Monitoring Fine and Associative Motor Learning in Mice Using the Erasmus Ladder

Alice Staffa; Moumita Chatterjee; Ariadna Diaz-Tahoces; Felix Leroy; Isabel Perez-Ota&#241;o

doi:10.3791/65958

JoVE Journal > Neuroscience

Neuroscience

Monitoring Fine and Associative Motor Learning in Mice Using the Erasmus Ladder

Published: December 15, 2023

doi:

10.3791/65958

Alice Staffa*¹, Moumita Chatterjee*¹, Ariadna Diaz-Tahoces*¹, Felix Leroy¹, Isabel Perez-Otaño¹

¹Instituto de Neurociencias, Sant Joan d’Alacant,Spain – Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández

Summary

This article presents a protocol that allows a non-invasive and automated assessment of fine motor performance, as well as adaptive and associative motor learning upon challenges, using a device called the Erasmus Ladder. Task difficulty can be titrated to detect motor impairment ranging from major to subtle degrees.

Abstract

Behavior is shaped by actions, and actions necessitate motor skills such as strength, coordination, and learning. None of the behaviors essential for sustaining life would be possible without the ability to transition from one position to another. Unfortunately, motor skills can be compromised in a wide array of diseases. Therefore, investigating the mechanisms of motor functions at the cellular, molecular, and circuit levels, as well as understanding the symptoms, causes, and progression of motor disorders, is crucial for developing effective treatments. Mouse models are frequently employed for this purpose.

This article describes a protocol that allows the monitoring of various aspects of motor performance and learning in mice using an automated tool called the Erasmus Ladder. The assay involves two phases: an initial phase where mice are trained to navigate a horizontal ladder built of irregular rungs ("fine motor learning"), and a second phase where an obstacle is presented in the path of the moving animal. The perturbation can be unexpected ("challenged motor learning") or preceded by an auditory tone ("associative motor learning"). The task is easy to conduct and is fully supported by automated software.

This report shows how different readouts from the test, when analyzed with sensitive statistical methods, allow fine monitoring of mouse motor skills using a small cohort of mice. We propose that the method will be highly sensitive to evaluate motor adaptations driven by environmental modifications as well as early-stage subtle motor deficits in mutant mice with compromised motor functions.

Introduction

A variety of tests have been developed to assess motor phenotypes in mice. Each test gives information on a specific aspect of motor behavior¹. For example, the open field test informs on general locomotion and anxiety state; the rotarod and walking beam tests on coordination and balance; footprint analysis is about gait; the treadmill or running wheel on forced or voluntary physical exercise; and the complex wheel is about motor skill learning. To analyze mouse motor phenotypes, investigators must perform these tests sequentially, which involves a lot of time and effort and often several animal cohorts. If there is information at the cellular or circuitry level, the investigator normally opts for a test that monitors a related aspect and follows from there. However, paradigms that discriminate different aspects of motor behavior in an automated way are lacking.

This article describes a protocol to use the Erasmus Ladder²^,³, a system that allows comprehensive assessment of a variety of motor learning features in mice. The main advantages are the reproducibility and sensitivity of the method, along with the ability to titrate motor difficulty and to separate deficits in motor performance from impaired associative motor learning. The main component consists of a horizontal ladder with alternate high (H) and low (L) rungs equipped with touch-sensitive sensors that detect the position of the mouse on the ladder. The ladder is made of 2 x 37 rungs (L, 6 mm; H, 12 mm) spaced 15 mm apart from each other and positioned in a left-right alternating pattern with 30 mm gaps (Figure 1A). Rungs can be moved individually to generate various levels of difficulty, that is, creating an obstacle (raising the high rungs by 18 mm). Coupled with an automated recording system and associating modifications of the rung pattern with sensory stimuli, the Erasmus ladder tests for fine motor learning and adaptation of motor performance in response to environmental challenges (appearance of a higher rung to simulate an obstacle, an unconditioned stimulus [US]) or association with sensory stimuli (a tone, a conditioned stimulus [CS]). Testing involves two distinct phases, each assessing improvement in motor performance over 4 days, during which mice undergo a session of 42 consecutive trials per day. In the initial phase, mice are trained to navigate the ladder to assess "fine" or "skilled" motor learning. The second phase consists of interleaved trials where an obstacle in the form of a higher rung is presented in the path of the moving animal. The perturbation can be unexpected to assess "challenged" motor learning (US-only trials) or announced by an auditory tone to assess "associative" motor learning (Paired trials).

