Browsing by Author "Hula, Andreas"
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- A machine-learning approach for differentiating borderline personality disorder from community participants with brain-wide functional connectivityLahnakoski, Juha M.; Nolte, Tobias; Solway, Alec; Vilares, Iris; Hula, Andreas; Feigenbaum, Janet; Lohrenz, Terry; Casas, Brooks; Fonagy, Peter; Montague, P. Read; Schilbach, Leonhard (Elsevier, 2024-05-26)Background: Functional connectivity has garnered interest as a potential biomarker of psychiatric disorders including borderline personality disorder (BPD). However, small sample sizes and lack of within-study replications have led to divergent findings with no clear spatial foci. Aims: Evaluate discriminative performance and generalizability of functional connectivity markers for BPD. Method: Whole-brain fMRI resting state functional connectivity in matched subsamples of 116 BPD and 72 control individuals defined by three grouping strategies. We predicted BPD status using classifiers with repeated cross-validation based on multiscale functional connectivity within and between regions of interest (ROIs) covering the whole brain—global ROI-based network, seed-based ROI-connectivity, functional consistency, and voxel-to-voxel connectivity—and evaluated the generalizability of the classification in the left-out portion of non-matched data. Results: Full-brain connectivity allowed classification (∼70 %) of BPD patients vs. controls in matched inner cross-validation. The classification remained significant when applied to unmatched out-of-sample data (∼61–70 %). Highest seed-based accuracies were in a similar range to global accuracies (∼70–75 %), but spatially more specific. The most discriminative seed regions included midline, temporal and somatomotor regions. Univariate connectivity values were not predictive of BPD after multiple comparison corrections, but weak local effects coincided with the most discriminative seed-ROIs. Highest accuracies were achieved with a full clinical interview while self-report results remained at chance level. Limitations: The accuracies vary considerably between random sub-samples of the population, global signal and covariates limiting the practical applicability. Conclusions: Spatially distributed functional connectivity patterns are moderately predictive of BPD despite heterogeneity of the patient population.
- Early childhood investment impacts social decision-making four decades laterLuo, 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.
- A model of risk and mental state shifts during social interactionHula, 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.
- Monte Carlo Planning Method Estimates Planning Horizons during Interactive Social ExchangeHula, 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.
- Multi-Round Trust Game Quantifies Inter-Individual Differences in Social Exchange from Adolescence to AdulthoodHula, Andreas; Moutoussis, Michael; Will, Geert-Jan; Kokorikou, Danae; Reiter, Andrea M.; Ziegler, Gabriel; NSPN Consortium; Bullmore, Ed; Jones, Peter B.; Goodyer, Ian; Fonagy, Peter; Montague, P. Read; Dolan, Raymond J. (Ubiquity Press, 2021-10)Investing in strangers in a socio-economic exchange is risky, as we may be uncertain whether they will reciprocate. Nevertheless, the potential rewards for cooperating can be great. Here, we used a cross sectional sample (n = 784) to study how the challenges of cooperation versus defection are negotiated across an important period of the lifespan: from adolescence to young adulthood (ages 14 to 25). We quantified social behaviour using a multi round investor-trustee task, phenotyping individuals using a validated model whose parameters characterise patterns of real exchange and constitute latent social characteristics. We found highly significant differences in investment behaviour according to age, sex, socio-economic status and IQ. Consistent with the literature, we showed an overall trend towards higher trust from adolescence to young adulthood but, in a novel finding, we characterized key cognitive mechanisms explaining this, especially regarding socio-economic risk aversion. Males showed lower risk-aversion, associated with greater investments. We also found that inequality aversion was higher in females and, in a novel relation, that socio-economic deprivation was associated with more risk averse play.
- Necessary, Yet Dissociable Contributions of the Insular and Ventromedial Prefrontal Cortices to Norm Adaptation: Computational and Lesion Evidence in HumansGu, 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.