工作记忆负荷对两种类别学习的影响
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摘要
类别学习是学习者经过一定的练习学会分类的过程,它一直是认知心理学研究的重点领域之一。传统的类别学习理论认为,人类只有一个单一的类别学习系统。但是近10年来,研究者越来越关注类别学习多重系统的研究,该理论认为,人类至少存在两个类别学习系统,外显的言语推理系统和内隐学习系统。基于规则的类别学习通过外显的言语推理学习系统进行,依赖工作记忆和执行注意；信息整合的类别学习通过内隐学习系统进行,不依赖工作记忆。
本研究根据多重系统理论的假设,探讨了同时进行的工作记忆负荷任务对基于规则和信息整合两种类别学习产生的影响,以及在不同难度的工作记忆负荷任务的条件下,两种类别学习的学习效果出现的变化。
本研究采用了双任务的范式。被试为某高校122名大学本科生,要求他们完成不同的类别学习任务。研究由两个实验组成：实验一比较了两种类别学习在单、双任务条件下的学习差异。结果表明在双任务条件下,基于规则的类别学习受到同时进行的工作记忆任务的干扰,学习效果出现下降；而信息整合的类别学习的学习效果不受工作记忆任务的影响。实验二探讨了两种类别学习在高、低两种工作记忆负荷水平中的学习差异,结果发现在高工作记忆负荷的条件下,基于规则的类别学习的分类正确率出现显著下降,分类反应时显著变长；信息整合的类别学习在两种条件下分类正确率没有显著差异,不受工作记忆负荷变化的影响,但是分类反应时出现了显著变长。
因此,综合两个实验的研究结果可以说明,两种类别学习在不同工作记忆负荷的情况下表现出了不同的变化趋势,基于规则的类别学习受到工作记忆负荷的干扰,并且随着工作记忆负荷的增加,受到的干扰也会越大；而信息整合的类别学习不受工作记忆负荷变化的影响。这与类别学习单一系统理论的观点不一致,表明了两种类别学习存在的差异性,也就是说可能存在两个不同的类别学习系统。
Category learning is a process that learners learn how to classify correctly after some practice. It is one of the most important aspects of cognitive psychology. The traditional theories of category learning consider that people has a single category learning system, but in past decade, its focus was the multiple systems of category learning, which suggests that there are at least two distinct types of category learning systems:an explicit, hypothesis-testing system and an implicit, procedural learning system. The rule-based category learning is based on the explicit, hypothesis-testing system and it depends on working memory and executive attention. The information-integration category learning is based on the implicit, procedural learning system.
On the base of the multiple systems of category learning, our research investigated the effects of a concurrent working memory load task on rule-based category learning and on information-integration category learning and the effects of the different working memory loads on these two kinds of category learning.
Our research used the pattern of dual task. The 122 subjects who were university students were tested in different category learning tasks. The research was composed of two experiments. The first experiment discussed the difference of the two kinds of category learning in single task and dual task. We found that the concurrent working memory load task impaired the rule-based category learning, but did not significantly impair the information-integration category learning. The second experiment investigated the difference of these two kinds of category learning in high working memory load condition and low working memory load condition. The results indicated that the rule-based category learning's classification accuracy was dramatically impaired and its classification reaction time became longer in the high working memory load condition. But there was no significant difference in the information-integration category learning's classification accuracy, however, its classification reaction time became much longer
In conclusion, the results of this research suggest that working memory load has different effects on these two kinds of category learning. The dual working memory load task disrupts the rule-based category learning and its performance become much worse when the working memory load is higher. But the information-integration category learning is not disrupted by the dual working memory load task. So, the results support the notion of at least two systems of category learning.
本研究根据多重系统理论的假设,探讨了同时进行的工作记忆负荷任务对基于规则和信息整合两种类别学习产生的影响,以及在不同难度的工作记忆负荷任务的条件下,两种类别学习的学习效果出现的变化。
本研究采用了双任务的范式。被试为某高校122名大学本科生,要求他们完成不同的类别学习任务。研究由两个实验组成：实验一比较了两种类别学习在单、双任务条件下的学习差异。结果表明在双任务条件下,基于规则的类别学习受到同时进行的工作记忆任务的干扰,学习效果出现下降；而信息整合的类别学习的学习效果不受工作记忆任务的影响。实验二探讨了两种类别学习在高、低两种工作记忆负荷水平中的学习差异,结果发现在高工作记忆负荷的条件下,基于规则的类别学习的分类正确率出现显著下降,分类反应时显著变长；信息整合的类别学习在两种条件下分类正确率没有显著差异,不受工作记忆负荷变化的影响,但是分类反应时出现了显著变长。
因此,综合两个实验的研究结果可以说明,两种类别学习在不同工作记忆负荷的情况下表现出了不同的变化趋势,基于规则的类别学习受到工作记忆负荷的干扰,并且随着工作记忆负荷的增加,受到的干扰也会越大；而信息整合的类别学习不受工作记忆负荷变化的影响。这与类别学习单一系统理论的观点不一致,表明了两种类别学习存在的差异性,也就是说可能存在两个不同的类别学习系统。
Category learning is a process that learners learn how to classify correctly after some practice. It is one of the most important aspects of cognitive psychology. The traditional theories of category learning consider that people has a single category learning system, but in past decade, its focus was the multiple systems of category learning, which suggests that there are at least two distinct types of category learning systems:an explicit, hypothesis-testing system and an implicit, procedural learning system. The rule-based category learning is based on the explicit, hypothesis-testing system and it depends on working memory and executive attention. The information-integration category learning is based on the implicit, procedural learning system.
