演绎与归纳推理比较的神经机制:问题与趋势
The Neural Mechanisms of Comparison between Deductive and Inductive Reasoning: Problems and Trends

作者: 李晓芳 , 张明明 , 龙长权 :西南大学心理学部,重庆;

关键词: 演绎推理归纳推理推理的心理学理论认知神经科学问题趋势Deductive Reasoning Inductive Reasoning Psychological Theories of Reasoning Cognitive Neuroscience Problems Trends

摘要:
演绎推理和归纳推理是两种主要形式的推理,单加工理论和双加工理论是推理心理学领域主要存在的两种相互竞争的理论。目前,已有多项研究采用认知神经科学技术来比较演绎推理和归纳推理,以检验推理是单加工过程还是双加工过程。但这些研究还面临诸多问题:正向推断逻辑的局限;不同的认知神经科学技术的差异;复杂多变的实验任务;以及认知神经科学本身所面临的质疑。未来的研究依然可以以正向推断为基本逻辑和突破口,采用多元的技术手段和规范的实验任务,对演绎和归纳推理比较的心理机制进行分子水平、神经元水平等更加微观化的研究。

Abstract: Deductive reasoning and inductive reasoning are two main forms of reasoning. Single-process ac-counts and dual-process accounts are two competing theories of reasoning psychology. At present, many studies compare deductive and inductive reasoning using cognitive neuroscience technology to test whether reasoning is a single or double process. But there are many problems in the studies: limitations of forward inference, differences in cognitive neuroscience techniques, complex and varied experimental tasks, challenges of cognitive neuroscience itself and so on. In future research, forward inference can still be the basic logic and breakthrough of studies; multivariate techniques and standard experimental tasks should be conducted; and studies on the neural mechanisms of comparison between deductive and inductive reasoning should go deep into more microscopic level, such as the level of molecule and neuron.

文章引用: 李晓芳 , 张明明 , 龙长权 (2016) 演绎与归纳推理比较的神经机制:问题与趋势。 心理学进展, 6, 376-383. doi: 10.12677/AP.2016.64049

参考文献

[1] 李红, 陈安涛, 冯廷勇, 李富洪, 龙长权(2004). 个体归纳推理能力的发展及其机制研究展望. 心理科学, 27(6), 1457- 1459.

[2] 肖凤, 李红, 龙长权, 陈庆飞, 王荣燕, 李富洪(2012). 归纳推理的认知神经机制. 心理科学进展, 20(8), 1268-1276.

[3] Blanchette, I., & El-Deredy, W. (2014). An ERP Investigation of Conditional Reasoning with Emotional and Neural Contents. Brain and Cognition, 91, 45-53.
http://dx.doi.org/10.1016/j.bandc.2014.08.001

[4] Bonnefond, M., Castelain, T., Cheylus, A., & Van der Henst, J. (2014). Reasoning from Transitive Premise: An EEG Study. Brain and Cognition, 90, 100-108.
http://dx.doi.org/10.1016/j.bandc.2014.06.010

[5] Bonnefond, M., Kaliuzhna, M., & Van der Henst, J. (2014). Disabling Conditional Inferences: An EEG Study. Neuropsychologia, 56, 255-262.
http://dx.doi.org/10.1016/j.neuropsychologia.2014.01.022

[6] Chiong, W., Wilson, S. M., D’Esposito, M., Kayser, A. S., Grossman, S. N., Poorzand, P. et al. (2013). The Salience Network Causally Influences Default Mode Network Activity during Moral Reasoning. Brain, 136, 1929-1941.
http://dx.doi.org/10.1093/brain/awt066

[7] Coltheart, M. (2004). Brain Imaging, Connectionism, and Cognitive Neuropsychology. Cognitive Neuropsychology, 21, 21- 25.
http://dx.doi.org/10.1080/02643290342000159

[8] Donoso, M., Collins, A. G., & Koechlin, E. (2014). Foundations of Human Reasoning in the Prefrontal Cortex. Science, 344, 1481-1486.
http://dx.doi.org/10.1126/science.1252254

[9] Elqayam, S., & Over, D. E. (2013). New Paradigm Psychology of Reasoning: An Introduction to the Special Issue Edited by Elqayam, Bonnefon, and Over. Thinking & Reasoning, 19, 249-265.
http://dx.doi.org/10.1080/13546783.2013.841591

[10] Evans, J.S.B.T., & Stanovich, K.E. (2013). Dual-Process Theories of Higher Cognition: Advancing the Debate. Perspectives on Psychological Science, 8, 223-241.
http://dx.doi.org/10.1177/1745691612460685

[11] Goel, V. (2007). Anatomy of Deductive Reasoning. Trends in Cognitive Sciences, 11, 435-441.
http://dx.doi.org/10.1016/j.tics.2007.09.003

