Research described here was supported by a grant from the Natural Sciences and Engineering Research Council of Canada to S.B.F.

<ol>
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B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+effects+of+inactivation+of+the+orbitofrontal+cortex+on+strategy+set-shifting+and+reversal+learning.">Differential effects of inactivation of the orbitofrontal cortex on strategy set-shifting and reversal learning.</a> Neurobiol Learn Mem. 89, 567-573 (2008).</li><li>Boulougouris, V., Dalley, J. W., Robbins, T. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+orbitofrontal,+infralimbic+and+prelimbic+cortical+lesions+on+serial+spatial+reversal+learning+in+the+rat.">Effects of orbitofrontal, infralimbic and prelimbic cortical lesions on serial spatial reversal learning in the rat.</a> Behav Brain Res. 179, 219-228 (2007).</li><li>Tseng, K. Y., Chambers, R. A., Lipska, B. 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Publication of and free access to this manuscript was supported by Med Associates, Inc.

The development of behavioral tasks to measure higher-order cognitive constructs in rodents is essential to advance knowledge of the neurobiology of cognition. With well-constructed and validated tasks, rodents can be assessed on tasks of complexity rivaling those of primates or even humans. Here we have shown how two aspects of executive function, strategy shifting and reversal learning, can be investigated in rodents using automated operant techniques. Using these automated tasks, we have replicated previous findings in cross-maze and digging tasks regarding the neural substrates of set-shifting and reversal learning11,13,18-21,27,29, suggesting that the operant tasks are valid assessments of these constructs.
These automated tasks have a number of benefits and advantages over existing non-automated cross-maze and digging tasks. Most compelling is the superior rate of data collection in the automated operant version. Each day&#8217;s training or testing takes only 30-60 minutes, and is fully computer-controlled requiring minimal supervision by the experimenter. Moreover, several animals can be tested simultaneously with a multi-chamber operant setup. Each task series, from shaping to final testing, can be completed in approximately 2-3 weeks. Another important advantage of the automated tasks is the precise control of stimulus presentation, thus minimizing the possibility of experimenter error. For example, the order of presentation of cue location on each trial is randomized and controlled by the computer, rather than by an experimenter manually consulting a trial-by-trial list. The timing between trials is precisely measured and consistent, and is not confounded by the time it takes an experimenter to, e.g., remove a rat from the cross-maze or rearrange the digging containers. Reinforcement delivery is automatic and is not subject to experimenter error (e.g., forgetting to bait the correct arm of a cross-maze). Data collection is similarly improved, with automatic recording of response patterns including the measurement of exact response latencies. In the absence of other motor abnormalities, changes in response latencies can be used to infer evidence of altered processing speed and/or to judge the level of cognitive complexity of a task21,22.
The automated tasks also retain one important advantage of the cross-maze tasks: the ability to conduct a detailed analysis of the types of errors made on the shift or reversal day. Distinguishing between set-shifting errors that replicate the previous day&#8217;s strategy (perseverative or regressive errors) and errors that represent previously untried strategies (never-reinforced errors) can assist in characterizing specific deficits in behavioral flexibility. In particular, perseverative errors occurring early in testing reflect an animal&#8217;s inability to abandon the previous strategy, while later-occurring regressive errors reflect an animal&#8217;s inability to maintain the new strategy once perseveration has ceased20. Never-reinforced errors may indicate a failure to acquire the new strategy, or an inability to respond systematically according to a rule20. Previous findings16,17,20 demonstrating dissociable neuroanatomical bases of these types of errors are also valuable in interpreting the results of these tasks.
Our procedures have been developed and optimized for use with rats. This being said, other groups have used similar procedures for testing set-shifting abilities in mice31. However, certain modifications need to be employed with mice to accommodate for species differences. These include longer presentation of the visual cue light prior to lever extension, training over multiple days using 30 trials/day and incorporation of a time-out punishment after incorrect choices. Although these modifications make this assay less amenable for use with pharmacological challenges, it could prove useful for assessing cognitive flexibility in genetically altered mice (although it is unclear whether these modifications would preserve the frontal cortex sensitivity of the task).
