Abstract
The description of neural dynamics, in terms of precise characterizations of action potential timings and shape and voltage related measures, is fundamental for a deeper understanding of the neural code and its information content. Not only such measures serve the scientific questions posed by experimentalists but are increasingly being used by computational neuroscientists for the construction of biophysically detailed data-driven models. Nonetheless, online resources enabling users to perform such feature extraction operation are lacking. To address this problem, in the framework of the Human Brain Project and the EBRAINS research infrastructure, we have developed and made available to the scientific community the NeuroFeatureExtract, an open-access online resource for the extraction of electrophysiological features from neural activity data. This tool allows to select electrophysiological traces of interest, fetched from public repositories or from users’ own data, and provides ad hoc functionalities to extract relevant features. The output files are properly formatted for further analysis, including data-driven neural model optimization.
Highlights
Data analysis of electrophysiological traces is at the core of a wide range of studies in the neuroscientific field
The broader is the range of electrophysiological features extracted from the experimental observations, the more precise and biophysically detailed is the computational model based on those features
The web application consists of a frontend and a backend components that, despite residing on the same Virtual Machine (VM), are logically separated and communicate through dedicated Representational State Transfer (REST) Application Programmer Interface (API) calls
Summary
Data analysis of electrophysiological traces is at the core of a wide range of studies in the neuroscientific field. The platform allows to: (1) upload any kind of neural models -which must be provided with ad hoc scripts to test their correct functioning; (2) label them; (3) run them on a dedicated simulation platform; (4) annotate, for each model, the relevant and/or relative scientific publications. Another collaborative public online resource is OpenSourceBrain (OSB) (Gleeson et al, 2019). OSB provides visualization, simulation, analysis, and sharing tools and services for standardized neural models. The web application leverages the Electrophys Feature Extract Library (eFEL) and the BluePyEfe library (see section Methods/eFEL and Methods/BluePyEfe) and provides result files properly formatted for further analysis (e.g., neural model optimization via the BluePyOpt optimization library, see section “Methods”)
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