Explore the words cloud of the COGNIBRAINS project. It provides you a very rough idea of what is the project "COGNIBRAINS" about.
The following table provides information about the project.
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
|Coordinator Country||France [FR]|
|Total cost||2˙870˙339 €|
|EC max contribution||2˙145˙339 € (75%)|
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
|Duration (year-month-day)||from 2020-04-01 to 2025-03-31|
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|1||CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS||FR (PARIS)||coordinator||2˙145˙339.00|
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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