Of course, there are also limitations to these tasks. Some of these limitations arise from the automated nature of the task, while others are related to the parameters of the task itself. With regard to the latter, the set-shifting task described here (as well as the cross-maze set-shifting task26) utilize a restricted set of stimuli and responses. Unlike the digging task, on which novel exemplars (e.g., unfamiliar scents or digging media) can be used to construct new attentional sets at each stage11,19, the operant set-shifting task necessarily requires choosing between two stimuli that are familiar to the animal &#8212; either the left vs. right cue light, or the left vs. right position. This means that the operant and cross-maze set-shifting tasks involve response conflict as well as strategy shifting, although the concept of shifting one&#8217;s strategy to a new, previously irrelevant stimulus dimension is preserved20,23. On a related note, the set-shifting and reversal operant tasks as described here do not allow for a third stimulus dimension, as in the digging task which may include digging media, odor, and texture11,19. However, we do not consider this a fatal flaw, as the operant set-shifting task still requires the animal to suppress the previously relevant discrimination strategy and attend to a previously ignored stimulus dimension. Additionally, it seems conceivable that modifications to the equipment and task parameters could support the addition of a third stimulus dimension, such as auditory cues or odor, although these additions would likely make learning more difficult and less amenable to single-day pharmacological tests.
Finally, a potential limitation of any operant-based task is the loss of direct information regarding rat behavior &#8212; i.e., the experimenter is no longer watching the rat. We feel that the advantages in objectivity and data collection speed conferred by automation more than make up for this loss, and cameras mounted in the operant chambers are a relatively easy way to restore individual visual access if desired.
There are a number of steps that can be taken to maximize success using these operant tasks. First, the importance of handling the animals before training begins cannot be overstated; as with any behavioral task, well-handled animals are easier to work with, are less stressed, and tend to produce less variable data. Second, some pilot testing may be necessary to determine the best time of day to conduct testing; we test during the light cycle, and find that performance is optimal when animals are tested near the end of this cycle (e.g., approximately 4:00 pm for a light cycle ending at 7:00 pm). Third, care should be taken to confirm that stable performance is established at each pretraining stage before an animal is advanced to the next step. For example, consistent and robust performance at the retractable lever training stage is an excellent predictor of proficient performance on the &#8220;set&#8221; discrimination task. Regarding the equipment, although all steps are automated, experimenter intervention remains necessary to confirm that all components are in working order. For example, an equipment check should be run daily (or more than once a day, if large number of animals are being tested) to ensure that all lights, levers, and reward delivery systems are operational. In particular, malfunctions in reward delivery systems (particularly pellet dispensers) can drastically affect performance. An unusually high number of omissions on a given day may indicate an issue with reward delivery equipment, and thus data output should be checked every day by an experimenter familiar with the task and expected performance levels. In the absence of an equipment malfunction, a high number of omissions may indicate other problems with motivation or animal health. If an animal is otherwise healthy, food restriction may be increased to take the animal to 80-85% of the free-feeding weight for a short time until performance recovers.
These set-shifting and reversal tasks can be used in a variety of experimental paradigms. For example, the effects of manipulations such as lesions, developmental treatments, dietary manipulations, long-term pharmacological treatment, or genetic modifications could be investigated. While the effect of a treatment on the set-shifting or reversal stage may be of primary interest, note that since such chronic or permanent treatments must necessarily be administered before training begins, effects on multiple stages of performance (particularly on the initial discrimination or &#8220;set&#8221;) must also be examined21. The use of acute manipulations, such as pharmacological treatments or temporary neuroanatomical inactivations, are particularly well-suited to these tasks. In such cases, the addition of a third group (as illustrated in Figure 2) is useful; thus, the primary experimental group receives the manipulation of interest on the day of shift or reversal, while one control group receives the manipulation on the day of initial discrimination or &#8220;set&#8221; to test for broad effects on learning, and a second control group receives no manipulations (or sham treatments) on both days20,22. Note that for such acute manipulation studies, it is advisable to match rats for performance during the learning of the initial set and allocate them to the experimental group and (second) control group accordingly. This minimizes the possibility that treatment-induced differences in performance may be confounded by individual variations in how readily rats learn to discriminate between stimuli. Furthermore, if an experiment requires testing of multiple cohorts over weeks or months, each cohort should include animals from all experimental groups. For example, a study testing the effects of acute pharmacological manipulations during a shift may require 48 rats in total and 3 experimental groups, tested in three cohorts of 16 animals each. In this case, each cohort should contain 5-6 rats in each experimental group. Ideally, the statistical analyses should include a factor that confirms there were no differences in performance across each cohort of rats. Finally, these operant tasks may be particularly useful for applying in vivo recording techniques, including microdialysis, voltammetry, and electrophysiology, due to components such as the controlled environment, precise timing of stimulus presentation and responses, and restricted movements of the animals which are not available or practical in the cross-maze or digging tasks.

