Responses to operant conditioning in the corn snake, Pantherophis guttatus, using olfactory and visual stimuli

Responses to operant conditioning in the corn snake, Pantherophis guttatus, using olfactory and visual stimuli | 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 Research Article Responses to operant conditioning in the corn snake, Pantherophis guttatus, using olfactory and visual stimuli Adam Green, Liam Andersen, Anna L Berenguer, Clifford Zeyl This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9066746/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Snakes are historically underrepresented in experimental studies of learning. Operant conditioning reinforced by food rewards has successfully been applied to a few species, and corn snakes have learned to use visual cues to locate a hiding spot, but despite the growing popularity of snakes as pets, their capacity for learning is largely unexplored. We used reinforcement with food rewards to train two cohorts of corn snakes ( Pantherophis guttatus , 15 snakes in total), on olfactory and visual cues in two separate experiments. We applied a criterion for acquisition of at least 7 correct decisions in any 8 consecutive trials, and for the first cohort tested for reversal learning of olfactory and then visual cues once the criterion was met. Error rates and latencies to correct choices declined significantly in cohort 1, a group of eight three-year-old snakes. The response of a second cohort of seven three-year-olds was more subtle: all but one reached criteria, but with no overall decline in error rates. When subjected to repeated reversals, in which the identity of the reinforced cue was switched, cohort 1 responded increasingly quickly to each successive reversal, demonstrating the cognitive abilities to inhibit learned responses and to switch their attention to the previously irrelevant cue. Corn snakes show promise as a representative species for learning in reptiles. Operant conditioning corn snakes reversal learning olfactory and visual cues Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Most of what is known about learning in animals comes from work on a small number of model species. But historically neglected vertebrate groups, in particular fish and reptiles, are beginning to receive more attention, challenging the view that they have little potential for learning. This view may have become established in part because their brains are smaller relative to their body size than those of endothermic vertebrates, and lack a cortex. Yet several studies have revealed quite sophisticated cognitive abilities in fish, including transitive inference in a cichlid (Grosenick et al. 2007) and self-awareness in cleaner wrasse (Kohda et al. 2023 ), despite the latter apparently lacking working memory (Bonin et al. 2025 ). Snakes are still among the most neglected taxa in studies of animal cognition, with a few pioneering exceptions. Burkhardt (2013) focused on reptile learning and behavior for decades, providing evidence that their capabilities had been widely underestimated. However, the ecology and physiology of snakes are unique (Title et al. 2024). Snakes tend to alternate between large meals and periods of fasting that can last for days, weeks or months, which may have selected for different learning abilities than the relentless need for more frequent smaller meals experienced by endotherms. These eating habits are also potentially problematic in operant conditioning experiments, which rely on regular sessions of repeated reinforcement with small quantities of food, although Burmese pythons ( Python bivittatus ) have proven willing to accept very small food items as reinforcement, enabling Emer et al. ( 2015 ) to train them to press a button for food when illuminated. This is all the more remarkable given that snakes are believed to rely more on olfaction than on vision when hunting. The general consensus is that they have fairly poor eyesight and are dichromatic, with their cones only reacting to blue and green wavelengths (Simões et al., 2016 ; Da Silva et al., 2020 ) and relatively few studies have applied conditioning to snakes using visual cues. Eliciting unnatural behavior such as pushing an illuminated button demonstrates a degree of behavioral flexibility that may be unexpected in the case of snakes, and their response to conditioning can be quite sensitive to the details of stimuli and type of reinforcement. Kellogg & Pomeroy ( 1936 ) used cold water as an aversive stimulus and warm water (10° and 32° respectively) as positive reinforcement and observed declines in both latency and error rates in 12 banded watersnakes in a maze ( Nerodia fasciata ), but Wolfle & Browne (1940) saw no evidence of learning in 11 diamondback watersnakes ( N. rhombifer ) using escape from hot water (48–55°) or from a mild electric shock as reinforcement. Williams et al. ( 2022 ) used positive reinforcement and shaping to train false water cobras ( Hydrodynastes gigas ) to follow a target into a shift container, and corn snakes can use visual cues to navigate in an arena to a hiding spot (Holtzmann et al 1999). In an early study, Takemasa and Nakamura ( 1935 , cited by Kleinginna, 1970 ) trained snakes to escape from a box, although a greater challenge might have been training them not to escape, as most snakes are from birth highly skilled at escaping. Crawford & Bartlett ( 1966 ) commented that “snakes have a well-earned reputation for being refractory.” But the same qualities that have made corn snakes, Pantherophis guttatus , popular pets by reptilian standards also make them well suited to research on animal learning. They can implement different hunting strategies in different environmental settings (DeGregorio et al. 2016). They are abundant and relatively inexpensive due to widespread captive breeding, calm and docile by nature, and flourish on a diet of frozen-thawed mice. Even adults willingly accept a series of 1–4 day-old mice or “pinkies” as reinforcement in lieu of an adult mouse. Here we characterize their responses to operant conditioning, and describe experimental and biological factors that contribute to variation among individuals. We began with odor cues. After successful conditioning of eight adult snakes using odor cues we imposed a series of cue reversals by switching which cue was reinforced, to assess their behavioral flexibility. We then changed to visual cues, followed by more reversals once the snakes had achieved criterion once again. We then compared the responses of the adults to a separate cohort of seven subadult corn snakes. Materials and Methods We began with an operant conditioning experiment on eight corn snakes which were just over two years old at the start of the experiment, three males and five females. The snakes were purchased online as hatchlings a few weeks old from VMSHerps in October 2019. Since then they have been singly housed in homemade 80 cm x 60 cm x 50 cm enclosures made of wood, painted glossy black for ease of cleaning, with a 40 cm by 56 cm acrylic window 0.32 cm thick in a vertically sliding door. A Pro Products (Mahopac, NY) heat panel is mounted on the roof of each enclosure in the back right corner to create a temperature gradient, enabling the snakes to thermoregulate. The heat panels are regulated by thermostats (Vivarium Electronics model VE-200D) set for 27°. The enclosures are located in a windowless room and are illuminated by a 60 cm fluorescent light on a timer set to a daily 12h light:12h dark cycle. Their substrate is a mix of cypress and aspen mulch. In September of 2021 another eight snakes were purchased from VMSHerps (which has since gone out of business) and housed singly in enclosures the same as those described above. The older and younger cohorts are henceforth referred to as cohorts 1 and 2 respectively. Cohort 1 are snakes 1, 2, 3, 4, 5, 7, 8 and 10, and cohort 2 are 11 through 18. Conditioning Experiments Two operant conditioning experiments were performed, both of them in the same arena and differing in which cohort was involved and in the cues that were used. The arena was a wooden oval 13.5” x 30 cm x 20 cm, with a tunnel 5.7 cm in diameter and 16 cm long on each side, made of clear acrylic so as not to confound the motivating effect of food by offering them an additional reward in the form of a hiding place, and so that the experimenter could see when a snake had finished swallowing (Fig. 1 ). During training sessions the arena floor was covered by bench paper, which was replaced between sessions. The arena was placed in an unoccupied snake enclosure in the same room where the snakes were housed, with a Nexigo web cam on the roof of the arena. All sessions were video-recorded. Cohort 1 was trained from September 2021 through November 2022, first on scent cues for 72 sessions, and then for 24 sessions on visual cues: a green 2 cm x 2 cm square and a blue circle 2 cm in diameter, both framed by a 2 cm white border, printed from a laptop and laminated. Experiment 2 trained cohort 2 on those same visual cues for 50 sessions. Experiment 1 began in September 2021, after an acclimation period that was unexpectedly prolonged by a ban on indoor research activities during the COVID-19 pandemic. When the restrictions were lifted, each snake was given a habituation period during which it was allowed to freely roam the arena to familiarize itself with the layout of the arena. To encourage exploration and get them accustomed to feeding in the tunnels, a frozen-thawed pinky was placed in each tunnel so the snakes were rewarded for exploration regardless of which tunnel they chose. Each snake was removed from the arena after consuming one pinky The scent cues used to begin Experiment 1 were essential oils of lavender and lemon, chosen to be distinctive and novel but innocuous. Preliminary experiments showed that the snakes had no initial preference for either scent. The odors were presented as 6 ul of essential oil pipetted onto 2 cm squares of filter paper which were taped above the tunnel entrances. To begin the experiment, the cues to be reinforced were assigned randomly to the eight snakes using an R