Summary
Social species, and specifically human and nonhuman primates, rely heavily on conspecifics for survival. Considerable time is spent watching each other’s behavior because this is often the most relevant source of information for preparing adaptive social responses. The project RELEVANCE aims to understand how the brain evolved special structures to process highly relevant social stimuli like bodies and to reveal how social vision sustains adaptive behaviour.
This requires a novel way of thinking about biological information processing, currently among the brains’ most distinctive and least understood characteristic that accounts for the biggest difference between brains and computers.
The project will develop a mechanistic and computational understanding of the visual processing of bodies and interactions and show how this processing sustains higher abilities such as understanding intention, action and emotion. Relevance will accomplish this by integrating advanced methods from multiple disciplines: psychophysics and high-field functional imaging in combination with virtual reality and neural stimulation in humans; electrophysiology with optogenetics and laminar recordings in monkeys.
Crosstalk between
human and monkey methods will establish homologies between the species, revealing cornerstones of the theory. In a radical departure from current practice, we will develop novel deep neural network models that unify the data. These models will not only capture detailed mechanisms of neural processing of complex social stimuli and its dynamics, but also reproduce the modulation of brain activity during active behavior.
RELEVANCE will reveal novel ways of understanding and diagnosing social communication deficits in neuropsychiatry, and suggest novel hypotheses about their genetic basis. It will motivate novel principles and architectures for processing of socially relevant information in computer and robotic systems.
This requires a novel way of thinking about biological information processing, currently among the brains’ most distinctive and least understood characteristic that accounts for the biggest difference between brains and computers.
The project will develop a mechanistic and computational understanding of the visual processing of bodies and interactions and show how this processing sustains higher abilities such as understanding intention, action and emotion. Relevance will accomplish this by integrating advanced methods from multiple disciplines: psychophysics and high-field functional imaging in combination with virtual reality and neural stimulation in humans; electrophysiology with optogenetics and laminar recordings in monkeys.
Crosstalk between
human and monkey methods will establish homologies between the species, revealing cornerstones of the theory. In a radical departure from current practice, we will develop novel deep neural network models that unify the data. These models will not only capture detailed mechanisms of neural processing of complex social stimuli and its dynamics, but also reproduce the modulation of brain activity during active behavior.
RELEVANCE will reveal novel ways of understanding and diagnosing social communication deficits in neuropsychiatry, and suggest novel hypotheses about their genetic basis. It will motivate novel principles and architectures for processing of socially relevant information in computer and robotic systems.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/856495 |
| Start date: | 01-07-2020 |
| End date: | 30-06-2026 |
| Total budget - Public funding: | 8 309 114,00 Euro - 8 309 114,00 Euro |
Cordis data
Original description
Social species, and specifically human and nonhuman primates, rely heavily on conspecifics for survival. Considerable time is spent watching each other’s behavior because this is often the most relevant source of information for preparing adaptive social responses. The project RELEVANCE aims to understand how the brain evolved special structures to process highly relevant social stimuli like bodies and to reveal how social vision sustains adaptive behaviour.This requires a novel way of thinking about biological information processing, currently among the brains’ most distinctive and least understood characteristic that accounts for the biggest difference between brains and computers.
The project will develop a mechanistic and computational understanding of the visual processing of bodies and interactions and show how this processing sustains higher abilities such as understanding intention, action and emotion. Relevance will accomplish this by integrating advanced methods from multiple disciplines: psychophysics and high-field functional imaging in combination with virtual reality and neural stimulation in humans; electrophysiology with optogenetics and laminar recordings in monkeys.
Crosstalk between
human and monkey methods will establish homologies between the species, revealing cornerstones of the theory. In a radical departure from current practice, we will develop novel deep neural network models that unify the data. These models will not only capture detailed mechanisms of neural processing of complex social stimuli and its dynamics, but also reproduce the modulation of brain activity during active behavior.
RELEVANCE will reveal novel ways of understanding and diagnosing social communication deficits in neuropsychiatry, and suggest novel hypotheses about their genetic basis. It will motivate novel principles and architectures for processing of socially relevant information in computer and robotic systems.
Status
SIGNEDCall topic
ERC-2019-SyGUpdate Date
27-04-2024
Images
No images available.
Geographical location(s)