The Erasmus ladder has been developed relatively recently²^,³. It has not been extensively used because setting up and optimizing the protocol required focused effort and was specifically designed to assess cerebellar-dependent associative learning without exploring in detail its potential to reveal other motor deficits. To date, it has been validated for its ability to unveil subtle motor impairments linked to cerebellar dysfunction in mice³^,⁴^,⁵^,⁶^,⁷^,⁸. For instance, connexin36 (Cx36) knockout mice, where gap junctions are impaired in olivary neurons, display firing deficits due to lack of electrotonic coupling but the motor phenotype had been hard to pinpoint. Testing using the Erasmus ladder suggested that the role of inferior olivary neurons in a cerebellar motor learning task is to encode precise temporal coding of stimuli and facilitate learning-dependent responses to unexpected events³^,⁴. Fragile X Messenger Ribonucleoprotein 1 (Fmr1) knockout mouse, a model for Fragile-X-Syndrome (FXS), exhibits a well-known cognitive impairment along with milder defects in procedural memory formation. Fmr1 knockouts showed no significant differences in step times, missteps per trial, or motor performance improvement over sessions in the Erasmus Ladder but failed to adjust their walking pattern to the suddenly appearing obstacle compared to their wild-type (WT) littermates, confirming specific procedural and associative memory deficits³^,⁵. Furthermore, cell-specific mouse mutant lines with defects in cerebellar function, including impaired Purkinje cell output, potentiation, and molecular layer interneuron or granule cell outputs, exhibited problems in motor coordination with altered acquisition of efficient step patterns and in the number of steps taken to cross the ladder⁶. Neonatal brain injury causes cerebellar learning deficits and Purkinje cell dysfunction that could also be detected with the Erasmus Ladder⁷^,⁸.

In this video, we present a comprehensive step-by-step guide, which details the setup of the behavioral room, the behavioral test protocol, and subsequent data analysis. This report is crafted to be accessible and user-friendly and is designed specifically to assist newcomers. This protocol provides insight into different phases of motor training and expected motor patterns that mice adopt. Finally, the article proposes a systematic workflow for data analysis using a powerful non-linear regression approach, complete with valuable recommendations and suggestions for adapting and applying the protocol in other research contexts.

Protocol

In the current study, adult (2-3 months old) C57BL/6J mice of both sexes were used. Animals were housed two to five per cage with ad libitum access to food and water in an animal unit under observation and maintained in a temperature-controlled environment on a 12 h dark/light cycle. All procedures were conducted in accordance with the European and Spanish regulations (2010/63/UE; RD 53/2013) and were approved by the Ethical Committee of the Generalitat Valenciana and the animal welfare committee of the Universidad Miguel Hernández.

1. Behavioral room setup

Reserve the behavioral testing room every day at the same time and establish the list and order of mice to be used, as well as arrangements for their hosting.
Keep the experimental mice outside the testing room so they do not hear the sounds of the air compressor and Erasmus Ladder tones when not being tested.
Check that all components of the Erasmus Ladder system are in order and ready to use: the network router, the computer with the software (see Table of Materials), the air compressor, two goal boxes, and the ladder with the rungs properly positioned.
Extensively clean the goal boxes, ladder, and rungs with water after each animal and with water and 70% ethanol at the end of each training day.

