语篇中指代词的分布规律与心理机制*

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1 ~ 200 Advances in Psychological Science * ( ) B842.5 Hofstadter [1] 1977 Sternberg 1 A a b c d B a b c B d * ( : ) Tel: ; liuchang@pine.njnu.edu.cn

2 Holyoak Markman Piaget Sternberg Gentner [2, 3] Keane List A Bill is smart Bill is tall List B Fido is hungry Blackie is friendly Tom is timid Blackie is frisky Tom is tall Rover is hungry Steve is smart Rover is friendly A B Keane Steve is smart Fido is hungry Steve is smart A Fido is hungry B 1997 Keane [5]

3 Keane [4] Keane Kubose [5] Gentner [6] Wharton [7] Yanowitz [8] Yanowitz [9] 2.2 [10]

4 Salthouse [11] Salthouse [12] [13,14] Jensen [15] Cowan [16] [ 11] 1991 Salthouse [17] Baddeley 2001 Baddeley [18] 1992 Just Carpenter [19] [10,20] 1990 Kyllonen Christal [21] 2002 Primi [22]

5 , 1991 Salthouse [23] ~ Tucker Warr [24] 1996 Fry Hale [25] 7 19 [26] 2002 Conway [14] (PET) (fmri) [27] 1997 Parbhakaran fmri Parbhakaran FMRI Parbhakaran

6 Gur [28] Gur [29] (PET) Goel [30] PET Golding [31] Watson Wharton [32] Wharton PET 12 (dorsomedial) [33] 4

7 [1] Gentner D, Holyoak K J, Kokinov B N. The analogical mind: perspectives from cognitive science. London: The MIT Press, 2001: 499~538 [2],,.., 2000, 23(6): [3],.. ( ), 2002, 28(4): 44~47 [4] Keane M T. What makes an analogy difficult? The effects of order and causal structure on analogical mapping. Journal of Experimental Psychology: Learning,Memory,and Cognition, 1997, 23(4): 946~967 [5] Kubose T T, Holyoak K J, Hummel J E. The role of textual coherence in incremental analogical mapping. Journal of Memory & Language, 2002, 47(3): 407~435 [6] Gentner D, Markman A B. Structure mapping in analogy and similarity. American Psychologist, 1997, 52: 45~56 [7] Wharton C M, Holyoak K J, Lange T E. Remote analogical reminding. Memory & Cognition, 1996, 24: 629~643 [8] Yanowitz K L. The effects of similarity of theme and instantiation in analogical reasoning. American Journal of Psychology, 2001, 114(4): 547~567 [9] Yanowitz K L. Transfer of structure-related and arbitrary information in analogical reasoning. The Psychological Record, 2001, 51: 357~379 [10] Süβ H M, Oberauer K, Wittmann W W, et al. Working-memory capacity explains reasoning ability and a little bit more. Intelligence, 2002, 30: 261~288 [11] Salthouse T A. The processing speed theory of adult age differences in cognition. Psychological Review, 1996, 103(3): 403~428 [12] Salthouse T A. Speed mediation of adult age differences in cognition. Developmental Psychology, 1993, 29: 722~738 [13] Bors D A, Forrin B. Age, speed of information processing, recall, and fluid intelligence. Intelligence, 1995, 20: 229~248 [14] Conway A R A, Cowan N, Bunting M F, et al. A latent variable analysis of working memory capacity, short-term memory capacity, processing speed, and general fluid intelligence. Intelligence, 2002, 30: 163~183 [15] Jensen A R. Why is reaction time correlated with psychometric g? Curr. Directions Pshcho. Sci, 1993, 2: 53~56 [16] Conwan N, Wood N L, Wood P K, et al. Two separate verbal processing rates contributing to short-term memory span. Journal of Experimental Psychology: General, 1998, 127: 141~160 [17] Salthouse T A. Decomposing adult age difference in working memory. Developmental Psychology, 1991, 27(5): 763~777 [18] Baddeley A D. Is working memory still working? American Psychologist, 2001, 56(11): 851~864 [10] Just M A, Carpenter P A. A capacity theory of comprehension: individual differences in working memory. Psychological Review, 1992, 99: 122~149 [20] Engle R W, Tuholski S W, Laughlin J E, et al. Working memory, short-term memory and general fluid intelligence: a latent variable approach. Journal of Experimental Psychology: General, 1999, 128: 309~331 [21] Kyllonen P C, Christal R E. Reasoning ability is ( little more than ) working-memory capacity?! Intelligence, 1990, 14: 389~433 [22] Primi R. Complexity of geometric inductive reasoning tasks: Contribution to the understanding of fluid intelligence. Intelligence, 2002, 30(1): 41~70 [23] Salthouse T A. Mediation of adult age differences in cognition by reductions in working memory and speed of processing. Psychological Science, 1991, 2(3): 179~183 [24] Tucker P, Warr P. Intelligence, elementary coginitive components, and cognitive styles as predictors of complex task performance. Personality and individual differences, 1996, 21(1): 91~102

