High alpha-band activity of prefrontal cortex contributes to the significant neural alterations in the initial two-month phase of a romantic relationship

High alpha-band activity of prefrontal cortex contributes to the significant neural alterations in the initial two-month phase of a romantic relationship | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report High alpha-band activity of prefrontal cortex contributes to the significant neural alterations in the initial two-month phase of a romantic relationship Zhizhen Zhang, Chuanliang Han This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5835787/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Romantic relationships are integral to human experience, with most individuals encountering them at some point in their lives. The neural mechanisms of romantic relationships have gradually gained attention. However, existing studies have mainly focused on the cross-sectional level, and longitudinal research is not sufficient, especially regarding the early stages when couples first enter a romantic relationship. The brain's neural transition from a normal state to the honeymoon phase of love remains poorly understood. To answer this question, we, the authors, used ourselves as subjects; after confirming our romantic relationship, we employed portable electroencephalography (EEG) to record neural activity in the prefrontal cortex during resting states (both with eyes open and closed). Data collection occurred irregularly over a period of around two months, resulting in 13 EEG data trials per individual. We found that there was a consistent decrease in the high alpha band neural activity under the closed-eye state for both of us over the two-month period, suggesting a potential correlation with the neural activity changes in the early stage of the romantic relationship. Further analysis revealed that this decrease was driven by changes in periodic components rather than non-periodic components. This study is the first to reveal a significant change in the alpha oscillatory activity of the prefrontal cortex in a couple during the initial two months after confirming their romantic relationship, which will further impact the understanding of the mechanism of alpha sub-oscillations and their application in the study of emotions process. Cognitive Neuroscience Alpha Oscillation EEG Periodical activity Love Relationship Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Romantic love is a universal experience that most people will encounter at some point in their lives 1,2 . Falling in love is an intimate relationship that individuals independently, voluntarily, and freely establish in their life journey 3–5 . The brain undergoes significant changes when in a state of love 6–10 , including various physiological and psychological aspects. When a couple officially confirms their romantic relationship, the specific neural, particularly during the initial honeymoon period, remain poorly understood. To explore the neural activity associated with romantic relationships 11,12 , previous studies have used methods such as functional magnetic resonance imaging (fMRI) 13,14 and electroencephalography (EEG) 15,16 . However, these studies are mainly cross-sectional, based on the differences between different groups and the neural responses to different love-related visual stimuli 14,17–19 . To date, no longitudinal study has explored how the neural activity of a couple evolves after they formally enter a romantic relationship. The scarcity of such research is primarily due to the inherent difficulty in obtaining this kind of data, which involves recruiting participants, initiating data collection immediately after the confirmation of their romantic relationship, and consistently tracking and collecting multiple EEG data over time from the same individuals. Neural oscillations are a key neurobiological feature in EEG signals, particularly the alpha oscillations (8-13Hz), which are significantly stronger in a closed-eye state than in an open-eye state 20–25 . They are also associated with various cognitive functions 26–30 , and abnormal alpha oscillations are linked to mental disorders 31–37 . In recent years, increasing research has discovered that the alpha band does not consist of a single type of oscillation; multiple sub-oscillations may exist within this narrow band 38–40 , each with different neural origins and potentially linked to different cognitive functions 41 . However, it is not entirely clear whether these different sub-oscillations are related to emotional states. Additionally, more recent studies have made more detailed distinctions in the spectral components: periodic and aperiodic components 42 , each representing different neural mechanisms. Analyzing these components separately can further our understanding of the mechanisms behind the spectrum. Yet, the association between romantic love and different spectral components remains unclear. Given our extensive experience in neuroscience and applied mathematics, we, the authors of this study, have chosen to serve as our own research subjects to investigate this phenomenon. After confirming our romantic relationship, we collected prefrontal EEG data 13 times over a span of two months (67 days) using portable EEG devices. During these periods, our