Exploring persistence in animal models: the sinking platform test

Abstract

Persistence is the capacity to sustain goal-oriented behavior despite recurring obstacles and setbacks. Recent studies have underscored the importance of this attribute as an integral facet of resilience and a protective factor against depression. In animal models, persistence is commonly examined through operant paradigms, wherein it is operationalized as resistance to the extinction of goal-directed actions. However, these methods are labor-intensive and resource-demanding, prompting questions about their efficiency in exploring the biological underpinnings of persistence and evaluating pharmacological interventions.

To address these challenges, our team developed the Sinking Platform Test (SPT), a high-throughput animal task designed to assess persistence under stressful conditions. In the SPT, mice are trained to escape from a water-filled tank by climbing onto a platform above the water. Training also encompasses occasional “failure trials”, where the platform is submerged after being climbed, compelling the mice to locate and ascend a new platform. The final test consists of a 5-minute session exclusively comprising failure trials, and persistence is measured as the number of climbed platforms. Our research revealed that chronic stress diminishes performance in the SPT, an effect reversed by chronic antidepressant treatment or voluntary exercise.

These findings highlight the potential of SPT for investigating persistence and exploring its role in resilience and depression. Ongoing efforts within our laboratory focus on refining the SPT to minimize stress while enhancing methodological rigor and reproducibility, notably through automation. Future research endeavors will aim to improve SPT’s translational relevance by adapting the paradigm for human application, potentially leveraging virtual-reality technologies.

Introduction

Stress is conceptualized as a state of real or perceived demands or threats that challenge an individual’s capacity to maintain homeostatic equilibrium. The organism responds by activating various physiological systems, such as the sympathetic-adrenal-medullary (SAM) and hypothalamic-pituitary-adrenal (HPA) axes, which help adapt to environmental changes and facilitate an effective response to the perceived stressors. However, when stress continues for a prolonged period, the adaptive benefits of this response decrease, leading to a maladaptive condition known as allostasis. The accumulated physiological strain from chronic stress, termed allostatic load, is linked to long-term adverse health effects, including an increased risk of depression, anxiety, and sleep disorders (Finlay et al., 2022; McEwen, 2003).

In recent years, scientific research on the relationship between stress and psychopathology has shifted from solely examining the factors that make individuals vulnerable to negative stress outcomes to focusing more on the characteristics that help certain people effectively manage both acute and chronic stress. These processes, collectively known as resilience, involve dynamic adaptation and thriving in the face of ongoing challenges by leveraging internal and external resources to minimize harm and promote positive development. This research has highlighted resilience as a complex and multifaceted construct shaped by the interaction of various personality traits, including flexible self-regulation, self-efficacy, and optimism (Bonanno et al., 2005; Carver et al., 2010; Pathak and Lata, 2019; Schwarzer and Warner, 2013; Snyder et al., 2002).

Another key factor influencing stress reactivity is the tendency to persistently pursue goals despite obstacles, challenges, or repeated failures. This trait, often referred to as persistence, perseverance of effort, industriousness, tenacity, or achievement orientation, encompasses sustained effort toward achieving goal-directed tasks (Baumeister et al., 2007; Deater-Deckard et al., 2006; Gusnard et al., 2003). Although subtle differences exist in the definitions of these terms, they all capture the essence of consistent effort toward goals (Duckworth et al., 2007; Eisenberger, 1992; Williams and DeSteno, 2008).

The concept of persistence has a rich historical background (Feather, 1962), with much of the literature traditionally focusing on its role in achievement psychology rather than its protective function in psychopathology. For example, early theoretical work identified persistence as a fundamental component of drive and purposive behavior (Bindra, 1959; Dollard and Miller, 1950; Hull, 1943; Tolman, 1932). Our current understanding of persistence is largely derived from Cloninger’s psychobiological model of temperament and character, which identifies this trait as one of the four primary dimensions of temperament, alongside novelty seeking, harm avoidance, and reward dependence (Cloninger et al., 1993; Cloninger and Svrakic, 2008; Stallings et al., 1996; Svrakic, 1993). Although persistence was initially considered a subscale of reward dependence, research has shown that it is relatively independent of the other three factors. Indeed, current frameworks describe persistence as the capacity to maintain consistent effort toward achieving goals, even in the absence of immediate rewards or in the face of adversity. Highly persistent individuals are often characterized as industrious, determined, diligent, and hard-working overachievers who tend to intensify their efforts in response to anticipated rewards and view frustration and fatigue as personal challenges. Research in positive psychology has recognized persistence as a strong predictor of educational and professional success (Duckworth and Quinn, 2009; Shechtman et al., 2018). Additionally, persistence is positively associated with well-being (Park et al., 2004) and increased life satisfaction (Park, 2004).

