Different neural systems contribute to semantic bias and conflict detection in the inclusion fallacy task

Dual-Process Theory of Thought and Inhibitory Control: An ALE Meta-Analysis

The dual-process theory of thought rests on the co-existence of two different thinking modalities: a quick, automatic, and associative process opposed to a slow, thoughtful, and deliberative process. The increasing interest in determining the neural foundation of the dual-process distinction has yielded mixed results, also given the difficulty of applying the fMRI standard approach to tasks usually employed in the cognitive literature. We report an activation likelihood estimation (ALE) meta-analysis to investigate the neural foundation of the dual-process theory of thought. Eligible studies allowed for the identification of cerebral areas associated with dual-process theory-based tasks without differentiating between fast and slow thinking. The ALE algorithm converged on the medial frontal cortex, superior frontal cortex, anterior cingulate cortex, insula, and left inferior frontal gyrus. These structures partially overlap with the cerebral areas recurrently reported in the literature about the neural basis of the dual-process distinction, where the PARCS theory-based interpretation emphasizes the role of the right inferior gyrus. The results confirm the potential (but still almost unexplored) common ground between the dual-process literature and the cognitive control literature.

Involvement of the Right Dorsolateral Prefrontal Cortex in Numerical Rule Induction: A Transcranial Direct Current Stimulation Study

Numerical inductive reasoning has been considered as one of the most important higher cognitive functions of the human brain. Importantly, previous behavioral studies have consistently reported that one critical component of numerical inductive reasoning is checking, which often occurs when a discrepant element is discovered, and reprocessing is needed to determine whether the discrepancy is an error of the original series. However, less is known about the neural mechanism underlying the checking process. Given that the checking effect involves cognitive control processes, such as the incongruent resolution, that are linked to the right dorsolateral prefrontal cortex (DLPFC), this study hypothesizes that the right DLPFC may play a specific role in the checking process. To test the hypothesis, this study utilized the transcranial direct current stimulation (tDCS), a non-invasive brain stimulation method that could modulate cortical excitability, and examined whether and how the stimulation of the right DLPFC via tDCS could modulate the checking effect during a number-series completion problem task. Ninety healthy participants were allocated to one of the anodal, cathodal, and sham groups. Subjects were required to verify whether number sequences formed rule-based series, and checking effect was assessed by the difference in performance between invalid and valid conditions. It was found that significantly longer response times (RTs) were exhibited in invalid condition compared with valid condition in groups of anodal, cathodal, and sham tDCS. Furthermore, the anodal tDCS significantly shortened the checking effect than those of the cathodal and sham groups, whereas no significantly prolonged checking effect was detected in the cathodal group. The current findings indicated that anodal tDCS affected the process of checking, which suggested that the right DLPFC might play a critical role in the checking process of numerical inductive reasoning by inhibiting incongruent response.

P3a amplitude is related to conclusion specificity during category-based induction

Category-based induction involves the generalization of a novel property (conclusion property) to a new category (conclusion category), based on the knowledge that a category exemplar (premise category) has the respective novel property. Previous studies have shown that conclusion specificity (i.e., specific [S] or generic categories [G]) influences category-based induction. However, the timing of brain activity underlying this effect is not well known, especially with controlling the similarities of premise and conclusion categories between S and G arguments. In this study, the event-related potential (ERP) responses to category-based induction between S and G arguments were compared under both congruent (+, premise and conclusion categories are related) and incongruent (-, premise and conclusion categories are unrelated) arguments; additionally, the similarities of premise and conclusion categories between S and G arguments were controlled. The results showed that replicating this effect, S+ arguments have increased “strong” response rates compared to G+ arguments, suggesting that category-based induction is contingent on factors beyond matched similarities. Moreover, S arguments have more liberal inductive decision thresholds than G arguments, which suggest that conclusion specificity affects the inductive decision reflected by inductive decision thresholds. Furthermore, G+ arguments elicit greater P3a amplitudes than S+ arguments, which suggest greater attention resources allocation to the review of decisions for G+ arguments than that for S+ arguments. Taken together, the conclusion specificity effect during semantic category-based induction can be revealed by “strong” response rates, inductive decision thresholds, and P3a component after controlling the premise-conclusion similarity, providing evidence that category-based induction rely on more than simple similarity judgment and conclusion specificity would affect category-based induction.

