Accounting for Dynamic Fluctuations across Time when Examining fMRI Test-Retest Reliability: Analysis of a Reward Paradigm in the EMBARC Study

Henry W Chase, Jay C Fournier, Tsafrir Greenberg, Jorge R Almeida, Richelle Stiffler, Carlos R Zevallos, Haris Aslam, Crystal Cooper, Thilo Deckersbach, Sarah Weyandt, Phillip Adams, Marisa Toups, Tom Carmody, Maria A Oquendo, Scott Peltier, Maurizio Fava, Patrick J McGrath, Myrna Weissman, Ramin Parsey, Melvin G McInnis, Benji Kurian, Madhukar H Trivedi, Mary L Phillips, Henry W Chase, Jay C Fournier, Tsafrir Greenberg, Jorge R Almeida, Richelle Stiffler, Carlos R Zevallos, Haris Aslam, Crystal Cooper, Thilo Deckersbach, Sarah Weyandt, Phillip Adams, Marisa Toups, Tom Carmody, Maria A Oquendo, Scott Peltier, Maurizio Fava, Patrick J McGrath, Myrna Weissman, Ramin Parsey, Melvin G McInnis, Benji Kurian, Madhukar H Trivedi, Mary L Phillips

Abstract

Longitudinal investigation of the neural correlates of reward processing in depression may represent an important step in defining effective biomarkers for antidepressant treatment outcome prediction, but the reliability of reward-related activation is not well understood. Thirty-seven healthy control participants were scanned using fMRI while performing a reward-related guessing task on two occasions, approximately one week apart. Two main contrasts were examined: right ventral striatum (VS) activation fMRI BOLD signal related to signed prediction errors (PE) and reward expectancy (RE). We also examined bilateral visual cortex activation coupled to outcome anticipation. Significant VS PE-related activity was observed at the first testing session, but at the second testing session, VS PE-related activation was significantly reduced. Conversely, significant VS RE-related activity was observed at time 2 but not time 1. Increases in VS RE-related activity from time 1 to time 2 were significantly associated with decreases in VS PE-related activity from time 1 to time 2 across participants. Intraclass correlations (ICCs) in VS were very low. By contrast, visual cortex activation had much larger ICCs, particularly in individuals with high quality data. Dynamic changes in brain activation are widely predicted, and failure to account for these changes could lead to inaccurate evaluations of the reliability of functional MRI signals. Conventional measures of reliability cannot distinguish between changes specified by algorithmic models of neural function and noisy signal. Here, we provide evidence for the former possibility: reward-related VS activations follow the pattern predicted by temporal difference models of reward learning but have low ICCs.

Conflict of interest statement

Competing Interests: Valeant Pharmaceuticals donated the Wellbutrin XL used in the study. Dr. Mary L. Phillips received funding from the National Institute of Mental Health (NIMH), including U01MH092221-01. Dr. Jorge Renner Cardoso de Almeida received funding from U01MH092221-01 (EMBARC). Dr. Jay Fournier’s research is supported by funding from NIMH. Drs. Mary L. Phillips and Henry W. Chase report no competing financial interests. Dr. Crystal Cooper reports no competing financial interests. Dr. Ramin Parsey reports no relevant or material financial interests that relate to the research described in this paper. Dr. Benji Kurian has received research grant support from the following organizations: Targacept, Inc., Pfizer, Inc., Johnson & Johnson, Evotec, Rexahn, Naurex, Forest Pharmaceuticals and the National Institute of Mental Health (NIMH). Dr. Marisa Toups and Dr. Madhukar Trivedi are or have been advisor/consultant to: Abbott Laboratories, Inc., Abdi Ibrahim, Akzo (Organon Pharmaceuticals Inc.), Alkermes, AstraZeneca, Axon Advisors, Bristol-Myers Squibb Company, Cephalon, Inc., Cerecor, Concert