类别学习是个体获得知识和技能的主要途径，而基于规则的类别学习或人工类别学习则是规则与概念获得的主要形式。自Bruner, Goodnow et al.（1956）以来，人工类别学习在行为水平上得到了大量研究，提出至少四种基本的研究范式，并在此基础上设计了大量的具体实验任务；而近十年来，以脑部损伤病人为研究对象的神经心理学在讨论类别学习的神经机制方面做出了重要贡献，由于某个部位（比如，额叶）受到损伤的病人无法完成特定形式的类别学习任务，因此可以有力地确定任务要求的心理加工与受到损伤的脑结构之间的关系。
The Neural Mechanism of Artificial Category Learning
The category learning is the main approach of acquiring knowledge and skills, and the based-rule category learning or artificial category learning is the main form of acquiring rule and concept. Since Bruner, Goodnow et al. (1965), on the level of behavioral research, there lots of researches have been conducted for the artificial category learning, and on the basis of at least four kinds of paradigms a number of experimental tasks were designed. And since 1990, the neuro-psychology, in which the subjects were brain lesion patient, contributed to understand the neural mechanism of category learning; because specific brain area was damaged the subjects can not complete specific category learning tasks, thus the result can powerfully ascertain the relationship between the mental processing in the task and the specific brain area damaged.
Although the neuro-psychological studies contributed much to our understanding of neural mechanism of category learning, the final conclusion is still far, and there are many room to improve the past relative researches. The current situation is that the kind of paradigm and experimental task is numerous and they are different very much from each other. More important, there is little consist results from these researches, and the theories based on these results are different from each other. Many cognitive activities are included in the category learning, however, there must exist the processing that reflects the nature of category learning, which is omitted in the past researches.
For the complexity of category learning, in this paper we would focus on the artificial category learning. We believe, the cognitive processing reflecting the nature of category learning is the category induction, by which the individual could acquire a general conclusion, which is the common feature in all category learning tasks. However, before ascertained the general conclusion is still a hypothesis, the processing of checking the hypothesis is categorization, in which the category membership of some stimulus is judged by the hypothesis, if the answer is wrong then the hypothesis is wrong, or the hypothesis will be supported. Therefore, we suppose that the categorization plays an important role in the category learning, for the feedback from categorization would directly affirm or denied the hypothesis from category induction. In the category induction and categorization, the cognitive control is important, in such higher level cognitive processing, cognitive control can detect the change or abnormality in the information and correct the way of thinking according to the anticipation: control the irrelative-task information and focus on the relative-task information.
Based on the above analysis, we design new category learning task. There are many features in the new task: first, the stimuli is geometric figures including color and orientation, which excludes effectively the difference of individual knowledge; second, the task can easily be decomposed into relative independent sub-tasks, such as category induction task, categorization task and cognitive control task etc.; third, the nature of task is still category learning, in which the subject must acquire the rule and give correct judgment according to it; forth, the task is relative easy, the three kinds of sub-tasks could be completed in one second which give the possibility for the ERP recorded during the solving these tasks.
Applying high density ERP technique and dipole source analysis, we studied the neural mechanism of category learning. Firstly, by the effective decomposing the category learning task, the category learning was decomposed into three relative and associative sub-tasks: category induction, categorization and cognitive control, the involving cognitive processes in the category learning were studied in cross aspect. And then, each sub-process would be studied in depth respectively, the ERP components, temporal courses and the corresponding cognitive processes involving in the three sub-processes were studied. The main results are showed in the following:
①,The ERP effect of category induction reflects on the LPC component, the corresponding processing attain the peak at 480 ms, the result of dipole source indicates that the encephalic source is about MTL, in which the active level of hippocampus in the category induction task is obvious higher than that in the feature matching task. Considering the relationship between hippocampus and novel connection formation, the activity of hippocampus in sovlving the task further ascertains that the nature of task is category induction.
②,Whether under clear anticipation or ambiguous anticipation, the ERP effect of categorization begins from N2 component and lasts till P3 component, the corresponding encephalic source result shows categorization processing exists from ACC activity to MTL activity, and the activity of ACC corresponds to N2 difference, and the activity of MTL corresponds to P3 difference. These results suggested that ACC is sensitive to the change in the information (violate the anticipation), the activity of ACC begins stronger indicates that the non-target is coming, and MTL plays an important role in the instrumentation of experience in the long-term memory for ascertaining the membership of stimuli.
③,The findings about cognitive control show that the irrelative-task information would elicit higher amplitude of N2 component whose corresponding encephalic source is about ACC, and the irrelative-task information would further elicit higher amplitude of P3 component in the negative orientation whose corresponding encephalic source is about PFC. These results provide direct support for the conflict monitoring theory of cognitive control, and suppose that there exist an activity transfer from ACC to PFC in the cognitive control, the possible processing is that ACC is responsible for the monitoring the change in the information and PFC subsequently is responsible for control the change.
Based on the integration of the results reported in current and past literatures, we put out a integrated neural mechanism mode of artificial category learning, in this mode the key brain structures include ACC, PFC and MTL. The visual information was processed primarily in the occiput and associated cortex, and then maintained in the working memory unit of PFC, and soon integrated in the level of perception in the PFC which reflects on the P2 and N2 components. The occurrence of N2 component indicates that the information processing has been stepped into the controlled phase, which happens in category induction, categorization and cognitive control three sub-processes. The dipole source results indicates that the occurrence of N2 is related with the activity of ACC which suggests that the brain detects the change in the information, and then the activity of ACC triggers PFC. In the category induction, FPC would transfer the feature information maintained into the MTL, the hippocampus in which conducts the abstract of common features during the category induction. In categorization, ACC would trigger the PFC and the later could judge whether the stimulus is the target stimuli directly according the information from ACC, which reflects on P3. The feedback from categorization would be used judge whether the rule maintained in PFC is correct. If the rule is wrong then the loop maintaining the rule would be disrupted and new rule would be selected through attention switch, and judge it’s membership again by categorization. In the attention switch, ACC and PFC play main role, ACC transfers the information whether the rule is right to PFC and PFC conducts the switch of attention.
This research has important theoretic and practical significance. For the theoretic significance, this research improves further theories related with artificial category learning, and new paradigm and method have been put out. Under the new study paradigm, the complex category learning could be deposed into clear sub-processes, and further in-depth studies could be done on each sub-process. For the practical significance, category learning is the main cognitive activity in acquirement of rule and concept, and the study on the neural mechanism of category learning is significant value for our understanding and analysis of human learning behavior, too, based on the results more effective neural-psychological diagnostic project would be put out for the cognitive function abnormality.
Key words: event-related potential, category learning, categorization, cognitive control, late positive component, Anterior cingulate cortex, Prefrontal cortex
人类进化,人类起源,人类基因研究,人的研究报告 人的研究报告1 人的研究报告2
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