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Figure 1.
Schematic Representation of the Human and Rat Response Bias Probabilistic Reward Task
Schematic Representation of the Human and Rat Response Bias Probabilistic Reward Task

A, In each trial, human participants were asked to choose whether a short (11.5 mm) or long (13 mm) mouth (briefly flashed for 100 milliseconds) had been presented on a mouthless schematic face by pressing a key (eg, z for short and / for long). In each of the 3 blocks (100 trials/block), the mouth stimuli were pseudorandomly presented in an equal number. For some of the correct trials, the participant received monetary reinforcement (5 cents). Unbeknownst to the participants, the reinforcement schedule was designed to favor 1 mouth length (ie, rich) over the other (ie, lean) in a 3:1 ratio. Only 40 correct trials were rewarded in each block (30 rich and 10 lean). Participants were instructed that the goal of the task was to win as much money as possible and that not all correct responses would receive a reward feedback. Response bias, our main variable of interest, was calculated as log b = ½ log [(richcorrect * leanincorrect)/(richincorrect * leancorrect)]. As evident from the formula, a high response bias emerges when participants tend to correctly identify the rich stimulus and misclassify the lean stimulus. Discriminability, which is the degree to which the participant can distinguish the 2 target stimuli and is a measure of task difficulty, was used as a control variable and was calculated as log d = ½ log [(richcorrect * leancorrect)/(richincorrect * leanincorrect)]. These formulae include the addition of 0.5 to each cell to allow for estimation in cases with a zero cell. Accuracy (percentage hit rate) and reaction time in response to the rich and lean stimuli represented additional secondary behavioral variables. B, Rats were food restricted and trained to discriminate between 2 tones varying in duration (5 kHz or 60 dB and 0.5 seconds or 2 seconds) by pressing 1 of the 2 levers associated with each tone. Tone durations and lever sides were counterbalanced across subjects and tones were presented in a random order over 100 trials. Each trial was initiated with presentation of a tone, after which levers were extended and rats had a 5-second limited hold period to respond. In each trial, correct identification of tones resulted in a single 45-mg food pellet (Test Diet 5TUM; Richmond, Indiana). Both levers retracted after a correct, incorrect, or omitted response, followed by a variable intertrial interval (5-8 seconds). Rats were trained daily until achieving at least 70% accuracy for 5 consecutive days. Rats that were successful in discriminating the tones were then trained with tone durations of 0.7 and 1.8 seconds for 2 days and tone durations of 0.9 and 1.6 seconds for 2 days. During a subsequent test session, the ambiguous tone durations (ie, 0.9 and 1.6 seconds) were reinforced for 60% and 20% of correct responses (counterbalanced across subjects) over 100 trials, which is identical to the 3:1 reinforcement ratio used in the human Response Bias Probabilistic Reward Task.30 Response bias, the primary variable, as well as the 3 secondary behavioral variables (discriminability, accuracy, and reaction time), were computed using identical formulae as for the human experimental data.

Figure 2.
Withdrawal of Nicotine and Blunted Reward Responsiveness in Humans and Rats
Withdrawal of Nicotine and Blunted Reward Responsiveness in Humans and Rats

A, Human participants (N = 31) developed a response bias toward the more frequently rewarded (rich) stimulus when smoking at their usual rate. By contrast, 24-hour abstinence from chronic tobacco smoking significantly decreased response bias. B, Control rats administered saline developed a response bias toward the more frequently rewarded (rich) stimulus. By contrast, withdrawal from chronic nicotine administration significantly decreased response bias.
aP < .05.

Figure 3.
Nicotine Abstinence and Reward Responsiveness in Humans Without (n = 14) and With (n = 17) a History of Depression
Nicotine Abstinence and Reward Responsiveness in Humans Without (n = 14) and With (n = 17) a History of Depression

Twenty-four–hour abstinence from chronic tobacco smoking was associated with decreased response bias in block 3 for smokers with a history of depression relative to smokers without a history of depression. Moreover, unlike smokers without a history of depression (A), those with such history failed to develop a response bias toward the more frequently rewarded stimulus (B).
aP < .05.

Figure 4.
Acute Nicotine-Induced Changes in Reward Responsiveness in Rats Previously Exposed to Chronic Nicotine (n = 17) or Saline (n = 15)
Acute Nicotine-Induced Changes in Reward Responsiveness in Rats Previously Exposed to Chronic Nicotine (n = 17) or Saline (n = 15)

Acute nicotine reexposure in rats previously treated with chronic nicotine significantly potentiated response bias compared with acute saline exposure and compared with acute nicotine exposure in rats previously treated with chronic saline. Moreover, acute nicotine treatment did not affect reward responsiveness in previously nicotine-naive rats.
aDifferent from chronic nicotine-treated rats administered 0 and 0.125 mg/kg of acute nicotine (P < .05).
bDifferent from chronic saline-treated rats administered the same acute nicotine dose (P < .01).

