Biology subjects

Bahrami, B.

Publications and source records attributed to Bahrami, B..

4 recordsLinked to original sources

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.

neuroscience↗

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.

neuroscience↗

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.

neuroscience↗

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.

neuroscience↗