0.03) compared to T0 (3.53 µV ± 0.77) and to T1 of controls ( p = 0.04). In contrast, in the Con group, the T1 (3.39 µV ± 0.50) did not differ significantly from the T0 (3.77 µV ± 0.60; p = 0.60), indicating that the observed modulation occurred selectively in the group receiving bilateral alternating stimulation. This interaction is reported in the lower panel of Figure 8. Figure 8 : Interaction between Group and Time in the Difference Wave (Negative minus Neutral). a) Frontal Positivity amplitude, b) central LPP (cLPP) amplitude. The vertical lines represent the 0.95 confidence interval. * p < 0.05. Discussion The present study provides neurophysiological evidence supporting the potential impact of BT, a self-administered form of bilateral alternating stimulation, in modulating neural indices of emotional reactivity. Specifically, the present findings suggest that a single session of BT may reduce the amplitude of an ERP component, the LPP, a centro-parietal wave that reflects enhanced cortical processing of emotionally salient stimuli (e.g., Cuthbert et al., 2000; Hajcak & Foti, 2020). It has been shown to be sensitive to both top-down and bottom-up interventions (Foti & Hajcak, 2008), including cognitive reappraisal, attentional deployment, and affective labeling (MacNamara et al., 2009). The reduction observed here suggests that the BT is capable of modulating the sustained allocation of attentional and evaluative resources to negative information, a process often associated with vulnerability to anxiety and mood disorders, as heightened and persistent engagement with negative information constitutes a known risk factor for internalizing psychopathology (Dennis & Hajcak, 2009). The scalp distribution of the effect observed was predominantly central, consistent with integrative models of the LPP that go beyond simple perceptual amplification. Recent accounts highlight the role of the LPP in interoceptive-affective integration, whereby sensory, limbic, and prefrontal inputs converge to shape sustained affective processing (Hajcak & Foti, 2020; Liu et al., 2012). In this context, the reduction in the central LPP amplitude observed after the stimulation supports the potential use of the BT as a non-cognitive technique modulating the neural reactivity to emotionally salient stimuli, possibly by disrupting or attenuating the automatic amplification of negative emotional content (Barrett & Wager, 2006). From a neurofunctional perspective, the BT may influence emotional reactivity by engaging embodied and sensorimotor mechanisms that alter the dynamics of affective processing. Within the broader framework of EMDR-related research, alternating bilateral stimulation is hypothesized to synchronize activity across hemispheres, enhancing communication between prefrontal regions involved in affective processing and subcortical structures, such as the amygdala and the insula (Amano & Toichi, 2016; Pagani et al., 2012), facilitating the reprocessing of emotionally charged memories by promoting a shift from dysfunctional to more adaptive neural representations of distressing affective responses. In line with the principles of the AIP model (Shapiro, 2001), in the BT, the rhythmic alternation of tactile input might serve as an embodied cue that facilitates the processing of emotionally charged material, potentially promoting adaptive integration. Importantly, the modulation of the LPP observed in the present study was not limited to specific stimuli previously encountered. Indeed, different image sets were used at T0 and T1, for both neutral and negative valence, to assess the generalizability of the effect and to minimize the habituation phenomena. The significance of the effect persistence towards novel stimuli suggests that the BT may influence more general aspects of affective neural responsiveness, extending beyond stimulus familiarity. This generalization effect has important implications for the potential use of the BT in clinical and non-clinical settings, indicating its capacity to modulate the neurophysiological substrates of affective responses in a more robust and transferable way, rather than being restricted to highly specific or conditioned contexts (Dennis & Hajcak, 2009; Hajcak & Nieuwenhuis, 2006). In contrast, early components, such as the P1, pP1, P2, which are typically associated with sensory encoding and exogenous attentional capture (Di Russo et al., 2019; Luck, 2014), even if not directly investigated, were not affected by the intervention, corroborating the hypothesis that the BT, rather than influencing low-level perceptual processes, may selectively target post-perceptual stages of affective processing. This pattern is consistent with prior evidence showing that implicit or non-cognitive regulatory techniques tend to modulate later stages of processing, while leaving early perceptual encoding unaffected (Hajcak et al., 2009; Schindler & Kissler, 2016). These studies underscore the potential complementarity of BT with cognitive strategies. Indeed, while cognitive reappraisal reshapes the meaning attributed to a stimulus from the outset, the BT may intercede downstream, reducing the affective load already generated by stimulus evaluation. In line with neurophysiological evidence, self-report measures revealed a selective improvement after the stimulation only in the experimental group, characterized by reduced state anxiety and discomfort, whereas the control group showed an opposite trend of increased distress. This pattern is consistent with previous studies reporting decreased subjective arousal and distress following bilateral stimulation, often accompanied by a self-perceived sense of calmness, grounding, and affective distance from emotionally charged material (e.g., Horn et al., 2016; Shapiro, 2017). Such experiential feedback has been interpreted as the subjective correlate of the neurophysiological reduction of emotional reactivity observed during bilateral stimulation (Sack et al., 2008a, 2008b; Pagani et al., 2017). The convergence between neurophysiological and subjective measures suggests that BT may influence both central and experiential aspects of emotional responding. Moreover, the behavioral results revealed a consistent valence effect, with slower responses for negative compared to neutral images, consistent with evidence that emotionally salient, especially unpleasant, stimuli capture and hold attention more strongly than neutral ones (Lang, Bradley, & Cuthbert, 1997; Schupp et al., 2006). This emotional slowing is commonly interpreted as a consequence of enhanced perceptual and attentional engagement driven by the motivational relevance of negative cues (Carretié et al., 2004; Vuilleumier et al., 2004). Neurocognitive models propose that such stimuli elicit prioritized processing within occipito-parietal and limbic circuits, resulting in greater evaluative depth at the expense of processing speed (Pessoa, 2009). At the same time, the lower number of omission errors for