2. Behavioral test protocol

Create an experiment and enter the protocol into the software (Supplementary Figure S1).
1. Turn on the software.
2. To create an experiment, choose File | New experiment | New or Set up | Experiment protocol.
  NOTE: The default protocol, used in this study, is named EMC and was designed at Erasmus University Medical Center, Rotterdam.
3. Give the experiment a name and click OK.
4. Check that the default EMC protocol selected consists of 4 days of undisturbed sessions (42 undisturbed trials per day) and 4 days of challenge sessions (42 daily mixed trials: undisturbed, CS-only (tone), US-only (obstacle), Paired (obstacle announced by tone) (see Figure 1B). In the right side panel, also check the light cue (3 s maximum duration), air cue (45 s maximum duration), and tailwind (Yes in all the trial types), used to encourage the mouse to cross the ladder, and the tone (250 ms, Yes only in CS-only and Paired trials).
5. To create a different protocol, choose Set up | Experiment protocol | New | From scratch or Copy from the EMC protocol and simply modify it, editing the table lines related to number of sessions (days of experiment) and number and type of trials per day.
  NOTE: Resting time, cues type and activation, duration, intensity, and interval can also be adapted according to the experimental questions.
6. To open the session list and name the subjects, choose Setup | Session List.
7. Click on Add Subjects and Variables.
8. Enter each specific Mouse Identifier, Birth Date, Sex, Genotype, and relevant categories, following the ordered list of mice.
Start the session (Supplementary Figure S2).
1. Before starting, check that the software is open, then turn on the Ladder.
2. Check that the air compressor is connected and switched on.
3. To open the Acquisition window, open the Experiment created.
4. Choose Acquisition | Open Acquisition.
5. Place the mouse with the identifier indicated by the software in the starting goal box (right side of the ladder).
6. Select the mouse identifier to acquire in the first session.
7. Click on Start Acquisition.
8. Press the red ladder menu knob 3x. Check that the session starts and automatically controls and records mouse movements until the end of the last trial of the session.
End the session.
1. Check that at the end of the 42^nd trial, the display shows the messages Sending Data and Acquired.
2. Return the mouse to the home cage.
3. Clean the ladder and the goal boxes.
4. Place the next mouse and repeat from step 2.2.6 onwards.
Perform the selected type of session every day until the end of the protocol. Repeat steps 2.2 and 2.3 every day according to the selected protocol.
Export the data (Supplementary Figure S2).
1. To visualize the recorded data, choose from the Analysis menu, Trial Statistics, Session statistics, and Group Statistic & Charts.
  NOTE: Data can be downloaded as a spreadsheet with data for individual trials and the means of the same trial types within a session. Sessions can also be filtered by variables chosen for specific analysis.
2. Click on the Export button at the top-right corner choosing the file format (spreadsheet) and folder location.
3. Right-click on the automatically generated charts and select Save to File as *.jpg.

3. Data analysis

NOTE: A list of parameters is automatically measured by the Erasmus Ladder based on the instantaneous recording of the activities of the touch-sensitive sensors. For analysis, output parameters selected by the user are organized and processed in the spreadsheets. Along with the software-generated graphs, users can generate graphs using the graphing software of choice to visualize specific changes in different parameters over sessions.

Choose specific parameters to analyze basal motivation or anxiety states, sensory responses, motor performance, and fine motor learning over the first 4 days.
1. Select and plot control parameters, including resting time in the goal box and time to exit the goal box after the resting period in response to light and air cues (Figure 2A).
  NOTE: Resting times or response to cues are relatively constant in WT mice. Other parameters such as frequency of exits are basically negligible in WT mice-the animals rarely leave the rest box without the cues or come back once in the ladder, resulting in frequencies of exit equal to 1 per trial. If an animal goes out before cues are applied, an airflow gets activated forcing the mouse to return to the goal box; this is not counted as a trial by the software.
2. Select and plot the time on ladder after cues, measured as the time spent crossing the ladder once the mouse leaves the goal box (Figure 2B).
  NOTE: A power non-linear regression is a robust method for evaluating learning. The Pearson or Spearman coefficients (R) will provide a measure of whether the data fitting is good (R values close to one when the animals learn/improve over sessions; R values close to 0 imply that the data are constant and mice do not learn).
3. Select and plot stepping pattern parameters such as the percentage of trials with missteps as a sensitive learning parameter (Figure 2C).
  1. Define a correct step as a step from a high rung to another high rung (H-H), irrespective of the length of the step. Consider step types that involve a lower rung as missteps.
  2. Divide correct steps and missteps into short and long steps, backsteps, and jumps depending on the length and directionality of the step between the rungs pressed (see Figure 1A).
Select and plot specific parameters to evaluate challenged motor learning (US-only trials) and associative learning (paired trials) over the last 4 days.
1. Select and plot the time on ladder after cues (Figure 3).
2. Select and plot the percentage of trials with missteps (Figure 4A).
3. Select and plot the pre and post perturbation step times, defined as a ms precision difference between rung activation just before (control step) and after the obstacle (adapted step) on the same side of the ladder (Figure 4B).
  NOTE: Pre vs post-perturbation step times analysis should be performed to compare data inside each type of session. The parameter measures the ability of the mice to predict and overcome the obstacles during associative learning.
Analyze the data with dedicated statistical software (e.g., SigmaPlot). Perform a power non-linear regression analysis of data collected from the same trial type across sessions to describe the learning process more efficiently and use Two-Way Repeated Measures (RM) ANOVA to compare between trial types.