High-level cognitive processes including rule generation, behavioral selection, and strategy evaluation are collectively referred to as &#8220;executive function&#8221; or &#8220;behavioral flexibility1.&#8221; Such processes are crucial to normal cognitive function, and may be impaired in such diverse disorders as schizophrenia, alcoholism, depression, stroke, and Alzheimer&#8217;s disease2-7. The regulation of executive function processes is primarily mediated by areas in the frontal cortex, including the dorsolateral prefrontal cortex and the orbitofrontal cortex in humans8-10.
The development of tasks to assess executive function and/or behavioral flexibility in nonhuman animals, particularly rodents, has greatly advanced the understanding of the neurobiology of cognition11-14. Such tasks have made it possible to separately measure distinct components of behavioral flexibility, including strategy shifting and reversal learning. Strategy shifting refers to the ability to actively suppress a previously learned response strategy while acquiring a new, competing strategy, particularly across stimulus dimensions (extradimensional shift) &#8212; e.g., switching from performing a visually-based discrimination (red vs. green, where red is &#8220;correct&#8221; and tactile stimuli are irrelevant) to performing a tactile discrimination (smooth vs. rough, where smooth is &#8220;correct&#8221; and visual stimuli are now irrelevant). On the other hand, reversal learning also involves a change in response strategy, but within the same stimulus dimension &#8212; e.g., in the &#8220;red vs. green&#8221; example, if red was previously correct, a reversal would dictate that green is now correct, while tactile stimuli would remain irrelevant.
Several tasks have been developed to investigate behavioral flexibility in rodents. The cross-maze task requires an animal to first learn either a direction-based rule (e.g., &#8220;always turn right&#8221;) or a visual-based rule (e.g., &#8220;always turn toward the visual cue&#8221;) to a certain criterion of performance. Then, the animal is required to unexpectedly shift either across modality to the opposite rule (strategy shifting, originally referred to as a &#8220;nonreversal shift&#8221;15) or shift within modality to the opposite contingency (reversal learning)13,14,16. Such tasks are sensitive to disruptions in cortical and subcortical networks, involving the prefrontal cortex, thalamus, and striatum1,13,14,16-18. Another type of attentional set-shifting task (sometimes referred to as the digging task) requires training animals to discriminate between two containers that differ along two or three stimulus dimensions (digging media, odor, and/or external texture). Similar to the cross-maze task, animals are then required to shift either across dimensions (strategy shifting) or within the same dimension (reversal learning), and these tasks are similarly sensitive to frontal cortex manipulations11,19. An advantage of this task is that during the extra-dimensional strategy shift, rats are presented with novel sets of stimuli (exemplars), which ensures that performance impairments during this stage are likely attributable to disruptions in the ability to shift attentional set to different aspects of compound stimuli, rather than an impaired ability to stop approaching a specific stimulus previously associated with reward. However, this feature also makes it more difficult to ascertain the specific nature of a deficit during a set shift.
Although the tasks described above have been well documented in the literature, they both suffer from a number of procedural disadvantages, primarily the length of time it takes to test animals. In both the cross-maze task and the digging task, only one animal may be tested at a time; furthermore, testing must be administered in real time by a dedicated experimenter, and may take up to several hr per day per animal. In addition, the presentation of stimuli and the recording of behavioral responses in both types of tasks are manually controlled by an experimenter, and are thus vulnerable to human error and subjective interpretation.
Here, we describe an automated method for assessing strategy shifting and reversal learning in the rat, using operant procedures that streamline stimulus control and data presentation, and dramatically improve the rate of data collection and throughput20,21. The methods used to shape and train rats are described, as well as the components of the task itself and the analysis of the resulting data. We have found that like the cross-maze and digging tasks, these automated tasks are sensitive to disruptions in prefrontal and subcortical circuitry, as well as to a neurodevelopmental manipulation that models schizophrenia20-23.

<table border="0" cellpadding="0" cellspacing="0" width="823">
	<tbody>
		<tr height="34">
			<td height="34" style="height:34px;width:231px;">Name of Material/ Equipment</td>
			<td style="width:153px;">Company</td>
			<td style="width:139px;">Catalog Number</td>
			<td style="width:301px;">Comments/Description</td>
		</tr>
		<tr height="84">
			<td height="84" style="height:84px;width:231px;">Behavioral Chamber Package with Retractable Levers</td>
			<td style="width:153px;">Med Associates, Inc.</td>
			<td style="width:139px;">MED-008-B2</td>
			<td style="width:301px;">Required components include two retractable levers, two stimulus lights, houselight, and reinforcement delivery system</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:231px;">MED-PC software</td>
			<td style="width:153px;">Med Associates, Inc.</td>
			<td style="width:139px;">SOF-735</td>
			<td style="width:301px;"></td>
		</tr>
		<tr height="42">
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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.

