Go to the content. | Move to the navigation | Go to the site search | Go to the menu | Contacts | Accessibility

| Create Account

Hope, Thomas (2008) On the Structure of Semantic Number Knowledge. [Ph.D. thesis]

Full text disponibile come:

[img]
Preview
Documento PDF
3072Kb

Abstract (english)

This doctoral thesis present the results of five distinct projects which all share a common focus - the structure of cognitive number processing. Two of the projects employ psychophysical methods to (a) establish some perceptual constraints on the processing of very large numbers (or very long digit strings) and (b) demonstrate a doissociation between subjects' sensitivities to these (large) numbers' holistic content from their sensitivities to the numbers' single-digit components. The other three projects are primarily computational; each proposes a novel model-building method, then applies it to a problem of relevance to numerical cognition. The results include (a) a novel proposal for the format of semantic number knowledge, which is supported by recent neurophysiological data, (b) a model-space analysis which suggests that this new format may be more effective than its conventional counterparts in driving models of multi-digit number comparison, and (c) a demonstration of model-building with minimal assumptions, which captures the optimal and near-optimal features of neural information processing in a well-known decision problem.


Statistiche Download - Aggiungi a RefWorks
EPrint type:Ph.D. thesis
Tutor:Zorzi, Marco
Ph.D. course:Ciclo 20 > Scuole per il 20simo ciclo > SCIENZE PSICOLOGICHE > SCIENZE COGNITIVE
Data di deposito della tesi:31 July 2008
Anno di Pubblicazione:31 July 2008
Key Words:numerical cognition, computational models, neural networks, representation, number comparison, evolution
Settori scientifico-disciplinari MIUR:Area 11 - Scienze storiche, filosofiche, pedagogiche e psicologiche > M-PSI/01 Psicologia generale
Struttura di riferimento:Dipartimenti > Dipartimento di Psicologia dello Sviluppo e della Socializzazione
Codice ID:1091
Depositato il:02 Dec 2008
Simple Metadata
Full Metadata
EndNote Format

Bibliografia

I riferimenti della bibliografia possono essere cercati con Cerca la citazione di AIRE, copiando il titolo dell'articolo (o del libro) e la rivista (se presente) nei campi appositi di "Cerca la Citazione di AIRE".
Le url contenute in alcuni riferimenti sono raggiungibili cliccando sul link alla fine della citazione (Vai!) e tramite Google (Ricerca con Google). Il risultato dipende dalla formattazione della citazione.

1. Ackley, D. H., Hinton, G. E., & Sejnowski, T. J. (1985). A Learning Algorithm for Boltzmann Machines, Cognitive Science, 9, 147-169. Cerca con Google

2. Aharanov, R., Segev, L., Meilijson, I., & Ruppin, E. (2003). Localization of function via lesion analysis. Neural Computation, 14(4), 885-913. Cerca con Google

3. Ahmad, K., Casey, M. C., & Bale, T. (2002). Connectionist Simulation of Quantification Skills. Connection Science, 14(3), 165-201. Cerca con Google

4. Akin, O. & Chase, W. (1978). Quantification of three-dimensional structures. Journal of Experimental Psychology: Human Perception and Performance, 4, 397–410. Cerca con Google

5. Aleksander, I. (1989). Neural Computing Architectures: the design of brain-like machines. Kogan Page. Cerca con Google

6. Ashcraft, M. H. (1992). Cognitive arithmetic: a review of data and theory. Cognition, 44, 75-106. Cerca con Google

7. Ashcraft, M., & Christy, K. (1995). The frequency of arithmetical facts in elementary texts: addition and multiplication in grades 1–6. Journal for Research in Mathematical Education, 26, 396-421. Cerca con Google

8. Atkinson, J., Campbell, F., & Francis, M. R. (1976). The magic number 4 ± 0: A new look at visual numerosity judgements. Perception, 5, 327–334. Cerca con Google

9. Bächthold, D., Baumüller, M., & Brugger, P. (1998). Stimulus-response compatibility in representational space. Neuropsychologia, 36, 731–735. Cerca con Google

10. Balakrishnan, J. D. & Ashby, F. G. (1991). Is subitizing a unique numerical ability? Perceptual Psychophysics, 50(6), 555–564. Cerca con Google

11. Balakrishnan, J. D. & Ashby, F. G. (1992). Subitizing: Magical numbers or mere superstition? Psychological Review, 54, 80–90 Cerca con Google

12. Bakker, B. (2000). The adaptive behavior approach to psychology. Cognitive Processing, 1, 39-70. Cerca con Google

13. Bechtel, W. & Abrahamsen, A.(1991). Connectionism and the Mind (chapter 6) Oxford: Blackwell. Cerca con Google

14. Beer, R. D. (1996). Towards the Evolution of Dynamical Neural Networks for Minimally Cognitive Behavior. In P. Maes, M. Mataric, J. Meyer, J. Pollack & S. Wilson (Eds.), From animals to animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior (p. 421-429). MIT Press. Cerca con Google

15. Beer, R. D. (2000). Dynamical approaches to cognitive science. Trends in Cognitive Sciences, 4(3), 91-99. Cerca con Google

16. Beer, R. D. (2003). The Dynamics of Active Categorical Perception in an Evolved Model Agent. Adaptive Behavior, 11, 209-243. Cerca con Google

17. Berkeley, I., S., N. (1997). Some Myths of Connectionism, http://www.ucs.louisiana.edu/~isb9112/dept/phil341/myths/myths.html. Vai! Cerca con Google

18. Bialystok, E. & Codd, J. (2000). Representing quantity beyond whole numbers: Some, none and part. Canadian Journal of Experimental Psychology, 54, 117-128. Cerca con Google