Representative Results

The Erasmus Ladder device, setup, and protocol applied are presented in Figure 1. The protocol consists of four undisturbed and four challenge sessions (42 trials each). Each trial is one run on the ladder between the starting and ending goal boxes. At the beginning of the session, a mouse is placed in one of the starting boxes. After a set time of 15 ± 5 s ("resting" state), the light is turned on (cue 1, for a maximum of 3 s). A light air cue (cue 2, 45 s maximum) is then applied to encourage the mice to leave the box and walk to the opposite end. The time to respond to the air cue can vary between mice and sessions and can be used as a parameter to compare motivation or anxiety states between groups. A new trial is immediately started after the mouse reaches the ending goal box.

No differences in resting time and time to respond to the light cue were observed in WT mice across days 1-4, but the time to respond to the air cue decreased slightly between days 1 and 2 (Figure 2A). Measurements of the time to cross the ladder yielded a significant learning curve from days 1 to 4 that could be fitted with a power regression curve (R = 0.50, *p = 0.047, Figure 2B). A key parameter that determines the time taken to cross the ladder is the occurrence of missteps. In line with the shortening of times on the ladder, the number of trials where mice made missteps decreased over undisturbed sessions as mice learned to walk on the upper rungs (H-H steps) and avoid the lower ones as a more efficient pattern to cross the ladder (R = 0.90, ***p < 0,0001, Figure 2C).

From days 5 to 8, the mice were subjected to challenge sessions where an unexpected obstacle (US) was introduced (one rung is randomly raised by 18 mm above the stepping surface). In some trials, a tone (CS, 90 dB, 15 kHz tone lasting 250 ms) is presented 250 ms before the US perturbation (see Figure 1B).

With the beginning of challenge sessions on day 5, animals required more time to cross the ladder during US-only trials because of the unpredicted introduction of the obstacle (day 4: 5.01 s; Figure 2B; day 5: 7.84 s; Figure 3; paired t-test,*p < 0.039). Mouse performance improved from days 5 to 8, yielding a significant learning curve across US-only sessions (R = 0.50, *p = 0.045, Figure 3, orange). In associative learning trials, where the obstacle was paired with a tone, animals completed the daily sessions significantly faster relative to US-only trials (R = 0.63, Figure 3, purple; two-way RM ANOVA, *p = 0.028). Finally, in control trials when the tone was presented alone (CS-only), a significant learning curve that resembled undisturbed sessions was reported (R = 0.82, ***p < 0.001, Figure 3, blue).

Analysis of the step patterns provided additional confirmation and enhanced sensitivity in detecting differences between US-only and associative trials. Figure 4A shows how the percentage of trials with missteps remained constant throughout US-only trials (R = 0.01, p = 0.90, orange), while a significant decrease in trials with missteps was observed during paired sessions (R = 0.61, *p = 0.01, purple). Figure 4B shows a significant difference between pre and post perturbation step times in US-only trials (two-way RM ANOVA, *p = 0.05) but not in paired trials where mice learned faster to overcome the obstacle. All the variables studied and the statistical tests applied are reported in Supplementary Table S1.

Figure 1: System, protocol, and parameters. (A) The Erasmus Ladder consists of a horizontal ladder flanked by two goal boxes. The cartoon represents the ladder with alternated high and low rungs and the main parameters recorded, including step types (normal steps, filled line; or missteps, dashed line) and pre and post perturbation step time defined as the time that the mouse needs to overcome an obstacle (unconditioned stimulus; higher rung) announced or not by a tone (conditioned stimulus). (B) The protocol consists of four undisturbed and four challenge sessions (one session/day, 42 trials/session) that allow for separately analyzing fine motor learning (undisturbed and CS-only in blue), challenged motor learning (US-only, in orange), and associative motor learning (paired CS + US, in purple). Abbreviations: H = high; L = low; CS = conditioned stimulus; US = unconditioned stimulus. Please click here to view a larger version of this figure.

