Objective
"Understanding the relationship between structure and function of cortical neurons and circuits is one of the key challenges in neuroscience. For inhibitory neurons, roughly 15 subtypes are well characterized and we know a fair bit about their function. However, the vast majority of neocortical neurons are excitatory. Yet we know little about how differences in the morphology of excitatory neurons relate to their computational properties in vivo. I hypothesize that there is a close correspondence between morphology and function of excitatory neurons: distinct subtypes can be identified not only by their morphological features, but also by how they respond to stimulation with natural stimuli. To test this hypothesis, I will build upon recent advances in machine learning and develop a data-driven approach to derive a ""bar code"" for each neuron: a low-dimensional representation of its morphological features and its response properties to natural stimuli. Using these techniques, I will tackle the structure-function question by harnessing a large-scale functional anatomy dataset: a combination of electron-microscopy reconstructions at sub-micrometer resolution with two-photon functional imaging of nearly all excitatory neurons in one cubic millimeter of the mouse visual cortex. If successful, my project could fundamentally change our view on the diversity of excitatory cell types and reveal how morphological features are linked to a neuron's computational output. It could pave the way towards a unified definition of cell types, one of the fundamental building blocks of the brain. The same approach could be used in other brain areas and even other cellular systems beyond the brain. More broadly, while machine learning is promising to transform the scientific discovery process as a whole, my project could serve as a prime example of this transformation process in neuroscience and show how machine learning can help to discover structure in nature."
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. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences neurobiology
- medical and health sciences basic medicine anatomy and morphology
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2021-STG
See all projects funded under this callHost institution
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
37073 Gottingen
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.