Project INF

Service Project: Data management for reproducible data-driven computational modeling cross-species and cross-labs

This project will provide expertise for access, description, and modelling of the data collected in the individual projects as well as Z02 and Z03. INF will continuously assess general workflows, resource requirements, and data analysis processes to capture between-project differences that may impact data comparability and re-usability across projects. INF will provide tools, services and training to help projects align their research output to (i) facilitate data analysis for extracting common activity patterns and mechanisms underlying motor behaviours across species, and (ii) promote data-driven computational modelling.

Please find more information about how to collect or process data within the SFB1451 here:

Go to rdm SFB1451

Project related publications

©Forschungszentrum Jülich, Sascha Kreklau

Prof. Dr. Silvia daun

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©MedizinFotoKöln

Prof. dr. Michael Hanke

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©private

Prof. Dr. Martin Nawrot

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Functional spiking neural network (SNN) modelling, neural population modelling, point processes in neuroscience, advanced analysis methods of multi-variate spike train and Ca2+-imaging data, analysis of intracellular electrophysiology, analysis of LFP and ECoG data

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