relationship deepened and strengthened than the beginning stage. If romantic love can affect neural responses, we assume that a couple would exhibit consistent changes in certain neurobiological characteristics. To test this hypothesis, we performed spectral analysis on each EEG data collection, aiming to identify specific frequencies in the prefrontal lobe where neural responses of both individuals exhibited significant changes with the duration of their acquaintance. Materials and Methods Participants Two right-handed healthy individuals, which is a couple (one male, HCL, aged 31 and one female, ZZZ, aged 24), participated in this study. Both subjects are Han Chinese, from northern part of China, and do not have any religious belief. Both participants provided informed consent, and the EEG data recording procedures adhered to the National Institutes of Health Guidelines and received ethical approve from the Shenzhen Institute of Advanced Science and Technology, Chinese Academy of Sciences (SIAT-IRB-231113-H0677). Neurophysiological recording Each participant contributed 13 sets of resting-state EEG data over approximately two-month period (67 days, from the first day they met in face in 2024), resulting in a total of 26 resting-state EEG datasets. Resting-state EEG recordings were obtained under both open-eye and closed-eye conditions using a single-electrode setup (Fpz) with the Brain Pro system (China) (Fig. 1 ). Each recording session involved both subjects being present simultaneously. One subject first had their EEG recorded for 3 minutes with their eyes open and then for another 3 minutes with their eyes closed. Subsequently, the other subject also underwent EEG recording first for 3 minutes with their eyes open followed by 3 minutes with their eyes closed. The reference electrode was positioned at the earlobe, and online data were filtered using a bandpass filter with cutoff frequencies of 0.5 and 30 Hz. The sampling rate was 512 Hz and the scalp impedance was maintained below 10 kΩ for the electrode. Eye-blink artifacts were removed with unsupervised machine learning algorithms 43 . Power Spectrum Analysis The power spectrum of the EEG response was estimated using the multitaper method 44,45 (time-bandwidth product, 3; tapers, 5; Chronux toolbox ( http://chronux.org/ ), implemented through custom software written in MATLAB. Spectrum analysis is a technique used to decompose complex signals into simpler ones based on the Fourier transform. Essentially, the multi-taper method aims to reduce the variance of spectral estimates by premultiplying the data with several orthogonal tapers known as Slepian functions. This method is widely applied in various biomedical studies (e.g., biological science 46–53 , and public health 54–58 . The relative power can be defined as Eq. 1(Fig. 1 C). $$\:Rel\:Power\left(f\right)=\frac{Power\left(f\right)}{\sum\:_{3Hz}^{20Hz}Power\left(f\right)}\:\:\:\:\:（1）$$ Where \(\:Power\left(f\right)\) denotes the absolute power calculated using multi-taper method. Descriptive Model for Dissecting Aperiodic and Periodic Activity The power spectrum was considered as the summation of two component: aperiodic and periodic components. The aperiodic component of the power spectrum was extracted using a 1/f like function (Eq. 2), where a, b, c and d represent the model parameters to be estimated. The periodic component was defined as the residual obtained by subtracting the aperiodic component from the raw power spectrum. This method has been used in the characterization of gamma-band and alpha-band activities 42,59,60 . $$\:Aperiodic\:Activity\left(f\right)=\frac{a}{{f}^{b}+c}+d\:\:\:\:\:\:\:\:\left(2\right)\:$$ Statistical Analysis Pearson correlation analysis was conducted to measure the relationship between relative power in the alpha band (low, medium and high alpha bands), as well as the aperiodic and periodic activity in the high alpha band, and the number of days elapsed since the start of romantic relationship. Analyses were performed separately for the open-eye and closed-eye states respectively. Results In this study, we collected and analyzed a precious dataset tracking the first two-month of prefrontal cortex EEG recordings (13 recording trials) from a typical couple (i.e. the two authors of this paper) who had just formally entered their romantic relationship (Fig. 1 ). During each trial, three-min of EEG data was recorded in both open-eye (Fig. 2 A, white curve) and closed-eye states (Fig. 2 A, black curve). Stable two months recordings of portable EEG devices Thirteen demo trace of EEG signal in the couple in both open and closed-eye state was shown in Fig. 1 A. Alpha oscillation was clearly induced by closing eyes of each subject compared with that in open-eye state in both time domain or frequency domain, which is consistent with previous studies 38,61 . Despite some minor variability of power spectrum in these 13 recordings, the current results still revealed that the frequency and bandwidth of the alpha oscillations remained stable across 13 recordings (Fig. 2 B-D), which suggests a stable EEG data quality throughout the 2-month recording using this portable one-channel EEG system. The two subjects have distinct alpha patterns, the alpha peak of HCL locates smaller than 10Hz, while that of ZZZ is larger