Bussey-Saksida Touch Screen Operant Conditioning Chamber

Introduction

The Bussey-Saksida Touch Screen Operant Conditioning Chamber was developed by Dr. Jennifer Bussey and Dr. David Saksida who designed the chamber to address the limitations of traditional operant conditioning chambers, which they found were often less interactive and less adaptable for studying complex cognitive processes in animals.

The chamber can be used for multiple purposes, such as in psychological testing to assess visual discrimination, working memory, task-switching abilities, and other cognitive processes in animals. In pharmacological studies, the chamber enables researchers to investigate how various substances or treatments, such as drugs, affect behavior and cognitive abilities. In the field of comparative neuroscience, the device allows for the comparison of behavior across different species, offering insights into animal cognition and the neurological foundations of behavior.

The motivation behind the invention was to create a more flexible and sophisticated tool that could support a broader range of behavioral tasks, particularly those that require the animal to interact with visual stimuli. Traditional operant conditioning chambers were typically limited to simple tasks like pressing levers or responding to cues in the environment. In contrast, the touch screen chamber allows for more complex, task-specific interactions, such as visual discrimination, working memory tests, and cognitive flexibility exercises, which are crucial for studying higher-order cognitive functions.

By incorporating a touch screen interface, the chamber provides a versatile platform for testing a variety of cognitive processes, including attention, memory, and decision-making. It also facilitates more precise data collection, allowing researchers to monitor detailed behaviors and responses with greater accuracy. The invention was intended to push the boundaries of behavioral neuroscience and provide more accurate and nuanced insights into animal cognition, learning, and the effects of different substances or conditions on behavior.

The Bussey-Saksida Touch Screen Operant Conditioning Chamber was developed to study advanced cognitive and behavioral research in animals, facilitating a deeper understanding of the neural mechanisms underlying learning and memory.

Software

• Our Operant system has multiple software options to best suit your needs.
  • Our Conductor software controls the system directly
  • For those looking for protocol set-up combined with video tracking and analysis, the system is compatible with  ConductVision, Noldus Ethovision XT,and ANY-Maze
• Each operant chamber includes a control box to control the chamber .
• The main controller connects to the PC via a USB (RS-232) cable and communicates with the software package on PC.
•  Protocols can be set per chamber or per group so that both control and treatment groups can be tested simultaneously with the same or different parameters.
• The software supports up to 16 chambers simultaneously and allows individual chambers to start/stop and run independently

Each order comes with the option of one task type as default. Popular paradigms include:

• Maze Engineers can collaborate closely with the user to enhance software packages to their needs
• Software customizations and 2+ paradigm packages upon request

Need tracking software?

Training Protocol

1. Habituation (Acclimation Phase)

Purpose: To familiarize the animal with the chamber environment.

• Place the animal in the chamber for a specified period (e.g., 10–30 minutes per day) over several days.
• No specific tasks are given; the goal is to reduce stress and encourage exploration.
• Food or liquid rewards may be dispensed to create a positive association with the chamber.

2. Pre-Training (Shaping Behavior)

Purpose: To teach the animal to interact with the touch screen.

• The screen displays simple stimuli (e.g., a bright shape or a dot).
• The animal is rewarded (e.g., with a food pellet or liquid reward) for touching the screen at the correct location.
• Incorrect responses may trigger a short timeout (e.g., 5 seconds with a blank screen) to encourage correct behavior.
• This phase continues until the animal consistently touches the screen.

3. Task Training (Experimental Phase)

Purpose: To train the animal on a specific cognitive or behavioral task.
Examples of Tasks:

• Visual Discrimination Task: The screen presents two images, and the animal must touch the correct one to receive a reward.
• Paired-Associate Learning: The animal learns associations between specific stimuli and must select the correct pair.
• Delayed Matching-to-Sample: A sample image appears, disappears, and then reappears alongside a distractor; the animal must choose the original image.
• Attentional Set-Shifting: The animal must learn and switch between different stimulus-response rules.

Procedure:

• The animal completes multiple trials per session (e.g., 30–100 trials per session, depending on species and task complexity).
• Difficulty may be adjusted dynamically (e.g., reducing stimulus size, introducing delays, or adding distractors).
• Incorrect responses may result in timeouts or correction trials.