19. Biro, D., & Matsuzawa, T. (2001). Use of numerical symbols by the chimpanzee (Pan troglodytes): Cardinals, ordinals, and the introduction of zero. Animal Cognition, 4, 193-199. Cerca con Google

20. Blumberg, B. (1995). Multi-Level Direction of Autonomous Creatures for Real-Time Virtual Environments. Proceedings of the 22nd annual conference on Computer graphics and interactive techniques, 47-54, ACM: New York. Cerca con Google

21. Bonato, M., Fabbri, S., Umiltà, C., & Zorzi, M. (2007). The Mental Representation of Numerical Fractions: Real or Integer? Journal of Experimental Psychology: Human Perception and Performance, 33(6), 1410-1419. Cerca con Google

22. Botvinick, M. & Plaut, D. C. (2004). Short-term memory for serial order: A recurrent neural network model. Psychological Review, 113, 201-233. Cerca con Google

23. Brannon, E.M., & Terrace, H.S. (2003). The evolution and ontogeny of ordinal numerical ability. In M. Beckoff (Ed.), The Cognitive Animal, 197–204, MIT Press. Cerca con Google

24. Brannon, E., Wusthoff, C., Gallistel, C. R., & Gibon, J. (2001). Numerical subtraction in the pigeon: Evidence for a linear subjective number scale. Psychological Science, 12, 238-243. Cerca con Google

25. Brooks, R. A. (1991). Intelligence without representation. Artificial Intelligence, 47, 139-159. Cerca con Google

26. Butterworth, B. (1999). The Mathematical Brain, Macmillan Butterworth, B. (2005). Developmental Dyscalculia. In J. I. D. Campbell (Ed.) The Handbook of Mathematical Cognition, Psychology Press, 455-467. Cerca con Google

27. Butterworth, B., Zorzi, M., Girelli, L., & Jonckheere, A. R. (2001). Storage and retrieval of addition facts: The role of number comparison. Quarterly Journal of Experimental Psychology, 54A, 1005-1029. Cerca con Google

28. Bynner, J. & Parsons, S. (1997). Does Numeracy Matter? Evidence from the National Child Development Study on the Impact of Poor Numeracy on Adult Life. Report to the UK Basic Skills Agency, London. Cerca con Google

29. Campbell, J. I. D. (1995). Mechanisms of simple addition and multiplication: A modified networkinterference theory and simulation. Mathematical Cognition, 1, 121-164. Cerca con Google

30. Campbell, J. I. D., & Xue, Q. (2001). Cognitive arithmetic across cultures. Journal of Experimental Psychology: General, 130, 299-315. Cerca con Google

31. Cantlon, J. & Brannon, E.M. (2006). Shared system for ordering small and large numbers in monkeys and humans. Psychological Science, 17(5), 401-406. Cerca con Google

32. Cappelletti, M., Butterworth, B., & Kopelman, M. (2001). Spared numerical abilities in a case of semantic dementia. Neuropsychologia, 39, 1224-1239. Cerca con Google

33. Cappelletti, M., Kopelman, M., & Butterworth, B. (2002). Why semantic dementia drives you the dogs (but not to the horses): A theoretical account. Cognitive Neuropsychology, 19(6), 483–503. Cerca con Google

34. Carey, S. (1998). Knowledge of Number: its Evolution and Ontogeny. Science, 282, 641-642 Cerca con Google

35. Carey, S. (2004). On the Origin of Concepts, Daedulus. Cerca con Google

36. Chomsky, N. (1959). Review of Verbal Behavior by B.F. Skinner. Language, 35, 26-58. Cerca con Google

37. Ciaramitaro, V. M. & Glimcher, P. W. (2001). Stimulus probability redirects spatial attention: an enhancement of sensitivity in humans and monkeys. Vision Research, 41, 57-75. Cerca con Google

38. Cipolotti, L., Butterworth, B., & Denes, G. (1991). A specific deficit for numbers in a case of dense acalculia. Brain, 114, 2619-2637. Cerca con Google

39. Clark, A. (1999). Embodied, situated, and distributed cognition. In W. Betchel and G. Graham (Eds), A Companion to Cognitive Science, Malden, MA: Blackwell Publishing. Cerca con Google

40. Cockcroft, W. H. (1986). Mathematics Counts. London: Her Majesty's Stationery Office. Cerca con Google

41. Colby C. L., Duhamel, J. R., & Goldberg, M. E. (1996). Visual, presaccadic, and cognitive activation of single neurons in monkey lateral intraparietal area. Journal of Neurophysiology, 76(5), 2841-2852. Cerca con Google

42. Cooper, R. & Shallice, T. (2000). Contention scheduling and the control of routine activities. Cognitive Neuropsychology, 17, 297–338. Cerca con Google

43. Cooper, R., & Shallice, T. (2006). Structured representations in the control of behavior cannot be so easily dismissed: A reply to Botvinick and Plaut. Psychological Review, 113, 887-916. Cerca con Google

44. Crick, F. H. C. (1989). The current excitement about neural networks. Nature, 337, 129-132. Cerca con Google

45. Crowther-Heyk, H. (1999). George Miller, language, and the computer metaphor. History of Psychology, 2, 37-64. Cerca con Google

46. Crutchfield, J. P. (1998). Dynamical embodiments of computation in cognitive processes, Behavioral and Brain Sciences, 21(5), 635-637. Cerca con Google

47. Dehaene, S. (1997). The Number Sense: How the Mind Creates Mathematics, Oxford University Press Cerca con Google

48. Dehaene, S. (2001) Subtracting pigeons: Logarithmic or linear ? Psychological Science, 12, 244-246. Cerca con Google

49. Dehaene, S. (2003). The neural basis of the Weber-Fechner law: a logarithmic mental number line. Trends in Cognitive Neurosciences, 7(4), 145-147. Cerca con Google

