This work was supported by the NINDS grant #NS054148.

All procedures involving animals were approved by the Michigan State University Institutional Animal Care and Use Committee (IACUC).
1. Experimental Setup
<ol>
	<li>Use an operant conditioning box which consists of a five-hole nosepoke wall on one side and a food delivery trough on the opposite side.
	<ol>
		<li>The center nosepoke hole is considered as a &#34;fixation&#34; hole and the four other holes (two on each side of the fixation hole) are considered motor target holes. Each hole is equipped with a tri-color LED and an infrared beam emitter-detector system that detects when the animal enters and retracts from the fixation hole.</li>
		<li>Use a programmable tone generator to generate single frequency tones with millisecond precision and connect it to a speaker mounted inside the operant box. Control the tone generator and nosepokes through the behavioral tracking system using the appropriate software. Use a hardware and software system that provides millisecond timescale monitoring of behavioral events and control of cues and responses. 
		Note: The amplitude of both tone and noise cues should be kept around 60 &#177; 3 dB SPL.</li>
	</ol>
	</li>
</ol>
2. Early Habituation
<ol>
	<li>Restrict the subject&#39;s food intake gradually to ~5 g&#160;per 100 g&#160;of the subject&#39;s normal weight (e.g. over the course of 3 days). The subject should maintain 85-90% of their ad libitum weight.</li>
	<li>Habituate the subject to handling by the experimenter and familiarize the subject with the apparatus from the first day of starting the food deprivation protocol. Start handling the animal and place it in the operant conditioning box while providing food pellets in the pellet trough to encourage the subject to explore the cage and get familiar with the reward delivery location.</li>
</ol>
3. Subject Training
<ol>
	<li>General notes
	<ol>
		<li>The task suggested here needs precise coordination between perception of an auditory cue, minimizing movements during the delay period and movement execution.</li>
		<li>Gradually train the subject step-by-step to prepare them for the final desired behavior.</li>
		<li>Make sure that at the end of each step, the subject maintains &#62;75% behavioral performance for at least three consecutive sessions before progressing to the next stage.</li>
		<li>Once the final stage is reached, keep the subject on the protocol for a week to ensure the performance is maintained at the desirable level.</li>
	</ol>
	</li>
	<li>Start: Familiarize the subject with the nosepoke holes, food delivery port and the association between the flashing holes and reward.
	<ol>
		<li>Select one out of the four targets on a random schedule.</li>
		<li>Play the Go cue (a white auditory noise) and keep the LED inside the hole flashing (0.3 sec pulse duration).</li>
		<li>Set the software to reward the subject upon visits to the hole.</li>
		<li>Time-out the trial after 30 sec&#160;if the hole is not visited and start a new trial.</li>
		<li>Do not reward any visits to the incorrect holes.</li>
	</ol>
	</li>
	<li>Target Selection: Punish erroneous visits to the nonselected holes.
	<ol>
		<li>Upon visits to incorrect holes, terminate the trial followed by 5 sec&#160;of black-out. 
		Note: During a black-out epoch, the fixation hole LED is turned off in the cage. This means that the subject cannot initiate a trial and needs to wait until the fixation hole LED starts flashing.</li>
		<li>Select a new hole and start a new trial.</li>
	</ol>
	</li>
	<li>Nosepoke: Train the subject to poke inside the fixation hole to start a trial.
	<ol>
		<li>Flash a yellow LED inside the fixation hole.</li>
		<li>Upon visiting the fixation hole immediately play the Go cue and start a new trial.</li>
		<li>Penalize incorrect visits by 5 sec&#160;of black-out.</li>
	</ol>
	</li>
	<li>Delay: Teach the subject to maintain their nose inside the fixation hole for a set period of time (delay period) that is increased gradually as training progresses.
	<ol>
		<li>Wait for the subject to visit the fixation hole.</li>
		<li>Terminate the trial if the subject retracts within 500 msec. Otherwise, play the Go cue.</li>
		<li>Penalize premature retractions by a black-out period for 7 sec.</li>
		<li>Reward the correct visits by delivering a food pellet.</li>
	</ol>
	</li>
	<li>Two Cues (with Light): Increase and randomize the delay period length and introduce the auditory instruction cue.
	<ol>
		<li>Increase the length of the delay period to an average of 1.5 sec.</li>
		<li>Choose a random delay period length at each trial based on a uniform density between 1.3-1.8 sec.</li>
		<li>Introduce the instruction cue as a single frequency auditory tone pulsed in triplets, with a pulse duration of 150 msec and interpulse interval of 100 msec.
		<ol>
			<li>Play the instruction cue immediately after the subject enters the fixation hole.</li>
			<li>Assign two instruction cues to each of the targets.</li>
			<li>Only use one cue associated for each target at this stage.</li>
		</ol>
		</li>
		<li>Let the subject use both auditory and visual cues to select the target hole.</li>
	</ol>
	</li>
	<li>Two Cues (without Light): Train the subject to only use auditory cues.
	<ol>
		<li>Turn off the flashing LEDs inside the target holes so that the subject would only use auditory instruction cues.</li>
	</ol>
	</li>
	<li>Four Cues: Introduce the two other cues to the sequence of randomly presented instruction cues and repeat sections 3.5.3-3.6.1.</li>
</ol>
4. Behavioral Data Analysis
<ol>
	<li>Success Rate: Define success rate as the percentage of correct visits to the targets divided by the total number of trials.
	<ol>
		<li>Measure the success rate at each stage of training.</li>
	</ol>
	</li>
	<li>Error types:
	<ol>
		<li>Premature retraction: measure the percentage of trials timed-out due to early retractions from the fixation hole.</li>
		<li>Comission error: Calculate the percentage of failed trials when the subject visits an uninstructed target</li>
		<li>Omission Error: Calculate the percentage of errors when the subject does not visit any of the targets after trial initiation.</li>
	</ol>
	</li>
	<li>Measured variables:
	<ol>
		<li>Reaction Time (RT): For each trial, measure the delay between the onset of the Go cue and the subject retracting from the fixation hole.</li>
		<li>Time to Target (TT): Measure the duration between the subject retraction from the fixation hole and entering the target hole.</li>
	</ol>
	</li>
</ol>

