Active Inference and the Circuits of Precision and Prediction
PREDICTION aims to uncover the neural mechanisms of high-level visual cognition by integrating advanced methods across disciplines to model hierarchical processing in the human brain.
Projectdetails
Introduction
The human brain exhibits remarkable cognitive abilities, such as imagery, attention, and mental simulation, which along with perception reflect our capacity to infer properties of the world. Perceptual inference involves a statistical hierarchical synthesis of information from the senses with prior knowledge of the world.
Predictive Processing
There is empirical evidence in favour of Predictive Processing where functional interaction of descending pathways carrying top-down prediction and precision signals interacts with the ascending pathways to generate prediction errors. PREDICTION will develop a mechanistic and computational understanding of the hierarchical processing underlying inference in vision-related human brain areas and will establish how feedback connections enable generative cognitive functions.
Novel Approaches
Unravelling the neural mechanisms of high-level visual cognitive functions requires novel ways of thinking about biological information processing and an integrated effort to measure and model cognitive functions at multiple brain scales. PREDICTION accomplishes this by integrating concepts and advanced methods from multiple disciplines:
- Molecular biology to characterise projection cell-types.
- Psychophysics and sub-millimetre ultra-high-field functional imaging of cortical layers and columns in the human brain.
- Precision viral tracing to investigate the anatomical origins and targets of generative networks in non-human primates (NHP).
- Spatio-temporal controlled activation of genetically identified feedback pathways with optogenetics together in multi-areal laminar recordings in NHPs.
- Biologically realistic multi-scale computational modelling.
Functional Circuits
PREDICTION will describe the functional circuits supporting hierarchical processing and their role in active vision. This will take us to the heart of cortical function and its causative role in perception, cognition, and decision-making, relative to a range of pathologies as well as to understand what makes us human.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.500.000 |
Totale projectbegroting | € 2.500.000 |
Tijdlijn
Startdatum | 1-1-2025 |
Einddatum | 31-12-2029 |
Subsidiejaar | 2025 |
Partners & Locaties
Projectpartners
- INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALEpenvoerder
- UNIVERSITEIT MAASTRICHT
Land(en)
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The UnderPressure project aims to investigate how mechanical constraints from 3D crowding affect cell proliferation and signaling in various organisms, with potential applications in reducing cancer chemoresistance.
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Vergelijkbare projecten uit andere regelingen
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It's about time: Towards a dynamic account of natural vision.TIME aims to revolutionize vision research by integrating semantic understanding and active information sampling through advanced brain imaging and bio-inspired deep learning, enhancing insights into visual cognition. | ERC STG | € 1.499.455 | 2022 | Details |
Personalized priors: How individual differences in internal models explain idiosyncrasies in natural visionThis project aims to uncover the contents of individual internal models of natural vision through creative drawing methods, enhancing understanding of scene perception and its neural underpinnings. | ERC STG | € 1.484.625 | 2023 | Details |
Empirical and mechanistic foundations for synergistic predictive processing in the sensory brainSynPrePro aims to integrate hierarchical predictive coding with subcortical processing to enhance understanding of sensory input processing and its implications for perceptual disorders. | ERC STG | € 1.499.945 | 2024 | Details |
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It's about time: Towards a dynamic account of natural vision.
TIME aims to revolutionize vision research by integrating semantic understanding and active information sampling through advanced brain imaging and bio-inspired deep learning, enhancing insights into visual cognition.
Personalized priors: How individual differences in internal models explain idiosyncrasies in natural vision
This project aims to uncover the contents of individual internal models of natural vision through creative drawing methods, enhancing understanding of scene perception and its neural underpinnings.
Empirical and mechanistic foundations for synergistic predictive processing in the sensory brain
SynPrePro aims to integrate hierarchical predictive coding with subcortical processing to enhance understanding of sensory input processing and its implications for perceptual disorders.
Using deep neural networks to understand functional specialization in the human visual cortex
This project aims to uncover the origins of functional specialization in the brain's visual pathway by integrating computational modeling, naturalistic behavior sampling, and neuroimaging.