Information-Processing Model of Concept Formation – Is First Language Acquisition Universal?

Slavova, Velina

doi:10.2478/cait-2018-0035

Abstract

The analysis of child’s speech corpora shows that the process of acquisition of English and French displays identical development of children’s expressions when the speech-utterances are presented as Fibonacci-weighted classes of concepts. A model of concept complexity and information processing based on principles of optimality is proposed to explain this statistical result.

References

1. Aurues, T. The Fibonacci Sequence in Nature Implies Thermodynamic Maximum Entropy (New Developments of Generalized Entropies by Functional Analysis). 2013, 13.12.2017. https://repository.kulib.kyoto-u.ac.jp/dspace/bitstream/2433/195148/1/1852-18.pdf.
Search in Google Scholar Back to article
2. Baluška, F. Recent Surprising Similarities between Plant Cells and Neurons. – Plant Signalling & Behaviour, Vol. 5, 2010, No 2, pp. 87-89.10.4161/psb.5.2.11237288410520150757
Search in Google Scholar Back to article
3. Barsalou, L. W. Situated Simulation in the Human Conceptual System. – Language and Cognitive Processes, Vol. 18, 2003, No 516, pp. 513-562.10.1080/01690960344000026
Search in Google Scholar Back to article
4. Barsalou, L. W. Cognitively Plausible Theories of Concept Composition. – In: Y. Winter, J. A. Hampton, Eds. Compositionality and Concepts in Linguistics and Psychology. London, Springer Publishing, 2017, pp. 9-30.10.1007/978-3-319-45977-6_2
Search in Google Scholar Back to article
5. Barsalou, L. W. What Does Semantic Tiling of the Cortex Tell Us About Semantics? – In: Neuropsychologia, Vol. 105, 2017, pp. 18-38.10.1016/j.neuropsychologia.2017.04.01128396096
Search in Google Scholar Back to article
6. Boman, B. M., et al. Why Do Fibonacci Numbers Appear in Patterns of Growth in Nature? – The Fibonacci Quarterly, Vol. 55, 2017, No 5, pp. 30-41.
Search in Google Scholar Back to article
7. Bowling, D. L., M. Hoeschele, K. Z. Gill, W. T. Fitch. The Nature and Nurture of Musical Consonance. – Music Perception: An Interdisciplinary Journal, Vol. 35, 2017, No 1, pp. 118-121.10.1525/mp.2017.35.1.118
Search in Google Scholar Back to article
8. Chomsky, N. The Minimalist Program. Cambridge, MA, MIT Press, 1995.
Search in Google Scholar Back to article
9. Conn, A., et al. A Statistical Description of Plant Shoot Architecture. – Current Biology, Vol. 27, 2017, No 14, pp. 2078-2088.10.1016/j.cub.2017.06.009613089328690115
Search in Google Scholar Back to article
10. Davis, G. B., M. Olson. Management Information Systems: Conceptual Foundations, Methods and Development. New York, McGraw-Hill, 1985.
Search in Google Scholar Back to article
11. Dehghani, M., et al. Decoding the Neural Representation of Story Meanings across Languages. 2017. Preprint DOI 10.17605/OSF.IO/QRPP3.10.31234/osf.io/qrpp3
Search in Google Scholar Back to article
12. Doron, M. et al. Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons. – Cell Reports, Vol. 21, 2017, No 6, pp. 1550-1561.10.1016/j.celrep.2017.10.03529117560
Search in Google Scholar Back to article
13. Elliott, M. A., J. Kelly, J. Friedel, J. Brodsky, P. Mulcahy. The Golden Section as Optical Limitation. – PloS One, Vol. 10, 2015, No 7, e0131045.10.1371/journal.pone.0131045449592326154761
Search in Google Scholar Back to article
14. Eriksson, J. E., et al. Neurocognitive Architecture of Working Memory. – Neuron, Vol. 88, 2015, No 1, pp. 33-46.10.1016/j.neuron.2015.09.020460554526447571
Search in Google Scholar Back to article
15. Dreyer, F. R., F. Pulvermüller. Abstract Semantics in the Motor System? – An Event-Related fMRI Study on Passive Reading of Semantic Word Categories Carrying Abstract Emotional and Mental Meaning. – Cortex, 2017. https://doi.org/10.1016/j.cortex.2017.10.02110.1016/j.cortex.2017.10.02129455946
Open DOI Search in Google Scholar Back to article
16. Gardiner, J., J. Marc. Arabidopsis Thaliana, a Plant Model Organism for the Neuronal Microtubule Cytoskeleton? – Journal of Experimental Botany, Vol. 62, 2010, No 1, pp. 89-97.10.1093/jxb/erq27820813785
Search in Google Scholar Back to article
