Stratified analyses reveal temporal instability and seasonal modulation of lateralized lying in domestic cats

Stratified analyses reveal temporal instability and seasonal modulation of lateralized lying in domestic cats | 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 Article Stratified analyses reveal temporal instability and seasonal modulation of lateralized lying in domestic cats Lu-Shu Yeh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8540763/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 Behavioral lateralization is often described as a stable trait expressed at either the population or individual level. However, such conclusions are frequently drawn from limited or uneven observations, raising questions about how lateralization should be interpreted under naturalistic conditions. Here, I investigated lateralized lying behavior in domestic cats using a large, citizen-science dataset characterized by highly variable observation frequencies. To address this heterogeneity, I applied a stratified analytical framework separating population-level, individual-level, and time-resolved analyses. Across low-frequency observations involving many individuals with sparse sampling, I found no evidence for a strong population-level lateral bias in lying posture. In contrast, cats with moderate observation frequencies exhibited pronounced inter-individual variability, with clear lateral preferences expressed in both directions but no uniform group-level orientation. Even among high-frequency individuals with extensive longitudinal records, overall lateralization indices remained modest when aggregated across time. However, fine-grained analyses across solar terms revealed substantial within-individual fluctuations, including directional reversals, indicating that lateralized lying behavior is dynamic rather than fixed. These temporal trajectories differed across individuals and were attenuated in an air-conditioned environment, consistent with context-dependent modulation. Together, my results suggest that lateralized lying in domestic cats is best understood as an individual-specific and environmentally modulated behavior, rather than a stable population-wide trait. By explicitly aligning analytical scale with data resolution, this study highlights the importance of longitudinal and context-aware approaches for interpreting behavioral lateralization under naturalistic conditions. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Neuroscience Biological sciences/Psychology Social science/Psychology Biological sciences/Zoology Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Behavioral lateralization, defined as the consistent preferential use of one side of the body over the other, has been documented across a wide range of animal taxa[ 1 , 2 ]. Such asymmetries are often interpreted as manifestations of hemispheric specialization and are frequently discussed at either the population level, where most individuals show the same directional bias, or the individual level, where stable preferences vary among individuals. This framework has yielded important insights into the evolution and function of lateralized behaviors, particularly in goal-directed tasks such as foraging, manipulation, or predator avoidance. However, many studies of behavioral lateralization rely on relatively short observation windows or uneven sampling across individuals[ 2 ], raising questions about the stability and interpretability of reported lateralization indices. In naturalistic settings, behaviors may be expressed flexibly in response to environmental and internal states, and aggregating observations across time may obscure dynamic patterns occurring within individuals. This concern is especially relevant for resting or postural behaviors, which are not explicitly goal-directed and may be influenced by multiple competing factors, including thermoregulation, vigilance, comfort, and environmental context. Domestic cats (Felis catus) provide a valuable model for examining lateralization under naturalistic conditions. As a familiar species living in close association with humans, cats exhibit a wide range of spontaneous behaviors that can be observed longitudinally in everyday environments. Previous studies have reported lateral biases in various feline behaviors, including paw use and turning direction, but findings have been mixed, and the extent to which such biases represent stable traits versus context-dependent expressions remains unresolved. Lateralized lying behavior, a common resting posture, has received comparatively little attention, despite its suitability for long-term observation and its potential sensitivity to environmental conditions. Recent work has reported a population-level bias in lateralized sleeping positions in domestic cats based on pooled observations across individuals [ 3 ]. However, the extent to which such inferences depend on observation density and temporal aggregation remains unclear. Here, I investigate lateralized lying behavior in domestic cats using a large citizen-science dataset characterized by highly heterogeneous observation frequencies[ 4 ]. Rather than treating uneven sampling as a limitation to be minimized, I explicitly leverage this structure by adopting a stratified analytical framework. Low-frequency observations are used to assess whether strong population-level biases are detectable, mid-frequency data to characterize inter-individual variability, and high-frequency longitudinal records to examine within-individual dynamics across solar terms. By aligning analytical scale with data resolution, this study aims to clarify how lateralization in a common resting behavior should be interpreted under naturalistic conditions, and to what extent it reflects stable traits versus dynamic, context-dependent modulation. Methods Study design and data collection This study combined systematic longitudinal observation with a citizen-science approach to capture lateralized lying behavior in domestic cats under naturalistic conditions. Data were collected from multiple households and varied substantially in observation frequency, reflecting differences in participant engagement and study duration. Longitudinal high-frequency observations Three cats residing in Hualien were monitored continuously as part of a high-frequency longitudinal protocol. Observations were conducted daily during two fixed time windows: 06:00–08:00 and 21:00–23:30. During each observation window, the lying posture of each cat was recorded whenever the cat was observed resting. These repeated observations allowed estimation of individual lateralization indices across time and facilitated time-resolved analyses across solar terms. Citizen-science data collection Data from additional cats were collected through a citizen-science framework. Cat owners voluntarily participated by submitting observations via a standardized Google Form designed by the authors. For each observation, participants recorded the date, time, cat identity, lying posture (left, right, or neutral), presence of other individuals, and the cat’s activity state (e.g., sleeping, resting, inactive). Participants were instructed to record observations opportunistically during everyday interactions with their cats, without imposing experimental manipulation. To encourage regular participation and sustained engagement, cumulative observation counts were publicly updated on a daily basis, and participants were awarded virtual badges recognizing consistent observation over time. These engagement mechanisms were implemented to increase longitudinal coverage while maintaining the naturalistic context of observations. Ethical considerations All observations were non-invasive and conducted in the cats’ usual living environments without physical interaction or behavioral manipulation. Participation by cat owners was voluntary, and no personal identifying information beyond cat names was collected. The study involved observational recording of companion animals in their home environments. Under local regulations, such observational studies do not require formal ethical approval. Informed consent was obtained from all participating pet owners prior to data collection. The study involved non-invasive, observational recording of naturally occurring behaviors in domestic cats, as reported by their owners. No experimental manipulation was performed on the animals. Definition of lateralization index and analytical stratification Lateralized lying behavior was quantified using a lateralization index (LI), defined as LI=(R − L)/(R + L), where R and L represent the number of right- and left-side lying observations, respectively. Neutral postures for which left–right orientation could not be determined were excluded from LI calculation. LI values range from − 1 (exclusive left-side lying) to + 1 (exclusive right-side lying), with values near zero indicating little or no directional bias. Given the highly uneven distribution of observations across individuals, analyses were stratified according to observation frequency to ensure that analytical scale was aligned with data resolution. Cats were classified into three groups: a low-frequency group, consisting of individuals with less than 10 observations; a mid-frequency group (more than 10 but less than 60 approximately), for which individual-level LI could be estimated with moderate confidence; and a high-frequency group, comprising individuals with extensive longitudinal records. Low-frequency data were analyzed only at the pooled population level to assess the presence of large population-wide biases, whereas mid-frequency data were used to examine inter-individual variability. High-frequency data enabled both overall individual LI estimation and time-resolved analyses across solar terms to capture within-individual dynamics. This stratified approach was adopted a priori to avoid conflating population-level, individual-level, and temporal sources of variation[ 1 , 2 ], and to prevent overinterpretation of sparse individual records. Statistical analysis Analyses were primarily descriptive and exploratory, reflecting the observational and naturalistic nature of the dataset. For the low-frequency group, left–right counts were pooled across individuals to estimate a group-level LI and corresponding proportions. For the mid-frequency group, individual LI values were calculated and visualized to characterize the distribution and range of inter-individual variation, without assuming a common underlying direction. For high-frequency individuals, overall LI values were calculated across the entire observation period, and time-resolved LI trajectories were examined by aggregating observations within successive solar terms. These trajectories were visualized to assess within-individual changes in magnitude and direction over time. Comparisons focused on qualitative patterns of variability, synchrony, and directional shifts rather than on formal hypothesis testing. No inferential statistical tests were used to compare LI values across groups, as the primary objective was to evaluate how lateralization patterns depend on sampling resolution and analytical scale, rather than to test a specific parametric model. All analyses were conducted using standard spreadsheet and statistical software, and figures were generated to emphasize transparency and interpretability of observed patterns. Results Results 1 Low-frequency observations show no evidence for a strong population-level lateral bias In the low-frequency group, most individuals contributed only one or a few observations, precluding reliable estimation of individual-level lateralization. Therefore, lateralized lying behavior was assessed exclusively at the group level by pooling all left–right observations. After excluding neutral postures with indeterminate orientation, a total of 176 observations were retained for analysis. The resulting lateralization index (LI) was 0.0552, corresponding to a right-lying proportion of approximately 52.8%, indicating only a very slight rightward bias. The observed effect size was small and did not support the presence of a strong or consistent population-level lateral preference. Given the sparse and uneven sampling at the individual level, this analysis was not intended to infer individual lateralization, but rather to evaluate whether a large population-level bias could be detected. The results indicate that, if population-level lateralization in lying posture exists, its magnitude is limited to a small effect size. Sex-stratified analyses of the low-frequency group showed a similar overall pattern and did not reveal pronounced directional differences (Supplementary Table S1 ). Taken together, the low-frequency observations provide no evidence for a strong or stable population-wide lateral bias in domestic cats’ lying behavior. Results 2 Mid-frequency observations reveal pronounced inter-individual variability in lateralized lying behavior In contrast to the low-frequency group, cats in the mid-frequency group contributed sufficient repeated observations to allow estimation of individual-level lateralization indices (LI). Examination of individual LI values revealed substantial variability across cats, spanning both positive and negative ranges (Fig. 2 ). LI values in this group ranged from strongly left-biased to strongly right-biased individuals, with several cats exhibiting pronounced lateralization in either direction, while others remained close to zero. Importantly, the distribution of LI values was not centered on a single dominant direction; instead, lateralized lying behavior manifested idiosyncratically at the individual level, with no uniform population-wide orientation. Although a slight predominance of positive LI values was observed, the presence of multiple strongly left-biased individuals resulted in a broad and overlapping distribution around zero. This pattern indicates that lateralization in lying posture, when present, does not converge on a consistent group-level direction but rather reflects marked inter-individual differences. Taken together, the mid-frequency data demonstrate that lateralized lying behavior in domestic cats is best characterized as an individual-specific phenomenon, rather than as a uniform population-level preference. These findings motivate further examination of within-individual dynamics under conditions of high-resolution longitudinal sampling. Results 3 Overall lateralization remains modest even in high-frequency individuals To determine whether extensive longitudinal sampling would reveal strong and stable lateralization, I examined overall LI values for cats in the high-frequency group. Despite substantially higher numbers of observations per individual, overall LI values remained modest and varied in direction across cats (Fig. 3 ). Among the eight high-frequency individuals, LI values ranged from weakly left-biased to moderately right-biased, with no cat exhibiting a consistently strong directional preference across the entire observation period. Several individuals showed LI values close to zero, indicating little net lateralization when observations were aggregated over time. These results indicate that increased sampling intensity alone does not yield pronounced or uniform lateralized lying behavior. Instead, even under dense longitudinal observation, overall lateralization appears limited in magnitude and heterogeneous in direction, suggesting that lateralized lying is not a fixed