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Unveiling the relationship between brain connectivity and function by integrated...

I will address the fundamental question of which is the role of neuron activity and plasticity in information elaboration and storage in the brain. I, together with an interdisciplinary team, will develop a hybrid neuro-morphic co... ver más

30/04/2024

UNITN

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

UNIVERSITA DEGLI STUDI DI TRENTO No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 2 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2024-04-30

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

ERC-2017-ADG: ERC Advanced Grant

I+D

Cerrada hace 7 años

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2 Participantes

UNITN

2.50M€ | Lider

CEMENTOS ALFA

549.86K€ | Participante

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: 70 meses Fecha Inicio: 2018-06-26
Fecha Fin: 2024-04-30

Líder del proyecto

UNIVERSITA DEGLI STUDI DI TRENTO

TRL 4-5

Presupuesto del proyecto 2M€

Descripción del proyecto I will address the fundamental question of which is the role of neuron activity and plasticity in information elaboration and storage in the brain. I, together with an interdisciplinary team, will develop a hybrid neuro-morphic computing platform. Integrated photonic circuits will be interfaced to both electronic circuits and neuronal circuits (in vitro experiments) to emulate brain functions and develop schemes able to supplement (backup) neuronal functions. The photonic network is based on massive reconfigurable matrices of nonlinear nodes formed by microring resonators, which enter in regime of self-pulsing and chaos by positive optical feedback. These networks resemble human brain. I will push this analogy further by interfacing the photonic network with neurons making hybrid network. By using optogenetics, I will control the synaptic strengthen-ing and the neuron activity. Deep learning algorithms will model the biological network functionality, initial-ly within a separate artificial network and, then, in an integrated hybrid artificial-biological network. My project aims at: 1. Developing a photonic integrated reservoir-computing network (RCN); 2. Developing dynamic memories in photonic integrated circuits using RCN; 3. Developing hybrid interfaces between a neuronal network and a photonic integrated circuit; 4. Developing a hybrid electronic, photonic and biological network that computes jointly; 5. Addressing neuronal network activity by photonic RCN to simulate in vitro memory storage and retrieval; 6. Elaborating the signal from RCN and neuronal circuits in order to cope with plastic changes in pathologi-cal brain conditions such as amnesia and epilepsy. The long-term vision is that hybrid neuromorphic photonic networks will (a) clarify the way brain thinks, (b) compute beyond von Neumann, and (c) control and supplement specific neuronal functions.

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