Biology subjects

Bahrami, B.

Publications and source records attributed to Bahrami, B..

10 recordsLinked to original sources

bioRxiv2026

Confidence Read from Others Movements Guides Collective Decisions

A central challenge in decision-making is deciding when to trust ones own judgement and when to rely on others. Because subjective confidence correlates with objective accuracy, a sensible strategy is to follow the choice made with higher confidence. Crucially, however, this strategy depends on accessing others confidence. Here, we show that humans spontaneously read out confidence from others movements and use this information to guide collective decisions. Dyads performed a collective perceptual decision-making task. In each trial, one participant--the arbitrator--first made an individual decision by reaching toward one of two targets, then observed their partner doing the same, and finally made the collective decision on behalf of the dyad, confirming or revising their initial choice. When own confidence was low or high, arbitrators relied on simple heuristics--revising their choice when uncertain and confirming it when certain. At intermediate confidence levels, however, they extracted confidence from their partner's movement kinematics to guide revision. Computational simulations demonstrated that integrating the partners encoded confidence improved collective accuracy. Our findings highlight the importance of bodily motion for the social transmission of confidence information in collective decision-making.

neuroscience↗

bioRxiv2025

Neural and Behavioural Correlates of Variance of Sensory Evidence

Neurobiology of perceptual decisions has largely focused on the neural correlates of the mean strength of sensory evidence. Much less is known about the neural coding of sensory variability. Here, we analyzed the EEG signals obtained from participants who judged the mean orientation of a sequence of gratings with varying variance but constant mean to identify the neural signatures of sensory variance and their relation to individual differences in choice confidence. The neural responses in the stimulus-entrained (4 Hz) and alpha (9-11 Hz) bands tracked variability independently of mean. The frontal and centro-parietal regions demonstrated a quadratic relationship (i.e., strongest responses to intermediate levels of uncertainty) to the standard deviation of the sequence. The occipital response coded the visual stimulus variability linearly. These neural markers of variability were correlated with inter-individual differences in computational components of metacognition. Centro-parietal activity was most predictive of metacognitive sensitivity, aligning with its known role in evidence accumulation. These findings advance our understanding of how the brain dynamically encodes uncertainty and help better characterise the electrophysiological basis of individual differences in metacognitive evaluation.

neuroscience↗

bioRxiv2022

Interpersonal alignment of neural evidence accumulation to social exchange of confidence

Private, subjective beliefs about uncertainty have been found to have idiosyncratic computational and neural substrates yet, humans share such beliefs seamlessly and cooperate successfully. Bringing together decision making under uncertainty and interpersonal alignment in communication, in a discovery plus pre-registered replication design, we examined the neuro-computational basis of the relationship between privately-held and socially-shared uncertainty. Examining confidence-speed-accuracy trade-off in uncertainty-ridden perceptual decisions under social vs isolated context, we found that shared (i.e., reported confidence) and subjective (inferred from pupillometry) uncertainty dynamically followed social information. An attractor neural network model incorporating social information as top-down additive input captured the observed behaviour and spontaneously demonstrated the emergence of social alignment in virtual dyadic simulations. Electroencephalography showed that social exchange of confidence modulated the neural signature of perceptual evidence accumulation in the central parietal cortex and produced a sustained top-down flow of information from prefrontal to parietal cortex. Our findings offer a neural population model for interpersonal alignment of shared beliefs.

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bioRxiv2021

Shared responsibility decreases the sense of agency in the human brain

Sharing responsibility in social decision-making helps individuals use the flexibility of the collective context to benefit themselves by claiming credit for good outcomes or avoiding the blame for bad outcomes. Using magnetoencephalography (MEG), we examined the neuronal basis of the impact that social context has on this flexible sense of responsibility. Participants performed a gambling task in various social contexts and reported feeling less responsibility when playing as a member of a team. A reduced MEG outcome processing effect was observed as a function of decreasing responsibility at 200 ms post outcome onset and was centred over parietal and pre-central brain regions. Prior to outcome revelation in socially made decisions, an attenuated motor preparation signature at 500 ms after stimulus onset was found. A boost in reported responsibility for positive outcomes in social contexts was associated with increased activity in regions related to social and reward processing. Together, these results show that sharing responsibility with others reduces agency, influencing pre-outcome motor preparation and post-outcome processing, and provides opportunities to flexibly claim credit for positive outcomes.

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bioRxiv2019

Imitation as a model-free process in human reinforcement learning

While there is not doubt that social signals affect human reinforcement learning, there is still no consensus about their exact computational implementation. To address this issue, we compared three hypotheses about the algorithmic implementation of imitation in human reinforcement learning. A first hypothesis, decision biasing, postulates that imitation consists in transiently biasing the learners action selection without affecting her value function. According to the second hypothesis, model-based imitation, the learner infers the demonstrators value function through inverse reinforcement learning and uses it for action selection. Finally, according to the third hypothesis, value shaping, demonstrators actions directly affect the learners value function. We tested these three psychologically plausible hypotheses in two separate experiments (N = 24 and N = 44) featuring a new variant of a social reinforcement learning task, where we manipulated the quantity and the quality of the demonstrators choices. We show through model comparison that value shaping is favored, which provides a new perspective on how imitation is integrated into human reinforcement learning.

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bioRxiv2019

Distributed neural replay of decision confidence mediates informational conformity

A change of mind in response to social influence could be driven by informational conformity to increase accuracy, or by normative conformity to comply with social norms such as reciprocity. Disentangling the behavioural, cognitive and neurobiological underpinnings of informational and normative conformity have proven elusive. Here, participants underwent fMRI while performing a perceptual task that involved both advice-taking and advice-giving to human and computer partners. The concurrent inclusion of two different social roles and two different social partners revealed distinct behavioural and neural markers for informational and normative conformity. dACC BOLD response tracked informational conformity towards both human and computer but tracked normative conformity only when interacting with human. A network of brain areas (dmPFC and TPJ) that tracked normative conformity increased their functional coupling with the dACC when interacting with humans. These findings enable differentiating the neural mechanisms by which different types of conformity shape social changes of mind.

