Deductive and inductive reasoning are fundamental logical processes critical to the solution of common practical problems in daily life. We used functional magnetic resonance imaging (fMRI) to investigate the brain networks involved in Contradictory, Deductive, and Inductive judgments. The experimental paradigm was based on categorical propositions of the Aristotelian Square of Opposition (ASoO). In a full factorial design, identical sentences were combined into premise–conclusion pairs. Each sentence started with ‘every’ or ‘some’. The order of the two propositions in the pair created two types of logical operators (every→some: deductive, or some→every: inductive). The descriptive attributes of the category could be Contradictory or non-Contradictory. Imaging data was analyzed using Group Independent component analysis of fMRI Toolbox (GIFT). Connectivity of nodes within four intrinsic connectivity networks (ICNs) was sensitive to attribute manipulation (Contradiction): the anterior default mode network (aDMN), and the language and cerebellum networks were more involved in Contradictory than non-Contradictory statements, while the anterior salience network (aSN) showed the opposite pattern. Five networks were associated with logical operator manipulation. Stronger positive associations with Inductive than Deductive reasoning were observed in the dorsal and ventral parts of the aDMN, aSN, and orbitofrontal networks (OFN). A stronger negative association with deductive than inductive reasoning was observed in the executive control (ExCN) and dorsal attention (DAN) networks. Differences in the fractional amplitude of low‐frequency fluctuation of the BOLD signal in aDMN, ExCN, and OFN explained 67% of the variance of the behavioural cost of inductive relative to deductive reasoning. The results suggest that different ICNs support logical reasoning and conflict identification. Finally, the magnitude of the differences was positively correlated with behavioural cost.
Frontal Intrinsic Connectivity Networks Support Contradiction Identification During Inductive and Deductive Reasoning
Porcaro C.
2022
Abstract
Deductive and inductive reasoning are fundamental logical processes critical to the solution of common practical problems in daily life. We used functional magnetic resonance imaging (fMRI) to investigate the brain networks involved in Contradictory, Deductive, and Inductive judgments. The experimental paradigm was based on categorical propositions of the Aristotelian Square of Opposition (ASoO). In a full factorial design, identical sentences were combined into premise–conclusion pairs. Each sentence started with ‘every’ or ‘some’. The order of the two propositions in the pair created two types of logical operators (every→some: deductive, or some→every: inductive). The descriptive attributes of the category could be Contradictory or non-Contradictory. Imaging data was analyzed using Group Independent component analysis of fMRI Toolbox (GIFT). Connectivity of nodes within four intrinsic connectivity networks (ICNs) was sensitive to attribute manipulation (Contradiction): the anterior default mode network (aDMN), and the language and cerebellum networks were more involved in Contradictory than non-Contradictory statements, while the anterior salience network (aSN) showed the opposite pattern. Five networks were associated with logical operator manipulation. Stronger positive associations with Inductive than Deductive reasoning were observed in the dorsal and ventral parts of the aDMN, aSN, and orbitofrontal networks (OFN). A stronger negative association with deductive than inductive reasoning was observed in the executive control (ExCN) and dorsal attention (DAN) networks. Differences in the fractional amplitude of low‐frequency fluctuation of the BOLD signal in aDMN, ExCN, and OFN explained 67% of the variance of the behavioural cost of inductive relative to deductive reasoning. The results suggest that different ICNs support logical reasoning and conflict identification. Finally, the magnitude of the differences was positively correlated with behavioural cost.
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