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COGNIBRAINS

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Cognition in an Insect Brain

There is a common perception that larger brains mediate higher cognitive capacity. Social insects, however, demonstrate that sophisticated cognition is possible with miniature brains. Honeybees display higher-order learning such a... ver más

31/12/2025

CNRS

3M€

Presupuesto del proyecto: 3M€

Líder del proyecto

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 4 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2019-11-06

ERC-2018-ADG: ERC Advanced Grant

I+D

Cerrada hace 6 años

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Información adicional privada

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

4 Participantes

CNRS

2.15M€ | Lider

SP BERNER PLASTIC GROUP

1.09M€ | Participante

UNIVERSITE TOULOUSE III - Pa...

417.50K€ | Participante

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Duración del proyecto: 73 meses Fecha Inicio: 2019-11-06
Fecha Fin: 2025-12-31

Líder del proyecto

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 3M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto There is a common perception that larger brains mediate higher cognitive capacity. Social insects, however, demonstrate that sophisticated cognition is possible with miniature brains. Honeybees display higher-order learning such as categorization, non-linear discriminations, concept learning and numerosity, which are unique among insects. These capacities are mediated by a miniature brain with only 950 000 neurons. Despite extensive behavioral analyses, no study has attempted to elucidate the neural mechanisms underpinning the higher-order learning of bees. Our current breakthrough establishing virtual-reality protocols for tethered honeybees offers a unique opportunity to uncover the minimal circuits that mediate higher-order forms of cognitive processing in the brain of a behaving bee. We have recently shown that bees learn to solve elemental and non-elemental problems in this experimental context, which allows integrating behavioral, neurobiological and computational approaches to unravel the neural mechanisms underlying non-elemental learning in the honeybee. I will combine behavioral recordings of bees learning non-linear discriminations and relational rules in a virtual reality environment, with access to their brain via multi-photon calcium imaging and multielectrode recordings of neural populations. I will determine the neural circuits of elemental and non-elemental visual learning along the visual circuits of the bee brain, and the necessity and sufficiency of these circuits for these capacities via selective knockdown and rescuing via wavelength-selective multi-photon uncaging of neurotransmitters. Data will be fed into computational models to test hypotheses about minimal neural architectures for visual cognition, working towards whole-brain modeling. This project will expand the information available on the neurobiology of insect learning, and will provide the first integral characterization of the mechanisms underlying cognition in a miniature brain.

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