Beyond the perspective of positive psychology, emerging research suggests that persistence may also play a crucial role in mitigating the detrimental effects of allostasis, including depression. Indeed, depression has been linked to factors closely associated with a lack of persistence, such as diminished motivation in the face of setbacks and failures (Hankin et al., 2015), reduced confidence in achieving goals (Dickson et al., 2016), and negative perceptions of goal progress (Salmela-Aro and Nurmi, 1996). Depressed individuals often perceive goals as harder to achieve, more effortful, more stressful, and less enjoyable (Cléry-Melin et al., 2011; Dickson and MacLeod, 2006; Lecci et al., 1994; Meyer et al., 2004; Winch et al., 2015). Consistent with this, several recent studies have demonstrated that a lack of persistence is associated with depressive symptoms (d’Acremont and Van Der Linden, 2007; Miller et al., 2003), while other studies have shown a strong association between persistence and lower depression levels (Disabato et al., 2019). This body of evidence highlights the significant potential of persistence as a protective factor against the development of depression following chronic stress. Understanding the neurobiological underpinnings of this trait could be invaluable in developing novel therapeutic approaches for depression. In the subsequent sections, we will explore how research on persistence may yield new insights into the biology of depression, focusing on the characteristics of a novel animal model paradigm that shows promise for studying persistence and its neurobiological basis.

Studying persistence in humans

One of the most significant challenges in studying persistence lies in the diverse terminology employed across various psychological theories, each offering a distinct conceptual framework. These differences are not merely semantic but often reflect fundamentally distinct psychological processes underlying persistent behavior. For instance, persistence has been conceptualized in various ways: as a response to tension from unmet needs (Lewin, 1935), as a manifestation of achievement motivation (Feather, 1962), or as a form of reactance to obstacles that threaten autonomy or progress (Wright and Brehm, 1989). These varying interpretations underscore that persistence is a multifaceted construct shaped by motivational, emotional, and cognitive mechanisms. Consequently, the lack of a unified definition complicates interdisciplinary research and theoretical integration, highlighting the need for precise terminology to bridge different conceptualizations.

Another significant obstacle to understanding persistence is the frequent conflation of persistence with related terms, such as perseveration, in both research and clinical contexts. While persistence refers to sustained effort and commitment toward a goal, perseveration is characterized by the pathological inability to suppress repetitive or ineffective actions, often resulting from neurological conditions (Bjorklund and Harnishfeger, 1990). This conflation has occasionally led to persistence being unfairly associated with traits such as rigidity or irrationality, particularly in clinical studies (Serpell et al., 2009). Distinguishing persistence from similar constructs is essential for accurately interpreting its role in adaptive behavior and avoiding potential mischaracterizations.

The lack of consensus on the definition of persistence has led to challenges in accurately measuring this trait. Persistence and its germane constructs, such as perseverance of effort, are often measured using specific self-report measures (Lufi and Cohen, 1987; Mukherjee, 1974; Wang, 1932) or as components of broader questionnaires, such as the Temperament and Character Inventory (Cloninger et al., 1991), the Self-Control Measure (Tangney et al., 2004), the Action Control Scale (Kuhl, 1994), or the Grit scale (Duckworth et al., 2007). All these questionnaires emphasize sustained involvement, renewed commitment, and increased effort in the face of obstacles. However, depending on their specific theoretical framework of reference, different scales may be inadequate to capture the complexity of persistence. This concern has led to the development of novel multifactor scales aligned with the concept of persistence as a positive resource linked to mental resilience and effective self-regulation (Styk et al., 2023).

An alternative method for capturing persistence in experimental settings involves using specific performance-based tasks. In these paradigms, persistence is typically defined by the time spent on challenging tasks or the ability to endure discomfort (Howells, 1933). This is often assessed by presenting an individual with a difficult or unsolvable task and allowing them unlimited time or attempts to complete it. The individual can switch to an alternative activity at any time, and persistence is measured by the total time or number of attempts spent on the task before choosing the alternative.