50. Dehaene, S., Bossini, S., & Giraux, P. (1993). The mental representation of parity and number magnitude. Journal of Experimental Psychology: General, 122, 371–396. Cerca con Google

51. Dehaene, S. & Changeux, J.P. (1993). Development of elementary numerical abilities: A neuronal model. Journal Cognitive Neuroscience, 5, 390-407. Cerca con Google

52. Dahaene, S., Cohen, L., Sigman, M., & Vinckier, F. (2005). The neural code for written words: a proposal. Trends in Cognitive Science, 9(7), 335-341. Cerca con Google

53. Dehaene, S., Dupoux, E., & Mehler, J. (1990). Is numerical comparison digital ? Analogical and symbolic effects in two-digit number comparison. Journal of Experimental Psychology: Human Perception and Performance, 16, 626-641 Cerca con Google

54. Dehaene, S, Piazza, M, Pinel, P, & Cohen, L. (2003). Three parietal circuits for number processing. Cognitive Neuropsycholy 2003, 20, 487-506 Cerca con Google

55. Den Heyer, K., & Briand, K. (1986). Priming single digit numbers: Automatic spreading activation dissipates as a function of semantic distance. American Journal of Psychology, 99, 315-340. Cerca con Google

56. DfES. (2001). Guidance to support pupils with dyslexia and dyscalculia (No. DfES 0512/2001). London: Department of Education and Skills. Cerca con Google

57. Di Luca, S., Grana, A., Semenza, C., Seron, X., & Pesenti, M. (2006). Finger-digit compatibility in Arabic numeral processing. Quarterly Journal of Experimental Psychology, 59(9), 1648-1663. Cerca con Google

58. Durgin, F. H. (1995). Texture Density Adaptation and the Perceived Numerosity and Distribution of Texture, Journal of Experimental Psychology: Human Perception and Performance, 21(1), 149-169. Cerca con Google

59. Eliasmith, C. (1996). The third contender: A critical examination of the dynamicist theory of cognition. Journal of Philosophical Psychology, 9(4), 441-463 Cerca con Google

60. Elman, J. L. (1991). Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning, 7(2/3), 195-226. Cerca con Google

61. Feigenson, L., Carey, S., & Hauser, M. (2002). Infants spontaneous representations of more and less. Psychological Science, 12(2), 150-156. Cerca con Google

62. Feldman, A. G., (1966). Functional Tuning of the Nervous System with Control of Movement of Maintenance of a Steady Posture of Movement or Maintenance of a Steady Posture-II. Controllable Parameters of the Muscles. Biofizika, 11, 498-508. Cerca con Google

63. Feldman, J. A., & Ballard, D. H. (1982). Connectionist Models and their Properties. Cognitive Science 6, 205-254. Cerca con Google

64. Fias, W., Brysbaert, M., Geypens, F., & d’Ydewalle, G. (1996). The importance of magnitude information in numerical processing: Evidence from the SNARC effect. Mathematical Cognition, 2, 95-110. Cerca con Google

65. Fias, W., & Fischer, M.H. (2005). Spatial Representation of Numbers. In J.I.D. Campbell (ed.) Handbook of Mathematical Cognition. Hove: Psychology Press. Cerca con Google

66. Fodor, J. & Pylyshyn, Z. (1988). Connectionism and cognitive architecture: A critical analysis. Cognition, 28, 3-71. Cerca con Google

67. Foltz, G. S., Poltrock, S. E. & Potts, G. R. (1984). Mental comparisons of size and magnitude. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 442–453 Cerca con Google

68. Friston, K.J., Worsley, K.J., Frackowiak, R.S.J., Mazziotta, J.C., & Evans, A.C. (1994). Assessing the significance of focal activations using their spatial extent. Human Brain Mapping, 1, 214-220. Cerca con Google

69. Funahashi S., Bruce C. J., & Goldman-Rakic P. S. (1993). Dorsolateral prefrontal lesions, and oculomotor delayed-response performance: evidence for mnemonic “scotomas.” Journal of Neuroscience, 13, 1479-1497. Cerca con Google

70. Gallistel, C. R., & Gelman, R. (1992). Preverbal and verbal counting and computation. Cognition, 44, 43-74. Cerca con Google

71. Gallistel, C. R., & Gelman, R. (2000). Non-verbal numerical cognition: From reals to integers. Trends in Cognitive Sciences, 4, 59-65. Cerca con Google

72. Gallistel, C. R., & Gelman, R. (2005). Mathematical Cognition. In K. Holyoak & R. Morrison (Eds.), The Cambridge handbook of thinking and reasoning, 559-588, Cambridge University Press. Cerca con Google

73. Ganor-Stern, D., Tzelgov, J., & Ellenbogen, R. (2007). Automaticity of two-digit numbers. Journal of Experimental Psychology: Human Perception and Performance, 33(2), 483-496. Cerca con Google

74. Gazzellini, S. & Laudanna, A. (2005). Are Two-Digit Numerals Decomposed or Holstically Represented? Evidence from Number Comparison. Abstract for a poster at the 27th Annual Conference of the Cognitive Science Society, available at http://www.psych.unito.it/csc/cogsci05/post_sessions.html. Vai! Cerca con Google

75. Geisler, W. S. (1989). Sequential ideal-observer analysis of visual discrimination. Psychological Review, 96, 267-314. Cerca con Google

76. Gelman, R. & Butterworth, B. (2005). Number and language: how are they related? Trends in Cognitive Neurosciences, 9(1), 6-10. Cerca con Google

77. Gevers, W., Reynvoet, B., & Fias, W. (2003). The mental representation of ordinal sequences is spatially organized. Cognition, 87(3), B87-95. Cerca con Google