[12] Goel, V., & Dolan, R.J. (2000). Anatomical Segregation of Com-ponent Processes in an Inductive Inference Task. Journal of Cognitive Neuroscience, 12, 110-119.
http://dx.doi.org/10.1162/08989290051137639

[13] Goel, V., & Dolan, R. J. (2004). Differential Involvement of Left Prefrontal Cortexin Inductive and Deductive Reasoning. Cognition, 93, B109-B121.
http://dx.doi.org/10.1016/j.cognition.2004.03.001

[14] Goel, V., Gold, B., Kapur, S., & Houle, S. (1997). The Seats of Reason? An Imaging Study of Deductive and Inductive Reasoning. NeuroReport, 8, 1305-1310.
http://dx.doi.org/10.1097/00001756-199703240-00049

[15] Hayes, B. K., Heit, E., & Rotello, C. (2014). Memory, Reasoning, and Categorization: Parallels and Common Mechanisms. Frontiers in Cognitive Science, 5, 529.
http://dx.doi.org/10.3389/fpsyg.2014.00529

[16] Hayes, B. K., Heit, E., & Swendsen, H. (2010). Inductive Reasoning. Wiley Interdisciplinary Reviews. Cognitive Science, 1, 278-292.
http://dx.doi.org/10.1002/wcs.44

[17] Heit, E. (2015). Brain Imaging, Forward Inference, and Theories of Reasoning. Frontiers in Human Neuroscience, 8, 1056.
http://dx.doi.org/10.3389/fnhum.2014.01056

[18] Henson, R. (2005). What Can Functional Neuroimaging Tell the Experimental Psychologist? The Quarterly Journal of Experimental Psychology, 58A, 193-233.
http://dx.doi.org/10.1080/02724980443000502

[19] Henson, R. (2006). Forward Inference Using Functional Neu-roimaging: Dissociations versus Associations. Trends in Cognitive Science, 10, 64-69.
http://dx.doi.org/10.1016/j.tics.2005.12.005

[20] Hill, H., & Windmann, S. (2014). Examining Event-Related Potential (ERP) Correlates of Decision Bias in Recognition Memory Judgments. PLoS ONE, 9, e106411.
http://dx.doi.org/10.1371/journal.pone.0106411

[21] Johnson, R. (1993). On the Neural Generators of the P300 Component of the Event-Related Potential. Psychophysiology, 30, 90-97.
http://dx.doi.org/10.1371/journal.pone.0106411

[22] Johnson-Laird, P. N. (1994). Mental Models and Probabilistic Thinking. Cognition, 50, 189-209.
http://dx.doi.org/10.1016/0010-0277(94)90028-0

[23] Kemp, C., & Jern, A. (2014). A Taxonomy of Inductive Prob-lems. Psychonomic Bulletin and Review, 21, 23-46.
http://dx.doi.org/10.3758/s13423-013-0467-3

[24] Lassiter, D., & Goodman, N. D. (2015). How Many Kinds of Reasoning? Inference, Probability, and Natural Language Semantics. Cognition, 136, 123-134.
http://dx.doi.org/10.1016/j.cognition.2014.10.016

[25] Liang, P., Jia, X., Taatgen, N., Zhong, N., & Li, K. (2014). Different Strategies in Solving Series Completion Inductive Reasoning Problems: An fMRI and Computational Study. In-ternational Journal of Psychophysiology, 93, 253-260.
http://dx.doi.org/10.1016/j.ijpsycho.2014.05.006

[26] Liang, P., Zhong, N., Lu, S., & Liu, J. (2010). ERP Characte-ristics of Sentential Inductive Reasoning in Time and Frequency Domains. Cognitive System Research, 11, 67-73.
http://dx.doi.org/10.1016/j.cogsys.2008.10.001

[27] Long, C., Lei, X., Chen, J., Chang, Y., Chen, A., & Li, H. (2015). Event-Related Potential Parameters of Category and Property Violations during Semantic Category-Based Induction. International Journal of Psychophysiology, 96, 141-148.
http://dx.doi.org/10.1016/j.ijpsycho.2015.04.005

[28] Mack, M. L., Preston, A. R., & Love, B. C. (2013). Decoding the Brain’s Algorithm for Categorization from Its Neural Implementation. Current Biology, 23, 2023-2027.
http://dx.doi.org/10.1016/j.cub.2013.08.035

[29] Malaia, E., Tommerdahl, J., & McKee, F. (2015). Deductive versus Probabilistic Reasoning in Healthy Adults: An EEG Analysis of Neural Differences. Journal of Psycholinguistic Research, 44, 533-544.
http://dx.doi.org/10.1007/s10936-014-9297-3

[30] Marr, D. (1982). Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. New York: W.H. Freeman and Company.

