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Related Experiment Video

Updated: Jun 8, 2026

STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces

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iRaster: a novel information visualization tool to explore spatiotemporal patterns in multiple spike trains.

J Somerville¹, L Stuart, E Sernagor

¹School of Computing and Mathematics, University of Plymouth, Plymouth, UK. jared.somerville@plymouth.ac.uk

Journal of Neuroscience Methods

|September 30, 2010

Summary

Neuroscientists can now analyze multiple spike trains with iRaster, a visual analytics tool. This software helps uncover neural activity patterns like synchronization and propagation for better system function insights.

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A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

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Last Updated: Jun 8, 2026

STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces

STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces

Published on: March 10, 2026

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'

Published on: February 10, 2017

Area of Science:

Neuroscience
Computer Science
Data Visualization

Background:

Simultaneous recordings of multiple spike trains are increasingly common in neuroscience.
Analyzing complex neural data requires advanced computational tools.

Purpose of the Study:

To introduce iRaster, an interactive visual analytics tool for analyzing multiple spike trains.
To demonstrate how visual analytics techniques can reveal patterns in neural activity.

Main Methods:

Development of iRaster, an interactive raster plot software.
Incorporation of statistical procedures for visualization and manipulation of spike trains.
Implementation of features such as re-ordering, rate representation, coordinated views, and zooming.

Main Results:

iRaster effectively visualizes and analyzes multiple spike trains, uncovering patterns like activity propagation and synchronization.
The tool supports flexible data manipulation and diverse visual representations.
Successful analysis of both synthetic and experimental datasets, including mouse retinal multi-electrode recordings.

Conclusions:

iRaster is a user-friendly, flexible tool for neuroscientists to explore and analyze multi-spike train data.
Visual analytics offers powerful methods for gaining new insights into neural system function.
The iRaster software is freely available as part of the VISA project.