script. Each training session consisted of four consecutive trials for each snake. Any snakes that were “opaque”, or about to shed, as evidenced by cloudy eyes, dull colors, and diminished appetites, were excluded from training sessions until after they had shed. In each session, we randomized the order in which the snakes were tested, and for each of a snake’s trials, whether the reinforced cue was presented above the right or left tunnel, again using R. The criterion for acquisition, or ‘graduation’, was a snake choosing correctly in at least 7 of any 8 consecutive trials, an established threshold in reptile learning experiments (e.g. Riley et al 2018 ; Szabo et al. 2018 ; Szabo et al. 2019 ; Szabo et al. 2021 ). Following successful acquisition by the entire cohort, the olfactory cues were reversed for all snakes after 42 sessions, meaning that the reinforced and non-reinforced cues were switched. The timings of subsequent reversals varied among snakes according to when they graduated from the preceding reversal. There were three reversals of olfactory cues, followed by the switch to visual cues on the 72nd session, and then three reversals of visual cues. In Experiment 2 we applied operant conditioning for 58 sessions of three trials, each using the same visual cues as in the latter portion of Experiment 1, to a second cohort of snakes, two years old at the start of the experiment, from October 2023 until November 2024. All 7 snakes in cohort 2 began with a habituation period as in Experiment 1. Snake 16 ceased to cooperate partway through the conditioning experiment and is excluded from all analyses. To conduct a single operant conditioning session, snakes were randomly ordered for testing, and the placement of the assigned visual cue by the entrance of either the left or right tunnel was randomly assigned for each trial in the session using an R script. The alternate cue was placed at the entrance of the opposite tunnel from the reinforced cue. Snakes were then placed at the entrance of the arena, where movement decisions were timed and recorded. For cohort 2, reinforcement during each trial was half a pinky rather than an entire one, so that these smaller snakes would not be satiated after the first trial or two. Half a pinky was placed in the correct tunnel prior to the start of each trial, and each individual trial ran until the snake had selected the correct tunnel and consumed the half pinky. As in Experiment 1, snakes that were “opaque” were excluded from training until after they had shed. Analysis Count data may be modeled with Poisson or negative-binomial regression. Poisson models assume that means and variances are equal, while count data are frequently characterized by overdispersion, or a variance greater than the mean. In both experiments, numbers of trials until success showed the expected overdispersion, with ratios of variance to mean of 2.36/1.11 in Experiment 1 and 5.09/2.43 in Experiment 2. The negative binomial distribution has an additional parameter to accommodate overdispersion and accounts for the fact that every trial ended with the first correct choice. We applied negative binomial regression both to numbers of errors and to latencies to correct decisions. Estimates of coefficients were very similar to those obtained from Poisson regressions, but the negative binomial models consistently yielded much lower AICs and estimates of the inverse dispersion parameter were below 0.2, confirming overdispersion. We used the glm function in R to fit the negative binomial regression model Trials Until Success ~ β session ·Session + β trial ·Trial + β snake ·Factor(Snake) using RStudio version 2025.09.2 with R 4.5.0. The repeated-measures aspect of the experimental design proved problematic. The assumption that each data point is independent of the others is violated by the fact that each snake contributed observations at many time points. This is addressed by modeling snake identity as a random factor nested within session number, but such models, run with two different R packages (MASS and glmmTNB), were plagued by singularities and failures to converge, which can result from strong collinearity between predictors or from a lack of variation among subjects. Other studies of reptile behavior have reported similar issues (e.g. Skinner et al. 2024). In our case a dearth of variation among individuals is the most likely cause. We therefore present results from models lacking a nested term. We also tested for effects of shed cycles on error rates and latencies, and for correlations between overall numbers of sheds and rates of learning. Results We first present results for Experiment 1 and then compare them with the outcome of Experiment 2. We analyze both counts of errors per training session, and numbers of attempts taken to make the first correct choice, noting that every trial ended on the first success. Mean error rates declined significantly over the course of Experiment 1 (Fig. 2). We detected no variation among snakes in the rate of that decline, nor across the trials within each session (Table 1 ). Two features of the experiment interrupted the overall trend. First, in the 42nd training session we applied the first of several reversals to all eight snakes simultaneously. Those that had been rewarded for choosing the tunnel marked by essential oil of lavender now had the scent of lemon reinforced, and vice versa. Second, starting with the 73rd session we replaced the odor cues with visual ones (Fig. 1 ). As expected, both changes were followed by temporary increases in error rates (Fig. 2). Figure 3 shows the response of each snake to those two disruptions and to reversals that were applied individually when a snake reached the criterion for acquisition again. Error rates increased in most snakes when odor cues were reversed, but they responded increasingly quickly to subsequent reversals (Fig. 4 ). Figure 2. Loess curve fitted to error rates of cohort 1 snakes in Experiment 1 using function geom_smooth in package ggplot2 in R, with “span” set to 0.3. The vertical lines indicate the time of the first reversal after 42 sessions followed by the switch from odor cues to visual cues after 72 sessions. Figure 3 . Loess curves fitted to error rates of individual snakes in Experiment 1. Vertical gray lines indicate timing of reversals during the odor-cue stage of the experiment, vertical purple line represents the switch to visual cues, and vertical orange lines indicate reversals of visual cues, for a) snake 1, b) snake 2, c) snake 3, d) snake 4, e) snake 5, f) snake 7, g) snake 8 and h) snake 10. Dots represent observed error counts. Another possible response to conditioning is a decreasing latency to correct decisions as the cues become increasingly familiar. Alternatively, a longer latency could reflect more careful decision-making, resulting in longer sessions and fewer errors. Sessions were shorter at the end of Experiment 1 than at the beginning (Fig. 5 ), and negative binomial regression showed a significant negative effect of session number on session duration (Table 2 ). Session duration (the cumulative length of the trials in a session) was positively correlated with numbers of errors (Spearman rank correlation, ρ = 0.118, P = 1.97x10 − 3 ). Since every trial ended with the first correct choice, more errors may have prolonged trials simply by delaying that success. In Experiment 2, cohort 2 as a whole showed no significant overall decline in numbers of attempts before success (Fig. 6 ; Table 3 ) even though 6 of the 7 snakes did reach criterion at some point. In contrast to experiment 1, in experiment 2 the duration of sessions did not decline over time. With all seven snakes from Experiment 2, we then asked whether it was the shapes of the cues (green square or blue circle) or their colors that they most attended to, using green circle and blue square cues. We tested each snake twice, reasoning that additional testing might have inhibited their conditioned responses. The correct color was chosen over the correct shape 12 times out of 14 trials. While suggestive, this is not significantly different from the null expectation of 7 out of 14 (Fisher’s Exact test, P = 0.103). Figure 7 compares the cumulative distributions of times to first acquisition in the two experiments. They show similar dynamics even though the response to conditioning was clearly greater in cohort 1 (Figs. 2 and 3 ; Table 1 ) than in cohort 2 (Fig. 7 ). To see whether the cohorts differed in the distribution of errors across trials, for each snake we drew from a binomial distribution 1000 random samples of a size equal to the number of choices that snake made during conditioning, using an error rate equal to that snake’s error rate averaged across the entire conditioning experiment. The observed distributions of errors over trials do not fit Poisson distributions for either cohort (chi-squared goodness of fit tests, P < 0.001 in both cases) because of a relative lack of one and two-error trials and an excess of error-free trials. While this doesn’t fully explain the contrasting timing of graduations in the two cohorts, it does suggest that wrong choices were not randomly distributed across trials, but instead tended to occur in clusters. We tested for a relationship between growth rates and rates of decline in error rates, reasoning that for an ectotherm, both growth rates and the response to conditioning would integrate multiple metabolic processes, so that faster-growing snakes might learn more quickly or more consistently. Linear regression on growth rates and negative binomial regression on trials until success were performed on the two cohorts combined. A Spearman’s rank correlation test confirmed a significant positive relationship between coefficients of growth-rate and trials until success (ρ = 0.657, P = 0.013). We also compared error rates in sessions that were preceded or followed within one week by a shed with error rates in other sessions, and found no difference. Numbers of trials until first graduation in cohort were positively correlated with total numbers of sheds during the conditioning experiment in cohort 1 (Spearman rho = 0.719, P = 0.045), but not in cohort 2 (Spearman rho = -0.086, P = 0.919). Discussion Mature corn snakes responded to operant conditioning using both olfactory and visual stimuli, all but one of eight reaching the criterion of choosing the reinforced cue in at least seven of any eight consecutive trials, and showing increasingly rapid reversal learning. Among a cohort of seven juveniles all but one reached criterion at some point, but without a detectable overall decline in error rates (Table 3 ) and with more variation among individuals (Table 3 ), even though the same visual cues, reinforcement and apparatus were used in both conditioning experiments. Reversal learning was not attempted with cohort 2 because without unambiguous declines in error rates it would have been unclear how to interpret the results. Cohort 2 was purchased from the same breeder at the same age (~ 2 months after hatching), and was then housed and fed in the same way as cohort 1 with the goal of minimizing effects on learning other than the two-year age difference. However, experiment 1 was performed entirely by one lab member (AG) and experiment 2 by two lab members (LA and AB) and we cannot rule out the possibility that the snakes were influenced by subtle differences in how they were handled. Snakes may learn more quickly when handled by only one person than when two lab members collaborate. Pending a direct experimental test, this is only anecdotal, although in their account of training banded watersnakes to find warmer water, Kellogg & Pomeroy ( 1936 ) noted that the same person handled all 12 snakes throughout a habituation period as well as the entire conditioning experiment, suggesting that they anticipated a handler effect. If that effect holds up to a direct experimental test, it would indicate a degree of sensitivity to human handling that would not be widely expected of a reptile. The switch from olfactory to visual cues in experiment 1 introduced the risk that snakes might then be able to smell the pinky in the reinforced tunnel before choosing which tunnel to enter. To test for this possibility, at the end of the experiment we ran additional sessions with no mouse in either tunnel; instead the snake was given a mouse with forceps after making the correct choice. We observed no change in their low error rates, and conclude that mouse odor was not a confounding factor during the experiment. In another difference between conditioning in cohorts 1 and 2, no variation among individuals was detected in the former (Table 1 ), while four cohort 2 snakes (14, 15, 16 and 18; Table 3 ) did significantly worse than the others. If there is an ontogenic component to aptitude for learning in corn snakes, greater variability in the younger cohort may reflect timing variation in the maturation of those learning abilities. Cohort 2 made errors at almost twice the rate of cohort 1 (0.432 errors per decision vs 0.229), but on average took slightly fewer trials to reach criterion than cohort 1 (35.9 vs 42.5 trials). Comparing the observed frequencies of error-free trials by each cohort with the frequencies obtained in random samples from binomial distributions with the observed error rates shows that the zero-error class of trials was over-represented in both cohorts, with a 6.2% excess in cohort 1 (2134 observed vs 2009 randomized) and a 16.8% excess in cohort 2 (563 observed vs. 482 randomized; Figure S1 ). Both cohorts also had fewer than expected trials with one error. Rather than occurring randomly, errors tended to cluster slightly in trials of 3 and 4 errors, inflating the frequencies of error-free trials and enabling earlier graduations than would have occurred with randomly distributed errors. After the completion of each experiment we tested the snakes’ memories at 3-month intervals using the last set of cues they had been trained on. Cohort 1 made correct choices on 95% of trials up to six months after that conditioning had stopped, after which their performance drifted towards randomness. Cohort 2, two years younger, made choices that were already indistinguishable from random 3 months after their conditioning ended, implying better long-term memory in the adult snakes. Perhaps our most striking result was the speed of reversal learning by cohort 1. Reversal learning requires the cognitive abilities to inhibit a learned response and to switch their attention to a previously irrelevant cue. Birch et al ( 2020 ) consider reversal learning to be a behavioral signature of a flexible “value system”, one of the eight features that they propose are hallmarks of the origin of biological consciousness. Unusually, cohort 1 required substantially fewer sessions to reach criterion again after each reversal than they did the first time: times to first graduation in Experiment 1 averaged 14.6 sessions, followed by 8.1, 2.4 and 1.2 sessions after three reversals respectively (Fig. 4 ), indicating that they had become aware that the rules of reinforcement could change, and responded more quickly to each reversal by switching their choices accordingly. This study joins several descriptions in the past few years of snakes demonstrating unexpected social behavior and behavioral plasticity (Skinner et al 2024a , b , c ), suggesting the potential for greater behavioral flexibility than they have historically been credited with. Declarations Conflict of Interest: The authors declare no conflicts of interest. Ethical Approval: All husbandry and experimental procedures performed with snakes were performed in compliance with Wake Forest University Institutional Animal Care and Use Committee protocol A23-060. Funding: This work was supported in part by Wake Forest University graduate and undergraduate research funds. Author Contribution Conceptualization: A.G. and C.Z, formal analysis: C.Z., A.G., L.A. and A.B., original draft: A.G, L.A., A.B. and C.Z., review and editing: C.Z., L.A., A.G. and A.B. All authors have seen and approved the final manuscript. Acknowledgement This work was supported in part by Wake Forest University Department of Biology graduate and undergraduate research funds. Data Availability The data that support the findings of this study will be available as a Supplementary Information file. References Birch J, Ginsburg S, Jablonka E (2020) Unlimited Associative Learning and the origins of consciousness: a primer and some predictions. Biol Philos 35:56. https://doi.org/10.1007/s10539-020-09772-0 Bonin L, Manrique HM, Bshary R (2025) Cleaner wrasse failed in early testing stages of both visual and spatial working memory paradigms. Anim Cogn 28:43. https://doi.org/10.1007/s10071-025-01959-w Burghardt G (2013) Environmental enrichment and cognitive complexity in reptiles and amphibians: Concepts, review, and implications for captive populations. Appl Anim Behav Sci 147:286–298. Https://doi.org/10.1016/j.applanim.2013.04.013 Crawford FT, Bartlett C (1966) Runway behavior of the gray rat snake with food and water reinforcement. Psychonomic Sci 4:99–100. https://doi.org/10.3758/BF03342197 Da Silva MO, Gade JT, Damsgaard C et al (2020) Morphology and evolution of the snake cornea. J Morphol 281:240–249. https://doi.org/10.1002/jmor.21094 Degregorio B (2016) Ecology and predation behavior of corn snakes ( Pantherophis guttatus ) on avian nests. Herpetological Conserv Biology 11:150–159 Emer SA, Mora CV, Harvey MT, Grace MS (2015) Predators in training: operant conditioning of novel behavior in wild Burmese pythons ( Python molurus bivitattus ). Anim Cogn 18:269–278. https://doi.org/10.1007/s10071-014-0797-1 Holtzman DA, Harris TW, Aranguren G, Bostock E (1999) Spatial learning of an escape task by young corn snakes, Elaphe guttata guttata . Anim Behav 57:51–60. https://doi.org/10.1006/anbe.1998.0971 Kellogg WN, Pomeroy WB (1936) Maze learning in water snakes. J Comp Psychol 21:275–295. https://doi.org/10.1037/h0063023 Kleinginna PR Jr. (1970) Operant conditioning in the indigo snake. Psychon Sci 18:53–55. https://doi.org/10.3758/BF03332330 Kohda M, Bshary R, Kubo N et al (2023) Cleaner fish recognize self in a mirror via self-face recognition like humans. Proc Natl Acad Sci USA 120:e2208420120. https://doi.org/10.1073/pnas.2208420120 Riley JL, Küchler A, Damasio T et al (2018) Learning ability is unaffected by isolation rearing in a family-living lizard. Behav Ecol Sociobiol 72:20. https://doi.org/10.1007/s00265-017-2435-9 Simões BF, Sampaio FL, Douglas RH et al (2016) Visual pigments, ocular filters and the evolution of snake vision. Mol Biol Evol 33:2483–2495. https://doi.org/10.1093/molbev/msw148 Skinner M, Nagabaskaran G, Gantert T, Miller N (2024a) Bolder together: conformity drives behavioral plasticity in eastern gartersnakes. Anim Cogn 27:2. https://doi.org/10.1007/s10071-024-01859-5 Skinner M, Hazell M, Jameson J, Lougheed SC (2024b) Social networks reveal sex- and age-patterned social structure in Butler’s gartersnakes ( Thamnophis butleri ). Behav Ecol 35:1–14. https://doi.org/10.1093/beheco/arad095 Skinner M, · Kumpan T, Miller N (2024c) Intense sociability in a non-social snake ( Python regius ). Behav Ecol Sociobiol 78:113. https://doi.org/10.1007/s00265-024-03535-7 Szabo B (2019) Context-specific response inhibition and differential impact of a learning bias in a lizard. Anim Cogn 22:317. https://doi.org/10.1007/s10071-019-01245-6 Szabo B, Noble DWA, Byrne RW et al (2018) Subproblem learning and reversal of a multidimensional visual cue in a lizard: evidence for behavioural flexibility? Anim Behav 144:17–26. https://doi.org/10.1016/j.anbehav.2018.07.018 Szabo B, Noble DWA, Byrne RW et al (2019) Precocial juvenile lizards show adult level learning and behavioural flexibility. Anim Behav 154:75–84. https://doi.org/10.1016/j.anbehav.2019.06.003 Szabo B, Noble DWA, Whiting MJ (2021) Learning simple and compound stimuli in a social lizard ( Egernia stokesii ). J Comp Psychol 135:208–218. https://doi.org/10.1037/com0000260 Takemasa T, Nakamura K (1935) Hebi mochieto hitotsumo gakushi iikken (A learning experiment with snakes). Kyotku Shinn Kerkvu 10:575–581 Title P (2024) The macroevolutionary singularity of snakes. Science 383:918–923. https://doi.org/10.1126/science.adh2 