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Bari S, Kim BW, Vike NL, Lalvani S, Stefanopoulos L, Maglaveras N, Block M, Strawn J, Katsaggelos AK, Breiter HC. A novel approach to anxiety level prediction using small sets of judgment and survey variables. NPJ MENTAL HEALTH RESEARCH 2024; 3:29. [PMID: 38890545 PMCID: PMC11189415 DOI: 10.1038/s44184-024-00074-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 05/16/2024] [Indexed: 06/20/2024]
Abstract
Anxiety, a condition characterized by intense fear and persistent worry, affects millions each year and, when severe, is distressing and functionally impairing. Numerous machine learning frameworks have been developed and tested to predict features of anxiety and anxiety traits. This study extended these approaches by using a small set of interpretable judgment variables (n = 15) and contextual variables (demographics, perceived loneliness, COVID-19 history) to (1) understand the relationships between these variables and (2) develop a framework to predict anxiety levels [derived from the State Trait Anxiety Inventory (STAI)]. This set of 15 judgment variables, including loss aversion and risk aversion, models biases in reward/aversion judgments extracted from an unsupervised, short (2-3 min) picture rating task (using the International Affective Picture System) that can be completed on a smartphone. The study cohort consisted of 3476 de-identified adult participants from across the United States who were recruited using an email survey database. Using a balanced Random Forest approach with these judgment and contextual variables, STAI-derived anxiety levels were predicted with up to 81% accuracy and 0.71 AUC ROC. Normalized Gini scores showed that the most important predictors (age, loneliness, household income, employment status) contributed a total of 29-31% of the cumulative relative importance and up to 61% was contributed by judgment variables. Mediation/moderation statistics revealed that the interactions between judgment and contextual variables appears to be important for accurately predicting anxiety levels. Median shifts in judgment variables described a behavioral profile for individuals with higher anxiety levels that was characterized by less resilience, more avoidance, and more indifference behavior. This study supports the hypothesis that distinct constellations of 15 interpretable judgment variables, along with contextual variables, could yield an efficient and highly scalable system for mental health assessment. These results contribute to our understanding of underlying psychological processes that are necessary to characterize what causes variance in anxiety conditions and its behaviors, which can impact treatment development and efficacy.
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Affiliation(s)
- Sumra Bari
- Department of Computer Science, University of Cincinnati, Cincinnati, OH, USA
| | - Byoung-Woo Kim
- Department of Computer Science, University of Cincinnati, Cincinnati, OH, USA
| | - Nicole L Vike
- Department of Computer Science, University of Cincinnati, Cincinnati, OH, USA
| | - Shamal Lalvani
- Department of Electrical Engineering, Northwestern University, Evanston, IL, USA
| | - Leandros Stefanopoulos
- Department of Electrical Engineering, Northwestern University, Evanston, IL, USA
- Laboratory of Medical Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Nicos Maglaveras
- Laboratory of Medical Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Martin Block
- Integrated Marketing Communications, Medill School of Journalism, Northwestern University, Evanston, IL, USA
| | - Jeffrey Strawn
- Department of Psychiatry and Behavioral Neuroscience, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Aggelos K Katsaggelos
- Department of Electrical Engineering, Northwestern University, Evanston, IL, USA
- Department of Computer Science, Northwestern University, Evanston, IL, USA
- Department of Radiology, Northwestern University, Chicago, IL, USA
| | - Hans C Breiter
- Department of Computer Science, University of Cincinnati, Cincinnati, OH, USA.
- Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH, USA.
- Department of Psychiatry, Massachusetts General Hospital and Harvard School of Medicine, Boston, MA, USA.
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Vike NL, Bari S, Stefanopoulos L, Lalvani S, Kim BW, Maglaveras N, Block M, Breiter HC, Katsaggelos AK. Predicting COVID-19 Vaccination Uptake Using a Small and Interpretable Set of Judgment and Demographic Variables: Cross-Sectional Cognitive Science Study. JMIR Public Health Surveill 2024; 10:e47979. [PMID: 38315620 PMCID: PMC10953811 DOI: 10.2196/47979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 08/08/2023] [Accepted: 01/10/2024] [Indexed: 02/07/2024] Open
Abstract
BACKGROUND Despite COVID-19 vaccine mandates, many chose to forgo vaccination, raising questions about the psychology underlying how judgment affects these choices. Research shows that reward and aversion judgments are important for vaccination choice; however, no studies have integrated such cognitive science with machine learning to predict COVID-19 vaccine uptake. OBJECTIVE This study aims to determine the predictive power of a small but interpretable set of judgment variables using 3 machine learning algorithms to predict COVID-19 vaccine uptake and interpret what profile of judgment variables was important for prediction. METHODS We surveyed 3476 adults across the United States in December 2021. Participants answered demographic, COVID-19 vaccine uptake (ie, whether participants were fully vaccinated), and COVID-19 precaution questions. Participants also completed a picture-rating task using images from the International Affective Picture System. Images were rated on a Likert-type scale to calibrate the degree of liking and disliking. Ratings were computationally modeled using relative preference theory to produce a set of graphs for each participant (minimum R2>0.8). In total, 15 judgment features were extracted from these graphs, 2 being analogous to risk and loss aversion from behavioral economics. These judgment variables, along with demographics, were compared between those who were fully vaccinated and those who were not. In total, 3 machine learning approaches (random forest, balanced random forest [BRF], and logistic regression) were used to test how well judgment, demographic, and COVID-19 precaution variables predicted vaccine uptake. Mediation and moderation were implemented to assess statistical mechanisms underlying successful prediction. RESULTS Age, income, marital status, employment status, ethnicity, educational level, and sex differed by vaccine uptake (Wilcoxon rank sum and chi-square P<.001). Most judgment variables also differed by vaccine uptake (Wilcoxon rank sum P<.05). A similar area under the receiver operating characteristic curve (AUROC) was achieved by the 3 machine learning frameworks, although random forest and logistic regression produced specificities between 30% and 38% (vs 74.2% for BRF), indicating a lower performance in predicting unvaccinated participants. BRF achieved high precision (87.8%) and AUROC (79%) with moderate to high accuracy (70.8%) and balanced recall (69.6%) and specificity (74.2%). It should be noted that, for BRF, the negative predictive value was <50% despite good specificity. For BRF and random forest, 63% to 75% of the feature importance came from the 15 judgment variables. Furthermore, age, income, and educational level mediated relationships between judgment variables and vaccine uptake. CONCLUSIONS The findings demonstrate the underlying importance of judgment variables for vaccine choice and uptake, suggesting that vaccine education and messaging might target varying judgment profiles to improve uptake. These methods could also be used to aid vaccine rollouts and health care preparedness by providing location-specific details (eg, identifying areas that may experience low vaccination and high hospitalization).
