Isolating Delay and Reinforcement Rate Effects on Resurgence: A Replication of Jarmolowicz & Lattal (2014)

Isolating Delay and Reinforcement Rate Effects on Resurgence: A Replication of Jarmolowicz & Lattal (2014) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Isolating Delay and Reinforcement Rate Effects on Resurgence: A Replication of Jarmolowicz & Lattal (2014) Carlos J. Flores, Julian C. Velasquez, Everardo E. Durán, A. Sofia Flores, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6613854/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Resurgence of a previously extinguished response often occurs when alternative conditions of reinforcement are worsened. Jarmolowicz and Lattal (2014) showed that delayed alternative reinforcement can cause resurgence, but it’s unclear whether the delay or a decrease in reinforcement rate is responsible. This study aimed to clarify this. The Replication group experienced increasing delays in alternative reinforcement schedules, while the Delay group experienced both increasing delays and richer frequencies of alternative reinforcement, ensuring that the reinforcement rate remained constant across sessions. Results showed more resurgence in the Replication group, suggesting that delay alone is not enough to produce resurgence. Resurgence Alternative reinforcement Delayed reinforcement Frequency of Reinforcement Rats Figures Figure 1 Figure 2 Introduction Resurgence is defined as an increase in suppressed behavior due to the worsening of alternative reinforcement conditions (Lattal et al., 2017). This phenomenon has been widely studied because of its relevance to understanding relapse in applied settings (Wathen & Podlesnik, 2018). Experimentally, resurgence is typically examined using a three-phase procedure: (1) reinforcement of a target behavior, (2) extinction of the target behavior while reinforcing an alternative response, and (3) disruption of alternative reinforcement, often by removing it entirely (Leitenberg et al., 1975; Lieving & Lattal, 2003). Some researchers have also used a four-phase procedure where the target response extinction occurs in an independent phase before the reinforcement of the alternative behavior (Cleland et al., 2001; Hernández et al., 2020; Lieving & Lattal, 2003 Experiment 1). While resurgence has traditionally been induced through extinction in the final phase (e.g. Epstein, 1983; Lieving & Lattal, 2003), research has identified additional ways in which alternative reinforcement can be “worsened” to produce resurgence. These include punishment of the alternative response (Fontes et al., 2018; Redner et al., 2024), reductions in reinforcement magnitude (Browning et al., 2022; Craig et al., 2017; Oliver et al., 2018) or quality (Shahan et al., 2024), local periods of extinction by abruptly or gradually reducing reinforcement rate, changing the schedule of reinforcement or delaying alternative reinforcement (Jarmolowicz & Lattal, 2014; Lieving & Lattal, 2003, Experiment 4; Nighbor et al., 2020; Schepers & Bouton, 2015; Sweeney & Shahan, 2013; Winterbauer & Bouton, 2012; Yensen et al., 2022). For instance, Lieving and Lattal (2003, Experiment 4) examined resurgence when alternative reinforcement transitioned from a variable interval (VI) 30 s to a VI 360 s schedule, thereby increasing inter-reinforcer intervals. Resurgence was observed across all subjects, being higher during longer inter-reinforcement intervals. This was similarly observed under thinning of alternative reinforcement rate (Schepers & Bouton, 2015; Sweeney & Shahan, 2013; Winterbauer & Bouton, 2012). Nighbor et al. (2020, Experiment 1) found resurgence in pigeons when local extinction periods were signaled using a delayed reinforcement schedule. Yensen et al. (2022) observed resurgence with unsignaled local extinction periods by transitioning from a VI to fixed interval (FI) schedules, with the highest response rates during longer FI schedules and extinction. These findings suggest that both signaled and unsignaled extinction periods can act as worsening conditions that induce resurgence. Jarmolowicz and Lattal (2014) proposed that increasing reinforcement delays in alternative conditions should lead to resurgence. Using pigeons as subjects, they found that longer delays produced resurgence of target responding in two of the four subjects. However, a key limitation of their design was that increasing delays not only decreased the response-reinforcer contingency but also reduced overall reinforcement frequency. This reduction in reinforcement rate may have introduced local extinction periods similar to those described in previous studies. The authors acknowledged this confound, noting that some research suggests delayed reinforcement effects can occur independently of changes in reinforcement rate (Jarmolowicz & Lattal, 2013). It is unclear whether resurgence is differentially affected by the combined manipulation of reinforcement delay and rate compared to delay alone. This study aims to (1) replicate Jarmolowicz and Lattal’s (2014) procedure with rats and (2) compare resurgence when delays are introduced without altering reinforcement frequency, isolating the effects of delay from rate changes to clarify conditions for resurgence and refine understanding of how degraded reinforcement contributes to behavioral relapse. Method Subjects 10 six-month old male Wistar rats were used. All rats had the same previous experience (i.e., number of sessions) with variable interval (VI) schedule with water as reinforcer. They had a food deprivation schedule and were maintained at 80% - 85% of their ad libitum weight. Each rat was individually housed in a controlled temperature colony under a 12:12 hr. light/dark cycle with constantaccess to water. The protocol accomplished the animal care guidelines of the institution’s ethical committee. Apparatus Eight Med Associates operant chambers (ENV-008) were used. Each chamber was equipped with a food dispenser (ENV-203 M) centered on the front panel that delivered 45 mg grain-based pellets (Bio Serv), two 4.5 cm long retractable levers (ENV-112CM) with a cue light (ENV-221M) above were placed on both