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PredictiveBrain

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Predicting the future: How our brain predicts future events for successful navig...

Predicting the future: How our brain predicts future events for successful navigation through our dynamic environment. To successfully navigate our dynamic environment, our brain needs to continuously update its representation of external information. This poses a fundamental problem: how does the brain cope with a stream of dynamic input? It take... ver más

31/12/2024

STICHTING RADBOUD...

188K€

Presupuesto del proyecto: 188K€

Líder del proyecto

STICHTING RADBOUD UNIVERSITEIT No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-08-08

Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:

HORIZON-MSCA-2021-PF-01-01: MSCA Postdoctoral Fellowships 2021

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Cerrada hace 3 años

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STICHTING RADBOUD UNIVERSITE...

187.62K€ | Lider

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Últimas noticias

29-11-2024: IDAE En las últimas 48 horas el Organismo IDAE ha otorgado 4 concesiones

29-11-2024: ECE En las últimas 48 horas el Organismo ECE ha otorgado 2 concesiones

29-11-2024: CMVAMADRID En las últimas 48 horas el Organismo CMVAMADRID ha otorgado 37 concesiones

Duración del proyecto: 28 meses Fecha Inicio: 2022-08-08
Fecha Fin: 2024-12-31

Líder del proyecto

STICHTING RADBOUD UNIVERSITEIT

TRL 4-5

Presupuesto del proyecto 188K€

Descripción del proyecto To successfully navigate our dynamic environment, our brain needs to continuously update its representation of external information. This poses a fundamental problem: how does the brain cope with a stream of dynamic input? It takes time to transmit and process information along the hierarchy of the visual system. Our capacity to interact with dynamic stimuli in a timely manner (e.g., catch a ball) suggests that our brain generates predictions of unfolding dynamics. While predictive processing theories assume an internal representation of future external states, empirical research typically employs neural measures that capture an indirect consequence of prediction. The representational nature of predictions remains largely unexplored. One approach for investigating neural representations is representational similarity analysis (RSA), which typically uses models of static stimulus features at different hierarchical levels of complexity (e.g., color, shape, category, concept) to investigate how these features are represented in the brain. I have recently developed a novel dynamic extension to RSA that uses temporally variable models to capture neural representations of dynamic stimuli. A proof-of-concept MEG study unveiled predictive neural representations of naturalistic dynamic input. These promising initial results open the door for addressing important outstanding questions on how our brain represents and predicts the dynamics of the world. In this project I aim to answer these questions. I will execute the project at the prestigious Donders Institute in the lab of Floris de Lange, a leading expert in the field of predictive processing. The proposed project is unique as it tackles the rich dynamics of predictive processing in terms of neural representations. It will allow me to conduct creative, original and important research, which will propel my scientific career, and strengthen my competitiveness as a scientist.

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