We propose that the intriguing bow effects in choice probabilities and
response times that are found in unidimensional absolute identificati
on might be a consequence of the mapping process required when a unidi
mensional psychological representation is mapped to a multidimensional
response vector. This idea builds on previous work by Lacouture & Mar
ley (1991) which modeled absolute identification using a connectionist
feed-forward network. A formal solution of the so-called ''encoder pr
oblem'' is the basis of the approach, and the inclusion in the model o
f ''noisy'' mappings and integrators allows us to model both the respo
nses made and the time to make them. The simulated model reproduces se
veral of the phenomenon in unidimensional absolute identification incl
uding bow, range, and some sequential effects. (C) 1995 Academic Press
, Inc.