1
|
Gu X, Banker S, Schafer M, Harrington M, Na S, Barkley S, Trayvick J, Peters A, Thinakaran A, Foss-Feig J, Schiller D. Phenotypical divergence between self-reported and clinically ascertained autism. RESEARCH SQUARE 2024:rs.3.rs-4314472. [PMID: 38766168 PMCID: PMC11100871 DOI: 10.21203/rs.3.rs-4314472/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
While allowing for rapid recruitment of large samples, online psychiatric and neurodevelopmental research relies heavily on participants' self-report of neuropsychiatric symptoms, foregoing the rigorous clinical characterization of laboratory settings. Autism spectrum disorder (ASD) research is one example where the clinical validity of such an approach remains elusive. Here, we compared participants characterized online via self-reports against in-person participants evaluated by clinicians. Despite having comparable self-reported autism symptoms, the online high-trait group reported significantly more social anxiety and avoidant behavior than in-person ASD subjects. Within the in-person sample, there was no relationship between self-rated and clinician-rated autism symptoms, suggesting these approaches may capture different aspects of ASD. The online high-trait and in-person ASD participants also differed in their behavior in well-validated social decision-making tasks: the in-person group perceived having less social control and acted less affiliative towards virtual characters. Our study aimed to draw comparisons at three levels: methodological platform (online versus in-person), symptom measurement (self- versus clinician-report), and social behavior. We identified a lack of agreement between self- and clinician-rated measures of symptoms and divergent social tendencies in groups ascertained by each method, highlighting the need for differentiation between in-person versus online samples in autism research.
Collapse
Affiliation(s)
- Xiaosi Gu
- Icahn School of Medicine at Mount Sinai
| | | | | | | | - Soojung Na
- Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai
| | | | | | | | | | | | | |
Collapse
|
2
|
Batten SR, Bang D, Kopell BH, Davis AN, Heflin M, Fu Q, Perl O, Ziafat K, Hashemi A, Saez I, Barbosa LS, Twomey T, Lohrenz T, White JP, Dayan P, Charney AW, Figee M, Mayberg HS, Kishida KT, Gu X, Montague PR. Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchange. Nat Hum Behav 2024; 8:718-728. [PMID: 38409356 PMCID: PMC11045309 DOI: 10.1038/s41562-024-01831-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 01/16/2024] [Indexed: 02/28/2024]
Abstract
Dopamine and serotonin are hypothesized to guide social behaviours. In humans, however, we have not yet been able to study neuromodulator dynamics as social interaction unfolds. Here, we obtained subsecond estimates of dopamine and serotonin from human substantia nigra pars reticulata during the ultimatum game. Participants, who were patients with Parkinson's disease undergoing awake brain surgery, had to accept or reject monetary offers of varying fairness from human and computer players. They rejected more offers in the human than the computer condition, an effect of social context associated with higher overall levels of dopamine but not serotonin. Regardless of the social context, relative changes in dopamine tracked trial-by-trial changes in offer value-akin to reward prediction errors-whereas serotonin tracked the current offer value. These results show that dopamine and serotonin fluctuations in one of the basal ganglia's main output structures reflect distinct social context and value signals.
Collapse
Affiliation(s)
- Seth R Batten
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA.
| | - Dan Bang
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA.
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
- Department of Experimental Psychology, University of Oxford, Oxford, UK.
| | - Brian H Kopell
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Neuromodulation, Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Arianna N Davis
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Matthew Heflin
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Qixiu Fu
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ofer Perl
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kimia Ziafat
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alice Hashemi
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ignacio Saez
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Leonardo S Barbosa
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA
| | - Thomas Twomey
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA
| | - Terry Lohrenz
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA
| | - Jason P White
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA
| | - Peter Dayan
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- University of Tübingen, Tübingen, Germany
| | - Alexander W Charney
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Martijn Figee
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Neuromodulation, Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Helen S Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Neuromodulation, Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kenneth T Kishida
- Department of Translational Neuroscience, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Neurosurgery, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Xiaosi Gu
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - P Read Montague
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
- Department of Physics, Virginia Tech, Blacksburg, VA, USA.