4. Data Collection and Analysis

Purpose: To record behavioral performance and analyze cognitive function.
Procedure:

• Automatically collect data on response accuracy, reaction time, learning curves, and task efficiency.
• Compare performance across experimental conditions (e.g., drug treatment vs. control, lesion studies, genetic models).
• Statistical analyses (e.g., ANOVA, t-tests) are conducted to assess behavioral patterns.

5. Experimental Adjustments & Endpoints

• Based on initial results, researchers may modify task parameters, introduce new conditions, or add pharmacological manipulations.
• The experiment concludes once the animal reaches predefined learning criteria or after a set number of sessions.

Example Protocol for the Rodent Continuous Performance Task (rCPT)

The rCPT task in rodents is based on the human Continuous Performance Task used in clinical neuropsychology. Its main purpose is to measure sustained attention and impulse control over extended periods.

The paradigm requires a touch screen to display 5 simple images in a randomised order. The subject must touch the target image to receive a pellet or liquid reward and withhold touching other images.

Performance Metrics

• Hit rate: proportion of correct touches to target stimuli.

• False alarm rate: touches to non-target stimuli.

• Reaction time: time between stimulus onset and touch.

• d′ (d-prime): sensitivity index combining hit and false alarm rates.

• Vigilance decrement: decline in performance over the session.

Go/No-Go Protocol

Stage 0 — Habituation (1–2 sessions)

• Turn the sound-attenuating chamber house light on and deliver free rewards every 20–30 s. End the session when the subject collects ≥30 rewards/session.

Stage 1 — Autoshaping to touch (2–3 sessions)

• Present the touch screen as a large white screen where any touch delivers a reward. The stimulus remains until the subject touches the screen (no limited hold yet).

• Criterion: ≥60 touches/session until reward collection latency is stable.

Stage 2 — Must-touch target (2–5 sessions)

• Present the target image only (e.g., white square) centrally and require the subject to touch the screen within a limited hold time (e.g. start 5 s → reduce to 2 s).

• No response = omission; re-initiate after Inter-Trial Interval (ITI).

• Criterion: ≥80% correct responses, omissions ≤20%.

Stage 3 — Introduce non-target (Go/No-Go, easy ratio) (3–6 sessions)

• Randomized trials: 70% target (Go), 30% non-target (No-Go).

• Responses:

  • Target + touch → reward (Hit); no touch → miss.

  • Non-target + no touch → correct rejection; touch → false alarm (timeout).

• Use longer ITI after false alarms to discourage impulsivity (e.g., +2 s).

• Criterion: d′ ≥ 1.5 (or Hit ≥70% with FA ≤30%) for two consecutive sessions.

Stage 4 — Balanced difficulty (50/50) (3–7 sessions)

• 50% target, 50% non-target; limited hold 1–2 s; ITI variable (mean 5 s).

• Criterion: d′ ≥ 1.8 (typical), omissions ≤15%, stable across 2–3 sessions.

Stage 5 — Stability & parameter tightening (optional, 3–5 sessions)

• Shorten limited hold (→1 s), increase ITI (3–7 s), shrink stimulus size or add distractors (e.g., brief houselight flicker).

• Establish baseline across ≥3 stable days before experiments.

Stage 6 — Test sessions (experimental manipulations)

• Keep parameters fixed from baseline.

• If pharmacological interventions or lesions used in subjects, counterbalance the trial order and include washout days as needed.

Trial structure (per trial)

1. ITI

2. Stimulus onset (target or non-target) + limited hold timer starts

3. Response window:

   • Target: touch = Hit (reward); no touch = Miss

   • Non-target: no touch = Correct Rejection; touch = False Alarm (timeout)

4. Outcome period (reward delivery or timeout)

5. Next ITI (longer after FA to discourage impulsivity)

Data Analysis

1. Basic Performance Analysis

• Accuracy (%): The proportion of correct responses out of total trials.
• Response Latency: The time taken to respond to a stimulus (e.g., touching the correct image).
• Trial Completion Rate: Percentage of trials completed in a session, which can indicate motivation or fatigue.
• Error Rate: Frequency of incorrect responses, which helps assess task difficulty and cognitive impairment.