sides of the dispenser at a height of 7 cm of the grid floor. All chambers were enclosed in a sound-attenuating box (ENV-022MD) with external-sound masking fans. Experimental events and data collection were programmed using Med-PC V ® software. Procedure Magazine and response training. The first session began with the illumination of houselight where rats were trained to enter in the magazine and consume pellets using a VT 60 s schedule. Each pellet delivery was accompanied by the offset of houselight for 3 s. Then, experimental sessions began with the introduction of one lever (right or left, according to a .5 probability) and each response was reinforced (CRF). After the delivery of the pellet, the operating lever was retracted and the other lever was inserted in the box, repeating this alternation until the end of the session. Once 30 reinforcers were produced under this arrangement in two consecutive days, the schedule was changed to a VI. The schedule value increased gradually (5, 15, 25) every two sessions, with each value remaining in effect until 30 reinforcers were delivered. Each schedule of reinforcement was derived from a 10-value list without replacement according to a Fleshler and Hoffman's (1962) distribution. All training sessions ended after 60 min or 30 pellet deliveries, whichever occurred first. Sessions were conducted on successive days, always at the same time. Phase 1: Target reinforcement. The 10 rats were randomly assigned to two groups, each comprising five animals . During this phase, one lever was inserted in the box (right or left, counterbalanced), accompanied by the cue light above. Responses to the target lever (TR) produced the delivery of one pellet according to a VI 30 s schedule. Time for consumption was fixed 3 s that were excluded from the total duration of the session. This phase lasted a minimum of 15 sessions and until stable responding was achieved. A relative stability criterion was used (Cumming & Schoenfeld, 1960) . For the six more recent sessions, the difference of the mean response rates of the last three sessions and first three sessions could not be more than +/- 5% of the grand mean. Each session lasted until 30 reinforcers were delivered. Across rats, this phase lasted between 15 and 26 sessions. Phase 2: Target extinction. Responses on the target lever were placed on extinction, with no programmed consequences. This phase continued until target lever responses ceased entirely or until a maximum of 30 sessions was completed. Each session duration matched that of the final session in the previous phase. Across rats, this phase lasted between 16 and 30 sessions. Phase 3: Alternative reinforcement. Sessions began with the insertion of both levers and the illumination of their respective cue light. Responses to the alternative lever (ALT) were reinforced according to a VI 30 s schedule, while responses to the TR remained without programmed consequences. This phase continued until reaching the same stability criteria for target response. Across rats, this phase lasted between 17 and 27 sessions. Phase 4: Delayed reinforcement. During this phase,alternative reinforcement was delivered with a tandem variable interval - fixed time (VI-FT) schedule. For subjects in the Replication group, the value of the VI schedule remained at 30 s while the FT schedule changed each session (i.e., .5, 1, 5, 10, 20 and 30 s). For the Delay group, both VI and FT values change per session, decreasing for the former (i.e., 29.5, 29, 25, 10, and CRF) and increasing for the latter (i.e., .5, 1, 5, 10, 20 and 30 s), in order to roughly maintain the inter-reinforcement time equal across sessions. This phase lasted 6 sessions for all rats. Results Figure 1 shows target and alternative response rates and reinforcement rates for the last six sessions of each phase for all subjects of the experiment. Overall, for all subjects, target responses were relatively stable during Phase 1 and decreased to near zero during Phase 2. During Phase 3, most of the responses were emitted on the alternative lever. Obtained target and alternative reinforcement rates were similar between Phase 1 and Phase 3. During Phase 4, the obtained reinforcement rate in the Replication group declined steeply across sessions as the delay increased. Most subjects exhibited a consistent and systematic decrease in alternative response rates, with the steepest declines observed in R9 and R10. In contrast, R1 maintained response rates similar to the previous phase during the initial sessions before decreasing with longer delays. For the Delay group, reinforcement rates remained relatively stable compared to the previous phase, though with a slight decrease. Alternative response rates decreased across sessions for all subjects, but less steeply than subjects in the Replication group. Figure 2 shows target response rates in both absolute values and as a proportion-of-baseline responding for both groups. Proportion of baseline response rates were calculated by dividing the target response rate of each session of Phase 4 by the mean of the stable sessions of the Phase 1 (i.e., last six sessions). In the Replication group, target response rates increased (i.e., resurgence), likely due to both reductions in alternative reinforcement and increases in alternative reinforcement delays, beginning at the 5 s delay. This increase was most pronounced and systematic for two rats. For one rat, target response rate was initially high during sessions with 5 s and 10 s delays but later declined to near zero levels in subsequent sessions. In contrast, the remaining rats maintained near zero response rates throughout the phase. Overall, response recovery ranged from 5% to 40% of baseline levels across subjects. In the Delay group, small increases in target responses were observed throughout the phase. Two rats showed gradual increases until the 20 s delay, while one rat exhibited only a slight increase at the 10 s delay. Two rats had increases at the 5 s, 20 s, and 30 s delays. Additionally, one of them showed an increase at the 0.5 s delay. Response recovery reached a maximum of only 5% of the baseline response rate