than 10Hz, they still fall in the range of alpha band and become weaker during eye-open state. Based on these stable recording and high-quality neural signals, we would do further analysis in the following sections. Strength of high alpha band activity decreases in the first two months of romantic relationship We then conducted correlation analysis between the relative power in each frequency and the number of days elapsed since the start of the romantic relationship (Fig. 3 ). Pearson correlations were calculated individually (Fig. 3 A for ZZZ, and Fig. 3 B for HCL), revealing significant correlations at specific frequencies (second rows in Fig. 3 A and 3 B). To identify consistent change between the two subjects, we averaged the correlations of ZZZ and HCL in open and closed-eye states (Fig. 3 C). Notably, a consistent and pronounced decrease in high alpha band was observed in the closed eye state (Fig. 3 C, black curves). Subsequently, we performed separate correlation analysis for low (8-9.5 Hz), medium (9.5-11Hz) and high (11.5-13Hz) alpha band with latency days, and verified a significant negative correlation in high alpha band in ZZZ (Fig. 3 D, first row, r=-0.76, p = 0.0026) and HCL (Fig. 3 D, second row, r=-0.73, p = 0.0045), but not in low or medium alpha band (ps > 0.05). Periodic activity in high alpha band contributes to the significant change in first two-month romantic relationship Furthermore, we dissected the power spectrums into aperiodic and periodic components for each trial in open-eye and closed-eye states individually (Fig. 4AB). Then we got 13 aperiodic and periodic activities in each subject. Given the significant findings in high alpha band in closed-eye state, we focused further analysis on this specific frequency band and state. Our results indicated that the significant correlation in high alpha band observed was primarily driven by periodic activity (ZZZ, r=-0.73, p = 0.0043; HCL, r=-0.75, p = 0.0029) rather than aperiodic activity (ZZZ, r=-0.22, p = 0.48; HCL, r=-0.39, p = 0.19) (Fig. 4 C). Discussion In this study, we present an interesting analysis of EEG data, which, to the best of our knowledge, is the first in the world to track and follow up on neural responses in a couple immediately after the establishment of a romantic relationship. Over a two-month period, we conducted 13 EEG recordings, directly capturing the changes in prefrontal lobe neural activity as the couple transitioned from confirming their relationship to the honeymoon phase. Our findings reveal that these changes are primarily reflected in the power spectrum concentrated in the high alpha frequency band. Furthermore, through mathematical modeling, we observed alterations in neural responses is mainly contributed by the periodic activity in the high alpha frequency band rather than by the aperiodic activity. Through longitudinal tracking, this study fills a gap in the field of romantic emotions and, as an exploratory investigation, holds significant value. The primary distinction between our work and previous research lies in our use of longitudinal follow-up collections to monitor neural responses from two individuals over time, in order to describe how neural activities in different frequencies change. Previous studies typically involved comparisons between two distinct groups—those in romantic relationships and those not 62 —in conjunction with visual 62–65 , auditory 62 , or sensory 66 perception tasks. These studies have highlighted significant associations between alpha band activity and romantic relationships, as well as differences in event-related potentials, such as the late positive potential (LPP), based on various cognitive tasks 14,15,17–19,67 . Our research represents an initial exploration into this area of research. Our results indicate a continuous decrease in high alpha band intensity over two months following the initiation of a romantic relationship. Since we only monitored the neural activity in the prefrontal lobe, and previous research indicates that the neural mechanisms of romantic relationships are relatively complex, involving cooperation of multiple brain regions 13,63,68–72 . According to the spatial characterization of different alpha sub-oscillations by predecessors, high alpha is more considered to be stronger in the parietal lobe 39,40 , and may be related to changes in spatial attention 41 . At present, we are unable to pinpoint the neural origin mechanism of the significant changes we discovered, which requires further research and exploration through the design of additional experiments. Another previous work 73 demonstrated that couples exhibit more efficient bi-brain and bi-behavioral synchronization compared to friends or strangers, with this balance enhancing their task performance, thus highlighting the impact of attachment on oscillatory synchronization. Our findings also provide a similar complementary perspective to this research. Regrettably, we did not conduct simultaneous data collection for the two individuals; in fact, we collected data sequentially with around 10-minute interval between the two. The consistent changes observed in our results between the two individuals could still be related to synchronous changes. This aspect can be further explored in future research. Limitations Emotional