A Comparison of Adult and Adolescent Rat Behavior in Operant Learning,Extinction, and Behavioral Inhibition Paradigms

Matthew E. AndrzejewskiThe Waisman Center

Terri L. SchochetUniversity of Wisconsin-Madison

Elizabeth C. Feit, Rachel Harris, andBrenda L. MckeeThe Waisman Center

Ann E. KelleyUniversity of Wisconsin-Madison

Poor self-control, lack of inhibition, and impulsivity contribute to the propensity of adolescents to engagein risky or dangerous behaviors. Brain regions (e.g., prefrontal cortex) involved in impulse-control,reward-processing, and decision-making continue to develop during adolescence, raising the possibilitythat an immature brain contributes to dangerous behavior during adolescence. However, very fewvalidated animal behavioral models are available for behavioral neuroscientists to explore the relation-ship between brain development and behavior. To that end, a valid model must be conducted in therelatively brief window of adolescence and not use manipulations that potentially compromise develop-ment. The present experiments used three operant arrangements to assess whether adolescent rats differfrom adults in measures of learning, behavioral inhibition, and impulsivity, within the aforementionedtime frame without substantial food restriction. In Experiment 1, separate squads of rats were trained tolever-press and then transitioned to two types of extinction. Relative to their baselines, adolescent ratsresponded more during extinction than adults, suggesting that they were less sensitive to the abolishmentof the reinforcement contingency. Experiment 2 demonstrated similar age-related differences duringexposure to a differential reinforcement of low rates schedule, a test of behavioral inhibition. Lastly, inExperiment 3, adolescent’s responding decreased more slowly than adults during exposure to a resettingdelay of reinforcement schedule, suggesting impaired self-control. Results from these experimentssuggest that adolescents exhibit impaired learning, behavioral inhibition and self-control, and in concertwith recent reports, provide researchers with three behavioral models to more fully explore neurobiologyof risk-taking behavior in adolescence.

Keywords: adolescent, learning, extinction, behavioral inhibition, rats

Adolescence generally refers to the developmental period be-tween childhood and adulthood that is distinguished by physical,emotional, and behavioral changes. The adolescent period hasbeen well characterized in terms of changes in secondary sexualcharacteristics, hormonal and endocrine functions (Sisk & Foster,2004); however, behavioral changes are less understood. Theincrease in “risk-taking” behaviors, impulsivity, and distractibilityrenders adolescents more vulnerable to harm (Donohew et al.,1999; Parsons, Siegel, & Cousins, 1997; Spear, 2000) often pro-

ducing detrimental long-term consequences (Kelley, Schochet, &Landry, 2004; Weaver, 2003). For example, even though substan-tial resources have been successful at raising teens’ awareness ofthe harmful and addictive properties of smoking (Johnston,O’Malley, Bachman, & Schulenberg, 2005), 90% of cigarettesmokers begin before the age of 21 (Julien, 2001). In addition, thedisproportionately high mortality rate in adolescence because ofautomobile-related deaths has been attributed to greater risk-takingwhile driving (Jonah & Dawson, 1987). Thus, a greater under-standing of the biological underpinnings of risky behavior inadolescence might help clarify why children start smoking, drug-taking, or engage in dangerous behaviors.

Recent interest in the vulnerabilities of adolescence has focusedon the dynamic cellular, molecular, and anatomical changes takingplace in the brain as a result of normal development and/orexperience (Kelley, Schochet, & Landry, 2004). The prefrontalcortex (PFC) and its connections to the amygdala, striatum, andhypothalamus are widely thought to be involved in decision-making, emotional regulation, behavioral inhibition, and the abilityto assess the future outcomes of behavior (Cardinal, Winstanley,Robbins, & Everitt, 2004). In addition, there is considerable evi-dence for continued development of these pathways during ado-lescence and young adulthood in both human and nonhuman

Matthew E. Andrzejewski, Elizabeth C. Feit, Rachel Harris, and BrendaL. Mckee, The Waisman Center; Terri L. Schochet and Ann E. Kelley,Department of Psychiatry, University of Wisconsin-Madison.

This work was supported by National Institute on Drug Abuse (NIDA)Grants DA016465 and DA04788 to M.E.A., and DA13780 and DA14464to A.E.K. T.L.S. was supported by training Grant NIGMS GM07507 andby NIDA Predoctoral National Research Service Award DA00003. B.L.M.was supported by DA023761 from NIDA. The authors thank MargaretMartinetti for her helpful comments on earlier drafts of this article.

Correspondence concerning this article should be addressed to MatthewE. Andrzejewski, University of Wisconsin-Madison, Waisman Center,1500 Highland Avenue, Madison, WI 53719. E-mail: mandrzejewsk@wisc.edu

Behavioral Neuroscience © 2011 American Psychological Association2011, Vol. 125, No. 1, 93–105 0735-7044/11/$12.00 DOI: 10.1037/a0022038

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animal models (Cruz, Eggan, & Lewis, 2003; Erickson & Lewis,2002; Giedd, 2004; Giedd et al., 1999; Rosenberg & Lewis, 1995;Sowell, Thompson, Holmes, Jernigan, & Toga, 1999). Thus, in-creases in risk-taking behaviors during adolescence, which coin-cide with underdeveloped brain circuitries associated withdecision-making and emotional regulation, may be a result ofimmature brain development. Studying these mechanisms of braindevelopment and behavior in humans is inherently limited byethical and pragmatic concerns; thus, an animal model wouldenable further exploration of the relationship between brain devel-opment and risk-taking behaviors.

In terms of a species for such an animal model, the rat appearsto be a very good candidate. Neural development, architecturesand chemistries are similar between rats and primates, and all havebeen fairly well-characterized. Rats can be tested in a wide varietyof laboratory situations, much is known about their learning capa-bilities, and they are easily bred. The rat adolescent period, how-ever, is generally considered to last only about 2–3 weeks, frompostnatal Day 28–45 (Spear, 2000). Thus, any behavioral trainingand testing that purports to model problems of adolescence mustbe conducted in this time period. In addition, because rats aregrowing rapidly during this period, experimental manipulationssuch as food restriction should be minimized or eliminated, ifpossible, so as to not compromise this rapid growth.