Pharmaceuticals, Inc., Eli Lilly & Company, Evotec, Fabre Kramer Pharmaceuticals, Inc., Forest Pharmaceuticals, GlaxoSmithKline, Janssen Global Services, LLC, Janssen Pharmaceutica Products, LP, Johnson & Johnson PRD, Libby, Lundbeck, Meade Johnson, MedAvante, Medtronic, Merck, Mitsubishi Tanabe Pharma Development America, Inc., Naurex, Neuronetics, Otsuka Pharmaceuticals, Pamlab, Parke-Davis Pharmaceuticals, Inc., Pfizer Inc., PgxHealth, Phoenix Marketing Solutions, Rexahn Pharmaceuticals, Ridge Diagnostics, Roche Products Ltd., Sepracor, SHIRE Development, Sierra, SK Life and Science, Sunovion, Takeda, Tal Medical/Puretech Venture, Targacept, Transcept, VantagePoint, Vivus, and Wyeth-Ayerst Laboratories. In addition, he has received research support from: Agency for Healthcare Research and Quality (AHRQ), Corcept Therapeutics, Inc., Cyberonics, Inc., National Alliance for Research in Schizophrenia and Depression, National Institute of Mental Health, National Institute on Drug Abuse, Novartis, Pharmacia & Upjohn, Predix Pharmaceuticals (Epix), and Solvay Pharmaceuticals, Inc. Dr. Thilo Deckersbach’s research has been funded by NIMH, NARSAD, TSA, IOCDF, Tufts University and DBDAT, he has received honoraria, consultation fees and/or royalties from the MGH Psychiatry Academy, BrainCells Inc., Clintara, LLC, Inc., Systems Research and Applications Corporation, Boston University, the Catalan Agency for Health Technology Assessment and Research, the National Association of Social Workers Massachusetts, the Massachusetts Medical Society, Tufts University, NIDA, NIMH, and Oxford University Press. He has also participated in research funded by NIH, NIA, AHRQ, Janssen Pharmaceuticals, The Forest Research Institute, Shire Development Inc., Medtronic, Cyberonics, Northstar, and Takeda. Dr. Fava has received research support from Abbot Laboratories; Alkermes, Inc.; American Cyanamid; Aspect Medical Systems; AstraZeneca; BioResearch; BrainCells Inc.; Bristol-Myers Squibb; CeNeRx BioPharma; Cephalon; Clintara, LLC; Covance; Covidien; Eli Lilly and Company;EnVivo Pharmaceuticals, Inc.; Euthymics Bioscience, Inc.; Forest Pharmaceuticals, Inc.; Ganeden Biotech, Inc.; GlaxoSmithKline; Harvard Clinical Research Institute; Hoffman-LaRoche; Icon Clinical Research; i3 Innovus/Ingenix; Janssen R&D, LLC; Jed Foundation; Johnson & Johnson Pharmaceutical Research & Development; Lichtwer Pharma GmbH; Lorex Pharmaceuticals; MedAvante; National Alliance for Research on Schizophrenia & Depression (NARSAD); National Center for Complementary and Alternative Medicine (NCCAM); National Institute of Drug Abuse (NIDA); National Institute of Mental Health (NIMH); Neuralstem, Inc.; Novartis AG; Organon Pharmaceuticals; PamLab, LLC.; Pfizer Inc.; Pharmacia-Upjohn; Pharmaceutical Research Associates, Inc.; Pharmavite® LLC;PharmoRx Therapeutics; Photothera; Roche Pharmaceuticals; RCT Logic, LLC (formerly Clinical Trials Solutions, LLC); Sanofi-Aventis US LLC; Shire; Solvay Pharmaceuticals, Inc.; Synthelabo; Wyeth-Ayerst Laboratories; he has served as advisor or consultant to Abbott Laboratories; Affectis Pharmaceuticals AG; Alkermes, Inc.; Amarin Pharma Inc.; Aspect Medical Systems; AstraZeneca; Auspex Pharmaceuticals; Bayer AG; Best Practice Project Management, Inc.; BioMarin Pharmaceuticals, Inc.; Biovail Corporation; BrainCells Inc; Bristol-Myers Squibb; CeNeRx BioPharma; Cephalon, Inc.; Cerecor;Clinical Trials Solutions; CNS Response, Inc.; Compellis Pharmaceuticals; Cypress Pharmaceutical, Inc.; DiagnoSearch Life Sciences (P) Ltd.; Dinippon Sumitomo Pharma Co. Inc.; Dov Pharmaceuticals, Inc.; Edgemont Pharmaceuticals, Inc.; Eisai Inc.; Eli Lilly and Company; EnVivo Pharmaceuticals, Inc.; ePharmaSolutions; EPIX Pharmaceuticals, Inc.; Euthymics Bioscience, Inc.; Fabre-Kramer