| |
Collapse
|
3
|
Wise T, Emery K, Radulescu A. Naturalistic reinforcement learning. Trends Cogn Sci 2024; 28:144-158. [PMID: 37777463 PMCID: PMC10878983 DOI: 10.1016/j.tics.2023.08.016] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 10/02/2023]
Abstract
Humans possess a remarkable ability to make decisions within real-world environments that are expansive, complex, and multidimensional. Human cognitive computational neuroscience has sought to exploit reinforcement learning (RL) as a framework within which to explain human decision-making, often focusing on constrained, artificial experimental tasks. In this article, we review recent efforts that use naturalistic approaches to determine how humans make decisions in complex environments that better approximate the real world, providing a clearer picture of how humans navigate the challenges posed by real-world decisions. These studies purposely embed elements of naturalistic complexity within experimental paradigms, rather than focusing on simplification, generating insights into the processes that likely underpin humans' ability to navigate complex, multidimensional real-world environments so successfully.
Collapse
Affiliation(s)
- Toby Wise
- Department of Neuroimaging, King's College London, London, UK.
| | - Kara Emery
- Center for Data Science, New York University, New York, NY, USA
| | - Angela Radulescu
- Center for Computational Psychiatry, Icahn School of Medicine at Mt. Sinai, New York, NY, USA
| |
Collapse
|
4
|
Gu X, McLaughlin C, Fu Q, Na S, Heflin M, Fiore V. Aberrant neural computation of social controllability in nicotine-dependent humans. RESEARCH SQUARE 2024:rs.3.rs-3854519. [PMID: 38343814 PMCID: PMC10854308 DOI: 10.21203/rs.3.rs-3854519/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Social controllability, defined as the ability to exert influence when interacting with others, is crucial for optimal decision-making. Inability to do so might contribute to maladaptive behaviors such as drug use, which often takes place in social settings. Here, we examined nicotine-dependent humans using fMRI, as they made choices that could influence the proposals from simulated partners. Computational modeling revealed that smokers under-estimated the influence of their actions and self-reported a reduced sense of control, compared to non-smokers. These findings were replicated in a large independent sample of participants recruited online. Neurally, smokers showed reduced tracking of forward projected choice values in the ventromedial prefrontal cortex, and impaired computation of social prediction errors in the midbrain. These results demonstrate that smokers were less accurate in estimating their personal influence when the social environment calls for control, providing a neurocomputational account for the social cognitive deficits in this population.
Collapse
Affiliation(s)
- Xiaosi Gu
- Icahn School of Medicine at Mount Sinai
| | | | | | | | | | | |
Collapse
|
5
|
Wise T, Charpentier CJ, Dayan P, Mobbs D. Interactive cognitive maps support flexible behavior under threat. Cell Rep 2023; 42:113008. [PMID: 37610871 PMCID: PMC10658881 DOI: 10.1016/j.celrep.2023.113008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 07/11/2023] [Accepted: 08/03/2023] [Indexed: 08/25/2023] Open
Abstract
In social environments, survival can depend upon inferring and adapting to other agents' goal-directed behavior. However, it remains unclear how humans achieve this, despite the fact that many decisions must account for complex, dynamic agents acting according to their own goals. Here, we use a predator-prey task (total n = 510) to demonstrate that humans exploit an interactive cognitive map of the social environment to infer other agents' preferences and simulate their future behavior, providing for flexible, generalizable responses. A model-based inverse reinforcement learning model explained participants' inferences about threatening agents' preferences, with participants using this inferred knowledge to enact generalizable, model-based behavioral responses. Using tree-search planning models, we then found that behavior was best explained by a planning algorithm that incorporated simulations of the threat's goal-directed behavior. Our results indicate that humans use a cognitive map to determine other agents' preferences, facilitating generalized predictions of their behavior and effective responses.