Impulsivity and behavioral inhibition have been tested in labo-ratory settings with rats using many procedures, like serial reactiontime tests (SRTT; McGaughy, Dalley, Morrison, Everitt, & Rob-bins, 2002) and delay/probability aversion paradigms (Cardinal,Pennicott, Sugathapala, Robbins, & Everitt, 2001; St Onge &Floresco, 2009). However, these procedures typically requirelengthy training phases and substantial food restriction. For exam-ple, the delay/probability aversion study reported by St Onge andFloresco (2009) required nearly 50 daily sessions. These prepara-tions, therefore, do not appear optimal for studies with adolescentrats because of the short adolescent period and the possible con-founding effects of food restriction on growth and/or development.Other operant-learning-based procedures, such as extinction, differ-ential reinforcement of low-rate (DRL), and differential reinforcementof other behavior (DRO) schedules also test impulsivity and behav-ioral inhibition (Monterosso & Ainslie, 1999; Neill, 1976; Van denBergh et al., 2006), and may be more suitable for testing withadolescent rats because they can be conducted in short period of timeand perhaps, under conditions of limited food-restriction.

In the first of these arrangements, extinction, the contingencybetween the behavior and consequence is abolished which resultsin a rapid decrease in responding. Contemporary theories hold thatanimals must readily adapt to extinction or face risks associatedwith (1) missing alternative sources of reinforcement and/or (2)expending energy on ineffective strategies (Catania, 1998). In thesecond arrangement, DRL schedules provide access to reinforcersonly after two responses have been separated by a predeterminedamount of time in which no responses have occurred; the animalmust “wait” some time before a response produces a reinforcer.The third arrangement, or a DRO schedule, provides reinforcersonly after a period of time when no response has occurred; re-sponses that occur during the delay period postpone the reinforcer,punishing the response. Thus, effective performance on extinction,DRL, and DRO appear to require some learning, inhibition, and/orself-control. While adolescent rodents have been shown to engage

in risk-like behaviors in an open field test, to interact more withnovel objects and to perform more hole-pokes compared toyounger or older animals (Laviola, Macri, Morley-Fletcher, &Adriani, 2003; Spear & Brake, 1983; Stansfield, Philpot, &Kirstein, 2004), fewer studies have examined operant behavior inadolescent rodents using the extinction, DRL and DRO. A recentstudy with operant extinction (Sturman, Mandell, & Moghaddam,2010) demonstrated an impairment associated with adolescenceversus adulthood, however, these deficits were only seen underconditions of food restriction and not when adolescents and adultswere fed ad libitum. Therefore, the authors concluded that moti-vational factors were largely responsible for age-related differ-ences, rather than impulsivity or behavioral inhibition.

The purpose of the present experiments, therefore, was to deter-mine if (1) Extinction, (2) DRL, and/or (3) DRO, preparations held totest impulsivity and behavioral inhibition, produce age-related perfor-mance differences in rats in the absence of food deprivation. Ifage-related behavioral differences are found using any of these threepreparations, they are likely to serve in studies clarifying issues ofbrain development and the vulnerabilities of adolescence.

Materials and Method

Subjects

There were 132 male Sprague–Dawley rats (Harlan, Madison,WI) housed in pairs in polyethylene cages in colony room with a12:12 hr light/dark cycle with lights on at 7 a.m. Rats were alwaystested in the light (inactive) part of the cycle. One half (n � 66)were 83 (�3) days old upon arrival (Adults) and weighed, onaverage 283.6 g (SEM � 4.4). The other 66 rats were 28 (�3) daysold upon arrival (Adolescents); average weight was 80.0 g (SEM �1.70). Adolescence in rodents is generally considered as the periodencompassing sexual maturation (beginning postnatal day (PND)28 and ending with full sexual maturity at PND45); some research-ers include a late adolescent period extending to about PND56(Laviola et al., 2003; Spear, 2000). The present experiments con-sidered rats as adolescents between P28-45. All rats were weighedand handled daily and provided with food and water ad libitum,except when noted. One group of adults (n � 8) and one group ofadolescents (n � 9), were used as controls for weight gain andgrowth. These two control groups arrived at the same time as thefirst experimental groups (Experiments 1 and 2) and were weighedand handled each day but did not participate in any behavioraltesting. Care of the rats was in accordance with University ofWisconsin-Madison animal care committee guidelines.

Operant Chambers

Sessions were conducted in standard operant chambers made ofsheet aluminum and Plexiglass, enclosed in ventilated chests.White noise, at roughly 68 dB, was played continuously in theroom to block out background noise. In addition, ventilation fansin the chambers provided some masking noise continuouslythroughout the session. Two retractable levers, 6 cm apart, couldbe projected into the chamber on the right-side wall. A force of .20N was required to depress either lever and register a response.Spaced equally between the two levers was a dipper trough intowhich liquid could be delivered. The reinforcer was 3s access to

94 ANDRZEJEWSKI ET AL.

0.05 ml of 50% chocolate Ensure/50% tap water solution deliveredvia the dipper. Above the feeder trough were a row of threestimulus lights (red, yellow, and green) and a 28-V houselight;only the houselight was used in these experiments. Experimentalevents were arranged and recorded via a personal computer in thesame room as the chambers, running Med-PC IV for Windows(Med Associates, St. Alban, VT).

Food Restriction/Exposure

One day after arrival, chocolate Ensure was provided to theanimals in a small bottle with a drinking spout, which was placedon every cage for 24 hr. This was done to reduce some of thenovelty to the Ensure. Two hours before the beginning of a day’srun, all food was removed from cages. After a day’s session, foodwas replaced; Ensure was only available in the operant chambersafter the initial exposure. This food restriction (2 hr restriction perday) was maintained throughout the entirety of the experiment.The mild food restriction used in these experiments was necessaryto establish the Ensure as a reinforcer, without compromising thenormal growth and development of the adolescent rats.