trait expressed consistently across time. This absence of strong overall lateralization in high-frequency individuals motivates a finer-grained, time-resolved analysis to examine whether lateralized lying behavior varies dynamically within individuals in response to environmental context. Results 4 Seasonal trajectories reveal context-dependent and individual-specific modulation of lateralized lying behavior To examine whether lateralized lying behavior varies dynamically within individuals, I analyzed longitudinal LI trajectories across solar terms in cats with continuous high-frequency observations. This analysis revealed pronounced within-individual fluctuations in LI values over time, often exceeding the magnitude of overall LI estimated across the entire observation period. In three cats continuously monitored across multiple solar terms in Hualien, LI values showed substantial seasonal variation, including marked shifts in both magnitude and direction (Fig. 4 A–C). In some individuals, LI values transitioned from strongly left-biased during summer solar terms to right-biased values in later seasons(Fig. 4 A), whereas others exhibited distinct but non-parallel trajectories. Notably, these seasonal changes were not synchronized across individuals, indicating that lateralized lying behavior does not follow a uniform seasonal pattern at the population level. Despite being exposed to the same regional climate and temporal progression of solar terms, each cat exhibited a unique LI trajectory, with changes occurring at different times and in different directions. This heterogeneity suggests that the expression of lateralized lying behavior is modulated in an individual-specific manner, rather than being driven by a shared external seasonal signal. In contrast, a cat housed in an air-conditioned environment showed attenuated seasonal variation in LI values (Fig. 4 D). Although short-term fluctuations were still observed, the magnitude of change across solar terms was reduced relative to cats exposed to ambient environmental conditions. This pattern is consistent with reduced sensitivity to external environmental variation under thermally regulated indoor conditions. Additional high-frequency individuals monitored across multiple solar terms exhibited intermediate patterns, with observable but less pronounced within-individual variability (Supplementary Fig. S1 ). Together, these results demonstrate that lateralized lying behavior in domestic cats is dynamic over time, shaped by environmental context and expressed idiosyncratically at the level of individual animals, rather than as a stable or synchronized seasonal trait. Discussion In this study, I examined lateralized lying behavior in domestic cats using a stratified analytical framework designed to accommodate highly uneven observational regimes typical of citizen-science data. Across low-frequency observations involving many individuals with sparse sampling, I found no evidence for a strong population-level lateral bias. In contrast, mid-frequency data revealed pronounced inter-individual variability, with some cats exhibiting clear lateral preferences in opposite directions. Even among high-frequency individuals with extensive longitudinal records, overall lateralization remained modest when aggregated across time. However, time-resolved analyses uncovered substantial within-individual fluctuations across solar terms, demonstrating that lateralized lying behavior is dynamic, context-dependent, and expressed idiosyncratically rather than as a stable trait. Our findings help reconcile apparent discrepancies with previous reports of population-level laterality in domestic cats [ 3 ], by showing that such patterns can emerge under low observation density but become unstable when individual-level and temporal dynamics are explicitly considered. Previous studies of behavioral lateralization in animals have often emphasized population-level asymmetries or interpreted individual biases as fixed traits reflecting hemispheric specialization[ 1 , 2 ]. My findings extend this literature by showing that, for a common resting posture in a familiar species, lateralization cannot be adequately characterized by a single static index. Instead, lateralized lying in domestic cats appears to emerge from the interaction between individual-specific tendencies and environmental context, becoming most evident under high-resolution longitudinal observation. By explicitly separating population-level, individual-level, and time-resolved analyses, this study highlights how conclusions about lateralization critically depend on data structure and analytical scale. A key methodological implication of this study concerns the widespread practice of summarizing behavioral lateralization using a single static index, often derived from limited or uneven observations[ 2 ]. My results demonstrate that such an approach can obscure both the absence of strong population-level biases and the presence of meaningful individual- and context-dependent variation. In particular, when observations are sparse or unevenly distributed across individuals, aggregating data without regard to sampling structure may either exaggerate apparent group-level asymmetries or mask dynamic patterns expressed within individuals. By explicitly stratifying analyses according to observational frequency and separating population-level, individual-level, and time-resolved perspectives, I show that lateralization cannot be treated as a unitary property invariant across analytical scales. Low-frequency data are informative for constraining the upper bound of population-level effects, but are ill-suited for inferring individual traits. Conversely, mid- and high-frequency data reveal that individual lateralization is heterogeneous and temporally labile, such that averaging across time can substantially underestimate within-individual variability. These findings underscore the importance of aligning analytical strategy with data resolution and caution against interpreting lateralization indices as fixed traits in the absence of sufficient longitudinal evidence. Beyond methodological considerations, the dynamic and individual-specific patterns observed here suggest that lateralized lying may be better understood as a situational behavioral expression rather than a fixed manifestation of hemispheric dominance. Resting postures in animals are known to balance multiple competing demands, including thermoregulation, vigilance, comfort, and rapid responsiveness to environmental cues. Variation in lying orientation across time and context may therefore reflect flexible adjustments to these demands, rather than stable lateral preferences per se. The absence of synchronized seasonal trajectories across individuals, even among cats exposed to similar external conditions, further supports this interpretation. If lateralized lying primarily reflected an intrinsic or population-wide asymmetry, more parallel shifts would be expected across individuals. Instead, the observed heterogeneity suggests that individual history, local microenvironment, and internal state may interact to shape posture selection at any given time. In this sense, lateralized lying may function less as a marker of neural specialization and more as a context-sensitive posture, whose expression emerges from the interplay between individual tendencies and moment-to-moment environmental constraints. Importantly, this perspective aligns with growing evidence across taxa that lateralized behaviors can be plastic, task-dependent, and modulated by external conditions, particularly in non-goal-directed contexts such as rest [ 2 ]. Interpreting lateralization in such behaviors therefore requires caution against overgeneralizing