Collapse
Affiliation(s)
- Toby Wise
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Department of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA.
| | - Caroline J Charpentier
- Department of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA; Department of Psychology, University of Maryland, College Park, MD, USA; Brain and Behavior Institute, University of Maryland, College Park, MD, USA
| | - Peter Dayan
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany; University of Tübingen, Tübingen, Germany
| | - Dean Mobbs
- Department of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA; Computation and Neural Systems Program, California Institute of Technology, Pasadena, CA, USA
| |
Collapse
|
6
|
Saez I, Gu X. Invasive Computational Psychiatry. Biol Psychiatry 2023; 93:661-670. [PMID: 36641365 PMCID: PMC10038930 DOI: 10.1016/j.biopsych.2022.09.032] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 08/25/2022] [Accepted: 09/27/2022] [Indexed: 01/16/2023]
Abstract
Computational psychiatry, a relatively new yet prolific field that aims to understand psychiatric disorders with formal theories about the brain, has seen tremendous growth in the past decade. Despite initial excitement, actual progress made by computational psychiatry seems stagnant. Meanwhile, understanding of the human brain has benefited tremendously from recent progress in intracranial neuroscience. Specifically, invasive techniques such as stereotactic electroencephalography, electrocorticography, and deep brain stimulation have provided a unique opportunity to precisely measure and causally modulate neurophysiological activity in the living human brain. In this review, we summarize progress and drawbacks in both computational psychiatry and invasive electrophysiology and propose that their combination presents a highly promising new direction-invasive computational psychiatry. The value of this approach is at least twofold. First, it advances our mechanistic understanding of the neural computations of mental states by providing a spatiotemporally precise depiction of neural activity that is traditionally unattainable using noninvasive techniques with human subjects. Second, it offers a direct and immediate way to modulate brain states through stimulation of algorithmically defined neural regions and circuits (i.e., algorithmic targeting), thus providing both causal and therapeutic insights. We then present depression as a use case where the combination of computational and invasive approaches has already shown initial success. We conclude by outlining future directions as a road map for this exciting new field as well as presenting cautions about issues such as ethical concerns and generalizability of findings.
Collapse
Affiliation(s)
- Ignacio Saez
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York.
| | - Xiaosi Gu
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York.
| |
Collapse
|
7
|
Ogawa A, Asano S, Osada T, Tanaka M, Tochigi R, Kamagata K, Aoki S, Konishi S. Role of right temporoparietal junction for counterfactual evaluation of partner's decision in ultimatum game. Cereb Cortex 2023; 33:2947-2957. [PMID: 35718541 PMCID: PMC10016052 DOI: 10.1093/cercor/bhac252] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 05/27/2022] [Accepted: 05/30/2022] [Indexed: 11/14/2022] Open
Abstract
Humans assess the distributions of resources based on their aversion to unfairness. If a partner distributes in an unfair manner even though the partner had a less unfair distribution option, a recipient will believe that the partner should have chosen the counterfactual option. In this study, we investigated the neural basis for fairness evaluation of actual and counterfactual options in the ultimatum game. In this task, a partner chose one distribution option out of two options, and a participant accepted or rejected the option. The behavioral results showed that the acceptance rate was influenced by counterfactual evaluation (CE), among others, as defined by the difference of monetary amount between the actual and counterfactual options. The functional magnetic resonance imaging results showed that CE was associated with the right ventral angular gyrus (vAG) that provided one of convergent inputs to the supramarginal gyrus related to decision utility, which reflects gross preferences for the distribution options. Furthermore, inhibitory repetitive transcranial magnetic stimulation administered to the right vAG reduced the behavioral component associated with CE. These results suggest that our acceptance/rejection of distribution options relies on multiple processes (monetary amount, disadvantageous inequity, and CE) and that the right vAG causally contributes to CE.
Collapse
Affiliation(s)
| | - Saki Asano
- Department of Neurophysiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Takahiro Osada
- Department of Neurophysiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Masaki Tanaka
- Department of Neurophysiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Reia Tochigi
- Department of Neurophysiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Seiki Konishi
- Department of Neurophysiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| |
Collapse
|
8
|
Barnby JM, Dayan P, Bell V. Formalising social representation to explain psychiatric symptoms. Trends Cogn Sci 2023; 27:317-332. [PMID: 36609016 DOI: 10.1016/j.tics.2022.12.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 12/09/2022] [Accepted: 12/13/2022] [Indexed: 01/06/2023]
Abstract
Recent work in social cognition has moved beyond a focus on how people process social rewards to examine how healthy people represent other agents and how this is altered in psychiatric disorders. However, formal modelling of social representation has not kept pace with these changes, impeding our understanding of how core aspects of social cognition function, and fail, in psychopathology. Here, we suggest that belief-based computational models provide a basis for an integrated sociocognitive approach to psychiatry, with the potential to address important but unexamined pathologies of social representation, such as maladaptive schemas and illusory social agents.