Preliminary Behavioral Training

After 2 days of habituation to the new housing conditions, ratswere transitioned directly into the experiment. All sessions were30 min in length. One session per day was run; sessions were run7 days per week between 11 a.m. and 3 p.m. Preliminary trainingsessions began with the illumination of the houselight and theprojection of both levers into the chamber. Both levers into thechambers to aid in the acquisition of lever pressing and avoidthe possibility that an individual rat’s “side-bias” might decreasethe likelihood of lever-pressing. Lever presses on either lever werecounted toward the completion of the operant schedule in force.For the first three sessions, responses on either lever produced 3 saccess to Ensure. A conjoint Random Time 30 s (RT-30s) schedulewas also operative that delivered the reinforcer on average every30 s, irrespective of the rat’s behavior. This conjoint RT-30sschedule was arranged to train the rats about the location of thereinforcer, teach the rats about the signals associated with rein-forcer delivery (e.g., the sound of the dipper operation), keep therats aroused, promote exploration, and allow some sampling of thereinforcer without it being dependent on the rat’s behavior. Whilethe RT-30s schedule of Ensure delivery may appear to weaken orcompete with the operant contingency, in our experience, the RTschedule appears to promote faster operant learning, perhaps be-cause of some of the aforementioned functions. The next threesessions (Sessions 4–6) began in the same manner except that theRT-30s schedule was eliminated. During the next 4 sessions (Ses-sions 7–10), the schedule was thinned to an intermittent schedule,either a Random Ratio 4 (RR-4) or Random Interval 15 s (RI-15s)schedule. During the RR-4, each response was reinforced with aprobability of 1/4. On the RI 15 s schedule, a reinforcer was set upevery second with a probability of 1/15. These intermittent sched-ules were used to shape higher rates of responding than an FR-1schedule. Rats were eliminated from statistical analyses of behav-ior, but not growth, if they failed to make at least 100 responses inthe last two sessions (Sessions 9 and 10) of preliminary training. Ingeneral, rats were either responding at a substantial rate (e.g., 200

Rs/session) or not responding at all, by the end of preliminarytraining. Each experiment began with 8–12 rats in each group; thefinal n of each group is reported in the results section.

Experiment 1: Extinction by Omission orNoncontingent Food Delivery

Typically, extinction is accomplished by omitting reinforcers;however, the process of omitting reinforcers confounds the effectsof contingency-abolishment (“extinction”) with food-delivery-omission. By omitting reinforcers, two independent variables havechanged at the same time. The experimental operation of extinc-tion could entail the continued delivery of food, but not contingenton responding, which would control for the influence of fooddelivery, per se, on responding. In this experiment, responding wasextinguished in one of two ways: by omission and by noncontin-gent RT-15s food delivery. One group of adolescents and onegroup of adults were exposed to extinction by omission (Experi-ment 1a); another two groups were exposed to the extinction byRT-15s food delivery schedule (Experiment 1b). RT-15s waschosen because it would closely match the rate of food deliveryduring the RI-15s phase.

These experiments addressed the question of whether the re-sponding of adolescents and adults decreases in a similar fashionduring extinction. Extinction has been shown to be highly corre-lated with other measures of impulsivity, like delay aversion (Vanden Bergh et al., 2006). The sequence of training/testing conditionsin Experiment 1 is presented in Table 1.

This experiment had two separate runs. The first run had fourrats in each group, and although a trend toward an effect of agewas found, this run had very little statistical power. A secondreplication was conducted later with an additional eight rats ineach group. The data were very consistent between the two runs,thus they were combined and are presented in the results section.

Because age differences were found in this experiment, a furthertest was conducted to clarify the role of age with the same rats. Inthis second phase of the experiment, all rats were maintained instandard housing conditions, but not run in the operant chambers,until the adolescents were 83 days old, nearly the age of the adultgroup at the beginning of experimentation. The “Aged” groupswere then run again through the extinction experiment, with theexception of the first 6 days of preliminary training (ConjointRT-30s/FR-1). These preliminary training sessions were deemedunnecessary because lever-pressing had already been established;once the rats were returned to the chamber they quickly beganlever pressing. Before the second extinction, all rats were exposedto four sessions of RI-15” retraining; the last three sessions servedas the baseline for the second extinction phase. All rats were testedtwice, with the following exceptions: 3 adults in the first run wereinadvertently not tested; 1 adolescent met the criteria for inclusionfor the second, but not first, extinction; and 1 aged adolescent diedafter the second phase of preliminary training. The pattern of theseomissions complicated the subsequent statistical analyses. Thus,we elected to perform repeated measures ANOVA, focusing ondifferences between groups during each extinction phase, but notwithin groups across extinctions (e.g., adolescent vs. aged adoles-cent) because the pattern of missing values required that weeliminate a substantial number of data points.

95ADOLESCENT RAT BEHAVIOR

Dependent Measures

The principle dependent measure was the proportion of baseline(POB) responding. Because there was a good deal of variability inresponse rates between rats, each rat’s average baseline rate ofresponding was computed from the last three sessions of RI-15”before extinction. Response rates during the testing sessions weredivided by this baseline rate to arrive at a proportional measure,standardized around 1. Adult rats generally responded at higherrates than adolescents, but this is likely because of the fact thatadults were larger and pressing the lever was easier for them. POBmeasures are used extensively in research interested in changes inresponse rate as a function of changes in other variables (Nevin,1988). Within-session rates of responding in 5 min bins served asanother dependent variable.

Experiment 2: DRL

A DRL schedule reinforces a response after a fixed amount oftime has elapsed (the delay interval) in which no response hasoccurred. If the rat makes a response in the delay interval, the timeris reset to its original value. Because consecutive responses on

DRL must exceed a certain interresponse time (IRT), DRL schedulesare sometimes called “IRT” schedules or “ IRT” schedules. DRLschedules are widely considered tests of self-control or responseinhibition (Monterosso & Ainslie, 1999; O’Donnell, Marek, &Seiden, 2005; Peterson, Wolf, & White, 2003). However, because therat must space responding to meet the timing contingencies involvedin the DRL, the DRL might also tap into “timing” abilities.

In the present experiment, two DRL values were used, 10 and15 s. In general, DRL suppresses lever-pressing, with longervalues producing more suppression. Experiment 2a, which endedwith exposure to DRL-10s, used an RR-4 schedule during prelim-inary training. This resulted in the adult group earning morereinforcers per session than the adolescent group, because theadults responded at higher rates than the adolescents. In an attemptto reduce this discrepancy, the schedule was changed to a RI-15sschedule in Experiment 2b, which ended with exposure to DRL-15s. The value DRL-15s was chosen to remain consistent with theschedule value in the preliminary training (RI-15s). Althoughdiscrepancies were still observed, adolescent rats earned about75% of the reinforcers adults earned. Table 2 summarizes the orderof conditions of Experiment 2.

