This research was supported by RMH Neuroscience Foundation, Australia; the Australian Brain Foundation; the RACP Thyne Reid Fellowship, Australia; and by a project grant from the Cognitive Sciences and Technologies Council, Iran to Abbas Haghparast.

All procedures explained here were approved and carried out in accordance with the Guide for the Care and Use of Laboratory Animals and were approved by the Florey Institute Animal Ethics Committee or the Neuroscience Research Center.
1. Housing, Handling, and Food Restriction
<ol>
	<li>Use adult (normally 8 weeks old) male rats (any strains) and keep them in the room with a 12-h light/dark cycle.</li>
	<li>Restrict their food access to encourage the animals to perform the task. 
	Note: Housing the animals singularly is suggested, as it provides a better control of each one&#8217;s food intake.</li>
	<li>On days 1 - 3, handle the animals for approximately 5 min, 2x a day. 
	Note: Handling familiarizes the animals with human contact and decreases the level of stress and anxiety in the animals throughout the experiments.</li>
	<li>Weigh the animals after each handling session. Use the first day&#8217;s weight as the free-feeding amount and keep the animals on about 80 - 85% of their free-feeding amount.</li>
</ol>
2. Experimental Set-up
<ol>
	<li>Use a T-maze equipped with 3 partitions or arms, 2 stimulus speakers, 5 retractable doors, and 5 infrared motion sensors or infrared beam (IRB) sensors. 
	Note: The T-maze can be constructed of medium-density fiberboard (MDF) or polyvinyl chloride (PVC).</li>
	<li>Control the maze constructed here by an Arduino microcontroller.</li>
	<li>Copy the Arduino code into the computer.</li>
	<li>Download the Arduino software from the software website and install it on a computer.</li>
	<li>Connect the microcontroller to the computer using a USB port.</li>
	<li>On the computer, click the software icon, go to Tools, and then select Port.</li>
	<li>From the drop-down menu, choose the COM port (Communication port) which connects the software to the computer.</li>
	<li>Go to Tools and select Boards. From the drop-down menu, select the type of Arduino that controls the T-maze.</li>
	<li>Click Upload on the top left of the interface window. Select the Arduino code. Wait until the process finishes.</li>
	<li>Click Serial monitor at the top right of the interface window. Then, in a new pop-out window, change the baud rate to 115200.</li>
</ol>
3. Habituation to the Maze
<ol>
	<li>Prior to each session of habituation, bring the animals to the experiment room at least 1 h prior to the experiment.</li>
	<li>Leave 10 sugar pellets at each goal arm and leave all doors open. 
	Note: At this stage, there is no need to track the animals&#8217; movements (Figure 1).</li>
	<li>Days 1 - 3: Place the animals individually in the maze for periods of 10 min, 1x per day, to explore the maze with no restrictions.</li>
	<li>Days 4 - 5: Place the animals individually in the maze. Leave 2 pellets in each arm and allow them to sample the food from both sides. Remove the animal from the maze immediately after eating pellets from both sides or after 5 min of being in the maze. 
	Note: The main difference between this stage and the previous stage is that animals need to be removed from the maze immediately after eating pellets from both sides. This would familiarize an animal with being removed from the maze at the end of a trial.</li>
	<li>After each session, clean the maze&#8217;s floors with 70% ethanol and make sure the ethanol has evaporated before placing the next animal in the maze.</li>
</ol>
4. Discrimination Training
<ol>
	<li>Maze preparation 
	<ol>
