- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04849208
NEUROR: Exploring the Neural Basis of Reasoning (NEUROR)
Exploring the Neural Basis of Reasoning
Decades of research have long established that people's reasoning can be biased by their intuitions and deviate from logical norms. Popular dual process models that characterize thinking as an interaction between intuitive and deliberate thought processes have presented an appealing explanation for this observation. Within this account logical reasoning is traditionally considered as a prototypical example of a task that requires effortful deliberate thinking. In recent years, however, a number of findings obtained with new behavioral paradigms have questioned the traditional dual process characterization. A key observation is that people can process logical principles in classic reasoning tasks intuitively without deliberation.
The fast or intuitive logic findings have far stretching theoretical implications for dual process theories and our view of human rationality. However, the nature of this newly discovered fast logical reasoning is not clear. One limitation is that its neural basis has not been explored. The primary goal of this project is to address this shortcoming in a functional magnetic resonance imaging (fMRI) study. In the study adult participants will solve classic reasoning problems (i.e., variants of the bat-and-ball problem) in the scanner. Half of the trials will be traditional "Slow" trials in which participants get ample time to deliberate (i.e., 20 s). The other half of the trials will be "Fast" trials in which people do not get sufficient time to deliberate (i.e., 4 s deadline) and need to rely on intuitive processing.
All participants in the fMRI study will be healthy adults aged between 18-45. In addition to contrasting correct responders' brain activation during fast and slow trials, we will also contrast the fast and slow activations for correct and incorrect responses. This will allows us to identify brain regions associated with both correct and incorrect fast and slow logical responses and reach our study objective.
Study Overview
Status
Conditions
Intervention / Treatment
Study Type
Enrollment (Anticipated)
Contacts and Locations
Study Contact
- Name: Khaoussou SYLLA, Dr.
- Phone Number: 01 45 65 76 78
- Email: k.sylla@ghu-paris.fr
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- right-handed
- signed informed consent form
- medical, neurological, neuroradiological healthy
- social security number
- use of contraception for female subjects
Exclusion Criteria:
- standard contra-indication for MRI examination (pacemaker, metallic implants/dental braces, claustrophobia, pregnancy)
- chronic drug or alcohol user
- cognitive disorders linked to cardiovascular accidents
- chronic neurological or psychiatric disorder
- history of major illness (diabetes, metabolic, cancer, immunological)
- use of medicines that can potentially interfere with cerebral imaging (psychotropic drugs, hypnotics, anxiolytics, neuroleptics, anti-parkinson drugs, benzodiazepines, steroidal anti-inflammatory drugs, antiepileptics, anti-histamines, central analgesics and muscle relaxants)
- dyschromatopsia
- pregnant female
- non-MRI compatible tattoo
Study Plan
How is the study designed?
Design Details
- Observational Models: Other
- Time Perspectives: Other
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
fMRI results
Time Frame: 2 years
|
Contrast of brain activations during correct and incorrect intuitive and deliberate reasoning
|
2 years
|
Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Catherine OPPENHEIM, Dr, Groupe Hospitalier Universitaire Paris - Psychiatrie & Neurosciences (GHU Paris)
Publications and helpful links
General Publications
- Tversky A, Kahneman D. Judgment under Uncertainty: Heuristics and Biases. Science. 1974 Sep 27;185(4157):1124-31. doi: 10.1126/science.185.4157.1124.
- Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.
- Evans JS, Stanovich KE. Dual-Process Theories of Higher Cognition: Advancing the Debate. Perspect Psychol Sci. 2013 May;8(3):223-41. doi: 10.1177/1745691612460685.
- Thompson VA, Prowse Turner JA, Pennycook G. Intuition, reason, and metacognition. Cogn Psychol. 2011 Nov;63(3):107-40. doi: 10.1016/j.cogpsych.2011.06.001. Epub 2011 Jul 27.
- Bago B, De Neys W. Fast logic?: Examining the time course assumption of dual process theory. Cognition. 2017 Jan;158:90-109. doi: 10.1016/j.cognition.2016.10.014. Epub 2016 Nov 4.
- Newman IR, Gibb M, Thompson VA. Rule-based reasoning is fast and belief-based reasoning can be slow: Challenging current explanations of belief-bias and base-rate neglect. J Exp Psychol Learn Mem Cogn. 2017 Jul;43(7):1154-1170. doi: 10.1037/xlm0000372. Epub 2017 Feb 13.
- Thompson VA, Pennycook G, Trippas D, Evans JSBT. Do smart people have better intuitions? J Exp Psychol Gen. 2018 Jul;147(7):945-961. doi: 10.1037/xge0000457.
- Bago B, & De Neys W. (2019). The smart System 1: Evidence for the intuitive nature of correct responding on the bat-and-ball problem. Thinking & Reasoning, 25(3), 257-299.
