Summary
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.
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.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101077874 |
| Start date: | 01-09-2023 |
| End date: | 30-09-2028 |
| Total budget - Public funding: | 1 496 524,00 Euro - 1 496 524,00 Euro |
Cordis data
Original 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.
Status
SIGNEDCall topic
ERC-2022-STGUpdate Date
31-07-2023
Images
No images available.
Geographical location(s)
