Neural correlates of deductive reasoning: An ERP study with the Wason Selection Task

• Published in: International journal of psychophysiology 2015-12, Vol.98 (3), p.381-388
• Main Authors: Cutmore, Tim R.H., Halford, Graeme S., Wang, Ya, Ramm, Brentyn J., Spokes, Tara, Shum, David H.K.
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Brain - physiology; Brain Mapping; Choice Behavior - physiology; Cognitive conflict; Complexity; Conditional reasoning; Deductive reasoning; Electroencephalography; Event-related potentials; Evoked Potentials - physiology; Female; Functional Laterality; Humans; Male; Photic Stimulation; Problem Solving - physiology; Young Adult
• ISSN: 0167-8760; 1872-7697
• DOI: 10.1016/j.ijpsycho.2015.07.004

The Wason Selection Task (WST) is a well-known test of reasoning in which one turns over cards to test a rule about the two faces. Modifications were made to the WST to enable more direct and analytical investigation of reasoning processes. The modifications included extensive training to reduce variations in task interpretation, isolation of working memory in the decision phase, a separate rule for each card and variations in the form of the rule (number-letter as well as letter-number), separate scoring for each card, and inclusion of control cards that could be recognized by features without relational processing. The cognitive complexity of each card was also analyzed to enable investigation of this factor. Behavioral and event-related potential data were recorded. Negative cards differed from positive cards and control cards were differentiated from cards involved in inferences. The N2 component differentiated the negative conditions (not-P, not-Q cards) from the positive conditions (P, Q cards). The P3 component was largest for control and P cards (the simpler conditions). The late slow wave tended to show more sustained processing of not-P, not-Q and Q cards and was little influenced by the simpler control and P cards. Effects were interpreted in terms of cognitive complexity. In particular, the negative conditions had a larger N2 response than the positive conditions, reflecting greater cognitive complexity of the former and their sustained processing. •High error rates common to the WST were overcome by our training procedure.•N2 differentiated negative (not-P, not-Q) from positive (P, Q) conditions.•P3 component was largest for control and P cards (the simpler conditions).•Slow wave component may reflect sustained processing of complex conditions.