Collapse
Affiliation(s)
- Joseph M Barnby
- Social Computation and Cognitive Representation Lab, Department of Psychology, Royal Holloway, University of London, Egham TW20 0EX, UK.
| | - Peter Dayan
- Max Planck Institute for Biological Cybernetics, Tübingen, 72076, Germany; University of Tübingen, Tübingen, 72074, Germany
| | - Vaughan Bell
- Clinical, Educational, and Health Psychology, University College London, London WC1E 7HB, UK; South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
| |
Collapse
|
9
|
Banker SM, Na S, Beltrán J, Koenigsberg HW, Foss-Feig JH, Gu X, Schiller D. Disrupted computations of social control in individuals with obsessive-compulsive and misophonia symptoms. iScience 2022; 25:104617. [PMID: 35800773 PMCID: PMC9253698 DOI: 10.1016/j.isci.2022.104617] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 05/05/2022] [Accepted: 06/10/2022] [Indexed: 11/28/2022] Open
Affiliation(s)
- Sarah M. Banker
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10027, USA
| | - Soojung Na
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10027, USA
| | - Jacqueline Beltrán
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Harold W. Koenigsberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Jennifer H. Foss-Feig
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Xiaosi Gu
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10027, USA
- Corresponding author
| | - Daniela Schiller
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10027, USA
- Corresponding author
| |
Collapse
|
10
|
Cao S, Liu X, Wu H. The neural mechanisms underlying effort process modulated by efficacy. Neuropsychologia 2022; 173:108314. [DOI: 10.1016/j.neuropsychologia.2022.108314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 06/29/2022] [Accepted: 06/30/2022] [Indexed: 11/26/2022]
|
11
|
Na S, Blackmore S, Chung D, O’Brien M, Banker S, Heflin M, Fiore VG, Gu X. Computational mechanisms underlying illusion of control in delusional individuals. Schizophr Res 2022; 245:50-58. [PMID: 35177284 PMCID: PMC9232936 DOI: 10.1016/j.schres.2022.01.054] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 01/24/2022] [Accepted: 01/25/2022] [Indexed: 10/19/2022]
Abstract
Humans navigate complex situations that require the accurate estimation of the controllability of the environment. Aberrant controllability computation might lead to maladaptive behaviors and poor mental health outcomes. Illusion of control, which refers to a heightened sense of control while the environment is uncontrollable, is one such manifestation and has been conceptually associated with delusional ideation. Nevertheless, this association has not yet been formally characterized in a computational framework. To address this, we used a computational psychiatry approach to quantify illusion of control in human participants with high (n = 125) or low (n = 126) trait delusion. Participants played a two-party exchange game in which their choices either did ("Controllable condition") or did not ("Uncontrollable condition") influence the future monetary offers made by simulated partners. We found that the two groups behaved similarly in model-agnostic measures (i.e., offer size, rejection rate). However, computational modeling revealed that compared to the low trait delusion group, the high delusion group overestimated their influence ("expected influence" parameter) over the offers made by their partners under the Uncontrollable condition. Highly delusional individuals also reported a stronger sense of control than those with low trait delusion in the Uncontrollable condition. Furthermore, the expected influence parameter and self-reported beliefs about controllability were significantly correlated in the Controllable condition in individuals with low trait delusion, whereas this relationship was diminished in those with high trait delusion. Collectively, these findings demonstrate that delusional ideation is associated with aberrant computation of and belief about environmental controllability, as well as a belief-behavior disconnect.