		<li>Day 6: Bring the animals to the experiment room at least 1 h prior to the experiment.</li>
		<li>Run the Arduino program and set the trial number to 14 of which the first 4 trials will be forced-choice and the rest will be choice trials. 
		Note: The program will randomly generate an equal number of trials to be assigned to the left and right side of the T-maze.</li>
		<li>Before each trial begins, place 4 pellets in the goal arm which is to be cued as the HRA and 2 pellets in the other arm which is the LRA.</li>
	</ol>
	</li>
	<li>Forced-choice trial training (4 trials)
	<ol>
		<li>Pseudo-randomly block one arm before each trial so that the animal is forced to select the other arm. 
		Note: The blocked arm can be a high reward arm or a low reward arm whilst the auditory signal highlights the side of the HRA.</li>
		<li>Place an animal in the start box (Figure 1). After 5 - 7 s, simultaneously open the start gate and click Start in the Arduino&#8217;s interface window.</li>
		<li>Collect the animal immediately after eating pellets or after 5 min of being in the maze.</li>
		<li>Leave the animal in the home cage for 2 min.</li>
	</ol>
	</li>
	<li>Choice trial training (10 trials)
	<ol>
		<li>Prior to each trial, close door-B&#160;in the arm which is selected by the software to be the HRA. Leave door-A open in the opposite arm (the LRA).</li>
		<li>Place an animal in the start box (Figure 1). After 5 - 7 s, simultaneously open the start gate and click Start.</li>
		<li>Let the animal freely choose either arm. If the animal chooses the HRA, open door-A, let the animal enter the chamber, shut door-A, and open door-B immediately to give the animal access to the selected food well.</li>
		<li>If the animal chooses the LRA, open door-B in order to give the animal access to the food well.</li>
		<li>Remove the animal after it has eaten all the food in the selected food well and leave it in the home cage for 2 min.</li>
		<li>Complete the 10 choice trials for each animal and record the animal&#8217;s choice (HRA or LRA) in each trial.</li>
		<li>Calculate the percentage of high reward choice (HRC) for all choice-trials after each training session.</li>
		<li>Following the completion of 14 trails, the individual times obtained by each infrared sensor are shown in the Arduino interface window.</li>
	</ol>
	</li>
</ol>
5. Delay Training
<ol>
	<li>Once each animal has reached 80% of HRC in the discrimination training (step 4), begin the delay training by running 10 trials per day for each animal. In this stage, door-B is to be opened after only a 5 s delay when the animal chooses the HRA.</li>
	<li>If the animal reaches an HRC of 80% at the end of a training session with a 5 s delay, increase the delay to 10 s for the next training session.</li>
	<li>Once the animal has reached an HRC of 80% with a 10 s delay, increase the delay to 15 s for the next training session.</li>
	<li>Record the animal&#8217;s choice for each trial to calculate the HRC after each training session.</li>
	<li>Following the completion of the trials, the individual times obtained by each infrared sensor are shown in the Arduino interface window. 
	Note 1: The timer starts when you click Enter. The &#8216;Time_decision&#8217; is the time after the nose-poke to the IRB-1. &#8216;Time_left_1&#8217; is the time when an animal breaks IRB-1L and &#8216;Time_left_2&#8217; is when IRB-2L is broken. If the behavioral study is combined with electrophysiology or neural imaging (e.g., calcium imaging) methods, film recording is suggested for a better synchronization of the animal&#8217;s behavior to neural signals.</li>
</ol>
6. Electrophysiology (Electrode Fabrication)
<ol>