from static indices or short observation windows, and instead calls for longitudinal approaches capable of capturing temporal variability and individual-specific trajectories. Several limitations of this study should be acknowledged. First, the data were derived from a citizen-science framework, resulting in highly uneven sampling across individuals and households[ 4 ]. Although this heterogeneity motivated my stratified analytical approach, it also constrained the types of inferences that could be drawn, particularly at the individual level for low-frequency observations. In addition, lying orientation was assessed from owner-reported observations rather than standardized experimental recordings, raising the possibility of observer-related variability. However, such variability is unlikely to systematically bias directionality across individuals and instead would tend to reduce detectable effect sizes, rendering my conclusions conservative. Second, although seasonal patterns were examined using solar terms as a temporally structured framework, environmental variables such as ambient temperature, light intensity, humidity, and household conditions (e.g., indoor climate control) were not independently manipulated and may be partially confounded. As illustrated by the attenuated variability observed in an air-conditioned environment, future studies incorporating direct measurements of microclimate or controlled manipulations will be essential for disentangling the relative contributions of light, temperature, and other contextual factors. Finally, the present study focused on a single, common resting posture in domestic cats. Whether similar dynamic and context-dependent lateralization patterns extend to other behaviors, postures, or species remains an open question. Future research combining long-term naturalistic observation with targeted experimental designs may help clarify when lateralization reflects stable individual tendencies and when it emerges as a flexible response to environmental conditions. Such integrative approaches will be critical for advancing a more nuanced understanding of behavioral lateralization beyond static population-level summaries. Declarations Funding This research received no external funding. Data Availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. References Vallortigara, G., & Rogers, L. J. (2005). Survival with an asymmetrical brain: Advantages and disadvantages of cerebral lateralization. Behavioral and Brain Sciences, 28(4), 575–589. https://doi.org/10.1017/S0140525X05000105 Rogers, L. J., Vallortigara, G., & Andrew, R. J. (2013). Divided brains: The biology and behaviour of brain asymmetries. Cambridge University Press. Isparta, S., Ocklenburg, S., Siniscalchi, M., Goursot, C., Ryan, C. L., Doucette, T. A., Reinhardt, P. R., Gosse, R., Çıldır, Ö. Ş., d’Ingeo, S., Freund, N., Güntürkün, O., & Demirbas, Y. S. (2025). Lateralized sleeping positions in domestic cats. Current Biology, 35(12), R587–R600. https://doi.org/10.1016/j.cub.2025.04.043 Dickinson, J. L., Zuckerberg, B., & Bonter, D. N. (2010). Citizen science as an ecological research tool: challenges and benefits. Annual Review of Ecology, Evolution, and Systematics, 41, 149–172. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigureandTablelegends.docx FigS1.jpg SupplementaryTableS1.xlsx SupplementaryTableS2.xlsx SupplementaryTableS3.xlsx 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. 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23:08:00","extension":"xml","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":43399,"visible":true,"origin":"","legend":"","description":"","filename":"eac9ba8c538141a4a1231a2af8c966921structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/013ede546e1f284a6d416361.xml"},{"id":100275709,"identity":"21edeed6-6617-4489-8857-fbf2056a342c","added_by":"auto","created_at":"2026-01-14 23:08:00","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":50608,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/4a6d8e96acea871d2e292665.html"},{"id":100275683,"identity":"8191331f-75a2-4ff0-87f8-a50ec7f5e520","added_by":"auto","created_at":"2026-01-14 23:07:59","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21085,"visible":true,"origin":"","legend":"\u003cp\u003eLow-frequency observations show minimal population-level lateral bias.\u003c/p\u003e\n\u003cp\u003eProportions of left- and right-side lying observations pooled across cats in the low-frequency group. Neutral postures were excluded from analysis. The resulting lateralization index (LI) indicates only a slight rightward deviation, reflecting the absence of a strong population-level bias in sparsely sampled individuals.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/f48ce89e86b831fce753dc8d.jpg"},{"id":100372905,"identity":"a5e8730c-dce5-4961-af4d-8d474dc372c6","added_by":"auto","created_at":"2026-01-16 08:13:23","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":33760,"visible":true,"origin":"","legend":"\u003cp\u003ePronounced inter-individual variability in lateralization among mid-frequency cats.\u003c/p\u003e\n\u003cp\u003eIndividual lateralization indices (LI) for cats in the mid-frequency group. Each point represents one cat, and the horizontal dashed line denotes LI = 0 (no directional bias). LI values span both positive and negative ranges, illustrating substantial inter-individual variation without a uniform group-level orientation.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/a71b4463911f92916d8b83fb.jpg"},{"id":100275685,"identity":"09e31763-662d-4b83-bd24-f2922afb2e22","added_by":"auto","created_at":"2026-01-14 23:07:59","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":35856,"visible":true,"origin":"","legend":"\u003cp\u003eOverall lateralization remains modest in high-frequency individuals.\u003c/p\u003e\n\u003cp\u003eOverall lateralization indices (LI) calculated across the entire observation period for each cat in the high-frequency group. Despite extensive longitudinal sampling, LI values remain small and heterogeneous in direction. The dashed line indicates LI = 0.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/6e29a3dc216e9e360e6aa15b.jpg"},{"id":100275690,"identity":"420d4b07-eb79-46a2-8aee-831bf132a6fd","added_by":"auto","created_at":"2026-01-14 23:08:00","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":114092,"visible":true,"origin":"","legend":"\u003cp\u003eTime-resolved lateralization trajectories across solar terms reveal dynamic and individual-specific patterns.\u003c/p\u003e\n\u003cp\u003e(A–C) Lateralization indices (LI) across successive solar terms for three cats continuously monitored in Hualien. LI values exhibit substantial within-individual fluctuations over time, including changes in both magnitude and direction, with no synchronized pattern across individuals.\u003c/p\u003e\n\u003cp\u003e(D) LI trajectory across solar terms for a cat housed in an air-conditioned environment, showing attenuated temporal variation relative to cats exposed to ambient environmental conditions. In all panels, the dashed line indicates LI = 0.