Pharmaceuticals, Inc.; Forest Pharmaceuticals, Inc.; GenOmind, LLC; GlaxoSmithKline; Grunenthal GmbH; i3 Innovus/Ingenis; Janssen Pharmaceutica; Jazz Pharmaceuticals, Inc.; Johnson & Johnson Pharmaceutical Research & Development, LLC; Knoll Pharmaceuticals Corp.; Labopharm Inc.; Lorex Pharmaceuticals; Lundbeck Inc.; MedAvante, Inc.; Merck & Co., Inc.; MSI Methylation Sciences, Inc.; Naurex, Inc.; Neuralstem, Inc.; Neuronetics, Inc.; NextWave Pharmaceuticals; Novartis AG;Nutrition 21; Orexigen Therapeutics, Inc.; Organon Pharmaceuticals; Otsuka Pharmaceuticals; Pamlab, LLC.; Pfizer Inc.; PharmaStar; Pharmavite® LLC.; PharmoRx Therapeutics; Precision Human Biolaboratory; Prexa Pharmaceuticals, Inc.; Puretech Ventures; PsychoGenics; Psylin Neurosciences, Inc.; Rexahn Pharmaceuticals, Inc.; Ridge Diagnostics, Inc.; Roche; Sanofi-Aventis US LLC.; Sepracor Inc.; Servier Laboratories; Schering-Plough Corporation; Solvay Pharmaceuticals, Inc.; Somaxon Pharmaceuticals, Inc.; Somerset Pharmaceuticals, Inc.; Sunovion Pharmaceuticals; Supernus Pharmaceuticals, Inc.; Synthelabo; Takeda Pharmaceutical Company Limited; Tal Medical, Inc.; Tetragenex Pharmaceuticals, Inc.; TransForm Pharmaceuticals, Inc.; Transcept Pharmaceuticals, Inc.; Vanda Pharmaceuticals, Inc.; he has received speaking or publishing fees from Adamed, Co; Advanced Meeting Partners; American Psychiatric Association; American Society of Clinical Psychopharmacology; AstraZeneca; Belvoir Media Group; Boehringer Ingelheim GmbH; Bristol-Myers Squibb; Cephalon, Inc.; CME Institute/Physicians Postgraduate Press, Inc.; Eli Lilly and Company; Forest Pharmaceuticals, Inc.; GlaxoSmithKline; Imedex, LLC; MGH Psychiatry Academy/Primedia; MGH Psychiatry Academy/Reed Elsevier; Novartis AG; Organon Pharmaceuticals; Pfizer Inc.; PharmaStar; United BioSource,Corp.; Wyeth-Ayerst Laboratories; he has equity holdings in Compellis and PsyBrain, Inc.; Dr Fava has patents for Sequential Parallel Comparison Design (SPCD) (7,647,235; 7,840,419; 7,983,936; 8,145,504; 8,219,149), which are licensed by MGH to Pharmaceutical Product Development, LLC; and a patent application for a combination of Scopolamine and Ketamine in Major Depressive Disorder (MDD) (PCT/US13/34524). He receives copyright royalties for the MGH Cognitive & Physical Functioning Questionnaire (CPFQ), Sexual Functioning Inventory (SFI), Antidepressant Treatment Response Questionnaire (ATRQ), Discontinuation-Emergent Signs & Symptoms (DESS), and SAFER; Lippincott, Williams & Wilkins; Wolkers Kluwer; World Scientific Publishing Co. Pte.Ltd. In the past two years, Dr. Myrna Weissman received funding from the National Institute of Mental Health (NIMH), the National Institute on Drug Abuse (NIDA), the National Alliance for Research on Schizophrenia and Depression (NARSAD), the Sackler Foundation, the Templeton Foundation and the Interstitial Cystitis Association; and receives royalties from the Oxford University Press, Perseus Press, the American Psychiatric Association Press, and MultiHealth Systems. Dr. Pat McGrath has received research grant support from the Forest Research Laboratories. Dr. Oquendo receives royalties for use of the Columbia Suicide Severity Rating Scale and received financial compensation from Pfizer for the safety evaluation of a clinical facility, unrelated to this study. She has received unrestricted educational grants and/or lecture fees from Astra-Zeneca, Bristol Myers Squibb, Eli Lilly, Janssen, Otsuko, Pfizer, Sanofi-Aventis, and Shire. Her family owns stock in Bristol Myers Squibb. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1. Figure shows the structure of…
Fig 1. Figure shows the structure of the guessing task, including phases for response, anticipation and outcome (only reward-related feedback shown).