1.
Centers for Disease Control and Prevention (CDC).  Cigarette smoking-attributable morbidity: United States, 2000. Morbidity and Mortality Weekly. 2003;52(35):842-844.
PubMed
2.
US Burden of Disease Collaborators.  The state of US health, 1990-2010: burden of diseases, injuries, and risk factors. JAMA. 2013;310(6):591-608.
PubMedArticle
3.
Ferguson  SG, Shiffman  S, Gwaltney  CJ.  Does reducing withdrawal severity mediate nicotine patch efficacy? a randomized clinical trial. J Consult Clin Psychol. 2006;74(6):1153-1161.
PubMedArticle
4.
Pergadia  ML, Agrawal  A, Heath  AC, Martin  NG, Bucholz  KK, Madden  PA.  Nicotine withdrawal symptoms in adolescent and adult twins. Twin Res Hum Genet. 2010;13(4):359-369.
PubMedArticle
5.
Cummings  KM, Jaén  CR, Giovino  G.  Circumstances surrounding relapse in a group of recent exsmokers. Prev Med. 1985;14(2):195-202.
PubMedArticle
6.
Hughes  JR.  Clinical significance of tobacco withdrawal. Nicotine Tob Res. 2006;8(2):153-156.
PubMedArticle
7.
Piasecki  TM, Fiore  MC, Baker  TB.  Profiles in discouragement: two studies of variability in the time course of smoking withdrawal symptoms. J Abnorm Psychol. 1998;107(2):238-251.
PubMedArticle
8.
Piasecki  TM, Jorenby  DE, Smith  SS, Fiore  MC, Baker  TB.  Smoking withdrawal dynamics, II: improved tests of withdrawal-relapse relations. J Abnorm Psychol. 2003;112(1):14-27.
PubMedArticle
9.
Donny  EC, Chaudhri  N, Caggiula  AR,  et al.  Operant responding for a visual reinforcer in rats is enhanced by noncontingent nicotine: implications for nicotine self-administration and reinforcement. Psychopharmacology (Berl). 2003;169(1):68-76.
PubMedArticle
10.
Caggiula  AR, Donny  EC, Palmatier  MI, Liu  X, Chaudhri  N, Sved  AF.  The role of nicotine in smoking: a dual-reinforcement model. Nebr Symp Motiv. 2009;55:91-109.
PubMed
11.
Asgaard  GL, Gilbert  DG, Malpass  D, Sugai  C, Dillon  A.  Nicotine primes attention to competing affective stimuli in the context of salient alternatives. Exp Clin Psychopharmacol. 2010;18(1):51-60.
PubMedArticle
12.
Gilbert  DG, Carlson  JM, Riise  H, Rabinovich  NE, Sugai  C, Froeliger  B.  Effects of nicotine and depressive traits on affective priming of lateralized emotional word identification. Exp Clin Psychopharmacol. 2008;16(4):293-300.
PubMedArticle
13.
Gilbert  DG, Rabinovich  NE, Malpass  D,  et al.  Effects of nicotine on affect are moderated by stressor proximity and frequency, positive alternatives, and smoker status. Nicotine Tob Res. 2008;10(7):1171-1183.
PubMedArticle
14.
al-Adawi  S, Powell  J.  The influence of smoking on reward responsiveness and cognitive functions: a natural experiment. Addiction. 1997;92(12):1773-1782.
PubMedArticle
15.
Dawkins  L, Powell  J.  Effects of nicotine and alcohol on affective responses to emotionally toned film clips. Psychopharmacology (Berl). 2011;216(2):197-205.
PubMedArticle
16.
Powell  J, Dawkins  L, Davis  RE.  Smoking, reward responsiveness, and response inhibition: tests of an incentive motivational model. Biol Psychiatry. 2002;51(2):151-163.
PubMedArticle
17.
Powell  JH, Pickering  AD, Dawkins  L, West  R, Powell  JF.  Cognitive and psychological correlates of smoking abstinence, and predictors of successful cessation. Addict Behav. 2004;29(7):1407-1426.
PubMedArticle
18.
Barr  RS, Pizzagalli  DA, Culhane  MA, Goff  DC, Evins  AE.  A single dose of nicotine enhances reward responsiveness in nonsmokers: implications for development of dependence. Biol Psychiatry. 2008;63(11):1061-1065.
PubMedArticle
19.
Epping-Jordan  MP, Watkins  SS, Koob  GF, Markou  A.  Dramatic decreases in brain reward function during nicotine withdrawal. Nature. 1998;393(6680):76-79.
PubMedArticle
20.
Watkins  SS, Stinus  L, Koob  GF, Markou  A.  Reward and somatic changes during precipitated nicotine withdrawal in rats: centrally and peripherally mediated effects. J Pharmacol Exp Ther. 2000;292(3):1053-1064.
PubMed
21.
Kenny  PJ, Gasparini  F, Markou  A.  Group II metabotropic and alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA)/kainate glutamate receptors regulate the deficit in brain reward function associated with nicotine withdrawal in rats. J Pharmacol Exp Ther. 2003;306(3):1068-1076.
PubMedArticle
22.
Der-Avakian  A, Markou  A.  Withdrawal from chronic exposure to amphetamine, but not nicotine, leads to an immediate and enduring deficit in motivated behavior without affecting social interaction in rats. Behav Pharmacol. 2010;21(4):359-368.
PubMedArticle
23.
LeSage  MG, Burroughs  D, Pentel  PR.  Effects of nicotine withdrawal on performance under a progressive-ratio schedule of sucrose pellet delivery in rats. Pharmacol Biochem Behav. 2006;83(4):585-591.
PubMedArticle
24.
Weaver  MT, Sweitzer  M, Coddington  S,  et al.  Precipitated withdrawal from nicotine reduces reinforcing effects of a visual stimulus for rats. Nicotine Tob Res. 2012;14(7):824-832.
PubMedArticle
25.
Dawkins  L, Powell  JH, Pickering  A, Powell  J, West  R.  Patterns of change in withdrawal symptoms, desire to smoke, reward motivation and response inhibition across 3 months of smoking abstinence. Addiction. 2009;104(5):850-858.
PubMedArticle
26.
Kalamboka  N, Remington  B, Glautier  S.  Nicotine withdrawal and reward responsivity in a card-sorting task. Psychopharmacology (Berl). 2009;204(1):155-163.
PubMedArticle
27.
Pizzagalli  DA, Jahn  AL, O’Shea  JP.  Toward an objective characterization of an anhedonic phenotype: a signal-detection approach. Biol Psychiatry. 2005;57(4):319-327.
PubMedArticle
28.
Pizzagalli  DA, Iosifescu  D, Hallett  LA, Ratner  KG, Fava  M.  Reduced hedonic capacity in major depressive disorder: evidence from a probabilistic reward task. J Psychiatr Res. 2008;43(1):76-87.
PubMedArticle
29.
Pizzagalli  DA, Bogdan  R, Ratner  KG, Jahn  AL.  Increased perceived stress is associated with blunted hedonic capacity: potential implications for depression research. Behav Res Ther. 2007;45(11):2742-2753.
PubMedArticle
30.
Der-Avakian  A, D'Souza  MS, Pizzagalli  DA, Markou  A.  Assessment of reward responsiveness in the response bias probabilistic reward task in rats: implications for cross-species translational research. Transl Psychiatry. 2013;3:e297.
PubMedArticle
31.
Vrieze  E, Pizzagalli  DA, Demyttenaere  K,  et al.  Reduced reward learning predicts outcome in major depressive disorder. Biol Psychiatry. 2013;73(7):639-645.
PubMedArticle
32.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders.ed 4. Washington, DC: American Psychiatric Association; 1994.
33.
Glassman  AH, Stetner  F, Walsh  BT,  et al.  Heavy smokers, smoking cessation, and clonidine: results of a double-blind, randomized trial. JAMA. 1988;259(19):2863-2866.
PubMedArticle
34.
Grant  BF, Hasin  DS, Chou  SP, Stinson  FS, Dawson  DA.  Nicotine dependence and psychiatric disorders in the United States: results from the national epidemiologic survey on alcohol and related conditions. Arch Gen Psychiatry. 2004;61(11):1107-1115.
PubMedArticle
35.
Covey  LS, Glassman  AH, Stetner  F.  Depression and depressive symptoms in smoking cessation. Compr Psychiatry. 1990;31(4):350-354.
PubMedArticle
36.
Madden  PA, Bucholz  KK, Dinwiddie  SH,  et al.  Nicotine withdrawal in women. Addiction. 1997;92(7):889-902.
PubMedArticle
37.
Xian  H, Scherrer  JF, Madden  PA,  et al.  Latent class typology of nicotine withdrawal: genetic contributions and association with failed smoking cessation and psychiatric disorders. Psychol Med. 2005;35(3):409-419.
PubMedArticle
38.
Japuntich  SJ, Smith  SS, Jorenby  DE, Piper  ME, Fiore  MC, Baker  TB.  Depression predicts smoking early but not late in a quit attempt. Nicotine Tob Res. 2007;9(6):677-686.
PubMedArticle
39.
Leventhal  AM, Waters  AJ, Kahler  CW, Ray  LA, Sussman  S.  Relations between anhedonia and smoking motivation. Nicotine Tob Res. 2009;11(9):1047-1054.
PubMedArticle
40.
Cook  J, Spring  B, McChargue  D, Doran  N.  Effects of anhedonia on days to relapse among smokers with a history of depression: a brief report. Nicotine Tob Res. 2010;12(9):978-982.
PubMedArticle
41.
Markou  A, Kosten  TR, Koob  GF.  Neurobiological similarities in depression and drug dependence: a self-medication hypothesis. Neuropsychopharmacology. 1998;18(3):135-174.
PubMedArticle
42.
Gilbert  DG. Smoking: Individual Differences, Psychopathology, and Emotion. Washington, DC: Taylor and Francis; 1995.
43.
Cook  JW, Spring  B, McChargue  D.  Influence of nicotine on positive affect in anhedonic smokers. Psychopharmacology (Berl). 2007;192(1):87-95.
PubMedArticle
44.
Spring  B, Cook  JW, Appelhans  B,  et al.  Nicotine effects on affective response in depression-prone smokers. Psychopharmacology (Berl). 2008;196(3):461-471.
PubMedArticle
45.
Leventhal  AM, Munafò  M, Tidey  JW,  et al.  Anhedonia predicts altered processing of happy faces in abstinent cigarette smokers. Psychopharmacology (Berl). 2012;222(2):343-351.
PubMedArticle
46.
Spring  B, Pingitore  R, McChargue  DE.  Reward value of cigarette smoking for comparably heavy smoking schizophrenic, depressed, and nonpatient smokers. Am J Psychiatry. 2003;160(2):316-322.
PubMedArticle
47.
Shiffman  S, Ferguson  SG, Gwaltney  CJ, Balabanis  MH, Shadel  WG.  Reduction of abstinence-induced withdrawal and craving using high-dose nicotine replacement therapy. Psychopharmacology (Berl). 2006;184(3-4):637-644.
PubMedArticle
48.
Westman  EC, Behm  FM, Simel  DL, Rose  JE.  Smoking behavior on the first day of a quit attempt predicts long-term abstinence. Arch Intern Med. 1997;157(3):335-340.
PubMedArticle
49.
Hughes  JR, Keely  J, Naud  S.  Shape of the relapse curve and long-term abstinence among untreated smokers. Addiction. 2004;99(1):29-38.
PubMedArticle
50.
Bucholz  KK, Cadoret  R, Cloninger  CR,  et al.  A new, semi-structured psychiatric interview for use in genetic linkage studies: a report on the reliability of the SSAGA. J Stud Alcohol. 1994;55(2):149-158.
PubMed
51.
Cottler  LB, Robins  LN, Grant  BF,  et al.  The CIDI-core substance abuse and dependence questions: cross-cultural and nosological issues: the WHO/ADAMHA Field Trial. Br J Psychiatry. 1991;159:653-658.
PubMedArticle
52.
McNair  DM, Lorr  M, Droppelman  LF. Manual for the Profile of Mood States. San Diego, CA: Education and Industrial Testing Service; 1971.
53.
Nyenhuis  DL, Yamamoto  C, Luchetta  T, Terrien  A, Parmentier  A.  Adult and geriatric normative data and validation of the profile of mood states. J Clin Psychol. 1999;55(1):79-86.
PubMedArticle
54.
Pizzagalli  DA, Goetz  E, Ostacher  M, Iosifescu  DV, Perlis  RH.  Euthymic patients with bipolar disorder show decreased reward learning in a probabilistic reward task. Biol Psychiatry. 2008;64(2):162-168.
PubMedArticle
55.
Parrott  AC.  Stress modulation over the day in cigarette smokers. Addiction. 1995;90(2):233-244.
PubMedArticle
56.
Ulrich  YM, Hargreaves  KM, Flores  CM.  A comparison of multiple injections versus continuous infusion of nicotine for producing up-regulation of neuronal [3H]-epibatidine binding sites. Neuropharmacology. 1997;36(8):1119-1125.
PubMedArticle
57.
Benwell  ME, Balfour  DJ, Anderson  JM.  Evidence that tobacco smoking increases the density of (-)-[3H]nicotine binding sites in human brain. J Neurochem. 1988;50(4):1243-1247.
PubMedArticle
58.
Small  E, Shah  HP, Davenport  JJ,  et al.  Tobacco smoke exposure induces nicotine dependence in rats. Psychopharmacology (Berl). 2010;208(1):143-158.
PubMedArticle
59.
Semenova  S, Markou  A.  Clozapine treatment attenuated somatic and affective signs of nicotine and amphetamine withdrawal in subsets of rats exhibiting hyposensitivity to the initial effects of clozapine. Biol Psychiatry. 2003;54(11):1249-1264.
PubMedArticle
60.
Markou  A, Chiamulera  C, Geyer  MA, Tricklebank  M, Steckler  T.  Removing obstacles in neuroscience drug discovery: the future path for animal models. Neuropsychopharmacology. 2009;34(1):74-89.
PubMedArticle
61.
Hyman  SE, Fenton  WS.  Medicine: what are the right targets for psychopharmacology? Science. 2003;299(5605):350-351.
PubMedArticle
Original Investigation
November 2014

