Summary
The primary visual cortex of the mouse is an ideal model system in which we can study network restructuring during
learning, due to the well-described functional properties of its neurons, the existence of a robust learning paradigm, and the feasibility of recording large populations of neurons. Here we aim to identify functional groups
of cortical neurons based on the robust estimation of their correlations and observe the topological re-structuring of
the network they form. We will build comprehensive Bayesian multi-level models that respect the multidimensional
structure of the data for estimation and interpretation of our results. We hypothesize that we will observe major re-
structuring of functional cortical sub-networks upon learning.
learning, due to the well-described functional properties of its neurons, the existence of a robust learning paradigm, and the feasibility of recording large populations of neurons. Here we aim to identify functional groups
of cortical neurons based on the robust estimation of their correlations and observe the topological re-structuring of
the network they form. We will build comprehensive Bayesian multi-level models that respect the multidimensional
structure of the data for estimation and interpretation of our results. We hypothesize that we will observe major re-
structuring of functional cortical sub-networks upon learning.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/895465 |
| Start date: | 01-03-2021 |
| End date: | 28-02-2023 |
| Total budget - Public funding: | 165 085,44 Euro - 165 085,00 Euro |
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Original description
The primary visual cortex of the mouse is an ideal model system in which we can study network restructuring duringlearning, due to the well-described functional properties of its neurons, the existence of a robust learning paradigm, and the feasibility of recording large populations of neurons. Here we aim to identify functional groups
of cortical neurons based on the robust estimation of their correlations and observe the topological re-structuring of
the network they form. We will build comprehensive Bayesian multi-level models that respect the multidimensional
structure of the data for estimation and interpretation of our results. We hypothesize that we will observe major re-
structuring of functional cortical sub-networks upon learning.
Status
CLOSEDCall topic
MSCA-IF-2019Update Date
28-04-2024
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