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CONSCIOUS

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Computational Neurophenomenology Explaining Concious Experiences in terms of Ne...

Computational Neurophenomenology Explaining Concious Experiences in terms of Neural Mechanisms How do conscious experiences depend on the brain? The CONSCIOUS project aims to make new progress on this oldest of questions by progressing from establishing correlations between patterns of brain activity and aspects of consciou... ver más

31/03/2028

UOS

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

THE UNIVERSITY OF SUSSEX No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-09-03

ERC-2020-ADG: ERC ADVANCED GRANT Specific Challenge:Objectives

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3 Participantes

UOS

2.39M€ | Lider

COBRA INSTALACIONES Y SERVIC...

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STICHTING RADBOUD UNIVERSITE...

48.33K€ | Participante

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Duración del proyecto: 78 meses Fecha Inicio: 2021-09-03
Fecha Fin: 2028-03-31

Líder del proyecto

THE UNIVERSITY OF SUSSEX No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 2M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto How do conscious experiences depend on the brain? The CONSCIOUS project aims to make new progress on this oldest of questions by progressing from establishing correlations between patterns of brain activity and aspects of consciousness, towards developing and testing explanations in terms of neural mechanisms. By following this strategy, I believe the problem of consciousness will be dissolved rather than outright solved – similar to what happened with the study of life, decades ago. One branch of CONSCIOUS will explore what it is like to be conscious ‘at all’. Here, I will make use of the concept of ‘emergence’ – the sense in which a system’s whole can seem to be more than the sum of its parts. I will test the idea that the globally unified character of conscious experiences emerges from neural dynamics, in a similar way to how a flock of birds emerges from the trajectories of the individual birds that make it up. This will involve developing new theoretically principled and practically applicable measures of emergence, and applying them to neurophysiological data reflecting different global states of consciousness. A second branch will explore the nature of specific conscious perceptions, appealing to the influential idea of the brain as a ‘prediction machine’. Here, I will develop novel machine learning models to investigate how particular conscious experiences can be understood as arising from the brain’s ‘best guesses’ of the causes of its sensory inputs. I will use combinations of behavioural experiments and neuroimaging to test the idea that different kinds of neurally-encoded predictions can account for different kinds of perceptual experience. CONSCIOUS is thoroughly multidisciplinary, bridging cognitive neuroscience, philosophy, statistical physics, machine learning, and artificial intelligence. It is only through such an approach that it is possible to make substantial progress towards a satisfying scientific account of conscious experience.

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