\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/56222a1e951551c1083c343a.jpg"},{"id":101625292,"identity":"98b24a41-c22f-45fd-ab42-d74db27e9e08","added_by":"auto","created_at":"2026-02-02 03:40:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":513054,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/9a7cdffc-d21f-48d3-9e9a-49e6567a8403.pdf"},{"id":100372885,"identity":"e2bd6323-5015-4060-991b-284494e63446","added_by":"auto","created_at":"2026-01-16 08:13:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14410,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigureandTablelegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/b41b498b7e27b36cef61d461.docx"},{"id":100372149,"identity":"e4f4565e-6e77-4dac-a26f-2b79edb2e2d1","added_by":"auto","created_at":"2026-01-16 08:11:45","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":74569,"visible":true,"origin":"","legend":"","description":"","filename":"FigS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/1013da55753331f5f3050358.jpg"},{"id":100275692,"identity":"e798bf47-7f2b-41ba-aa50-083609075265","added_by":"auto","created_at":"2026-01-14 23:08:00","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":4910,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/089f9cb00e3d7bdb047e11c4.xlsx"},{"id":100275697,"identity":"4d5eb44a-e26d-4327-85de-74e4691e5d93","added_by":"auto","created_at":"2026-01-14 23:08:00","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":5231,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/912d04078e7f0ffa032711ee.xlsx"},{"id":100275696,"identity":"bc94a489-5566-44c0-b6eb-8c50a90e3d24","added_by":"auto","created_at":"2026-01-14 23:08:00","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":5589,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8540763/v1/14c0d51bbf1d5eb1ea653b81.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Stratified analyses reveal temporal instability and seasonal modulation of lateralized lying in domestic cats","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBehavioral lateralization, defined as the consistent preferential use of one side of the body over the other, has been documented across a wide range of animal taxa[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Such asymmetries are often interpreted as manifestations of hemispheric specialization and are frequently discussed at either the population level, where most individuals show the same directional bias, or the individual level, where stable preferences vary among individuals. This framework has yielded important insights into the evolution and function of lateralized behaviors, particularly in goal-directed tasks such as foraging, manipulation, or predator avoidance.\u003c/p\u003e \u003cp\u003eHowever, many studies of behavioral lateralization rely on relatively short observation windows or uneven sampling across individuals[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], raising questions about the stability and interpretability of reported lateralization indices. In naturalistic settings, behaviors may be expressed flexibly in response to environmental and internal states, and aggregating observations across time may obscure dynamic patterns occurring within individuals. This concern is especially relevant for resting or postural behaviors, which are not explicitly goal-directed and may be influenced by multiple competing factors, including thermoregulation, vigilance, comfort, and environmental context.\u003c/p\u003e \u003cp\u003eDomestic cats (Felis catus) provide a valuable model for examining lateralization under naturalistic conditions. As a familiar species living in close association with humans, cats exhibit a wide range of spontaneous behaviors that can be observed longitudinally in everyday environments. Previous studies have reported lateral biases in various feline behaviors, including paw use and turning direction, but findings have been mixed, and the extent to which such biases represent stable traits versus context-dependent expressions remains unresolved. Lateralized lying behavior, a common resting posture, has received comparatively little attention, despite its suitability for long-term observation and its potential sensitivity to environmental conditions.\u003c/p\u003e \u003cp\u003eRecent work has reported a population-level bias in lateralized sleeping positions in domestic cats based on pooled observations across individuals [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, the extent to which such inferences depend on observation density and temporal aggregation remains unclear.\u003c/p\u003e \u003cp\u003eHere, I investigate lateralized lying behavior in domestic cats using a large citizen-science dataset characterized by highly heterogeneous observation frequencies[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Rather than treating uneven sampling as a limitation to be minimized, I explicitly leverage this structure by adopting a stratified analytical framework. Low-frequency observations are used to assess whether strong population-level biases are detectable, mid-frequency data to characterize inter-individual variability, and high-frequency longitudinal records to examine within-individual dynamics across solar terms. By aligning analytical scale with data resolution, this study aims to clarify how lateralization in a common resting behavior should be interpreted under naturalistic conditions, and to what extent it reflects stable traits versus dynamic, context-dependent modulation.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eStudy design and data collection\u003c/p\u003e\u003cp\u003eThis study combined systematic longitudinal observation with a citizen-science approach to capture lateralized lying behavior in domestic cats under naturalistic conditions. Data were collected from multiple households and varied substantially in observation frequency, reflecting differences in participant engagement and study duration.\u003c/p\u003e\u003cp\u003eLongitudinal high-frequency observations\u003c/p\u003e\u003cp\u003eThree cats residing in Hualien were monitored continuously as part of a high-frequency longitudinal protocol. Observations were conducted daily during two fixed time windows: 06:00–08:00 and 21:00–23:30. During each observation window, the lying posture of each cat was recorded whenever the cat was observed resting. These repeated observations allowed estimation of individual lateralization indices across time and facilitated time-resolved analyses across solar terms.\u003c/p\u003e\u003cp\u003eCitizen-science data collection\u003c/p\u003e\u003cp\u003eData from additional cats were collected through a citizen-science framework. Cat owners voluntarily participated by submitting observations via a standardized Google Form designed by the authors. For each observation, participants recorded the date, time, cat identity, lying posture (left, right, or neutral), presence of other individuals, and the cat’s activity state (e.g., sleeping, resting, inactive). Participants were instructed to record observations opportunistically during everyday interactions with their cats, without imposing experimental manipulation.\u003c/p\u003e\u003cp\u003eTo encourage regular participation and sustained engagement, cumulative observation counts were publicly updated on a daily basis, and participants were awarded virtual badges recognizing consistent observation over time. These engagement mechanisms were implemented to increase longitudinal coverage while maintaining the naturalistic context of observations.\u003c/p\u003e\u003cp\u003eEthical considerations\u003c/p\u003e\u003cp\u003eAll observations were non-invasive and conducted in the cats’ usual living environments without physical interaction or behavioral manipulation. Participation by cat owners was voluntary, and no personal identifying information beyond cat names was collected. The study involved observational recording of companion animals in their home environments. Under local regulations, such observational studies do not require formal ethical approval.\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eInformed consent\u003c/strong\u003e \u003c/p\u003e\u003cp\u003ewas obtained from all participating pet owners prior to data collection. The study involved non-invasive, observational recording of naturally occurring behaviors in domestic cats, as reported by their owners. No experimental manipulation was performed on the animals.