Abstract
In this study, we investigated the stages of information processing in associative recognition. We recorded EEG data while participants performed an associative recognition task that involved manipulations of word length, associative fan, and probe type, which were hypothesized to affect the perceptual encoding, retrieval, and decision stages of the recognition task, respectively. Analyses of the behavioral and EEG data, supplemented with classification of the EEG data using machine-learning techniques, provided evidence that generally supported the sequence of stages assumed by a computational model developed in the Adaptive Control of Thought-Rational cognitive architecture. However, the results suggested a more complex relationship between memory retrieval and decision-making than assumed by the model. Implications of the results for modeling associative recognition are discussed. The study illustrates how a classifier approach, in combination with focused manipulations, can be used to investigate the timing of processing stages.
Highlights
A longstanding interest of cognitive psychologists and neuroscientists has been the development of methods to identify different stages of human information processing
The frequency was higher for Fan 2 pairs than for Fan 1 pairs (3.4 vs. 1.4, respectively), reflecting a main effect of Fan, F(1, 19) = 15.48, mean squared prediction error (MSE) = 15.62, p < .01, this fan effect decreased across blocks, consistent with an interaction between Block and Fan, F(2, 38) = 9.41, MSE = 10.83, p
We conducted an EEG experiment that involved manipulations of word length, associative fan, and probe type, which were intended to tap the perceptual encoding, retrieval, and decision stages assumed by an Adaptive Control of Thought-Rational (ACT-R) model of associative recognition
Summary
A longstanding interest of cognitive psychologists and neuroscientists has been the development of methods to identify different stages of human information processing. The temporal precision afforded by recording neurally generated electrical signals on a millisecond basis allows researchers to determine whether, when, and for how long an experimental manipulation modulates the neural activity underlying cognitive processes, even in cases where the manipulation does not produce an effect on overall RT (Coles, 1988).
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