Hola,
¿eres nuevo aquí?

Registrate y conecta tu empresa con financiación pública, partners y proyectos.

CreateKnow

Financiado

Creating Knowledge

In this project I want to unravel how we build-up and update our knowledge networks depending on the amount of previous experience we have by testing my new theory on experience dependent learning. Current theory postulates memori... ver más

31/05/2029

STICHTING RADBOUD...

2M€

Presupuesto del proyecto: 2M€

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 2024-01-31

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

ERC-2023-COG: ERC CONSOLIDATOR GRANTS

I+D

Cerrada hace 1 año

0% 100% 100%

1 Participantes

STICHTING RADBOUD UNIVERSITE...

2.00M€ | Lider

Proyectos interesantes

IJCI-2017-34840 Neural circuits underlying working memory: analysis of neura... 64K€ Cerrado

OutOfSpace Structuring spatial knowledge through domain-general, non-sp... 1M€ Cerrado

BFU2009-09537 MECANISMOS DE REDES DISTRIBUIDAS EN MEMORIA DE TRABAJO Y ATE... 235K€ Cerrado

DyNeRfusion Dynamic Network Reconstruction of Human Perceptual and Rewar... 2M€ Cerrado

BFU2012-33413 CODIFICACION Y CONSOLIDACION DE LA MEMORIA: UN ESTUDIO COMPU... 105K€ Cerrado

DANAL Dendritic Activity and Neuromodulators in Active Learning 212K€ Cerrado

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: 64 meses Fecha Inicio: 2024-01-31
Fecha Fin: 2029-05-31

Líder del proyecto

STICHTING RADBOUD UNIVERSITEIT

TRL 4-5

Presupuesto del proyecto 2M€

Descripción del proyecto In this project I want to unravel how we build-up and update our knowledge networks depending on the amount of previous experience we have by testing my new theory on experience dependent learning. Current theory postulates memories to be stored initially as sets of neural representations spanning the hippocampus and weakly interacting neocortical modules. The spontaneous reactivation of new memories during a consolidation phase, would lead to strengthening of the neocortical memory trace. Consequently, pre-existing knowledge is proposed to be coded in the brain as a cortical network of neurons that allows for more efficient consolidation of new information. I recently developed a new theory, proposing that the existence of previous knowledge and therefore the extent of the cortical memory network, is a gradient of experience instead of being either present or not. The size and complexity of the knowledge network would influence where in the brain memories are encoded and how fast they are consolidated. I propose combining my innovative behavioural paradigm – the HexMaze - that enables investigatory access to various levels of experience, with different techniques in three species to test this theory. In mice, with immediate early gene expression techniques to visualize and manipulate the brain-wide memory network with the resolution of individual neurons. In rats, with electrophysiology to measure and manipulate memory reactivations during sleep as the mechanisms to enable consolidation. In humans, with targeted memory reactivation and magnetic resonance imaging to follow the evolution of learning over one year. The combination of species with their respective methods enables to observe effects as well as test for causality. The unique combination of meaningful behaviour with appropriate, precise techniques would provide ground-breaking insight into how we create and update our knowledge networks and change the way we view and test memory.

Conecta tu I+D

Entra hoy

Financiación

Empresas

CTIs/Universidades

Proyectos

Investigadores