Linked Life Data

15935616

Source:http://linkedlifedata.com/resource/pubmed/id/15935616

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
7
pubmed:dateCreated
2005-9-9
pubmed:abstractText
The development of neural network models has greatly enhanced the comprehension of cognitive phenomena. Here, we show that models using multiplicative processing of inputs are both powerful and simple to train and understand. We believe they are valuable tools for cognitive explorations. Our model can be viewed as a subclass of networks built on sigma-pi units and we show how to derive the Kronecker product representation from the classical sigma-pi unit. We also show how the connectivity requirements of the Kronecker product can be relaxed considering statistical arguments. We use the multiplicative network to implement what we call an Elman topology, that is, a simple recurrent network (SRN) that supports aspects of language processing. As an application, we model the appearance of hallucinated voices after network damage, and show that we can reproduce results previously obtained with SRNs concerning the pathology of schizophrenia.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0893-6080
pubmed:author
pubmed:issnType
Print
pubmed:volume
18
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
863-77
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Elman topology with sigma-pi units: an application to the modeling of verbal hallucinations in schizophrenia.
pubmed:affiliation
Sección Biofísica, Facultad de Ciencias, Universidad de la República, Iguá 4225, Montevideo 11400, Uruguay. juancvl@fcien.edu.uy
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't