Acute, reversible inactivation of the prefrontal cortex can be accomplished by infusion of the local anesthetic bupivacaine hydrochloride (0.75%, 0.5 &#181;l) into the prelimbic region via a surgically implanted infusion cannula20 approximately 10 min prior to testing. Furthermore, the effects of inactivation during either the first task (&#8220;Set&#8221;) or the second task (&#8220;Shift&#8221; or &#8220;Reversal&#8221;) can be assessed to investigate possible general effects on learning. Figure 2 illustrates the results of such inactivations on animals performing the Cue-to-Response strategy-shifting sequence. Prefrontal inactivation on the first day, the Cue/&#8220;Set&#8221; task, did not impair performance (Figure 2A), suggesting that the medial prefrontal cortex is not necessary for initial discrimination learning. However, prefrontal inactivation on the second day, the Response/&#8220;Shift&#8221; task, significantly impaired performance in that animals required a substantially greater number of trials to reach criterion performance (Figure 2B). When the prefrontal cortex was inactivated, animals made more perseverative-like errors than never-reinforced errors on the Shift task (Figure 2C). These findings replicate previous data regarding the importance of the medial prefrontal cortex for strategy shifting and, in particular, in suppressing a previously learned strategy13,20.
Conversely, animals trained in the Reversal of Response sequence did not show this prefrontal dependency. Animals receiving inactivation of the prefrontal cortex on the &#8220;Reversal&#8221; day did not differ from saline-infused animals on either the initial response discrimination (Figure 3A) or the subsequent reversal (Figure 3B)20.These findings are consistent with previous research showing that the orbitofrontal cortex, not the medial prefrontal cortex, regulates reversal learning on a variety of tasks12,19,26, including an operant task similar to the one described here27.
<img alt="Figure 2" src="/files/ftp_upload/52387/52387fig2highres.jpg" /> 
Figure 2. Inactivation of the Prefrontal Cortex Impairs Strategy Shifting. A, Trials to criterion on the initial Cue discrimination task (&#8220;Set&#8221;) by rats receiving infusions of saline or bupivacaine (Bupi) into the medial prefrontal cortex on the set day. Prefrontal inactivation had no effect on initial acquisition. B, Trials to criterion on the shift to the Response task (&#8220;Shift&#8221;) following medial prefrontal infusions of either saline or bupivacaine on the shift day. Inactivation of the prefrontal cortex impaired the strategy shift to the response task. C, Types of errors committed by animals on the shift day. Prefrontal inactivation prior to the shift task (&#8220;sal-bupi&#8221; group) led to an increase in perseverative-like errors. *, p &#60; .05 vs. saline-saline. This figure has been modified from Floresco et al.20 <a href="https://www.jove.com/files/ftp_upload/52387/52387fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/52387/52387fig3highres.jpg" /> 
Figure 3. Inactivation of the Prefrontal Cortex Leaves Reversal Learning Intact. A, Trials to criterion during the initial response discrimination training by rats that would subsequently receive infusions of saline or bupivacaine (Bupi) into the medial prefrontal cortex prior to reversal training. No differences were seen. B, Trials to criterion during the reversal of the response discrimination, following medial prefrontal infusions of either saline or bupivacaine. Prefrontal inactivation did not impair reversal learning. This figure has been modified from Floresco et al.20
Data presented in Figure 4 provides an example of how requiring rats to perform &#8220;reminder&#8221; trials using the old rule prior to a strategy shift can aid in data interpretation. In this study (Enomotor and Floresco, unpublished observations), rats were matched for performance on acquiring a visual cue rule on Day 1 (Figure 4A). On Day 2, rats received vehicle or 0.2 mg/kg haloperidol. At the start of the Day 2 test session, they were given 20 trials where they were required to respond using the visual cue rule acquired on Day 1, after which the rule switched mid-session to a response discrimination. As displayed in Figure 4B, this treatment impaired retrieval of the visual cue rule during the first 20 reminder trials of the session. Subsequently, haloperidol-treated rats required fewer trials to achieve criterion (Figure 4C) and made fewer perseverative errors (Figure 4D) on the strategy shift. Note that had we not used the reminder trials prior to the shift, these data may have been interpreted as an improvement in set shifting by haloperidol. However, the impairment during the rule retrieval phase suggests that these effects are better understood as impaired memory for the previously acquired rule, which may have led to less response conflict when rats were required to learn a novel rule and thus faster shifting. 
