Fast and slow thinking: Electrophysiological evidence for early conflict sensitivity

Bagó, Bence; Frey, Darren; Vidal, Julie; Houdé, Olivier; Borst, Grégoire; Neys, Wim De

doi:10.1016/j.neuropsychologia.2018.07.017

Cited by 37 publications

(24 citation statements)

References 53 publications

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“…Our findings add to a growing body of EEG and fMRI literature [11][12][13][14] investigating the neural basis of reasoning. Our results are also in line with studies examining cognitive control and executive functioning that have probed the underlying mechanisms of reasoning by employing niche tasks to assess specific theorized mechanisms 27 .…”

Section: Discussionsupporting

confidence: 58%

“…To address this gap, in the current study we used electroencephalography to probe the neural correlates of human rationality. We accomplished this by having participants complete base-rate problems (e.g., Bago et al 11 ) so that we could examine whether neural oscillations are sensitive to intuitive and rational reasoning 15 . Furthermore, neural oscillations are theorized to correspond to the degree of communication across the brain -fast oscillations reflect localized brain activity and slow oscillations reflect the coordination of structures across a diverse brain network 16 .…”

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confidence: 99%

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A Window into the Rational Mind: The Neural Underpinnings of Human Reasoning

Williams¹,

F²,

Krigolson³

2021

Preprint

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Humans reason intuitively by relying on gut hunches or rationally through analytical contemplation. The majority of research on human reasoning has relied on behavioural data and thus the neural underpinnings of this process remain unclear. To address this, we had participants perform a classic reasoning task while electroencephalographic (EEG) data was recorded. Within our reasoning task, participants completed a series of base-rate word problems wherein their decisions were either biased by a provided stereotype or based on statistical probability. Post experiment, we defined participant rationality as the percentage of responses that were made based on likelihood. We then examined frontal theta neural oscillations and found that increased power in this frequency range was associated with increased rationality. Our findings imply that theta oscillations are sensitive to rationality and further that rational reasoning involves a diverse brain network relative to intuitive reasoning.

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Section: Discussionsupporting

confidence: 58%

mentioning

confidence: 99%

A Window into the Rational Mind: The Neural Underpinnings of Human Reasoning

Williams¹,

F²,

Krigolson³

2021

Preprint

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“…This brings up the question of hybrid models (Bago & De Neys, 2017; Banks, 2017; De Neys, 2012; Epstein, 1994; Handley & Trippas, 2015; Johnson et al, 2016; Nakamura & Kawaguchi, 2016; Pennycook et al, 2014, 2015; Sloman, 1996; Smith & DeCoster, 2000; Thompson & Johnson, 2014; Trippas et al, 2016, 2017; Trippas & Handley, 2017). Bago et al (2018) developed a hybrid dual-process model in which the faster System 1 thinking cues both heuristic, belief-based responses (stereotypes) and elementary logico-mathematical principles (base rates). Julmi (2019) also took this approach, adopting a parallel-competitive view based on growing evidence from neurological and experimental studies (Alós-Ferrer & Strack, 2014; Healey et al, 2015; Kuo et al, 2009; Lieberman, 2007).…”

Section: Theoretical Frameworkmentioning

confidence: 99%

The Role of Intuition in Evaluative Judgment and Decision

Hurteau

Rahmanian

Houle

et al. 2020

American Journal of Evaluation

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Expert intuition is increasingly considered to be a valid form of knowledge, and research has proven its effectiveness in judgment and decision making in various fields. Theorists seem to recognize the contributions of intuition within evaluative practice, but it has never been well-documented. This article presents a study on expert intuition, addressing the manner in which intuition is developed, as well as how it contributes to producing judgments in the specific context of program evaluation. In-depth, in-person interviews were conducted with eight novice evaluators and eight experienced evaluators in order to assess the contributions of experience and expertise. Two key observations emerged from interview analyses. The first was that intuition is developed through a long, complex, and demanding process in which reflective analysis of experiments, successes, and failures play an essential role; the second was that the development of intuition is fostered by expertise and experience.

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“…This is, however, not what the available evidence suggests. A large body of conflict detection studies shows that when people give heuristic responses on conflict versions of reasoning problems, they show decreased response confidence in comparison with the noconflict versions (Frey & De Neys, 2017;Mevel et al, 2014;Stupple, Ball, & Ellis, 2013), prolonged response times (Pennycook et al, 2015;Stupple & Ball, 2008;Swan, Calvillo, & Revlin, 2018), lower feelings of rightness about their answers (Thompson & Johnson, 2014), better recall of information presented in the task (De Neys & Glumicic, 2008), changes in skin conductance (De Neys, Moyens, & Vansteenwegen, 2010), and other neurophysiological changes (Bago et al, 2018;De Neys, Vartanian, & Goel, 2008;Vartanian et al, 2018). This seems to indicate that even when people are biased, they are at least implicitly sensitive to the fact that their response is not in line with the logically correct response (De Neys, 2012, 2017 however, for critics of this account see Mata, Ferreira, Voss, & Kollei, 2017;Pennycook, Fugelsang, & Koehler, 2012;Singmann, Klauer, & Kellen, 2014).…”

Section: Introductionmentioning

confidence: 99%

Predicting individual differences in conflict detection and bias susceptibility during reasoning

Šrol

Neys

2020

Thinking & Reasoning

Self Cite

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One of the key components of the susceptibility to cognitive biases is the ability to monitor for conflict that may arise between intuitively cued "heuristic" answers and logical principles. While there is evidence that people differ in their ability to detect such conflicts, it is not clear which individual factors are driving these differences. In the present large-scale study (N = 399) we explored the role of cognitive ability, thinking dispositions, numeracy, cognitive reflection, and mindware instantiation (i.e. knowledge of logical principles) as potential predictors of individual differences in conflict detection ability and overall accuracy on a battery of reasoning problems. Results showed that mindware instantiation was the single best predictor of both conflict detection efficiency and reasoning accuracy. Cognitive reflection, thinking dispositions, numeracy, and cognitive ability played a significant but smaller role. The full regression model accounted for 40% of the variance in overall reasoning accuracy, but only 7% of the variance in conflict detection efficiency. We discuss the implications of these findings for popular process models of bias susceptibility.

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Fast and slow thinking: Electrophysiological evidence for early conflict sensitivity

Cited by 37 publications

References 53 publications

A Window into the Rational Mind: The Neural Underpinnings of Human Reasoning

A Window into the Rational Mind: The Neural Underpinnings of Human Reasoning

The Role of Intuition in Evaluative Judgment and Decision

Predicting individual differences in conflict detection and bias susceptibility during reasoning

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