Patients with Lesions to Left Prefrontal Cortex (BA 9 and BA 10) Have Less Entrenched Beliefs and Are More Skeptical Reasoners

The effect of prior beliefs on reasoning and decision-making is a robust, poorly understood phenomenon, exhibiting considerable individual variation. Neuroimaging studies widely show the involvement of the left pFC in reasoning involving beliefs. However, little patient data exist to speak to the necessity and role of the left pFC in belief-based inference. To address this shortcoming, we tested 102 patients with unilateral focal penetrating traumatic brain injuries and 49 matched controls. Participants provided plausibility ratings (plausible/implausible) to simple inductive arguments and (separately) strength of believability ratings of the conclusion to those same arguments. A voxel-based lesion symptom mapping analysis identified 10 patients, all with lesions to the left pFC (BA 9 and BA 10) as rating significantly fewer arguments with highly believable conclusions as "plausible," compared with all other patients. Subsequent analyses, incorporating the right hemisphere homologue of these patients (n = 12) and normal controls (n = 24), revealed patients with lesions to left pFC found fewer arguments plausible in the high believable than either of these groups, and there was no difference in the behavioral scores of the right pFC patients and normal controls. Further analysis, utilizing the belief ratings as the dependent measure, revealed a Group × Belief Rating interaction, with left pFC patients having less intense beliefs about the conclusions of moderately believable and highly believable arguments. We interpreted these results to indicate that lesions to left pFC (BA 9, BA 10) increase incredulity and make these patients more skeptical reasoners. The former can partially, but not fully, explain the latter. The other relevant factor may be that unilateral left pFC lesions disrupt hemispheric equilibrium and allow for an increased inhibitory role of the right pFC. We speculate that individual differences in belief bias in reasoning in the normal population may be a function of individual differences in the left and right pFC interactional dynamics.

Hemispheric asymmetry in the prefrontal cortex for complex cognition

With the exception of language, hemispheric asymmetry has not historically been an important issue in the frontal lobe literature. Data generated over the past 20 years is forcing a reconsideration of this position. There is now considerable evidence to suggest that the left prefrontal cortex is an inference engine that automatically makes simple conceptual, logical, and causal connections to fill in missing information and eliminate uncertainty or indeterminacy. This is a fine-tuning of the "left hemisphere interpreter" account from the callosotomy patient literature. What is new is an understanding of the important contributions of the right prefrontal cortex to formal logical inference, conflict detection, and indeterminacy tolerance and maintenance. This chapter articulates these claims and reviews the data on which they are based. The chapter concludes by speculating that the inference capabilities of the left prefrontal cortex are built into the very fabric of language and can be accounted for by the left hemisphere dominance for language. The roles of the right PFC require multiple mechanisms for explanation. Its role in formal inference may be a function of its visual-spatial processing capabilities. Its role in conflict detection may be explained as a system for checking for consistency between existing beliefs and new information coming into the system and inferences drawn from beliefs and/or new information. There are at least three possible mechanisms to account for its role in indeterminacy tolerance. First, it could contain a representational system with properties very different from those of language, and an accompanying inference engine. Second, it could just contain this different representational system, and the information is at some point passed back to the left prefrontal cortex for inference. Third, the role of the right prefrontal cortex may be largely preventative. That is, it doesn't provide alternative representational and inference capabilities but simply prevents the left prefrontal cortex from settling on initial, local inferences. The current data do not allow differentiating between these possibilities. Successful real-world functioning requires the participation of both hemispheres.

The Neural Correlates of Relational Reasoning: A Meta-analysis of 47 Functional Magnetic Resonance Studies

It is a core cognitive ability of humans to represent and reason about relational information, such as “the train station is north of the hotel” or “Charles is richer than Jim.” However, the neural processes underlying the ability to draw conclusions about relations are still not sufficiently understood. Central open questions are as follows: (1) What are the neural correlates of relational reasoning? (2) Where can deductive and inductive reasoning be localized? (3) What is the impact of different informational types on cerebral activity? For that, we conducted a meta-analysis of 47 neuroimaging studies. We found activation of the frontoparietal network during both deductive and inductive reasoning, with additional activation in an extended network during inductive reasoning in the basal ganglia and the inferior parietal cortex. Analyses revealed a double dissociation concerning the lateral and medial Brodmann's area 6 during deductive and inductive reasoning, indicating differences in terms of processing verbal information in deductive and spatial information in inductive tasks. During semantic and symbolic tasks, the frontoparietal network was found active, whereas geometric tasks only elicited prefrontal activation, which can be explained by the reduced demand for the construction of a mental representation in geometric tasks. Our study provides new insights into the cognitive mechanisms underlying relational reasoning and clarifies previous controversies concerning involved brain areas.