78. Gevers, W., Reynvoet, B., & Fias, W. (2004). The mental representation of ordinal sequences is spatially organized: evidence from days of the week. Cortex, 40(1), 171-172. Cerca con Google

79. Girelli, L., Lucangeli, D. & Butterworth, B. (2000). The development of automaticity in accessing number magnitude. Journal of Experimental Child Psychology, 76, 104–122. Cerca con Google

80. Gnadt, J. W. & Mays, L. E. (1995). Neurons in monkey parietal area LIP are tuned for eye movement parameters in three-dimensional space. Journal of Neurophysiology, 73(1), 280-297. Cerca con Google

81. Gold, J. I. & Shadlen, M. N. (2000). Representation of a perceptual decision in developing oculomotor commands. Nature, 404, 390 – 394. Cerca con Google

82. Gold, J. I. & Shadlen, M. N. (2001). Neural computations that underlie decisions about sensory stimuli. Trends in Cognitive Science, 5, 10-16. Cerca con Google

83. Gold, J. I. & Shadlen, M. N. (2003). The influence of behavioral context on the representation of a perceptual decision in developing oculomotor commands. Journal of Neuroscience, 23, 632-651. Cerca con Google

84. Goldberg D. E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley Publishing Company. Cerca con Google

85. Gonzalez, R. C. & and Richard, E. W. (1992). Digital image processing. Addison Wessley Publishing Company. Cerca con Google

86. Grainger, J. & Holcomb, P. J. (in press). Neural constraints on a functional architecture for word recognition. In P. Cornelissen, P. Hansen, M. Kringelbach & K. Pugh (Eds.), The neural basis of reading. Oxford University Press: Oxford Cerca con Google

87. Groen, G. J., & Parkman, J. M. (1972). A chronometric analysis of simple addition, Psychological Review, 79, 329-343. Cerca con Google

88. Gross-Tsur, V., Manor, O., & Shalev, R. S. (1996). Development dyscalculia: Prevalence and demographic features. Developmental Medicine and Child Neurology, 38, 25-33. Cerca con Google

89. Grossberg, S. & Repin, D. (2003). A neural model of how the brain represents and compares multidigit numbers: spatial and categorical processes. Neural Networks, 16, 1107-1140. Cerca con Google

90. Hammond, E. J. & Green, D. W. (1982). Detecting targets in letter and non-letter arrays. Canadian Journal of Psychology, 36, 67-82 Cerca con Google

91. Harvey, I. (1996). Untimed and misrepresented: connectionism and the computer metaphor. Newsletter of the Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB Quarterly), 96, 20-27. Cerca con Google

92. Harvey, I. (2001). Artificial Evolution: A Continuing SAGA. In G. Takashi (Ed.) Evolutionary Robotics: From Intelligent Robots to Artificial Life, Proceedings of the 8th International Symposium on Evolutionary Robotics. Springer-Verlag Lecture Notes in Computer Science LNCS 2217. Cerca con Google

93. Harvey, I., Husbands, P., Cliff, D., Thompson, A., & Jakobi, N. (1996). Evolutionary Robotics at Sussex. In Robotics and Manufacturing: Recent trends in research and applications (Proc. World Automation Conf. WAC'96), p 293-298. New York: ASME Press. Cerca con Google

94. Henik, A., & Tzelgov, J. (1982). Is three greater than five: The relation between physical and semantic size in comparison tasks. Memory and Cognition, 10, 389–395 Cerca con Google

95. Henschen, S. E. (1920) Klinische und Anatomische Beitrage zu Pathologie des Gehirns, Nordiska Bokhandeln. Cerca con Google

96. Hodgkin, A. & Huxley, A. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology, 117, 500-544. Cerca con Google

97. Honavar, V. & Uhr, L. (1989). Brain-structured connectionist networks that perceive and learn. Connection Science, 1(2), 139-159. Cerca con Google

98. Joanisse, M. & Seidenberg, M. S. (1999). Impairments in verb morphology following brain injury: A connectionist model. Proceedings of the National Academy of Sciences, 96, 7592-7597. Cerca con Google

99. Jordan, K. & Brannon E.M. (2006a). A common representational system governed by Weber's Law: Nonverbal numerical similarity judgments in 6-year-olds and rhesus macaques. Journal of Experimental Child Psychology, 95, 215-229 . Cerca con Google

100. Jordan, K. & Brannon, E.M. (2006b) The influence of Weber's law on the numerical representations of rhesus macaques (Macaca mulatta). Animal Cognition, 9, 159-172. Cerca con Google

101. Johnson-Laird, P. (1988). The Computer and the Mind. Harvard University Press. Cerca con Google

102. Keinan, A., Sandbank, B., Hilgetag, C. C., Meilijson, I., & Ruppin, E. (2004a). Fair attribution of functional contribution in artificial and biological networks. Neural Computation, 16(9), 1887-1915. Cerca con Google

103. Keinan, A., Hilgetag, C. C., Meilijson, I., & Ruppin, E. (2004b). Causal localization of neural function: The Shapley value method, Neurcomputing, 58-60C, 215-222. Cerca con Google

104. Kelso, J.A.S. (1995). Dynamic Patterns, MIT Press. Cerca con Google

105. Kim, J-N & Shadlen, M. N. (1999). Neural correlates of a decision in the dorsolateral prefrontal cortex of the macaque. Nature Neuroscience, 2(2), 176-185. Cerca con Google

106. Koechlin, E., Naccache, L., Block, E., & Dehaene, S. (1999). Primed numbers: Exploring the modularity of numerical representaions with masked and unmasked priming. Journal of Experimental Psychology: Human Perception and Performance, 25,1882-1905. Cerca con Google