For example, the Anagram–Riddle Task (ART) presents participants with a series of easy and difficult anagrams and riddles online, measuring how long they spend on the more challenging problems (Ventura et al., 2013). Other performance-based tasks include the Block Design Subtest of the Wechsler Intelligence tests, such as the Wechsler Preschool and Primary Scale of Intelligence (WPPSI), the Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV; Wechsler, 2003), and the Wechsler Adult Intelligence Scale, Fourth Edition (WAIS-IV; Wechsler, 2008). This test primarily assesses visual-spatial and organizational processing abilities, as well as nonverbal problem-solving skills. As a timed task, it also reflects fine motor skills. The individual is provided with identical blocks that are solid red, solid white, or half red and half white. Using an increasing number of these blocks, they must replicate a pattern shown by the test administrator, first as a physical model and then as a two-dimensional picture. The time spent on the most difficult models is considered a good measure of persistence (Teubner-Rhodes et al., 2017). This gap underscores the importance of examining the relationship between persistence in experimental tasks and real-world outcomes, as well as developing approaches that more accurately capture the multifaceted nature of persistence in everyday life. Combining performance-based tasks with longitudinal studies and self-report measures is essential for gaining a more holistic understanding of persistence as a dynamic and context-dependent phenomenon.

Studying persistence in animal models

While numerous studies have emphasized the psychological significance of persistence, its neurobiological foundations remain largely unexplored. Animal models offer a controlled environment to isolate the mechanisms underlying persistence. A major contribution to operationalizing persistence in animal models came from Abram Amsel, who proposed that learning to maintain a response despite disruptive stimuli through a counterconditioning process enhances persistent behavior. Notably, Amsel’s research demonstrated that learning under partial reinforcement (where behavior is only occasionally reinforced) is more robust than under continuous reinforcement. This led to an alternative definition of persistence as resistance to the extinction of goal-directed behavior, measurable through the partial reinforcement extinction effect (PREE) (Chen and Amsel, 1975). In this phenomenon, intermittent reinforcement during the acquisition of an instrumental task leads to more persistent responding during extinction, compared to continuous reinforcement (Mackintosh, 1974). In other words, individuals exhibiting high persistence are more resistant to the extinction of behavior that was previously intermittently rewarded compared to those who were continuously reinforced.

Building on these concepts, research in rodent models has utilized operant tasks to study persistence. A prominent example is the operant effort-discounting protocol developed by Floresco et al. (2008), which assesses how rats balance effort and reward through a series of choice trials that vary the effort required for a higher reward. Similarly, the weight-lifting task developed by Porter and Hillman (2019) measures persistence by requiring rats to perform a sustained, multi-step action to obtain a reward, with the effort needed increasing over time. These operant tasks are highly time- and labor-intensive, as they require an extensive training period to teach animals specific and artificial sequences of actions to receive a positive reward. Consequently, these tests demand significant cognitive effort from the animals, which may not be feasible for mice. Therefore, concerns have been raised regarding their practicality for studying the neurobiological mechanisms underlying persistence.

A different method has been employed in mice using the long alley test to assess persistence. In this paradigm, mice are trained over ten days to reach a food reward placed at the end of a long alley. Following the acquisition phase, an extinction phase is conducted, during which the food reward is removed. After a 10-day break, the mice are tested again in the same arena for a reacquisition phase. Persistence is evaluated using the average times taken by the mice to reach the goal box during extinction and the distance moved within the goal box (Sauce et al., 2018).

A critical challenge in assessing persistence through the extinction of a reward-based task lies in the prerequisites for stable learning of the task’s strategy, particularly when the rewards are palatable. Achieving consistent and reliable task performance often necessitates food restriction to motivate animals toward the reward. However, chronic food restriction itself can intrinsically alter brain function and behavioral responses (Avena et al., 2013; Jahng et al., 2007), confounding the interpretation of persistence-related behaviors. Additionally, the process of training rodents to adopt and stabilize a specific strategy for obtaining the reward can be time-intensive, frequently requiring several weeks. This extended training period significantly reduces the throughput of such experiments, making it less feasible for high-volume or large-scale studies.