for this group. Discussion This study examined whether the resurgence reported by Jarmolowicz and Lattal ( 2014 ) was driven solely by reinforcement delay or resulted from the combined effects of increasing delays and reduced reinforcement frequency. The findings suggest that resurgence occurred in a greater extent when both factors were present, indicating that delays alone may be insufficient to induce resurgence. Our results replicated the findings of Jarmolowicz and Lattal ( 2014 ) on delayed alternative reinforcement, originally demonstrated with pigeons. Specifically, resurgence was observed consistently and to a considerable extent across delays for most rats of Replication group. Additionally, reinforcement frequency progressively decreased for all subjects, and alternative response rates declined across sessions (except for R1). Jarmolowicz and Lattal suggested that their results were driven more by a degradation of the response-reinforcement contingency, which led to decreased alternative responding, rather than by local extinction periods resulting from reinforcement delays. However, our results do not support this interpretation. Although both groups experienced a reduction in response-reinforcer contiguity, resurgence was observed only in a greater extent in the Replication group, where reinforcement delays also introduced local periods of extinction by reducing the overall reinforcement rate, making it a relevant condition under resurgence could be observed. These findings align with prior research demonstrating increased target responding following reinforcement thinning (Schepers & Bouton, 2015 ; Sweeney & Shahan, 2013 ) and abrupt reductions in alternative reinforcement rates (Lieving & Lattal, 2003 ; Marsteller & St Peter, 2012 ). The absence of resurgence in Delay group is consistent with Lieving and Lattal’s ( 2003 , Experiment 3) findings, where eliminating the response-reinforcement contingency via response-independent reinforcement did not produce resurgence when overall reinforcement frequency remained unchanged. A possible explanation for this outcome is that, although response-reinforcer contiguity was progressively reduced in the Delay group, the higher reinforcement frequency likely prevented the rats from discriminating a worsening of alternative conditions. Prior research suggests that the discrimination of worsening is critical for resurgence, even if overall reinforcement rates remain constant. For instance, Nighbor et al. ( 2020 ) found that signaled local extinction periods without altering overall reinforcement rates induced resurgence, while Yensen et al. (2020) demonstrated that transitioning from a variable interval (VI) to a fixed interval (FI) schedule produced resurgence, likely due to the increased salience of local extinction periods inherent to FI schedules. Compared to these manipulations, lengthening reinforcement delays may be a less salient cue for worsening conditions when reinforcement remains frequent. A limitation of the present experiment was the difference in delay durations between this study and that of Jarmolowicz and Lattal ( 2014 ). Their study implemented delays of up to 640 s, whereas our design restricted delays to a maximum of 30 s to maintain comparable reinforcement rates between groups. Despite this constraint, resurgence was still observed in the Replication group, indicating that even moderate delays can contribute to resurgence when reinforcement frequency is simultaneously reduced. Future research should further investigate the role of reinforcement delay in resurgence, as this dimension has received less attention compared to other reinforcement parameters, such as rate and magnitude. Overall, these results suggest that under delayed alternative reinforcement, resurgence is more likely a function of experiencing local extinction periods rather than a mere reduction in response-reinforcer contiguity. This outcome contributes to a broader understanding of the conditions under which resurgence occurs beyond typical extinction, including other forms of “worsening” such as punishment (Fontes et al., 2018 ; Redner et al., 2024 ) and reductions in reinforcement magnitude (Browning et al., 2022 ; Craig et al., 2017 ; Oliver et al., 2018 ) or quality (Shahan et al., 2024 ). Declarations Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest. References Browning, K. O., Sutton, G. M., Nist, A. N., & Shahan, T. A. (2022). The effects of large, small, and thinning magnitudes of alternative reinforcement on resurgence. Behavioural Processes , 104586-104586. https://doi.org/10.1016/j.beproc.2022.104586 Cleland, B. S., Guerin, B., Foster, T. M., & Temple, W. (2001). Resurgence. The Behavior Analyst , 24 , 255-260. https://doi.org/10.1007/BF03392035 Craig, A. R., Browning, K. O., Nall, R. W., Marshall, C. M., & Shahan, T. A. (2017). Resurgence and alternative-reinforcer magnitude. Journal of the Experimental Analysis of Behavior , 107 (2), 218-233. https://doi.org/10.1002/jeab.245 Epstein, R. (1983). Resurgence of previously reinforced behavior during extinction. Behaviour Analysis Letters , 3 (6), 391-397. Fleshler, M., & Hoffman, H. S. (1962). A progression for generating variable-interval schedules. Journal of the Experimental Analysis of Behavior , 5 (4), 529-530. https://doi.org/10.1901/jeab.1962.5-529 Fontes, R. M., Todorov, J. C., & Shahan, T. A. (2018). Punishment of an alternative behavior generates resurgence of a previously extinguished target behavior. Journal of the Experimental Analysis of Behavior , 110 (2), 171-184. https://doi.org/10.1002/jeab.465 Hernández, C., Madrigal, K., & Flores, C. (2020). Resurgence after different number of target-extinction or alternative-reinforcement sessions in rats. Learning and Motivation , 71 , 101652. https://doi.org/10.1016/j.lmot.2020.101652 Jarmolowicz, D. P., & Lattal, K. A. (2013). Delayed reinforcement and fixed‐ratio performance. Journal of the Experimental Analysis of Behavior , 100 (3), 370-395. https://doi.org/10.1002/jeab.48 Jarmolowicz, D. P., & Lattal, K. A. (2014). Resurgence under delayed reinforcement. Psychological Record , 64 (2), 