107. Kohonen, T. (1995). Self-Organizing Maps, Berlin: Springer-Verlag. Cerca con Google

108. Korvorst, M., & Damian, M. F. (2007). The differential influence of decades and units on multidigit number comparison. Quarterly Journal of Experimental Psychology, available at http://www.informaworld.com/smpp/content~content=a782895981~db=all~order=author. Vai! Cerca con Google

109. Lefton, L. A., Fisher, D. F. & Kuhn, D. M. (1978). Left-to-right processing of alphabetic material is independent of retinal location. Bulletin of the Psychonomic Society, 12, 171-174 Cerca con Google

110. LeFevre, J., Sadesky, G. S., & Bisanz, J. (1996). Selection of procedures in mental addition: Reassessing the problem size effect in adults. Journal of Experimental Psychology: Learning, Memory, & Cognition, 22, 216-230. Cerca con Google

111. Lengyel M., Kwag J., Paulsen O., & Dayan P. (2006). Matching storage and recall: hippocampal spike timing-dependent plasticity and phase response curves. Nature Neuroscience, 8, 1677-1683. Cerca con Google

112. Lewis, C., Hitch, G., & Walker, P. (1994). The prevalence of specific arithmetic difficulties and specific reading difficulties in 9-and 10-year-old boys and girls. Journal of Child Psychology and Psychiatry, 35, 283 –292. Cerca con Google

113. Lewin, R. (1992). Complexity: Life at the edge of chaos. Macmillan. Cerca con Google

114. Lorch, R. F. Jr. & Myers, J. L. (1990). Regression analyses of repeated measures data in cognitive research. Journal of Experimental Psychology: Learning, Memory, & Cognition, 16(1), 149-157. Cerca con Google

115. Lories, G., Aubrun, A., & Seron, X. (1994). Lesioning McCloskey & Lindemann's 1992 Mathnet: the effect of damage location and amount. Journal of Biological Systems, 2(3), 335-356. Cerca con Google

116. Mandler, G. & Shebo, B. J. (1982). Subitizing: An analysis of its component processes. Journal of Experimental Psychology: General, 11, 1–22 Cerca con Google

117. Marr, D. (1982) Vision. A computational investigation into the human representation and processing of visual information. New York: W.H. Freeman. Cerca con Google

118. Mason, M. (1982). Recognition time for letters and nonletters: Effects of serial position, array size, and processing order. Journal of Experimental Psychology, 8, 724-738 Cerca con Google

119. McCloskey, M. & Lindemann, A. M. (1992). MATHNET: Preliminary results from a distributed model of arithmetic fact retrieval. In J. I. D. Campbell (Ed.), The Nature and Origins of Mathematical Skills. Elsevier Science Publishers B.V. Cerca con Google

120. McConkie, G. W. & Rayner, K. (1975). The span of the effective stimulus during a fixation in reading, Perception & Psychophysics, 17, 578-586. Cerca con Google

121. McClelland, J. L., & Rumelhart, D. E. (1981). An interactive activation model of context effects in letter perception, Part 1: An account of basic findings. Psychological Review, 88, 375-405. Cerca con Google

122. McLeod, P., Plunkett, K., & Rolls, E. T. (1998), Introduction to Connectionist Modelling of Cognitive Processes, Oxford University Press. Cerca con Google

123. Meck, W. H., & Church, R. M. (1983). A mode control model of counting and timing processes. Journal of Experimental Psychology: Animal Behaviour Processes, 9, 320-324. Cerca con Google

124. Meyer, D. E., & Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology, 90, 227-234. Cerca con Google

125. Miller, A., & Baker, G. (1968). The effects of shape, size, heterogeneity and instructional set on the judgment of visual number. American Journal of Psychology, 81, 83-91. Cerca con Google

126. Miller, E. K. & Desimone, R. (1991). A neural mechanism for working and recognition memory in the inferior temporal cortex. Science, 254, 1377-1379. Cerca con Google

127. Mix, K. S., Huttenlocher, J., & Levine, S. C. (2002) Quantitative Development in Infancy and Early Childhood, Oxford University Press. Cerca con Google

128. Moyer, R. S. & Landauer, T. K. (1967). Time required for judgements of numerical inequality. Nature, 215, 1519-1520 Cerca con Google

129. Naccache, L., & Dahaene, S. (2001). The priming method : imaging unconscious repetition priming reveals an abstract representation of number in the parietal lobes. Cerebral Cortex, 11, 966-974. Cerca con Google

130. Najemnik, J. & Geisler, W. S. (2005). Optimal eye movement strategies in visual search. Nature, 434, 387-391. Cerca con Google

131. Neely, J. H. (1991). Semantic priming effects in visual word recognition: A selective review of current findings and theories. In D. Besner, & G. W. Humphreys (Eds.), Basic processes in reading , 264-336. Hillsdale, NJ: Lawrence Erlbaum Associates. Cerca con Google

132. Nieder, A., Freedman, D. J., & Miller, E. K. (2002). Representation of the quantity of visual items in the primate prefrontal cortex. Science, 297, 1708. Cerca con Google

133. Nieder, A. & Miller, E. K. (2003). Coding of cognitive magnitude: Compressed scaling of numerical information in the primate pre-frontal cortex. Neuron, 37, 149-157. Cerca con Google

134. Nieder, A. & Miller, E. K. (2004). A parieto-frontal network for visual numerical information in the monkey. Proceedings of the National Academy of Science (USA), 101, 7457-7462. Cerca con Google

135. Norris, D. & McQueen, J.M. (in press). Shortlist B: A Bayesian model of continuous speech recognition. Psychological Review. Cerca con Google

136. Nowack, A. (2004). Dynamical Minimalism: Why Less is More in Psychology. Personality and Social Psychology Review, 8(2), 183-192. Cerca con Google