Fig 2. Significant VS PE-related activity was…
Fig 2. Significant VS PE-related activity was observed at time 1 (A) but not time 2 (B).
Significant VS RE-related activation was observed at time 2 (C) but not time 1 (D). Figures thresholded at p200.
Fig 3. Left: Change in right VS…
Fig 3. Left: Change in right VS RE activation from time 1 to time 2 is negatively correlated with the change in right VS PE activation from time 1 to time 2.
Right: Right VS RE activation at time 1 is negatively correlated with right VS PE activation at time 1.

References

    1. Aron AR, Gluck MA, Poldrack RA. Long-term test-retest reliability of functional MRI in a classification learning task. Neuroimage. 2006;29: 1000–1006.
    1. Lipp I, Murphy K, Wise RG, Caseras X. Understanding the contribution of neural and physiological signal variation to the low repeatability of emotion-induced BOLD responses. Neuroimage. 2014;86: 335–342 10.1016/j.neuroimage.2013.10.015
    1. Bennett CM, Miller MB. How reliable are the results from functional magnetic resonance imaging? Ann N Y Acad Sci. 2010;1191: 133–155. 10.1111/j.1749-6632.2010.05446.x
    1. Vul E, Harris C, Winkielman P, Pashler H. Puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition. Perspect Psychol Sci. 2009;4: 274–290.
    1. Strother SC, Anderson J, Hansen LK, Kjems U, Kustra R, Sidtis J, et al. The quantitative evaluation of functional neuroimaging experiments: the NPAIRS data analysis framework. Neuroimage. 2002;15: 747–771.
    1. Strother S, La Conte S, Kai Hansen L, Anderson J, Zhang J, Pulapura S, et al. Optimizing the fMRI data-processing pipeline using prediction and reproducibility performance metrics: I. A preliminary group analysis. Neuroimage. 2004;23 Suppl 1:S196–207.
    1. Rosenfeld ES, Pearlson GD, Sweeney JA, Tamminga CA, Keshavan MS, Nonterah C, et al. Prolonged hemodynamic response during incidental facial emotion processing in inter-episode bipolar I disorder. Brain Imaging Behav. 2014;8: 73–86 10.1007/s11682-013-9246-z
    1. Churchill NW, Yourganov G, Spring R, Rasmussen PM, Lee W, Ween JE, et al. PHYCAA: data-driven measurement and removal of physiological noise in BOLD fMRI. Neuroimage. 2012;59: 1299–1314. 10.1016/j.neuroimage.2011.08.021
    1. Fournier JC, Chase HW, Almeida J, Phillips ML. Model Specification and the Reliability of fMRI Results: Implications for Longitudinal Neuroimaging Studies in Psychiatry. Plos One. 2014;9:e105169 10.1371/journal.pone.0105169
    1. Sauder CL, Hajcak G, Angstadt M, Phan KL. Test-retest reliability of amygdala response to emotional faces. Psychophysiology. 2013;50: 1147–1156. 10.1111/psyp.12129
    1. Plichta MM, Schwarz AJ, Grimm O, Morgen K, Mier D, Haddad L, et al. Test-retest reliability of evoked BOLD signals from a cognitive-emotive fMRI test battery. Neuroimage. 2012;60: 1746–1758. 10.1016/j.neuroimage.2012.01.129
    1. Fournier JC, Keener MT, Mullin BC, Hafeman DM, Labarbara EJ, Stiffler RS, et al. Heterogeneity of amygdala response in major depressive disorder: the impact of lifetime subthreshold mania. Psychol Med. 2013;43: 293–302. 10.1017/S0033291712000918
    1. Phillips ML, Medford N, Young AW, Williams L, Williams SC, Bullmore ET, et al. Time courses of left and right amygdalar responses to fearful facial expressions. Hum Brain Mapp. 2001;12: 193–202.