Table 1Sequence of Operant Contingencies in Experiment 1: Extinction

Session Ages (adol/adult) Experiment 1a (omission) Experiment 1b (RT 15s)

1 31/86 Conjoint FR 1/RT 30s Conjoint FR 1/RT 30s Preliminarytraining2 32/87 Conjoint FR 1/RT 30s Conjoint FR 1/RT 30s3 33/88 Conjoint FR 1/RT 30s Conjoint FR 1/RT 30s4 34/89 FR 1 FR 15 35/90 FR 1 FR 16 36/91 FR 1 FR 17 37/92 RI 15s RI 15s8 38/93 RI 15s RI 15s9 39/94 RI 15s RI 15s

10 40/95 Extinction by omission Extinction by RT food Testing11 41/96 Extinction by omission Extinction by RT food12 42/97 Extinction by omission Extinction by RT food13 43/98 Extinction by omission Extinction by RT food14 44/99 Extinction by omission Extinction by RT food

Table 2Sequence of Operant Contingencies in Experiment 2: Differential Reinforcement of Low Rates

Session Ages (adol/adult) Experiment 2a (DRL 10s) Experiment 2b (DRL 15s)

1 31/86 Conjoint FR 1/RT 30s Conjoint FR 1/RT 30s Preliminarytraining2 32/87 Conjoint FR 1/RT 30s Conjoint FR 1/RT 30s3 33/88 Conjoint FR 1/RT 30s Conjoint FR 1/RT 30s4 34/89 FR 1 FR 15 35/90 FR 1 FR 16 36/91 FR 1 FR 17 37/92 RR 4 RI 15s8 38/93 RR 4 RI 15s9 39/94 RR 4 RI 15s

10 40/95 DRL 10s DRL 15s Testing11 41/96 DRL 10s DRL 15s12 42/97 DRL 10s DRL 15s13 43/98 DRL 10s DRL 15s14 44/99 DRL 10s DRL 15s

96 ANDRZEJEWSKI ET AL.

Experiment 3: DRO Behavior

On a DRO schedule (also known as a resetting delay), the ratmust make a response and wait for a predetermined amount of time(the delay interval) before a reinforcer is delivered. Responses inthe delay interval reset the timer, although a response after thedelay interval is timed out is not required for the reinforcer, incontrast to a DRL schedule. DRO schedules generally suppressresponding, with longer delay values producing greater decrementsin responding. However, DRO and DRL schedules differ in im-portant ways, specifically in the possible discriminative effects ofreinforcer delivery in a DRO schedule, which are absent in a DRLschedule. In other words, the delivery of a reinforcer in a DROschedule may signal the rat to make a single response and wait.The spontaneously hypertensive rat, widely thought to modelattention deficit/hyperactivity disorder, is impaired in operant ac-quisition under DRO contingencies (Hand, Fox, & Reilly, 2006),suggesting that DRO may assay impulsivity.

In Experiment 3, a single DRO value of 15 s was used. Twogroups of rats, one adolescent group and one adult group wereused. Training conditions were similar to Experiment 1 and 2; thesequence of conditions is presented in Table 3.

Data Analysis

Data were analyzed using RM ANOVA, with age and sessions(or bins) as factors. Significance level was set at .05. Student-Newman–Keuls post hoc tests were conducted, when appropriate.Details of the specific tests conducted are contained in the resultssection for each experiment.

Results

Weight Gain/Growth

Figure 1 shows the average weight gain, per day, for the 6experimental groups and two control groups. Because mild foodrestriction was used, average weight gain was compared to that oftwo control groups exposed to identical housing conditions but had

neither exposure to Ensure/pellets nor to the operant chambers.These data are presented to attenuate any concern that the mild foodrestriction used in these experiments might compromise health anddevelopment of the adolescents, thereby affecting behavior.

As can be seen from Figure 1, adolescents generally gainedmore weight than adults, in any given experiment, which is notsurprising given their relative position on the growth curve. Two-way ANOVA on weight gain revealed statistically significanteffects of age, F(1, 108) � 87.11, p � .001, experiment, F(3,108) � 4.64, p � .001, and Age � experiment interaction, F(3,108) � 3.10, p � .03. Post hoc comparisons on the interactioneffects revealed that within each experiment, control groups in-cluded, the adolescent groups gained more weight than the adults.No differences in weight gain were seen between the adolescentgroups in Experiment 1–3 and the control. The adults in Experiment3 gained more weight than controls. Response rates during the pre-liminary training sessions were highest in Experiment 3, resulting ina greater number of reinforcers. Thus, this weight gain was likelybecause of the additional calories provided by the Ensure.

Experiment 1: Extinction of Operant Responding

Figure 2 shows the effects of extinction by omission on operantresponding. In all, 12 adolescents and 12 adults began the exper-iment, divided evenly between the two arrangements (n � 12 percondition); final n’s are shown in the figures.

As can be seen in Figure 2, extinction by omission of operantresponding was impaired in adolescent rats when compared toadults. In Panel A, RM ANOVA revealed main effects of Age,F(1, 20) � 5.670, p � .027 and Session, F(4, 80) � 108.43, p �.001, but no Age � Session interaction, F(4, 80) � 0.508, p �.730. Analyses of within-session patterns of responding, shown in

Table 3Sequence of Operant Contingencies in Experiment 3:Delay of Reinforcement

SessionAges

(adol/adult)Experiment 3(DELAY 15s)

1 31/86 Conjoint FR 1/RT 30s Preliminary training2 32/87 Conjoint FR 1/RT 30s3 33/88 Conjoint FR 1/RT 30s4 34/89 FR 15 35/90 FR 16 36/91 FR 17 37/92 RI 15s8 38/93 RI 15s9 39/94 RI 15s

10 40/95 DRO 15s Testing11 41/96 DRO 15s12 42/97 DRO 15s13 43/98 DRO 15s14 44/99 DRO 15s

Contro

l

Exp 1

Exp 2

Exp 3

Contro

l

Exp 1

Exp 2

Exp 3

Ave

rage

Wei

ght G

ain

(g p

er d

ay)

0

2

4

6

8Adults Adolescents

**

**p < .01 compared to age-matched controls

Figure 1. Average weight gain per day, over the course of experimenta-tion, for adults (left half) and adolescents (right half of figure), for the threeexperiments (black and shaded bars) and control groups (open bars) thatwere not part of the present experiments. The adult group from Experiment3 gained more weight per day than the adult control group. No differencesin the amount of weight gained were found among the adolescent groups.�� p � .01 in comparison to same-age control group.