To address these limitations, we have recently developed the Sinking Platform Test (SPT), a novel paradigm for mice that requires minimal resources and labor. The SPT utilizes instinctual negative reinforcement, where mice climb onto a visible platform to escape from a water tank. This approach significantly shortens the training duration, with the current training protocol requiring only 8 days, during which mice typically master the task by day 5. On the 9th day, persistence is evaluated based on the number of platforms climbed as they are repeatedly submerged. Unlike other tasks, the SPT enables the study of persistence in response to a real stressor, providing a unique opportunity to examine persistence as a key component of resilience. Additionally, the SPT offers several distinct advantages over other methods, such as eliminating the need for food restriction and supporting a relatively high-throughput approach. A comparison of the methodologies and limitations of existing rodent protocols designed to measure persistence is presented in Table 1.

Table 1:

Persistence test currently available in literature.

Protocol	Species	Food restriction	Duration	Number of daily sessions	Reference
Operant effort and delay-discounting procedure	Rat	Yes	Starting from 3 weeks	1 session/day (32 min/session)	Floresco et al., 2008
Effort-based decision	Mouse	Yes	Starting from 6 weeks	30 trials/session/day	Pardo et al., 2012
Long Alley	Mouse	Yes	14 days	6 sessions/day (at least 80 seconds)	Sauce et al., 2018
Weight-lifting task	Rat	Yes	Starting from 3 weeks	1 session /day (max 1 hr/session)	Porter and Hillman, 2019
Effort-based decision making	Mouse	Yes	10 weeks	1 session/day (30 min/session)	Yang et al., 2020
Sinking platform test	Mouse	No	9 days	4 session/day (max 2 min/session)	Floris et al., 2024

In the following section, we will outline the detailed procedural protocol of the SPT, emphasizing the specific refinements made to better capture persistence in the context of a stressful environment. Here, we present key methodological details of the published procedure, including the statistical tools employed in the analysis, to equip researchers with the necessary resources to replicate our study.

Methodological elements and experimental steps

The SPT has been developed in adult C57BL/6J mice, housed 3–4 per cage (except for specific experimental procedures, i.e. social isolation and exercise experiments) with free access to food and water on a 12-hour light/dark schedule. Mice are acclimated for at least one week before beginning behavioral procedures. Before the experiment, it should be ensured that animals do not have any sensory or motor impairments that could affect testing.

The apparatus is a galvanized steel cylindrical water tank with a diameter of 91.5 cm (3 feet) and a height of 61 cm (2 feet). Two custom-made steel rods, each 90.7 cm long (35.7 inches), are placed parallel to the tank’s diameter and 11 cm (4.33 inches) apart, level with the tank’s rim. Around the tank’s circumference, eight equidistant spatial reference points are labeled alphabetically, with points A and E situated diametrically opposite on the midline between the rods. Four additional points (I, J, K, and L) are marked on the rods, each 30 cm (11.8 inches) apart (Figure 1A). For the equipment setup, the tank is filled with 30 cm (11.8 inches) of water maintained at a temperature of 27 ± 2°C. The water temperature, room luminosity, and ambient noise levels should be controlled and kept consistent throughout all procedures (specifically, room temperature 27 ± 2°C, room luminosity 400 lux, and ambient noise 50 dB).

Figure 1:

(A) Apparatus used for the sinking platform test. The platform locations are also reported in the panel. In the center of the galvanized steel tank, two metal rods allow for the placement of the central platforms (specifically, I, J, K, and L). (B) Depiction of the platform: The circular platform is equipped with a hemispherical base and a metal handle with a curved end for suspension from the tank’s rim. Detailed platform dimensions are provided in the text. (C) Overview of the training protocol: The table outlines the sequence of the three training phases (days 1–3: Fixed ratio; days 4–6: Transition; days 7–8: Progressive ratio) and the pseudorandom organization of sessions, trials, and platform placement throughout the training regimen (in bold are reported the central platforms, distributed throughout the training to avoid thigmotaxis-based strategy).

The platforms are 3D-printed using gray acrylic filament and measure 7 cm (2.76 inches) in diameter and 1 cm (0.39 inches) in thickness, with a conjoined hemisphere (5-cm diameter = 1.97 inches) at the bottom to ensure stability in water. Each platform is attached to a 29 cm-long metal rod (11.4 inches), allowing it to be suspended from the tank’s edge. The configuration of each platform is detailed in Figure 1B.

Additional materials include: a thermometer to monitor and maintain water temperature; stopwatches to monitor the duration of each session as well as the test; towels to dry the mice at the end of each session; spreadsheets and pens to register the sequence of each experiment and annotate for any potential observed abnormality; an overhead camera to place at least 2 m (6.56 feet) above the tank; behavioral tracking software to monitor and quantify movements throughout the experiment.

