Objective
How do we create mental images? Despite extensive research, we still miss an overarching mechanistic understanding of mental imagery: How do the various brain regions involved in mental imagery contribute to the unified percept in our mind's eye? Why do we experience imagery so differently ranging from no to extremely vivid mental images? In this project, we propose a novel perspective on mental imagery, viewing it as a personalised computational process that takes into account individual brain characteristics. The task of this computational process is to progressively transform abstract object descriptions (input) into sensory-like visual representations (output) through feedback connections in the brains processing hierarchy. To unravel the stages of this conversion process, we will employ advanced fMRI techniques to measure neural activity across the entire brain at an unparalleled level of detail. Using sophisticated analysis methods, we will decode topographic and semantic information about the content of mental images from activated brain areas. To investigate the causal involvement of specific areas, we will transiently disrupt their activity using transcranial magnetic stimulation (TMS). Informed by the fMRI and TMS data, we will develop the first personalized AI-inspired neural network model of mental imagery. This model will simulate the emergence of sensory representations backwards through the processing hierarchy and predict the perceived vividness of generated images for each individual. By implementing the model into a Brain Computer Interface, we will enable participants to see imagined objects on a screen during fMRI scanning. This opens up new applications, such as training the strength of mental imagery by providing neurofeedback based on predicted vividness. This interdisciplinary project, at the intersection of psychology, neuroscience, and AI, will provide an integrative framework of the generation of subjective experiences in the mind's eye.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
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Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
6200 MD Maastricht
Netherlands