97ADOLESCENT RAT BEHAVIOR

Panels B and C, show that response rates were not significantlydifferent between adolescent and adult groups during Session 1,but were different during Session 5 of extinction (main effect ofAge, F(1, 21) � 5.260, p � .032 and Bin (F(5, 105) � 13.782, p �.001, but no interaction, F(5, 105) � 0.949, p � .453).

After the adolescents reached the same age as the original adultgroup, the second phase was run and those results are presented inPanels D, E, and F of Figure 2. Although the expected effects ofsession (in Panel D) and Bin (in Panels E and F) were highlysignificant, no statistically significant effects of Age or interactionwere found (all F’s � 1.200).

Identical analyses were conducted on the data from the extinc-tion by RT food delivery. Figure 3A shows that the effect of Ageon extinction with continued food delivery was statistically signif-icant, F(1, 20) � 6.477, p � .019; the effect of Sessions was alsohighly significant, F(4, 80) � 53.252, p � .001, but the Age �Session interaction was not.

Panels B and C show that adolescents and adults did not differin rate of responding during Session 1, but did during Session 5(main effect of age: F(1, 19) � 4.888, p � .040). Once again, theeffects of Bin were highly significant (in both sessions), but therewere no Age � Bin interactions.

The second phase produced the surprising result that the re-sponding of Aged Adolescents continued to extinguish moreslowly than aged adults, as shown in Panel D (Age effect: F(1,16) � 9.205, p � .008). However, within-session analysis ofresponse rates during Sessions 1 and 5 of extinction, indicated nodifferences between groups as shown in Panels E and F.

Experiment 2: DRL

Figure 4 shows the results of exposure to DRL-10s. As can beseen in Panel A, adult rats’ POB responding was lower duringDRL-10s than adolescents. Statistically significant effects of Age,F(1, 14) � 15.18, p � .002 and Sessions, F(4, 56) � 30.35, p �.001, were noted, however no interaction was found, F(4, 56) �0.37, p � .83. In addition, although total responses per session (B)were significantly higher for adults during baseline (main effect ofAge: F(1, 14) � 13.08, p � .003) they were lower for adults duringthe third and fifth sessions of DRL-10s (main effect of Age: F(1,14) � 2.72, p � .12; main effect of Sessions: F(4, 56) � 46.22, p �.001; Age � Sessions interaction: F(4, 56) � 6.58, p � .001; Sessions2 and 4 differences were nearly significant at p � .08).

Extinction

1 2 3 1 2 3 4 5

Pro

port

ion

of B

asel

ine

(PO

B)

Res

pond

ing

0.00

0.25

0.50

0.75

1.00

1.25

Adult (n = 12)Adol (n = 10)*

RI-15s

5 min bins

1 2 3 4 5 6

Res

pons

e R

ate

(per

min

)0

5

10

15

20

5 min bins

1 2 3 4 5 60

1

2

3

4

5 min bins

1 2 3 4 5 6

Res

pons

e R

ate

(per

min

)

0

5

10

15

20

5 min bins

1 2 3 4 5 60

1

2

3

4

1st Extinction

1st Session 5th Session*

2nd Extinction

5th Session1st Session

Baseline Test

A

C

D

E

Extinction

1 2 3 1 2 3 4 5

Pro

port

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of B

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(PO

B)

Res

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0.00

0.25

0.50

0.75

1.00

1.25

Aged Adult (n = 9)Aged Adol. (n = 11)

BBaseline Test

RI-15s

D

F*p < .05

Extinction by Omission

Figure 2. Responding during Extinction by Omission. Panels A and D: Average proportion of baselineresponding (POB) over sessions during the last 3 days of preliminary training (“Baseline”) and the 5 days ofextinction by omission (“Test”) for a group of adult rats (black symbols) and a group of adolescent rats (graysymbols) at two different ages (circles and triangles). The dotted line represents the change in contingencies fromRI-15s to Extinction. The adolescents had higher POB than the adults during extinction (� p � .05, main effectof age). Panels B and C: The average number of responses per minute during Sessions 1 and 5 of extinction forthe same groups shown in Panel A. The adolescents had higher response rates than the adults during Session 5(� p � .05, main effect of age), but not during Session 1. Panels E and F: The average rate of responding duringthe first and fifth sessions of the second extinction for each of the two groups (aged adults and aged adolescents).Responding was not different between the two groups.

98 ANDRZEJEWSKI ET AL.

Performance on a DRL schedule may be difficult to interpret ifbaseline responding is already meeting the DRL contingenciesbefore the change (e.g., low baseline rates of responding during theRR-4, such that there are a high proportion of long, or �10s,IRTs). In other word, a rat’s behavior might be less sensitive to thechange from RR-4 to DRL-10s because its behavior does not, infact, encounter the reset of the timer contingency. Panel C showsthe results of an analysis on IRTs. There was no Age main effect,F(1, 14) � 0.00, p � .999 on IRTs, but both Bin, F(5, 70) �724.73, p � .001 and the Age � Bin interaction, F(5, 70) � 13.83,p � .001 were significant; the results of the post hoc tests founddifferences in proportions of IRTs �2s, 2-4s, and 4-6s, butnot�10s, thereby suggesting that adolescents were not meeting theIRT contingency initially to any greater degree than the adults. Incontrast, by Session 5, ANOVA on IRT distributions (D) revealedsignificant difference in the proportion of IRTs�10s (and also �2sand 4–6 s; Age � Bin interaction, F(5, 70) � 5.25, p � .001).IRTs were further classified in two ways: short IRTs (�2s) andreinforced IRTs (�10s). ANOVA on short IRTs revealed an Ageeffect, F(1, 14) � 4.652, p � .049 and Session effect, F(4, 56) �42.254, p � .001, but no interaction of Age and Session, F(4,56) � 0.48, p � .75. More importantly, an ANOVA on reinforcedIRTs across sessions of DRL, shown in Panel F, revealed a main

effect of Age, F(1, 14) � 11.45, p � .004, Session, F(4, 56) �11.36, p � .001, and interaction, F(4, 56) � 2.92, p � .03; post hocanalyses revealed that the adolescents had a smaller proportion ofreinforced IRTs during Sessions 3 and 5 when compared to adults.

