Developmental frontal brain activation differences in overcoming heuristic bias

Mevel, Katell; Poirel, Nicolas; Simon, Grégory; Orliac, François; Houdé, Olivier; Neys, Wim De

doi:10.1016/j.cortex.2019.03.004

Cited by 12 publications

(5 citation statements)

References 54 publications

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“…These findings are consistent with other developmental studies that have shown age-related improvements on the RCB tasks, including base-rate sensitivity, framing effects, ratio bias, belief-bias syllogisms, and temporal discounting (Almy et al, 2018;De Neys & Van Gelder, 2009;Evans & Perry, 1995;Green et al, 1994;Handley et al, 2004;Klaczynski, 2001b;Kokis et al, 2002;Markovits & Bouffard-Bouchard, 1992;Mevel et al, 2019;Prencipe et al, 2011;Scheres et al, 2006;Steinberg et al, 2009;Toplak et al, 2014;Weller et al, 2011 Our results are consistent with Almy et al (2018), who also reported age-related increases in performance on the IGT in a sample of 9-to 31-year-old participants. The development of RCB performance is comparable with the rapid changes that have been reported on the development of cognitive abilities during this same period of development.…”

Section: Discussionsupporting

confidence: 91%

Resistance to cognitive biases: Longitudinal trajectories and associations with cognitive abilities and academic achievement across development

Toplak

Flora

2020

Behavioral Decision Making

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Cognitive failures on several reasoning and judgment tasks can be explained by miserly information processing tendencies. These tasks have been examined in child and youth samples, and we extend this work by examining the developmental trajectory of performance on these cognitive bias tasks and their association with other markers of cognitive sophistication. A longitudinal design was used to examine the development of resistance to cognitive biases in a sample of 204 typically developing children and youth. These youth were 8-14 years of age at first assessment and were assessed at three measurement occasions separated by 3 years. Resistance to cognitive biases as represented by performance on five reasoning and judgment tasks, including ratio bias, belief-bias syllogisms, attribute framing problems, base-rate sensitivity, and temporal discounting. The developmental trajectory of resistance to cognitive biases was examined. We also estimated associations between trajectories of resistance to cognitive biases and measures of cognitive abilities, actively openminded thinking, and superstitious thinking to examine how individual differences in other measures of cognitive sophistication were associated with the development of resistance to cognitive biases. Cognitive ability measures included intelligence (verbal and nonverbal) and executive function tasks (interference control and set-shifting). Growth modeling results showed that resistance to cognitive biases increased linearly from 8 to 15 years of age, followed by a flat mean trajectory up to age 20. Cognitive ability, actively open-minded thinking, and superstitious thinking predicted individual differences in resistance to cognitive biases, but not changes in resistance to cognitive biases. Performance on resistance to cognitive biases tasks was positively correlated with self-and parent-reported academic achievement.

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Section: Discussionsupporting

confidence: 91%

Resistance to cognitive biases: Longitudinal trajectories and associations with cognitive abilities and academic achievement across development

Toplak

Flora

2020

Behavioral Decision Making

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“…This is also consistent with experimental data demonstrating that good thinkers have good intuitions, and as such have the ability to think logically, quickly, and without deliberation (Raoelison et al, 2020;Thompson et al, 2018). Note that this conclusion also fits with recent neuroimaging work in which adolescents' and adults' performance on the ratio bias task was contrasted (Mevel et al, 2019). Although Mevel et al found that adults behaviorally outperformed adolescents, such correct responding was associated with less frontal activation in cognitive control regions for adults than adolescents.…”

Section: Discussionsupporting

confidence: 87%

Can a fast thinker be a good thinker? The neural correlates of base-rate neglect measured using a two-response paradigm

Vartanian

Lam

Maceda

et al. 2021

Cognitive Neuropsychology

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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“…This re-parametrization would be a discrete event that qualitatively separates T1 and T2 reasoning. There is evidence that the same network implements T1 and T2 reasoning: the right inferior prefrontal cortex has been implicated in metacognitive control (De Neys et al, 2008;Oldrati et al, 2016;Vartanian et al, 2018;Mevel et al, 2019;Andersson et al, 2020) and it is known to drive inhibitory feedback through subcortical regions back to the same cortical networks that initially trigger metacognitive control (Aron et al, 2004(Aron et al, , 2014. 15 However, there is still no evidence whether metacognitive control causes a discrete re-parametrization of the same network (per DPT) or continuously modulates the same network (per SPT).…”

Section: §4 Metacognitive Controlmentioning

confidence: 99%

Metacognitive control in single- vs. dual-process theory

Dewey

2022

Thinking & Reasoning

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Recent work in cognitive modelling has found that most of the data that has been cited as evidence for the dual-process theory (DPT) of reasoning is best explained by non-linear, "monotonic" one-process models (Stephens et al., 2018(Stephens et al., , 2019. In this paper, I consider an important caveat of this research: it uses models that are committed to unrealistic assumptions about how effectively task conditions can isolate Type-1 and Type-2 reasoning. To avoid this caveat, I develop a coordinated theoretical, experimental, and modelling strategy to better test DPT. First, I propose that Type-1 and Type-2 reasoning are defined as reasoning that precedes and follows metacognitive control, respectively. Second, I argue that reasoning that precedes and follows metacognitive control can be effectively isolated using debiasing paradigms that manipulate metacognitive heuristics (e.g., processing fluency) to prevent or trigger metacognitive control, respectively. Third, I argue that monotonic modelling can allow us to decisively test DPT only when we use them to analyse data from this particular kind of debiasing paradigm.

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Developmental frontal brain activation differences in overcoming heuristic bias

Cited by 12 publications

References 54 publications

Resistance to cognitive biases: Longitudinal trajectories and associations with cognitive abilities and academic achievement across development

Resistance to cognitive biases: Longitudinal trajectories and associations with cognitive abilities and academic achievement across development

Can a fast thinker be a good thinker? The neural correlates of base-rate neglect measured using a two-response paradigm

Metacognitive control in single- vs. dual-process theory

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