Visualisation of synchronous firing in multi-dimensional spike trains.

L Stuart; M Walter; R Borisyuk

doi:10.1016/s0303-2647(02)00084-9

Visualisation of synchronous firing in multi-dimensional spike trains.

L Stuart
, M Walter
, R Borisyuk

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

The gravity transform algorithm is used to study the dependencies in firing of multi-dimensional spike trains. The pros and cons of this algorithm are discussed and the necessity for improved representation of output data is demonstrated. Parallel coordinates are introduced to visualise the results of the gravity transform and principal component analysis (PCA) is used to reduce the quantity of data represented whilst minimising loss of information.

Original language	English
Pages (from-to)	265-279
Number of pages	15
Journal	BioSystems
Volume	67
Issue number	1-3
Early online date	23 Nov 2002
DOIs	https://doi.org/10.1016/s0303-2647(02)00084-9
Publication status	Published (in print/issue) - Dec 2002

Keywords

Multi-dimensional spike trains
Synchronous activity
Information visualisation
Parallel coordinates
Gravity transform
Principal component analysis

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10.1016/s0303-2647(02)00084-9

Cite this

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title = "Visualisation of synchronous firing in multi-dimensional spike trains.",

abstract = "The gravity transform algorithm is used to study the dependencies in firing of multi-dimensional spike trains. The pros and cons of this algorithm are discussed and the necessity for improved representation of output data is demonstrated. Parallel coordinates are introduced to visualise the results of the gravity transform and principal component analysis (PCA) is used to reduce the quantity of data represented whilst minimising loss of information.",

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AB - The gravity transform algorithm is used to study the dependencies in firing of multi-dimensional spike trains. The pros and cons of this algorithm are discussed and the necessity for improved representation of output data is demonstrated. Parallel coordinates are introduced to visualise the results of the gravity transform and principal component analysis (PCA) is used to reduce the quantity of data represented whilst minimising loss of information.

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KW - Synchronous activity

KW - Information visualisation

KW - Parallel coordinates

KW - Gravity transform

KW - Principal component analysis

UR - https://app.dimensions.ai/details/publication/pub.1015226517

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DO - 10.1016/s0303-2647(02)00084-9

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VL - 67

SP - 265

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JO - BioSystems

JF - BioSystems

IS - 1-3

ER -

Visualisation of synchronous firing in multi-dimensional spike trains.

Abstract

Keywords

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