Summary
Social information pervades every aspect of our lives, and our ability to process it and respond appropriately is essential to our success as individuals and of society as a whole. Despite its critical importance, there are profound individual differences in social processing abilities. The key to understanding this variance may lie beyond isolated cortical regions, in the poorly understood large-scale interactions between different cortical networks which facilitate the integration of information and the execution of complex tasks. We propose a novel framework, designed to introduce new tools to the study of some of the most fundamental questions in social neuroscience: are there dedicated brain mechanisms for the processing of social information? What goes wrong in social information processing disorders, and how does social information processing relate to social anxiety? Do these abilities fluctuate over long time scales (years)? Can we predict their change? We will create new behavioral tasks to tease apart social task elements, and objectively estimate individual social processing abilities using our innovative measure of typicality. We will quantify individual differences in performance on social tasks, and identify the variance in neural activity which predicts them from a wide range of network features at the high resolution of ultra-high field 7 Tesla fMRI. This will yield testable hypotheses about the links between networks and social behavior. Finally and most crucially, to test these hypotheses, we will use covert neurofeedback, a cutting-edge technique which I have been developing, to perturb the networks, establishing their causal contribution to behavior.
The combination of novel behavioral, neurocomputational, and above all perturbation tools for testing causality, will provide insights which will profoundly impact our understanding of social information processing in health, and advance the reality of personalized treatment of social disorders.
The combination of novel behavioral, neurocomputational, and above all perturbation tools for testing causality, will provide insights which will profoundly impact our understanding of social information processing in health, and advance the reality of personalized treatment of social disorders.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101077921 |
| Start date: | 01-06-2023 |
| End date: | 31-05-2028 |
| Total budget - Public funding: | 1 637 981,00 Euro - 1 637 981,00 Euro |
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Original description
Social information pervades every aspect of our lives, and our ability to process it and respond appropriately is essential to our success as individuals and of society as a whole. Despite its critical importance, there are profound individual differences in social processing abilities. The key to understanding this variance may lie beyond isolated cortical regions, in the poorly understood large-scale interactions between different cortical networks which facilitate the integration of information and the execution of complex tasks. We propose a novel framework, designed to introduce new tools to the study of some of the most fundamental questions in social neuroscience: are there dedicated brain mechanisms for the processing of social information? What goes wrong in social information processing disorders, and how does social information processing relate to social anxiety? Do these abilities fluctuate over long time scales (years)? Can we predict their change? We will create new behavioral tasks to tease apart social task elements, and objectively estimate individual social processing abilities using our innovative measure of typicality. We will quantify individual differences in performance on social tasks, and identify the variance in neural activity which predicts them from a wide range of network features at the high resolution of ultra-high field 7 Tesla fMRI. This will yield testable hypotheses about the links between networks and social behavior. Finally and most crucially, to test these hypotheses, we will use covert neurofeedback, a cutting-edge technique which I have been developing, to perturb the networks, establishing their causal contribution to behavior.The combination of novel behavioral, neurocomputational, and above all perturbation tools for testing causality, will provide insights which will profoundly impact our understanding of social information processing in health, and advance the reality of personalized treatment of social disorders.
Status
SIGNEDCall topic
ERC-2022-STGUpdate Date
31-07-2023
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