Neurophysiological bases of decision-making processes: dissociating risk and uncertainty in the human brain - Data Management Plan

Humans face a daily variety of decision-making challenges in distinct aspects of life [1]. Most of these decisions are made under uncertainty, a concept employed to describe an imperfect knowledge about the expected outcomes for distinct choices [2]. Although the conceptual distinction between uncertainty and risk was formulated in the early 1920s by Frank Knight [3], the distinction is not always clearly stated in the neuroscientific study of decision-making, leading to an often-interchangeable misuse of the concepts of risk and uncertainty. Nonetheless, research in neuroscience has provided evidence for the dissociation of the neuronal underpinnings of decision-making in situations of risk and uncertainty, pointing towards the recruitment of distinct mechanisms in processing risk and uncertainty: risk has been mainly associated with increased activation in brain regions typically associated with cognitive and attentional processes, and uncertainty has been associated with brain regions usually related to emotional reactivity (e.g.,[4,5]). Most existing studies on the neuronal underpinnings of risk and uncertainty processing in decision making rely on the functional Magnetic Resonance Imaging (fMRI) technique. The fMRI offers high spatial resolution in the study of the recruited brain regions, but lacks the temporal precision required to disentangle the distinct processes related with risk and uncertainty processing. In order to overcome the existing limitations in the literature and shed light on the temporal brain dynamics of risk and uncertainty processing while controlling for methodological confounds, we propose a research plan that aims to: (a) experimentally dissociate the neuronal correlates of risk and uncertainty processing in decision-making, while controlling for expected value and utility; and to (b) provide a multilevel assessment of risk and uncertainty processing, complementing behavioral data with neurophysiological correlates of the autonomic and central nervous systems. In the context of the present research plan, two related studies are proposed.