expression inherently exhibits individual variability, making the study of individual emotions an important topic. Although our sample size is not large, our research demonstrates a novel data collection method and experimental design. The use of portable EEG for multiple data collections from the same subject, along with follow-ups and tracking, will become mainstream in future EEG research. Declarations Conflicts of interest statement: The co-authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Contributors: CH and ZZ conceived and designed the study, literature search and the interpretation of results, and wrote the paper. Acknowledgement: We thank the EEG equipment provided by Shenzhen Shuimu AI Technology Co., Ltd. References Jankowiak, W. R. & Fischer, E. F. A Cross-Cultural Perspective on Romantic Love. Ethnology 31 , 149 (1992). 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Hum Brain Mapp 32 , 249–257 (2011). Djalovski, A., Dumas, G., Kinreich, S. & Feldman, R. Human attachments shape interbrain synchrony toward efficient performance of social goals. Neuroimage 226 , (2021). Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5835787","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":402583595,"identity":"978b1476-c758-4134-bed6-90cabcacfd99","order_by":0,"name":"Zhizhen Zhang","email":"","orcid":"","institution":"University of Massachusetts at Amherst","correspondingAuthor":false,"prefix":"","firstName":"Zhizhen","middleName":"","lastName":"Zhang","suffix":""},{"id":402583596,"identity":"0c2e16f7-424b-4b03-a0b6-74051018b8e6","order_by":1,"name":"Chuanliang Han","email":"data:image/png;base64,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","orcid":"","institution":"The Chinese University of Hong Kong","correspondingAuthor":true,"prefix":"","firstName":"Chuanliang","middleName":"","lastName":"Han","suffix":""}],"badges":[],"createdAt":"2025-01-15 15:38:54","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5835787/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5835787/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74036655,"identity":"a49f7e15-8c8b-4155-83aa-34f33afe436f","added_by":"auto","created_at":"2025-01-17 07:50:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":106709,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePortable EEG devices and data recording\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. thirteen recording EEG trials from the couple using the portable EEG device, where the recording site locates in prefrontal lobe.\u003c/p\u003e\n\u003cp\u003eB. Demo of the portable EEG device with reference in earlobe.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5835787/v1/29ee6410c6562360048996e3.png"},{"id":74036656,"identity":"f0a698f7-788d-4329-9043-0be58a474abc","added_by":"auto","created_at":"2025-01-17 07:50:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":424232,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDemonstration of 13 EEG recordings in prefrontal cortex and their power spectrums\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. All 13 demo traces of EEG signals (shown in 1 second) recorded from prefrontal cortex for subject ZZZ and HCL, both in open-eye and closed -eye states.\u003c/p\u003e\n\u003cp\u003eB and C. All 13 power spectrums in prefrontal cortex for subject ZZZ and HCL, both in open-eye and closed -eye states.\u003c/p\u003e\n\u003cp\u003eD. Averaged power spectrum prefrontal cortex for subject ZZZ and HCL, both in open-eye and closed -eye states.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5835787/v1/fd39066a52641d84d4db4acc.png"},{"id":74038126,"identity":"e613a9d8-0b6f-4429-a10b-98f85de1f6d5","added_by":"auto","created_at":"2025-01-17 07:58:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":254761,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConsistent alteration of alpha band activities in first two months\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Correlation between latency days and relative power in difference frequencies in open-eye and closed-eye states (first row) and its significance (second row) in ZZZ.\u003c/p\u003e\n\u003cp\u003eB. Correlation between latency days and relative power in difference frequencies in open-eye and closed-eye states (first row) and its significance (second row) in HCL.\u003c/p\u003e\n\u003cp\u003eC. Averaged correlation between latency days and relative power in difference frequencies in open-eye (first row) and closed-eye states (second row).\u003c/p\u003e\n\u003cp\u003eD. Scatter plot between low, medium and high alpha power in closed-eye state and latency days of romantic relationship (ZZZ for first row and HCL for second row).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5835787/v1/abf75a9d15e28479934a92dd.png"},{"id":74038131,"identity":"51ba8463-b707-4889-9f9a-08c6417cc73a","added_by":"auto","created_at":"2025-01-17 07:58:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":461007,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConsistent alteration of aperiodic and periodic activity in alpha band in first two months\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Raw power spectrum (first row), aperiodic (second row) and periodic (third row) activities in 13 EEG recordings of open-eye and closed-eye states in HCL and ZZZ.