Predicting human cortical connectivity for language areas using the Conel database

Ryuta Fukuda, Junko Hara, William R. Shankle, Toshio Inui, Masaru Tomita

Research output: Contribution to conferencePaper

Abstract

Connectivity between language-related Brodmann areas derived from analyses of data source provided by J. L. Conel has been proposed. The analysis consisted of computing the correlation coefficients between each layer of one cortical area to each layer of another cortical area over the 8 age points. A `connection' was created between two layers of two cortical areas if: 1) its z-score have significance level less than 20%; and 2) the two layers began myelinating at the same age point. Predicted connections are consistent with neural network models derived neuroimaging, psychological tests, and also support some seemingly unusual findings reported by others.

Original languageEnglish
Pages293-295
Number of pages3
Publication statusPublished - 1999 Dec 1
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: 1999 Jul 101999 Jul 16

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA
Period99/7/1099/7/16

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ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Fukuda, R., Hara, J., Shankle, W. R., Inui, T., & Tomita, M. (1999). Predicting human cortical connectivity for language areas using the Conel database. 293-295. Paper presented at International Joint Conference on Neural Networks (IJCNN'99), Washington, DC, USA, .