\u003c/p\u003e\u003cp\u003eDefinition of lateralization index and analytical stratification\u003c/p\u003e\u003cp\u003eLateralized lying behavior was quantified using a lateralization index (LI), defined as\u003c/p\u003e\u003cp\u003eLI=(R − L)/(R + L),\u003c/p\u003e\u003cp\u003ewhere R and L represent the number of right- and left-side lying observations, respectively. Neutral postures for which left–right orientation could not be determined were excluded from LI calculation. LI values range from − 1 (exclusive left-side lying) to + 1 (exclusive right-side lying), with values near zero indicating little or no directional bias.\u003c/p\u003e\u003cp\u003eGiven the highly uneven distribution of observations across individuals, analyses were stratified according to observation frequency to ensure that analytical scale was aligned with data resolution. Cats were classified into three groups: a low-frequency group, consisting of individuals with less than 10 observations; a mid-frequency group (more than 10 but less than 60 approximately), for which individual-level LI could be estimated with moderate confidence; and a high-frequency group, comprising individuals with extensive longitudinal records. Low-frequency data were analyzed only at the pooled population level to assess the presence of large population-wide biases, whereas mid-frequency data were used to examine inter-individual variability. High-frequency data enabled both overall individual LI estimation and time-resolved analyses across solar terms to capture within-individual dynamics.\u003c/p\u003e\u003cp\u003eThis stratified approach was adopted a priori to avoid conflating population-level, individual-level, and temporal sources of variation[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], and to prevent overinterpretation of sparse individual records.\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAnalyses were primarily descriptive and exploratory, reflecting the observational and naturalistic nature of the dataset. For the low-frequency group, left–right counts were pooled across individuals to estimate a group-level LI and corresponding proportions. For the mid-frequency group, individual LI values were calculated and visualized to characterize the distribution and range of inter-individual variation, without assuming a common underlying direction.\u003c/p\u003e\u003cp\u003eFor high-frequency individuals, overall LI values were calculated across the entire observation period, and time-resolved LI trajectories were examined by aggregating observations within successive solar terms. These trajectories were visualized to assess within-individual changes in magnitude and direction over time. Comparisons focused on qualitative patterns of variability, synchrony, and directional shifts rather than on formal hypothesis testing.\u003c/p\u003e\u003cp\u003eNo inferential statistical tests were used to compare LI values across groups, as the primary objective was to evaluate how lateralization patterns depend on sampling resolution and analytical scale, rather than to test a specific parametric model. All analyses were conducted using standard spreadsheet and statistical software, and figures were generated to emphasize transparency and interpretability of observed patterns.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eResults 1\u003c/p\u003e \u003cp\u003eLow-frequency observations show no evidence for a strong population-level lateral bias\u003c/p\u003e \u003cp\u003eIn the low-frequency group, most individuals contributed only one or a few observations, precluding reliable estimation of individual-level lateralization. Therefore, lateralized lying behavior was assessed exclusively at the group level by pooling all left\u0026ndash;right observations. After excluding neutral postures with indeterminate orientation, a total of 176 observations were retained for analysis.\u003c/p\u003e \u003cp\u003eThe resulting lateralization index (LI) was 0.0552, corresponding to a right-lying proportion of approximately 52.8%, indicating only a very slight rightward bias. The observed effect size was small and did not support the presence of a strong or consistent population-level lateral preference.\u003c/p\u003e \u003cp\u003eGiven the sparse and uneven sampling at the individual level, this analysis was not intended to infer individual lateralization, but rather to evaluate whether a large population-level bias could be detected. The results indicate that, if population-level lateralization in lying posture exists, its magnitude is limited to a small effect size.\u003c/p\u003e \u003cp\u003eSex-stratified analyses of the low-frequency group showed a similar overall pattern and did not reveal pronounced directional differences (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Taken together, the low-frequency observations provide no evidence for a strong or stable population-wide lateral bias in domestic cats\u0026rsquo; lying behavior.\u003c/p\u003e \u003cp\u003eResults 2\u003c/p\u003e \u003cp\u003eMid-frequency observations reveal pronounced inter-individual variability in lateralized lying behavior\u003c/p\u003e \u003cp\u003eIn contrast to the low-frequency group, cats in the mid-frequency group contributed sufficient repeated observations to allow estimation of individual-level lateralization indices (LI). Examination of individual LI values revealed substantial variability across cats, spanning both positive and negative ranges (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLI values in this group ranged from strongly left-biased to strongly right-biased individuals, with several cats exhibiting pronounced lateralization in either direction, while others remained close to zero. Importantly, the distribution of LI values was not centered on a single dominant direction; instead, lateralized lying behavior manifested idiosyncratically at the individual level, with no uniform population-wide orientation.\u003c/p\u003e \u003cp\u003eAlthough a slight predominance of positive LI values was observed, the presence of multiple strongly left-biased individuals resulted in a broad and overlapping distribution around zero. This pattern indicates that lateralization in lying posture, when present, does not converge on a consistent group-level direction but rather reflects marked inter-individual differences.\u003c/p\u003e \u003cp\u003eTaken together, the mid-frequency data demonstrate that lateralized lying behavior in domestic cats is best characterized as an individual-specific phenomenon, rather than as a uniform population-level preference. These findings motivate further examination of within-individual dynamics under conditions of high-resolution longitudinal sampling.\u003c/p\u003e \u003cp\u003eResults 3\u003c/p\u003e \u003cp\u003eOverall lateralization remains modest even in high-frequency individuals\u003c/p\u003e \u003cp\u003eTo determine whether extensive longitudinal sampling would reveal strong and stable lateralization, I examined overall LI values for cats in the high-frequency group. Despite substantially higher numbers of observations per individual, overall LI values remained modest and varied in direction across cats (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong the eight high-frequency individuals, LI values ranged from weakly left-biased to moderately right-biased, with no cat exhibiting a consistently strong directional preference across the entire observation period. Several individuals showed LI values close to zero, indicating little net lateralization when observations were aggregated over time.