Abstract:
:The richness and complexity of data sets acquired from PET or fMRI studies of human cognition have not been exploited until recently by computational neural-modeling methods. In this article, two neural-modeling approaches for use with functional brain imaging data are described. One, which uses structural equation modeling, estimates the functional strengths of the anatomical connections between various brain regions during specific cognitive tasks. The second employs large-scale neural modeling to relate functional neuroimaging signals in multiple, interconnected brain regions to the underlying neurobiological time-varying activities in each region. Delayed match-to-sample (visual working memory for form) tasks are used to illustrate these models.
journal_name
Trends Cogn Scijournal_title
Trends in cognitive sciencesauthors
Horwitz B,Tagamets MA,McIntosh ARdoi
10.1016/s1364-6613(99)01282-6subject
Has Abstractpub_date
1999-03-01 00:00:00pages
91-98issue
3eissn
1364-6613issn
1879-307Xpii
S1364-6613(99)01282-6journal_volume
3pub_type
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