- Advancing the specification of dual process models of higher cognition: a critical test of the hybrid model view. Thinking & Reasoning, 1-30. doi:10.1080/13546783.2018.1552194
- Ball, L. J.; Thompson, V. A., & Stupple, E. J.N. (2017). Conflict and dual process theory: the case of belief bias. In W. De Neys (Ed.), Dual Process Theory 2.0 (pp. 100-120). Oxon, UK: Routledge. doi: 10.4324/9781315204550-7
- Banks, A. (2017). Comparing dual process theories: Evidence from event-related potentials. In W. De Neys (Ed.), Dual Process Theory 2.0 (pp. 66-81). Oxon, UK: Routledge. doi: 10.4324/9781315204550-5
- De Neys W. Bias and Conflict: A Case for Logical Intuitions. Perspect Psychol Sci. 2012 Jan;7(1):28-38. doi: 10.1177/1745691611429354. Epub 2012 Jan 5.
- Pennycook, G. (2017). A perspective on the theoretical foundation of dual process models. In W. De Neys (Ed.), Dual Process Theory 2.0 (pp. 5-27). Oxon, UK: Routledge. doi: 10.4324/9781315204550-2
- Thompson, V. A., & Newman, I. (2017). Logical intuitions and other conundra for dual process theories. In W. De Neys (Ed.), Dual Process Theory 2.0 (pp. 121-136). Oxon, UK: Routledge. doi: 10.4324/9781315204550-8
- Trippas, D., & Handley, S. (2017). The parallel processing model of belief bias: Review and extensions. In W. De Neys (Ed.), Dual Process Theory 2.0 (pp. 28-46). Oxon, UK: Routledge. doi: 10.4324/9781315204550-3
- Pennycook G, Fugelsang JA, Koehler DJ. What makes us think? A three-stage dual-process model of analytic engagement. Cogn Psychol. 2015 Aug;80:34-72. doi: 10.1016/j.cogpsych.2015.05.001. Epub 2015 Jun 16.
- De Neys, W. (Ed.) (2017). Dual Process Theory 2.0. Oxon, UK: Routledge.
- De Neys W, Vartanian O, Goel V. Smarter than we think: when our brains detect that we are biased. Psychol Sci. 2008 May;19(5):483-9. doi: 10.1111/j.1467-9280.2008.02113.x.
- De Martino B, Kumaran D, Seymour B, Dolan RJ. Frames, biases, and rational decision-making in the human brain. Science. 2006 Aug 4;313(5787):684-7.
- Goel V, Buchel C, Frith C, Dolan RJ. Dissociation of mechanisms underlying syllogistic reasoning. Neuroimage. 2000 Nov;12(5):504-14.
- Houde O, Pineau A, Leroux G, Poirel N, Perchey G, Lanoe C, Lubin A, Turbelin MR, Rossi S, Simon G, Delcroix N, Lamberton F, Vigneau M, Wisniewski G, Vicet JR, Mazoyer B. Functional magnetic resonance imaging study of Piaget's conservation-of-number task in preschool and school-age children: a neo-Piagetian approach. J Exp Child Psychol. 2011 Nov;110(3):332-46. doi: 10.1016/j.jecp.2011.04.008. Epub 2011 Jun 1.
- Leroux G, Spiess J, Zago L, Rossi S, Lubin A, Turbelin MR, Mazoyer B, Tzourio-Mazoyer N, Houdé O, Joliot M. Adult brains don't fully overcome biases that lead to incorrect performance during cognitive development: an fMRI study in young adults completing a Piaget-like task. Dev Sci. 2009 Mar;12(2):326-38. doi: 10.1111/j.1467-7687.2008.00785.x.
- Stollstorff M, Vartanian O, Goel V. Levels of conflict in reasoning modulate right lateral prefrontal cortex. Brain Res. 2012 Jan 5;1428:24-32. doi: 10.1016/j.brainres.2011.05.045. Epub 2011 May 25.
- Prado J, Chadha A, Booth JR. The brain network for deductive reasoning: a quantitative meta-analysis of 28 neuroimaging studies. J Cogn Neurosci. 2011 Nov;23(11):3483-97. doi: 10.1162/jocn_a_00063. Epub 2011 May 13.
- Prado J, Noveck IA. Overcoming perceptual features in logical reasoning: a parametric functional magnetic resonance imaging study. J Cogn Neurosci. 2007 Apr;19(4):642-57.
- Vartanian O, Beatty EL, Smith I, Blackler K, Lam Q, Forbes S. One-way traffic: The inferior frontal gyrus controls brain activation in the middle temporal gyrus and inferior parietal lobule during divergent thinking. Neuropsychologia. 2018 Sep;118(Pt A):68-78. doi: 10.1016/j.neuropsychologia.2018.02.024. Epub 2018 Feb 23.
- Frederick, S (2005). Cognitive reflection and decision making. Journal of Economic perspectives, 19(4), 25-42.
Study record dates
Study Major Dates
Study Start (Anticipated)
Primary Completion (Anticipated)
Study Completion (Anticipated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Other Study ID Numbers
- 2019-A02022-55
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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