Williams ML, Torrini LA, Nolan EJ, Loughman ZJ (2022) Using Classical and Operant Conditioning to Train a Shifting Behavior in Juvenile False Water Cobras ( Hydrodynastes gigas ). Animals 12:1229. https://doi.org/10.3390/ani12101229 Wolfle D, Brown C (1940) A Learning Experiment with Snakes. Copeia 1940:134. https://doi.org/doi.org/10.1007/s10071-021-01566-5 Tables Table 1 Negative binomial regression of tries until success in Experiment 1. Coefficients for individual snakes are relative to snake 1. Coefficient Estimate Standard Error Z P Intercept 0.408 0.038 10.695 < 0.001 Session -0.003 3.51 x 10 − 4 -8.914 < 0.001 Trial -0.002 0.009 -0.257 0.797 Snake 2 0.037 0.038 0.989 0.323 Snake 3 0.03 0.039 0.851 0.395 Snake 4 -0.023 0.038 -0.592 0.554 Snake 5 -0.031 0.0385 -0.812 0.417 Snake 7 -0.008 0.0390 -0.196 0.845 Snake 8 0.007 0.0381 0.187 0.852 Snake 10 -0.0001 0.0382 -0.003 0.997 Table 2 Negative binomial regression of duration of sessions in Experiment 1. Coefficients for individual snakes are relative to snake 1. The dispersion parameter was estimated to be 0.143, indicating overdispersion. Coefficient Estimate Std.Error Z P Intercept 4.177 0.149 28.030 < 0.001 Session -0.015 0.001 -11.085 < 0.001 Trial -0.048 0.034 -1.410 0.159 Snake 2 0.289 0.147 1.959 0.050 Snake 3 0.073 0.153 0.477 0.633 Snake 4 -0.280 0.150 -1.870 0.062 Snake 5 -0.130 0.149 -0.873 0.383 Snake 7 -0.275 0.152 -1.815 0.070 Snake 8 -0.153 0.148 -1.033 0.302 Snake 10 -0.195 0.149 -1.309 0.191 Table 3 Negative binomial regression of tries until success in Experiment 2. Coefficients for individual snakes are relative to snake 11. Term Estimate Standard Error Z P Intercept 0.528 0.074 7.158 < 0.001 Session -0.001 0.001 -1.254 0.210 Trial -0.011 0.023 -0.504 0.614 Snake 12 -0.032 0.070 -0.455 0.649 Snake 13 0.042 0.074 0.576 0.564 Snake 14 0.161 0.069 2.323 0.020 Snake 15 0.231 0.068 3.377 < 0.001 Snake 17 0.084 0.069 1.226 0.221 Snake 18 0.254 0.068 3.749 < 0.001 Additional Declarations No competing interests reported. Supplementary Files Greenetalcornsnakesdata.xlsx S1.png Figure S1. Comparison of observed distributions of errors across trials for each cohort with distributions generated by sampling from binomial distributions with the same error rate. Cohort 1 underwent more trials than cohort 2 because their training lasted longer and included eight snakes while cohort 2 had seven. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 15 Apr, 2026 Reviews received at journal 15 Apr, 2026 Reviews received at journal 13 Apr, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers invited by journal 09 Mar, 2026 Editor assigned by journal 09 Mar, 2026 Submission checks completed at journal 09 Mar, 2026 First submitted to journal 08 Mar, 2026 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. 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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-9066746","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":603376722,"identity":"e0293324-41e2-43f0-bc3b-3b1f06667349","order_by":0,"name":"Adam Green","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Adam","middleName":"","lastName":"Green","suffix":""},{"id":603376723,"identity":"d4c2a0eb-00a8-40f6-a1a5-c3e190433516","order_by":1,"name":"Liam Andersen","email":"","orcid":"","institution":"Wake Forest University","correspondingAuthor":false,"prefix":"","firstName":"Liam","middleName":"","lastName":"Andersen","suffix":""},{"id":603376724,"identity":"b615dc08-f63d-4381-84d3-ae083236044c","order_by":2,"name":"Anna L Berenguer","email":"","orcid":"","institution":"Wake Forest University","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"L","lastName":"Berenguer","suffix":""},{"id":603376725,"identity":"6a0d5d2f-a9a6-43a4-966b-fa9c8b8fdf00","order_by":3,"name":"Clifford Zeyl","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYHACxgMMDDYM7A1AJg+xeoBa0hh4DpCo5TAJWuTbewwO/Gw7n9gjkcD44G0bEVoYe84YHOxtuw3Swmw4lxgtzBI5BocZt93O3S+RwCbNS4wWNvk3IC3ncoG2sP8mSguPBA9IywGQFjZmorRI8KQVHOz9l1zfw/OwWXLOOSK0yLcf3vjgxxk7Yx725IMf3pQRoYWBgcMAymBsIEo9ELA/IFblKBgFo2AUjFQAAFRLN6AXwppVAAAAAElFTkSuQmCC","orcid":"","institution":"Wake Forest University","correspondingAuthor":true,"prefix":"","firstName":"Clifford","middleName":"","lastName":"Zeyl","suffix":""}],"badges":[],"createdAt":"2026-03-08 22:23:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9066746/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9066746/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104518890,"identity":"d5c94ca2-ff3d-43fe-a90c-a79860a1dd12","added_by":"auto","created_at":"2026-03-12 18:39:59","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":67596,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic drawing of the training and testing arena (not to scale). Visual cues shown above the tunnels were displayed inside the arena above the entrances to the tunnels.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9066746/v1/f2dcd67ad7c26b0a9a1bdd90.jpg"},{"id":104518886,"identity":"ea7e1b7e-c1c4-4db0-bdf0-dec5840f24da","added_by":"auto","created_at":"2026-03-12 18:39:58","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":40084,"visible":true,"origin":"","legend":"\u003cp\u003eLoess curve fitted to error rates of cohort 1 snakes in Experiment 1 using function geom_smooth in package ggplot2 in R, with “span” set to 0.3. The vertical lines indicate the time of the first reversal after 42 sessions followed by the switch from odor cues to visual cues after 72 sessions.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9066746/v1/b5c2a2c966034a1a0f868db3.jpg"},{"id":104518874,"identity":"901083ba-fbc2-4565-aa70-687a36cd9d3f","added_by":"auto","created_at":"2026-03-12 18:39:46","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":133447,"visible":true,"origin":"","legend":"\u003cp\u003eLoess curves fitted to error rates of individual snakes in Experiment 1. Vertical gray lines indicate timing of reversals during the odor-cue stage of the experiment, vertical purple line represents the switch to visual cues, and vertical orange lines indicate reversals of visual cues, for a) snake 1, b) snake 2, c) snake 3, d) snake 4, e) snake 5, f) snake 7, g) snake 8 and h) snake 10. Dots represent observed error counts.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9066746/v1/8e852192165187c2ef53ca21.jpg"},{"id":104518934,"identity":"87994ef9-ac67-4877-93d0-a6f3ae7d2abd","added_by":"auto","created_at":"2026-03-12 18:40:02","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":47742,"visible":true,"origin":"","legend":"\u003cp\u003eSnakes required progressively fewer trials to adjust to successive reversals after the first one. Each graduation was immediately followed by another reversal. Timing of reversals varied among snakes because of varying times to graduation so neither reversals nor subsequent graduations were synchronized.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9066746/v1/cb40c340af026502ccde60c1.jpg"},{"id":104518885,"identity":"b61503b1-c74e-4e32-a9a3-a0e96611a3f0","added_by":"auto","created_at":"2026-03-12 18:39:58","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":35017,"visible":true,"origin":"","legend":"\u003cp\u003eLatencies to correct choice in Experiment 1. The blue line is a Loess fit through data pooled across cohort 1 snakes. Vertical lines represent the first reversal in session \u003cstrong\u003eX\u003c/strong\u003e and the switch from olfactory to visual cues in session \u003cstrong\u003eY\u003c/strong\u003e. The grey bands represent the 95% confidence interval.\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9066746/v1/835a49efdb2b9c05bcecdbac.jpg"},{"id":104518871,"identity":"860b7a9a-88ff-4c51-898d-d693e7c1dd3b","added_by":"auto","created_at":"2026-03-12 18:39:45","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":29568,"visible":true,"origin":"","legend":"\u003cp\u003eError rates in Experiment 2.\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9066746/v1/e92b635445cea6e0c463979a.jpg"},{"id":104518891,"identity":"d451d7cf-95cb-46fc-9219-025dd9b08f64","added_by":"auto","created_at":"2026-03-12 18:39:59","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":33898,"visible":true,"origin":"","legend":"\u003cp\u003eEmpirical cumulative distribution functions of graduation in Experiment 1 (green) and Experiment 2 (blue).\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9066746/v1/a4d1c72aedef8ae945326af3.jpg"},{"id":104518953,"identity":"e6ff1106-9c99-4eac-b517-426d09238d22","added_by":"auto","created_at":"2026-03-12 18:40:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":953573,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9066746/v1/eff68bb4-0f1d-4b2a-bec5-063e693b5d9e.pdf"},{"id":104518888,"identity":"3b6ea211-ae86-4e92-af05-a837f673c89f","added_by":"auto","created_at":"2026-03-12 18:39:59","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":618606,"visible":true,"origin":"","legend":"","description":"","filename":"Greenetalcornsnakesdata.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9066746/v1/6042500452574ad29968b773.xlsx"},{"id":104518870,"identity":"ef80caa0-e547-4600-a428-d588a2f02f2f","added_by":"auto","created_at":"2026-03-12 18:39:45","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":44105,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S1. Comparison of observed distributions of errors across trials for each cohort with distributions generated by sampling from binomial distributions with the same error rate. Cohort 1 underwent more trials than cohort 2 because their training lasted longer and included eight snakes while cohort 2 had seven.\u003c/p\u003e","description":"","filename":"S1.png","url":"https://assets-eu.researchsquare.com/files/rs-9066746/v1/f6e47f5c7bbb6e4bd1c376fd.