negative stimuli suggests that emotional salience not only prolongs perceptual evaluation but also enhances vigilance and response readiness. This is consistent with evidence showing that emotionally salient stimuli increase tonic alertness through the activation of occipital, parietal and limbic regions, such as the amygdala, which prioritize emotional content through attentional bias (Vuilleumier, 2005; Schupp et al., 2006). Finally, omission errors were globally lower at T1 compared to T0, regardless of valence or group, indicating a practice or adaptation effect. Repeated exposure to the task likely improved attentional efficiency and response monitoring, reflecting a general optimization of cognitive performance over time (MacNamara et al., 2009). Together, these findings indicate that the behavioral data reflects general affective and temporal dynamics in performance rather than specific effects of BT. From a clinical perspective, these findings are particularly relevant. The potential role of BT in reducing cortical responsivity to negative stimuli suggests that it may represent an accessible tool for populations with limited resources or reduced capacity to engage in cognitively demanding strategies, such as individuals experiencing chronic stress, subclinical anxiety, depressive symptomatology, or in early preventive contexts (e.g., Hajcak & Nieuwenhuis, 2006). Moreover, the observed generalization effect increases the translational potential of the BT. If such modulatory effects extend to novel, previously unseen stimuli, this approach may be relevant for everyday affective functioning beyond trauma-related contexts, with potential implications for resilience-related processes. Despite these promising findings, several limitations should be acknowledged. First, the sample size, although determined a priori and consistent with similar ERP studies, remains relatively small. Second, the absence of direct autonomic measures, such as heart rate variability or electrodermal activity, prevents verification of the hypothesized activation of the parasympathetic system, which previous work has linked to alternating bilateral stimulation and reduced physiological arousal (Sack et al., 2008a, 2008b; Thayer et al., 2012). Integrating autonomic indices with electrophysiological markers would therefore allow us to confirm that the observed decrease in LPP amplitude reflects an autonomic downregulation rather than an attentional disengagement or reduced motivational salience. Moreover, the participants were primarily young adults recruited from a Western, educated university population. Therefore, the findings should be interpreted within this demographic and cultural context. Finally, the short-term design does not allow conclusions about the durability of the observed effects. Indeed, it could be useful to address these issues by employing longitudinal designs and follow-up assessments to evaluate the persistence and potential reinforcement of BT effects over time. Furthermore, future studies should investigate whether these effects are mediated by changes in large-scale brain networks, such as the salience network, default mode network, or central executive network. The integration of EEG with functional neuroimaging or source localization could provide important insights into the precise neural generators of the observed effects. In conclusion, the present study contributes to the growing literature on embodied and bottom-up techniques for affective modulation by providing neurophysiological evidence that BT may attenuate cortical responses to negative emotional stimuli, warranting replication in larger samples and clinical contexts. By selectively reducing the LPP, the BT appears to influence evaluative stages of affective processing of aversive content, extending beyond stimulus familiarity and and potentially generalizing across contexts. These findings hold both theoretical and applied implications, highlighting emotional reactivity as a meaningful target for future research and supporting further investigation of BT as a simple, accessible technique capable of influencing affective neural dynamics. Constraints on Generality The present findings are based on a sample of young, healthy, right-handed adults recruited from a university population, which may limit their generalizability to other demographic or clinical groups. The results may not extend to individuals with psychiatric or neurological conditions, older adults, or populations with different cultural backgrounds. Moreover, the effects observed were derived from a single 15-minute session of Butterfly Tapping applied in a controlled laboratory context using visual emotional stimuli. Therefore, caution should be exercised when generalizing these outcomes to long-term applications, real-life emotional experiences, or different sensory modalities. Author Note Author contributions According to the CRediT taxonomy, M.F. contributed to the conceptualization, methodology, formal analysis, investigation, visualization, project administration, and writing of the original draft. C.P. contributed to methodological development and data curation. L.B. and B.M.D.B. contributed to data acquisition. M.A. and A.C. contributed to validation procedures and methodological supervision during the initial phases of the study. F.S., S.P., and F.D.R. supervised the project and contributed to its conceptualization, while F.S. and F.D.R. also secured the funding that supported this research. 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Authors Affiliations Margherita Filosa 0009-0000-7078-2659 [email protected] Universita degli Studi di Roma Foro Italico View all articles by this author Camilla Panacci 0009-0008-2157-2004 Universita degli Studi di Roma Foro Italico View all articles by this author Luca Boccacci Universita degli Studi di Roma Foro Italico View all articles by this author BiancaMaria Di Bello 0009-0006-6784-9713 Universita degli Studi di Roma Foro Italico View all articles by this author Andrea Casella 0009-0009-0886-0439 Universita degli Studi di Roma Foro Italico View all articles by this author Merve Aydin Universita degli Studi di Roma Foro Italico View all articles by this author Francesca Strappini Universita degli Studi di Roma Foro Italico View all articles by this author Sabrina Pitzalis Universita degli Studi di Roma Foro Italico View all articles by this author Francesco Di Russo 0000-0002-3127-9433 Universita degli Studi di Roma Foro Italico View all articles by this author Metrics & Citations Metrics Article Usage 237 views 65 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Margherita Filosa, Camilla Panacci, Luca Boccacci, et al. Modulation of Emotional Reactivity through Self-Administered Bilateral Stimulation Indexed by Neurophysiological Measures. Authorea . 13 February 2026. DOI: https://doi.org/10.22541/au.177099141.10864120/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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