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Affiliation(s)
- Nicole L Vike
- Department of Computer Science, University of Cincinnati, Cincinnati, OH, United States
| | - Sumra Bari
- Department of Computer Science, University of Cincinnati, Cincinnati, OH, United States
| | - Leandros Stefanopoulos
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
- School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Shamal Lalvani
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
| | - Byoung Woo Kim
- Department of Computer Science, University of Cincinnati, Cincinnati, OH, United States
| | - Nicos Maglaveras
- School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Martin Block
- Integrated Marketing Communications, Medill School, Northwestern University, Evanston, IL, United States
| | - Hans C Breiter
- Department of Computer Science, University of Cincinnati, Cincinnati, OH, United States
- Department of Psychiatry, Massachusetts General Hospital, Harvard School of Medicine, Boston, MA, United States
| | - Aggelos K Katsaggelos
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
- Department of Computer Science, Northwestern University, Evanston, IL, United States
- Department of Radiology, Northwestern University, Evanston, IL, United States
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Vike NL, Bari S, Kim BW, Katsaggelos AK, Blood AJ, Breiter HC. Characterizing major depressive disorder and substance use disorder using heatmaps and variable interactions: The utility of operant behavior and brain structure relationships. PLoS One 2024; 19:e0299528. [PMID: 38466739 PMCID: PMC10927130 DOI: 10.1371/journal.pone.0299528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 02/13/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Rates of depression and addiction have risen drastically over the past decade, but the lack of integrative techniques remains a barrier to accurate diagnoses of these mental illnesses. Changes in reward/aversion behavior and corresponding brain structures have been identified in those with major depressive disorder (MDD) and cocaine-dependence polysubstance abuse disorder (CD). Assessment of statistical interactions between computational behavior and brain structure may quantitatively segregate MDD and CD. METHODS Here, 111 participants [40 controls (CTRL), 25 MDD, 46 CD] underwent structural brain MRI and completed an operant keypress task to produce computational judgment metrics. Three analyses were performed: (1) linear regression to evaluate groupwise (CTRL v. MDD v. CD) differences in structure-behavior associations, (2) qualitative and quantitative heatmap assessment of structure-behavior association patterns, and (3) the k-nearest neighbor machine learning approach using brain structure and keypress variable inputs to discriminate groups. RESULTS This study yielded three primary findings. First, CTRL, MDD, and CD participants had distinct structure-behavior linear relationships, with only 7.8% of associations overlapping between any two groups. Second, the three groups had statistically distinct slopes and qualitatively distinct association patterns. Third, a machine learning approach could discriminate between CTRL and CD, but not MDD participants. CONCLUSIONS These findings demonstrate that variable interactions between computational behavior and brain structure, and the patterns of these interactions, segregate MDD and CD. This work raises the hypothesis that analysis of interactions between operant tasks and structural neuroimaging might aide in the objective classification of MDD, CD and other mental health conditions.
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Affiliation(s)
- Nicole L. Vike
- Department of Computer Science, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Sumra Bari
- Department of Computer Science, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Byoung Woo Kim
- Department of Computer Science, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Aggelos K. Katsaggelos
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, Illinois, United States of America
- Department of Computer Science, Northwestern University, Evanston, Illinois, United States of America
- Department of Radiology, Northwestern University, Chicago, Illinois, United States of America
| | - Anne J. Blood
- Department of Psychiatry, Mood and Motor Control Laboratory (MAML), Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Psychiatry, Laboratory of Neuroimaging and Genetics, Massachusetts General Hospital and Harvard School of Medicine, Boston, Massachusetts, United States of America
| | - Hans C. Breiter
- Department of Computer Science, University of Cincinnati, Cincinnati, Ohio, United States of America
- Department of Psychiatry, Mood and Motor Control Laboratory (MAML), Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Psychiatry, Laboratory of Neuroimaging and Genetics, Massachusetts General Hospital and Harvard School of Medicine, Boston, Massachusetts, United States of America
- Department of Biomedical Engineering, University of Cincinnati, Cincinnati, Ohio, United States of America
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Gutentag T, Tamir M. Putting Effort into Emotion Regulation: Manipulating Desirability and Motivational Strength. AFFECTIVE SCIENCE 2022; 3:878-893. [PMID: 36519146 PMCID: PMC9743940 DOI: 10.1007/s42761-022-00155-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 09/15/2022] [Indexed: 06/17/2023]
Abstract
Although people often want to regulate their emotions, they are sometimes reluctant to invest the necessary effort in doing so. We propose that people could be motivated to invest effort in emotion regulation, by rendering the target emotional state more desirable. Rendering an emotion goal more desirable can motivate people to invest effort in emotion regulation, ultimately facilitating successful emotion regulation. In three studies (N = 452), we show that both inside and outside the lab, rendering calmness more desirable, boosted the motivational strength to increase calmness, increasing the effort people invested to increase calmness, and ultimately made people calmer. This investigation points to the importance of motivational strength as a potential means to promote effort and success in emotion regulation. Supplementary Information The online version contains supplementary material available at 10.1007/s42761-022-00155-0.
