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Cortical to Subcortical Information Transfer Underlying Skill Learning

The stability-plasticity dilemma is a critical constraint in brain networks underlying learning and memory. The dilemma is how the brain can acquire new information (plasticity) without overriding older knowledge (stability). This... ver más

31/12/2021

IIT

86K€

Presupuesto del proyecto: 86K€

Líder del proyecto

FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-12-31

MSCA-IF-2019: Individual Fellowships

I+D

Cerrada hace 5 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

IIT

85.74K€ | Lider

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Duración del proyecto: 20 meses Fecha Inicio: 2020-04-06
Fecha Fin: 2021-12-31

Líder del proyecto

FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 86K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The stability-plasticity dilemma is a critical constraint in brain networks underlying learning and memory. The dilemma is how the brain can acquire new information (plasticity) without overriding older knowledge (stability). This project aims to understand how the brain solves this dilemma by investigating the underlying circuits that allow for the transition from the initial exploration of a behavior to its long-term storage. One possibility is that distinct brain circuits drive exploration and storage. Alternatively, a shared circuit may mediate both abilities through the transfer of behaviorally relevant information across brain regions. To rigorously test these models, we need a method to measure behaviorally relevant information transfer, something that is not possible with current methods. In this project I propose to work with Dr. Panzeri, a leading expert in applying information theory to neuroscience, to develop such a method. We will apply this method to a dataset I collected during my PhD, consisting of high-resolution, high-channel count chronic multi-site in vivo electrophysiology in the rat during novel skill learning. This dataset contains simultaneously recorded activity from motor cortex and the basal ganglia, regions that have been implicated in the exploration and the storage of behaviors, respectively. The results of this project will shed light on a fundamental principle in the brain, while providing the broader field of systems neuroscience with an important tool that we will disseminate in an open source format for maximum impact. This project is an ideal progression from my PhD and will allow me to strengthen my skills in computational neuroscience, complementing my training in experimental neuroscience, and preparing me to lead an interdisciplinary lab that combines high-quality in vivo electrophysiology with cutting-edge computational methods to investigate how interactions across brain regions generate complex behaviors.

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