137. Nürk, H. C., Bauer, F., Krummenacher, J., Heller, D., & Willmes, K. (2005). The power of the mental number line. How the Magnitude of Unattended Numbers affects Performance in an Eriksen Task. Psychology Science: Special Issue Brain and Number, 42, 34-50. Cerca con Google

138. Nürk, H.C., Weger, U., & Willmes, K. (2001). Decade breaks in the mental number line? Putting the tens and units back in different bins. Cognition, 82, B25-B33. Cerca con Google

139. Oja, E. (1989). Neural networks, principal components, and subspaces. International Journal of Neural Systems, 1(1), 61-68. Cerca con Google

140. O'Regan, J. K. (1990). Eye movements and reading. In E. Kowler (Ed.), Eye movements and their role in visual and cognitive processes. (Vol. 4 of Reviews of Oculomotor Research), 395-453, Elsevier, Amsterdam. Cerca con Google

141. O’Regan, J. K., Lévy-Schoen, A., & Jacobs, A. M. (1983).The effect of visibility on eye-movement parameters in reading. Perception & Psychophysics,34 ,457-64. Cerca con Google

142. O'Reilly, R. C. (1998). Six Principles for Biologically-Based Computational Models of Cortical Cognition. Trends in Cognitive Sciences, 2, 455-462. Cerca con Google

143. Ostad, S. E. (1998). Developmental progression of subtraction studies:a comparison of mathematically normal and mathematically disabled childre. European Journal of Special Needs Education, 14 (1), 21-36. Cerca con Google

144. Palmer, J., Huk, A. C., & Shadlen, M. N. (2005). The effect of stimulus strength on the speed and accuracy of a perceptual decision. Journal of Vision, 5, 376-404. Cerca con Google

145. Peterson, S. & Simon, T. J. (2000). Computational evidence for the subitizing phenomenon as an emergent property of the human cognitive architecture. Cognitive Science, 24, 93–122 Cerca con Google

146. Pesenti, M., Thioux, M., Seron, X., & De Volder, A. (2000). Neuroanatomical substrates of Arabic number processing, numerical comparison and simple addition: A PET study. Journal of Cognitive Neuroscience, 12(3), 461-479. Cerca con Google

147. Phattanasri, P., Chiel, H.J., & Beer, R.D. (submitted). The dynamics of associative learning in evolved model circuits. Submitted to the Journal of Adaptive Behaviour, available at http://vorlon.case.edu/~beer/Papers/LearningPaper2.pdf Vai! Cerca con Google

148. Piazza, M., Izard, V., Pinel, P., Le Bihan, D., & Dehaene, S. (2004). Tuning curves for approximate numerosity in the human intraparietal sulcus.. Neuron, 44(3), 547-55. Cerca con Google

149. Piazza, M., Mechelli, A., Butterworth, B. & Price, C. J. (2002). Are Subitizing and Counting Implemented as Separate or Functionally Overlapping Processes? NeuroImage, 15, 435-446. Cerca con Google

150. Platt, M. and Glimcher, P.W. (1998) Neurons in LIP carry information correlated with movement probability and reward magnitude. Investigative Opthalmolology and Visual Science, 39, S326. Cerca con Google

151. Plaut, D. C. & Shallice, T. (1993). Deep dyslexia: A case study of connectionist neuropsychology. Cognitive Neuropsychology, 10, 377-500. Cerca con Google

152. Port, R.F. & van Gelder, T. (1995). Mind as Motion, MIT Press. Cerca con Google

153. Ramsey, W., Stich, S. P., & Garon, J. (1991). Connectionism, eliminativism, and the future of folk psychology. In W. Ramsey, S. P. Stich, & D. E. Rumelhart (Eds.), Philosophy and connectionist theory, 199-228, Hillsdale, NJ: Lawrence Erlbaum. Cerca con Google

154. Rao, C. R. (1964). The Use and Interpretation of Principal Component Analysis in Applied Research. Sankhya A 26, 329-358. Cerca con Google

155. Ratcliff, R. (1978). A theory of memory retrieval. Psychological Review, 85, 59-108. Cerca con Google

156. Ratcliff, R. (2001). Diffusion and random walk processes. International encyclopedia of the social and behavioral sciences, Oxford, England: Elsevier, 6, 3668-3673. Cerca con Google

157. Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: Theory and data for two-choice decision tasks. Neural Computation, 20, 873-922. Cerca con Google

158. Ratcliff, R., & Rouder, J.N. (1998). Modeling response times for two-choice decisions. Psychological Science, 9, 347-356. Cerca con Google

159. Ratcliff, R., Van Zandt, T., & McKoon, G. (1999). Connectionist and diffusion models of reaction time. Psychological Review, 106, 261-300. Cerca con Google

160. Rayner, K. (1998). Eye Movements in Reading and Information Processing: 20 Years of Research. Psychological Bulletin, 124, 372-422. Cerca con Google

161. Rayner K. & Fisher D.L. (1987). Eye movements and the perceptual span during visual search. In J. K. O'Regan & A. Levy-Schoen (Eds) Eye movements: From Physiology to Cognition. Amsterdam: North-Holland, 293-302. Cerca con Google

162. Reder, S. M. (1973). On-line monitoring of eye position signals in contingent and noncontingent paradigms. Behaviour Research Methods & Instrumentation, 5, 218-228. Cerca con Google

163. Reicher, G.M. (1969). Perceptual recognition as a function of meaningfulness of stimulus material. Journal of Experimental Psychology, 81, 275-280. Cerca con Google

164. Reynvoet, B., & Brysbaert, M. (1999). Single-digit and two-digit Arabic numerals address the same semantic number line. Cognition, 72, 191-201. Cerca con Google