189-193. https://doi.org/10.1007/s40732-014-0040-0 Leitenberg, H., Rawson, R. A., & Mulick, J. A. (1975). Extinction and reinforcement of alternative behavior. Journal of Comparative and Physiological Psychology , 88 (2), 640-652. https://doi.org/10.1037/h0076418 Lieving, G. A., & Lattal, K. A. (2003). Recency, repeatability, and reinforcer retrenchment: An experimental analysis of resurgence. Journal of the Experimental Analysis of Behavior , 80 (2), 217-233. https://doi.org/10.1901/jeab.2003.80-217 Marsteller, T. M., & St Peter, C. C. (2012). Resurgence during treatment challenges. Revista Mexicana de Análisis de La Conducta , 38 (1), 7-23. Nighbor, T. D., Oliver, A. C., & Lattal, K. A. (2020). Resurgence without overall worsening of alternative reinforcement. Behavioural Processes , 179 , 104219. https://doi.org/10.1016/j.beproc.2020.104219 Oliver, A. C., Nighbor, T. D., & Lattal, K. A. (2018). Reinforcer magnitude and resurgence. Journal of the Experimental Analysis of Behavior , 110 (3), 440-450. https://doi.org/10.1002/jeab.481 Redner, R., Kestner, K. M., Lotfizadeh, A., & Poling, A. (2024). Punishment-induced resurgence. Behavioural Processes , 220 , 105058. https://doi.org/10.1016/j.beproc.2024.105058 Schepers, S. T., & Bouton, M. E. (2015). Effects of reinforcer distribution during response elimination on resurgence of an instrumental behavior. Journal of Experimental Psychology. Animal Learning and Cognition , 41 (2), 179-192. https://doi.org/10.1037/xan0000061 Shahan, T. A., Sutton, G. M., Van Allsburg, J., Avellaneda, M., & Greer, B. D. (2024). Resurgence following higher or lower quality alternative reinforcement. Journal of the Experimental Analysis of Behavior , 121 (2), 246-258. https://doi.org/10.1002/jeab.904 Sweeney, M. M., & Shahan, T. A. (2013). Effects of high, low, and thinning rates of alternative reinforcement on response elimination and resurgence. Journal of the Experimental Analysis of Behavior , 100 (1), 102-116. https://doi.org/10.1002/jeab.26 Wathen, S. N., & Podlesnik, C. A. (2018). Laboratory models of treatment relapse and mitigation techniques. Behavior Analysis: Research and Practice , 18 (4), 362-387. https://doi.org/10.1037/bar0000119 Winterbauer, N. E., & Bouton, M. E. (2012). Effects of thinning the rate at which the alternative behavior is reinforced on resurgence of an extinguished instrumental response. Journal of experimental psychology. Animal behavior processes , 38 (3), 279-291. https://doi.org/10.1037/a0028853 Yensen, C. P., Nighbor, T. D., Cook, J. E., Oliver, A. C., & Lattal, K. A. (2022). Resurgence during transitions from variable- to fixed-interval schedules. Behavioural Processes , 195 , 104567. https://doi.org/10.1016/j.beproc.2021.104567 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6613854","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":453384011,"identity":"7e3c24f1-f212-486a-b12b-e6993bc9262d","order_by":0,"name":"Carlos J. Flores","email":"","orcid":"","institution":"Universidad de Guadalajara","correspondingAuthor":false,"prefix":"","firstName":"Carlos","middleName":"J.","lastName":"Flores","suffix":""},{"id":453384012,"identity":"6c11218c-fc12-458a-b8fe-1c4d8930e76b","order_by":1,"name":"Julian C. 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Target (TR) and alternative (ALT) response rates (left y-axis) and reinforcement (SR) rates (right y-axis) from the final sessions of Phases 1–3 and all sessions of Phase 4 are shown.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6613854/v1/b794210d742d7c72866c66b1.png"},{"id":82348979,"identity":"6af923cd-73f1-4771-8fb8-6ebdf2ebe4ff","added_by":"auto","created_at":"2025-05-09 10:44:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":56958,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAbsolute and Proportion-of-Baseline Target Response Rates from Phase 3 to Phase 4 by Group\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003eThe upper panel shows absolute response rates and the bottom panel shows proportion-of-baseline response rate. Solid lines indicate group mean and gray lines indicate data from individual subjects. The arrow and numbers refer to the response rate for a single rat outside the y-axis boundary.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6613854/v1/0ddf9299e22de86e660da395.png"},{"id":82350507,"identity":"f7e998de-18e4-4612-897f-2bd19be0bcd5","added_by":"auto","created_at":"2025-05-09 10:52:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":460276,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6613854/v1/2d0c3168-6aa7-4c3f-a08e-10d043756029.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eIsolating Delay and Reinforcement Rate Effects on Resurgence: A Replication of Jarmolowicz \u0026amp; Lattal (2014)\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eResurgence is defined as an increase in suppressed behavior due to the worsening of alternative reinforcement conditions (Lattal et al., 2017). This phenomenon has been widely studied because of its relevance to understanding relapse in applied settings (Wathen \u0026amp; Podlesnik, 2018). Experimentally, resurgence is typically examined using a three-phase procedure: (1) reinforcement of a target behavior, (2) extinction of the target behavior while reinforcing an alternative response, and (3) disruption of alternative reinforcement, often by removing it entirely (Leitenberg et al., 1975; Lieving \u0026amp; Lattal, 2003). Some researchers have also used a four-phase procedure where the target response extinction occurs in an independent phase before the reinforcement of the alternative behavior (Cleland et al., 2001; Hern\u0026aacute;ndez et al., 2020; Lieving \u0026amp; Lattal, 2003 Experiment 1).\u003c/p\u003e\n\u003cp\u003eWhile resurgence has traditionally been induced through extinction in the final phase (e.g. Epstein, 1983; Lieving \u0026amp; Lattal, 2003), research has identified additional ways in which alternative reinforcement can be \u0026ldquo;worsened\u0026rdquo; to produce resurgence. These include punishment of the alternative response (Fontes et al., 2018; Redner et al., 2024), reductions in reinforcement magnitude (Browning et al., 2022; Craig et al., 2017; Oliver et al., 2018) or quality (Shahan et al., 2024), local periods of extinction by abruptly or gradually reducing reinforcement rate, changing the schedule of reinforcement or delaying alternative reinforcement (Jarmolowicz \u0026amp; Lattal, 2014; Lieving \u0026amp; Lattal, 2003, Experiment 4; Nighbor et al., 2020; Schepers \u0026amp; Bouton, 2015; Sweeney \u0026amp; Shahan, 2013; Winterbauer \u0026amp; Bouton, 2012; Yensen et al., 2022).