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Responses to operant conditioning in the corn snake, Pantherophis guttatus, using olfactory and visual stimuli","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMost of what is known about learning in animals comes from work on a small number of model species. But historically neglected vertebrate groups, in particular fish and reptiles, are beginning to receive more attention, challenging the view that they have little potential for learning. This view may have become established in part because their brains are smaller relative to their body size than those of endothermic vertebrates, and lack a cortex. Yet several studies have revealed quite sophisticated cognitive abilities in fish, including transitive inference in a cichlid (Grosenick et al. 2007) and self-awareness in cleaner wrasse (Kohda et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), despite the latter apparently lacking working memory (Bonin et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSnakes are still among the most neglected taxa in studies of animal cognition, with a few pioneering exceptions. Burkhardt (2013) focused on reptile learning and behavior for decades, providing evidence that their capabilities had been widely underestimated. However, the ecology and physiology of snakes are unique (Title et al. 2024). Snakes tend to alternate between large meals and periods of fasting that can last for days, weeks or months, which may have selected for different learning abilities than the relentless need for more frequent smaller meals experienced by endotherms. These eating habits are also potentially problematic in operant conditioning experiments, which rely on regular sessions of repeated reinforcement with small quantities of food, although Burmese pythons (\u003cem\u003ePython bivittatus\u003c/em\u003e) have proven willing to accept very small food items as reinforcement, enabling Emer et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) to train them to press a button for food when illuminated. This is all the more remarkable given that snakes are believed to rely more on olfaction than on vision when hunting. The general consensus is that they have fairly poor eyesight and are dichromatic, with their cones only reacting to blue and green wavelengths (Sim\u0026otilde;es et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Da Silva et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and relatively few studies have applied conditioning to snakes using visual cues.\u003c/p\u003e \u003cp\u003eEliciting unnatural behavior such as pushing an illuminated button demonstrates a degree of behavioral flexibility that may be unexpected in the case of snakes, and their response to conditioning can be quite sensitive to the details of stimuli and type of reinforcement. Kellogg \u0026amp; Pomeroy (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1936\u003c/span\u003e) used cold water as an aversive stimulus and warm water (10\u0026deg; and 32\u0026deg; respectively) as positive reinforcement and observed declines in both latency and error rates in 12 banded watersnakes in a maze (\u003cem\u003eNerodia fasciata\u003c/em\u003e), but Wolfle \u0026amp; Browne (1940) saw no evidence of learning in 11 diamondback watersnakes (\u003cem\u003eN. rhombifer\u003c/em\u003e) using escape from hot water (48\u0026ndash;55\u0026deg;) or from a mild electric shock as reinforcement. Williams et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) used positive reinforcement and shaping to train false water cobras (\u003cem\u003eHydrodynastes gigas\u003c/em\u003e) to follow a target into a shift container, and corn snakes can use visual cues to navigate in an arena to a hiding spot (Holtzmann et al 1999). In an early study, Takemasa and Nakamura (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1935\u003c/span\u003e, cited by Kleinginna, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1970\u003c/span\u003e) trained snakes to escape from a box, although a greater challenge might have been training them not to escape, as most snakes are from birth highly skilled at escaping. Crawford \u0026amp; Bartlett (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1966\u003c/span\u003e) commented that \u0026ldquo;snakes have a well-earned reputation for being refractory.\u0026rdquo;\u003c/p\u003e \u003cp\u003eBut the same qualities that have made corn snakes, \u003cem\u003ePantherophis guttatus\u003c/em\u003e, popular pets by reptilian standards also make them well suited to research on animal learning. They can implement different hunting strategies in different environmental settings (DeGregorio et al. 2016). They are abundant and relatively inexpensive due to widespread captive breeding, calm and docile by nature, and flourish on a diet of frozen-thawed mice. Even adults willingly accept a series of 1\u0026ndash;4 day-old mice or \u0026ldquo;pinkies\u0026rdquo; as reinforcement in lieu of an adult mouse. Here we characterize their responses to operant conditioning, and describe experimental and biological factors that contribute to variation among individuals. We began with odor cues. After successful conditioning of eight adult snakes using odor cues we imposed a series of cue reversals by switching which cue was reinforced, to assess their behavioral flexibility. We then changed to visual cues, followed by more reversals once the snakes had achieved criterion once again. We then compared the responses of the adults to a separate cohort of seven subadult corn snakes.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eWe began with an operant conditioning experiment on eight corn snakes which were just over two years old at the start of the experiment, three males and five females. The snakes were purchased online as hatchlings a few weeks old from VMSHerps in October 2019. Since then they have been singly housed in homemade 80 cm x 60 cm x 50 cm enclosures made of wood, painted glossy black for ease of cleaning, with a 40 cm by 56 cm acrylic window 0.32 cm thick in a vertically sliding door. A Pro Products (Mahopac, NY) heat panel is mounted on the roof of each enclosure in the back right corner to create a temperature gradient, enabling the snakes to thermoregulate. The heat panels are regulated by thermostats (Vivarium Electronics model VE-200D) set for 27\u0026deg;. The enclosures are located in a windowless room and are illuminated by a 60 cm fluorescent light on a timer set to a daily 12h light:12h dark cycle. Their substrate is a mix of cypress and aspen mulch. In September of 2021 another eight snakes were purchased from VMSHerps (which has since gone out of business) and housed singly in enclosures the same as those described above. The older and younger cohorts are henceforth referred to as cohorts 1 and 2 respectively. Cohort 1 are snakes 1, 2, 3, 4, 5, 7, 8 and 10, and cohort 2 are 11 through 18.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eConditioning Experiments\u003c/h2\u003e \u003cp\u003eTwo operant conditioning experiments were performed, both of them in the same arena and differing in which cohort was involved and in the cues that were used. The arena was a wooden oval 13.5\u0026rdquo; x 30 cm x 20 cm, with a tunnel 5.7 cm in diameter and 16 cm long on each side, made of clear acrylic so as not to confound the motivating effect of food by offering them an additional reward in the form of a hiding place, and so that the experimenter could see when a snake had finished swallowing (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). During training sessions the arena floor was covered by bench paper, which was replaced between sessions. The arena was placed in an unoccupied snake enclosure in the same room where the snakes were housed, with a Nexigo web cam on the roof of the arena. All sessions were video-recorded.\u003c/p\u003e \u003cp\u003eCohort 1 was trained from September 2021 through November 2022, first on scent cues for 72 sessions, and then for 24 sessions on visual cues: a green 2 cm x 2 cm square and a blue circle 2 cm in diameter, both framed by a 2 cm white border, printed from a laptop and laminated. Experiment 2 trained cohort 2 on those same visual cues for 50 sessions. Experiment 1 began in September 2021, after an acclimation period that was unexpectedly prolonged by a ban on indoor research activities during the COVID-19 pandemic. When the restrictions were lifted, each snake was given a habituation period during which it was allowed to freely roam the arena to familiarize itself with the layout of the arena. To encourage exploration and get them accustomed to feeding in the tunnels, a frozen-thawed pinky was placed in each tunnel so the snakes were rewarded for exploration regardless of which tunnel they chose. Each snake was removed from the arena after consuming one pinky\u003c/p\u003e \u003cp\u003eThe scent cues used to begin Experiment 1 were essential oils of lavender and lemon, chosen to be distinctive and novel but innocuous. Preliminary experiments showed that the snakes had no initial preference for either scent. The odors were presented as 6 ul of essential oil pipetted onto 2 cm squares of filter paper which were taped above the tunnel entrances. To begin the experiment, the cues to be reinforced were assigned randomly to the eight snakes using an R script. Each training session consisted of four consecutive trials for each snake. Any snakes that were \u0026ldquo;opaque\u0026rdquo;, or about to shed, as evidenced by cloudy eyes, dull colors, and diminished appetites, were excluded from training sessions until after they had shed. In each session, we randomized the order in which the snakes were tested, and for each of a snake\u0026rsquo;s trials, whether the reinforced cue was presented above the right or left tunnel, again using R. The criterion for acquisition, or \u0026lsquo;graduation\u0026rsquo;, was a snake choosing correctly in at least 7 of any 8 consecutive trials, an established threshold in reptile learning experiments (e.g. Riley et al \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Szabo et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Szabo et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Szabo et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Following successful acquisition by the entire cohort, the olfactory cues were reversed for all snakes after 42 sessions, meaning that the reinforced and non-reinforced cues were switched. The timings of subsequent reversals varied among snakes according to when they graduated from the preceding reversal. There were three reversals of olfactory cues, followed by the switch to visual cues on the 72nd session, and then three reversals of visual cues.