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The authors declare&#160;no competing financial interests.

Rats have been widely used in neuroscience research for over a century. Since Thorndike&#39;s introduction of the concept of the law of effect in cats34, operant conditioning has been the standard approach to test different aspects of animal behavior. Many neuroscience experiments involving decision making and motor preparation include a delay period between the instruction cues and the action interval. It is desirable to minimize movements during these delay periods to reduce any confounds to the neural data ...

Studying the relation between neurophysiology and behavior is the ultimate goal in systems neuroscience. Historically, there has been a tradeoff between animal model choice and behavioral repertoire1-5. While simple organisms like sea slugs6 or squids7 have been used extensively to study properties of single ion channels, neurons and simple neural circuits, higher order species are needed to study more complex functions such as spatial navigation, decision making8-11 and cognitive control12-14. Despite being a standard animal model for human like behavior, use of nonhuman primates prompts cost and ethical considerations that precludes their use across a wide range of experiments in a single laboratory setting15-18. Simpler animal models such as rodents are generally preferred19, provided they have similar neural substrates underlying the behaviors of interest.
There's ample evidence suggesting that rodents share similar cortical and subcortical structures as those found in primates20-22. Rodents are also known to integrate information across multiple sensory modalities to guide their action23-25, for example, by coordinating whisking and sniffing during exploratory behavior26 or by integrating auditory and visual/olfactory events25,27.
Here we describe a framework for operant conditioning of rodents used to test cognitive tasks28-32. In this framework, subjects are required to fixate inside a nosepoke hole and maintain their snout inside the hole until the presentation of a go cue. The behavioral task is a five-hole nosepoke design that is conventionally used for 5-choice serial reaction time task studies. During the delay period, a range of instruction cues is presented to guide the subject to perform an action. This framework can easily be modified to suit a wide range of experiments in which training the subject to minimize its overt movement over a brief interval is needed. This permits studying the extent to which spiking activity of individual neurons is affected by specific cues during this interval. The protocol can minimize the training time and can reduce across-subject learning variability. A schematic flowchart of the task is shown in Figure 1.