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Affiliation(s)
- Tony Gutentag
- Department of Psychology, The Hebrew University of Jerusalem, 91905 Jerusalem, Israel
| | - Maya Tamir
- Department of Psychology, The Hebrew University of Jerusalem, 91905 Jerusalem, Israel
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Bari S, Vike NL, Stetsiv K, Woodward S, Lalvani S, Stefanopoulos L, Kim BW, Maglaveras N, Breiter HC, Katsaggelos AK. The Prevalence of Psychotic Symptoms, Violent Ideation, and Disruptive Behavior in a Population With SARS-CoV-2 Infection: Preliminary Study. JMIR Form Res 2022; 6:e36444. [PMID: 35763758 PMCID: PMC9384857 DOI: 10.2196/36444] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 04/06/2022] [Accepted: 05/14/2022] [Indexed: 11/26/2022] Open
Abstract
Background The COVID-19 disease results from infection by the SARS-CoV-2 virus to produce a range of mild to severe physical, neurological, and mental health symptoms. The COVID-19 pandemic has indirectly caused significant emotional distress, triggering the emergence of mental health symptoms in individuals who were not previously affected or exacerbating symptoms in those with existing mental health conditions. Emotional distress and certain mental health conditions can lead to violent ideation and disruptive behavior, including aggression, threatening acts, deliberate harm toward other people or animals, and inattention to or noncompliance with education or workplace rules. Of the many mental health conditions that can be associated with violent ideation and disruptive behavior, psychosis can evidence greater vulnerability to unpredictable changes and being at a greater risk for them. Individuals with psychosis can also be more susceptible to contracting COVID-19 disease. Objective This study aimed to investigate whether violent ideation, disruptive behavior, or psychotic symptoms were more prevalent in a population with COVID-19 and did not precede the pandemic. Methods In this preliminary study, we analyzed questionnaire responses from a population sample (N=366), received between the end of February 2021 and the start of March 2021 (1 year into the COVID-19 pandemic), regarding COVID-19 illness, violent ideation, disruptive behavior, and psychotic symptoms. Using the Wilcoxon rank sum test followed by multiple comparisons correction, we compared the self-reported frequency of these variables for 3 time windows related to the past 1 month, past 1 month to 1 year, and >1 year ago among the distributions of people who answered whether they tested positive or were diagnosed with COVID-19 by a clinician. We also used multivariable logistic regression with iterative resampling to investigate the relationship between these variables occurring >1 year ago (ie, before the pandemic) and the likelihood of contracting COVID-19. Results We observed a significantly higher frequency of self-reported violent ideation, disruptive behavior, and psychotic symptoms, for all 3 time windows of people who tested positive or were diagnosed with COVID-19 by a clinician. Using multivariable logistic regression, we observed 72% to 94% model accuracy for an increased incidence of COVID-19 in participants who reported violent ideation, disruptive behavior, or psychotic symptoms >1 year ago. Conclusions This preliminary study found that people who reported a test or clinician diagnosis of COVID-19 also reported higher frequencies of violent ideation, disruptive behavior, or psychotic symptoms across multiple time windows, indicating that they were not likely to be the result of COVID-19. In parallel, participants who reported these behaviors >1 year ago (ie, before the pandemic) were more likely to be diagnosed with COVID-19, suggesting that violent ideation, disruptive behavior, in addition to psychotic symptoms, were associated with COVID-19 with an approximately 70% to 90% likelihood.
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Affiliation(s)
- Sumra Bari
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Nicole L Vike
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Khrystyna Stetsiv
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Sean Woodward
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Shamal Lalvani
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
| | - Leandros Stefanopoulos
- Laboratory of Medical Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Byoung Woo Kim
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, United States
| | - Nicos Maglaveras
- Laboratory of Medical Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Hans C Breiter
- Laboratory of Neuroimaging and Genetics, Division of Psychiatric Neuroscience, Massachusetts General Hospital, Charlestown, MA, United States
| | - Aggelos K Katsaggelos
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
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Waugh JL, Hassan A, Kuster JK, Levenstein JM, Warfield SK, Makris N, Brüggemann N, Sharma N, Breiter HC, Blood AJ. An MRI method for parcellating the human striatum into matrix and striosome compartments in vivo. Neuroimage 2021; 246:118714. [PMID: 34800665 PMCID: PMC9142299 DOI: 10.1016/j.neuroimage.2021.118714] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 11/02/2021] [Accepted: 11/05/2021] [Indexed: 11/19/2022] Open
Abstract
The mammalian striatum is comprised of intermingled tissue compartments, matrix and striosome. Though indistinguishable by routine histological techniques, matrix and striosome have distinct embryologic origins, afferent/efferent connections, surface protein expression, intra-striatal location, susceptibilities to injury, and functional roles in a range of animal behaviors. Distinguishing the compartments previously required post-mortem tissue and/or genetic manipulation; we aimed to identify matrix/striosome non-invasively in living humans. We used diffusion MRI (probabilistic tractography) to identify human striatal voxels with connectivity biased towards matrix-favoring or striosome-favoring regions (determined by prior animal tract-tracing studies). Segmented striatal compartments replicated the topological segregation and somatotopic organization identified in animal matrix/striosome studies. Of brain regions mapped in prior studies, our human brain data confirmed 93% of the compartment-selective structural connectivity demonstrated in animals. Test-retest assessment on repeat scans found a voxel classification error rate of 0.14%. Fractional anisotropy was significantly higher in matrix-like voxels, while mean diffusivity did not differ between the compartments. As mapped by the Talairach human brain atlas, 460 regions were significantly biased towards either matrix or striosome. Our method allows the study of striatal compartments in human health and disease, in vivo, for the first time.
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Affiliation(s)
- J L Waugh
- Division of Pediatric Neurology, Department of Pediatrics, University of Texas Southwestern, Dallas, TX, United States; Division of Child Neurology, University of Texas Southwestern, Dallas, TX, United States; Boston Children's Hospital, Harvard Medical School, Boston, MA, United States; Mood and Motor Control Laboratory, Boston, MA, United States; Martinos Center for Biomedical Imaging, United States; Massachusetts General Hospital, Charlestown, MA, United States.
| | - Aao Hassan
- Division of Pediatric Neurology, Department of Pediatrics, University of Texas Southwestern, Dallas, TX, United States
| | - J K Kuster
- Mood and Motor Control Laboratory, Boston, MA, United States; Laboratory of Neuroimaging and Genetics, United States; Martinos Center for Biomedical Imaging, United States; Rheumatology, Allergy and Immunology Section, Massachusetts General Hospital, Boston, MA, United States.
| | - J M Levenstein
- Mood and Motor Control Laboratory, Boston, MA, United States; Martinos Center for Biomedical Imaging, United States; Yale School of Medicine, New Haven, CN, United States; Wellcome Centre for Integrative Neuroimaging, National Institutes of Health, Bethesda, MD, United States.
| | - S K Warfield
- Department of Radiology, United States; Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.
| | - N Makris
- Boston Children's Hospital, Harvard Medical School, Boston, MA, United States; Center for Morphometric Analysis, United States; Martinos Center for Biomedical Imaging, United States; Departments of Neurology and Psychiatry, Charlestown, MA, United States.
| | - N Brüggemann
- Department of Neurology, University of Oxford, Oxford, United Kingdom; Institute of Neurogenetics, University of Lübeck, Lübeck, Germany.
| | - N Sharma
- Boston Children's Hospital, Harvard Medical School, Boston, MA, United States; Massachusetts General Hospital, Charlestown, MA, United States.
| | - H C Breiter
- Laboratory of Neuroimaging and Genetics, United States; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
| | - A J Blood
- Mood and Motor Control Laboratory, Boston, MA, United States; Laboratory of Neuroimaging and Genetics, United States; Martinos Center for Biomedical Imaging, United States; Departments of Neurology and Psychiatry, Charlestown, MA, United States.