On the base of the multiple systems of category learning, our research investigated the effects of a concurrent working memory load task on rule-based category learning and on information-integration category learning and the effects of the different working memory loads on these two kinds of category learning.
Our research used the pattern of dual task. The 122 subjects who were university students were tested in different category learning tasks. The research was composed of two experiments. The first experiment discussed the difference of the two kinds of category learning in single task and dual task. We found that the concurrent working memory load task impaired the rule-based category learning, but did not significantly impair the information-integration category learning. The second experiment investigated the difference of these two kinds of category learning in high working memory load condition and low working memory load condition. The results indicated that the rule-based category learning's classification accuracy was dramatically impaired and its classification reaction time became longer in the high working memory load condition. But there was no significant difference in the information-integration category learning's classification accuracy, however, its classification reaction time became much longer
In conclusion, the results of this research suggest that working memory load has different effects on these two kinds of category learning. The dual working memory load task disrupts the rule-based category learning and its performance become much worse when the working memory load is higher. But the information-integration category learning is not disrupted by the dual working memory load task. So, the results support the notion of at least two systems of category learning.
引文
[1]Ashby F G, Maddox W T. Integrating information from separable psychological dimensions, Journal of experimental psychology:Human Perception and Performance,1990,16(3):598-612
[2]Ashby F G, Alfonso-Reese L A, Turken A U, et al. A neuropsychological theory of multiple systems in category learning, Psychological Review,1998,105(3): 442-481
[3]Bruner J S, Goodnow J J, Austin G A. A study of thinking, New York:John Wiley,1956
[4]M·W·艾森克,M·T·基恩著.认知心理学(第四版)(上册).高定国,肖晓云译.上海：华东师范大学出版社
[5]Ashby F G, Gott R E. Decision rules in the perception and categorization of multidimensional stimuli. Journal of Experimental Psychology:learning, Memory, and Cognition,1988,14(1):33-53
[6]Ashby F G, Maddox W T. Relations between prototype, exemplar, and decision bound models of categorization. Journal of Mathematical Psychology,1993, 37:372-400
[7]Waldron E M, Ashby F G. The effects of concurrent task inference on category learning, Psychonomic, Bulletin & Review,2001,8:168-176
[8]Maddox W T, Filoteo J V, Hejl K D, et al. Category number impacts rule-based but not information-integration category learning:evidence for dissociable category-learning systems, Journal of experimental psychology:learning, memory, and cognition.2004,30(1):227-245
[9]Maddox W T, Ashby F G, Ing A D, et al. Disrupting feedback processing interferes with rule-based but not information-integration category learning, Memory & Cognition, Austin,2004,32(4):582-591
[10]Ashby F G, Queller S, Berretty P T. On the dominance of unidimensional rules inunsupervised categorization, Perception& Psychophysics,1999, 61:1178-1199
[11]Ashby F G, Maddox W T, Bohil C J. Observational versus feedback training in rule-based and Information-ntegration category learning, Memory & Cognition,2002,30(5):666-667
[12]Maddox W T, Ashby F G, Bohil C J. Delayed feedback effects on rule-based and information-integration category learning, Journal of experimental psychology:learning, memory, andcognition,2003,29 (4):650-662
[13]Ashby F G, Ell S W, Waldron E M. Procedual learning in perceptual categorization, Memory&Cognition,2003,31(7):1114-1125
[14]Maddox W T, Bohil C J, Ing A D. Evidence for a procedural-learning based system in perceptual category learning, Psychonomic Bulletin & Review, 2004,11(5):945-952
[15]Maddox W T, Filoteo J V, Laurizen J S, et al. Discontinuous categories affect information-integration but not rule-based category learning, Journal of experimental psychology:learning, memory, and cognition,2005,31(4):654-669
[16]knowlton B J, Mangels J A, Squire L R. A neostriatal habit learning system in humans, Science,1996,273:1399-1402
[17]Filoteo J V, Maddox W T, Salmon D P, et al. Information-integration category learning inpatients with striatal dysfunction, Neuropsychology, 2005,19.(2):212-222
[18]Ashby F G, Nobel S, Filoteo J V, et al. Category learning deficits in Parkinson's disease, Neuropsychology,2003,17(1):115-124
[19]Smith J G, McDowall J. When artificial grammar acquisition in Parkinson s disease is impaired:The case of learning via trial-by-trial feedback. Brain Research,2006,1067:216-228
[20]Knowlton B J, Squire L R. Artificial grammar learning depends on implicit acquisition of both abstract and exemplar-specific information, Journal of Experimental Psychology:learning, Memory, and Cognition,1996,22:169-181
[21]Zeithamova, D., Maddox, W. T.. Dual-task interference in perceptual category learning. Memory & Cognition,2006,34:387-398.