	<li>Use single or bipolar electrodes to record the local field potentials (LFPs). 
	Note: The use of bipolar electrodes is suggested because it enables local re-referencing to reduce the impact of the volume conduction. Therefore, the recorded LFP is the differential voltage between 2 electrodes with a ~200 &#956;m distance between the tips.</li>
	<li>To make a bipolar electrode, glue 2 tungsten electrodes together or wind 2 stainless-steel wires together (normally, PFA-coated stainless-steel wires with a 50 &#956;m diameter are used).</li>
	<li>Solder the grounding and recording wires to a mini plug/socket to become a connector to the electrophysiology recording system.</li>
</ol>
7. Anesthesia
<ol>
	<li>To implant the electrodes, anesthetize the rats by an intraperitoneal injection of a mixture of ketamine (100 mg/kg) and xylazine (8 mg/kg), or by administering isoflurane as described in the following steps. 
	Note: Isoflurane is recommended due to the improved control of its anesthetic depth.</li>
	<li>Use an anesthetic machine with a controlled oxygen and anesthetic vapor flow.</li>
	<li>To anesthetize the animal by isoflurane, place it in the induction chamber and set isoflurane at a rate of around 4% and oxygen at 500 - 1,000 mL/min on the anesthetic machine.</li>
	<li>Continue the induction until the righting reflex of the animal disappears.</li>
	<li>Set the anesthetic maintenance rate at 1 - 2.5% isoflurane and 300 - 400 mL/min oxygen on the machine.</li>
	<li>Place a heat-pad with insulation (cotton wool) on a stereotaxic device and then immobilize the animal in the stereotaxic device.</li>
	<li>Measure the level of anesthesia by pinching the toes of the animal.</li>
</ol>
8. Surgical procedure
<ol>
	<li>Using an electric shaver or a pair of scissors, shave the animal&#8217;s head where the incision is to be made.</li>
	<li>Scrub the surgery area with ethanol and then with povidone&#8211;iodine, 4%.</li>
	<li>Apply eye lubricant to protect the animal&#8217;s cornea during the surgery.</li>
	<li>Using tissue forceps, gently pull the skin between the animal&#8217;s eyes and ears. Using scissors, cut the skin that is pinched between the forceps and remove the periosteum.</li>
	<li>Use hydrogen peroxide to clean and disinfect the skull.</li>
	<li>Find the location of the electrode insertion point by using stereotaxic coordinates and mark it on the skull with a permanent marker.</li>
	<li>Use a handheld drill to make one hole for the grounding electrode, one for anchoring the implant, and one hole per recording electrode.</li>
	<li>Insert the electrodes at a very slow rate to minimize the possible cortical and subcortical damage.</li>
	<li>Connect the grounding electrode to the skull using a small screw.</li>
	<li>Secure the connector plug/socket in place by using a thin layer of dental acrylic cement.</li>
	<li>Inject buprenorphine (15 &#181;g/kg, subcutaneously) or meloxicam (1 - 3 mg/kg, subcutaneously) as a painkiller.</li>
	<li>Leave the animal in a cage on a heated mat to recover. Observe the animal at least every 30 min until it has recovered from the anesthetic.</li>
</ol>
9. Post-procedure Training
<ol>
	<li>Following the surgery, allow at least a 10-day recovery period. House the animals individually with free access to food and water ad libitum and monitor them on a daily basis (see Rudebeck, Walton, Smyth, Bannerman, and Rushworth7 for more information).</li>
	<li>Following the recovery, start restricting the animal&#8217;s diet to 85% of their free-feeding amount.</li>
	<li>Retrain the animals in the maze to recall the discrimination phase (step 4).</li>
	<li>Continue re-training the mice until they have achieved 80% of HRC.</li>
</ol>