\u003c/p\u003e\n\u003cp\u003eFor instance, Lieving and Lattal (2003, Experiment 4) examined resurgence when alternative reinforcement transitioned from a variable interval (VI) 30 s to a VI 360 s schedule, thereby increasing inter-reinforcer intervals. Resurgence was observed across all subjects, being higher during longer inter-reinforcement intervals. This was similarly observed under thinning of alternative reinforcement rate (Schepers \u0026amp; Bouton, 2015; Sweeney \u0026amp; Shahan, 2013; Winterbauer \u0026amp; Bouton, 2012). Nighbor et al. (2020, Experiment 1) found resurgence in pigeons when local extinction periods were signaled using a delayed reinforcement schedule. Yensen et al. (2022) observed resurgence with unsignaled local extinction periods by transitioning from a VI to fixed interval (FI) schedules, with the highest response rates during longer FI schedules and extinction. These findings suggest that both signaled and unsignaled extinction periods can act as worsening conditions that induce resurgence.\u003c/p\u003e\n\u003cp\u003eJarmolowicz and Lattal (2014) proposed that increasing reinforcement delays in alternative conditions should lead to resurgence. Using pigeons as subjects, they found that longer delays produced resurgence of target responding in two of the four subjects. However, a key limitation of their design was that increasing delays not only decreased the response-reinforcer contingency but also reduced overall reinforcement frequency. This reduction in reinforcement rate may have introduced local extinction periods similar to those described in previous studies. The authors acknowledged this confound, noting that some research suggests delayed reinforcement effects can occur independently of changes in reinforcement rate (Jarmolowicz \u0026amp; Lattal, 2013). \u003c/p\u003e\n\u003cp\u003eIt is unclear whether resurgence is differentially affected by the combined manipulation of reinforcement delay and rate compared to delay alone. This study aims to (1) replicate Jarmolowicz and Lattal\u0026rsquo;s (2014) procedure with rats and (2) compare resurgence when delays are introduced without altering reinforcement frequency, isolating the effects of delay from rate changes to clarify conditions for resurgence and refine understanding of how degraded reinforcement contributes to behavioral relapse.\u003cstrong\u003e\u003cbr\u003e \u003c/strong\u003e\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003e\u003cstrong\u003eSubjects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e10 six-month old male Wistar rats were used. All rats had the same previous experience (i.e., number of sessions) with variable interval (VI) schedule with water as reinforcer. They had a food deprivation schedule and were maintained at 80% - 85% of their \u003cem\u003ead libitum\u003c/em\u003e weight. Each rat was individually housed in a controlled temperature colony under a 12:12 hr. light/dark cycle with constantaccess to water. The protocol accomplished the animal care guidelines of the institution\u0026rsquo;s ethical committee.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eApparatus\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEight Med Associates operant chambers (ENV-008) were used. Each chamber was equipped with a food dispenser (ENV-203 M) centered on the front panel that delivered 45 mg grain-based pellets (Bio Serv), two 4.5 cm long retractable levers (ENV-112CM) with a cue light (ENV-221M) above were placed on both sides of the dispenser at a height of 7 cm of the grid floor. All chambers were enclosed in a sound-attenuating box (ENV-022MD) with external-sound masking fans. Experimental events and data collection were programmed using Med-PC V\u003csup\u003e\u0026reg;\u003c/sup\u003e software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMagazine and response training.\u003c/em\u003e The first session began with the illumination of houselight where rats were trained to enter in the magazine and consume pellets using a VT 60 s schedule. Each pellet delivery was accompanied by the offset of houselight for 3 s. Then, experimental sessions began with the introduction of one lever (right or left, according to a .5 probability) and each response was reinforced (CRF). After the delivery of the pellet, the operating lever was retracted and the other lever was inserted in the box, repeating this alternation until the end of the session. Once 30 reinforcers were produced under this arrangement in two consecutive days, the schedule was changed to a VI. The schedule value increased gradually (5, 15, 25) every two sessions, with each value remaining in effect until 30 reinforcers were delivered. Each schedule of reinforcement was derived from a 10-value list without replacement according to a Fleshler and Hoffman\u0026apos;s (1962) distribution. All training sessions ended after 60 min or 30 pellet deliveries, whichever occurred first. Sessions were conducted on successive days, always at the same time.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePhase 1: Target reinforcement.\u0026nbsp;\u003c/em\u003eThe 10 rats were randomly assigned to two groups, each comprising five animals\u003cem\u003e.\u0026nbsp;\u003c/em\u003eDuring this phase, one lever was inserted in the box (right or left, counterbalanced), accompanied by the cue light above. Responses to the target lever (TR) produced the delivery of one pellet according to a VI 30 s schedule. Time for consumption was fixed 3 s that were excluded from the total duration of the session. This phase lasted a minimum of 15 sessions and until stable responding was achieved. A relative stability criterion was used\u0026nbsp;\u003ca href=\"https://www.zotero.org/google-docs/?QKJWtY\"\u003e(Cumming \u0026amp; Schoenfeld, 1960)\u003c/a\u003e. For the six more recent sessions, the difference of the mean response rates of the last three sessions and first three sessions could not be more than +/- 5% of the grand mean. Each session lasted until 30 reinforcers were delivered. Across rats, this phase lasted between 15 and 26 sessions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePhase 2: Target extinction.