Training is organized into several daily blocks, each comprising four sessions at least 30 minutes apart. Every session ends with an “exit trial” where the mouse is removed from the water once it reaches a visible platform, which is positioned 1 cm (0.39 inches) above the water level at one of twelve possible locations. Mice typically show improvement in reaching the platforms within the first 3–5 days. To enhance outcomes, we tested two training conditions: continuous reinforcement after each successful climb and occasional platform submersion according to a progressive ratio schedule, making successes increasingly rare. The latter approach resulted in significantly greater persistence during testing, as shown by a higher number of platforms reached (Floris et al., 2024). This outcome aligns with the PREE, applied here to negative reinforcement.

In our settings, at least two trained experimenters conduct both the training and the subsequent testing. Prior to the procedure, animals should gain familiarity with the operators. Daily preparation should include: gathering all supplies (towels, stopwatches, etc.), cleaning the tank, and filling it with water at 27 ± 2 °C. The platform is set at the correct level and positioned according to a schematic (Figure 1A), with perimeter locations labeled A-H and interior positions labeled I-L (with the interior platforms facing outward). The training protocol has been refined to an 8-day regimen divided into three phases (a schematic is reported in Figure 1C).

Fixed-ratio phase (Days 1–3):

Each session includes a single “exit trial” with platforms placed at different positions. Mice are gently placed in the center of the tank, with the timer starting as they enter the water. At least one of the four platforms is placed in one of the 4 central positions, to promote active seeking of the platform rather than thigmotaxis-based strategies. Operators should ensure that the mice do not float or engage in thigmotaxis (swimming along the tank’s edge). If these behaviors occur, the experimenters gently prod the mice either to stimulate swimming or to move the mouse away from the edge, respectively. To promote active searching, at least one platform is placed at one of the four central points. Each trial should be limited to 2 minutes, if a mouse fails to reach the platform within this time, the operator gently guides it there. After a mouse successfully climbs the platform with all four limbs, the mouse is removed using the platform to reinforce the rescue association, then dried and returned to its home cage.

Transition phase (Days 4–6):

This phase introduces “sinking trials”, where one operator submerges the platform while another presents a new visible platform in a different location, with each session concluding with an “exit trial”. This phase is best handled by two operators, to ensure smooth platform placement, sinking, and removal. One researcher should be responsible for submerging the platform to prompt the mouse to swim to the next platform, while the second researcher sets up the new platform. Alternating these roles between researchers helps prevent bias and ensures consistency in the mice’s habituation to different handling procedures, thus maintaining the integrity of behavioral assessments and minimizing operator-specific confounding effects.

Progressive-ratio phase (Days 7–8):

The difficulty increases, culminating in five consecutive “sinking trials” before the final “exit trial”. The same procedural recommendations issued for the transition phase should be applied during this stage.

The analysis of training progression is estimated using the Mean Session Latency to reach Platforms (MSLP), calculated as the average of the four mean session latencies calculated for each individual session throughout the day, as depicted in the following formula:

$$MSLP=\frac{{\sum }_{s=1}^n\frac{latenc{y}_t}{n}}{4}$$

Where s=session (n=4) and t=trial (with n depending on the day of the training).

For example, let’s suppose an animal on the 8^th day of the training performs as follows:

	Latency to each platform (s)
1st session (1 platform)	5
2nd session (2 platforms)	7, 4
3rd session (4 platforms)	10, 8, 5, 7
4th session (6 platforms)	5, 3, 7, 3, 10, 8

The average latency for each session will be calculated:

	Latency to each platform (s)	Mean latency (s)
1st session (1 platform)	5	5
2nd session (2 platforms)	7, 4	5.5
3rd session (4 platforms)	10, 8, 5, 7	7.5
4th session (6 platforms)	5, 3, 7, 3, 10, 8	6

The MSLP will be calculated as the average of the four mean latencies, namely: <mi>. Thus, the MSLP for this set will be indicated at 6 s.

A representative graph showing the learning curve of mice exposed to SPT is reported in Figure 2A.