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bioRxiv2018

Group decision-making is optimal in adolescence

Group decision-making is required in early life in educational settings and central to a well-functioning society. However, there is little research on group decision-making in adolescence, despite the significant neuro-cognitive changes during this period. Researchers have studied adolescent decision-making in static social contexts, such as risk-taking in the presence of peers, and largely deemed adolescent decision-making sub-optimal. It is not clear whether these findings generalise to more dynamic social contexts, such as the discussions required to reach a group decision. Here we test the optimality of group decision-making at different stages of adolescence. Pairs of male pre-to-early adolescents (8 to 13 years of age) and mid-to-late adolescents (14 to 17 years of age) together performed a low-level, perceptual decision-making task. Whenever their individual decisions differed, they were required to negotiate a joint decision. While there were developmental differences in individual performance, the joint performance of both adolescent groups was at adult levels (data obtained from a previous study). Both adolescent groups achieved a level of joint performance expected under optimal integration of their individual information into a joint decision. Young adolescents joint, but not individual, performance deteriorated over time. The results are consistent with recent findings attesting to the competencies, rather than the shortcomings, of adolescent social behaviour.

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bioRxiv2017

Neural Computations Underpinning The Strategic Management Of Influence In Advice Giving

Research on social influence has mainly focused on the target of influence (e.g. consumer, voter), while the cognitive and neurobiological underpinnings of the source of the influence (e.g. marketer, politician) remain unexplored. Here we show that advisers managed their influence over their client strategically, by modulating the confidence of their advice, depending on the interaction between advisers level of influence on the client (i.e., being ignored or chosen by the client), and relative merit (i.e., their accuracy in comparison with a rival). Functional magnetic resonance imaging showed that these sources of social information were tracked in distinct regions of the brains social and valuation systems: relative merit in the medial-prefrontal cortex, and selection by client in the temporo-parietal junction. In addition, increased functional connectivity between these two regions during positive merit trials predicted their effect on behaviour. Both sources of social information modulated the activity in the ventral striatum. These results further our understanding of human interactions and provide a framework for investigating the neurobiology of how we try to influence others.

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bioRxiv2017

Stochastic satisficing account of choice and confidence in uncertain value-based decisions

Every day we make choices under uncertainty; choosing what route to work or which queue in a supermarket to take, for example. It is unclear how outcome variance, e.g. uncertainty about waiting time in a queue, affects decisions and confidence when outcome is stochastic and continuous. How does one evaluate and choose between an option with unreliable but high expected reward, and an option with more certain but lower expected reward? Here we used an experimental design where two choices payoffs took continuous values, to examine the effect of outcome variance on decision and confidence. We found that our participants probability of choosing the good (high expected reward) option decreased when the good or the bad options payoffs were more variable. Their confidence ratings were affected by outcome variability, but only when choosing the good option. Unlike perceptual detection tasks, confidence ratings correlated only weakly with decisions time, but correlated with the consistency of trial-by-trial choices. Inspired by the satisficing heuristic, we propose a \"stochastic satisficing\" (SSAT) model for evaluating options with continuous uncertain outcomes. In this model, options are evaluated by their probability of exceeding an acceptability threshold, and confidence reports scale with the chosen options thus-defined satisficing probability. Participants decisions were best explained by an expected reward model, while the SSAT model provided the best prediction of decision confidence. We further tested and verified the predictions of this model in a second experiment. Our model and experimental results generalize the models of metacognition from perceptual detection tasks to continuous-value based decisions. Finally, we discuss how the stochastic satisficing account of decision confidence serves psychological and social purposes associated with the evaluation, communication and justification of decision-making.\n\nAuthor SummaryEvery day we make several choices under uncertainty, like choosing a queue in a supermarket. However, the computational mechanisms underlying such decisions remain unknown. For example, how does one choose between an option with unreliable high expected reward, like the volatile express queue, and an option with more certain but lower expected reward in the standard queue? Inspired by bounded rationality and the notion of satisficing, i.e. settling for a good enough option, we propose that such decisions are made by comparing the likelihood of different actions to surpass an acceptability threshold. When facing uncertain decisions, our participants confidence ratings were not consistent with the expected outcomes rewards, but instead followed the satisficing heuristic proposed here. Using an acceptability threshold may be especially useful when evaluating and justifying decisions under uncertainty.

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bioRxiv2017

The idiosyncratic nature of confidence

Confidence is the feeling of knowing that accompanies decision making and guides processes such as learning, error detection, and inter-personal communication. Bayesian theory proposes that confidence is a function of the probability that a decision is correct given the evidence. Empirical research has shown, however, that humans tend to report confidence in very different ways. This idiosyncratic behaviour suggests that different individuals may perform different computations to estimate confidence from uncertain evidence. We tested this hypothesis by collecting confidence reports from healthy adults making decisions under either visual or numerical uncertainty. We found that for most individuals, confidence did indeed reflect the perceived probability of being correct. However, in approximately half of them, confidence also reflected a different probabilistic quantity: the observed Fisher information. We isolated the influence of each of these two quantities on confidence, and found that this decomposition is stable across weeks, and consistent across tasks involving uncertainty in both perceptual and cognitive domains. Our findings provide, for the first time, a mechanistic interpretation of individual differences in the human sense of confidence.

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