Figure 5 shows the results of Experiments 2b. Panel A shows aneffect of Age on POB during DRL-15s, F(1, 36) � 7.08, p � .01and an effect of Sessions, F(4, 36) � 4.97, p � .01; no interactionwas found. Panel B shows that response rates were higher in theAdult group during baseline (Age: F(1, 9) � 24.42, p � .01,Session: F(2, 18) � 0.12, p � .89, Age � Session: F(2, 18) �0.37, p � .70). However, that difference was reversed duringDRL-15s exposure (Age: F(1, 9) � 1.65, p � .24, Session: F(4,36) � 20.71, p � .01, Age � Session: F(4, 36) � 9.081, p � .01).Post hoc analyses found that the adult group responding at higherrate during the first session of DRL, but at a lower rate during thesecond. Age differences were nearly significant during the thirdand fifth sessions ( p � .07).

Panel C shows that the relative frequency of IRTs (in 3 s), atany given bin, were not different between groups in the firstsession. However, by the fifth session (D), adults had a sub-stantially greater proportion of reinforced IRTs ( p � .01).Panels E and F of Figure 5 show the changes in the proportionof brief and reinforced IRTs (�3 or 15 s) over the course of the

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Figure 3. Responding during Extinction by RT-15s. Panels A and D: Average proportion of baselineresponding (POB) over sessions. The adolescents had higher POB than the adults during first extinction and asaged adolescents during the second extinction (� p � .05, main effect of age). Panels B and C: The averagenumber of responses per minute during Sessions 1 and 5 of extinction for the same groups shown in Panel A.The adolescents had higher response rates than the adults during Session 5 (� p � .05, main effect of age), butnot during Session 1. Panels E and F: The average rate of responding during the first and fifth sessions of thesecond extinction for each of the two groups (aged adults and aged adolescents). Responding was not differentbetween the two groups in Sessions 1 and 5.

99ADOLESCENT RAT BEHAVIOR

five sessions of DRL-15s. Panel E shows that the relativefrequency of short IRTs was not different between age groups(Age: F(1, 9) � 0.48, p � .51). There was an effect of Session:F(4, 36) � 30.66, p � .01 and a significant Age � Sessioninteraction: F(4, 36) � 4.25, p � .01). Post hoc analysesrevealed one difference between age groups during the secondsession. More importantly, even though the adult and adoles-cent groups begin the DRL portion of the experiment emittingroughly the same proportion of reinforced IRTs, as shown inPanel F, the adult’s proportion quickly increased over sessions,whereas the adolescent’s proportion changed only slightly

(Age: F(1, 9) � 7.22, p � .03, Session: F(4, 36) � 25.09, p �.01, Age � Session: F(4, 36) � 6.71, p � .01; results of posthoc tests are noted on Panel F).

Experiment 3: DRO Performance Is Impaired inAdolescent Rats

Figure 6 shows the results of Experiment 3, which exposed onegroup of adult rats and one group of adolescent rats to a DRO 15 sschedule. ANOVA found a statistically significant effect of age,F(1, 11) � 25.48, p � .001, a reliable effect of sessions, F(4,

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Figure 4. Responses measures and IRTs during DRL-10s. A: The POB responding across sessions duringexposure to a DRL-10s. The dotted line represents the change in contingencies from RR-4 to DRL-10s. POB washigher in the adolescent group during DRL-10s (�� p � .01). B: Average rates of responding for each groupacross the same sessions represented in Panel A. Although baseline responding was higher in the adult group(�� p � .01), responding in the adults was lower than the adolescents during Sessions 3 and 5 of DRL-10s (� p �.05, post hoc comparisons following significant interaction). C: Relative frequency distribution of interresponsetimes (IRTs) in 2 s bins during the first session of exposure to the DRL-10s (� p � .05, post hoc between agegroup differences following significant Age � Bin interaction). Note that IRTs greater than 10 s producedreinforcers, represented by a dotted line. D: Relative frequency distribution of interresponse times (IRTs) in 2-sbins during the fifth session of exposure to the DRL-10s (� p � .05, post hoc between age group differences).E: The proportion of brief or “impulsive” IRTs across sessions for the two groups exposed to DRL-10s (�� p �.01, main effect of age). F: The proportion of reinforced IRTs across sessions for the two groups exposed toDRL-10s (� p � .05, �� p � .01, post hoc between age group differences following significant Age � Bininteraction)

100 ANDRZEJEWSKI ET AL.

44) � 53.36, p � .001, but no interaction (F � 0.93). Once again,there was an age-dependent difference in absolute response ratesduring the baseline training, F(1, 11) � 12.99, p � .001, butduring DRO, response rates for the adult group were at or belowthose of the adolescent group by the second session, although nostatistically significant differences were found.

Discussion

The present experiments demonstrate that adolescent rats(�41– 45 days of age during testing), when compared to iden-

tically treated adult rats, were less sensitive to a change inoperant contingencies from intermittent reinforcement to ex-tinction, DRL, or DRO, situations that are widely held to testbehavioral inhibition and/or self-control (Monterosso & Ain-slie, 1999; Neill, 1976). The present results, in combinationwith recent data using an intolerance-to-delay protocol (Adriani& Laviola, 2006) and extinction of operant nose-poking (Stur-man, Mandell, & Moghaddam, 2010), support the contentionthat adolescent rats have impaired self-control and/or behav-ioral inhibition. More importantly, the present results provideresearchers several additional behavioral paradigms to more

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Figure 5. Response measures and IRTs during DRL-15s. A: The POB responding across sessions of theDRL-15s test. The dotted line represents the change in contingencies from RI-15s to DRL. POB was higherin the adolescent group during DRL-15s (�� p � .01, main effect of age). B: Average rates of respondingfor each group across the same sessions represented in Panel A (� p � .05, p � .01, main effect of age andpost hoc between age comparisons following significant interaction). C: Relative frequency distribution ofinterresponse times (IRTs) in 3-s bins during the 1st session of exposure to the DRL-15s. D: Relativefrequency distribution of interresponse times (IRTs) in 3-s bins during the fifth session of exposure to theDRL-15s (�� p � .01, post hoc between age comparison following significant interaction). E: Theproportion of short IRTs across sessions for the two groups exposed to DRL-15s (� p � .05, post hocbetween age comparisons following significant interaction). F: The proportion of reinforced IRTs acrosssessions for the two groups exposed to DRL-15s (�� p � .01, post hoc between age comparisons followingsignificant interaction).