\u003c/p\u003e\n\u003cp\u003eB. Averaged raw power spectrum, aperiodic and periodic activities in closed-eye state of HCL and ZZZ.\u003c/p\u003e\n\u003cp\u003eC. Scatter plot between aperiodic and periodic activity in high alpha band in closed-eye state and latency days of start of romantic relationship (blue for HCL and red for ZZZ).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5835787/v1/c4a85994db27e24be69c76bb.png"},{"id":74039723,"identity":"a587e366-d226-4337-badb-009ae08266f3","added_by":"auto","created_at":"2025-01-17 08:15:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2005626,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5835787/v1/6d84c46a-64ca-41f8-abae-e5eca61e1f6c.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eHigh alpha-band activity of prefrontal cortex contributes to the significant neural alterations in the initial two-month phase of a romantic relationship\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRomantic love is a universal experience that most people will encounter at some point in their lives\u003csup\u003e1,2\u003c/sup\u003e. Falling in love is an intimate relationship that individuals independently, voluntarily, and freely establish in their life journey\u003csup\u003e3\u0026ndash;5\u003c/sup\u003e. The brain undergoes significant changes when in a state of love\u003csup\u003e6\u0026ndash;10\u003c/sup\u003e, including various physiological and psychological aspects. When a couple officially confirms their romantic relationship, the specific neural, particularly during the initial honeymoon period, remain poorly understood. To explore the neural activity associated with romantic relationships\u003csup\u003e11,12\u003c/sup\u003e, previous studies have used methods such as functional magnetic resonance imaging (fMRI)\u003csup\u003e13,14\u003c/sup\u003e and electroencephalography (EEG)\u003csup\u003e15,16\u003c/sup\u003e. However, these studies are mainly cross-sectional, based on the differences between different groups and the neural responses to different love-related visual stimuli\u003csup\u003e14,17\u0026ndash;19\u003c/sup\u003e. To date, no longitudinal study has explored how the neural activity of a couple evolves after they formally enter a romantic relationship. The scarcity of such research is primarily due to the inherent difficulty in obtaining this kind of data, which involves recruiting participants, initiating data collection immediately after the confirmation of their romantic relationship, and consistently tracking and collecting multiple EEG data over time from the same individuals.\u003c/p\u003e \u003cp\u003eNeural oscillations are a key neurobiological feature in EEG signals, particularly the alpha oscillations (8-13Hz), which are significantly stronger in a closed-eye state than in an open-eye state\u003csup\u003e20\u0026ndash;25\u003c/sup\u003e. They are also associated with various cognitive functions\u003csup\u003e26\u0026ndash;30\u003c/sup\u003e, and abnormal alpha oscillations are linked to mental disorders\u003csup\u003e31\u0026ndash;37\u003c/sup\u003e. In recent years, increasing research has discovered that the alpha band does not consist of a single type of oscillation; multiple sub-oscillations may exist within this narrow band\u003csup\u003e38\u0026ndash;40\u003c/sup\u003e, each with different neural origins and potentially linked to different cognitive functions\u003csup\u003e41\u003c/sup\u003e. However, it is not entirely clear whether these different sub-oscillations are related to emotional states. Additionally, more recent studies have made more detailed distinctions in the spectral components: periodic and aperiodic components\u003csup\u003e42\u003c/sup\u003e, each representing different neural mechanisms. Analyzing these components separately can further our understanding of the mechanisms behind the spectrum. Yet, the association between romantic love and different spectral components remains unclear.\u003c/p\u003e \u003cp\u003eGiven our extensive experience in neuroscience and applied mathematics, we, the authors of this study, have chosen to serve as our own research subjects to investigate this phenomenon. After confirming our romantic relationship, we collected prefrontal EEG data 13 times over a span of two months (67 days) using portable EEG devices. During these periods, our relationship deepened and strengthened than the beginning stage. If romantic love can affect neural responses, we assume that a couple would exhibit consistent changes in certain neurobiological characteristics. To test this hypothesis, we performed spectral analysis on each EEG data collection, aiming to identify specific frequencies in the prefrontal lobe where neural responses of both individuals exhibited significant changes with the duration of their acquaintance.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eTwo right-handed healthy individuals, which is a couple (one male, HCL, aged 31 and one female, ZZZ, aged 24), participated in this study. Both subjects are Han Chinese, from northern part of China, and do not have any religious belief. Both participants provided informed consent, and the EEG data recording procedures adhered to the National Institutes of Health Guidelines and received ethical approve from the Shenzhen Institute of Advanced Science and Technology, Chinese Academy of Sciences (SIAT-IRB-231113-H0677).