DocumentCode
1136451
Title
Automatic Relevance Determination for Identifying Thalamic Regions Implicated in Schizophrenia
Author
Browne, Antony ; Jakary, Angela ; Vinogradov, Sophia ; Fu, Yu ; Deicken, Raymond F.
Author_Institution
Comput. Dept., Univ. of Surrey, Guildford
Volume
19
Issue
6
fYear
2008
fDate
6/1/2008 12:00:00 AM
Firstpage
1101
Lastpage
1107
Abstract
There have been many theories about and computational models of the Schizophrenic disease state. Brain imaging techniques have suggested that abnormalities of the Thalamus may contribute to the pathophysiology of Schizophrenia. Several studies have found the Thalamus to be altered in Schizophrenia, and the Thalamus has connections with other brain structures implicated in the disorder. This paper describes an experiment examining thalamic levels of the metabolite N-acetylaspartate (NAA), taken from schizophrenics and controls using in vivo proton magnetic resonance spectroscopic imaging. Automatic relevance determination was performed on neural networks trained on this data, identifying NAA group differences in the pulvinar and mediodorsal nucleus, underscoring the importance of examining thalamic subregions in schizophrenia.
Keywords
biomedical MRI; brain; learning (artificial intelligence); magnetic resonance spectroscopy; neural nets; Schizophrenic disease; automatic relevance determination; brain imaging techniques; in vivo proton magnetic resonance spectroscopic imaging; mediodorsal nucleus; metabolite N-acetylaspartate; neural networks; pathophysiology; thalamic regions; Aspartic Acid; Brain Mapping; Choline; Humans; Image Processing, Computer-Assisted; Linear Models; Magnetic Resonance Spectroscopy; Male; Nerve Net; Protons; Schizophrenia; Thalamus;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/TNN.2008.2000203
Filename
4493273
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