Abstract

A premise monotonicity effect during category-based induction is a robust effect, in which participants are more likely to generalize properties shared by many instances rather than those shared by few instances. Previous studies have shown the event-related potentials (ERPs) elicited by this effect. However, the neural oscillations in the brain underlying this effect are not well known, and such oscillations can convey task-related cognitive processing information which is lost in traditional ERP analysis. In the present study, the phase-locked and non-phase-locked power of neural oscillations related to this effect were measured by manipulating the premise sample size [single (S) vs. two (T)] in a semantic category-based induction task. For phase-locked power, the results illustrated that the premise monotonicity effect was revealed by anterior delta power, suggesting differences in working memory updating. The results also illustrated that T arguments evoked larger posterior theta-alpha power than S arguments, suggesting that T arguments led to enhanced subjectively perceived inductive confidence than S arguments. For non-phase-locked power, the results illustrated that the premise monotonicity effect was indicated by anterior theta power, suggesting that the differences in sample size were related to a change in the need for cognitive control and the implementation of adaptive cognitive control. Moreover, the results illustrated that the premise monotonicity effect was revealed by alpha-beta power, which suggested the unification of sentence and inference-driven information. Therefore, the neural oscillation profiles of the premise monotonicity effect during semantic category-based induction were elucidated, and supported the connectionist models of category-based induction.

Highlights

  • Category-based induction plays a significant role in human learning and adaptation (Anderson, 1991; Heit and Hayes, 2011), and involves exploiting knowledge about a property of the premise categories to infer the same property about the members of a conclusion category (Kemp and Jern, 2014; Hayes and Heit, 2018)

  • For phase-locked power we predicted that the premise monotonicity effect during semantic category-based induction would lead to changes in delta and theta-alpha band power, indexing working memory (WM) updating, subjectively perceived confidence, and cognitive processing facilitation

  • For non-phase-locked power, we predicted that the premise monotonicity effect during semantic category-based induction would lead to changes in theta and alpha-beta power, indexing cognitive control and unification respectively

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Summary

INTRODUCTION

Category-based induction plays a significant role in human learning and adaptation (Anderson, 1991; Heit and Hayes, 2011), and involves exploiting knowledge about a property of the premise categories to infer the same property about the members of a conclusion category (Kemp and Jern, 2014; Hayes and Heit, 2018). Cui et al (2018) measured the event-related potentials (ERPs) elicited by the premise monotonicity effect during categorybased induction to explore the timing of brain activity underlying this effect In their study, they manipulated the types of premise categories via displaying one (S arguments, e.g., tigers) or two types of premise categories (T arguments, e.g., tigers and lions) with a novel property (e.g., X1) in the arguments. For phase-locked power we predicted that the premise monotonicity effect during semantic category-based induction would lead to changes in delta and theta-alpha band power, indexing working memory (WM) updating, subjectively perceived confidence, and cognitive processing facilitation. For non-phase-locked power, we predicted that the premise monotonicity effect during semantic category-based induction would lead to changes in theta and alpha-beta power, indexing cognitive control and unification respectively. We predicted that T arguments would generate lower (larger) alpha-beta power than S arguments in a relatively early (late) period

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Behavioral Results
ERP Results
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DATA AVAILABILITY STATEMENT
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