Association Between Nicotine Withdrawal and Reward Responsiveness in Humans and Rats

Author Affiliations
  • 1Department of Psychiatry, Washington University School of Medicine, St Louis, Missouri
  • 2currently with Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton
  • 3Department of Psychiatry, University of California San Diego
  • 4Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania
  • 5Department of Psychiatry, Harvard Medical School, Belmont, Massachusetts
JAMA Psychiatry. 2014;71(11):1238-1245. doi:10.1001/jamapsychiatry.2014.1016
Abstract

Importance  Reward-related disturbances after withdrawal from nicotine are hypothesized to contribute to relapse to tobacco smoking but mechanisms underlying and linking such processes remain largely unknown.

Objective  To determine whether withdrawal from nicotine affects reward responsiveness (ie, the propensity to modulate behavior as a function of prior reinforcement experience) across species using translational behavioral assessments in humans and rats.

Design, Setting, Participants  Experimental studies used analogous reward responsiveness tasks in both humans and rats to examine whether reward responsiveness varied in (1) an ad libitum smoking condition compared with a 24-hour acute nicotine abstinence condition in 31 human smokers with (n = 17) or without (n = 14) a history of depression; (2) rats 24 hours after withdrawal from chronic nicotine (n = 19) or saline (n = 20); and (3) rats following acute nicotine exposure after withdrawal from either chronic nicotine or saline administration.

Main Outcomes and Measures  Performance on a reward responsiveness task under nicotine and nonnicotine conditions.

Results  In both human smokers and nicotine-treated rats, reward responsiveness was significantly reduced after 24-hour withdrawal from nicotine (P < .05). In humans, withdrawal-induced deficits in reward responsiveness were greater in those with a history of depression. In rats previously exposed to chronic nicotine, acute nicotine reexposure long after withdrawal potentiated reward responsiveness (P < .05).

Conclusions and Relevance  These findings across species converge in suggesting that organisms have diminished ability to modulate behavior as a function of reward during withdrawal of nicotine. This blunting may contribute to relapse to tobacco smoking, particularly in depression-vulnerable individuals, to reinstate responsiveness to natural rewards and to experience potentiated nicotine-induced reward responsiveness. Moreover, demonstration of behavioral homology across humans and rodents provides a strong translational framework for the investigation and development of clinical treatments targeting reward responsiveness deficits during early withdrawal of nicotine.

