Project description
Brain size doesn't matter
Larger brains do not always exhibit more complex behaviour. Take for example the honeybees and other social insects that have miniature brains. Despite their tiny brain size they are capable of huge feats like categorisation and concept learning, and even numerosity. All this with just 950 000 neurons (the human brain contains around 100 billion neurons). The EU-funded COGNIBRAINS project will study the honeybees to find out which minimal circuits mediate higher-order forms of cognitive processing in the brain. It will also combine behavioural recordings of bees learning non-linear discriminations and relational rules. The overall aim of this project is to provide the first integral characterisation of the mechanisms underlying cognition in a miniature brain.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesneurobiology
- natural scienceschemical sciencesinorganic chemistryalkaline earth metals
- social sciencessociologysocial issuessocial inequalities
- natural sciencesbiological scienceszoologyentomologyapidology
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Funding Scheme
ERC-ADG - Advanced GrantHost institution
75794 Paris
France