Parallel distributed processing and neuropsychology: a neural network model of Wisconsin Card Sorting and verbal fluency.
Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.
Parks
R W
RW
Laboratory of Clinical Science, National Institute of Mental Health, Bethesda, Maryland.
Levine
D S
DS
Long
D L
DL
Crockett
D J
DJ
Dalton
I E
IE
Weingartner
H
H
Fedio
P
P
Coburn
K L
KL
Siler
G
G
Matthews
J R
JR
D001288:Attention / Q000502:physiology*; D001925:Brain Damage, Chronic / Q000503:physiopathology*; D004193:Discrimination Learning / Q000502:physiology*; D005625:Frontal Lobe / Q000503:physiopathology; D006801:Humans; D011939:Mental Recall / Q000502:physiology*; D016571:Neural Networks, Computer; D009483:Neuropsychological Tests / Q000706:statistics & numerical data*; D011594:Psychometrics; D009435:Synaptic Transmission / Q000502:physiology