\u0026nbsp;\u003c/em\u003eResponses on the target lever were placed on extinction, with no programmed consequences. This phase continued until target lever responses ceased entirely or until a maximum of 30 sessions was completed. Each session duration matched that of the final session in the previous phase. Across rats, this phase lasted between 16 and 30 sessions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePhase 3: Alternative reinforcement.\u0026nbsp;\u003c/em\u003eSessions began with the insertion of both levers and the illumination of their respective cue light. Responses to the alternative lever (ALT) were reinforced according to a VI 30 s schedule, while responses to the TR remained without programmed consequences. This phase continued until reaching the same stability criteria for target response. Across rats, this phase lasted between 17 and 27 sessions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePhase 4: Delayed reinforcement.\u0026nbsp;\u003c/em\u003eDuring this phase,alternative reinforcement was delivered with a tandem variable interval - fixed time (VI-FT) schedule. For subjects in the Replication group, the value of the VI schedule remained at 30 s while the FT schedule changed each session (i.e., .5, 1, 5, 10, 20 and 30 s). For the Delay group, both VI and FT values change per session, decreasing for the former (i.e., 29.5, 29, 25, 10, and CRF) and increasing for the latter (i.e., .5, 1, 5, 10, 20 and 30 s), in order to roughly maintain the inter-reinforcement time equal across sessions. This phase lasted 6 sessions for all rats.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFigure 1 shows target and alternative response rates and reinforcement rates for the last six sessions of each phase for all subjects of the experiment. Overall, for all subjects, target responses were relatively stable during Phase 1 and decreased to near zero during Phase 2. During Phase 3, most of the responses were emitted on the alternative lever. Obtained target and alternative reinforcement rates were similar between Phase 1 and Phase 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDuring Phase 4, the obtained reinforcement rate in the Replication group declined steeply across sessions as the delay increased. Most subjects exhibited a consistent and systematic decrease in alternative response rates, with the steepest declines observed in R9 and R10. In contrast, R1 maintained response rates similar to the previous phase during the initial sessions before decreasing with longer delays. For the Delay group, reinforcement rates remained relatively stable compared to the previous phase, though with a slight decrease. Alternative response rates decreased across sessions for all subjects, but less steeply than subjects in the Replication group.\u003c/p\u003e\n\u003cp\u003eFigure 2 shows target response rates in both absolute values and as a proportion-of-baseline responding for both groups. Proportion of baseline response rates were calculated by dividing the target response rate of each session of Phase 4 by the mean of the stable sessions of the Phase 1 (i.e., last six sessions). In the Replication group, target response rates increased (i.e., resurgence), likely due to both reductions in alternative reinforcement and increases in alternative reinforcement delays, beginning at the 5 s delay. This increase was most pronounced and systematic for two rats. For one rat, target response rate was initially high during sessions with 5 s and 10 s delays but later declined to near zero levels in subsequent sessions. In contrast, the remaining rats maintained near zero response rates throughout the phase. Overall, response recovery ranged from 5% to 40% of baseline levels across subjects. In the Delay group, small increases in target responses were observed throughout the phase. Two rats showed gradual increases until the 20 s delay, while one rat exhibited only a slight increase at the 10 s delay. Two rats had increases at the 5 s, 20 s, and 30 s delays. Additionally, one of them showed an increase at the 0.5 s delay. Response recovery reached a maximum of only 5% of the baseline response rate for this group.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined whether the resurgence reported by Jarmolowicz and Lattal (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) was driven solely by reinforcement delay or resulted from the combined effects of increasing delays and reduced reinforcement frequency. The findings suggest that resurgence occurred in a greater extent when both factors were present, indicating that delays alone may be insufficient to induce resurgence.\u003c/p\u003e \u003cp\u003eOur results replicated the findings of Jarmolowicz and Lattal (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) on delayed alternative reinforcement, originally demonstrated with pigeons. Specifically, resurgence was observed consistently and to a considerable extent across delays for most rats of Replication group. Additionally, reinforcement frequency progressively decreased for all subjects, and alternative response rates declined across sessions (except for R1). Jarmolowicz and Lattal suggested that their results were driven more by a degradation of the response-reinforcement contingency, which led to decreased alternative responding, rather than by local extinction periods resulting from reinforcement delays. However, our results do not support this interpretation. Although both groups experienced a reduction in response-reinforcer contiguity, resurgence was observed only in a greater extent in the Replication group, where reinforcement delays also introduced local periods of extinction by reducing the overall