Introduction

Smoking is a leading cause of disease and mortality worldwide,1,2 and many smokers experience difficulty with quitting and with nicotine withdrawal.38 While exposure to nicotine is associated with increased responsiveness to rewards918 in rodents and humans, less is known about the role of different reward-related processes during nicotine withdrawal. Studies in rodents using the intracranial self-stimulation procedure1921 have consistently shown decrements in brain reward function during nicotine withdrawal but assessments of motivation and effort for natural rewards in rodents2224 and humans14,16,25,26 have produced less-consistent results likely owing to the heterogeneity of tests measuring motivation and reward responsiveness between humans and rodents. Thus, it remains unclear which reward-related processes are compromised after withdrawal from nicotine, hindering development of cessation treatments.

Here, we examined the effects of withdrawal of nicotine on reward responsiveness, defined as the propensity to modulate behavior as a function of prior reinforcement experience,2729 using a Response Bias Probabilistic Reward Task (RB-PRT) developed to objectively quantify reward responsiveness in humans27 and rats.30 During this task, both rats and humans must distinguish between 2 ambiguous stimuli, whereby correct identification of either stimulus is partially reinforced (Figure 1). Unbeknownst to them, throughout the test session, correct identification of 1 stimulus (rich) is rewarded 3 times more frequently than correct identification of the other stimulus (lean). Because of the differential reinforcement schedule, healthy rats and humans develop a response bias in favor of the more frequently rewarded (rich) stimulus. In a placebo-controlled study, acute nicotine administration in current nonsmokers was associated with potentiated reward responsiveness.18 However, the study included individuals with prior smoking history, which may differentially mediate reward responsiveness during acute nicotine reexposure relative to those without prior smoking experience. Notably, human participants with elevated depression-related symptoms27,28,31 show blunted reward responsiveness (ie, reduced response bias) in this task.

Given that nicotine withdrawal is characterized by depression-like symptoms,32 these previous findings for depression27,28,31 may suggest that withdrawal of nicotine is also associated with blunted reward responsiveness. Moreover, many smokers have a history of major depression33,34; such individuals are more likely to experience nicotine-withdrawal symptoms and continue smoking,4,33,3538 and trait anhedonia is associated with relapse to smoking.39,40 Such findings promoted the hypothesis that many smokers are self-medicating an underlying depressive vulnerability,41,42 which has received varying degrees of support. In smokers with trait anhedonia or history of depression, nicotine use is related to increased positive mood,43,44 while abstinence is associated with reduced attentional bias toward positive stimuli.45 Similarly, smokers with a history of depression ascribe greater value to cigarettes relative to natural rewards,46 which may hinder substitution of healthy rewards for cigarettes during cessation. However, to our knowledge, there has been limited consideration of depression history in regards to the effects of withdrawal of nicotine on reward processes. Moreover, the high rate of relapse to smoking during withdrawal from nicotine4749 may potentially arise from reward responsiveness deficits, with the resumption of nicotine use reversing such deficits.

In light of prior independent lines of evidence, we hypothesized that (1) withdrawal from chronic nicotine exposure would be associated with blunted reward responsiveness (ie, reduced response bias) in human smokers and rats; (2) withdrawal-related changes in reward responsiveness would be exacerbated in human smokers with a history of major depressive disorder; and (3) acute nicotine reexposure after nicotine withdrawal would enhance reward responsiveness in rats.

Methods
Humans
Participants

Heavy smokers (smoking ≥15 cigarettes per day and smoking for ≥5 years) not planning to quit permanently over the next month participated. Exclusion criteria included age younger than 18 years, current use of smoking-cessation aids, and current or planned pregnancy. Ninety-three percent of ineligible candidates (n = 314) did not meet cigarette use criteria or planned to quit cigarettes permanently over the next month. Eligible candidates were scheduled for a screening interview and study overview, read and signed an informed consent, and verified smoking status using an ecolyzer to measure expired carbon monoxide. All procedures were approved by the Human Research Protection Office at Washington University.

Of the 99 individuals enrolled, 60 completed baseline and 2 test sessions (described further on). The RB-PRT was added halfway through data collection for 37 completed participants (details provided in eAppendix 1 in the Supplement). This sample of 37 had the following characteristics: mean (SD) cigarettes smoked per day, 22.3 (6.0); mean (SD) years smoking, 23.3 (13.5); mean (SD) age, 41.1 (14.2) years; 54% women; 57% with a lifetime history of major depression; and 89% with a high school education or higher.

Procedures and Assessments
Baseline Visit

Candidates meeting preliminary inclusion criteria were administered self-report questionnaires and a diagnostic interview, a modified Semi-Structured Assessment for the Genetics of Alcoholism,50 with the smoking section modified from the Composite International Diagnostic Interview,51 which included lifetime assessments of nicotine withdrawal and major depression.32

Approximately 90-Minute Test Sessions

During sessions separated by a median of 7 days and counterbalanced across participants, participants completed self-report questionnaires and were tested under (1) ad libitum smoking and (2) 24-hour nicotine-abstinence conditions. Smoking and abstinence were verified by self-report and a noninvasive breath test ecolyzer measurement of exhaled carbon monoxide (eAppendix 1 in the Supplement). The RB-PRT was administered to quantify reward responsiveness. Response bias (the main variable of interest; see Figure 1 for calculation details), discriminability (control variable), accuracy (ie, correct responses/[correct + incorrect responses]) and reaction time for each stimulus type (ie, rich/lean) were calculated. Reaction time shorter than 150 milliseconds or longer than 2500 milliseconds were removed; participants with more than 10% of trials with outlying reaction times were removed entirely (n = 6), leaving 31 participants with valid data from both test sessions. The 6 individuals removed were similar in sample characteristics from the remaining 31 participants (all P > .05). Of these 31 smokers, 55% (n = 17) had a history of lifetime major depression. The sample was sufficiently remitted at baseline, reflected by the average Profile of Mood States Total Mood Disturbance Scale52 score of participants without (mean [SD], 9.9 [23.1]) and with (mean [SD], 17.8 [31.3]) a history of depression being lower and within range of the average score published for normative nonpsychiatric participants (range, 17-19),53 respectively.

Statistical Analyses

For response bias, mixed analysis of variance with nicotine status (smoking or 24-hour abstinence) and block (1, 2, or 3; 100 trials/block) as repeated measures and history of depression (present or absent) as the between-subjects factor were performed. Greenhouse-Geisser corrected estimates are reported.

Rats
Subjects

Forty-six adult male Wistar rats (Charles River Laboratories, Raleigh, North Carolina) were pair housed with food and water available ad libitum prior to behavioral training. All procedures were conducted in accordance with guidelines from the National Institutes of Health and the Association for the Assessment and Accreditation of Laboratory Animal Care and were approved by the University of California San Diego’s institutional animal care and use committee.