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Warren C, Schneider S, Smith KB, Hibbing JR. Motivated viewing: Selective exposure to political images when reasoning is not involved. PERSONALITY AND INDIVIDUAL DIFFERENCES 2020. [DOI: 10.1016/j.paid.2019.109704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Shi Z, Wang AL, Jagannathan K, Fairchild VP, O'Brien CP, Childress AR, Langleben DD. Effects of extended-release naltrexone on the brain response to drug-related stimuli in patients with opioid use disorder. J Psychiatry Neurosci 2018; 43:170036. [PMID: 29485031 PMCID: PMC6019353 DOI: 10.1503/jpn.170036] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 07/22/2017] [Accepted: 10/07/2017] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Heightened response to drug-related cues is a hallmark of addiction. Extended-release naltrexone (XR-NTX) is a US Food and Drug Administration-approved pharmacotherapy for relapse prevention in patients with opioid use disorder (OUD). In these patients, XR-NTX has been shown to reduce brain responses to opioid-related visual stimuli. To assess the biomarker potential of this phenomenon, it is necessary to determine whether this effect is limited to opioid-related stimuli and whether it is associated with key OUD symptoms. METHODS Using functional MRI (fMRI), we measured the brain responses to opioid-related and control (i.e., sexual and aversive) images in detoxified patients with OUD before, during and after XR-NTX treatment. Craving and withdrawal severity were evaluated using clinician- and self-administered instruments during each session. RESULTS We included 24 patients with OUD in our analysis. During XR-NTX treatment, we found reduced responses to opioid-related stimuli in the nucleus accumbens (NAcc) and medial orbitofrontal cortex (mOFC). The reduction in mOFC response was specific to the opioid-related stimuli. The reduced NAcc and mOFC opioid cue reactivity was correlated with reduction in clinician-assessed and self-reported withdrawal symptoms, respectively. LIMITATIONS The study was not placebo-controlled owing to ethical, safety and feasibility concerns. CONCLUSION Extended-release naltrexone reduces the NAcc and mOFC cue reactivity in patients with OUD. This effect is specific to opioid-related stimuli in the mOFC only. The reduction in neural response to opioid-related stimuli is more robust in patients with greater decline in withdrawal severity. Our results support the clinical utility of mesocorticolimbic cue reactivity in monitoring the XR-NTX treatment outcomes and highlight the link between opioid withdrawal symptomatology and neural opioid cue reactivity.
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Affiliation(s)
- Zhenhao Shi
- From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa. (Shi, Wang, Jagannathan, Fairchild, O'Brien, Childress, Langleben); the Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY (Wang); the Annenberg Public Policy Center, University of Pennsylvania, Philadelphia, Pa. (Langleben); and the Corporal Michael J. Crescenz Veterans Administration Medical Center, Philadelphia, Pa. (Langleben)
| | - An-Li Wang
- From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa. (Shi, Wang, Jagannathan, Fairchild, O'Brien, Childress, Langleben); the Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY (Wang); the Annenberg Public Policy Center, University of Pennsylvania, Philadelphia, Pa. (Langleben); and the Corporal Michael J. Crescenz Veterans Administration Medical Center, Philadelphia, Pa. (Langleben)
| | - Kanchana Jagannathan
- From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa. (Shi, Wang, Jagannathan, Fairchild, O'Brien, Childress, Langleben); the Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY (Wang); the Annenberg Public Policy Center, University of Pennsylvania, Philadelphia, Pa. (Langleben); and the Corporal Michael J. Crescenz Veterans Administration Medical Center, Philadelphia, Pa. (Langleben)
| | - Victoria P Fairchild
- From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa. (Shi, Wang, Jagannathan, Fairchild, O'Brien, Childress, Langleben); the Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY (Wang); the Annenberg Public Policy Center, University of Pennsylvania, Philadelphia, Pa. (Langleben); and the Corporal Michael J. Crescenz Veterans Administration Medical Center, Philadelphia, Pa. (Langleben)
| | - Charles P O'Brien
- From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa. (Shi, Wang, Jagannathan, Fairchild, O'Brien, Childress, Langleben); the Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY (Wang); the Annenberg Public Policy Center, University of Pennsylvania, Philadelphia, Pa. (Langleben); and the Corporal Michael J. Crescenz Veterans Administration Medical Center, Philadelphia, Pa. (Langleben)
| | - Anna Rose Childress
- From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa. (Shi, Wang, Jagannathan, Fairchild, O'Brien, Childress, Langleben); the Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY (Wang); the Annenberg Public Policy Center, University of Pennsylvania, Philadelphia, Pa. (Langleben); and the Corporal Michael J. Crescenz Veterans Administration Medical Center, Philadelphia, Pa. (Langleben)
| | - Daniel D Langleben
- From the Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa. (Shi, Wang, Jagannathan, Fairchild, O'Brien, Childress, Langleben); the Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY (Wang); the Annenberg Public Policy Center, University of Pennsylvania, Philadelphia, Pa. (Langleben); and the Corporal Michael J. Crescenz Veterans Administration Medical Center, Philadelphia, Pa. (Langleben)
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Livengood SL, Sheppard JP, Kim BW, Malthouse EC, Bourne JE, Barlow AE, Lee MJ, Marin V, O'Connor KP, Csernansky JG, Block MP, Blood AJ, Breiter HC. Keypress-Based Musical Preference Is Both Individual and Lawful. Front Neurosci 2017; 11:136. [PMID: 28512395 PMCID: PMC5412065 DOI: 10.3389/fnins.2017.00136] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Accepted: 03/06/2017] [Indexed: 11/13/2022] Open
Abstract
Musical preference is highly individualized and is an area of active study to develop methods for its quantification. Recently, preference-based behavior, associated with activity in brain reward circuitry, has been shown to follow lawful, quantifiable patterns, despite broad variation across individuals. These patterns, observed using a keypress paradigm with visual stimuli, form the basis for relative preference theory (RPT). Here, we sought to determine if such patterns extend to non-visual domains (i.e., audition) and dynamic stimuli, potentially providing a method to supplement psychometric, physiological, and neuroimaging approaches to preference quantification. For this study, we adapted our keypress paradigm to two sets of stimuli consisting of seventeenth to twenty-first century western art music (Classical) and twentieth to twenty-first century jazz and popular music (Popular). We studied a pilot sample and then a separate primary experimental sample with this paradigm, and used iterative mathematical modeling to determine if RPT relationships were observed with high R2 fits. We further assessed the extent of heterogeneity in the rank ordering of keypress-based responses across subjects. As expected, individual rank orderings of preferences were quite heterogeneous, yet we observed mathematical patterns fitting these data similar to those observed previously with visual stimuli. These patterns in music preference were recurrent across two cohorts and two stimulus sets, and scaled between individual and group data, adhering to the requirements for lawfulness. Our findings suggest a general neuroscience framework that predicts human approach/avoidance behavior, while also allowing for individual differences and the broad diversity of human choices; the resulting framework may offer novel approaches to advancing music neuroscience, or its applications to medicine and recommendation systems.
