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NeuroscienceNeuroinformatics
Peer-reviewed journal article

Porthole and Stormcloud: Tools for visualisation of spatiotemporal M/EEG statistics

Jeremy A TayloriD, Marta Isabel GarridoiD

Abstract

Electro- and magneto-encephalography are functional neuroimaging modalities characterised by their ability to quantify dynamic spatiotemporal activity within the brain. However, the visualisation techniques currently used to illustrate these effects are currently limited to single- or multi-channel time series plots, topographic scalp maps and orthographic cross-sections of the spatiotemporal data structure. Whilst these methods each have their own strength and weaknesses, they are only able to show a subset of the data and are suboptimal at articulating one or both of the space-time components. Here, we propose Porthole and Stormcloud, a set of data visualisation tools which can automatically generate context appropriate graphics for both print and screen with the following graphical capabilities: O_LIAnimated two-dimensional scalp maps with dynamic timeline annotation and optional user interaction; C_LIO_LIThree-dimensional construction of discrete clusters within sparse spatiotemporal volumes, rendered with cloud-like appearance and augmented by cross-sectional scalp maps indicating local maxima. C_LI These publicly available tools were designed specifically for visualisation of M/EEG spatiotemporal statistical maps, however, we also demonstrate alternate use cases of posterior probability maps and weight maps produced by machine learning classifiers. In principle, the methods employed here are transferrable to visualisation of any spatiotemporal image.

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02 /Specification & Classification

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