Figure 2: Motor performance of WT mice during undisturbed sessions. (A) Resting time in the goal box (constant, 15 s), time to respond to cues: light (constant, 3 s) and air (variable); over days 1-4 of undisturbed sessions. (B) Time to cross the ladder after cue (light and air) during undisturbed sessions. (C) Percentage of trials in each undisturbed session where the animal missed a step. A power regression analysis was used to study the learning progress (R= 0.50: *p = 0.047, R= 0.90 ***p < 0.0001, respectively, n = 4 mice). Abbreviation: WT = wild type. Please click here to view a larger version of this figure.

Figure 3: Performance of WT mice during challenge sessions. Average time on the ladder after cues during days 5-8 for US-only (orange), paired (purple), and CS-only (light blue) trials. A power non-linear regression analysis was used to study the learning progress (*p = 0.047, **p = 0.0093, ***p < 0.001, n=4 mice). Two-way RM ANOVA to compare trial types (*p = 0.028, **p = 0.008, n=4 mice, two males and two females, mean ± SEM). Abbreviations: CS = conditioned stimulus; US = unconditioned stimulus. Please click here to view a larger version of this figure.

Figure 4: Changes in mouse step patterns over challenge sessions. (A) Percentage of trials per session where the animal missed a step during US-only and paired sessions. A power regression analysis was used to study the learning process (*p = 0.013) and a Two-way RM ANOVA for comparison between trial types (*p = 0.032, n = 4 mice). (B) Pre and post-perturbation step time (s) in US-only and paired sessions throughout the sessions. Two-way Repeated Measures ANOVA, *p < 0.05, n = 4 mice, two males and two females, mean ± SEM. Please click here to view a larger version of this figure.

Supplementary Figure S1: Software interface: how to create an experiment and select a protocol. Screenshots from the software illustrating the workflow described in protocol step 2.1, covering steps 2.1.4 to 2.1.8. Please click here to download this File.

Supplementary Figure S2: Software interface: how to start the session and export the data. Screenshots from the software illustrating the workflow described in protocol steps 2.2 and 2.5, covering steps 2.2.4 to 2.2.7 and 2.5.1 to 2.5.3. Please click here to download this File.

Supplementary Table S1: Statistical table. Description of all the variables studied and the statistical tests applied, reported in Figure 2B,C, Figure 3, and Figure 4A,B. Please click here to download this File.

Discussion

The Erasmus Ladder presents major advantages for motor phenotype assessment beyond current approaches. Testing is easy to conduct, automated, reproducible, and allows researchers to assess various aspects of motor behavior separately using a single mouse cohort. In the current study, reproducibility allowed the generation of robust data with a small number of WT mice taking advantage of the features of the device, experimental design, and analysis methods. For instance, when compared to traditional beam-walk assays, the addition of motivational cues (air and light) to enter the ladder path and the tailwind to complete the trial increases consistency and skips the need for experimenter intervention which is a major source of variability.

An air compressor system is required to generate an airflow that can be adjusted to the direction and position of the mouse. The airflow creates a 30 km/h headwind from the opposite direction when a mouse attempts to leave the goal box before the scheduled trial initiation, making the mice return to the goal box. It also generates a constant tailwind (1 to 16 km/h) during the trial until the mouse completely crosses the ladder and enters the opposite goal box. Without the pressurized air as an incentive to cross the ladder, mice frequently pause on the rungs and reverse directions at a leisurely pace, which introduces an exploratory variable counterproductive for the analysis.

The standard protocol described here provides measurements of basic fine motor coordination and learning (undisturbed sessions), as well as of adaptation to challenges and associative motor learning (challenge sessions) over a time span of 8 days. The task is easy for WT mouse strains typically used for neuroscience studies such as the C57Bl6J mice used here, and is safe, with no injuries observed in any of the testing sessions. In addition, we did not detect signs of fatigue when compared to other motor tests such as the rotarod or treadmill.

