Just at the onset of the ERC project, we had obtained findings showing that the limited computational precision of inference drives a dominant fraction of decision variability under uncertainty. These results were obtained in the context of perceptual decisions about sequences of visual stimuli. We decided to design a series of original experiments to test the generalizability of these findings for reward-guided decisions. The obtained results have underlined the degree of generality of our research hypothesis, and resulted in a key modification of the reinforcement learning (RL) models used to fit human reward-guided decisions. We have also identified the neural substrates of this learning variability in the human brain using neuroimaging data. Our results point toward an important role for the noradrenergic system in the regulation of learning precision. These results were published in in Nature Neuroscience, a broad-audience journal. I also contacted the Project Promotion team of the ERC in September 2019 and wrote with them a general-audience piece on the ERC website. Our article in Nature Neuroscience has resulted in several invitations at international research institutes to present our findings. We have also written an invited review on the origin, impact and function of computation noise for human learning and decision-making, in Current Opinion in Behavioral Sciences. We have extended this line of work by studying individual differences in learning precision across a large cohort of subjects for which non-clinical psychiatric scores are being measured. The study has recently been published in Nature Mental Health, and emphasizes the subjective and clinical relevance of the proposed accuracy-cost trade-off (our second research hypothesis). Further studies in this direction have revealed cognitive bottlenecks on human decision-making that were identified in my research proposal. In collaboration with other members of my group, using a combined behavioral-neuroimaging experiment, we have compared cue-based and outcome-based inference in healthy human participants. This research has confirmed the strong overlap between these two forms of inference at the core of perceptual and reward-guided decisions, but has also revealed selective differences between them. A first article describing the results of this study has been published in Nature Communications, a broad-audience journal, and a second one in eLife. Last, in collaboration with medical collaborators, I have conducted research to validate the clinical relevance of the experimental approaches developed in my research project. In particular, we have applied a new cognitive task to severe OCD patients and observed selective differences in the outcome-based condition of the task.