\u003c/p\u003e \u003cp\u003eIn Experiment 2 we applied operant conditioning for 58 sessions of three trials, each using the same visual cues as in the latter portion of Experiment 1, to a second cohort of snakes, two years old at the start of the experiment, from October 2023 until November 2024. All 7 snakes in cohort 2 began with a habituation period as in Experiment 1.\u003c/p\u003e \u003cp\u003eSnake 16 ceased to cooperate partway through the conditioning experiment and is excluded from all analyses.\u003c/p\u003e \u003cp\u003eTo conduct a single operant conditioning session, snakes were randomly ordered for testing, and the placement of the assigned visual cue by the entrance of either the left or right tunnel was randomly assigned for each trial in the session using an R script. The alternate cue was placed at the entrance of the opposite tunnel from the reinforced cue. Snakes were then placed at the entrance of the arena, where movement decisions were timed and recorded. For cohort 2, reinforcement during each trial was half a pinky rather than an entire one, so that these smaller snakes would not be satiated after the first trial or two. Half a pinky was placed in the correct tunnel prior to the start of each trial, and each individual trial ran until the snake had selected the correct tunnel and consumed the half pinky. As in Experiment 1, snakes that were \u0026ldquo;opaque\u0026rdquo; were excluded from training until after they had shed.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnalysis\u003c/h3\u003e\n\u003cp\u003eCount data may be modeled with Poisson or negative-binomial regression. Poisson models assume that means and variances are equal, while count data are frequently characterized by overdispersion, or a variance greater than the mean. In both experiments, numbers of trials until success showed the expected overdispersion, with ratios of variance to mean of 2.36/1.11 in Experiment 1 and 5.09/2.43 in Experiment 2. The negative binomial distribution has an additional parameter to accommodate overdispersion and accounts for the fact that every trial ended with the first correct choice. We applied negative binomial regression both to numbers of errors and to latencies to correct decisions. Estimates of coefficients were very similar to those obtained from Poisson regressions, but the negative binomial models consistently yielded much lower AICs and estimates of the inverse dispersion parameter were below 0.2, confirming overdispersion. We used the glm function in R to fit the negative binomial regression model\u003c/p\u003e \u003cp\u003eTrials Until Success\u0026thinsp;~\u0026thinsp;β\u003csub\u003esession\u003c/sub\u003e \u0026middot;Session\u0026thinsp;+\u0026thinsp;β\u003csub\u003etrial\u003c/sub\u003e \u0026middot;Trial\u0026thinsp;+\u0026thinsp;β\u003csub\u003esnake\u003c/sub\u003e \u0026middot;Factor(Snake)\u003c/p\u003e \u003cp\u003eusing RStudio version 2025.09.2 with R 4.5.0.\u003c/p\u003e \u003cp\u003eThe repeated-measures aspect of the experimental design proved problematic. The assumption that each data point is independent of the others is violated by the fact that each snake contributed observations at many time points. This is addressed by modeling snake identity as a random factor nested within session number, but such models, run with two different R packages (MASS and glmmTNB), were plagued by singularities and failures to converge, which can result from strong collinearity between predictors or from a lack of variation among subjects. Other studies of reptile behavior have reported similar issues (e.g. Skinner et al. 2024). In our case a dearth of variation among individuals is the most likely cause. We therefore present results from models lacking a nested term. We also tested for effects of shed cycles on error rates and latencies, and for correlations between overall numbers of sheds and rates of learning.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe first present results for Experiment 1 and then compare them with the outcome of Experiment 2. We analyze both counts of errors per training session, and numbers of attempts taken to make the first correct choice, noting that every trial ended on the first success. Mean error rates declined significantly over the course of Experiment 1 (Fig.\u0026nbsp;2). We detected no variation among snakes in the rate of that decline, nor across the trials within each session (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Two features of the experiment interrupted the overall trend. First, in the 42nd training session we applied the first of several reversals to all eight snakes simultaneously. Those that had been rewarded for choosing the tunnel marked by essential oil of lavender now had the scent of lemon reinforced, and vice versa. Second, starting with the 73rd session we replaced the odor cues with visual ones (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As expected, both changes were followed by temporary increases in error rates (Fig.\u0026nbsp;2). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the response of each snake to those two disruptions and to reversals that were applied individually when a snake reached the criterion for acquisition again. Error rates increased in most snakes when odor cues were reversed, but they responded increasingly quickly to subsequent reversals (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure 2. Loess curve fitted to error rates of cohort 1 snakes in Experiment 1 using function geom_smooth in package ggplot2 in R, with \u0026ldquo;span\u0026rdquo; set to 0.3. The vertical lines indicate the time of the first reversal after 42 sessions followed by the switch from odor cues to visual cues after 72 sessions.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Loess curves fitted to error rates of individual snakes in Experiment 1. Vertical gray lines indicate timing of reversals during the odor-cue stage of the experiment, vertical purple line represents the switch to visual cues, and vertical orange lines indicate reversals of visual cues, for a) snake 1, b) snake 2, c) snake 3, d) snake 4, e) snake 5, f) snake 7, g) snake 8 and h) snake 10. Dots represent observed error counts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnother possible response to conditioning is a decreasing latency to correct decisions as the cues become increasingly familiar. Alternatively, a longer latency could reflect more careful decision-making, resulting in longer sessions and fewer errors. Sessions were shorter at the end of Experiment 1 than at the beginning (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e), and negative binomial regression showed a significant negative effect of session number on session duration (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Session duration (the cumulative length of the trials in a session) was positively correlated with numbers of errors (Spearman rank correlation, ρ\u0026thinsp;=\u0026thinsp;0.118, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.97x10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e). Since every trial ended with the first correct choice, more errors may have prolonged trials simply by delaying that success.\u003c/p\u003e \u003cp\u003eIn Experiment 2, cohort 2 as a whole showed no significant overall decline in numbers of attempts before success (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) even though 6 of the 7 snakes did reach criterion at some point. In contrast to experiment 1, in experiment 2 the duration of sessions did not decline over time.\u003c/p\u003e \u003cp\u003eWith all seven snakes from Experiment 2, we then asked whether it was the shapes of the cues (green square or blue circle) or their colors that they most attended to, using green circle and blue square cues. We tested each snake twice, reasoning that additional testing might have inhibited their conditioned responses. The correct color was chosen over the correct shape 12 times out of 14 trials. While suggestive, this is not significantly different from the null expectation of 7 out of 14 (Fisher\u0026rsquo;s Exact test, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.103).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e compares the cumulative distributions of times to first acquisition in the two experiments. They show similar dynamics even though the response to conditioning was clearly greater in cohort 1 (Figs.\u0026nbsp;2 and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) than in cohort 2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e). To see whether the cohorts differed in the distribution of errors across trials, for each snake we drew from a binomial distribution 1000 random samples of a size equal to the number of choices that snake made during conditioning, using an error rate equal to that snake\u0026rsquo;s error rate averaged across the entire conditioning experiment. The observed distributions of errors over trials do not fit Poisson distributions for either cohort (chi-squared goodness of fit tests, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 in both cases) because of a relative lack of one and two-error trials and an excess of error-free trials. While this doesn\u0026rsquo;t fully explain the contrasting timing of graduations in the two cohorts, it does suggest that wrong choices were not randomly distributed across trials, but instead tended to occur in clusters.