How types of premises modulate the typicality effect in category-based induction: diverging evidence from the P2, P3, and LPC effects

Behavioural studies have indicated that semantic typicality influences processing time and accuracy during the performance of inductive reasoning (i.e., the typicality effect). The present study examines this effect by manipulating the types of premises and conclusions (i.e., general, typical, or atypical) at an electrophysiological level using a semantic category-based induction task. With regard to behavioural results, higher inductive strength was found in typical conclusions in all premise conditions, whereas a longer response time for atypical conclusions was only found in general and typical premise conditions. The ERP results had different response patterns: in the general premise condition, a larger P2, as well as a smaller P3 and LPC (500–600 ms), were elicited by atypical conclusions relative to typical ones; in the typical premise condition, a larger P2 and LPC (600–700 ms) were found for atypical conclusions; in the atypical premise condition, however, only a larger P2 was found for atypical conclusions. The divergent evidence for the typicality effect indicated that the processing of the typicality effect in general, and specific premise conditions, might involve different cognitive processes, such as resource allocation and inference violation, which yielded new insights into the neural underpinnings of the typicality effect in a category-based induction.

Dissociable roles of medial and lateral PFC in rule learning

INTRODUCTION

Although the neural basis of rule learning is of great interest to cognitive neuroscientists, the pattern of transient brain activation during rule discovery remains to be investigated.

METHOD

In this study, we measured event-related functional magnetic resonance imaging (fMRI) during distinct phases of rule learning. Twenty-one healthy human volunteers were presented with a series of cards, each containing a clock-like display of 12 circles numbered sequentially. Participants were instructed that a fictitious animal would move from one circle to another either in a regular pattern (according to a rule hidden in consecutive trials) or randomly. Participants were then asked to judge whether a given step followed a rule.

RESULTS

While the rule-search phase evoked more activation in the posterior lateral prefrontal cortex (LPFC), the rule-following phase caused stronger activation in the anterior medial prefrontal cortex (MPFC). Importantly, the intermediate phase, the rule-discovery phase evoked more activations in MPFC and dorsal anterior cingulate cortex (dACC) than rule search, and more activations in LPFC than rule following.

CONCLUSION

Therefore, we can conclude that the medial and lateral PFC have dissociable contributions in rule learning.

What makes us think? A three-stage dual-process model of analytic engagement

The distinction between intuitive and analytic thinking is common in psychology. However, while often being quite clear on the characteristics of the two processes ('Type 1' processes are fast, autonomous, intuitive, etc. and 'Type 2' processes are slow, deliberative, analytic, etc.), dual-process theorists have been heavily criticized for being unclear on the factors that determine when an individual will think analytically or rely on their intuition. We address this issue by introducing a three-stage model that elucidates the bottom-up factors that cause individuals to engage Type 2 processing. According to the model, multiple Type 1 processes may be cued by a stimulus (Stage 1), leading to the potential for conflict detection (Stage 2). If successful, conflict detection leads to Type 2 processing (Stage 3), which may take the form of rationalization (i.e., the Type 1 output is verified post hoc) or decoupling (i.e., the Type 1 output is falsified). We tested key aspects of the model using a novel base-rate task where stereotypes and base-rate probabilities cued the same (non-conflict problems) or different (conflict problems) responses about group membership. Our results support two key predictions derived from the model: (1) conflict detection and decoupling are dissociable sources of Type 2 processing and (2) conflict detection sometimes fails. We argue that considering the potential stages of reasoning allows us to distinguish early (conflict detection) and late (decoupling) sources of analytic thought. Errors may occur at both stages and, as a consequence, bias arises from both conflict monitoring and decoupling failures.