<table border="0" cellpadding="0" cellspacing="0" width="757">
	<colgroup>
		<col />
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		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:359px;"> 5-HOLED NOSE POKE WITH 3STIM CUE LIGHT - RAT CAGE</td>
			<td style="width:112px;">Coulbourn</td>
			<td style="width:119px;"> H21-06M/R</td>
			<td style="width:167px;"> </td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:359px;">TEST CAGE</td>
			<td style="width:112px;">Coulbourn</td>
			<td style="width:119px;">H10-11R-TC</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:359px;">Graphic State Software</td>
			<td style="width:112px;">Coulbourn</td>
			<td style="width:119px;"> </td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:359px;">PROGRAMMABLE TONE/NOISE GENERATOR</td>
			<td style="width:112px;">Coulbourn</td>
			<td style="width:119px;">A12-33</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:359px;">Dustless Precision Pellets</td>
			<td style="width:112px;">Bio-Serv</td>
			<td style="width:119px;">F0165</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:359px;"> SPEAKER MODULE</td>
			<td style="width:112px;">Coulbourn</td>
			<td style="width:119px;">H12-01R</td>
			<td></td>
		</tr>
	</tbody>
</table>

a fully automated rodent conditioning protocol for sensorimotor integration and cognitive control experiments

Rodents have been traditionally used as a standard animal model in laboratory experiments involving a myriad of sensory, cognitive, and motor tasks. Higher cognitive functions that require precise control over sensorimotor responses such as decision-making and attentional modulation, however, are typically assessed in nonhuman primates. Despite the richness of primate behavior that allows multiple variants of these functions to be studied, the rodent model remains an attractive, cost-effective alternative to primate models. Furthermore, the ability to fully automate operant conditioning in rodents adds unique advantages over the labor intensive training of nonhuman primates while studying a broad range of these complex functions.
Here, we introduce a protocol for operantly conditioning rats on performing working memory tasks. During critical epochs of the task, the protocol ensures that the animal's overt movement is minimized by requiring the animal to 'fixate' until a Go cue is delivered, akin to nonhuman primate experimental design. A simple two alternative forced choice task is implemented to demonstrate the performance. We discuss the application of this paradigm to other tasks.

The suggested framework enables training the subject on a range of cognitive tasks. Here we implemented an instructed delay task designed to investigate the mechanisms of goal-directed actions in the rodent prefrontal cortex. Figure 1 shows a flowchart of the experimental design.
To ensure that the subject understands the task requirement at every step, performance measures should be continuously assessed. Figure 2 shows an example performance of one subject a...

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A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments

A fully automated protocol for rodent operant conditioning is proposed. The protocol relies on precise temporal control of behavioral events to investigate the extent to which this control influences neural activity underlying sensorimotor integration and cognitive control experiments.

Rodents have been traditionally used as a standard animal model in laboratory experiments involving a myriad of sensory, cognitive, and motor tasks. ...

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10.5K Views.  Michigan State University. A fully automated protocol for rodent operant conditioning is proposed. The protocol relies on precise temporal control of behavioral events to investigate the extent to which this control influences neural activity underlying sensorimotor integration and cognitive control experiments.

Video: A Fully Automated Rodent Conditioning Protocol for Sensorimotor Integration and Cognitive Control Experiments

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional Change Card Sort task, participants switch from sorting cards one way, such as shape, to sorting them a different way, such as color. Adjusting behavior in this way exacts a small performance cost, or switch cost, such that responses are typically slower and more error-prone on switch trials in which the sorting rule changes as compared to repeat trials in which the sorting rule remains the same. The ability to flexibly adjust behavior is often said to develop gradually, in part because behavioral costs such as switch costs typically decrease with increasing age. Why aspects of higher-order cognition, such as behavioral flexibility, develop so gradually remains an open question. One hypothesis is that these changes occur in association with functional changes in broad-scale cognitive control networks. On this view, complex mental operations, such as switching, involve rapid interactions between several distributed brain regions, including those that update and maintain task rules, re-orient attention, and select behaviors. With development, functional connections between these regions strengthen, leading to faster and more efficient switching operations. The current video describes a method of testing this hypothesis through the collection and multivariate analysis of fMRI data from participants of different ages.