2. Learning and Progression Analysis

• Learning Curves: Plotting accuracy over multiple sessions to assess improvement over time.
• Trial-to-Criterion Analysis: Number of trials required to reach a predefined accuracy threshold (e.g., 80% correct in three consecutive sessions).
• Performance Stability: Analyzing variability in responses across sessions to determine if performance is consistent.

3. Reaction Time and Decision-Making Analysis

• Reaction Time Distribution: Examining how response times vary across correct and incorrect trials.
• Speed-Accuracy Tradeoff: Analyzing whether faster responses lead to more errors, often visualized in scatterplots or regression analyses.
• Choice Preference Bias: Evaluating whether the subject prefers specific stimuli or locations on the screen.

4. Comparative and Statistical Analyses

• ANOVA (Analysis of Variance): Used for comparing performance across different experimental groups (e.g., drug-treated vs. control).
• t-Tests: Comparing mean accuracy or reaction times between two conditions.
• Regression Analysis: Identifying relationships between variables, such as whether increased task difficulty leads to longer reaction times.
• Repeated Measures Analysis: Used for within-subject comparisons across multiple testing sessions.

5. Cognitive and Behavioral Assessments

• Cognitive Flexibility Analysis: Examining performance in set-shifting tasks where rules change mid-task.
• Memory Performance Analysis: Evaluating performance in delayed-matching tasks by measuring how accuracy declines with increasing delay durations.
• Attention Analysis: Tracking omissions (missed responses) to assess attentional lapses.

6. Pharmacological and Neuroscience Studies

• Dose-Response Curves: Analyzing behavioral changes across different drug dosages.
• Neuropsychological Comparisons: Comparing subjects with brain lesions, genetic modifications, or pharmacological interventions.
• Machine Learning Approaches: Using algorithms to classify behavioral patterns or predict future performance based on past data.

Summary

The Bussey-Saksida Touch Screen Operant Conditioning Chamber has become a widely used tool in behavioral neuroscience, offering an advanced platform for investigating cognitive functions such as learning, memory, attention, and decision-making. Unlike traditional operant conditioning chambers, which rely on levers and nose pokes, this touch screen-based system allows for more complex cognitive tasks that parallel those used in human psychological assessments. Researchers have used this apparatus across a variety of domains, including neuropsychology, pharmacology, and neurodegenerative disease models.

References

Bari, A., Theobald, D. E. H., Caprioli, D., Mar, A. C., Aidoo-Micah, A., Dalley, J. W., & Robbins, T. W. (2015). Dissociable effects of noradrenaline and dopamine lesions on probabilistic learning and reversal in the rat. Journal of Neuroscience, 35(3), 1636–1646.

Bussey, T. J., Saksida, L. M., & Rothblat, L. A. (2012). Dissecting cognitive function in rodent models of schizophrenia using the touchscreen testing method. Neuropharmacology, 62(3), 1351–1361.

Graybeal, C., Feyder, M., Schulman, E., Saksida, L. M., Bussey, T. J., & Brigman, J. L. (2014). The touchscreen operant platform for assessing executive function in mice. Nature Protocols, 9(11), 2738–2752.

Heath, C. J., Bussey, T. J., & Saksida, L. M. (2016). Motivational assessment in mice using the touchscreen operant platform. Frontiers in Behavioral Neuroscience, 10, 126.

Horner, A. E., Heath, C. J., Hvoslef-Eide, M., Kent, B. A., Kim, C. H., Bussey, T. J., & Saksida, L. M. (2013). The touchscreen operant platform for testing learning and memory in rats and mice. Nature Protocols, 8(10), 1961–1984.

Kamin, D., Sachs, B. D., & Sawa, A. (2017). The impact of dopamine depletion on decision-making and learning in Parkinson’s disease models. Behavioural Brain Research, 332, 128–139.

Mar, A. C., Horner, A. E., Nilsson, S. R., Kent, B. A., Kim, C. H., & Saksida, L. M. (2013). Progressive cognitive decline in a model of Alzheimer's disease: A touchscreen-based assessment. Brain Research, 1527, 108–120.

Talpos, J. C., McTighe, S. M., Dias, R., Saksida, L. M., & Bussey, T. J. (2010). Trial-unique, delayed nonmatching-to-location (TUNL): A novel touchscreen-based automated task for assessing working memory in rats. Journal of Neuroscience Methods, 191(2), 199–209.

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