Collapse
Affiliation(s)
- Soojung Na
- Nash Family Department of Neuroscience, Icahn School of
Medicine at Mount Sinai,Department of Psychiatry, Icahn School of Medicine at
Mount Sinai
| | | | | | - Madeline O’Brien
- Nash Family Department of Neuroscience, Icahn School of
Medicine at Mount Sinai,Department of Psychiatry, Icahn School of Medicine at
Mount Sinai,Center for Computational Psychiatry, Icahn School of
Medicine at Mount Sinai
| | - Sarah Banker
- Nash Family Department of Neuroscience, Icahn School of
Medicine at Mount Sinai,Department of Psychiatry, Icahn School of Medicine at
Mount Sinai,Center for Computational Psychiatry, Icahn School of
Medicine at Mount Sinai
| | - Matthew Heflin
- Department of Psychiatry, Icahn School of Medicine at
Mount Sinai,Center for Computational Psychiatry, Icahn School of
Medicine at Mount Sinai
| | - Vincenzo G. Fiore
- Department of Psychiatry, Icahn School of Medicine at
Mount Sinai,Center for Computational Psychiatry, Icahn School of
Medicine at Mount Sinai
| | - Xiaosi Gu
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, United States of America; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, United States of America; Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, United States of America.
| |
Collapse
|
12
|
Klein-Flügge MC, Bongioanni A, Rushworth MFS. Medial and orbital frontal cortex in decision-making and flexible behavior. Neuron 2022; 110:2743-2770. [PMID: 35705077 DOI: 10.1016/j.neuron.2022.05.022] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/17/2022] [Accepted: 05/19/2022] [Indexed: 11/15/2022]
Abstract
The medial frontal cortex and adjacent orbitofrontal cortex have been the focus of investigations of decision-making, behavioral flexibility, and social behavior. We review studies conducted in humans, macaques, and rodents and argue that several regions with different functional roles can be identified in the dorsal anterior cingulate cortex, perigenual anterior cingulate cortex, anterior medial frontal cortex, ventromedial prefrontal cortex, and medial and lateral parts of the orbitofrontal cortex. There is increasing evidence that the manner in which these areas represent the value of the environment and specific choices is different from subcortical brain regions and more complex than previously thought. Although activity in some regions reflects distributions of reward and opportunities across the environment, in other cases, activity reflects the structural relationships between features of the environment that animals can use to infer what decision to take even if they have not encountered identical opportunities in the past.
Collapse
Affiliation(s)
- Miriam C Klein-Flügge
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3TA, UK; Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Nuffield Department of Clinical Neurosciences, Level 6, West Wing, John Radcliffe Hospital, Oxford OX3 9DU, UK; Department of Psychiatry, University of Oxford, Warneford Lane, Headington, Oxford OX3 7JX, UK.
| | - Alessandro Bongioanni
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3TA, UK
| | - Matthew F S Rushworth
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3TA, UK; Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Nuffield Department of Clinical Neurosciences, Level 6, West Wing, John Radcliffe Hospital, Oxford OX3 9DU, UK
| |
Collapse
|
13
|
Hwang M, Kim SP, Chung D. Exploring the impacts of implicit context association and arithmetic booster in impulsivity reduction. Front Psychiatry 2022; 13:961484. [PMID: 36177221 PMCID: PMC9513136 DOI: 10.3389/fpsyt.2022.961484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 08/22/2022] [Indexed: 12/02/2022] Open
Abstract
People have a higher preference for immediate over delayed rewards, and it is suggested that such an impulsive tendency is governed by one's ability to simulate future rewards. Consistent with this view, recent studies have shown that enforcing individuals to focus on episodic future thoughts reduces their impulsivity. Inspired by these reports, we hypothesized that administration of a simple cognitive task linked to future thinking might effectively modulate individuals' delay discounting. Specifically, we used one associative memory task targeting intervention of context information, and one working memory task targeting enhancement of individual's ability to construct a coherent future event. To measure whether each type of cognitive task reduces individuals' impulsivity, a classic intertemporal choice task was used to quantify individuals' baseline and post-intervention impulsivity. Across two experiments and data from 216 healthy young adult participants, we observed that the impacts of intervention tasks were inconsistent. Still, we observed a significant task repetition effect such that the participants showed more patient choices in the second impulsivity assessment. In conclusion, there was no clear evidence supporting that our suggested intervention tasks reduce individuals' impulsivity, and that the current results call attention to the importance of taking into account task repetition effects in studying the impacts of cognitive training and intervention.
Collapse
Affiliation(s)
- Minho Hwang
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| | - Dongil Chung
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
| |
Collapse
|