This video presents a method of examining age-related changes in functional connectivity of cognitive control networks engaged by targeted tasks/processes. The technique is based on multi-variate analysis of fMRI data.

The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional ...

Automated Visual Cognitive Tasks for Recording Neural Activity Using a Floor Projection Maze

Neuropsychological tasks used in primates to investigate mechanisms of learning and memory are typically visually guided cognitive tasks. We have developed visual cognitive tasks for rats using the Floor Projection Maze1,2&#160;that are optimized for visual abilities of rats permitting stronger comparisons of experimental findings with other species.
In order to investigate neural correlates of learning and memory, we have integrated electrophysiological recordings into fully automated cognitive tasks on the Floor Projection Maze1,2. Behavioral software interfaced with an animal tracking system allows monitoring of the animal's behavior with precise control of image presentation and reward contingencies for better trained animals. Integration with an in vivo electrophysiological recording system enables examination of behavioral correlates of neural activity at selected epochs of a given cognitive task.
We describe protocols for a model system that combines automated visual presentation of information to rodents and intracranial reward with electrophysiological approaches. Our model system offers a sophisticated set of tools as a framework for other cognitive tasks to better isolate and identify specific mechanisms contributing to particular cognitive processes.

We describe protocols for training rats for chronic electrophysiological recordings in fully automated cognitive tasks on a Floor Projection Maze.

Neuropsychological tasks used in primates to investigate mechanisms of learning and memory are typically visually guided cognitive tasks. We have ...

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device (ALDM) Test Systems

Fagot &#38; Paleressompoulle1 and Fagot &#38; Bonte2 have published an automated learning device (ALDM) for the study of cognitive abilities of monkeys maintained in semi-free ranging conditions. Data accumulated during the last five years have consistently demonstrated the efficiency of this protocol to investigate individual/physical cognition in monkeys, and have further shown that this procedure reduces stress level during animal testing3. This paper demonstrates that networks of ALDM can also be used to investigate different facets of social cognition and in-group expressed behaviors in monkeys, and describes three illustrative protocols developed for that purpose. The first study demonstrates how ethological assessments of social behavior and computerized assessments of cognitive performance could be integrated to investigate the effects of socially exhibited moods on the cognitive performance of individuals. The second study shows that batteries of ALDM running in parallel can provide unique information on the influence of the presence of others on task performance. Finally, the last study shows that networks of ALDM test units can also be used to study issues related to social transmission and cultural evolution. Combined together, these three studies demonstrate clearly that ALDM testing is a highly promising experimental tool for bridging the gap in the animal literature between research on individual cognition and research on social cognition.

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems

Fagot &#38; Paleressompoulle1 have published an automated learning device (ALDM) aimed at testing individual cognitive abilities in semi-free ranging monkeys. The main goal of our protocol is to use a network of ALDM test units to study social cognition in non-human primates.

Fagot &#38; Paleressompoulle1 and Fagot &#38; Bonte2 have published an automated learning device (ALDM) for the study of cognitive abilities of monkeys ...

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Advances in robotic systems have resulted in prostheses for the upper limb that can produce multifunctional movements. However, these sophisticated systems require upper limb amputees to learn complex control schemes. Humans have the ability to learn new movements through imitation and other learning strategies. This protocol describes a structured rehabilitation method, which includes imitation, repetition, and reinforcement learning, and aims to assess if this method can improve multifunctional prosthetic control. A left below elbow amputee, with 4 years of experience in prosthetic use, took part in this case study. The prosthesis used was a Michelangelo hand with wrist rotation, and the added features of wrist flexion and extension, which allowed more combinations of hand movements. The participant&#8217;s Southampton Hand Assessment Procedure score improved from 58 to 71 following structured training. This suggests that a structured training protocol of imitation, repetition and reinforcement may have a role in learning to control a new prosthetic hand. A larger clinical study is however required to support these findings.

As prosthetic development moves towards the goal of natural control, harnessing amputees&#8217; inherent ability to learn new motor skills may enable proficiency. This manuscript describes a structured rehabilitation protocol, which includes imitation, repetition, and reinforcement learning strategies, for improved multifunctional prosthetic control.

