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Neurophysiological analytics for all! Free open-source software tools for documenting, analyzing, visualizing, and sharing using electronic notebooks
Internal Dataset

UID: 27

Author(s): Rosenberg, David M., Horn, Charles C.*+ * Corresponding Author + University of Pittsburgh Author
Description
This Github repository contains raw data and code to explore open-source neurophysiology data analysis tools within an included Jupyter notebook. Software dependencies are listed within each data supplement folder, and can be downloaded with Docker via the associated Github repository described in the related data catalog record: Software: Docker image with JupyterLab, Python 3, Python 2, and R. The supplementary data were collected from electrophysiological recordings of the musk shrew vagus, a model system to investigate gut-brain communication.
Keywords
Electronic Lab Notebooks
Electrophysiology
Neurophysiology
Software
Access via Github

Data files, full list of dependencies, and author-supplied instructions and information.

Access Restrictions
Free to all
Access Instructions
Download data files or access Binder link through Github. More information and instructions are available through the associated publication.
Associated Publications
Rosenberg DM, Horn CC. Neurophysiological analytics for all! Free open-source software tools for documenting, analyzing, visualizing, and sharing using electronic notebooks. J Neurophysiol. 2016 Aug 1;116(2):252-62. doi: 10.1152/jn.00137.2016. Epub 2016 Apr 20. PMID: 27098025; PMCID: PMC4969392.
Data Type
Electrophysiological
Software Used
ez

R package for analysis of factorial experiments.

ggplot2

R package for data visualization.

Jupyter Notebook

App to create, edit, and run documents containing computer code and rich text.

Matplotlib

Python 2D plotting library.

Neo

Python module for loading and saving multiple electrophysiology data formats.

NumPy

Python scientific computing package.

OpenElectrophy

Python module for electrophysiology data analysis.

pandas

Open-source data analysis Python library.

plyr

R package for splitting, applying, and combining data.

Python

Open-source interpreted, interactive, object-oriented programming language.

quantities

Python package for arithmetic and conversions of physical quantities.

R

Free software environment for statistical computing and graphics.

reshape2

R package to restructure and aggregate data.

rpy2

Interface for using R within Python.

scikit-learn

Python module for machine learning.

SciPy

Collection of Python software for scientific computing, including NumPy and pandas.

Spike2

Multi-channel continuous data acquisition and analysis package

STAR

R package to analyze spike trains.

Dataset Format(s)
CSV (.csv), TXT (.txt), PY (.py), Spike2 data (.smr, .smrx), IPYNB (.ipynb), Spike2 resource (.s2r, .s2rx)
Resource Type(s)
Software
Dataset Size
8.61 MB
Grant Support
U18 EB021772/NIBIB
P30 CA047904/NCI
Data Catalog Record Updated
2021-02-09

Notice and Disclaimer: Please note that the information in this catalog is provided as a courtesy, as is, and with no representations or warranties of any kind. When you contact the responsible individual(s) listed in each record, or, where applicable, access a data repository listed, you will be subject to terms and conditions required by the data custodian/data repository. The University of Pittsburgh does not attempt to judge the scholarly quality of the data referenced and relies on the judgment and research expertise of those who created and/or deposited it.