[31] McClure, S. M., Ericson, K. M., Laibson, D. I., Loewenstein, G., & Cohen, J. D. (2007). Time Discounting for Primary Rewards. The Journal of Neuroscience, 27, 5796-5804.
http://dx.doi.org/10.1523/JNEUROSCI.4246-06.2007

[32] Nosofsky, R. M., Little, D. R., & James, T. W. (2012). Activation in the Neural Network Responsible for Categorization and Recognition Reflects Parameter Changes. Proceedings of the National Academy of Sciences of the United States of America, 109, 333-338.
http://dx.doi.org/10.1073/pnas.1111304109

[33] Oaksford, M., & Chater, N. (2007). Bayesian Rationality: The Probabilistic Approach to Human Reasoning. Oxford: Oxford University Press.
http://dx.doi.org/10.1093/acprof:oso/9780198524496.001.0001

[34] Osherson, D., Perani, D., Cappa, S., Schnur, T., Grassi, F., & Fazio, F. (1998). Distinct Brain Loci in Deductive versus Probabilistic Reasoning. Neuropsychologia, 36, 369-376.
http://dx.doi.org/10.1016/S0028-3932(97)00099-7

[35] Parsons, L. M., & Osherson, D. (2001). New Evi-dence for Distinct Right and Left Brain Systems for Deductive versus Probabilistic Reasoning. Cerebral Cortex, 11, 954-965.
http://dx.doi.org/10.1093/cercor/11.10.954

[36] Poeppel, D. (1996). A Critical Review of PET Studies of Phonological Processing. Brain and Language, 55, 317-351.
http://dx.doi.org/10.1006/brln.1996.0108

[37] Prado, J., Chadha, A., & Booth, J. R. (2011). The Brain Network for Deductive Reasoning: A Quantitative Meta-Analysis of 28 Neuroimaging Studies. Journal of Cognitive Neuroscience, 23, 3483-3497.
http://dx.doi.org/10.1162/jocn_a_00063

[38] Rips, L. J. (2001). Two Kinds of Reasoning. Psychological Science, 12, 129-134.
http://dx.doi.org/10.1111/1467-9280.00322

[39] Roser, M. E., Evans, J. S. B., McNair, N. A., Fuggetta, G., Handley, S. J., Carroll, L. S., & Trippas, D. (2015). Investigating Reasoning with Multiple Integrated Neuroscientific Methods. Frontiers in Human Neuroscience, 9, 41.
http://dx.doi.org/10.3389/fnhum.2015.00041

[40] Rotello, C. M., & Heit, E. (2009). Modeling the Effects of Argu-ment Length and Validity on Inductive and Deductive Reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35, 1317-1330.
http://dx.doi.org/10.1037/a0016648

[41] Rotello, C. M., & Heit, E. (2014). The Neural Correlates of Belief Bias: Activation in Inferior Frontal Cortex Reflects Response Rate Differences. Frontiers in Human Neuroscience, 8, 862.
http://dx.doi.org/10.3389/fnhum.2014.00862

[42] Satel, S., & Lilienfeld, S. (2013). Brainwashed: The Seductive Appeal of Mindless Neuroscience. New York: Basic Books.

[43] Tenenbaum, J. B., Griffiths, T. L., & Kemp, C. (2006). Theory-Based Bayesian Models of Inductive Learning and Reasoning. Trends in Cognitive Sciences, 10, 309-318.
http://dx.doi.org/10.1016/j.tics.2006.05.009

[44] Tsujii, T., Okada, M., & Watanabe, S. (2010). Effects of Aging on Hemispheric Asymmetry in Inferior Frontal Cortex Activity during Belief-Bias Syllogistic Reasoning: A Near-Infrared Spectroscopy Study. Behavioural Brain Research, 210, 178-183.
http://dx.doi.org/10.1016/j.bbr.2010.02.027

[45] Turner, B. O., Marinsek, N., Ryhal, E., & Miller, M. B. (2015). Hemispheric Lateralization in Reasoning. Annals of the New York Academy of Science, 1359, 47-64.
http://dx.doi.org/10.1111/nyas.12940

[46] Uttal, W. R. (2011). Mind and Brain: A Critical Appraisal of Cognitive Neuropsychology. Cambridge, MA: MIT Press.
http://dx.doi.org/10.7551/mitpress/9780262015967.001.0001

[47] Van Orden, G. C., & Paap, K. R. (1997). Func-tional Neuroimages Fail to Discover Pieces of Mind in the Parts of the Brain. Philosophy of Science, 64, S85-S94.
http://dx.doi.org/10.1086/392589

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