Apparatus

Training and testing were conducted in operant chambers (Med Associates; St. Albans, Vermont) consisting of 2 metal retractable levers, a food receptacle located between the levers, and a speaker located above the food receptacle. Tones were generated using a multipurpose sound generator. All programs and data collection were controlled by a computer running MED-PC IV software.30

Procedure

Rats were trained on the RB-PRT and tested under baseline conditions (see Figure 1 and the study by Der-Avakian et al30 for details). Rats were then surgically prepared with subcutaneous osmotic minipumps (Alzet Osmotic Pumps; Cupertino, California) delivering either a 6.32-mg/kg/d (base) (-)-nicotine hydrogen tartrate solution (Sigma, St Louis, Missouri) or vehicle (sterile 0.9% saline) for 28 days.

Rats continued to train during drug administration with the parameters described in Figure 1. Before minipump removal, rats received increasingly ambiguous tones as stimuli while being equally reinforced for all correct responses. Twenty-four hours after minipump removal, rats were tested with the same tone and reinforcement parameters as during the baseline test session.

After the withdrawal test, rats were exposed to the training parameters for 2 weeks and tested in response to acute nicotine administration. Two days prior to the initial acute nicotine test, all rats received 0.125 mg/kg of nicotine (base) subcutaneously after the training session to habituate to the subjective experience of acute nicotine exposure. Rats then received either 0, 0.125, 0.25, or 0.5 mg/kg of nicotine (base; 15-minute pretreatment) in a within-subjects Latin-square design, and reward responsiveness was assessed 2, 4, 6, and 8 weeks after the withdrawal test.

Statistical Analyses

Data were cumulated and analyzed across blocks 1 (trials 1-33), 2 (trials 34-67), and 3 (trials 68-100). Rats were excluded owing to insufficient accuracy during discrimination training (ie, <70%; n = 5) and complications with minipumps (1 nicotine and 1 saline). Thus, data from 39 rats were available for the withdrawal test. Rats with less than 30% accuracy for either stimulus during testing were excluded because insufficient responding prevents the differential (ie, 3:1) reward distribution, as in the human task. Five chronic saline-treated rats and 2 chronic nicotine-treated rats were excluded from the acute nicotine test. Response bias was calculated as described here for humans. For the withdrawal test, response bias was analyzed with a 2-way mixed analysis of covariance with chronic drug treatment (between subjects) and block (within subjects) as factors. For the acute nicotine tests, acute nicotine dose was included as a within-subjects factor. Inherent side biases unrelated to the differential reinforcement schedule during testing were controlled as a covariate, defined as the change in response bias from blocks 1 to 3 during the pretest training session.

For human and rat data analyses, significant main and interaction effects involving analysis of variance factors (eg, nicotine status, block, and depression in smokers and acute nicotine dose in rats) were clarified using post hoc t tests. The significance level was 0.05. Additional detail on samples and procedures for humans and rats are available in eAppendix 1 in the Supplement.

Results
Response Bias in Humans

Among adult heavy-smoking humans, a 3-way analysis of variance with nicotine status (ad libitum smoking or 24-hour abstinence), block (1, 2, or 3), and history of depression (present or absent) as factors revealed that 24-hour nicotine abstinence was associated with a significant reduction in response bias (nicotine status: F1,29 = 6.61, P = .02; partial eta squared [ηp2] = 0.19) (Figure 2A). No other effects emerged. Although the nicotine status by history of depression interaction reached only a statistical trend (P = .10; ηp2 = 0.09), a priori subsidiary analyses found that smokers without depression history exhibited significant increases in response bias (ie, reward learning) across blocks during abstinence (P = .03, ηp2 = 0.25; ad libitum: P = .94, ηp2 = 0.01). Smokers with a history of depression failed to show changes in response bias across blocks (abstinence: P = .46, ηp2 = 0.05; ad libitum: P = .45, ηp2 = 0.05). This group effect was detectable by block 3, whereby smokers with a history of depression had a smaller response bias during 24-hour abstinence than smokers without such history (t = 2.06, P = .048, ηp2 = 0.13; ad libitum: t = −1.30, P = .21, ηp2 = 0.06) (Figure 3).

Response Bias in Rats

A 2-way analysis of covariance with chronic drug treatment (nicotine or saline) and block (1, 2, or 3) as factors and inherent bias as a covariate revealed that withdrawal from chronic nicotine administration significantly reduced response bias relative to saline treatment (chronic drug treatment: F1,36 = 4.18; P = .048; ηp2 = 0.10) (Figure 2B). There was also a main effect of block (F2,72 = 6.05; P = .004; ηp2 = 0.14) due to significantly higher response bias in block 3 relative to block 1 (t38 = −2.49; P = .02) and block 2 (t38 = −3.64; P < .001), indicating that the differential reinforcement schedule was effective.

After withdrawal from chronic nicotine or saline administration, a 3-way analysis of covariance with chronic drug treatment, block, and acute nicotine dose (0, 0.125, 0.25, or 0.5 mg/kg of nicotine) as factors revealed that acute nicotine treatment differentially altered response bias depending on previous nicotine experience (chronic drug treatment by acute nicotine dose interaction: F3,87 = 4.44; P = .006; ηp2 = 0.13). Specifically, post hoc analyses revealed greater response biases in rats previously treated with chronic nicotine after 0.25 mg/kg (P = .08) and 0.5 mg/kg (P = .007) of acute nicotine treatment compared with previously saline-treated rats administered the same doses and compared with chronic nicotine-treated rats administered 0 and 0.125 mg/kg of nicotine (all P < .05) (Figure 4). There was also a main effect of block (F2,58 = 15.10; P < .01; ηp2 = 0.34) owing to significantly increased response bias from block 1 to block 2 to block 3 (all P < .05).

Secondary analyses of discriminability, accuracy, and reaction time for humans and rats are detailed in eAppendix 2 and the eFigure in the Supplement.

Discussion

Capitalizing on a task rooted in signal detection theory previously shown to be sensitive to detecting reward responsiveness deficits in depression and other mood disorders,2729,31,54 the current results provide converging evidence across human smokers and rats chronically administered nicotine that withdrawal from nicotine is associated with reduced reward responsiveness. This compromised ability to modulate behavior as a function of rewarding experiences after withdrawal from chronic nicotine exposure, an effect that was exacerbated in humans with a history of major depression, was reversed with acute nicotine reexposure in rats. The results suggest that restoring or potentiating responsiveness to natural rewards through nicotine reexposure may contribute to relapse to tobacco smoking. Furthermore, these findings may help rectify previous inconsistent findings across species,14,16,1926 which used heterogeneous measures to assess reward processing during withdrawal from nicotine, generated mixed results, and thus yielded limited translational opportunities. Our findings highlight the value of using a conceptually identical reward task across species to objectively measure withdrawal-related decrements in reward responsiveness and provide a strong translational framework for identifying novel treatment strategies for smoking cessation.

