Michael Pereira
Host institution: University Grenoble Alpes
Laboratory: LPNC
Call for Projects: Starting (SH4)
Project name: LEAP – A leaky evidence accumulation process (LEAP) for consciousness
Amount: 1.49 M€
Description:
How we consciously experience the world remains a mystery in science. To tackle this problem, scientific works on perceptual consciousness contrast brain activity when participants consciously perceive a stimulus versus when they are unaware of it. To report stimulus awareness, participants need to make decisions. However, the extent to which the well-studied mechanisms of decision-making apply to consciousness is unclear. One possible reason is that standard neuroimaging methods lack the sensitivity to observe whether the mechanisms of decision-making also operate in the absence of task relevance, as when participants become conscious of a stimulus irrespective of any task.
In this project, I will test the hypothesis that a mechanism of decision-making –evidence accumulation– explains how perceptual consciousness unfolds over time. First, I will develop a computational model of a latent evidence accumulation process (LEAP) and test it on behavioral measures of phenomenal aspects of perceptual experience: its duration and intensity. Second, I will search for single neuron activity in humans that instantiates evidence accumulation and test whether it also determines these phenomenal aspects of perceptual experience. Third, I will stimulate the corresponding brain regions to disentangle their causal role in either solely triggering perceptual experience or shaping it. Last, I will use the LEAP model to explain hallucinatory-like experiences in patients with Parkinson’s disease and test whether deep-brain stimulation affects only decision-making –as previously shown– or also perceptual experience.
By combining computational modeling and cutting-edge electrophysiology, the LEAP project will provide unique mechanistic insights on how neuronal activity determines perceptual experience and guides its temporal dynamics. It will also provide a tool to better understand hallucinations, which remain today a major debilitating symptom in numerous psychiatric disorders.