101ADOLESCENT RAT BEHAVIOR

fully study the biological underpinnings of impaired behavioralinhibition in adolescents without substantial food deprivationand within the relatively brief adolescent period of the rat.

Alternatives to Behavioral Inhibition Impairments

While the present experiments seemingly demonstrate that ad-olescents’ behavior does not adapt as readily as adults to extinc-tion, DRL, or DRO, several alternative explanations require con-sideration. First, several theories of operant extinction, which canalso be applied to DRL and DRO performance, have relevance tothe present experiments. For example, habit strength-based theo-ries (e.g., Hull, 1943) predict that extinction or behavioral adap-tation proceeds as a function of the number of reinforcers earned.Behavior that has produced more reinforcers will have greater

strength, and habits with greater strength will be more resistant toextinction or change (Hilgard & Bower, 1975; Hull, 1943). Thepartial-reinforcement extinction effect (PREE) predicts that par-tially reinforced (i.e., “PRF” or intermittently reinforced) re-sponses will show greater resistance to extinction than a continu-ously reinforced responses because exposure to PRF necessarilyinvolves occasions where responses did not produce reinforce-ment. Behavioral Momentum Theory (“BMT,” Nevin, 1988) sug-gests that, all else being equal, the response associated with thehigher reinforcement rate will be more resistant to extinction orchange. In the current experiments, the adults had earned a greaternumber of reinforcers for lever-pressing, had higher rates of re-sponding, and had higher rates of reinforcement, but their behaviorchanged more quickly when exposed to extinction, DRL, andDRO, suggesting that habit-strength theories, PREE and BMTcannot account for the present results.

A second, intuitive, suggestion is that adults should extinguishor adapt more slowly because the response (i.e., depressing a lever)is easier for them given their size. The “response cost” of lever-pressing is less for adults thereby making responding during ex-tinction, DRL or DRO more likely. This size differential shouldhave worked in favor of a more rapid extinction or change in theadolescents, a prediction that did not hold. Thus, the present resultsstrongly indicate that adaptation to extinction, DRL, or DRO isslower in comparably treated adolescents than adults, regardless ofbaseline rates of responding, reinforcement, or size.

A third possible explanation in DRL responding schedules maylie in the fact that these schedules test some aspect of “timing.”That is to say, adolescent rats may be impaired in their ability torepresent the passage of time when compared to adults. Mon-terosso and Ainslie (1999) recently argued that while DRL hasbeen seen as the gold standard test of behavioral inhibition, it mayalso lend itself to an intolerance to delay (essentially “timing”)interpretation. Recent experiments, using a multivariate factoranalysis, demonstrate that school-aged boys’ performance on DRLloaded on a factor independent of inhibitory behavioral control(Avila, Cuenca, Felix, Parcet, & Miranda, 2004). In other words,the correlation, in adolescent boys, between DRL performance andinhibitory control measured in other ways (e.g., the “Stop Task”and the Continuous Performance Test) was not significant, al-though it did correlate with performance on other tasks (e.g., theWisconsin Card Sorting Test) supposedly unrelated to behavioralinhibition. Age-dependent insensitivities to delay contingencieshave been demonstrated in human children in decision makingcontexts (Crone, Bunge, Latenstein, & van der Molen, 2005).Moreover, recent research indicates that undergraduates demon-strating high-impulsivity are less sensitive to punishment contin-gencies than their normal counterparts (Potts, George, Martin, &Barratt, 2006). The present rat data are therefore consistent withsome contemporary research showing age-related insensitivity todelays in humans.

A fourth possibility that could account for the present results isthat the stress produced by shipping and the relatively shortcolony-habituation period (2 days) produced adverse effects onbehavior. While the adult groups were shipped at the same time,the effects of stress are known to vary across age. For example,“juvenile” stress (from ages 27–29 days) affects learning andproduces increased freezing to a cue, less novel-setting explora-tion, and poor active avoidance learning when tested during adult-

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102 ANDRZEJEWSKI ET AL.

hood in comparison to rats receiving similar stress but duringadulthood (M. Tsoory & Richter-Levin, 2006; M. M. Tsoory,Guterman, & Richter-Levin, 2010). It remains feasible that thestress of shipping affected the adolescents differently than adultsand this resulted in the deficits in extinction, DRL and DROlearning observed here; these alternatives should be explored infuture experimentation.

A fifth possible explanation for the present results is simply thatadolescents do not learn or adapt to new contingencies as quicklyas adults. The present results closely conform to a recent reportwhich demonstrated that adolescents can learn an operant response(a nosepoke) as readily as adults, but extinction of that response isimpaired in adolescents (Sturman, Mandell, & Moghaddam,2010). Although methodological differences exist between theirreport and the present data (e.g., dependent measures, responsestopographies, deprivation conditions), taken together, theystrongly suggest that extinction of operant responding occurs moreslowly in adolescents. Extinction entails new learning about achange in circumstance: previously reinforced behavior patternsare no longer effective. Although explanations based on responsestrength, rate of reinforcement, and response costs do not appear toapply to the current data, there is the real possibility that adoles-cents do not learn as quickly as adults. The fact that adolescentspersist in patterns of responding under extinction, DRL, and DROfor longer periods than adults may help explain behavior problemsassociated with adolescence, like continuing to behave in ways thatare no longer effective. This also leads to intriguing questions forfurther research: do adults exercise self-control and less risk-takingbecause they learned from their experience during their adoles-cence or are these age-related behavioral differences a result ofimmature neurobiological mechanisms? Can deficits in extinctionduring adolescence be attenuated by practice, therapy, or experi-ence?