reinforcement rate, making it a relevant condition under resurgence could be observed. These findings align with prior research demonstrating increased target responding following reinforcement thinning (Schepers \u0026amp; Bouton, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sweeney \u0026amp; Shahan, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and abrupt reductions in alternative reinforcement rates (Lieving \u0026amp; Lattal, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Marsteller \u0026amp; St Peter, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe absence of resurgence in Delay group is consistent with Lieving and Lattal\u0026rsquo;s (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, Experiment 3) findings, where eliminating the response-reinforcement contingency via response-independent reinforcement did not produce resurgence when overall reinforcement frequency remained unchanged. A possible explanation for this outcome is that, although response-reinforcer contiguity was progressively reduced in the Delay group, the higher reinforcement frequency likely prevented the rats from discriminating a worsening of alternative conditions. Prior research suggests that the discrimination of worsening is critical for resurgence, even if overall reinforcement rates remain constant. For instance, Nighbor et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found that signaled local extinction periods without altering overall reinforcement rates induced resurgence, while Yensen et al. (2020) demonstrated that transitioning from a variable interval (VI) to a fixed interval (FI) schedule produced resurgence, likely due to the increased salience of local extinction periods inherent to FI schedules. Compared to these manipulations, lengthening reinforcement delays may be a less salient cue for worsening conditions when reinforcement remains frequent.\u003c/p\u003e \u003cp\u003eA limitation of the present experiment was the difference in delay durations between this study and that of Jarmolowicz and Lattal (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Their study implemented delays of up to 640 s, whereas our design restricted delays to a maximum of 30 s to maintain comparable reinforcement rates between groups. Despite this constraint, resurgence was still observed in the Replication group, indicating that even moderate delays can contribute to resurgence when reinforcement frequency is simultaneously reduced. Future research should further investigate the role of reinforcement delay in resurgence, as this dimension has received less attention compared to other reinforcement parameters, such as rate and magnitude.\u003c/p\u003e \u003cp\u003eOverall, these results suggest that under delayed alternative reinforcement, resurgence is more likely a function of experiencing local extinction periods rather than a mere reduction in response-reinforcer contiguity. This outcome contributes to a broader understanding of the conditions under which resurgence occurs beyond typical extinction, including other forms of \u0026ldquo;worsening\u0026rdquo; such as punishment (Fontes et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Redner et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and reductions in reinforcement magnitude (Browning et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Craig et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Oliver et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) or quality (Shahan et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest.\u003c/p\u003e \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBrowning, K. O., Sutton, G. M., Nist, A. N., \u0026amp; Shahan, T. A. (2022). The effects of large, small, and thinning magnitudes of alternative reinforcement on resurgence. \u003cem\u003eBehavioural Processes\u003c/em\u003e, 104586-104586. https://doi.org/10.1016/j.beproc.2022.104586\u003c/li\u003e\n \u003cli\u003eCleland, B. S., Guerin, B., Foster, T. M., \u0026amp; Temple, W. (2001). Resurgence. \u003cem\u003eThe Behavior Analyst\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e, 255-260. https://doi.org/10.1007/BF03392035\u003c/li\u003e\n \u003cli\u003eCraig, A. R., Browning, K. O., Nall, R. W., Marshall, C. M., \u0026amp; Shahan, T. A. (2017). Resurgence and alternative-reinforcer magnitude. \u003cem\u003eJournal of the Experimental Analysis of Behavior\u003c/em\u003e, \u003cem\u003e107\u003c/em\u003e(2), 218-233. https://doi.org/10.1002/jeab.245\u003c/li\u003e\n \u003cli\u003eEpstein, R. (1983). Resurgence of previously reinforced behavior during extinction. \u003cem\u003eBehaviour Analysis Letters\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e(6), 391-397.\u003c/li\u003e\n \u003cli\u003eFleshler, M., \u0026amp; Hoffman, H. S. (1962). A progression for generating variable-interval schedules. \u003cem\u003eJournal of the Experimental Analysis of Behavior\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(4), 529-530. https://doi.org/10.1901/jeab.1962.5-529\u003c/li\u003e\n \u003cli\u003eFontes, R. M., Todorov, J. C., \u0026amp; Shahan, T. A. (2018). Punishment of an alternative behavior generates resurgence of a previously extinguished target behavior. \u003cem\u003eJournal of the Experimental Analysis of Behavior\u003c/em\u003e, \u003cem\u003e110\u003c/em\u003e(2), 171-184. https://doi.org/10.1002/jeab.465\u003c/li\u003e\n \u003cli\u003eHern\u0026aacute;ndez, C., Madrigal, K., \u0026amp; Flores, C. (2020). Resurgence after different number of target-extinction or alternative-reinforcement sessions in rats. \u003cem\u003eLearning and Motivation\u003c/em\u003e, \u003cem\u003e71\u003c/em\u003e, 101652. https://doi.org/10.1016/j.lmot.2020.101652\u003c/li\u003e\n \u003cli\u003eJarmolowicz, D. P., \u0026amp; Lattal, K. A. (2013). Delayed reinforcement and fixed‐ratio performance. \u003cem\u003eJournal of the Experimental Analysis of Behavior\u003c/em\u003e, \u003cem\u003e100\u003c/em\u003e(3), 370-395. https://doi.org/10.1002/jeab.48\u003c/li\u003e\n \u003cli\u003eJarmolowicz, D. P., \u0026amp; Lattal, K. A. (2014). Resurgence under delayed reinforcement. \u003cem\u003ePsychological