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Affiliation(s)
- Sherri L Livengood
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern UniversityChicago, IL, USA.,Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA
| | - John P Sheppard
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern UniversityChicago, IL, USA.,Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA.,David Geffen School of Medicine, University of California, Los AngelesLos Angeles, CA, USA
| | - Byoung W Kim
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern UniversityChicago, IL, USA.,Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA.,Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood DisordersBoston, MA, USA
| | - Edward C Malthouse
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA.,Medill Integrated Marketing Communications, Northwestern UniversityEvanston, IL, USA
| | - Janet E Bourne
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA.,Music Department, Bates CollegeLewiston, ME, USA
| | - Anne E Barlow
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA.,KV 265, The Communication of Science through ArtWillow Springs, IL, USA
| | - Myung J Lee
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern UniversityChicago, IL, USA.,Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA.,Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood DisordersBoston, MA, USA
| | - Veronica Marin
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern UniversityChicago, IL, USA
| | - Kailyn P O'Connor
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern UniversityChicago, IL, USA
| | - John G Csernansky
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern UniversityChicago, IL, USA
| | - Martin P Block
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA.,Medill Integrated Marketing Communications, Northwestern UniversityEvanston, IL, USA
| | - Anne J Blood
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA.,Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood DisordersBoston, MA, USA.,Mood and Motor Control Laboratory, Department of Psychiatry, Massachusetts General HospitalBoston, MA, USA.,Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General HospitalBoston, MA, USA.,Department of Neurology, Massachusetts General HospitalBoston, MA, USA
| | - Hans C Breiter
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern UniversityChicago, IL, USA.,Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA.,Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood DisordersBoston, MA, USA.,Mood and Motor Control Laboratory, Department of Psychiatry, Massachusetts General HospitalBoston, MA, USA.,Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General HospitalBoston, MA, USA
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10
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Viswanathan V, Sheppard JP, Kim BW, Plantz CL, Ying H, Lee MJ, Raman K, Mulhern FJ, Block MP, Calder B, Lee S, Mortensen DT, Blood AJ, Breiter HC. A Quantitative Relationship between Signal Detection in Attention and Approach/Avoidance Behavior. Front Psychol 2017; 8:122. [PMID: 28270776 PMCID: PMC5318395 DOI: 10.3389/fpsyg.2017.00122] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Accepted: 01/17/2017] [Indexed: 11/13/2022] Open
Abstract
This study examines how the domains of reward and attention, which are often studied as independent processes, in fact interact at a systems level. We operationalize divided attention with a continuous performance task and variables from signal detection theory (SDT), and reward/aversion with a keypress task measuring approach/avoidance in the framework of relative preference theory (RPT). Independent experiments with the same subjects showed a significant association between one SDT and two RPT variables, visualized as a three-dimensional structure. Holding one of these three variables constant, further showed a significant relationship between a loss aversion-like metric from the approach/avoidance task, and the response bias observed during the divided attention task. These results indicate that a more liberal response bias under signal detection (i.e., a higher tolerance for noise, resulting in a greater proportion of false alarms) is associated with higher "loss aversion." Furthermore, our functional model suggests a mechanism for processing constraints with divided attention and reward/aversion. Together, our results argue for a systematic relationship between divided attention and reward/aversion processing in humans.
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Affiliation(s)
- Vijay Viswanathan
- Medill Integrated Marketing Communications, Northwestern UniversityEvanston, IL, USA; Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA
| | - John P Sheppard
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of MedicineChicago, IL, USA
| | - Byoung W Kim
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of MedicineChicago, IL, USA; Laboratory of Neuroimaging and Genetics, and Mood and Motor Control Laboratory, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical SchoolBoston, MA, USA; MGH Center for Translational Research in Prescription Drug Abuse, Department of Anesthesia, Massachusetts General Hospital and Harvard Medical SchoolBoston, MA, USA; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood DisordersChicago, IL, USA
| | - Christopher L Plantz
- Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign Urbana, IL, USA
| | - Hao Ying
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA; Department of Electrical Engineering, Wayne State UniversityDetroit, MI, USA
| | - Myung J Lee
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of MedicineChicago, IL, USA; Laboratory of Neuroimaging and Genetics, and Mood and Motor Control Laboratory, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical SchoolBoston, MA, USA; MGH Center for Translational Research in Prescription Drug Abuse, Department of Anesthesia, Massachusetts General Hospital and Harvard Medical SchoolBoston, MA, USA; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood DisordersChicago, IL, USA
| | - Kalyan Raman
- Medill Integrated Marketing Communications, Northwestern UniversityEvanston, IL, USA; Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA
| | - Frank J Mulhern
- Medill Integrated Marketing Communications, Northwestern UniversityEvanston, IL, USA; Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA
| | - Martin P Block
- Medill Integrated Marketing Communications, Northwestern UniversityEvanston, IL, USA; Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA
| | - Bobby Calder
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA; Department of Marketing, Kellogg School of Management, Northwestern UniversityEvanston, IL, USA
| | - Sang Lee
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA; Laboratory of Neuroimaging and Genetics, and Mood and Motor Control Laboratory, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical SchoolBoston, MA, USA; MGH Center for Translational Research in Prescription Drug Abuse, Department of Anesthesia, Massachusetts General Hospital and Harvard Medical SchoolBoston, MA, USA; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood DisordersChicago, IL, USA
| | - Dale T Mortensen
- Department of Economics, Northwestern University College of Arts and Sciences Evanston, IL, USA
| | - Anne J Blood
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA; Laboratory of Neuroimaging and Genetics, and Mood and Motor Control Laboratory, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical SchoolBoston, MA, USA; MGH Center for Translational Research in Prescription Drug Abuse, Department of Anesthesia, Massachusetts General Hospital and Harvard Medical SchoolBoston, MA, USA; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood DisordersChicago, IL, USA
