Confirmation bias in decision-making

Confirmation bias is the tendency to interpret new information such that it agrees with prior beliefs and hypotheses. It is one of the fundamental biases in human reasoning, with descriptions dating back to 5th century BC. Despite its ubiquitous nature, less is known about the mechanisms underlying this bias. To address this, we devised a novel psychophysical task protocol that allowed us to induce confirmation bias in low-level sensory decisions in a systematic and reproducible fashion and to quantify it in individual participants by means of psychophysical and computational modelling techniques. We found that confirmation bias arises through selective overweighting of evidence consistent with a previous choice, akin to feature-based attention (Talluri, Urai et al. 2018). In this ongoing study, my collaborators and I use computational Neuroimaging to probe the underlying neural mechanisms of confirmation bias, with task protocols that allow us to directly compare this bias to selective attention.

Serial dependencies in perceptual decision-making

Real-world decisions humans make are often influenced by past decisions and experiences. Such an influence can be beneficial owing to the statistical autocorrelations in the natural world. At what stage in the decision-making process does this influence enter? What are the neurobiological and computational mechanisms that govern this influence? To answer these questions, I combine computational modelling with fMRI while human subjects perform simple perceptual decisions. We manipulate the trial -order statistics in the experiments to better identify these bias signals.