Record\u003c/em\u003e, \u003cem\u003e64\u003c/em\u003e(2), 189-193. https://doi.org/10.1007/s40732-014-0040-0\u003c/li\u003e\n \u003cli\u003eLeitenberg, H., Rawson, R. A., \u0026amp; Mulick, J. A. (1975). Extinction and reinforcement of alternative behavior. \u003cem\u003eJournal of Comparative and Physiological Psychology\u003c/em\u003e, \u003cem\u003e88\u003c/em\u003e(2), 640-652. https://doi.org/10.1037/h0076418\u003c/li\u003e\n \u003cli\u003eLieving, G. A., \u0026amp; Lattal, K. A. (2003). Recency, repeatability, and reinforcer retrenchment: An experimental analysis of resurgence. \u003cem\u003eJournal of the Experimental Analysis of Behavior\u003c/em\u003e, \u003cem\u003e80\u003c/em\u003e(2), 217-233. https://doi.org/10.1901/jeab.2003.80-217\u003c/li\u003e\n \u003cli\u003eMarsteller, T. M., \u0026amp; St Peter, C. C. (2012). Resurgence during treatment challenges. \u003cem\u003eRevista Mexicana de An\u0026aacute;lisis de La Conducta\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(1), 7-23.\u003c/li\u003e\n \u003cli\u003eNighbor, T. D., Oliver, A. C., \u0026amp; Lattal, K. A. (2020). Resurgence without overall worsening of alternative reinforcement. \u003cem\u003eBehavioural Processes\u003c/em\u003e, \u003cem\u003e179\u003c/em\u003e, 104219. https://doi.org/10.1016/j.beproc.2020.104219\u003c/li\u003e\n \u003cli\u003eOliver, A. C., Nighbor, T. D., \u0026amp; Lattal, K. A. (2018). Reinforcer magnitude and resurgence. \u003cem\u003eJournal of the Experimental Analysis of Behavior\u003c/em\u003e, \u003cem\u003e110\u003c/em\u003e(3), 440-450. https://doi.org/10.1002/jeab.481\u003c/li\u003e\n \u003cli\u003eRedner, R., Kestner, K. M., Lotfizadeh, A., \u0026amp; Poling, A. (2024). Punishment-induced resurgence. \u003cem\u003eBehavioural Processes\u003c/em\u003e, \u003cem\u003e220\u003c/em\u003e, 105058. https://doi.org/10.1016/j.beproc.2024.105058\u003c/li\u003e\n \u003cli\u003eSchepers, S. T., \u0026amp; Bouton, M. E. (2015). Effects of reinforcer distribution during response elimination on resurgence of an instrumental behavior. \u003cem\u003eJournal of Experimental Psychology. Animal Learning and Cognition\u003c/em\u003e, \u003cem\u003e41\u003c/em\u003e(2), 179-192. https://doi.org/10.1037/xan0000061\u003c/li\u003e\n \u003cli\u003eShahan, T. A., Sutton, G. M., Van Allsburg, J., Avellaneda, M., \u0026amp; Greer, B. D. (2024). Resurgence following higher or lower quality alternative reinforcement. \u003cem\u003eJournal of the Experimental Analysis of Behavior\u003c/em\u003e, \u003cem\u003e121\u003c/em\u003e(2), 246-258. https://doi.org/10.1002/jeab.904\u003c/li\u003e\n \u003cli\u003eSweeney, M. M., \u0026amp; Shahan, T. A. (2013). Effects of high, low, and thinning rates of alternative reinforcement on response elimination and resurgence. \u003cem\u003eJournal of the Experimental Analysis of Behavior\u003c/em\u003e, \u003cem\u003e100\u003c/em\u003e(1), 102-116. https://doi.org/10.1002/jeab.26\u003c/li\u003e\n \u003cli\u003eWathen, S. N., \u0026amp; Podlesnik, C. A. (2018). Laboratory models of treatment relapse and mitigation techniques. \u003cem\u003eBehavior Analysis: Research and Practice\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(4), 362-387. https://doi.org/10.1037/bar0000119\u003c/li\u003e\n \u003cli\u003eWinterbauer, N. E., \u0026amp; Bouton, M. E. (2012). Effects of thinning the rate at which the alternative behavior is reinforced on resurgence of an extinguished instrumental response. \u003cem\u003eJournal of experimental psychology. Animal behavior processes\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(3), 279-291. https://doi.org/10.1037/a0028853\u003c/li\u003e\n \u003cli\u003eYensen, C. P., Nighbor, T. D., Cook, J. E., Oliver, A. C., \u0026amp; Lattal, K. A. (2022). Resurgence during transitions from variable- to fixed-interval schedules. \u003cem\u003eBehavioural Processes\u003c/em\u003e, \u003cem\u003e195\u003c/em\u003e, 104567. https://doi.org/10.1016/j.beproc.2021.104567\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"f64e0eee-2bb4-4770-aef6-5766790fc374","identifier":"10.13039/501100003141","name":"Consejo Nacional de Ciencia y Tecnología","awardNumber":"Project CF-2023-I-1099","order_by":0},{"identity":"d16eaf30-a7d5-456d-a00a-a5bf14020ca9","identifier":"10.13039/100016991","name":"Universidad de Guadalajara","awardNumber":"Proyecto de Fortalecimiento a la Investigación","order_by":1}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Guadalajara","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Resurgence, Alternative reinforcement, Delayed reinforcement, Frequency of Reinforcement, Rats","lastPublishedDoi":"10.21203/rs.3.rs-6613854/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6613854/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eResurgence of a previously extinguished response often occurs when alternative conditions of reinforcement are worsened. Jarmolowicz and Lattal (2014) showed that delayed alternative reinforcement can cause resurgence, but it’s unclear whether the delay or a decrease in reinforcement rate is responsible. This study aimed to clarify this. The Replication group experienced increasing delays in alternative reinforcement schedules, while the Delay group experienced both increasing delays and richer frequencies of alternative reinforcement, ensuring that the reinforcement rate remained constant across sessions. Results showed more resurgence in the Replication group, suggesting that delay alone is not enough to produce resurgence.\u003c/p\u003e","manuscriptTitle":"Isolating Delay and Reinforcement Rate Effects on Resurgence: A Replication of Jarmolowicz \u0026amp; Lattal (2014)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 10:44:24","doi":"10.21203/rs.3.rs-6613854/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cc3a7f15-6bd8-4217-bceb-8ea89945c88c","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-09T10:44:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-09 10:44:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6613854","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6613854","identity":"rs-6613854","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}