\u003c/p\u003e \u003cp\u003eWe tested for a relationship between growth rates and rates of decline in error rates, reasoning that for an ectotherm, both growth rates and the response to conditioning would integrate multiple metabolic processes, so that faster-growing snakes might learn more quickly or more consistently. Linear regression on growth rates and negative binomial regression on trials until success were performed on the two cohorts combined. A Spearman\u0026rsquo;s rank correlation test confirmed a significant positive relationship between coefficients of growth-rate and trials until success (ρ\u0026thinsp;=\u0026thinsp;0.657, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013). We also compared error rates in sessions that were preceded or followed within one week by a shed with error rates in other sessions, and found no difference. Numbers of trials until first graduation in cohort were positively correlated with total numbers of sheds during the conditioning experiment in cohort 1 (Spearman rho\u0026thinsp;=\u0026thinsp;0.719, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.045), but not in cohort 2 (Spearman rho = -0.086, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.919).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMature corn snakes responded to operant conditioning using both olfactory and visual stimuli, all but one of eight reaching the criterion of choosing the reinforced cue in at least seven of any eight consecutive trials, and showing increasingly rapid reversal learning. Among a cohort of seven juveniles all but one reached criterion at some point, but without a detectable overall decline in error rates (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and with more variation among individuals (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), even though the same visual cues, reinforcement and apparatus were used in both conditioning experiments. Reversal learning was not attempted with cohort 2 because without unambiguous declines in error rates it would have been unclear how to interpret the results. Cohort 2 was purchased from the same breeder at the same age (~\u0026thinsp;2 months after hatching), and was then housed and fed in the same way as cohort 1 with the goal of minimizing effects on learning other than the two-year age difference. However, experiment 1 was performed entirely by one lab member (AG) and experiment 2 by two lab members (LA and AB) and we cannot rule out the possibility that the snakes were influenced by subtle differences in how they were handled. Snakes may learn more quickly when handled by only one person than when two lab members collaborate. Pending a direct experimental test, this is only anecdotal, although in their account of training banded watersnakes to find warmer water, Kellogg \u0026amp; Pomeroy (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1936\u003c/span\u003e) noted that the same person handled all 12 snakes throughout a habituation period as well as the entire conditioning experiment, suggesting that they anticipated a handler effect. If that effect holds up to a direct experimental test, it would indicate a degree of sensitivity to human handling that would not be widely expected of a reptile.\u003c/p\u003e \u003cp\u003eThe switch from olfactory to visual cues in experiment 1 introduced the risk that snakes might then be able to smell the pinky in the reinforced tunnel before choosing which tunnel to enter. To test for this possibility, at the end of the experiment we ran additional sessions with no mouse in either tunnel; instead the snake was given a mouse with forceps after making the correct choice. We observed no change in their low error rates, and conclude that mouse odor was not a confounding factor during the experiment.\u003c/p\u003e \u003cp\u003eIn another difference between conditioning in cohorts 1 and 2, no variation among individuals was detected in the former (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), while four cohort 2 snakes (14, 15, 16 and 18; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) did significantly worse than the others. If there is an ontogenic component to aptitude for learning in corn snakes, greater variability in the younger cohort may reflect timing variation in the maturation of those learning abilities. Cohort 2 made errors at almost twice the rate of cohort 1 (0.432 errors per decision vs 0.229), but on average took slightly fewer trials to reach criterion than cohort 1 (35.9 vs 42.5 trials). Comparing the observed frequencies of error-free trials by each cohort with the frequencies obtained in random samples from binomial distributions with the observed error rates shows that the zero-error class of trials was over-represented in both cohorts, with a 6.2% excess in cohort 1 (2134 observed vs 2009 randomized) and a 16.8% excess in cohort 2 (563 observed vs. 482 randomized; Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Both cohorts also had fewer than expected trials with one error. Rather than occurring randomly, errors tended to cluster slightly in trials of 3 and 4 errors, inflating the frequencies of error-free trials and enabling earlier graduations than would have occurred with randomly distributed errors.\u003c/p\u003e \u003cp\u003eAfter the completion of each experiment we tested the snakes\u0026rsquo; memories at 3-month intervals using the last set of cues they had been trained on. Cohort 1 made correct choices on 95% of trials up to six months after that conditioning had stopped, after which their performance drifted towards randomness. Cohort 2, two years younger, made choices that were already indistinguishable from random 3 months after their conditioning ended, implying better long-term memory in the adult snakes.\u003c/p\u003e \u003cp\u003ePerhaps our most striking result was the speed of reversal learning by cohort 1. Reversal learning requires the cognitive abilities to inhibit a learned response and to switch their attention to a previously irrelevant cue. Birch et al (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) consider reversal learning to be a behavioral signature of a flexible \u0026ldquo;value system\u0026rdquo;, one of the eight features that they propose are hallmarks of the origin of biological consciousness. Unusually, cohort 1 required substantially fewer sessions to reach criterion again after each reversal than they did the first time: times to first graduation in Experiment 1 averaged 14.6 sessions, followed by 8.1, 2.4 and 1.2 sessions after three reversals respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e), indicating that they had become aware that the rules of reinforcement could change, and responded more quickly to each reversal by switching their choices accordingly. This study joins several descriptions in the past few years of snakes demonstrating unexpected social behavior and behavioral plasticity (Skinner et al \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003eb\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003ec\u003c/span\u003e), suggesting the potential for greater behavioral flexibility than they have historically been credited with.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest:\u003c/h2\u003e \u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthical Approval:\u003c/h2\u003e \u003cp\u003e All husbandry and experimental procedures performed with snakes were performed in compliance with Wake Forest University Institutional Animal Care and Use Committee protocol A23-060.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported in part by Wake Forest University graduate and undergraduate research funds.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: A.G. and C.Z, formal analysis: C.Z., A.G., L.A. and A.B., original draft: A.G, L.A., A.B. and C.Z., review and editing: C.Z., L.A., A.G. and A.B. All authors have seen and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis work was supported in part by Wake Forest University Department of Biology graduate and undergraduate research funds.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study will be available as a Supplementary Information file.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBirch J, Ginsburg S, Jablonka E (2020) Unlimited Associative Learning and the origins of consciousness: a primer and some predictions. Biol Philos 35:56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10539-020-09772-0\u003c/span\u003e\u003cspan address=\"10.1007/s10539-020-09772-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonin L, Manrique HM, Bshary R (2025) Cleaner wrasse failed in early testing stages of both visual and spatial working memory paradigms. Anim Cogn 28:43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10071-025-01959-w\u003c/span\u003e\u003cspan address=\"10.1007/s10071-025-01959-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurghardt G (2013) Environmental enrichment and cognitive complexity in reptiles and amphibians: Concepts, review, and implications for captive populations. Appl Anim Behav Sci 147:286\u0026ndash;298. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eHttps://doi.org/10.1016/j.applanim.2013.04.013\u003c/span\u003e\u003cspan address=\"Https://10.1016/j.applanim.2013.04.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrawford FT, Bartlett C (1966) Runway behavior of the gray rat snake with food and water reinforcement. Psychonomic Sci 4:99\u0026ndash;100. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3758/BF03342197\u003c/span\u003e\u003cspan address=\"10.3758/BF03342197\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDa Silva MO, Gade JT, Damsgaard C et al (2020) Morphology and evolution of the snake cornea. J Morphol 281:240\u0026ndash;249. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jmor.21094\u003c/span\u003e\u003cspan address=\"10.1002/jmor.21094\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDegregorio B (2016) Ecology and predation behavior of corn snakes (\u003cem\u003ePantherophis guttatus\u003c/em\u003e) on avian nests. Herpetological Conserv Biology 11:150\u0026ndash;159\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEmer SA, Mora CV, Harvey MT, Grace MS (2015) Predators in training: operant conditioning of novel behavior in wild Burmese pythons (\u003cem\u003ePython molurus bivitattus\u003c/em\u003e). Anim Cogn 18:269\u0026ndash;278. