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NeoAnalysis: a Python-based toolbox for quick electrophysiological data processing and analysis
- Source :
- BioMedical Engineering OnLine, Vol 16, Iss 1, Pp 1-17 (2017), BioMedical Engineering
- Publication Year :
- 2017
- Publisher :
- Springer Science and Business Media LLC, 2017.
-
Abstract
- Background In a typical electrophysiological experiment, especially one that includes studying animal behavior, the data collected normally contain spikes, local field potentials, behavioral responses and other associated data. In order to obtain informative results, the data must be analyzed simultaneously with the experimental settings. However, most open-source toolboxes currently available for data analysis were developed to handle only a portion of the data and did not take into account the sorting of experimental conditions. Additionally, these toolboxes require that the input data be in a specific format, which can be inconvenient to users. Therefore, the development of a highly integrated toolbox that can process multiple types of data regardless of input data format and perform basic analysis for general electrophysiological experiments is incredibly useful. Results Here, we report the development of a Python based open-source toolbox, referred to as NeoAnalysis, to be used for quick electrophysiological data processing and analysis. The toolbox can import data from different data acquisition systems regardless of their formats and automatically combine different types of data into a single file with a standardized format. In cases where additional spike sorting is needed, NeoAnalysis provides a module to perform efficient offline sorting with a user-friendly interface. Then, NeoAnalysis can perform regular analog signal processing, spike train, and local field potentials analysis, behavioral response (e.g. saccade) detection and extraction, with several options available for data plotting and statistics. Particularly, it can automatically generate sorted results without requiring users to manually sort data beforehand. In addition, NeoAnalysis can organize all of the relevant data into an informative table on a trial-by-trial basis for data visualization. Finally, NeoAnalysis supports analysis at the population level. Conclusions With the multitude of general-purpose functions provided by NeoAnalysis, users can easily obtain publication-quality figures without writing complex codes. NeoAnalysis is a powerful and valuable toolbox for users doing electrophysiological experiments. Electronic supplementary material The online version of this article (10.1186/s12938-017-0419-7) contains supplementary material, which is available to authorized users.
- Subjects :
- 0301 basic medicine
Offline sorting
lcsh:Medical technology
Computer science
Spike train
Biomedical Engineering
Spike
computer.software_genre
Data type
Saccade detection
Biomaterials
User-Computer Interface
03 medical and health sciences
0302 clinical medicine
Data visualization
Data acquisition
Saccades
Humans
Radiology, Nuclear Medicine and imaging
NeoAnalysis
computer.programming_language
Data processing
Radiological and Ultrasound Technology
business.industry
Signal Processing, Computer-Assisted
General Medicine
Python (programming language)
Toolbox
Electrophysiological Phenomena
Electrophysiology
030104 developmental biology
lcsh:R855-855.5
Spike sorting
Data mining
business
computer
Software
Algorithms
Analysis
030217 neurology & neurosurgery
Python
Subjects
Details
- ISSN :
- 1475925X
- Volume :
- 16
- Database :
- OpenAIRE
- Journal :
- BioMedical Engineering OnLine
- Accession number :
- edsair.doi.dedup.....aabd278164a44c27ef466f8aace0962d