Figure 2:

(A) Graph depicting the progression of mean session latencies to reach platforms (MSLP) across the 8-day multi-phase training protocol in both male and female mice. The “P” indicates the first day when mice reached a performance plateau, meaning their average time to reach a platform did not significantly differ from day 4 onward. Data were analyzed by two-way ANOVA (main effect of time, F(7,154)=55.73, p<0.0001; main effect of sex, F(1,22)=0.11, p=0.74; interaction effect, F(7,154)=1.312, p=0.248). (B) Number of platforms reached by male and female mice during the test of the SPT. Data were analyzed by one-way ANOVA (F(1,22)=0.472, p=0.499, partial η²=0.021). (C) Kaplan-Meier survival curves for males and females in the SPT. Data were analyzed by Mantel-Cox test (χ²(1)=1.501, p=0.220). (D) Binning analysis of male and female performance during the test day of the SPT (main effect of time, F(4,88)=40.32, p<0.0001; main effect of sex, F(1,22)=0.402, p=0.53; interaction effect, F(4,88)=2.022, p=0.098). Original data from Floris et al., 2024.

Training curve analysis is customarily performed using a multi-way repeated-measures ANOVA, followed by post-hoc comparisons for each day. A training performance plateau is defined as the earliest day on which overall performance across groups does not exhibit statistically significant differences from subsequent days (as determined via post-hoc analyses of the main effect of time). The plateau is typically observed around the 4th or 5th day of training. However, if differences persist throughout the last three days, training should be extended to achieve stability — defined as the condition in which performance remains statistically consistent over at least three consecutive days.

When the SPT is employed to assess the acute effects of one or more drugs (i.e., when the drug is administered only on the day of testing, rather than during the training phase), it is essential to use the performance on the final day, as measured by MSLPs, to define each treatment group. This ensures that all groups demonstrate statistically equivalent performance levels, thereby minimizing the potential bias arising from differential training effects. To achieve this, we recommend the use of stratification strategies to ensure an even distribution of performance levels across all groups. Conversely, when the SPT is used to evaluate a drug under a chronic regimen (extending beyond the training period), it is imperative to ensure that performance across groups has reached a plateau. If this criterion is not met, training should be extended until a plateau is attained.

After at least three consecutive days of plateau in performance (i.e., statistically comparable MSLPs), the test session may be performed. It involves a 5-minute sequence of sinking trials presented in a pseudorandom order. The number of platforms climbed during the test serves as an index of persistence, reflecting the mouse’s tendency to continue making escape attempts despite repeated failures. Test analysis is performed by inferential statistics, by comparing the number of platforms climbed in each group. Depending on the experimental design, these comparisons can be made using either one-way or multi-way ANOVA (Figure 2B). Additionally, group performance can be assessed using Kaplan-Meier survival analysis (Figure 2C). An alternative approach is to examine differences in the number of platforms climbed within each minute-long interval during the test. This binning method allows for the detection of subtle differences in performance over time (Figure 2D).

It is crucial to ensure that any observed differences in persistence are not due to variations in motor activity. To address this, a video-based behavioral tracking system should be employed, using footage captured by an overhead camera. This approach helps confirm that differences in performance are genuinely related to persistence and not confounded by differences in locomotor activity.

Based on our experience, we recommend at least 8–12 mice per experimental group. Given that the test is likely to induce learning reversal of the escape strategy learnt during training, it is not recommended to use animals more than once.

Validation of the sinking platform test as a method to screen depressive phenotype

As mentioned above, persistence is often considered a dimension of resilience, particularly in the context of psychological resilience. Individuals who demonstrate persistence are often better equipped to overcome difficulties and maintain a positive outlook, which can contribute to overall resilience. While depression is characterized by feelings of hopelessness, lack of motivation, and a reduced capacity to find pleasure in life (anhedonia), persistent individuals are more likely to continue engaging in goal-directed activities even when faced with setbacks.

For example, persistent efforts in maintaining social connections, pursuing hobbies, or sticking to a routine can provide structure and purpose, reducing the risk of depressive symptoms. Moreover, persistence can promote a sense of mastery and achievement, which are important for self-esteem and emotional well-being. This can help buffer against the negative thought patterns and feelings of helplessness that are common in depression. Thus, fostering persistence through behavioral interventions, therapy, or supportive environments could potentially reduce the risk of developing depression or aid in its treatment. In summary, persistence can contribute to reducing the risk of depression by promoting positive coping mechanisms, goal-directed behavior, and a sense of control over one’s life.

Based on these premises, we hypothesized that the SPT may be useful in screening for both antidepressant and depressogenic effects of different interventions. In line with this idea, we found that chronic administration of established antidepressants like fluoxetine or imipramine results in a significant increase in platform-climbing behavior (Floris et al., 2024). Conversely, both acute and chronic administration of haloperidol, a dopamine antagonist, reduces this persistence, highlighting its depressogenic effects (Floris et al., 2024).