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10071-014-0797-1\u003c/span\u003e\u003cspan address=\"10.1007/s10071-014-0797-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoltzman DA, Harris TW, Aranguren G, Bostock E (1999) Spatial learning of an escape task by young corn snakes, \u003cem\u003eElaphe guttata guttata\u003c/em\u003e. Anim Behav 57:51\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1006/anbe.1998.0971\u003c/span\u003e\u003cspan address=\"10.1006/anbe.1998.0971\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKellogg WN, Pomeroy WB (1936) Maze learning in water snakes. J Comp Psychol 21:275\u0026ndash;295. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/h0063023\u003c/span\u003e\u003cspan address=\"10.1037/h0063023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKleinginna PR Jr. (1970) Operant conditioning in the indigo snake. Psychon Sci 18:53\u0026ndash;55. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3758/BF03332330\u003c/span\u003e\u003cspan address=\"10.3758/BF03332330\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKohda M, Bshary R, Kubo N et al (2023) Cleaner fish recognize self in a mirror via self-face recognition like humans. Proc Natl Acad Sci USA 120:e2208420120. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.2208420120\u003c/span\u003e\u003cspan address=\"10.1073/pnas.2208420120\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRiley JL, K\u0026uuml;chler A, Damasio T et al (2018) Learning ability is unaffected by isolation rearing in a family-living lizard. Behav Ecol Sociobiol 72:20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00265-017-2435-9\u003c/span\u003e\u003cspan address=\"10.1007/s00265-017-2435-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSim\u0026otilde;es BF, Sampaio FL, Douglas RH et al (2016) Visual pigments, ocular filters and the evolution of snake vision. Mol Biol Evol 33:2483\u0026ndash;2495. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/molbev/msw148\u003c/span\u003e\u003cspan address=\"10.1093/molbev/msw148\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkinner M, Nagabaskaran G, Gantert T, Miller N (2024a) Bolder together: conformity drives behavioral plasticity in eastern gartersnakes. Anim Cogn 27:2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10071-024-01859-5\u003c/span\u003e\u003cspan address=\"10.1007/s10071-024-01859-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkinner M, Hazell M, Jameson J, Lougheed SC (2024b) Social networks reveal sex- and age-patterned social structure in Butler\u0026rsquo;s gartersnakes (\u003cem\u003eThamnophis butleri\u003c/em\u003e). Behav Ecol 35:1\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/beheco/arad095\u003c/span\u003e\u003cspan address=\"10.1093/beheco/arad095\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkinner M, \u0026middot; Kumpan T, Miller N (2024c) Intense sociability in a non-social snake (\u003cem\u003ePython regius\u003c/em\u003e). Behav Ecol Sociobiol 78:113. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00265-024-03535-7\u003c/span\u003e\u003cspan address=\"10.1007/s00265-024-03535-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzabo B (2019) Context-specific response inhibition and differential impact of a learning bias in a lizard. Anim Cogn 22:317. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10071-019-01245-6\u003c/span\u003e\u003cspan address=\"10.1007/s10071-019-01245-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzabo B, Noble DWA, Byrne RW et al (2018) Subproblem learning and reversal of a multidimensional visual cue in a lizard: evidence for behavioural flexibility? Anim Behav 144:17\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.anbehav.2018.07.018\u003c/span\u003e\u003cspan address=\"10.1016/j.anbehav.2018.07.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzabo B, Noble DWA, Byrne RW et al (2019) Precocial juvenile lizards show adult level learning and behavioural flexibility. Anim Behav 154:75\u0026ndash;84. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.anbehav.2019.06.003\u003c/span\u003e\u003cspan address=\"10.1016/j.anbehav.2019.06.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzabo B, Noble DWA, Whiting MJ (2021) Learning simple and compound stimuli in a social lizard (\u003cem\u003eEgernia stokesii\u003c/em\u003e). J Comp Psychol 135:208\u0026ndash;218. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/com0000260\u003c/span\u003e\u003cspan address=\"10.1037/com0000260\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakemasa T, Nakamura K (1935) Hebi mochieto hitotsumo gakushi iikken (A learning experiment with snakes). Kyotku Shinn Kerkvu 10:575\u0026ndash;581\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTitle P (2024) The macroevolutionary singularity of snakes. Science 383:918\u0026ndash;923. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1126/science.adh2\u003c/span\u003e\u003cspan address=\"10.1126/science.adh2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilliams ML, Torrini LA, Nolan EJ, Loughman ZJ (2022) Using Classical and Operant Conditioning to Train a Shifting Behavior in Juvenile False Water Cobras (\u003cem\u003eHydrodynastes gigas\u003c/em\u003e). Animals 12:1229. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ani12101229\u003c/span\u003e\u003cspan address=\"10.3390/ani12101229\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolfle D, Brown C (1940) A Learning Experiment with Snakes. Copeia 1940:134. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/doi.org/10.1007/s10071-021-01566-5\u003c/span\u003e\u003cspan address=\"10.1007/s10071-021-01566-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNegative binomial regression of tries until success in Experiment 1. Coefficients for individual snakes are relative to snake 1.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.51 x 10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-8.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.554\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.845\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNegative binomial regression of duration of sessions in Experiment 1. Coefficients for individual snakes are relative to snake 1. The dispersion parameter was estimated to be 0.143, indicating overdispersion.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd.Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-11.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNegative binomial regression of tries until success in Experiment 2. Coefficients for individual snakes are relative to snake 11.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTerm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnake 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"animal-cognition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anco","sideBox":"Learn more about [Animal Cognition](http://link.springer.com/journal/10071)","snPcode":"10071","submissionUrl":"https://submission.nature.com/new-submission/10071/3","title":"Animal Cognition","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Operant conditioning, corn snakes, reversal learning, olfactory and visual cues","lastPublishedDoi":"10.21203/rs.3.rs-9066746/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9066746/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSnakes are historically underrepresented in experimental studies of learning. Operant conditioning reinforced by food rewards has successfully been applied to a few species, and corn snakes have learned to use visual cues to locate a hiding spot, but despite the growing popularity of snakes as pets, their capacity for learning is largely unexplored. We used reinforcement with food rewards to train two cohorts of corn snakes (\u003cem\u003ePantherophis guttatus\u003c/em\u003e, 15 snakes in total), on olfactory and visual cues in two separate experiments. We applied a criterion for acquisition of at least 7 correct decisions in any 8 consecutive trials, and for the first cohort tested for reversal learning of olfactory and then visual cues once the criterion was met. Error rates and latencies to correct choices declined significantly in cohort 1, a group of eight three-year-old snakes. The response of a second cohort of seven three-year-olds was more subtle: all but one reached criteria, but with no overall decline in error rates. When subjected to repeated reversals, in which the identity of the reinforced cue was switched, cohort 1 responded increasingly quickly to each successive reversal, demonstrating the cognitive abilities to inhibit learned responses and to switch their attention to the previously irrelevant cue. Corn snakes show promise as a representative species for learning in reptiles.\u003c/p\u003e","manuscriptTitle":"Responses to operant conditioning in the corn snake, Pantherophis guttatus, using olfactory and visual stimuli","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-12 18:38:13","doi":"10.21203/rs.3.rs-9066746/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-15T18:06:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-15T16:03:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-13T07:36:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"229407532833732469590233630881785146180","date":"2026-03-20T13:41:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"22235636915688269181228171960253837352","date":"2026-03-20T13:28:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-09T20:14:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-09T20:06:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-09T07:45:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Animal Cognition","date":"2026-03-08T22:18:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"animal-cognition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anco","sideBox":"Learn more about [Animal Cognition](http://link.springer.com/journal/10071)","snPcode":"10071","submissionUrl":"https://submission.nature.com/new-submission/10071/3","title":"Animal Cognition","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"be8c9a49-d3c9-4c04-ac09-63a692c9a2c3","owner":[],"postedDate":"March 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-04-15T18:09:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-12 18:38:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9066746","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9066746","identity":"rs-9066746","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}