    1. Plichta MM, Grimm O, Morgen K, Mier D, Sauer C, Haddad L, et al. Amygdala habituation: A reliable fMRI phenotype. Neuroimage. 2014;103C: 383–390.
    1. Li J, Schiller D, Schoenbaum G, Phelps EA, Daw ND. Differential roles of human striatum and amygdala in associative learning. Nat Neurosci. 2011;14: 1250–1252. 10.1038/nn.2904
    1. Esber GR, Roesch MR, Bali S, Trageser J, Bissonette GB, Puche AC, et al. Attention-related Pearce-Kaye-Hall signals in basolateral amygdala require the midbrain dopaminergic system. Biol Psychiatry. 2012;72: 1012–1019. 10.1016/j.biopsych.2012.05.023
    1. O'Doherty JP, Dayan P, Friston K, Critchley H, Dolan RJ. Temporal difference models and reward-related learning in the human brain. Neuron. 2003;38: 329–337.
    1. Schultz W, Dayan P, Montague PR. A neural substrate of prediction and reward. Science. 1997;275: 1593–1599.
    1. O'Reilly RC, Frank MJ, Hazy TE, Watz B. PVLV: the primary value and learned value Pavlovian learning algorithm. Behav Neurosci. 2007;121: 31–49.
    1. Delgado MR, Nystrom LE, Fissell C, Noll DC, Fiez JA. Tracking the hemodynamic responses to reward and punishment in the striatum. J Neurophysiol. 2000;84: 3072–3077.
    1. Forbes EE, Hariri AR, Martin SL, Silk JS, Moyles DL, Fisher PM, et al. Altered striatal activation predicting real-world positive affect in adolescent major depressive disorder. Am J Psychiatry. 2009;166: 64–73. 10.1176/appi.ajp.2008.07081336
    1. Chase HW, Nusslock R, Almeida JR, Forbes EE, Labarbara EJ, Phillips ML. Dissociable patterns of abnormal frontal cortical activation during anticipation of an uncertain reward or loss in bipolar versus major depression. Bipolar Disord. 2013;15: 839–854 10.1111/bdi.12132
    1. Chowdhury R, Guitart-Masip M, Lambert C, Dayan P, Huys Q, Duzel E, et al. Dopamine restores reward prediction errors in old age. Nat Neurosci. 2013;16: 648–653. 10.1038/nn.3364
    1. O'Doherty J, Dayan P, Schultz J, Deichmann R, Friston K, Dolan RJ. Dissociable roles of ventral and dorsal striatum in instrumental conditioning. Science. 2004;304: 452–454.
    1. Knutson B, Bhanji JP, Cooney RE, Atlas LY, Gotlib IH. Neural responses to monetary incentives in major depression. Biol Psychiatry. 2008;63: 686–692.
    1. Pizzagalli DA, Holmes AJ, Dillon DG, Goetz EL, Birk JL, Bogdan R, et al. Reduced caudate and nucleus accumbens response to rewards in unmedicated individuals with major depressive disorder. Am J Psychiatry. 2009;166: 702–710. 10.1176/appi.ajp.2008.08081201
    1. Dombrovski AY, Szanto K, Clark L, Reynolds CF, Siegle GJ. Reward Signals, Attempted Suicide, and Impulsivity in Late-Life Depression. JAMA Psychiatry. 2013. 70: 1020–1030
    1. Gradin VB, Kumar P, Waiter G, Ahearn T, Stickle C, Milders M, et al. Expected value and prediction error abnormalities in depression and schizophrenia. Brain. 2011;134: 1751–1764. 10.1093/brain/awr059
    1. Kumar P, Waiter G, Ahearn T, Milders M, Reid I, Steele JD. Abnormal temporal difference reward-learning signals in major depression. Brain. 2008;131: 2084–2093. 10.1093/brain/awn136
    1. Stoy M, Schlagenhauf F, Sterzer P, Bermpohl F, Hagele C, Suchotzki K, et al. Hyporeactivity of ventral striatum towards incentive stimuli in unmedicated depressed patients normalizes after treatment with escitalopram. J Psychopharmacol. 2012;26: 677–688. 10.1177/0269881111416686
    1. Phillips ML, Chase HW, Sheline YI, Etkin A, Almeida JR, Deckersbach T, et al. Identifying predictors, moderators, and mediators of antidepressant response in major depressive disorder: neuroimaging approaches. Am J Psychiatry. 2015;172: 124–138. 10.1176/appi.ajp.2014.14010076
    1. Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull. 1979;86: 420–428.
