Title
Elman topology with sigma-pi units: An application to the modeling of verbal hallucinations in schizophrenia
Abstract
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.
Year
DOI
Venue
2005
10.1016/j.neunet.2005.03.009
Neural Networks
Keywords
Field
DocType
schizophrenia,neural network model,kronecker product
Topology,Kronecker product,Multiplicative function,Hallucinated,Artificial intelligence,Sigma,Artificial neural network,Cognition,Machine learning,Comprehension,Mathematics,Schizophrenia
Journal
Volume
Issue
ISSN
18
7
0893-6080
Citations 
PageRank 
References 
8
0.59
12
Authors
4
Name
Order
Citations
PageRank
Juan C. Valle-Lisboa1214.11
Florencia Reali2519.91
Héctor Anastasía380.59
Eduardo Mizraji4518.82