Increased depressive symptoms32 and subjective stress levels55 during withdrawal from chronic nicotine may accompany reward responsiveness deficits, and resuming nicotine use may act to reverse these deficits. Fitting this hypothesis, in the current study, acute nicotine exposure potentiated reward responsiveness in rats previously treated with chronic nicotine without affecting reward responsiveness in nicotine-naïve rats. These acute nicotine effects were observed 2 to 8 weeks after initiation of withdrawal from chronic nicotine. Moreover, human participants not currently smoking, but some with a history of smoking, showed similar acute nicotine-induced enhancement of reward responsiveness in a previous study.18 However, it is unclear whether individuals without a history of smoking, who were included in that overall analysis,18 displayed similar increases in reward responsiveness. By contrast, somatic signs of withdrawal in rats peaked within the first 24 hours of and dissipated 3 days after termination of chronic nicotine exposure.19 These results raise the possibility that enhanced reward responsiveness that is produced by acute nicotine reexposure long after initiation of abstinence, when other symptoms of withdrawal have dissipated, may contribute to relapse that occurs during protracted abstinence. Subsequent studies should consider the extent to which these results relate to putative therapeutic effects of smoking cessation treatment.

We also found suggestive evidence that nicotine abstinence resulted in an exacerbated decrease in reward responsiveness for smokers with a history of depression relative to smokers without such history. This finding extends prior reports that trait anhedonia is associated with reduced attentional bias toward positive stimuli during nicotine abstinence45 and increased risk for relapse to smoking.39,40 While there is debate regarding the impact of negative affect on relapse, deficits in reward responsiveness observed here appear to be unrelated to negative affect. Consistent with the literature,6 our human sample exhibited increased negative affect after 24 hours of withdrawal from nicotine, as measured by increases in the Profile of Mood States Total Mood Disturbance Scale52 score (F1,28 = 26.2; P < .001). However, changes in Total Mood Disturbance Scale score were not correlated with changes in reward responsiveness (r = −0.09), suggesting that reward responsiveness deficits observed during withdrawal of nicotine may be distinct from the nicotine withdrawal syndrome characterized by negative mood symptoms.6,32

Blunted reward responsiveness is likely not associated with decrements in discriminability (observed in rats) or cognitive processes, such as attention, as accuracy for the lean stimulus was similar during withdrawal and smoking/control conditions in humans and rats, respectively. Furthermore, only accuracy for the rich stimulus was disrupted during withdrawal in both species, suggesting that deficits in responding during the task were selective for the rich stimulus rather than globally for both stimuli, reflecting decreased reward responsiveness and unimpaired cognitive processing (eAppendix 2 in the Supplement). Although the average response bias during abstinence/withdrawal was lower than levels observed during smoking/saline treatment, response bias slightly increased across blocks. This pattern of results may suggest that reinforcement learning was occurring during withdrawal of nicotine but at a slower rate than smoking/saline conditions. Indeed, reinforcement learning (ie, changing behavior based on prior reinforcement) is a key component of reward responsiveness. Future work may further examine how blunted reward responsiveness interrelates with additional cognitive processes across species.

Because of the nature of human and rodent research, it remains challenging to implement completely homologous cross-species procedures. One strength of the RB-PRT used here is its complete objectivity that allows for assessment across species and comparable statistical analyses and data interpretation. The experimental manipulations, while analogous, have some noted dissimilarities. For example, humans intermittently smoke cigarettes throughout the day while ingesting numerous chemicals in addition to nicotine, whereas rats were administered only nicotine continuously via osmotic pumps. While not identical, continuous nicotine infusion is preferred over repeated, intermittent nicotine administration because it more effectively upregulates neuronal nicotinic receptors,56 as observed in human heavy smokers.57 Moreover, strictly controlling for administration of nicotine in the present rat study suggests that nicotine, and not necessarily other components of cigarette smoke, contribute to deficits in reward responsiveness observed in humans during withdrawal. Lastly, spontaneous withdrawal signs have not been observed after chronic exposure to tobacco smoke vapor in rats,58 whereas signs of withdrawal have been well characterized using the same continuous nicotine exposure procedure as presented here.59 Thus, the continuous nicotine infusion procedure used in rats is the most appropriate method for replicating the effects of spontaneous withdrawal of chronic nicotine in heavy-smoking humans. The extent to which our findings generalize to lighter smokers should be examined in future investigations.

Conclusions

Using an analogous reward responsiveness task in humans and rats, we found that reward responsiveness was significantly reduced after withdrawal from nicotine. Our strong phenotypic alignment is directed at circumventing the typical translational bottleneck, which continues to impede progress in psychiatric treatments.60,61 The fact that humans and rats showed similar deficits in reward responsiveness using conceptually and procedurally identical versions of the RB-PRT reflects the strong convergent validity of this objective measure. Importantly, our cross-species behavioral paradigm developed and validated in this study may facilitate the identification of novel neurobiological substrates mediating nicotine withdrawal and the testing of new smoking-cessation treatments.

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Article Information

Corresponding Author: Michele L. Pergadia, PhD, Florida Atlantic University, Charles E. Schmidt College of Medicine, 777 Glades Rd, Bldg 71, Room 313A, Boca Raton, FL 33431 (mpergadia@health.fau.edu).

Submitted for Publication: November 26, 2013; final revision received February 26, 2014; accepted April 21, 2014.

Published Online: September 10, 2014. doi:10.1001/jamapsychiatry.2014.1016.

Author Contributions: Drs Pergadia and Der-Avakian had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. In the work reported, Drs Pergadia and Der-Avakian contributed equally as first authors and Drs Markou and Pizzagalli as senior authors.

Study concept and design: Pergadia, Der-Avakian, Madden, Shiffman, Markou, Pizzagalli.

Acquisition, analysis, or interpretation of data: Pergadia, Der-Avakian, D’Souza, Heath, Shiffman, Markou, Pizzagalli.

Drafting of the manuscript: Pergadia, Der-Avakian, D’Souza, Markou, Pizzagalli.

Critical revision of the manuscript for important intellectual content: Pergadia, Der-Avakian, Madden, Heath, Shiffman, Markou, Pizzagalli.

Statistical analysis: Pergadia, Der-Avakian, Markou, Pizzagalli.

Obtained funding: Pergadia, Markou, Pizzagalli.

Administrative, technical, or material support: Pergadia, Markou, Pizzagalli.

Study supervision: Pergadia, Der-Avakian, D’Souza, Heath, Markou, Pizzagalli.

Conflict of Interest Disclosures: During the last 3 years, Dr Shiffman has received consulting fees from GlaxoSmithKline and has been a partner in a venture to develop nicotine medications. During the last 3 years, Dr Markou has received consulting fees from AbbVie and contract research support from Bristol-Myers Squibb, Forest Laboratories, and AstraZeneca for studies unrelated to this work. Dr Markou has a patent on the use of metabotropic glutamate receptor compounds for the treatment of drug dependence. Over the last 3 years, Dr Pizzagalli has received consulting fees from Advanced Neuro Technology, AstraZeneca, Ono Pharma USA, Pfizer, Servier, and Shire Pharmaceuticals for studies unrelated to this work. No other disclosures were reported.

Funding/Support: The study was supported by National Institutes of Health grants DA019951 (Dr Pergadia), MH078979 (Drs Markou and Pizzagalli), DA011946 (Dr Markou), DA012854 (Dr Madden), and AA017688 (Dr Heath).