Advances in robotic systems have resulted in prostheses for the upper limb that can produce multifunctional movements. However, these sophisticated ...

Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

We demonstrate a method for capturing emotional response to beverages and liquefied foods in a sensory evaluation laboratory using automated facial expression analysis (AFEA) software. Additionally, we demonstrate a method for extracting relevant emotional data output and plotting the emotional response of a population over a specified time frame. By time pairing each participant's treatment response to a control stimulus (baseline), the overall emotional response over time and across multiple participants can be quantified. AFEA is a prospective analytical tool for assessing unbiased response to food and beverages. At present, most research has mainly focused on beverages. Methodologies and analyses have not yet been standardized for the application of AFEA to beverages and foods; however, a consistent standard methodology is needed. Optimizing video capture procedures and resulting video quality aids in a successful collection of emotional response to foods. Furthermore, the methodology of data analysis is novel for extracting the pertinent data relevant to the emotional response. The combinations of video capture optimization and data analysis will aid in standardizing the protocol for automated facial expression analysis and interpretation of emotional response data.

A protocol for capturing and statistically analyzing emotional response of a population to beverages and liquefied foods in a sensory evaluation laboratory using automated facial expression analysis software is described.

We demonstrate a method for capturing emotional response to beverages and liquefied foods in a sensory evaluation laboratory using automated facial ...

Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder with pathological involvement of upper and lower motoneurons, subsequently leading to progressive loss of motor and speech abilities. In addition, cognitive functions are impaired in a subset of patients. To evaluate these potential deficits in severely physically impaired ALS patients, eye-tracking is a promising means to conduct cognitive tests. The present article focuses on how eye movements, an indirect means of communication for physically disabled patients, can be utilized to allow for detailed neuropsychological assessment. The requirements, in terms of oculomotor parameters that have to be met for sufficient eye-tracking in ALS patients are presented. The properties of stimuli, including type of neuropsychological tests and style of presentation, best suited to successfully assess cognitive functioning, are also described. Furthermore, recommendations regarding procedural requirements are provided. Overall, this methodology provides a reliable, easy to administer and fast approach for assessing cognitive deficits in patients who are unable to speak or write such as patients with severe ALS. The only confounding factor might be deficits in voluntary eye movement control in a subset of ALS patients.

Cognitive deficits are common in about one third of patients with amyotrophic lateral sclerosis, a neurological condition leading to progressive impairments in speech and movement abilities. To conduct cognitive tests in patients unable to speak or write a reliable and easy to administer eye-tracking paradigm was developed.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder with pathological involvement of upper and lower motoneurons, subsequently leading to ...

Automated, Long-term Behavioral Assay for Cognitive Functions in Multiple Genetic Models of Alzheimer's Disease, Using IntelliCage

Multiple factors&#8212;such as aging and genes&#8212;are frequently associated with cognitive decline. Genetically modified mouse models of cognitive decline, such as Alzheimer&#39;s disease (AD), have become a promising tool to elucidate the underlying mechanisms and promote the therapeutic advances. An important step is the validation and characterization of expected behavioral abnormality in the models, in the case of AD, cognitive decline. The long-term behavioral investigations of laboratory animals to study the effect of aging demand substantial efforts from researchers. The IntelliCage system is a high-throughput and cost-effective test battery for mice that eliminates the need for daily human handling. Here, we describe how the system is utilized in the long-term phenotyping of a genetic Alzheimer&#39;s disease model, specifically focusing on the cognitive functions. The experiment employs repeated battery of tests that assess spatial learning and executive functions. This cost-effective age-dependent phenotyping allows us to identify the transient and/or permanent effects of genes on various cognitive aspects.

Automated, Long-term Behavioral Assay for Cognitive Functions in Multiple Genetic Models of Alzheimer&#039;s Disease, Using IntelliCage

This paper describes a protocol for cognitive assessments for genetic models of the Alzheimer&#39;s disease using the IntelliCage system, which is a high throughput automated behavioral monitoring system with operant conditioning.

Multiple factors&#8212;such as aging and genes&#8212;are frequently associated with cognitive decline. Genetically modified mouse models of cognitive ...