The sensitivity of SPT to environmental factors is also noteworthy. Mice subjected to six weeks of social isolation exhibit a marked reduction in SPT performance, reflecting the impact of chronic stress on motivation and resilience. Notably, we found that the effects of social isolation are effectively rescued by chronic imipramine and voluntary running, demonstrating the assay’s capacity to detect the therapeutic effects of antidepressant interventions (Floris et al., 2024).

Compared to traditional methods for screening antidepressant and depressogenic drugs, the SPT offers several distinct advantages. It is a relatively simple, cost-effective, and high-throughput procedure that can be easily implemented in a laboratory setting. Moreover, the SPT provides a direct measure of persistence—a key component of resilience—that may be more relevant to the underlying mechanisms of depression than other behavioral assays.

As reviewed by Hasler (Hasler et al., 2004), depression encompasses a range of psychopathological and neurobiological endophenotypes. Therefore, having a specific tool like the SPT, providing a sensitive and reliable measure of motivation and resilience to dissect persistence, could be critically important in preclinical research. Its ability to detect changes in persistence following various interventions makes it a valuable tool for screening both antidepressant and depressogenic interventions. Furthermore, the insights gained from SPT studies could help uncover the biological mechanisms that drive persistence and resilience, ultimately guiding the development of novel treatments for depression.

Future directions

3R.

A critical challenge of the Sinking Platform Test (SPT) is its reliance on animal models, necessitating adherence to the 3R principle —Replacement, Reduction, and Refinement— which is a cornerstone of ethical research involving animals. The SPT demonstrates a more refined approach compared to other behavioral assays, such as the Forced Swim Test (FST), which is commonly used for screening antidepressants. While both tests assess stress-related behaviors in rodents, the SPT incorporates specific elements that align more closely with the 3R principles.

The focus of SPT on evaluating cognitive persistence allows for a more precise behavioral assessment, offering greater opportunities for Refinement. For example, the SPT allows for modifications that reduce animal stress, such as maintaining water at room temperature, in contrast to the colder water used in the FST, and minimizing stress through training. The FST, on the other hand, subjects animals to continuous exposure to an inescapable stressor, with limited options for reducing discomfort. Additionally, the SPT’s design permits gradual adaptation to the test environment, further reducing stress and enhancing alignment with the Refinement principle.

An area for further optimization of the SPT involves reducing water-related stress, particularly during the early stages of training. For instance, exposing naïve mice to multiple platforms within the tank during initial sessions could mitigate the stress associated with water exposure. To address this, we are developing a modified training protocol in which animals encounter multiple platforms during the first two days, with each platform serving as an “exit trial.” This adaptation is expected to accelerate the formation of rescue associations and enhance the overall learning process while simultaneously minimizing stress for the animals.

Another important consideration is the test’s inherent design, which involves repeated failure during each climb. This repetitive failure could potentially be perceived as an inescapable scenario by the mice, inducing significant stress and possibly contributing to neurobiological changes in the brain. These potential outcomes highlight the need for further investigation to assess the extent of stress induced by the test and its long-term implications for brain function. Addressing these concerns will not only refine the SPT further but also ensure its ethical and scientific rigor as a tool for understanding stress and resilience in animal models.

An additional critical consideration is the opportunity to utilize the SPT for examining persistence across multiple species. This approach confers significant methodological advantages by facilitating the exploration of interspecies variability in behavioral responses and stress-related adaptations. Such cross-species testing enhances the translational value of the findings, offering a more comprehensive understanding of the mechanisms underlying persistence. A logical next step in the development of the SPT would be its adaptation to other rodent species commonly used in experimental research, such as rats and voles. Compared to mice, rats display distinct behavioral patterns and physiological responses to various stimuli, making them an excellent model for evaluating the versatility and generalizability of the SPT. Testing the SPT in rats could provide valuable insights into the robustness of the method and further underscore its innovation in assessing persistence. Voles, another promising candidate for SPT adaptation, offer unique advantages due to their highly social behavior and well-characterized neurobiological mechanisms underlying social bonds and stress responses. Incorporating voles into SPT testing could expand the method’s applicability to research areas involving social and affiliative behaviors, as well as resilience in the context of social stressors. Validating the SPT across these and other rodent species would not only enhance its utility in diverse research contexts but also solidify its role as a flexible and comprehensive tool for behavioral studies.