| | - Hans C Breiter
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern UniversityEvanston, IL, USA; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of MedicineChicago, IL, USA; Laboratory of Neuroimaging and Genetics, and Mood and Motor Control Laboratory, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical SchoolBoston, MA, USA; MGH Center for Translational Research in Prescription Drug Abuse, Department of Anesthesia, Massachusetts General Hospital and Harvard Medical SchoolBoston, MA, USA; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood DisordersChicago, IL, USA
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11
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Braeutigam S. Invited Frontiers Commentary. Tier Climbing Article: Redefining Neuromarketing as an Integrated Science of Influence. Front Neurosci 2017; 11:22. [PMID: 28184186 PMCID: PMC5266867 DOI: 10.3389/fnins.2017.00022] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Accepted: 01/11/2017] [Indexed: 11/20/2022] Open
Affiliation(s)
- Sven Braeutigam
- Department of Psychiatry, Oxford Centre for Human Brain Activity, University of Oxford Oxford, UK
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12
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Lee S, Lee MJ, Kim BW, Gilman JM, Kuster JK, Blood AJ, Kuhnen CM, Breiter HC. The Commonality of Loss Aversion across Procedures and Stimuli. PLoS One 2015; 10:e0135216. [PMID: 26394306 PMCID: PMC4579072 DOI: 10.1371/journal.pone.0135216] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2014] [Accepted: 07/20/2015] [Indexed: 11/27/2022] Open
Abstract
Individuals tend to give losses approximately 2-fold the weight that they give gains. Such approximations of loss aversion (LA) are almost always measured in the stimulus domain of money, rather than objects or pictures. Recent work on preference-based decision-making with a schedule-less keypress task (relative preference theory, RPT) has provided a mathematical formulation for LA similar to that in prospect theory (PT), but makes no parametric assumptions in the computation of LA, uses a variable tied to communication theory (i.e., the Shannon entropy or information), and works readily with non-monetary stimuli. We evaluated if these distinct frameworks described similar LA in healthy subjects, and found that LA during the anticipation phase of the PT-based task correlated significantly with LA related to the RPT-based task. Given the ease with which non-monetary stimuli can be used on the Internet, or in animal studies, these findings open an extensive range of applications for the study of loss aversion. Furthermore, the emergence of methodology that can be used to measure preference for both social stimuli and money brings a common framework to the evaluation of preference in both social psychology and behavioral economics.
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Affiliation(s)
- Sang Lee
- Warren Wright Adolescent Center, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America
- Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), Boston, MA, United States of America
- Massachusetts General Hospital and Northwestern University Phenotype Genotype Project in Addiction and Mood Disorders
| | - Myung J. Lee
- Warren Wright Adolescent Center, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America
- Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), Boston, MA, United States of America
- Massachusetts General Hospital and Northwestern University Phenotype Genotype Project in Addiction and Mood Disorders
| | - Byoung W. Kim
- Warren Wright Adolescent Center, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America
- Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), Boston, MA, United States of America
- Massachusetts General Hospital and Northwestern University Phenotype Genotype Project in Addiction and Mood Disorders
| | - Jodi M. Gilman
- Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), Boston, MA, United States of America
- Massachusetts General Hospital and Northwestern University Phenotype Genotype Project in Addiction and Mood Disorders
| | - John K. Kuster
- Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), Boston, MA, United States of America
- Mood and Motor Control Laboratory, MGH and HMS, Boston, MA, United States of America
- Massachusetts General Hospital and Northwestern University Phenotype Genotype Project in Addiction and Mood Disorders
| | - Anne J. Blood
- Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), Boston, MA, United States of America
- Mood and Motor Control Laboratory, MGH and HMS, Boston, MA, United States of America
- Massachusetts General Hospital and Northwestern University Phenotype Genotype Project in Addiction and Mood Disorders
| | - Camelia M. Kuhnen
- Kenan-Flagler Business School, University of North Carolina, Chapel Hill, NC, United States of America
| | - Hans C. Breiter
- Warren Wright Adolescent Center, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America
- Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital (MGH) and Harvard Medical School (HMS), Boston, MA, United States of America
- Mood and Motor Control Laboratory, MGH and HMS, Boston, MA, United States of America
- Massachusetts General Hospital and Northwestern University Phenotype Genotype Project in Addiction and Mood Disorders
- * E-mail:
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13
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From Affective Experience to Motivated Action: Tracking Reward-Seeking and Punishment-Avoidant Behaviour in Real-Life. PLoS One 2015; 10:e0129722. [PMID: 26087323 PMCID: PMC4472779 DOI: 10.1371/journal.pone.0129722] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2014] [Accepted: 05/12/2015] [Indexed: 01/08/2023] Open
Abstract
Many of the decisions and actions in everyday life result from implicit learning processes. Important to psychopathology are, for example, implicit reward-seeking and punishment-avoidant learning processes. It is known that when specific actions get associated with a rewarding experience, such as positive emotions, that this will increase the likelihood that an organism will engage in similar actions in the future. Similarly, when actions get associated with punishing experiences, such as negative emotions, this may reduce the likelihood that the organism will engage in similar actions in the future. This study examines whether we can observe these implicit processes prospectively in the flow of daily life. If such processes take place then we expect that current behaviour can be predicted by how similar behaviour was experienced (in terms of positive and negative affect) at previous measurement moments. This was examined in a sample of 621 female individuals that had participated in an Experience Sampling data collection. Measures of affect and behaviour were collected at 10 semi-random moments of the day for 5 consecutive days. It was examined whether affective experience that was paired with certain behaviours (physical activity and social context) at previous measurements modified the likelihood to show similar behaviours at next measurement moments. Analyses were performed both at the level of observations (a time scale with units of ± 90 min) and at day level (a time scale with units of 24 h). As expected, we found that affect indeed moderated the extent to which previous behaviour predicted similar behaviour later in time, at both beep- and day-level. This study showed that it is feasible to track reward-seeking and punishment-avoidant behaviour prospectively in humans in the flow of daily life. This opens up a new toolbox to examine processes determining goal-oriented behaviour in relation to psychopathology in humans.
