Project INF
Data Management for Computational Modelling
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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:
©Forschungszentrum Jülich, Sascha Kreklau
Prof. Dr. Silvia daun
Principal Investigator
Project
Mathematical modelling, neural oscillator models, phase oscillators, dynamical systems, bifurcation theory, dynamic causal modelling (DCM), inter-area connectivitiy, development of analysis tools for EEG / MEG data
©MedizinFotoKöln
Prof. dr. Michael Hanke
Principal Investigator
Project
Functional neuroimaging, machine learning, high-throughput computing, FAIR data management, open-source software development
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Prof. Dr. Martin Nawrot
Principal Investigator
Project
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
©MedizinFotoKöln
Dr. Michal Szczepanik
Postdoc
Project
FAIR data management, open-source software development, communication
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DR. MAHAN HOSSEINI
Postdoc
Project
AutoGaitA – Automated Gait Analysis in Python
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Gina Schumacher
PhD candidate
Project
INF Expert Team
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Dr. Paola Mengotti
Principal Investigator
Project
Computational modelling of behavioural data (response times), Bayesian learning schemes
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Prof. Dr. Simon Eickhoff
Principal Investigator
Project
MRI processing and data analytics (morphometry, functional connectivity, activation), machine learning & predictive modelling
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Prof. Dr. Marc Tittgemeyer
Principal Investigator
Project
Computational modelling, modelling of structural and functional neuroimaging data, homeostatic model, body-brain interaction
©MedizinFotoKöln
Prof. Simone Vossel
Principal Investigator
Project
Coputational modelling of behavioural data (response times), Bayesian learning schemes, Dynamic Causal Modelling for fMRI data
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Dr. Lionel Rigoux
Senior Postdoc
Project
Statistics, Bayesian modelling, nonlinear models for neurobiological and behavioural data, modelling of decision processes
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Dr. Vahid Rostami
Senior Postdoc
Project
Functional spiking neural network (SNN) modelling, advanced methods of multi-variate spike train analysis, Machine Learning (ML), Deep Learning (DL)
©MedizinFotoKöln
Dr. Azamat Yeldesbay
Senior Postdoc
Project
Mathematical modelling, phase oscillators, dynamic causal modelling, development of analysiss tools for EGG / MEG