[22]Marci S. DeCaro, Robin D. Thomas, Sian L. Beilock. Individual differences in category learning:Sometimes less working memory capacityis better than more. Cognition,2008,107:284-294
[23]Constantinidis, C. et al. The sensory nature of mnemonic representation in the primate prefrontal cortex. Nat. Neurosci.2001,4:311-316
[24]Curtis, C. E. and D'Esposito,M. Persistent activity in theprefrontal cortex during workingmemory. Trends Cogn. Sci.2003,7,415-423
[25]Kimberg, D. Y. et al. Frontal lobes:Cognitive neuropsychological issues. In Behavioral Neurology and Neuropsychology (2nd edn) (Feinberg, T. E. and Farah, M.J., eds),2003,393-400,
[26]Robinson, A. L. et al. The utility of the Wisconsin Card Sorting Test in detecting and localizing frontal lobe lesions. J. Consult. Clin. Psychol. 1980,48:605-614
[27]Konishi, S. et al. Contribution of working memory to transient activation in human inferior prefrontal cortex during performance of the Wisconsin Card Sorting Test. Cereb. Cortex,1999,9:745-753
[28]Lombardi, W. J. et al. Wisconsin Card sorting Test performance following head injury:Dorsolateral fronto-striatal circuit activity predicts perseveration. J. Clin. Exp. Neuropsychol.1999,21:2-16
[29]Rao, S. M. et al. FunctionalMRI evidence for subcortical participation in conceptual reasoning sklls. Neuroreport,1997,8:1987-1993
[30]Rogers, R. D. et al. Contrasting cortical and subcortical activations produced by attentional-set shifting and reversal learning in humans. J. Cogn. Neurosci.2000,12:142-162
[31]Hayes, N. A.,& Broadbent, D. E. (1988). Two modes of learning for interactive tasks. Cognition,28,249-276.
[32]Green, R. E. A.,& Shanks, D. R. (1993). On the existence of independent explicit and implicit learning systems:An examination of some evidence. Memory & Language,21,304-317.
[33]Volz, H-P. et al. Brain activation during cognitive stimulation with the Wisconsin Card Sorting Test:A functional MRI study on healthy volunteers and schizophrenics. Psychiatry Res. Neuroimaging,1997,75:45-157
[34]张奇,刘万伦.规则策略和样例策略在归类过程中的运用.心理科学进展2007,15(1)：78-87
[35]刘万伦,张奇.类别学习的神经心理学研究.心理科学进展2008,16(1)：36-41
[2]Ashby F G, Alfonso-Reese L A, Turken A U, et al. A neuropsychological theory of multiple systems in category learning, Psychological Review,1998,105(3): 442-481
[3]Bruner J S, Goodnow J J, Austin G A. A study of thinking, New York:John Wiley,1956
[4]M·W·艾森克,M·T·基恩著.认知心理学(第四版)(上册).高定国,肖晓云译.上海：华东师范大学出版社
[5]Ashby F G, Gott R E. Decision rules in the perception and categorization of multidimensional stimuli. Journal of Experimental Psychology:learning, Memory, and Cognition,1988,14(1):33-53
[6]Ashby F G, Maddox W T. Relations between prototype, exemplar, and decision bound models of categorization. Journal of Mathematical Psychology,1993, 37:372-400
[7]Waldron E M, Ashby F G. The effects of concurrent task inference on category learning, Psychonomic, Bulletin & Review,2001,8:168-176
[8]Maddox W T, Filoteo J V, Hejl K D, et al. Category number impacts rule-based but not information-integration category learning:evidence for dissociable category-learning systems, Journal of experimental psychology:learning, memory, and cognition.2004,30(1):227-245
[9]Maddox W T, Ashby F G, Ing A D, et al. Disrupting feedback processing interferes with rule-based but not information-integration category learning, Memory & Cognition, Austin,2004,32(4):582-591
[10]Ashby F G, Queller S, Berretty P T. On the dominance of unidimensional rules inunsupervised categorization, Perception& Psychophysics,1999, 61:1178-1199
[11]Ashby F G, Maddox W T, Bohil C J. Observational versus feedback training in rule-based and Information-ntegration category learning, Memory & Cognition,2002,30(5):666-667