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14
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Viswanathan V, Lee S, Gilman JM, Kim BW, Lee N, Chamberlain L, Livengood SL, Raman K, Lee MJ, Kuster J, Stern DB, Calder B, Mulhern FJ, Blood AJ, Breiter HC. Age-related striatal BOLD changes without changes in behavioral loss aversion. Front Hum Neurosci 2015; 9:176. [PMID: 25983682 PMCID: PMC4415398 DOI: 10.3389/fnhum.2015.00176] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2014] [Accepted: 03/15/2015] [Indexed: 12/21/2022] Open
Abstract
Loss aversion (LA), the idea that negative valuations have a higher psychological impact than positive ones, is considered an important variable in consumer research. The literature on aging and behavior suggests older individuals may show more LA, although it is not clear if this is an effect of aging in general (as in the continuum from age 20 and 50 years), or of the state of older age (e.g., past age 65 years). We also have not yet identified the potential biological effects of aging on the neural processing of LA. In the current study we used a cohort of subjects with a 30 year range of ages, and performed whole brain functional MRI (fMRI) to examine the ventral striatum/nucleus accumbens (VS/NAc) response during a passive viewing of affective faces with model-based fMRI analysis incorporating behavioral data from a validated approach/avoidance task with the same stimuli. Our a priori focus on the VS/NAc was based on (1) the VS/NAc being a central region for reward/aversion processing; (2) its activation to both positive and negative stimuli; (3) its reported involvement with tracking LA. LA from approach/avoidance to affective faces showed excellent fidelity to published measures of LA. Imaging results were then compared to the behavioral measure of LA using the same affective faces. Although there was no relationship between age and LA, we observed increasing neural differential sensitivity (NDS) of the VS/NAc to avoidance responses (negative valuations) relative to approach responses (positive valuations) with increasing age. These findings suggest that a central region for reward/aversion processing changes with age, and may require more activation to produce the same LA behavior as in younger individuals, consistent with the idea of neural efficiency observed with high IQ individuals showing less brain activation to complete the same task.
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Affiliation(s)
- Vijay Viswanathan
- Medill Integrated Marketing Communications, Northwestern University Evanston, IL, USA ; Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA
| | - Sang Lee
- Mood and Motor Control Laboratory or Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital Boston, MA, USA ; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA ; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood Disorders Chicago, IL, USA
| | - Jodi M Gilman
- Mood and Motor Control Laboratory or Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital Boston, MA, USA
| | - Byoung Woo Kim
- Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA ; Mood and Motor Control Laboratory or Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital Boston, MA, USA ; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA ; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood Disorders Chicago, IL, USA
| | - Nick Lee
- Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA ; Marketing Group, Aston Business School Birmingham, UK
| | - Laura Chamberlain
- Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA ; Marketing Group, Aston Business School Birmingham, UK
| | - Sherri L Livengood
- Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA ; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA
| | - Kalyan Raman
- Medill Integrated Marketing Communications, Northwestern University Evanston, IL, USA ; Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA ; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA ; Department of Marketing, Kellogg School of Management, Northwestern University Evanston, IL, USA
| | - Myung Joo Lee
- Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA ; Mood and Motor Control Laboratory or Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital Boston, MA, USA ; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA ; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood Disorders Chicago, IL, USA
| | - Jake Kuster
- Mood and Motor Control Laboratory or Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital Boston, MA, USA ; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood Disorders Chicago, IL, USA
| | - Daniel B Stern
- Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA ; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA
| | - Bobby Calder
- Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA ; Department of Marketing, Kellogg School of Management, Northwestern University Evanston, IL, USA
| | - Frank J Mulhern
- Medill Integrated Marketing Communications, Northwestern University Evanston, IL, USA ; Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA
| | - Anne J Blood
- Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA ; Mood and Motor Control Laboratory or Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital Boston, MA, USA ; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood Disorders Chicago, IL, USA
| | - Hans C Breiter
- Applied Neuromarketing Consortium: Northwestern University, Wayne State University, University of Michigan, Loughborough University School of Business and Economics (UK) and Massachusetts General Hospital/Harvard University Chicago, IL, USA ; Mood and Motor Control Laboratory or Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital Boston, MA, USA ; Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA ; Northwestern University and Massachusetts General Hospital Phenotype Genotype Project in Addiction and Mood Disorders Chicago, IL, USA
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15
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Breiter HC, Block M, Blood AJ, Calder B, Chamberlain L, Lee N, Livengood S, Mulhern FJ, Raman K, Schultz D, Stern DB, Viswanathan V, Zhang FZ. Redefining neuromarketing as an integrated science of influence. Front Hum Neurosci 2015; 8:1073. [PMID: 25709573 PMCID: PMC4325919 DOI: 10.3389/fnhum.2014.01073] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Accepted: 12/29/2014] [Indexed: 11/13/2022] Open
Abstract
Multiple transformative forces target marketing, many of which derive from new technologies that allow us to sample thinking in real time (i.e., brain imaging), or to look at large aggregations of decisions (i.e., big data). There has been an inclination to refer to the intersection of these technologies with the general topic of marketing as "neuromarketing". There has not been a serious effort to frame neuromarketing, which is the goal of this paper. Neuromarketing can be compared to neuroeconomics, wherein neuroeconomics is generally focused on how individuals make "choices", and represent distributions of choices. Neuromarketing, in contrast, focuses on how a distribution of choices can be shifted or "influenced", which can occur at multiple "scales" of behavior (e.g., individual, group, or market/society). Given influence can affect choice through many cognitive modalities, and not just that of valuation of choice options, a science of influence also implies a need to develop a model of cognitive function integrating attention, memory, and reward/aversion function. The paper concludes with a brief description of three domains of neuromarketing application for studying influence, and their caveats.
