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Chaitanya Chintaluri

Researcher at Nencki Institute of Experimental Biology

Publications -  15
Citations -  468

Chaitanya Chintaluri is an academic researcher from Nencki Institute of Experimental Biology. The author has contributed to research in topics: Computational neuroscience & Network model. The author has an hindex of 7, co-authored 14 publications receiving 218 citations. Previous affiliations of Chaitanya Chintaluri include Institute of Science and Technology Austria & University of Oxford.

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Training deep neural density estimators to identify mechanistic models of neural dynamics

Pedro J. Gonçalves, +17 more
- 18 Nov 2019 - 
TL;DR: A machine learning tool that uses density estimators based on deep neural networks— trained using model simulations—to infer data-compatible parameters for a wide range of mechanistic models will help close the gap between data-driven and theory-driven models of neural dynamics.
Journal ArticleDOI

Training deep neural density estimators to identify mechanistic models of neural dynamics.

Pedro J. Gonçalves, +19 more
- 17 Sep 2020 - 
TL;DR: A machine learning tool which uses deep neural density estimators—trained using model simulations—to carry out Bayesian inference and retrieve the full space of parameters compatible with raw data or selected data features, which will help close the gap between data-driven and theory-driven models of neural dynamics.
Journal ArticleDOI

Modelling and Analysis of Electrical Potentials Recorded in Microelectrode Arrays (MEAs)

Torbjørn V. Ness, +7 more
- 31 Mar 2015 - 
TL;DR: A biophysical forward-modelling formalism based on the finite element method (FEM) is used to establish quantitatively accurate links between neural activity in the slice and potentials recorded in the MEA set-up, and methods for estimation of current-source density (CSD) from MEA potentials are explored.
Journal ArticleDOI

25th Annual Computational Neuroscience Meeting: CNS-2016

Tatyana O. Sharpee, +738 more
- 18 Aug 2016 - 

25th Annual Computational Neuroscience Meeting: CNS-2016

Tatyana O. Sharpee, +582 more
TL;DR: Table of contents Functional advantages of cell-type heterogeneity in neural circuits, Dynamics and biomarkers of mental disorders, and Objective criteria for computational neuroscience model selection are presented.