Browsing by Author "Dayan, Peter"

Now showing 1 - 6 of 6
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    Computational Phenotyping of Two-Person Interactions Reveals Differential Neural Response to Depth-of-Thought
    Xiang, Ting; Ray, Debajyoti; Lohrenz, Terry; Dayan, Peter; Montague, P. Read (Public Library of Science, 2012-12-27)
    Reciprocating exchange with other humans requires individuals to infer the intentions of their partners. Despite the importance of this ability in healthy cognition and its impact in disease, the dimensions employed and computations involved in such inferences are not clear. We used a computational theory-of-mind model to classify styles of interaction in 195 pairs of subjects playing a multi-round economic exchange game. This classification produces an estimate of a subject's depth-of-thought in the game (low, medium, high), a parameter that governs the richness of the models they build of their partner. Subjects in each category showed distinct neural correlates of learning signals associated with different depths-of-thought. The model also detected differences in depth-of-thought between two groups of healthy subjects: one playing patients with psychiatric disease and the other playing healthy controls. The neural response categories identified by this computational characterization of theory-of-mind may yield objective biomarkers useful in the identification and characterization of pathologies that perturb the capacity to model and interact with other humans.
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    Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchange
    Batten, Seth R.; Bang, Dan; Kopell, Brian H.; Davis, Arianna N.; Heflin, Matthew; Fu, Qixiu; Perl, Ofer; Ziafa, Kimia; Hashemi, Alice; Saez, Ignacio; Barbosa, Leonardo S.; Twomey, Thomas; Lohrenz, Terry; White, Jason P.; Dayan, Peter; Charney, Alexander W.; Figee, Martijn; Mayberg, Helen S.; Kishida, Kenneth T.; Gu, Xiaosi; Montague, P. Read (Nature Research, 2024-02-26)
    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.
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    Early childhood investment impacts social decision-making four decades later
    Luo, Yi; Hétu, Sébastien; Lohrenz, Terry; Hula, Andreas; Dayan, Peter; Ramey, Sharon L.; Sonnier-Netto, Mary Elizabeth; Lisinski, Jonathan; LaConte, Stephen M.; Nolte, Tobias; Fonagy, Peter; Rahmani, Elham; Montague, P. Read; Ramey, Craig T. (Nature Research, 2018-11-20)
    Early childhood educational investment produces positive effects on cognitive and non-cognitive skills, health, and socio-economic success. However, the effects of such interventions on social decision-making later in life are unknown. We recalled participants from one of the oldest randomized controlled studies of early childhood investment—the Abecedarian Project (ABC)—to participate in well-validated interactive economic games that probe social norm enforcement and planning. We show that in a repeated-play ultimatum game, ABC participants who received high-quality early interventions strongly reject unequal division of money across players (disadvantageous or advantageous) even at significant cost to themselves. Using a multi-round trust game and computational modeling of social exchange, we show that the same intervention participants also plan further into the future. These findings suggest that high quality early childhood investment can result in long-term changes in social decision-making and promote social norm enforcement in order to reap future benefits.
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    A model of risk and mental state shifts during social interaction
    Hula, Andreas; Vilares, Iris; Lohrenz, Terry; Dayan, Peter; Montague, P. Read (PLOS, 2018-02-15)
    Cooperation and competition between human players in repeated microeconomic games offer a window onto social phenomena such as the establishment, breakdown and repair of trust. However, although a suitable starting point for the quantitative analysis of such games exists, namely the Interactive Partially Observable Markov Decision Process (I-POMDP), computational considerations and structural limitations have limited its application, and left unmodelled critical features of behavior in a canonical trust task. Here, we provide the first analysis of two central phenomena: a form of social risk-aversion exhibited by the player who is in control of the interaction in the game; and irritation or anger, potentially exhibited by both players. Irritation arises when partners apparently defect, and it potentially causes a precipitate breakdown in cooperation. Failing to model one's partner's propensity for it leads to substantial economic inefficiency. We illustrate these behaviours using evidence drawn from the play of large cohorts of healthy volunteers and patients. We show that for both cohorts, a particular subtype of player is largely responsible for the breakdown of trust, a finding which sheds new light on borderline personality disorder.
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    Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social Exchange
    Hula, Andreas; Montague, P. Read; Dayan, Peter (PLOS, 2015-06)
    Reciprocating interactions represent a central feature of all human exchanges. They have been the target of various recent experiments, with healthy participants and psychiatric populations engaging as dyads in multi-round exchanges such as a repeated trust task. Behaviour in such exchanges involves complexities related to each agent's preference for equity with their partner, beliefs about the partner's appetite for equity, beliefs about the partner's model of their partner, and so on. Agents may also plan different numbers of steps into the future. Providing a computationally precise account of the behaviour is an essential step towards understanding what underlies choices. A natural framework for this is that of an interactive partially observable Markov decision process (IPOMDP). However, the various complexities make IPOMDPs inordinately computationally challenging. Here, we show how to approximate the solution for the multi-round trust task using a variant of the Monte-Carlo tree search algorithm. We demonstrate that the algorithm is efficient and effective, and therefore can be used to invert observations of behavioural choices. We use generated behaviour to elucidate the richness and sophistication of interactive inference.
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    Necessary, Yet Dissociable Contributions of the Insular and Ventromedial Prefrontal Cortices to Norm Adaptation: Computational and Lesion Evidence in Humans
    Gu, Xiaosi; Wang, Xingchao; Hula, Andreas; Wang, Shiwei; Xu, Shuai; Lohrenz, Terry; Knight, Robert T.; Gao, Zhixian; Dayan, Peter; Montague, P. Read (Society for Neuroscience, 2015-01-14)
    Social norms and their enforcement are fundamental to human societies. The ability to detect deviations from norms and to adapt to norms in a changing environment is therefore important to individuals’ normal social functioning. Previous neuroimaging studies have highlighted the involvement of the insular and ventromedial prefrontal (vmPFC) cortices in representing norms. However, the necessity and dissociability of their involvement remain unclear. Using model-based computational modeling and neuropsychological lesion approaches,weexamined the contributions of the insula andvmPFCtonormadaptation in sevenhumanpatients with focal insula lesions and six patients with focal vmPFC lesions, in comparison with forty neurologically intact controls and six brain-damaged controls. There were three computational signals of interest as participants played a fairness game (ultimatum game): sensitivity to the fairness of offers, sensitivity to deviations from expected norms, and the speed at which people adapt to norms. Significant group differences were assessed using bootstrapping methods. Patients with insula lesions displayed abnormally low adaptation speed to norms, yet detected norm violations with greater sensitivity than controls. Patients with vmPFC lesions did not have such abnormalities, but displayed reduced sensitivity to fairness and were more likely to accept the most unfair offers. These findings provide compelling computational and lesion evidence supporting the necessary, yet dissociable roles of the insula and vmPFC in norm adaptation in humans: the insula is critical for learning to adapt when reality deviates from norm expectations, and that the vmPFC is important for valuation of fairness during social exchange.