165. Reynvoet, B., Brysbaert, M., & Fias, W. (2002). Semantic priming in number naming. The Quarterly Journal of Experimental Psychology, 55A(4), 1127-1139. Cerca con Google

166. Reynvoet, B., Caessens, B., & Brysbaert, M. (2002). Automatic stimulus–response associations may be semantically mediated. Psychonomic Bulletin & Review, 9, 107-112. Cerca con Google

167. Roitman, J., Brannon. E.M. & Platt, M.L. (2007). Monotonic Coding of Numerosity in Macaque. PLoS Biology, 5(8). Cerca con Google

168. Roitman J. & Shadlen M.N. (2002). Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. Journal of Neuroscience, 22, 9475-9489. Cerca con Google

169. Rumelhart, D. E. & McClelland, J. L. (1986). Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Volumes 1 and 2. Cambridge, MA: MIT Press. Cerca con Google

170. Schacter, D. L., Alpert, N. M., Savage, C. R., Rauch, S. L., & Albert, M. S. (1996). Conscious recollection and the human hippocampal formation: evidence from positron emission topography. Proceedings of the National Academy of Science (USA), 93, 321-325. Cerca con Google

171. Schacter, D. L. & Buckner, R. L. (1998). Priming and the brain. Neuron, 20, 185-195. Cerca con Google

172. Seidenberg, M. S. & McClelland, J. L. (1989). A distributed, developmental model of word recognition and naming. Psychological Review, 96, 523-568. Cerca con Google

173. Sejnowski, T.J., & Rosenberg, C.R. (1987). Parallel networks that learn to pronounce English text. Complex Systems, 1, 145-168. Cerca con Google

174. Seth, A.K. (1998). Evolving action selection and selective attention without actions, attention, or selection. In R. Pfeifer, B. Blumberg, J. Meyer, & S. Wilson (Eds.), From animals to animats 5: Proceedings of the Fifth International Conference on the Simulation of Adaptive Behavior, 139-147, Cambridge, MA. MIT Press. Cerca con Google

175. Seth, A.K. (2008). Causal networks in simulated neural systems. Cognitive Neurodynamics, 2, 49-64. Cerca con Google

176. Shadlen, M. N., Hanks, T. D., Churchland, A. K., Kiani, R., & Yang, T. (2006). The speed and accuracy of a simple perceptual decision: a mathematical primer. In K. Doya, S. Ishii, R. Rao, and A. Pouget (Eds.) Bayesian Brain: Probabilistic Approaches to Neural Coding, MIT Press: Cambridge. Cerca con Google

177. Shalev, R. S., Auerbach, J., Manor, O. & Gross-Tsur, V. (2000). Developmental dyscalculia: prevalence and prognosis. European child & adolescent psychiatry, 9(2), 58-64. Cerca con Google

178. Shallice, T. (1988). From neuropsychology to mental structure. Cambridge: Cambridge University Press. Cerca con Google

179. Shapley, S. L. (1953). A Value for n-person Games. In H.W. Kuhn & A.W. Tucker (Eds.), Contributions to the Theory of Games, volume II; Annals of Mathematical Studies, 28, 307-317, Princeton University Press. Cerca con Google

180. Siegler, R. S. & Opfer, J. E. (2003). The Development of Numerical Estimation: Evidence for Multiple Representations of Numerical Quantity. Psychological Science, 14(3), 237-243. Cerca con Google

181. Simon, O., Mangin, J. F., Cohen, L., Le Bihan D., & Dehaene, S. (2002). Topographical layout of hand, eye, calculation, and language-related areas in the human parietal lobe. Neuron, 33, 475-487. Cerca con Google

182. Simon, T. J., Peterson, S., Patel, G. & Sathian, K. (1998). Do the magnocellular and parvocellular visual pathways contribute differentially to subitizing and counting? Perceptual Psychophysics, 60(3), 451–464 Cerca con Google

183. Simon, T. & Vaishnavi, S. (1996). Subitizing and counting depend on different attentional mechanisms: Evidence from visual enumeration in afterimages. Perceptual Psychophysics, 58(6), 915–926. Cerca con Google

184. Smolensky, P. (1987). On Variable Binding and the Representation of Symbolic Structures in Connectionist Systems. Technical report CU-CS-355-87, Department of Computer Science, University of Colorado at Boulder. Cerca con Google

185. Spieler, D.H., & Balota, D.A. (1997). Bringing computational models of word naming down to the item level. Psychological Science, 8, 411-416. Cerca con Google

186. Squire, L. R., Ojemann, J. G., Miezin, F. M., Petersen, S. E., Videen, T. O., & Raichle, M. E. (1992). Activation of the hippocampus in normal humans: a functional anatomical study of memory. Proceedings of the National Academy of Science (USA), 89, 1837-1841. Cerca con Google

187. Steen, L. (1990). Numeracy. Daedalus Special Issue on "Literacy in America", 119(2), 211-231. Cerca con Google

188. Stevens, M. & Grainger, J. (2003). Letter visibility and the viewing position effect in visual word recognition. Perception & Psychophysics, 65, 133-151 Cerca con Google

189. Stich, S., & Ravenscroft, I. (1994). What is Folk Psychology? Cognition, 50, 447-68. Cerca con Google

190. Tomko, G., & Crapper, T. (1974). Neuronal variability: non-stationary responses to identical visual stimuli. Brain Research, 79, 405-418. Cerca con Google

191. Trick, L. M. & Pylyshyn, Z. W. (1994). Why are small and large numbers enumerated differently? A limited-capacity preattentive stage in vision. Psychological Review, 101(1), 80-102. Cerca con Google

192. Tydgat, H. & Grainger, J. (in press). Serial Position Effects in the Identification of Letters, Digits, and Symbols. Journal of Experimental Psychology: Human Perception and Performance. Cerca con Google