Neurobiology of Operant Extinction, DRL, and DROCorrelate With Immature Adolescent BrainDevelopment

Explicit studies on the neurobiology of operant extinction, DRL,and DRO are fairly scant, but suggest a crucial role for frontalcortical structures and for dopamine. For example, orbital frontalcortex (OFC) ablations in adult rhesus monkeys lead to deficits inoperant extinction (Butter, Mishkin, & Rosvold, 1963). Further, ifone considers reversal learning as involving extinction (i.e., oneresponse strategy is no longer reinforced while another is), thenmany studies corroborate a role for the OFC (Chudasama &Robbins, 2003; Schoenbaum, Chiba, & Gallagher, 2000; Schoen-baum, Setlow, Nugent, Saddoris, & Gallagher, 2003). The OFChas traditionally been characterized as a critical structure involvedin behavioral flexibility, and a role for the OFC in extinction, DRLand/or DRO is entirely consistent with this position, as exposure tothese contingencies involves learning or adapting to new circum-stances.

Behavioral inhibition also engages processes in the prefrontalcortex (PFC). Lesions of the mouse or rat PFC or hippocampushave been shown to disrupt DRL performance, but lesions of thedorsal striatum do not (Cho & Jeantet, 2010; Neill, 1976; Neill &Herndon, 1978). Timing behavior has been shown to be differen-tially sensitive to PFC lesions, but not hippocampal lesions (Di-

etrich & Allen, 1998), which may impact DRL performance, assuggested earlier. Septal lesions disrupt DRL and DRO behavior(Atnip & Hothersall, 1975; Fried, 1972), however, the extent ofthese lesions is indeterminate (especially with respect to theireffects on hippocampal functioning). Moreover, other studies sug-gest that the response suppression contingencies of DRL are ef-fective in rats with septal lesions when tested with adequatecontrols (Ellen, Mokohon, & Richardson, 1978). Taken together,extinction, DRL, and DRO appear to involve dissociable processesin the PFC, OFC, VLS, and quite possibly the hippocampus, butnot in the DS. DRL seems to involve structures that subserve bothbehavioral inhibition and timing, with the hippocampus and PFCperhaps involved in those respective processes.

Dopamine (DA) signaling also appears to mediate some of theprocesses related to extinction, DRL, and DRO. For example, DAtransporter knock out mice respond more during extinction thanwild-type controls (Hironaka, Ikeda, Sora, Uhl, & Niki, 2004). DAefflux in the nucleus accumbens is significantly reduced by ex-tinction when compared to variable interval reinforcement (Ahn &Phillips, 2007), although extinction and NAcc DA depletion pro-duce different behavioral profiles (Salamone, Kurth, McCullough,& Sokolowski, 1995). As noted above, DRL performance isstrongly impacted by DAergic manipulations in distinct regions ofthe striatum (Neill & Herndon, 1978; Neill, Peay, & Gold, 1978),and is impaired by disruptions in DAergic signaling produced byamphetamine withdrawal (Peterson, Wolf, & White, 2003). Takentogether, DAergic signaling processes are strongly implicated inbehavioral inhibition and impulsivity (Arnsten, 1997).

It is important to enumerate the neurocircuitry and neurochem-istry mediating extinction, DRL, and DRO learning, and to com-pare those processes to neuroanatomical and neurochemical devel-opmental profiles, for the purposes of corroborating behavioraldeficits with immature brain structures as well as elucidating someof the functional, behavioral consequences of adolescence. Indeed,adolescence is a dynamic period of brain development. There aresubstantial data suggesting continued development of the PFC andits connections to the amygdala and striatum (Cruz, Eggan, &Lewis, 2003; Cunningham, Bhattacharyya, & Benes, 2002; Erick-son & Lewis, 2002; Giedd, 2004; Giedd et al., 1999; Rosenberg &Lewis, 1995; Sowell, Thompson, Holmes, Jernigan, & Toga,1999). In addition, while direct evidence is lacking, it is assumedthat the OFC undergoes continued maturation during childhoodand adolescence (Happaney & Zelazo, 2004). Moreover, dopami-nergic systems undergo significant alterations during adolescence,including changes in DA concentration, synthesis, and turnover,modifications of DA fiber density and receptor pruning, namelyD1 receptors, whose activation in the PFC are held to be crucialduring operant learning (Baldwin, Sadeghian, & Kelley, 2002).Therefore, deficits in extinction, DRL, and DRO learning duringadolescence perhaps reflect immature OFC-, PFC-related, and/orDAergic systems. These learning deficits demonstrate a certaininsensitivity to consequences or outcome, widely considered to beone of the hallmarks of behavior problems during adolescence(Kelley, Schochet, & Landry, 2004)

Summary

The primary goal of the present experiments was to determinesuitable behavioral assays of age-related differences in rats, such

103ADOLESCENT RAT BEHAVIOR

that future research combining invasive pharmacological, physio-logical, or endocrinal methods could help uncover the vulnerabil-ities conferred by adolescence. Indeed, combined with recent re-ports, the present results confirm that adolescents performdifferently than adults when exposed to tests of impulsivity andbehavioral inhibition, like operant extinction, DRL, and DRO.However, the present research also eliminated the potential con-founding effect of food deprivation, which is typical in operantexperiments. The present experiments used only 2 hr food restric-tion, and a highly palatable reinforcer (chocolate Ensure). Thus,the results cannot be attributed to effects on growth and develop-ment, but rather to the features of adolescence, itself. Given thatoperant paradigms are used to assess the reinforcing efficacy ofdrugs of abuse (e.g., self-administration; Donny et al., 1999),self-control (e.g., delay aversion; Evenden & Ryan, 1999), pre-clinical antidepressant screening (e.g., DRL (O’Donnell, Marek, &Seiden, 2005), and attention (e.g., signal detection; Berridge et al.,2006), the present findings increase the number of validated mod-els for researchers studying adolescence.

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Arnsten, A. F. (1997). Catecholamine regulation of the prefrontal cortex.Journal of Psychopharmacology, 11(2), 151–162.

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Received May 14, 2010Revision received September 30, 2010

Accepted October 18, 2010 �

105ADOLESCENT RAT BEHAVIOR