Role of the Funder/Sponsor: The National Institutes of Health had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

References
1.
Centers for Disease Control and Prevention (CDC).  Cigarette smoking-attributable morbidity: United States, 2000. Morbidity and Mortality Weekly. 2003;52(35):842-844.
PubMed
2.
US Burden of Disease Collaborators.  The state of US health, 1990-2010: burden of diseases, injuries, and risk factors. JAMA. 2013;310(6):591-608.
PubMedArticle
3.
Ferguson  SG, Shiffman  S, Gwaltney  CJ.  Does reducing withdrawal severity mediate nicotine patch efficacy? a randomized clinical trial. J Consult Clin Psychol. 2006;74(6):1153-1161.
PubMedArticle
4.
Pergadia  ML, Agrawal  A, Heath  AC, Martin  NG, Bucholz  KK, Madden  PA.  Nicotine withdrawal symptoms in adolescent and adult twins. Twin Res Hum Genet. 2010;13(4):359-369.
PubMedArticle
5.
Cummings  KM, Jaén  CR, Giovino  G.  Circumstances surrounding relapse in a group of recent exsmokers. Prev Med. 1985;14(2):195-202.
PubMedArticle
6.
Hughes  JR.  Clinical significance of tobacco withdrawal. Nicotine Tob Res. 2006;8(2):153-156.
PubMedArticle
7.
Piasecki  TM, Fiore  MC, Baker  TB.  Profiles in discouragement: two studies of variability in the time course of smoking withdrawal symptoms. J Abnorm Psychol. 1998;107(2):238-251.
PubMedArticle
8.
Piasecki  TM, Jorenby  DE, Smith  SS, Fiore  MC, Baker  TB.  Smoking withdrawal dynamics, II: improved tests of withdrawal-relapse relations. J Abnorm Psychol. 2003;112(1):14-27.
PubMedArticle
9.
Donny  EC, Chaudhri  N, Caggiula  AR,  et al.  Operant responding for a visual reinforcer in rats is enhanced by noncontingent nicotine: implications for nicotine self-administration and reinforcement. Psychopharmacology (Berl). 2003;169(1):68-76.
PubMedArticle
10.
Caggiula  AR, Donny  EC, Palmatier  MI, Liu  X, Chaudhri  N, Sved  AF.  The role of nicotine in smoking: a dual-reinforcement model. Nebr Symp Motiv. 2009;55:91-109.
PubMed
11.
Asgaard  GL, Gilbert  DG, Malpass  D, Sugai  C, Dillon  A.  Nicotine primes attention to competing affective stimuli in the context of salient alternatives. Exp Clin Psychopharmacol. 2010;18(1):51-60.
PubMedArticle
12.
Gilbert  DG, Carlson  JM, Riise  H, Rabinovich  NE, Sugai  C, Froeliger  B.  Effects of nicotine and depressive traits on affective priming of lateralized emotional word identification. Exp Clin Psychopharmacol. 2008;16(4):293-300.
PubMedArticle
13.
Gilbert  DG, Rabinovich  NE, Malpass  D,  et al.  Effects of nicotine on affect are moderated by stressor proximity and frequency, positive alternatives, and smoker status. Nicotine Tob Res. 2008;10(7):1171-1183.
PubMedArticle
14.
al-Adawi  S, Powell  J.  The influence of smoking on reward responsiveness and cognitive functions: a natural experiment. Addiction. 1997;92(12):1773-1782.
PubMedArticle
15.
Dawkins  L, Powell  J.  Effects of nicotine and alcohol on affective responses to emotionally toned film clips. Psychopharmacology (Berl). 2011;216(2):197-205.
PubMedArticle
16.
Powell  J, Dawkins  L, Davis  RE.  Smoking, reward responsiveness, and response inhibition: tests of an incentive motivational model. Biol Psychiatry. 2002;51(2):151-163.
PubMedArticle
17.
Powell  JH, Pickering  AD, Dawkins  L, West  R, Powell  JF.  Cognitive and psychological correlates of smoking abstinence, and predictors of successful cessation. Addict Behav. 2004;29(7):1407-1426.
PubMedArticle
18.
Barr  RS, Pizzagalli  DA, Culhane  MA, Goff  DC, Evins  AE.  A single dose of nicotine enhances reward responsiveness in nonsmokers: implications for development of dependence. Biol Psychiatry. 2008;63(11):1061-1065.
PubMedArticle
19.
Epping-Jordan  MP, Watkins  SS, Koob  GF, Markou  A.  Dramatic decreases in brain reward function during nicotine withdrawal. Nature. 1998;393(6680):76-79.
PubMedArticle
20.
Watkins  SS, Stinus  L, Koob  GF, Markou  A.  Reward and somatic changes during precipitated nicotine withdrawal in rats: centrally and peripherally mediated effects. J Pharmacol Exp Ther. 2000;292(3):1053-1064.
PubMed
21.
Kenny  PJ, Gasparini  F, Markou  A.  Group II metabotropic and alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA)/kainate glutamate receptors regulate the deficit in brain reward function associated with nicotine withdrawal in rats. J Pharmacol Exp Ther. 2003;306(3):1068-1076.
PubMedArticle
22.
Der-Avakian  A, Markou  A.  Withdrawal from chronic exposure to amphetamine, but not nicotine, leads to an immediate and enduring deficit in motivated behavior without affecting social interaction in rats. Behav Pharmacol. 2010;21(4):359-368.
PubMedArticle
23.
LeSage  MG, Burroughs  D, Pentel  PR.  Effects of nicotine withdrawal on performance under a progressive-ratio schedule of sucrose pellet delivery in rats. Pharmacol Biochem Behav. 2006;83(4):585-591.
PubMedArticle
24.
Weaver  MT, Sweitzer  M, Coddington  S,  et al.  Precipitated withdrawal from nicotine reduces reinforcing effects of a visual stimulus for rats. Nicotine Tob Res. 2012;14(7):824-832.
PubMedArticle
25.
Dawkins  L, Powell  JH, Pickering  A, Powell  J, West  R.  Patterns of change in withdrawal symptoms, desire to smoke, reward motivation and response inhibition across 3 months of smoking abstinence. Addiction. 2009;104(5):850-858.
PubMedArticle
26.
Kalamboka  N, Remington  B, Glautier  S.  Nicotine withdrawal and reward responsivity in a card-sorting task. Psychopharmacology (Berl). 2009;204(1):155-163.
PubMedArticle
27.
Pizzagalli  DA, Jahn  AL, O’Shea  JP.  Toward an objective characterization of an anhedonic phenotype: a signal-detection approach. Biol Psychiatry. 2005;57(4):319-327.
PubMedArticle
28.
Pizzagalli  DA, Iosifescu  D, Hallett  LA, Ratner  KG, Fava  M.  Reduced hedonic capacity in major depressive disorder: evidence from a probabilistic reward task. J Psychiatr Res. 2008;43(1):76-87.
PubMedArticle
29.
Pizzagalli  DA, Bogdan  R, Ratner  KG, Jahn  AL.  Increased perceived stress is associated with blunted hedonic capacity: potential implications for depression research. Behav Res Ther. 2007;45(11):2742-2753.
PubMedArticle