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The authors have nothing to disclose.

Rodents have long been used in neuroscientific studies that deal with different topics, from cognitive abilities such as learning and memory2,14 and reinforced behavior7,15,16 to the central control of organs17,18 and neuropharmacology19,20. The proposed ...

Decision making is the process of recognizing and selecting choices based on the values and preferences of the decision maker and the consequences of the selected action1. Although decision making has been extensively studied in different fields (i.e., economics, psychology, and neuroscience), neural mechanisms underlying such cognitive abilities are not yet fully understood. Two subcategories of decision making are perceptual decision making and reinforcement-guided decision making. Though they incorporate considerable overlapping elements and concepts, perceptual decision making relies on the available sensory information1,2, whereas reinforcement-guided decision-making deals with the relative value of actions gained over a specific timescale3. One important aspect of reinforced decision making is the cost-benefit analysis which is performed intuitively by the brain by computing the benefits of the given choices and subtracting the associated costs of each alternative1.
The T-maze (or the variant Y-maze) is one of the most-used mazes in cognitive experiments using rodents. Animals are placed in the start arm (the base of the T) and permitted to choose the goal arm (one of the side arms). Tasks such as a forced alternation or left-right discrimination are mainly used with rodents in the T-maze to test reference and working memory4. T-mazes are also widely used in decision-making experiments5,6,7. In the simplest design, the reward is placed in only one goal arm. The choice is predictable, and animals would certainly prefer the reward rather than nothing, regardless of the reward value. Another option is to place rewards in both goal arms and then let the animals make a choice of which path to take depending on several parameters (i.e., the natural preference of the animal, the difference in the value of the rewards, and the costs to be paid). In the value-based design, the task is more complicated by having weighing-scale properties. In this way, an animal receives differently valued rewards by choosing between the two alternatives, as well as between the costs of the actions [i.e., the amount of waiting (delay-based) or the amount of effort (effort-based) needed to receive rewards], each contributing to the decision that is made5,6.
In traditional delay-based T-maze decision making, animals are trained to select the high reward arm (HRA) and avoid the opposite low reward arm (LRA). The sides of the HRA and the LRA remain unchanged throughout the experiment. Although the task described above has been well documented in the literature, it suffers from several procedural drawbacks. Firstly, by having a fixed goal arm, the animal knows which arm to choose from the beginning of each trial. In this scenario, animals may select the goal arm based on their memory rather than on decision making. Hence, in a delay-based decision-making paradigm, if an animal selects the low reward because of the study intervention, it will not be clear whether this is due to a loss of memory or to the study intervention. A memory control group to segregate the observed behavior from the memory problem might be considered, but this burdens researchers and animals alike because of the additional work7. A second concern is the moment of decision making by the animal: once animals reach the decision zone (the junction of all three arms), they usually look to the left and to the right, weigh the costs and benefits regarding each arm, and then make their decision. However, after a few trials, they perform such a computation prior to arriving at the decision zone and simply run directly to the reward arm. As a result, these two drawbacks&#8212;a pre-bias to one arm and finding the moment of decision making&#8212;both highly interrupt the interpretation of electrophysiological and neuroimaging data.
In the method explained in this paper, the preferred arm (HRA) is cued by an auditory cue and may vary from trial to trial. Animals initiate the trials by entering the test zone (Figure 1) and triggering the auditory cue by &#34;nose-poking&#34; an infrared gate that has been placed at the junction of the three arms. The audio signal (20 dB, between 500 and 1,000 ms) is played from a speaker at the end of the goal arm.

<table><tbody><tr><td>T-maze</td><td></td><td></td><td>Self made</td></tr><tr><td>Dustless Precision Sugar Pellets</td><td>TSE Systems Intl. Group</td><td>F0023</td><td>45 mg, Sucrose</td></tr><tr><td>Ketamine Hydrochloride Injection, USP</td><td>Sigma-Aldrich</td><td>6740-87-0</td><td></td></tr><tr><td>Xylazine</td><td>Sigma-Aldrich</td><td>7361-61-7</td><td></td></tr><tr><td>stereotaxic device</td><td>Stoelting</td><td></td><td></td></tr><tr><td>Isofluran</td><td>Santa Cruz Biotechnology</td><td>sc-363629Rx</td><td></td></tr><tr><td>PFA-coated stainless-steel wires</td><td>A-M systems</td><td></td><td></td></tr><tr><td>acrylic cement</td><td>Vertex, MA, USA</td><td></td><td></td></tr><tr><td>(wooden or PVC (polyvinyl chloride)-made)</td><td>local suppliers</td><td></td><td></td></tr><tr><td>Mini-Fit Power Connector</td><td>Molex</td><td>15243048</td><td></td></tr><tr><td>ethannol 70%</td><td>Local suppliers</td><td></td><td></td></tr><tr><td>buprenorphine</td><td>diamondback drugs</td><td></td><td></td></tr><tr><td>Arduino UNO</td><td>Arduino</td><td></td><td>https://www.arduino.cc/</td></tr><tr><td>Infrared emitting diode</td><td>Sharp</td><td>GL480E00000F</td><td>http://www.sharp-world.com/</td></tr><tr><td>Chronux Toolbox</td><td></td><td></td><td>Chronux.org</td></tr><tr><td>Arduino codes</td><td></td><td></td><td>https://github.com/dechuans/arduino-maze</td></tr></tbody></table>

operant protocols for assessing the cost-benefit analysis during reinforced decision making by rodents

Reinforcement-guided decision making is the ability to choose between competing courses of action based on the relative value of the benefits and their consequences. This process is integral to the normal human behavior and has been shown to be disrupted by neurological and psychiatric disorders such as addiction, schizophrenia, and depression. Rodents have long been used to uncover the neurobiology of human cognition. To this end, several behavioral tasks have been developed; however, most are non-automated and are labor-intensive. The recent development of the open-source microcontroller has enabled researchers to automate operant-based tasks for assessing a variety of cognitive tasks, standardizing the stimulus presentation, improving the data recording and consequently, improving the research output. Here, we describe an automated delay-based reinforcement-guided decision-making task, using an operant T-maze controlled by custom-written software programs. Using these decision-making tasks, we show the changes in the local field potential activities in the anterior cingulate cortex of a rat whilst it performs a delay-based cost-and-benefit decision-making task.

