TY  - CONF
AU  - Denker, Michael
TI  - Orchestrating analysis workflows using Elephant and Neo.
M1  - FZJ-2021-02239
PY  - 2021
AB  - In order to deal with the increasing complexity of data from electrophysiological experiments and spiking neural network simulations, concepts and tools to perform data acquisition and analysis in a reproducible fashion are in high demand. Here, following [1], we demonstrate open-source software solutions that support such workflows, each addressing different aspects of the process: (i) electrophysiological data of different origins are represented in a standard description using Neo (RRID:SCR_000634) [2], (ii) complex metadata accumulating in the electrophysiological experiment [3] are organized [4] using the open metadata markup language (odML, RRID:SCR_001376) [5], and (iii) analysis is performed using the Electrophysiology Analysis Toolkit (Elephant, RRID:SCR_003833, http://python-elephant). Elephant acts as the central modular software component that provides generic library functions to perform standard and advanced analysis methods for parallel, multi-scale activity data. We outline how the integration of such workflows into the EBRAINS infrastructure facilitates interdisciplinary, collaborative work including access to high-performance computing. In particular, we demonstrate how such tools form the basis for rigorous approaches to model validation [6].
T2  - NeuroFrance 2021
CY  - 19 May 2021 - 21 May 2021, Online (Online)
Y2  - 19 May 2021 - 21 May 2021
M2  - Online, Online
LB  - PUB:(DE-HGF)6
UR  - https://juser.fz-juelich.de/record/892653
ER  -