    1. Gallistel CR. The importance of proving the null. Psychol Rev. 2009;116: 439–453. 10.1037/a0015251
    1. Kass RE, Raftery AE. Bayes Factors. Journal of the American Statistical Association. 1995;90: 773–795.
    1. Van Dijk KR, Sabuncu MR, Buckner RL. The influence of head motion on intrinsic functional connectivity MRI. Neuroimage. 2012;59:431–438. 10.1016/j.neuroimage.2011.07.044
    1. Yu AJ, Dayan P. Uncertainty, neuromodulation, and attention. Neuron. 2005;46: 681–692.
    1. Mackintosh NJ. Theory of Attention—Variations in Associability of Stimuli with Reinforcement. Psychological Review. 1975;82: 276–298.
    1. Le Pelley ME. The role of associative history in models of associative learning: a selective review and a hybrid model. Q J Exp Psychol B. 2004;57: 193–243.
    1. Fliessbach K, Rohe T, Linder NS, Trautner P, Elger CE, Weber B. Retest reliability of reward-related BOLD signals. Neuroimage. 2010;50: 1168–1176. 10.1016/j.neuroimage.2010.01.036
    1. Wu CC, Samanez-Larkin GR, Katovich K, Knutson B. Affective traits link to reliable neural markers of incentive anticipation. Neuroimage. 2014;84: 279–289. 10.1016/j.neuroimage.2013.08.055
    1. Wacker J, Dillon DG, Pizzagalli DA. The role of the nucleus accumbens and rostral anterior cingulate cortex in anhedonia: integration of resting EEG, fMRI, and volumetric techniques. Neuroimage. 2009;46: 327–337. 10.1016/j.neuroimage.2009.01.058
    1. Freyer T, Valerius G, Kuelz AK, Speck O, Glauche V, Hull M, et al. Test-retest reliability of event-related functional MRI in a probabilistic reversal learning task. Psychiatry Res. 2009;174: 40–46. 10.1016/j.pscychresns.2009.03.003
    1. Hampton AN, Bossaerts P, O'Doherty JP. The role of the ventromedial prefrontal cortex in abstract state-based inference during decision making in humans. J Neurosci. 2006;26: 8360–8367.
    1. Specht K, Willmes K, Shah NJ, Jancke L. Assessment of reliability in functional imaging studies. Journal of magnetic resonance imaging: JMRI. 2003;17: 463–471.
    1. Caceres A, Hall DL, Zelaya FO, Williams SC, Mehta MA. Measuring fMRI reliability with the intra-class correlation coefficient. Neuroimage. 2009;45: 758–768. 10.1016/j.neuroimage.2008.12.035
    1. Chen G, Saad ZS, Nath AR, Beauchamp MS, Cox RW. FMRI group analysis combining effect estimates and their variances. Neuroimage. 2012;60: 747–765. 10.1016/j.neuroimage.2011.12.060
    1. Friston KJ, Stephan KE, Lund TE, Morcom A, Kiebel S. Mixed-effects and fMRI studies. Neuroimage. 2005;24: 244–252.
    1. Thompson B. If statistical significance tests are broken/misused, what practices should supplement or replace them? Theor Psychol. 1999;9: 165–181.
    1. Whelan R, Garavan H. When Optimism Hurts: Inflated Predictions in Psychiatric Neuroimaging. Biol Psychiatry. 2013;75: 746–748 10.1016/j.biopsych.2013.05.014
    1. Hastie T, Tibshirani R, Friedman J. The Elements of Statistical Learning: Prediction, Inference and Data Mining: Springer Verlag; 2009.
    1. Nestler EJ, Carlezon WA Jr. The mesolimbic dopamine reward circuit in depression. Biol Psychiatry. 2006;59: 1151–1159.

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