The data presented here is the recorded LFP from the left orbitofrontal cortex (OFC) and the anterior cingulate cortex (ACC) of six male Wistar rats using bipolar electrodes (of PFA-coated stainless steel). Table 1 shows the behavioral acquisition length for each training stage. The coordinates for the target locations were determined from a rat brain atlas9 and are as follows: for the AAC, 1.2 mm anterior to the bregma, 0.8 mm lateral to the midli...

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Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

A cost-benefit analysis is a weighing-scale approach that the brain performs during the course of decision making. Here, we propose a protocol to train rats on an operant-based decision-making paradigm where rats choose higher rewards at the expense of waiting for 15 s to receive them.

Reinforcement-guided decision making is the ability to choose between competing courses of action based on the relative value of the benefits and their ...

operant-protocols-for-assessing-cost-benefit-analysis-during

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5.9K Views.  The University of Melbourne. Een kosten-batenanalyse is een weging-schaal aanpak waarmee de hersenen in de loop van de besluitvorming. Hier stellen wij een protocol te trainen ratten op een operante gebaseerde besluitvorming paradigma waar ratten kiezen hogere beloningen ten koste van het wachten op 15 s om hen te ontvangen.

Video: Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

A Novel Procedure for Evaluating the Reinforcing Properties of Tastants in Laboratory Rats: Operant Intraoral Self-administration

This paper describes a novel method for studying the bio-behavioral basis of addiction to food. This method combines the surgical component of taste reactivity with the behavioral aspects of operant self-administration of drugs. Under very brief general anaesthesia, rats are implanted with an intraoral (IO) cannula that allows delivery of test solutions directly in the oral cavity. Animals are then tested in operant self-administration chambers whereby they can press a lever to receive IO infusions of test solutions. IO self-administration has several advantages over experimental procedures that involve drinking a solution from a spout&#160;or operant responding for solid pellets or solutions delivered in a receptacle. Here, we show that IO self-administration can be employed to study self-administration of high fructose corn syrup (HFCS). Rats were first tested for self-administration on a progressive ratio (PR) schedule, which assesses the maximum amount of operant behavior that will be emitted for different concentrations of HFCS (i.e.&#160;8%, 25%, and 50%). Following this test, rats self-administered these concentrations on a continuous schedule of reinforcement (i.e.&#160;one infusion for each lever press) for 10 consecutive days (1 session/day; each lasting 3 hr), and then they were retested on the PR schedule. On the continuous reinforcement schedule, rats took fewer infusions of higher concentrations, although the lowest concentration of HFCS (8%) maintained more variable self-administration. Furthermore, the PR tests revealed that 8% had lower reinforcing value than 25% and 50%. These results indicate that IO self-administration can be employed to study acquisition and maintenance of responding for sweet solutions. The sensitivity of the operant response to differences in concentration and schedule of reinforcement makes IO self-administration an ideal procedure to investigate the neurobiology of voluntary intake of sweets.

The current study evaluates a novel procedure for assessing the reinforcing effects of palatable solutions in laboratory rats: intraoral self-administration. To this end, operant responding (i.e.&#160;lever pressing) for intraoral infusions of sweet solutions at different concentrations was measured on continuous and progressive ratios schedules of reinforcement.

This paper describes a novel method for studying the bio-behavioral basis of addiction to food. This method combines the surgical component of taste ...

Behavior

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.

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. ...