8 [25] Fry A F, Hale S. Processing speed, working memory, and fluid intelligence: evidence for a developmental cascade. Psychological Science, 1996, 7: 237~241 [26] Kail R. Speed of information processing: Developmental change and links to intelligence. Journal of School Psychology, 2000, 38(1): 51~61 [27] Prabhakaran V, Jennifer A L, Smith J E, et al. Neural substrates of fluid reasoning: an fmri study of neocortical activation during performance of the Raven s Progressive Matrices Test. Cognitive Psychology, 1997, 33: 43~63 [28] Gur R C, Ragland J D, Resnick S M, et al. Lateralized increases in cerebral blood flow during performance of verbal spatial tasks: Relationship with performance level. Brain and Cognition, 1994, 24: 244~258 [29] Halford G S. Analogical reasoning and conceptual complexity in cognitive development. Human Development, 1992, 35: 193~217 [30] Goel V, Gold B, Kapur S, et al. Neuroanatomical correlates of human reasoning. Journal of Cognitive Neuroscience, 1998, 10(3): 293~302 [31] Golding E. The effect of unilateral brain lesion on reasoning. Cortex, 1981, 17: 31~40 [32] Wharton C M, Grafman J, Flitman S S, et al. Toward neuroanatomical models of analogy: A positron emission tomography study of analogical reasoning. Cognitive Psychology, 2000, 40: 173~197 [33].., 2002, 34(6): 634~642 Some Behavioral and Functional Neuroimaging Studies on Analogical Reasoning Tang Huilin, Liu Chang (Institute of Psychology, Nanjing Normal University, Nanjing ) Abstract: As one of central abilities in human cognitive development, analogical reasoning, which is different from deductive and inductive reasoning, has become an active field to study in current researching on human cognition. It was Indicated that analogical reasoning is not only affected by some characteristics of items, such as order, causal structure, contextual coherence et al, but also associated with other cognitive abilities, such as processing speed and working memory. The relationship between analogical reasoning and working memory is also revealed by functional neuroimaging, which indicated that the anterior and posterior regions of left hemisphere of human brain is involved in analogical reasoning. Key words: analogical reasoning, processing speed, working memory.

9 British Telecom IBM (Emotion Mouse) [14] MIT (Kansei Information Processing) [15] 1996 MIT Picard [16] P.Ekman [17] Picard [18] (Wearable Computers) 4

10 [1] Lewis M, Haviland-Jones J. Handbook of Emotion. 2nd ed. New York Guilford Press, ~520 [2] Cacioppo J T, Berntson G G, Adolphs R, et al. Foundations in social neuroscience. Cambridge,MA: MIT Press, ~236 [3] Sternberg R J. Measuring the Intelligence of an Idea: How Intelligent is the idea of Emotional Intelligence? In: Ciarrochi J, Forgas J P,Mayer J D eds. Emotional Intelligence in everyday life. Philadelphia:Psychology Press, ~193 [4] Bar-On R, Parker J D A. Handbook of Emotional Intelligence. San Francisco:Jossey-Bass, ~386 [5] Ciarrochi J, Forgas J P J, Mayer J D. Emotional intelligence in everyday life. Philadelphia: Psychology Press, 2001 [6] Picard R W. Affective Computing.Cambridge, MA: MIT Press, ~9 [7] Mayer J D, Salovey P, Caruso D R, et al. Emotional intelligence as a standard intelligence: A Reply. Emotion, ~242 [8] Goleman ~48 [9] Bar-On R.Emotional Quotient Inventory EQ-i : Technical Manual. Toronto: Multi- Health Systems, ~23 [10] Minsky M. The Society of Mind. New York: Simon & Schuster, ~15 [11]

11 [12] Epstein, Jeffrey H. Computers with emotions.the Futurist, 1998, 32(3): 12 [13] Barnes A, Thagard P. Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society. Erlbaum, ~429 [14] Andrews P.Affective computing:knowing how you feel,executive Tek Report.IBM Global Services.August 30,2001 [15] Akamatsu S. Science and Technology in Human Information Processing ¾ Computational Studies on KANSEI Information Conveyed by Human Face. ATR Technical Publications, 1997, 2: 239~242 [16] [17] Ekman P. Facial expressions. In: Dalgleish T, Power T eds. The Handbook of Cognition and Emotion. Sussex. UK: John Wiley & Sons, Ltd, ~320 [18] Picard R W. Frustrating the user on purpose:a step toward building an affective computer.interacting with Computers, 2002, 14 2 : 93~118 Discussing the Relations Between Emotional Intelligence and Affective Computing in Artificial Intelligence Simply Xu Yuanli, Guo Dejun (Department of Psychology, Capital Normal University, Beijing ) Abstract: Emotional intelligence is the ability which processes emotion and emotional information, and affective computing in artificial intelligence is to make the computer possess the ability of processing affective information between man-machine interacting, it can draw an analogy between the computer and the brain in processing emotional information. In the last few years, artificial intelligence experts have already been cognizant of the important function and meaning of emotional intelligence in affective computing, the computer has been possessed to identify and express affective ability, and the computer have been developed with inferior affective ability. The development and application of senior affective computer will depend on the close collaboration between artificial intelligence experts and psychologists, both their achievements can be used for reference and complementary each other. Key words: emotional intelligence, affective computing, artificial intelligence, relation.

言语理解中的知觉表征与命题表征*

言语理解中的知觉表征与命题表征* * (,510631) 96 t 1 2 3 1 propositional symbol system [1] [2] [3-5] Barsalou perceptual symbol system [6-8] arbitrary linguistic-like analogue perceptual [7] 1 * 30270477 t-a-b-l-e [ 9, 10 ] [11] Barsalou