\u003c/p\u003e \u003cp\u003eThese results indicate that increased sampling intensity alone does not yield pronounced or uniform lateralized lying behavior. Instead, even under dense longitudinal observation, overall lateralization appears limited in magnitude and heterogeneous in direction, suggesting that lateralized lying is not a fixed trait expressed consistently across time.\u003c/p\u003e \u003cp\u003eThis absence of strong overall lateralization in high-frequency individuals motivates a finer-grained, time-resolved analysis to examine whether lateralized lying behavior varies dynamically within individuals in response to environmental context.\u003c/p\u003e \u003cp\u003eResults 4\u003c/p\u003e \u003cp\u003eSeasonal trajectories reveal context-dependent and individual-specific modulation of lateralized lying behavior\u003c/p\u003e \u003cp\u003eTo examine whether lateralized lying behavior varies dynamically within individuals, I analyzed longitudinal LI trajectories across solar terms in cats with continuous high-frequency observations. This analysis revealed pronounced within-individual fluctuations in LI values over time, often exceeding the magnitude of overall LI estimated across the entire observation period.\u003c/p\u003e \u003cp\u003eIn three cats continuously monitored across multiple solar terms in Hualien, LI values showed substantial seasonal variation, including marked shifts in both magnitude and direction (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u0026ndash;C). In some individuals, LI values transitioned from strongly left-biased during summer solar terms to right-biased values in later seasons(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), whereas others exhibited distinct but non-parallel trajectories. Notably, these seasonal changes were not synchronized across individuals, indicating that lateralized lying behavior does not follow a uniform seasonal pattern at the population level.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDespite being exposed to the same regional climate and temporal progression of solar terms, each cat exhibited a unique LI trajectory, with changes occurring at different times and in different directions. This heterogeneity suggests that the expression of lateralized lying behavior is modulated in an individual-specific manner, rather than being driven by a shared external seasonal signal.\u003c/p\u003e \u003cp\u003eIn contrast, a cat housed in an air-conditioned environment showed attenuated seasonal variation in LI values (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Although short-term fluctuations were still observed, the magnitude of change across solar terms was reduced relative to cats exposed to ambient environmental conditions. This pattern is consistent with reduced sensitivity to external environmental variation under thermally regulated indoor conditions.\u003c/p\u003e \u003cp\u003eAdditional high-frequency individuals monitored across multiple solar terms exhibited intermediate patterns, with observable but less pronounced within-individual variability (Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Together, these results demonstrate that lateralized lying behavior in domestic cats is dynamic over time, shaped by environmental context and expressed idiosyncratically at the level of individual animals, rather than as a stable or synchronized seasonal trait.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, I examined lateralized lying behavior in domestic cats using a stratified analytical framework designed to accommodate highly uneven observational regimes typical of citizen-science data. Across low-frequency observations involving many individuals with sparse sampling, I found no evidence for a strong population-level lateral bias. In contrast, mid-frequency data revealed pronounced inter-individual variability, with some cats exhibiting clear lateral preferences in opposite directions. Even among high-frequency individuals with extensive longitudinal records, overall lateralization remained modest when aggregated across time. However, time-resolved analyses uncovered substantial within-individual fluctuations across solar terms, demonstrating that lateralized lying behavior is dynamic, context-dependent, and expressed idiosyncratically rather than as a stable trait. Our findings help reconcile apparent discrepancies with previous reports of population-level laterality in domestic cats [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], by showing that such patterns can emerge under low observation density but become unstable when individual-level and temporal dynamics are explicitly considered.\u003c/p\u003e \u003cp\u003ePrevious studies of behavioral lateralization in animals have often emphasized population-level asymmetries or interpreted individual biases as fixed traits reflecting hemispheric specialization[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. My findings extend this literature by showing that, for a common resting posture in a familiar species, lateralization cannot be adequately characterized by a single static index. Instead, lateralized lying in domestic cats appears to emerge from the interaction between individual-specific tendencies and environmental context, becoming most evident under high-resolution longitudinal observation. By explicitly separating population-level, individual-level, and time-resolved analyses, this study highlights how conclusions about lateralization critically depend on data structure and analytical scale.\u003c/p\u003e \u003cp\u003eA key methodological implication of this study concerns the widespread practice of summarizing behavioral lateralization using a single static index, often derived from limited or uneven observations[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. My results demonstrate that such an approach can obscure both the absence of strong population-level biases and the presence of meaningful individual- and context-dependent variation. In particular, when observations are sparse or unevenly distributed across individuals, aggregating data without regard to sampling structure may either exaggerate apparent group-level asymmetries or mask dynamic patterns expressed within individuals.\u003c/p\u003e \u003cp\u003eBy explicitly stratifying analyses according to observational frequency and separating population-level, individual-level, and time-resolved perspectives, I show that lateralization cannot be treated as a unitary property invariant across analytical scales. Low-frequency data are informative for constraining the upper bound of population-level effects, but are ill-suited for inferring individual traits. Conversely, mid- and high-frequency data reveal that individual lateralization is heterogeneous and temporally labile, such that averaging across time can substantially underestimate within-individual variability. These findings underscore the importance of aligning analytical strategy with data resolution and caution against interpreting lateralization indices as fixed traits in the absence of sufficient longitudinal evidence.\u003c/p\u003e \u003cp\u003eBeyond methodological considerations, the dynamic and individual-specific patterns observed here suggest that lateralized lying may be better understood as a situational behavioral expression rather than a fixed manifestation of hemispheric dominance. Resting postures in animals are known to balance multiple competing demands, including thermoregulation, vigilance, comfort, and rapid responsiveness to environmental cues. Variation in lying orientation across time and context may therefore reflect flexible adjustments to these demands, rather than stable lateral preferences per se.