Visualization in the neurosciences: Seeing abstractions in real time

Gerry Leisman, Paul Koch

Research output: Contribution to journalReview articlepeer-review

Abstract

One explicit goal of visualization in the neurosciences is to present data to human observers in a way that is informative and meaningful, on the one hand, yet intuitive and effortless on the other. Multidimensional data visualization is concerned with the question "How can we display high-dimensional data elements in a low-dimensional environment, such as on a computer screen or the printed page?" This goal is often pursued by attaching "features" such as hue, intensity, spatial location, and size to each data element. Features are chosen to reveal properties of data elements as well as relationships among them. An ad hoc assignment of features to individual data dimensions may not result in a useful visualization tool. Indeed, too often the tool itself interferes with the viewer's ability to extract the desired information due to a poor choice of feature assignment. The articles presented in this issue address the concerns of representing data to better elucidate complex concepts in the neurosciences.

Original languageEnglish
Pages (from-to)373-380
Number of pages8
JournalInternational Journal of Neuroscience
Volume116
Issue number4
DOIs
StatePublished - Apr 2006

Bibliographical note

Funding Information:
One explicit goal of visualization in the neurosciences is to present data to human observers in a way that is informative and meaningful, on the one hand, yet intuitive and effortless on the other. Multidimensional data visualization is concerned with the question “How can we display high-dimensional data elements in a low-dimensional environment, such as on a computer screen or the printed page?” This goal is often pursued by attaching “features” such as hue, intensity, spatial location, and size to each data element. Features are chosen to reveal properties of data elements as well as relationships among them. An ad Received 17 February 2005. This work was supported in part by a grant-in-aid from the Foundation for Cognitive Neuroscience to the first author. Address correspondence to Dr. Gerry Leisman, Carrick Institute for Clinical Ergonomics, Rehabilitation, and Applied Neurosciences, 1700 Union Blvd., Bay Shore, NY 11706, USA. E-mail: drgersh@yahoo.com

Keywords

  • Computational medicine
  • Large scale computing
  • Modeling
  • Scientific visualization

ASJC Scopus subject areas

  • General Neuroscience

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