<img alt="Figure 4" src="/files/ftp_upload/52387/52387fig4highres.jpg" /> 
Figure 4. Impaired Rule Retrieval and Facilitated Set-Shifting Induced by Haloperidol Treatment. A, Trials to criterion on visual cue discrimination from rats that were to receive vehicle (saline) or the dopamine D2 antagonist haloperidol (0.2 mg/kg) prior to the strategy shifting sequence on the following day. Animals in both groups showed comparable pre-drug performance. B, At the beginning of testing on Day 2, rats received 20 reminder trials where they were required to continue to respond using the visual cue rule from Day 1. Treatment with haloperidol significantly decreased accuracy during these reminder trials. C, After the 20 reminder trials, the rule shifted mid-session to a response discrimination. Haloperidol treated rats required fewer trials to achieve criterion during the shift. D. Haloperidol treatment also reduced perseverative errors. Although these data could suggest improved performance, the impairment in rule retrieval display in B indicates that the apparent &#8220;enhanced strategy shifting&#8221; is more likely attributable to reduced interference from the previously acquired rule. Enomoto and Floresco, unpublished observations. *, p &#60; .05 vs. vehicle.
The neonatal ventral hippocampal lesion (NVHL) manipulation has been used to model some aspects of schizophrenia in rats28, particularly cognitive impairments29,30. Briefly, an excitotoxic lesion is administered to the hippocampus of 7-day old rats, and testing is carried out in adults (60+ days postnatal). This models the hypothesized developmental trajectory of schizophrenia28. Figure 5 illustrates performance of NVHL and control rats on the pre-exposed version of the Set-Shifting: Response to Cue sequence. NVHL rats are unimpaired at learning the first rule (Response/&#8221;Set&#8221;, Figure 5A), but are dramatically impaired at shifting to the new rule (Cue/&#8221;Shift&#8221;) as shown by the increase in the number of trials required to reach criterion (Figure 5B). Moreover, this deficit was due primarily to an increase in perseverative errors, as shown in Figure 5C, suggesting prefrontal abnormalities20,21. These results confirm previous findings of impaired strategy shifting in NVHL animals using the cross-maze task29.
Similar to the data from prefrontally-inactivated animals shown above, NVHL animals were not impaired at reversal learning (Figure 6A,B), although they were slower to respond (Figure 6C,D). This negative finding implies that the observed strategy shifting deficits are not attributable to a simple inability to switch between stimuli21.
<img alt="Figure 5" src="/files/ftp_upload/52387/52387fig5highres.jpg" /> 
Figure 5. Impaired Set-Shifting in the NVHL Model of Schizophrenia. Performance on the pre-exposed version of the set-shifting sequence (Response-to-Cue) in NVHL and sham control animals. A, NVHL animals were unimpaired on the Response (&#8220;Set&#8221;) task. B, However, NVHL animals required significantly more trials than shams to reach criterion on the Visual Cue (&#8220;Shift&#8221;) task. C, Errors on the &#8220;Shift&#8221; day. NVHL animals made more perseverative errors than sham animals, but did not differ on regressive or never-reinforced errors. *, p &#60; .05 vs. sham. This figure has been modified from Placek et al.21
<img alt="Figure 6" src="/files/ftp_upload/52387/52387fig6highres.jpg" /> 
Figure 6. Lack of NVHL Impairment on Reversal Learning. A,B, NVHL and sham animals did not differ in their ability to acquire either the initial Response Learning task (&#8220;Set&#8221;), or the Response Reversal. C,D, NVHL animals were slower than shams to respond on both the &#8220;Set&#8221; and the &#8220;Reversal&#8221; tasks. This figure has been modified from Placek et al.21
Finally, pilot testing has indicated that animals are virtually unable to learn a reversal of the Cue task, i.e., to press the lever opposite the illuminated stimulus light. Five of six animals tested completed 450 reversal trials (3 days) without reaching criterion, and the sixth animal required 418 trials (Brady, unpublished observations; data not shown). This is likely because the stimulus lights are very salient and attractive cues that make it very difficult for rats to direct responding away from them. Thus, this testing sequence is not recommended.

Watch this Scientific Journal Video about Operant Procedures for Assessing Behavioral Flexibility in Rats at JoVE.com

Operant Procedures for Assessing Behavioral Flexibility in Rats

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 ...

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20.5K Views.  St. Mary's College of Maryland. 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. 