\u003c/p\u003e \u003cp\u003eThe absence of synchronized seasonal trajectories across individuals, even among cats exposed to similar external conditions, further supports this interpretation. If lateralized lying primarily reflected an intrinsic or population-wide asymmetry, more parallel shifts would be expected across individuals. Instead, the observed heterogeneity suggests that individual history, local microenvironment, and internal state may interact to shape posture selection at any given time. In this sense, lateralized lying may function less as a marker of neural specialization and more as a context-sensitive posture, whose expression emerges from the interplay between individual tendencies and moment-to-moment environmental constraints.\u003c/p\u003e \u003cp\u003eImportantly, this perspective aligns with growing evidence across taxa that lateralized behaviors can be plastic, task-dependent, and modulated by external conditions, particularly in non-goal-directed contexts such as rest [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Interpreting lateralization in such behaviors therefore requires caution against overgeneralizing from static indices or short observation windows, and instead calls for longitudinal approaches capable of capturing temporal variability and individual-specific trajectories.\u003c/p\u003e \u003cp\u003eSeveral limitations of this study should be acknowledged. First, the data were derived from a citizen-science framework, resulting in highly uneven sampling across individuals and households[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Although this heterogeneity motivated my stratified analytical approach, it also constrained the types of inferences that could be drawn, particularly at the individual level for low-frequency observations. In addition, lying orientation was assessed from owner-reported observations rather than standardized experimental recordings, raising the possibility of observer-related variability. However, such variability is unlikely to systematically bias directionality across individuals and instead would tend to reduce detectable effect sizes, rendering my conclusions conservative.\u003c/p\u003e \u003cp\u003eSecond, although seasonal patterns were examined using solar terms as a temporally structured framework, environmental variables such as ambient temperature, light intensity, humidity, and household conditions (e.g., indoor climate control) were not independently manipulated and may be partially confounded. As illustrated by the attenuated variability observed in an air-conditioned environment, future studies incorporating direct measurements of microclimate or controlled manipulations will be essential for disentangling the relative contributions of light, temperature, and other contextual factors.\u003c/p\u003e \u003cp\u003eFinally, the present study focused on a single, common resting posture in domestic cats. Whether similar dynamic and context-dependent lateralization patterns extend to other behaviors, postures, or species remains an open question. Future research combining long-term naturalistic observation with targeted experimental designs may help clarify when lateralization reflects stable individual tendencies and when it emerges as a flexible response to environmental conditions. Such integrative approaches will be critical for advancing a more nuanced understanding of behavioral lateralization beyond static population-level summaries.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Data Availability\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eVallortigara, G., \u0026amp; Rogers, L. J. (2005). Survival with an asymmetrical brain: Advantages and disadvantages of cerebral lateralization. Behavioral and Brain Sciences, 28(4), 575–589. https://doi.org/10.1017/S0140525X05000105\u003c/li\u003e\n \u003cli\u003eRogers, L. J., Vallortigara, G., \u0026amp; Andrew, R. J. (2013). Divided brains: The biology and behaviour of brain asymmetries. Cambridge University Press.\u003c/li\u003e\n \u003cli\u003eIsparta, S., Ocklenburg, S., Siniscalchi, M., Goursot, C., Ryan, C. L., Doucette, T. A., Reinhardt, P. R., Gosse, R., Çıldır, Ö. Ş., d’Ingeo, S., Freund, N., Güntürkün, O., \u0026amp; Demirbas, Y. S. (2025). Lateralized sleeping positions in domestic cats. Current Biology, 35(12), R587–R600. https://doi.org/10.1016/j.cub.2025.04.043\u003c/li\u003e\n \u003cli\u003eDickinson, J. L., Zuckerberg, B., \u0026amp; Bonter, D. N. (2010). Citizen science as an ecological research tool: challenges and benefits. Annual Review of Ecology, Evolution, and Systematics, 41, 149–172.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","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":"","lastPublishedDoi":"10.21203/rs.3.rs-8540763/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8540763/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBehavioral lateralization is often described as a stable trait expressed at either the population or individual level. However, such conclusions are frequently drawn from limited or uneven observations, raising questions about how lateralization should be interpreted under naturalistic conditions. Here, I investigated lateralized lying behavior in domestic cats using a large, citizen-science dataset characterized by highly variable observation frequencies. To address this heterogeneity, I applied a stratified analytical framework separating population-level, individual-level, and time-resolved analyses.\u003c/p\u003e \u003cp\u003eAcross low-frequency observations involving many individuals with sparse sampling, I found no evidence for a strong population-level lateral bias in lying posture. In contrast, cats with moderate observation frequencies exhibited pronounced inter-individual variability, with clear lateral preferences expressed in both directions but no uniform group-level orientation. Even among high-frequency individuals with extensive longitudinal records, overall lateralization indices remained modest when aggregated across time. However, fine-grained analyses across solar terms revealed substantial within-individual fluctuations, including directional reversals, indicating that lateralized lying behavior is dynamic rather than fixed. These temporal trajectories differed across individuals and were attenuated in an air-conditioned environment, consistent with context-dependent modulation.\u003c/p\u003e \u003cp\u003eTogether, my results suggest that lateralized lying in domestic cats is best understood as an individual-specific and environmentally modulated behavior, rather than a stable population-wide trait. By explicitly aligning analytical scale with data resolution, this study highlights the importance of longitudinal and context-aware approaches for interpreting behavioral lateralization under naturalistic conditions.\u003c/p\u003e","manuscriptTitle":"Stratified analyses reveal temporal instability and seasonal modulation of lateralized lying in domestic cats","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-14 23:07:55","doi":"10.21203/rs.3.rs-8540763/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":"4cedd781-7f78-470d-ba39-245b1daa0d45","owner":[],"postedDate":"January 14th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61047404,"name":"Biological sciences/Ecology"},{"id":61047405,"name":"Earth and environmental sciences/Ecology"},{"id":61047406,"name":"Biological sciences/Neuroscience"},{"id":61047407,"name":"Biological sciences/Psychology"},{"id":61047408,"name":"Social science/Psychology"},{"id":61047409,"name":"Biological sciences/Zoology"}],"tags":[],"updatedAt":"2026-02-02T03:39:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-14 23:07:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8540763","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8540763","identity":"rs-8540763","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}