Rigor and reproducibility.

Procedural modifications to the SPT may be introduced to minimize variables that could introduce bias or inconsistency in the results. From this perspective, modifying protocols to reduce the inherent stressfulness of the test (for example, by including multiple platforms in the initial training phases) may lead to more consistent learning outcomes across subjects, and ensure that all animals reach a similar level of task proficiency before the actual testing, thereby improving the comparability of results. Another key challenge is the need for operators for the manual lowering of platforms. This process must be done swiftly to prevent animals from clinging during descent or ascent. Automating this process would be a key improvement also to reduce potential variabilities stemming from interindividual differences across operators and enhance experimental consistency. To address this issue, our group is developing the Aqua Smartsink system, an automated apparatus to maneuver platforms throughout the training protocol and the test. Aqua Smartsink features a circular tank made from non-reflective, easily sanitized anodized aluminum (Figure 3A–B). Rough-surfaced circular platforms are strategically positioned as primary escape routes for the mice, each mounted on a pneumatic cylinder that allows precise control over its elevation (Figure 3C). A DMX control system, managed through an intuitive user interface, orchestrates platform movements based on pre-programmed protocols or manual input. A ceiling-mounted camera, combined with advanced video-analysis software, tracks each mouse’s position, enabling automated platform movements triggered by the mouse’s proximity or escape attempt. This automation minimizes human interference, enhancing data accuracy and reproducibility. Aqua Smartsink meticulously records escape latency and swimming patterns, including the mice’s speed, trajectory, and search strategies. This comprehensive dataset allows for objective quantification and analysis of each mouse’s persistence in the face of escalating challenges. Insights gained from this phase will inform the development of novel virtual reality protocols for retro-translation from mice to humans.

Fig. 3.

View from the side (A) and top (B) of the Aqua SmartSink system, and platform details (C). The platforms are mounted on a pneumatic cylinder, allowing for precise control, smooth and consistent platform movement, crucial for generating repeatable experimental conditions.

Concluding statements

Our findings underscore the potential of the Sinking Platform Test (SPT) as a valuable tool for investigating the neurochemical and biological mechanisms underlying persistence in animal models. However, research on this method is still in its early stages, and further advancements are necessary to fully determine the effectiveness of SPT in measuring persistence. The opportunity to explore the biological basis of the SPT arises as new methodological developments in translational strategies and behavioral sciences create a promising environment for future progress. The field of phenotypic characterization is at a critical juncture, with the introduction of broad-ranging approaches such as transcriptomics, proteomics, metabolomics, and epigenetics. For instance, we employed bulk transcriptomics of the prefrontal cortex to investigate differences between high and low SPT performers. These studies revealed that, one day after the test, high performers exhibited lower levels of immediate early gene transcripts. This suggests that if persistence is considered a trait, reduced activation of these genes may be crucial. This could be because animals with lower concentrations of these molecules might perceive lower stress levels in response to acute stress, enabling a more sustained response. Alternatively, the reduction in gene expression might indicate a stronger perception of stress, given that the test primarily presents challenges. Further research is required to determine which interpretation best aligns with experimental data.

A critical question is whether persistence, as measured by the SPT, can predict resilience to chronic stressors like chronic mild stress and social defeat stress. Additionally, research should examine the role of neurochemical factors in resilience and the potential of the SPT in screening antidepressants, particularly since chronic fluoxetine and imipramine have been shown to improve SPT performance. Nonetheless, further research is required to evaluate the effects of other antidepressants within the SPT paradigm, administered in both chronic and acute settings. Such investigations are essential to determine whether different classes of antidepressants, with varying mechanisms of action, produce similar or distinct outcomes in the context of the SPT. This could help clarify the broader utility of the SPT as a tool for assessing drug efficacy and specificity, potentially leading to a deeper understanding of how antidepressant treatments influence persistence-related behaviors and other neurobiological processes underlying depression. Moreover, expanding the range of compounds studied could aid in the identification of novel therapeutic targets and improve our ability to tailor interventions to individual patient needs based on their specific psychopathological profiles.

It is also essential to emphasize the importance of retrotranslation from rodents to humans, potentially utilizing virtual reality in tasks analogous to the SPT. Given the high-throughput nature of the SPT, this test could be integrated into a broader neurophenomic approach to explore the dimensions of persistence.