Information-processing architectures in multidimensional classification: a validation test of the systems factorial technology.
A growing methodology, known as the systems factorial technology (SFT), is being developed to diagnose the types of information-processing architectures (serial, parallel, or coactive) and stopping rules (exhaustive or self-terminating) that operate in tasks of multidimensional perception. Whereas most previous applications of SFT have been in domains of simple detection and visual-memory search, this research extends the applications to foundational issues in multidimensional classification. Experiments are conducted in which subjects are required to classify objects into a conjunctive-rule category structure. In one case the stimuli vary along highly separable dimensions, whereas in another case they vary along integral dimensions. For the separable-dimension stimuli, the SFT methodology revealed a serial or parallel architecture with an exhaustive stopping rule. By contrast, for the integral-dimension stimuli, the SFT methodology provided clear evidence of coactivation. The research provides a validation of the SFT in the domain of classification and adds to the list of converging operations for distinguishing between separable-dimension and integral-dimension interactions.
Fific
Mario
M
Department of Psychology and Brian Sciences, Indiana University, Bloomington, IN 47405, USA. mfific@indiana.edu
Nosofsky
Robert M
RM
Townsend
James T
JT
D000328:Adult; D000704:Analysis of Variance; D002965:Classification; D003119:Color Perception Tests; D019295:Computational Biology / Q000379:methods*; D004192:Discrimination, Psychological / Q000502:physiology*; D006801:Humans; D008606:Mental Processes / Q000502:physiology*; D008959:Models, Neurological; D010465:Perception / Q000502:physiology*; D010775:Photic Stimulation / Q000379:methods; D021641:Recognition, Psychology / Q000502:physiology; D012016:Reference Values