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eNeurophysiological recording\u003c/h3\u003e\n\u003cp\u003eEach participant contributed 13 sets of resting-state EEG data over approximately two-month period (67 days, from the first day they met in face in 2024), resulting in a total of 26 resting-state EEG datasets. Resting-state EEG recordings were obtained under both open-eye and closed-eye conditions using a single-electrode setup (Fpz) with the Brain Pro system (China) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Each recording session involved both subjects being present simultaneously. One subject first had their EEG recorded for 3 minutes with their eyes open and then for another 3 minutes with their eyes closed. Subsequently, the other subject also underwent EEG recording first for 3 minutes with their eyes open followed by 3 minutes with their eyes closed. The reference electrode was positioned at the earlobe, and online data were filtered using a bandpass filter with cutoff frequencies of 0.5 and 30 Hz. The sampling rate was 512 Hz and the scalp impedance was maintained below 10 kΩ for the electrode. Eye-blink artifacts were removed with unsupervised machine learning algorithms\u003csup\u003e43\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003ePower Spectrum Analysis\u003c/h3\u003e\n\u003cp\u003eThe power spectrum of the EEG response was estimated using the multitaper method\u003csup\u003e44,45\u003c/sup\u003e (time-bandwidth product, 3; tapers, 5; Chronux toolbox (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://chronux.org/\u003c/span\u003e\u003cspan address=\"http://chronux.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), implemented through custom software written in MATLAB. Spectrum analysis is a technique used to decompose complex signals into simpler ones based on the Fourier transform. Essentially, the multi-taper method aims to reduce the variance of spectral estimates by premultiplying the data with several orthogonal tapers known as Slepian functions. This method is widely applied in various biomedical studies (e.g., biological science\u003csup\u003e46\u0026ndash;53\u003c/sup\u003e, and public health\u003csup\u003e54\u0026ndash;58\u003c/sup\u003e. The relative power can be defined as Eq.\u0026nbsp;1(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Rel\\:Power\\left(f\\right)=\\frac{Power\\left(f\\right)}{\\sum\\:_{3Hz}^{20Hz}Power\\left(f\\right)}\\:\\:\\:\\:\\:（1）$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:Power\\left(f\\right)\\)\u003c/span\u003e\u003c/span\u003e denotes the absolute power calculated using multi-taper method.\u003c/p\u003e\n\u003ch3\u003eDescriptive Model for Dissecting Aperiodic and Periodic Activity\u003c/h3\u003e\n\u003cp\u003eThe power spectrum was considered as the summation of two component: aperiodic and periodic components. The aperiodic component of the power spectrum was extracted using a 1/f like function (Eq.\u0026nbsp;2), where a, b, c and d represent the model parameters to be estimated. The periodic component was defined as the residual obtained by subtracting the aperiodic component from the raw power spectrum. This method has been used in the characterization of gamma-band and alpha-band activities\u003csup\u003e42,59,60\u003c/sup\u003e.\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:Aperiodic\\:Activity\\left(f\\right)=\\frac{a}{{f}^{b}+c}+d\\:\\:\\:\\:\\:\\:\\:\\:\\left(2\\right)\\:$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003ePearson correlation analysis was conducted to measure the relationship between relative power in the alpha band (low, medium and high alpha bands), as well as the aperiodic and periodic activity in the high alpha band, and the number of days elapsed since the start of romantic relationship. Analyses were performed separately for the open-eye and closed-eye states respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eIn this study, we collected and analyzed a precious dataset tracking the first two-month of prefrontal cortex EEG recordings (13 recording trials) from a typical couple (i.e. the two authors of this paper) who had just formally entered their romantic relationship (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). During each trial, three-min of EEG data was recorded in both open-eye (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, white curve) and closed-eye states (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, black curve).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eStable two months recordings of portable EEG devices\u003c/h3\u003e\n\u003cp\u003eThirteen demo trace of EEG signal in the couple in both open and closed-eye state was shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA. Alpha oscillation was clearly induced by closing eyes of each subject compared with that in open-eye state in both time domain or frequency domain, which is consistent with previous studies\u003csup\u003e38,61\u003c/sup\u003e. Despite some minor variability of power spectrum in these 13 recordings, the current results still revealed that the frequency and bandwidth of the alpha oscillations remained stable across 13 recordings (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-D), which suggests a stable EEG data quality throughout the 2-month recording using this portable one-channel EEG system. The two subjects have distinct alpha patterns, the alpha peak of HCL locates smaller than 10Hz, while that of ZZZ is larger than 10Hz, they still fall in the range of alpha band and become weaker during eye-open state. Based on these stable recording and high-quality neural signals, we would do further analysis in the following sections.