Operant Procedures for Assessing Behavioral Flexibility in Rats

Executive functions consist of multiple high-level cognitive processes that drive rule generation and behavioral selection. An emergent property of these processes is the ability to adjust behavior in response to changes in one&#8217;s environment (i.e., behavioral flexibility). These processes are essential to normal human behavior, and may be disrupted in diverse neuropsychiatric conditions, including schizophrenia, alcoholism, depression, stroke, and Alzheimer&#8217;s disease. Understanding of the neurobiology of executive functions has been greatly advanced by the availability of animal tasks for assessing discrete components of behavioral flexibility, particularly strategy shifting and reversal learning. While several types of tasks have been developed, most are non-automated, labor intensive, and allow testing of only one animal at a time. The recent development of automated, operant-based tasks for assessing behavioral flexibility streamlines testing, standardizes stimulus presentation and data recording, and dramatically improves throughput. Here, we describe automated strategy shifting and reversal tasks, using operant chambers controlled by custom written software programs. Using these tasks, we have shown that the medial prefrontal cortex governs strategy shifting but not reversal learning in the rat, similar to the dissociation observed in humans. Moreover, animals with a neonatal hippocampal lesion, a neurodevelopmental model of schizophrenia, are selectively impaired on the strategy shifting task but not the reversal task. The strategy shifting task also allows the identification of separate types of performance errors, each of which is attributable to distinct neural substrates. The availability of these automated tasks, and the evidence supporting the dissociable contributions of separate prefrontal areas, makes them particularly well-suited assays for the investigation of basic neurobiological processes as well as drug discovery and screening in disease models.

The ability to assess executive functions such as behavioral flexibility in rats is useful for investigating the neurobiology of cognition in both intact animals and disease models. Here we describe automated tasks for assessing strategy shifting and reversal learning, which are particularly sensitive to disruptions in prefrontal cortical networks.

Executive functions consist of multiple high-level cognitive processes that drive rule generation and behavioral selection. An emergent property of these ...

Quantifying Social Motivation in Mice Using Operant Conditioning

In this protocol, social motivation is measured in mice through a pair of operant conditioning paradigms. To conduct the experiments, two-chambered shuttle boxes were equipped with two operant levers (left and right) and a food receptacle in one chamber, which was then divided from the second chamber by an automated guillotine door covered by a wire grid. Different stimulus mice, rotated across testing days, served as a social stimulus behind the wire grid, and were only visible following the opening of the guillotine door. Test mice were trained to lever press in order to open the door and gain access to the stimulus partner for 15 sec. The number of lever presses required to obtain the social reward progressively increased on a fixed schedule of 3. Testing sessions ended after test mice stopped lever pressing for 5 consecutive minutes. The last reinforced ratio or breakpoint can be used as a quantitative measure of social motivation. For the second paradigm, test mice were trained to discriminate between left and right lever presses in order to obtain either a food reward or the social reward. Mice were rewarded for every 3 presses of each respective lever. The number of food and social rewards can be compared as a measurement of the value placed upon each reward. The ratio of each reward type can also be compared between mouse strains and the change in this ratio can be monitored within testing sessions to measure satiation with a given reward type. Both of these operant conditioning paradigms are highly useful for the quantification of social motivation in mouse models of autism and other disorders of social behavior.

This article describes a new protocol for the quantitative measurement of social motivation in mice using operant conditioning for a social reward. The protocol is useful for the measurement of social motivation in mouse models of autism and other disorders of social behavior.

In this protocol, social motivation is measured in mice through a pair of operant conditioning paradigms. To conduct the experiments, two-chambered ...

A Fully Automated and Highly Versatile System for Testing Multi-cognitive Functions and Recording Neuronal Activities in Rodents

We have developed a fully automated system for operant behavior testing and neuronal activity recording by which multiple cognitive brain functions can be investigated in a single task sequence. The unique feature of this system is a custom-made, acoustically transparent chamber that eliminates many of the issues associated with auditory cue control in most commercially available chambers. The ease with which operant devices can be added or replaced makes this system quite versatile, allowing for the implementation of a variety of auditory, visual, and olfactory behavioral tasks. Automation of the system allows fine temporal (10 ms) control and precise time-stamping of each event in a predesigned behavioral sequence. When combined with a multi-channel electrophysiology recording system, multiple cognitive brain functions, such as motivation, attention, decision-making, patience, and rewards, can be examined sequentially or independently.