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Investigating the interactions among multiple participants is a challenge for researchers from various disciplines, including the decision sciences and spatial cognition. With a local area network and dedicated software platform, experimenters can efficiently monitor the behavior of the participants that are simultaneously immersed in a desktop virtual environment and digitalize the collected data. These capabilities allow for experimental designs in spatial cognition and navigation research that would be difficult (if not impossible) to conduct in the real world. Possible experimental variations include stress during an evacuation, cooperative and competitive search tasks, and other contextual factors that may influence emergent crowd behavior. However, such a laboratory requires maintenance and strict protocols for data collection in a controlled setting. While the external validity of laboratory studies with human participants is sometimes questioned, a number of recent papers suggest that the correspondence between real and virtual environments may be sufficient for studying social behavior in terms of trajectories, hesitations, and spatial decisions. In this article, we describe a method for conducting experiments on decision-making and navigation with up to 36 participants in a networked desktop virtual reality setup (i.e., the Decision Science Laboratory or DeSciL). This experiment protocol can be adapted and applied by other researchers in order to set up a networked desktop virtual reality laboratory.

This paper describes a method for conducting multi-user experiments on decision-making and navigation using a networked computer laboratory.

Investigating the interactions among multiple participants is a challenge for researchers from various disciplines, including the decision sciences and ...

Virtual Reality Experiments with Physiological Measures

Virtual reality (VR) experiments are increasingly employed because of their internal and external validity compared to real-world observation and laboratory experiments, respectively. VR is especially useful for geographic visualizations and investigations of spatial behavior. In spatial behavior research, VR provides a platform for studying the relationship between navigation and physiological measures (e.g., skin conductance, heart rate, blood pressure). Specifically, physiological measures allow researchers to address novel questions and constrain previous theories of spatial abilities, strategies, and performance. For example, individual differences in navigation performance may be explained by the extent to which changes in arousal mediate the effects of task difficulty. However, the complexities in the design and implementation of VR experiments can distract experimenters from their primary research goals and introduce irregularities in data collection and analysis. To address these challenges, the Experiments in Virtual Environments (EVE) framework includes standardized modules such as participant training with the control interface, data collection using questionnaires, the synchronization of physiological measurements, and data storage. EVE also provides the necessary infrastructure for data management, visualization, and evaluation. The present paper describes a protocol that employs the EVE framework to conduct navigation experiments in VR with physiological sensors. The protocol lists the steps necessary for recruiting participants, attaching the physiological sensors, administering the experiment using EVE, and assessing the collected data with EVE evaluation tools. Overall, this protocol will facilitate future research by streamlining the design and implementation of VR experiments with physiological sensors.

Virtual reality (VR) experiments can be difficult to implement and require meticulous planning. This protocol describes a method for the design and implementation of VR experiments that collect physiological data from human participants. The Experiments in Virtual Environments (EVE) framework is employed to accelerate this process.

Virtual reality (VR) experiments are increasingly employed because of their internal and external validity compared to real-world observation and ...

Visual Classical Conditioning in Wood Ants

Several species of insects have become model systems for studying learning and memory formation. Although many studies focus on freely moving animals, studies implementing classical conditioning paradigms with harnessed insects have been important for investigating the exact cues that individuals learn and the neural mechanisms underlying learning and memory formation. Here we present a protocol for evoking visual associative learning in wood ants through classical conditioning. In this paradigm, ants are harnessed and presented with a visual cue (a blue cardboard), the conditional stimulus (CS), paired with an appetitive sugar reward, the unconditional stimulus (US). Ants perform a Maxilla-Labium Extension Reflex (MaLER), the unconditional response (UR), which can be used as a readout for learning. Training consists of 10 trials, separated by a 5-minute intertrial interval (ITI). Ants are also tested for memory retention 10 minutes or 1 hour after training. This protocol has the potential to allow researchers to analyze, in a precise and controlled manner, the details of visual memory formation and the neural basis of learning and memory formation in wood ants.

We present a protocol for the classical conditioning of harnessed ants that permits researchers to study visual learning and memory formation at a level of analysis not possible with freely moving individuals.

Several species of insects have become model systems for studying learning and memory formation. Although many studies focus on freely moving animals, ...