[12]Maddox W T, Ashby F G, Bohil C J. Delayed feedback effects on rule-based and information-integration category learning, Journal of experimental psychology:learning, memory, andcognition,2003,29 (4):650-662
[13]Ashby F G, Ell S W, Waldron E M. Procedual learning in perceptual categorization, Memory&Cognition,2003,31(7):1114-1125
[14]Maddox W T, Bohil C J, Ing A D. Evidence for a procedural-learning based system in perceptual category learning, Psychonomic Bulletin & Review, 2004,11(5):945-952
[15]Maddox W T, Filoteo J V, Laurizen J S, et al. Discontinuous categories affect information-integration but not rule-based category learning, Journal of experimental psychology:learning, memory, and cognition,2005,31(4):654-669
[16]knowlton B J, Mangels J A, Squire L R. A neostriatal habit learning system in humans, Science,1996,273:1399-1402
[17]Filoteo J V, Maddox W T, Salmon D P, et al. Information-integration category learning inpatients with striatal dysfunction, Neuropsychology, 2005,19.(2):212-222
[18]Ashby F G, Nobel S, Filoteo J V, et al. Category learning deficits in Parkinson's disease, Neuropsychology,2003,17(1):115-124
[19]Smith J G, McDowall J. When artificial grammar acquisition in Parkinson s disease is impaired:The case of learning via trial-by-trial feedback. Brain Research,2006,1067:216-228
[20]Knowlton B J, Squire L R. Artificial grammar learning depends on implicit acquisition of both abstract and exemplar-specific information, Journal of Experimental Psychology:learning, Memory, and Cognition,1996,22:169-181
[21]Zeithamova, D., Maddox, W. T.. Dual-task interference in perceptual category learning. Memory & Cognition,2006,34:387-398.
[22]Marci S. DeCaro, Robin D. Thomas, Sian L. Beilock. Individual differences in category learning:Sometimes less working memory capacityis better than more. Cognition,2008,107:284-294
[23]Constantinidis, C. et al. The sensory nature of mnemonic representation in the primate prefrontal cortex. Nat. Neurosci.2001,4:311-316
[24]Curtis, C. E. and D'Esposito,M. Persistent activity in theprefrontal cortex during workingmemory. Trends Cogn. Sci.2003,7,415-423
[25]Kimberg, D. Y. et al. Frontal lobes:Cognitive neuropsychological issues. In Behavioral Neurology and Neuropsychology (2nd edn) (Feinberg, T. E. and Farah, M.J., eds),2003,393-400,
[26]Robinson, A. L. et al. The utility of the Wisconsin Card Sorting Test in detecting and localizing frontal lobe lesions. J. Consult. Clin. Psychol. 1980,48:605-614
[27]Konishi, S. et al. Contribution of working memory to transient activation in human inferior prefrontal cortex during performance of the Wisconsin Card Sorting Test. Cereb. Cortex,1999,9:745-753
[28]Lombardi, W. J. et al. Wisconsin Card sorting Test performance following head injury:Dorsolateral fronto-striatal circuit activity predicts perseveration. J. Clin. Exp. Neuropsychol.1999,21:2-16
[29]Rao, S. M. et al. FunctionalMRI evidence for subcortical participation in conceptual reasoning sklls. Neuroreport,1997,8:1987-1993
[30]Rogers, R. D. et al. Contrasting cortical and subcortical activations produced by attentional-set shifting and reversal learning in humans. J. Cogn. Neurosci.2000,12:142-162
[31]Hayes, N. A.,& Broadbent, D. E. (1988). Two modes of learning for interactive tasks. Cognition,28,249-276.
[32]Green, R. E. A.,& Shanks, D. R. (1993). On the existence of independent explicit and implicit learning systems:An examination of some evidence. Memory & Language,21,304-317.
[33]Volz, H-P. et al. Brain activation during cognitive stimulation with the Wisconsin Card Sorting Test:A functional MRI study on healthy volunteers and schizophrenics. Psychiatry Res. Neuroimaging,1997,75:45-157
[34]张奇,刘万伦.规则策略和样例策略在归类过程中的运用.心理科学进展2007,15(1)：78-87
[35]刘万伦,张奇.类别学习的神经心理学研究.心理科学进展2008,16(1)：36-41