193. Tzelgov, J., Meyer, J. & Henik, A. (1992). Automatic and intentional processing of numerical information. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18, 166-179. Cerca con Google

194. Uller, C., Jaeger, R., Guidry, G., & Martin, C. (2003). Salamanders (Plethodon cinereus) go for more: rudiments of number in an amphibian. Animal Cognition, 6, 105-112. Cerca con Google

195. Underwood, N. R. & McConkie, G. (1985). Perceptual span for letter distinctions during reading. Reading Research Quarterly, 20, 153-162. Cerca con Google

196. Usher, M. & McClelland, J. L. (2001). On the Time Course of Perceptual choice: The leaky competing accumulator model. Psychological Review, 108, 550-592. Cerca con Google

197. Van Gelder, T. (1995). What might cognition be, if not computation? The Journal of Philosophy, 91(7), 345-381. Cerca con Google

198. Van Gelder, T. (1998). The dynamical hypothesis in cognitive science. Behavioural Brain Science, 21, 615-665. Cerca con Google

199. Van Gelder, T. (1999). Dynamic approaches to cognition. In Wilson, R., Keil, F. (Eds.), The MIT Encyclopedia of Cognitive Sciences, 244-246, Cambridge MA: MIT Press. Cerca con Google

200. Van Selst, M. & Jolicoeur, P. (1994). A solution to the effect of sample size on outlier elimination. Quarterly Journal of Experimental Psychology, 47A, 631-650. Cerca con Google

201. Verguts, T. & De Moor, W. (2005). Two Digit Comparison: Decomposed, Holistic or Hybrid? Journal of Experimental Psychology, 52(3), 195-200 Cerca con Google

202. Verguts, T. & Fias, W. (2004). The representation of number in humans and animals: a neural model. Journal of Cognitive Neuroscience, 16(9), 1493-1504 Cerca con Google

203. Verguts, T., Fias, W., & Stevens, M. (2005). A model of exact small-number representation. Psychonomic Bulletin and Review, 12, 66-80. Cerca con Google

204. Verguts, T. & Van Opstal, F. (2005). Dissociation of the distance effect and size effect in one-digit numbers. Psychonomic Bulletin & Review, 12, 925-930. Cerca con Google

205. Viscuso, S. R., Anderson, J. A., & Spoehr, K. T. (1989). Representing simple arithmetic in neural networks. In G. Tiberghien (Ed.), Advances in Cognitive Science (Vol. 2). Chichester (UK): Ellis Horwood. Cerca con Google

206. Wagenmakers, E-J., van der Maas, H., & Grasman, R. (2007). An EZ-diffusion model for response time and accuracy. Psychonomic Bulletin and Review, 14, 3-22. Cerca con Google

207. Watson, R. A. & Pollack, J. B. (2001). Coevolutionary Dynamics in a Minimal Substrate. In L. Spector et al (Eds.), Proceedings of the 2001 Genetic and Evolutionary Computation Conference, Morgan Kaufmann. Cerca con Google

208. Wellman, H. M. & Miller, K. F. (1986). Thinking about nothing: Development of concepts of zero. Journal of Developmental Psychology, 4, 31042. Cerca con Google

209. Whalen, J. (1997). The influence of semantic magnitude representations on arithmetic: Theory, data, and simulation. In M. G. Shafto & P. Langley (Eds.), Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society, 814-819, Mahwah, NJ: Erlbaum. Cerca con Google

210. Whalen, J., Gallistel, C. R., & Gelman, R. (1999). Nonverbal Counting in Humans: The Psychophysics of Number Representation. Psychological Science, 10(2), 130-137. Cerca con Google

211. Wheeler, D. D. (1970). Processes in word recognition. Cognitive Psychology, 1, 59–85 Cerca con Google

212. Wilson, F. A., O'Scalaidhe, S. P., & Goldman-Rakic, P. S. (1993). Dissociation of object and spatial processing domains in primate prefrontal cortex. Science, 260, 1955-1958. Cerca con Google

213. Wong, K.F. & Wang, X.J. (2006). A Recurrent Network Mechanism of Time Integration in Perceptual Decisions. Journal of Neuroscience, 26, 1314-1328. Cerca con Google

214. Zbrodoff, N. J., & Logan, G. D. (2005). What everyone finds. The problem size effect. In J. Campbell (Ed.), Handbookof Mathematical Cognition, 331-345, New York and Hove: Psychology Press. Cerca con Google

215. Zebian, S. (2005). Linkages between number concepts, spatial thinking, and directionality of writing. The SNARC effect and the reverse SNARC effect in English and Arabic monoliterates, biliterates, and illiterate Arabic speakers. Journal of Cognition & Culture, 5, 165-190. Cerca con Google

216. Zorzi, M., & Butterworth, B. (1999). A computational model of number comparison. In: M. Hahn & S. C. Stoness (Eds.), Proceedings of the Twenty First Annual Conference of the Cognitive Science Society (p. 778-783). Mahwah (NJ): Erlbaum. Cerca con Google

217. Zorzi, M. and Priftis, K., & Umilta, C. (2002) Brain damage: neglect disrupts the mental number line. Nature, 417(6885), 138-139. Cerca con Google

218. Zorzi, M., Stoianov, I., Becker, S., Umiltà, C., & Butterworth, B. (under revision). The numerosity code for the representation of numerical magnitude. Psychological Review. Cerca con Google

219. Zorzi, M., Stoianov, I., & Umiltà, C. (2005) Computational modeling of numerical cognition. In J. Campbell (Ed.), Handbook of mathematical cognition, chapter 5, 67-83, London: Psychology Press. Cerca con Google

Download statistics

Solo per lo Staff dell Archivio: Modifica questo record

EPrints Logo
Padua@Research is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.