Over the 4 day initial phase, WT mice master the skill and cross the ladder by learning to adopt the most efficient running pattern (H-H steps) and missteps occur rarely by day 4 (Figure 2B,C). On day 5 of the second phase, mice are slower when they first encounter the obstacle but quickly adapt (Figure 3, US-only). Coupling the obstacle with a conditioning stimulus (tone) facilitates learning to the extent that trial duration equals trials where the obstacle is not presented (Figure 3, paired). Of note, the number of trials with missteps remained constant throughout US-only trials (Figure 4A), while a significant decrease was observed in paired sessions (Figure 4A), confirming the effectiveness of the associative learning process.

We propose a workflow for the analysis of representative parameters provided by the Erasmus Ladder software. The power regression analysis allowed us to register significant learning curves and detect differences in challenged versus associative learning using four WT mice. Based on additional literature and pilot experiments, experimental designs involving mutant or treated mice might require increasing mouse numbers to 7-10 mice⁴^,⁵^,⁶. In our hands, 42 trials per session was an optimal number to obtain robust data with a small mouse cohort because averaging several trials decreases variability. While the number might appear high, each 42 trial session takes between 15 min and 35 min, and 12-16 mice can be reasonably tested per day. Trial duration (including the resting time and response to cues plus time to traverse the ladder) varies between 20 s and 50s, depending on the training day and type of trial.

Nevertheless, the versatility of the system will allow researchers to design customized protocols by adjusting various settings, including the number of sessions and trials per day, the intensity and duration of cues and CS, as well as the nature of the US. For example, our data showed a rapid learning curve in WT mice, particularly between day 1 and day 2 after performance reaches a plateau (Figures 2B,C). This suggested that the additional 2 days might not be strictly necessary for testing basic motor learning in undisturbed sessions, and modifications to the standard protocol can be implemented by reducing the training duration to just 2 days. Yet this adaptation might not be suitable for the second phase of the protocol, which incorporates interleaved undisturbed, US-only, CS-only, and paired trials. The stimuli are presented randomly and unexpectedly to assess specific behaviors, and the need to divide experimental trials into these four categories makes 42 a suitable number of trials required for statistical power. Thus, a reorganization of the protocol would need to assess the feasibility of reducing the number of undisturbed trials or increasing specific challenge trials. The inter-stimulus interval (ISI) between CS (90 dB, 15 kHz tone) and US, here set at 250 ms, can also be varied to study the stimulus-response association. This kind of adjustment would allow researchers to titrate the level of difficulty or focus on different behaviors according to the scientific question.

To date, the Erasmus ladder has been mostly used to detect subtle defects in motor coordination of cerebellar origin. For instance, missteps are a measure of whole-body locomotor coordination. In this study, young adult mice were used but mice as young as P23 have been used by others to study the maturation of locomotor functions⁷^,⁸. Ipsilateral pathologies of central origin could be studied through discriminative analysis of the position of the mouse's right and left paws. Finally, mastering motor skills in the Erasmus ladder likely engages other motor control circuits, involving the basal ganglia, motor cortex, and connecting pathways, including the corpus callosum. Combining this behavioral paradigm with cellular, molecular, and circuit techniques will be useful to investigate circuit mechanisms that mediate motor adaptation and can be harnessed to boost motor learning. One such example would be to study the influence on axonal myelination, which is highly sensitive to the acquisition of fine motor skills in mouse models of demyelination⁹^,¹⁰.

Disclosures

The authors have nothing to disclose.

Acknowledgements

We acknowledge the audiovisual technician and video producer Rebeca De las Heras Ponce as well as the head veterinarian Gonzalo Moreno del Val, for the supervision of good practice during mouse experimentation. Work was funded by grants from the GVA Excellence Program (2022/8) and the Spanish Research Agency (PID2022143237OB-I00) to Isabel Pérez-Otaño.

Materials

C57BL/6J mice (Mus musculus)	Charles Rivers
Erasmus Ladder device	Noldus, Wageningen, Netherlands
Erasmus Ladder 2.0 software	Noldus, Wageningen, Netherlands
Excel software	Microsoft
Sigmaplot software	Systat Software, Inc.

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Staffa, A., Chatterjee, M., Diaz-Tahoces, A., Leroy, F., Perez-Otaño, I. Monitoring Fine and Associative Motor Learning in Mice Using the Erasmus Ladder. J. Vis. Exp. (202), e65958, doi:10.3791/65958 (2023).

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