\u003c/p\u003e\n\u003ch3\u003eStrength of high alpha band activity decreases in the first two months of romantic relationship\u003c/h3\u003e\n\u003cp\u003eWe then conducted correlation analysis between the relative power in each frequency and the number of days elapsed since the start of the romantic relationship (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Pearson correlations were calculated individually (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA for ZZZ, and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB for HCL), revealing significant correlations at specific frequencies (second rows in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). To identify consistent change between the two subjects, we averaged the correlations of ZZZ and HCL in open and closed-eye states (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Notably, a consistent and pronounced decrease in high alpha band was observed in the closed eye state (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, black curves). Subsequently, we performed separate correlation analysis for low (8-9.5 Hz), medium (9.5-11Hz) and high (11.5-13Hz) alpha band with latency days, and verified a significant negative correlation in high alpha band in ZZZ (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, first row, r=-0.76, p\u0026thinsp;=\u0026thinsp;0.0026) and HCL (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, second row, r=-0.73, p\u0026thinsp;=\u0026thinsp;0.0045), but not in low or medium alpha band (ps\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePeriodic activity in high alpha band contributes to the significant change in first two-month romantic relationship\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFurthermore, we dissected the power spectrums into aperiodic and periodic components for each trial in open-eye and closed-eye states individually (Fig.\u0026nbsp;4AB). Then we got 13 aperiodic and periodic activities in each subject. Given the significant findings in high alpha band in closed-eye state, we focused further analysis on this specific frequency band and state. Our results indicated that the significant correlation in high alpha band observed was primarily driven by periodic activity (ZZZ, r=-0.73, p\u0026thinsp;=\u0026thinsp;0.0043; HCL, r=-0.75, p\u0026thinsp;=\u0026thinsp;0.0029) rather than aperiodic activity (ZZZ, r=-0.22, p\u0026thinsp;=\u0026thinsp;0.48; HCL, r=-0.39, p\u0026thinsp;=\u0026thinsp;0.19) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we present an interesting analysis of EEG data, which, to the best of our knowledge, is the first in the world to track and follow up on neural responses in a couple immediately after the establishment of a romantic relationship. Over a two-month period, we conducted 13 EEG recordings, directly capturing the changes in prefrontal lobe neural activity as the couple transitioned from confirming their relationship to the honeymoon phase. Our findings reveal that these changes are primarily reflected in the power spectrum concentrated in the high alpha frequency band. Furthermore, through mathematical modeling, we observed alterations in neural responses is mainly contributed by the periodic activity in the high alpha frequency band rather than by the aperiodic activity. Through longitudinal tracking, this study fills a gap in the field of romantic emotions and, as an exploratory investigation, holds significant value.\u003c/p\u003e \u003cp\u003eThe primary distinction between our work and previous research lies in our use of longitudinal follow-up collections to monitor neural responses from two individuals over time, in order to describe how neural activities in different frequencies change. Previous studies typically involved comparisons between two distinct groups\u0026mdash;those in romantic relationships and those not\u003csup\u003e62\u003c/sup\u003e \u0026mdash;in conjunction with visual\u003csup\u003e62\u0026ndash;65\u003c/sup\u003e, auditory\u003csup\u003e62\u003c/sup\u003e, or sensory\u003csup\u003e66\u003c/sup\u003e perception tasks. These studies have highlighted significant associations between alpha band activity and romantic relationships, as well as differences in event-related potentials, such as the late positive potential (LPP), based on various cognitive tasks\u003csup\u003e14,15,17\u0026ndash;19,67\u003c/sup\u003e. Our research represents an initial exploration into this area of research.