Building a virtual archive using brain architecture and Web 3D to deliver neuropsychopharmacology content over the Internet

  • Authors:
  • R. Mongeau;M. A. Casu;L. Pani;G. Pillolla;L. Lianas;A. Giachetti

  • Affiliations:
  • Neuroscienze Pharmaness, Scientific and Technological Park of Sardinia, Sardegna Ricerche, Building #5, Pula, Italy;Neuroscienze Pharmaness, Scientific and Technological Park of Sardinia, Sardegna Ricerche, Building #5, Pula, Italy;Neuroscienze Pharmaness, Scientific and Technological Park of Sardinia, Sardegna Ricerche, Building #5, Pula, Italy and Institute of Biomedical Technologies, C.N.R., Milan, Italy;Department of Neuroscience B.B. Brodie, University of Cagliari, Italy;Center for Research and Study (CRS4), Scientific and Technological Park of Sardinia, Sardegna Ricerche, Building #1, Pula, Italy;Center for Research and Study (CRS4), Scientific and Technological Park of Sardinia, Sardegna Ricerche, Building #1, Pula, Italy and Department of Computer Science, University of Verona, Italy

  • Venue:
  • Computer Methods and Programs in Biomedicine
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

The vast amount of heterogeneous data generated in various fields of neurosciences such as neuropsychopharmacology can hardly be classified using traditional databases. We present here the concept of a virtual archive, spatially referenced over a simplified 3D brain map and accessible over the Internet. A simple prototype (available at http://aquatics.crs4.it/neuropsydat3d) has been realized using current Web-based virtual reality standards and technologies. It illustrates how primary literature or summary information can easily be retrieved through hyperlinks mapped onto a 3D schema while navigating through neuroanatomy. Furthermore, 3D navigation and visualization techniques are used to enhance the representation of brain's neurotransmitters, pathways and the involvement of specific brain areas in any particular physiological or behavioral functions. The system proposed shows how the use of a schematic spatial organization of data, widely exploited in other fields (e.g. Geographical Information Systems) can be extremely useful to develop efficient tools for research and teaching in neurosciences.