In this report, we present a fully automated and highly versatile system capable of simultaneously testing multi-cognitive behaviors and recording neuronal activities for rodents.

We have developed a fully automated system for operant behavior testing and neuronal activity recording by which multiple cognitive brain functions can be ...

An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in  Free Moving Rodents

Many neurological and psychiatric patients demonstrate difficulties and/or deficits in decision making. Rodent models are helpful to produce a deeper understanding of the neurobiological causes underlying the decision-making problems. A cost-benefit based T-maze task is used for measuring decision making in which rodents choose between a high reward arm (HRA) and a low reward arm (LRA). There are two paradigms of the T-maze decision-making task, one in which the cost is a time delay and the other in which it is physical effort. Both paradigms require a tedious and labor-intensive management of experimental animals, multiple doors, pellet reward, and arm choice recordings. In the current work, we invented an apparatus based on traditional T-maze with full automation for pellet delivery, door management and choice recordings. This automated setup can be used for the evaluation of both delay- and effort-based decision making in rodents. With the protocol described here, our lab investigated the decision-making phenotypes of multiple genetically modified mice. In the representative data, we showed that the mice with ablated medial habenular showed aversions of both delay and effort and tended to choose the immediate and effortless reward. This protocol helps to decrease the variability caused by experimenter intervention and to enhance experiment efficiency. In addition, chronic silicon probe or microelectrode recording, fiber-optic imaging and/or manipulation of neural activity can be easily applied during the decision-making task using the setup described here.

This article introduces an automated T-maze apparatus that we invented, and a protocol based on this apparatus for analyzing delay-based decision making and effort-based decision making in free moving rodents.

Many neurological and psychiatric patients demonstrate difficulties and/or deficits in decision making. Rodent models are helpful to produce a deeper ...

Three Laboratory Procedures for Assessing Different Manifestations of Impulsivity in Rats

The present article provides a guide for the conduction and analysis of three conditioning-based protocols to evaluate impulsivity in rats. Impulsivity is a meaningful concept because it is associated with psychiatric conditions in humans and with maladaptive behavior in non-human animals. It is believed that impulsivity is composed of separate factors. There are laboratory protocols devised to assess each of these factors using standardized automated equipment. Delay discounting is associated with the incapacity to be motivated by delayed outcomes. This factor is evaluated through intertemporal choice protocols, which consist&#160;of presenting the individual with a choice situation involving an immediate reward and a larger but delayed reward. Response inhibition deficit is associated with the incapacity to withhold prepotent responses. Differential reinforcement of low rates (DLR) and feature-negative discrimination protocols assess the response inhibition deficit factor of impulsivity. The former imposes a condition to a motivated individual in which most wait a minimum period of time for a response to be rewarded. The latter evaluates the capacity of individuals to refrain from food seeking responses when a signal of the absence of food is presented. The purpose of these protocols is to construct an objective quantitative measure of impulsivity, which serves to make cross-species comparisons, allowing the possibility of translational research. The advantages of these particular protocols include their easy set-up and application, which stems from the relatively small amount of equipment needed and the automated nature of these protocols.

We present three protocols that assess different forms of impulsivity in rats and other small mammals. Intertemporal choice procedures evaluate the tendency to discount the value of delayed outcomes. Differential reinforcement of low rates and feature-negative discrimination evaluate response inhibition capacity with and without punishment for inappropriate responses, respectively.

The present article provides a guide for the conduction and analysis of three conditioning-based protocols to evaluate impulsivity in rats. Impulsivity is ...

A Conflict Model of Reward-seeking Behavior in Male Rats

The present protocol describes a novel conflict task as a model of inhibitory control in rats. In this model, a natural rewarding stimulus (sexual stimulus) that represents a high-value reward, and the aversive stimuli (pins), are concurrently presented. The male rats have to climb or jump over the obstacle full of pins to approach and investigate the sexual partner. If the animal persists in their approaching behavior regardless of the aversive stimuli, it is considered as a maladaptive or risky reward-seeking behavior. The conflict task permits the evaluation of deficit in inhibitory control resulting from exposure to abused drug, such as morphine, or a stressful event. 
The main advantage of this model is that it provides a simple and quick way to discover the deficit in inhibitory control after exposure to opiate drugs or other stressful events. In addition to opiates, this behavioral model would also be useful for quickly discovering the inhibitory control deficits induced by other addictive drugs. However, the limitation is that the male rats' performance may be subject to exercising effects with repeated testing under this conflict task. In the future, one can hope that the individuals with the compulsive phenotype of reward-seeking behavior after exposure to opiates will be identified based on modifying this conflict model.