\u003c/p\u003e \u003cp\u003eOur results indicate a continuous decrease in high alpha band intensity over two months following the initiation of a romantic relationship. Since we only monitored the neural activity in the prefrontal lobe, and previous research indicates that the neural mechanisms of romantic relationships are relatively complex, involving cooperation of multiple brain regions\u003csup\u003e13,63,68\u0026ndash;72\u003c/sup\u003e. According to the spatial characterization of different alpha sub-oscillations by predecessors, high alpha is more considered to be stronger in the parietal lobe \u003csup\u003e39,40\u003c/sup\u003e, and may be related to changes in spatial attention \u003csup\u003e41\u003c/sup\u003e. At present, we are unable to pinpoint the neural origin mechanism of the significant changes we discovered, which requires further research and exploration through the design of additional experiments.\u003c/p\u003e \u003cp\u003eAnother previous work\u003csup\u003e73\u003c/sup\u003e demonstrated that couples exhibit more efficient bi-brain and bi-behavioral synchronization compared to friends or strangers, with this balance enhancing their task performance, thus highlighting the impact of attachment on oscillatory synchronization. Our findings also provide a similar complementary perspective to this research. Regrettably, we did not conduct simultaneous data collection for the two individuals; in fact, we collected data sequentially with around 10-minute interval between the two. The consistent changes observed in our results between the two individuals could still be related to synchronous changes. This aspect can be further explored in future research.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eEmotional expression inherently exhibits individual variability, making the study of individual emotions an important topic. Although our sample size is not large, our research demonstrates a novel data collection method and experimental design. The use of portable EEG for multiple data collections from the same subject, along with follow-ups and tracking, will become mainstream in future EEG research.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of interest statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe co-authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributors:\u0026nbsp;\u003c/strong\u003eCH and ZZ conceived and designed the study, literature search and the interpretation of results, and wrote the paper.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u0026nbsp;\u003c/strong\u003eWe thank the EEG equipment provided by Shenzhen Shuimu AI Technology Co., Ltd.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eJankowiak, W. 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Human attachments shape interbrain synchrony toward efficient performance of social goals. \u003cem\u003eNeuroimage\u003c/em\u003e \u003cstrong\u003e226\u003c/strong\u003e, (2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"The Chinese University of Hong Kong","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Alpha Oscillation, EEG, Periodical activity, Love, Relationship","lastPublishedDoi":"10.21203/rs.3.rs-5835787/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5835787/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRomantic relationships are integral to human experience, with most individuals encountering them at some point in their lives. The neural mechanisms of romantic relationships have gradually gained attention. However, existing studies have mainly focused on the cross-sectional level, and longitudinal research is not sufficient, especially regarding the early stages when couples first enter a romantic relationship. The brain's neural transition from a normal state to the honeymoon phase of love remains poorly understood. To answer this question, we, the authors, used ourselves as subjects; after confirming our romantic relationship, we employed portable electroencephalography (EEG) to record neural activity in the prefrontal cortex during resting states (both with eyes open and closed). Data collection occurred irregularly over a period of around two months, resulting in 13 EEG data trials per individual. We found that there was a consistent decrease in the high alpha band neural activity under the closed-eye state for both of us over the two-month period, suggesting a potential correlation with the neural activity changes in the early stage of the romantic relationship. Further analysis revealed that this decrease was driven by changes in periodic components rather than non-periodic components. This study is the first to reveal a significant change in the alpha oscillatory activity of the prefrontal cortex in a couple during the initial two months after confirming their romantic relationship, which will further impact the understanding of the mechanism of alpha sub-oscillations and their application in the study of emotions process.\u003c/p\u003e","manuscriptTitle":"High alpha-band activity of prefrontal cortex contributes to the significant neural alterations in the initial two-month phase of a romantic relationship","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-17 07:50:52","doi":"10.21203/rs.3.rs-5835787/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2574a22c-9d57-498b-a978-6df3eea5bc26","owner":[],"postedDate":"January 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":42934641,"name":"Cognitive Neuroscience"}],"tags":[],"updatedAt":"2025-01-17T07:50:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-17 07:50:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5835787","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5835787","identity":"rs-5835787","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}