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Affiliation(s)
- Hans C Breiter
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA ; Mood and Motor Control Laboratory or Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital Boston, MA, USA ; Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA
| | - Martin Block
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA ; Medill Integrated Marketing Communications, Northwestern University Evanston, IL, USA
| | - Anne J Blood
- Mood and Motor Control Laboratory or Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital Boston, MA, USA ; Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA
| | - Bobby Calder
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA ; Department of Marketing, Kellogg School of Management, Northwestern University Evanston, IL, USA
| | - Laura Chamberlain
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA ; Aston Business School Birmingham, UK
| | - Nick Lee
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA ; School of Business and Economics, Loughborough University Leicestershire, UK
| | - Sherri Livengood
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA ; Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA
| | - Frank J Mulhern
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA ; Medill Integrated Marketing Communications, Northwestern University Evanston, IL, USA
| | - Kalyan Raman
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA ; Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA ; Medill Integrated Marketing Communications, Northwestern University Evanston, IL, USA
| | - Don Schultz
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA ; Medill Integrated Marketing Communications, Northwestern University Evanston, IL, USA
| | - Daniel B Stern
- Warren Wright Adolescent Center, Department of Psychiatry and Behavioral Science, Northwestern University Feinberg School of Medicine Chicago, IL, USA ; Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA
| | - Vijay Viswanathan
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA ; Medill Integrated Marketing Communications, Northwestern University Evanston, IL, USA
| | - Fengqing Zoe Zhang
- Applied Neuromarketing Consortium, Medill, Kellogg, and Feinberg Schools, Northwestern University Evanston, IL, USA ; Department of Statistics, Northwestern University Evanston, IL, USA ; Department of Psychology, Drexel University Philadelphia, PA, USA
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16
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Ågmo A, Smith AS, Birnie AK, French JA. Behavioral characteristics of pair bonding in the black tufted-ear marmoset ( Callithrix penicillata). BEHAVIOUR 2012; 149:407-440. [PMID: 30504964 PMCID: PMC6261535 DOI: 10.1163/156853912x638454] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
The present study describes how the development of a pair bond modifies social, sexual and aggressive behavior. Five heterosexual pairs of marmosets, previously unknown to each other, were formed at the beginning of the study. At the onset of pairing, social, sexual, exploratory and aggressive behaviors were recorded for 40 min. The animals were then observed for 20 min, both in the morning and afternoon for 21 days. The frequency and/or duration of behaviors recorded on Day 1 were compared to those recorded at later observations. The behavior displayed shortly after pairing should be completely unaffected by the pair bond, while such a bond should be present at later observations. Thus, it was possible to determine how the behavior between the pair was modified by the development of a pair bond. Social behaviors increased from Day 1 to Days 2-6 and all subsequent days observed. Conversely, other behaviors, such as open mouth displays (usually considered to be an invitation to sexual activity), had a high frequency during the early part of cohabitation but declined towards the end. Consequently, pair bonding manifests itself in an increased intensity of social behaviors. It is suggested that the intrinsically rewarding properties of grooming and perhaps other social behaviors turn the pair mate into a positive incentive, activating approach and further interactions when possible. Thus, the pair bond may be a motivational state activated by the conditioned incentive properties of the partner. This notion can explain all forms of pair bonds, including those occurring between individuals of the same sex and in promiscuous species.
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Affiliation(s)
- Anders Ågmo
- Department of Psychology, University of Tromsø, Tromsø, Norway
| | - Adam S. Smith
- Department of Psychology and Program in Neuroscience, Florida State University, Tallahassee, FL, USA
| | - Andrew K. Birnie
- Department of Psychology and Callitrichid Research Facility, University of Nebraska at Omaha, Omaha, NE, USA
| | - Jeffrey A. French
- Department of Psychology and Callitrichid Research Facility, University of Nebraska at Omaha, Omaha, NE, USA
- Department of Biology, University of Nebraska at Omaha, Omaha, NE, USA
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Blood AJ, Iosifescu DV, Makris N, Perlis RH, Kennedy DN, Dougherty DD, Kim BW, Lee MJ, Wu S, Lee S, Calhoun J, Hodge SM, Fava M, Rosen BR, Smoller JW, Gasic GP, Breiter HC. Microstructural abnormalities in subcortical reward circuitry of subjects with major depressive disorder. PLoS One 2010; 5:e13945. [PMID: 21124764 PMCID: PMC2993928 DOI: 10.1371/journal.pone.0013945] [Citation(s) in RCA: 104] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2010] [Accepted: 09/16/2010] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Previous studies of major depressive disorder (MDD) have focused on abnormalities in the prefrontal cortex and medial temporal regions. There has been little investigation in MDD of midbrain and subcortical regions central to reward/aversion function, such as the ventral tegmental area/substantia nigra (VTA/SN), and medial forebrain bundle (MFB). METHODOLOGY/PRINCIPAL FINDINGS We investigated the microstructural integrity of this circuitry using diffusion tensor imaging (DTI) in 22 MDD subjects and compared them with 22 matched healthy control subjects. Fractional anisotropy (FA) values were increased in the right VT and reduced in dorsolateral prefrontal white matter in MDD subjects. Follow-up analysis suggested two distinct subgroups of MDD patients, which exhibited non-overlapping abnormalities in reward/aversion circuitry. The MDD subgroup with abnormal FA values in VT exhibited significantly greater trait anxiety than the subgroup with normal FA values in VT, but the subgroups did not differ in levels of anhedonia, sadness, or overall depression severity. CONCLUSIONS/SIGNIFICANCE These findings suggest that MDD may be associated with abnormal microstructure in brain reward/aversion regions, and that there may be at least two subtypes of microstructural abnormalities which each impact core symptoms of depression.
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Affiliation(s)
- Anne J. Blood
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Motivation and Emotion Neuroscience Collaboration (MENC) and Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Dan V. Iosifescu
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Mount Sinai School of Medicine, New York, New York, United States of America
| | - Nikos Makris
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Morphometric Analysis and Center for Integrative Informatics, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Roy H. Perlis
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Psychiatric and Neurodevelopmental Genetics Unit and Center for Human Genetic Research, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - David N. Kennedy
- Center for Morphometric Analysis and Center for Integrative Informatics, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Darin D. Dougherty
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Byoung Woo Kim
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Motivation and Emotion Neuroscience Collaboration (MENC) and Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Myung Joo Lee
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Motivation and Emotion Neuroscience Collaboration (MENC) and Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Shirley Wu
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Sang Lee
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Motivation and Emotion Neuroscience Collaboration (MENC) and Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Jesse Calhoun
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Motivation and Emotion Neuroscience Collaboration (MENC) and Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Steven M. Hodge
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Motivation and Emotion Neuroscience Collaboration (MENC) and Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Morphometric Analysis and Center for Integrative Informatics, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Maurizio Fava
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Psychiatric and Neurodevelopmental Genetics Unit and Center for Human Genetic Research, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Bruce R. Rosen
- Motivation and Emotion Neuroscience Collaboration (MENC) and Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Jordan W. Smoller
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Psychiatric and Neurodevelopmental Genetics Unit and Center for Human Genetic Research, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Gregory P. Gasic
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Motivation and Emotion Neuroscience Collaboration (MENC) and Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Hans C. Breiter
- Depression Clinic and Research Program, Mood and Motor Control Laboratory, Addiction Research Program, Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Motivation and Emotion Neuroscience Collaboration (MENC) and Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
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