This conflict model is used to measure the impairment of inhibitory control after exposure to addictive drugs, or other factors that may influence inhibitory control. A sexual stimulus and an aversive obstacle are concurrently presented, thus male rats have to conquer the obstacle to approach the sexual reward.

The present protocol describes a novel conflict task as a model of inhibitory control in rats. In this model, a natural rewarding stimulus (sexual ...

Assessment of Stress Effects on Cognitive Flexibility using an Operant Strategy Shifting Paradigm

Stress affects cognitive function. Whether stress enhances or impairs cognitive function depends on several factors, including the 1) type, intensity, and duration of the stressor; 2) type of cognitive function under study; and 3) timing of the stressor in relation to learning or executing the cognitive task. Furthermore, sex differences among the effects of stress on cognitive function have been widely documented. Described here is an adaptation of an automated operant strategy shifting paradigm to assess how variations in stress affect cognitive flexibility in male and female Sprague Dawley rats. Specifically, restraint stress is used before or after training in this operant-based task to examine how stress affects cognitive performance in both sexes. Particular brain areas associated with each task in this automated paradigm have been well-established (i.e., the medial prefrontal cortex and orbitofrontal cortex). This allows for targeted manipulations during the experiment or the assessment of particular genes and proteins in these regions upon completion of the paradigm. This paradigm also allows for the detection of different types of performance errors that occur after stress, each of which has defined neural substrates. Also identified are distinct sex differences in perseverative errors after a repeated restraint stress paradigm. The use of these techniques in a preclinical model may reveal how stress affects the brain and impairs cognition in psychiatric disorders, such as post-traumatic stress disorder (PTSD) and major depressive disorder (MDD), which display marked sex differences in prevalence.

Stressful life events impair cognitive function, increasing the risk of psychiatric disorders. This protocol illustrates how stress affects cognitive flexibility using an automated operant strategy shifting paradigm in male and female Sprague Dawley rats. Specific brain areas underlying particular behaviors are discussed, and translational relevance of results are explored.

Stress affects cognitive function. Whether stress enhances or impairs cognitive function depends on several factors, including the 1) type, intensity, and ...

Gathering Self-Initiated Rat Behavioral Data to Characterize Post-Stroke Deficits

Behavioral testing in rat models is frequently utilized for diverse purposes, including psychological, biomedical, and behavioral research. Many traditional approaches involve individual, one-on-one testing sessions between a single researcher and each animal in an experiment. This setup can be very time consuming for the researcher, and their presence may impact the behavioral data in unwanted ways. Additionally, traditional caging for rat research imposes a lack of enrichment, exercise, and socialization that would normally be typical for the species, and this context may also skew the results of behavioral data. Overcoming these limitations may be worthwhile for several research applications, including the study of acquired brain injury. Here, an example method is presented for automatically training and testing individual rat behavior in a colony cage without the presence of humans. Radio frequency identification can be utilized to tailor sessions to the individual rat. The validation of this system occurred in the example context of measuring skilled forelimb motor performance before and after stroke. Traditional characteristics of post-stroke behavioral impairments and novel measures enabled by the system are measured, including success rate, various aspects of pull force, bout analysis, initiation rate and patterns, session duration, and circadian patterns. These variables can be collected automatically with few limitations; though the apparatus removes experimental control of exposure, timing and practice, the validation produced reasonable consistency in these variables from animal to animal.

A system for acquiring data from self-initiated individual behavior sessions within a social colony cage setting is presented. The efficacy of this system is demonstrated using an automated skilled reach assessment, enabling the characterization of post-stroke motor impairments, potential behavioral alterations related to motivation, circadian variations, and other innovative dependent variables.

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

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