30.
Der-Avakian  A, D'Souza  MS, Pizzagalli  DA, Markou  A.  Assessment of reward responsiveness in the response bias probabilistic reward task in rats: implications for cross-species translational research. Transl Psychiatry. 2013;3:e297.
PubMedArticle
31.
Vrieze  E, Pizzagalli  DA, Demyttenaere  K,  et al.  Reduced reward learning predicts outcome in major depressive disorder. Biol Psychiatry. 2013;73(7):639-645.
PubMedArticle
32.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders.ed 4. Washington, DC: American Psychiatric Association; 1994.
33.
Glassman  AH, Stetner  F, Walsh  BT,  et al.  Heavy smokers, smoking cessation, and clonidine: results of a double-blind, randomized trial. JAMA. 1988;259(19):2863-2866.
PubMedArticle
34.
Grant  BF, Hasin  DS, Chou  SP, Stinson  FS, Dawson  DA.  Nicotine dependence and psychiatric disorders in the United States: results from the national epidemiologic survey on alcohol and related conditions. Arch Gen Psychiatry. 2004;61(11):1107-1115.
PubMedArticle
35.
Covey  LS, Glassman  AH, Stetner  F.  Depression and depressive symptoms in smoking cessation. Compr Psychiatry. 1990;31(4):350-354.
PubMedArticle
36.
Madden  PA, Bucholz  KK, Dinwiddie  SH,  et al.  Nicotine withdrawal in women. Addiction. 1997;92(7):889-902.
PubMedArticle
37.
Xian  H, Scherrer  JF, Madden  PA,  et al.  Latent class typology of nicotine withdrawal: genetic contributions and association with failed smoking cessation and psychiatric disorders. Psychol Med. 2005;35(3):409-419.
PubMedArticle
38.
Japuntich  SJ, Smith  SS, Jorenby  DE, Piper  ME, Fiore  MC, Baker  TB.  Depression predicts smoking early but not late in a quit attempt. Nicotine Tob Res. 2007;9(6):677-686.
PubMedArticle
39.
Leventhal  AM, Waters  AJ, Kahler  CW, Ray  LA, Sussman  S.  Relations between anhedonia and smoking motivation. Nicotine Tob Res. 2009;11(9):1047-1054.
PubMedArticle
40.
Cook  J, Spring  B, McChargue  D, Doran  N.  Effects of anhedonia on days to relapse among smokers with a history of depression: a brief report. Nicotine Tob Res. 2010;12(9):978-982.
PubMedArticle
41.
Markou  A, Kosten  TR, Koob  GF.  Neurobiological similarities in depression and drug dependence: a self-medication hypothesis. Neuropsychopharmacology. 1998;18(3):135-174.
PubMedArticle
42.
Gilbert  DG. Smoking: Individual Differences, Psychopathology, and Emotion. Washington, DC: Taylor and Francis; 1995.
43.
Cook  JW, Spring  B, McChargue  D.  Influence of nicotine on positive affect in anhedonic smokers. Psychopharmacology (Berl). 2007;192(1):87-95.
PubMedArticle
44.
Spring  B, Cook  JW, Appelhans  B,  et al.  Nicotine effects on affective response in depression-prone smokers. Psychopharmacology (Berl). 2008;196(3):461-471.
PubMedArticle
45.
Leventhal  AM, Munafò  M, Tidey  JW,  et al.  Anhedonia predicts altered processing of happy faces in abstinent cigarette smokers. Psychopharmacology (Berl). 2012;222(2):343-351.
PubMedArticle
46.
Spring  B, Pingitore  R, McChargue  DE.  Reward value of cigarette smoking for comparably heavy smoking schizophrenic, depressed, and nonpatient smokers. Am J Psychiatry. 2003;160(2):316-322.
PubMedArticle
47.
Shiffman  S, Ferguson  SG, Gwaltney  CJ, Balabanis  MH, Shadel  WG.  Reduction of abstinence-induced withdrawal and craving using high-dose nicotine replacement therapy. Psychopharmacology (Berl). 2006;184(3-4):637-644.
PubMedArticle
48.
Westman  EC, Behm  FM, Simel  DL, Rose  JE.  Smoking behavior on the first day of a quit attempt predicts long-term abstinence. Arch Intern Med. 1997;157(3):335-340.
PubMedArticle
49.
Hughes  JR, Keely  J, Naud  S.  Shape of the relapse curve and long-term abstinence among untreated smokers. Addiction. 2004;99(1):29-38.
PubMedArticle
50.
Bucholz  KK, Cadoret  R, Cloninger  CR,  et al.  A new, semi-structured psychiatric interview for use in genetic linkage studies: a report on the reliability of the SSAGA. J Stud Alcohol. 1994;55(2):149-158.
PubMed
51.
Cottler  LB, Robins  LN, Grant  BF,  et al.  The CIDI-core substance abuse and dependence questions: cross-cultural and nosological issues: the WHO/ADAMHA Field Trial. Br J Psychiatry. 1991;159:653-658.
PubMedArticle
52.
McNair  DM, Lorr  M, Droppelman  LF. Manual for the Profile of Mood States. San Diego, CA: Education and Industrial Testing Service; 1971.
53.
Nyenhuis  DL, Yamamoto  C, Luchetta  T, Terrien  A, Parmentier  A.  Adult and geriatric normative data and validation of the profile of mood states. J Clin Psychol. 1999;55(1):79-86.
PubMedArticle
54.
Pizzagalli  DA, Goetz  E, Ostacher  M, Iosifescu  DV, Perlis  RH.  Euthymic patients with bipolar disorder show decreased reward learning in a probabilistic reward task. Biol Psychiatry. 2008;64(2):162-168.
PubMedArticle
55.
Parrott  AC.  Stress modulation over the day in cigarette smokers. Addiction. 1995;90(2):233-244.
PubMedArticle
56.
Ulrich  YM, Hargreaves  KM, Flores  CM.  A comparison of multiple injections versus continuous infusion of nicotine for producing up-regulation of neuronal [3H]-epibatidine binding sites. Neuropharmacology. 1997;36(8):1119-1125.
PubMedArticle
57.
Benwell  ME, Balfour  DJ, Anderson  JM.  Evidence that tobacco smoking increases the density of (-)-[3H]nicotine binding sites in human brain. J Neurochem. 1988;50(4):1243-1247.
PubMedArticle
58.
Small  E, Shah  HP, Davenport  JJ,  et al.  Tobacco smoke exposure induces nicotine dependence in rats. Psychopharmacology (Berl). 2010;208(1):143-158.
PubMedArticle
59.
Semenova  S, Markou  A.  Clozapine treatment attenuated somatic and affective signs of nicotine and amphetamine withdrawal in subsets of rats exhibiting hyposensitivity to the initial effects of clozapine. Biol Psychiatry. 2003;54(11):1249-1264.
PubMedArticle
60.
Markou  A, Chiamulera  C, Geyer  MA, Tricklebank  M, Steckler  T.  Removing obstacles in neuroscience drug discovery: the future path for animal models. Neuropsychopharmacology. 2009;34(1):74-89.
PubMedArticle
61.
Hyman  SE, Fenton  WS.  Medicine: what are the right targets for psychopharmacology? Science. 2003;299(5605):350-351.
PubMedArticle
×