17. Goldin-Meadow, S., C. Yang. Statistical Evidence That a Child Can Create a Combinatorial Linguistic System without External Linguistic Input: Implications for language Evolution. – Neuroscience & Biobehavioral Reviews. Corrected Proof 12.2017 (in Press). http://www.sciencedirect.com/science/article/pii/S014976341630110510.1016/j.neubiorev.2016.12.016549137228041786
Search in Google Scholar Back to article
18. Horibe, Y. An Entropy View of Fibonacci Trees. – The Fibonacci Quarterly, Vol. 20, 1982, No 2, pp. 168-178.
Search in Google Scholar Back to article
19. Horibe, Y. Notes on Fibonacci Trees and Their Optimality. – The Fibonacci Quarterly, Vol. 21, 1983, No 2, pp. 118-128.
Search in Google Scholar Back to article
20. Huth, A. G., S. Nishimoto, A. T. Vu, J. L. Gallant. A Continuous Semantic Space Describes the Representation of Thousands of Object and Action Categories Across the Human Brain. – Neuron, Vol. 76, 2012, No 6, pp. 1210-1224.10.1016/j.neuron.2012.10.014355648823259955
Search in Google Scholar Back to article
21. Huth, A. G., W. A. de Heer, T. vL. Griffiths, F. E. Theunissen, J. L. Gallant. Natural Speech Reveals the Semantic Maps that Tile Human Cerebral Cortex. – Nature, Vol. 532, 2016, No 7600, pp. 453-458.10.1038/nature17637485230927121839
Search in Google Scholar Back to article
22. Kim, K., M. K. Johnson. Activity in Ventromedial Prefrontal Cortex during Self-Related Processing: Positive Subjective Value or Personal Significance? – Social Cognitive and Affective Neuroscience, Vol. 10, 2014, No 4, pp. 494-500.10.1093/scan/nsu078438123324837477
Search in Google Scholar Back to article
23. Liuzzi, A. G., et al. Cross-Modal Representation of Spoken and Written Word Meaning in Left Pars Triangularis. – NeuroImage, Vol. 150, 2017, pp. 292-307.10.1016/j.neuroimage.2017.02.03228213115
Search in Google Scholar Back to article
24. Llinás, R. R. Intrinsic Electrical Properties of Mammalian Neurons and CNS Function: A Historical Perspective. – Frontiers in Cellular Neuroscience, Vol. 8, 2014.10.3389/fncel.2014.00320421945825408634
Search in Google Scholar Back to article
25. Llinás, R. R., et al. Reconstruction of Human Brain Spontaneous Activity Based on Frequency-Pattern Analysis of Magnetoencephalography Data. – Frontiers in Neuroscience, Vol. 9, 2015, No 373, pp. 1-8.10.3389/fnins.2015.00373460836326528119
Search in Google Scholar Back to article
26. Mao, X., Y. Wang, Y. Wu, C. Guo. Self-Referential Information Alleviates Retrieval Inhibition of Directed Forgetting Effects – An ERP Evidence of Source Memory. – Frontiers in Behavioral Neuroscience, Vol. 11, 2017, No 187.10.3389/fnbeh.2017.00187564130829066962
Search in Google Scholar Back to article
27. Just, M. A, J. Wang, V. Cherkassky. Neural Representations of the Concepts in Simple Sentences: Concept Activation Prediction and Context Effects. – NeuroImage, Vol. 157, 2017, No 15, pp. 511-520.10.1016/j.neuroimage.2017.06.033560084428629977
Search in Google Scholar Back to article
28. McDermott, J. H., A. F. Schultz, E. A. Undurraga, R. A. Godoy. Indifference to Dissonance in Native Amazonians Reveals Cultural Variation in Music Perception. – Nature, Vol. 535, 2016, No 7613, pp. 547-550.10.1038/nature1863527409816
Search in Google Scholar Back to article
29. Moran, P., J. Tommerdahl. A Case Study of Linguistic Isolation and Questions about Subsequent Language Support and Educational Provision in the United Kingdom. – In: The Linguistic Association of Canada and the United States, LACUS Forum 36: Mechanisms of Linguistic Behavior, 2011, pp. 229-240.
Search in Google Scholar Back to article
30. Morin, A., J. Michaud. Self-Awareness and the Left Inferior Frontal Gyrus: Inner Speech Use during Self-Related Processing. – Brain Research Bulletin, Vol. 74, 2007, No 6, pp. 387-396.10.1016/j.brainresbull.2007.06.01317920447
Search in Google Scholar Back to article
31. Nakagawa, Y. The Golden Ratios Which Imply Maximum Entropy in Nuclear Physics. Japan Fibonacci Association, 2017 (Accessed 15.12.2017). http://www.zg.em-net.ne.jp/~aurues/triage/room1/MagicNumbers20170926.pdf
Search in Google Scholar Back to article
32. Northoff, G. From Emotions to Consciousness–A Neuro-Phenomenal and Neuro-Relational Approach. – Frontiers in Psychology, Vol. 3, 2012.10.3389/fpsyg.2012.00303343161222969736
Search in Google Scholar Back to article
33. Northoff, G., F. Bermpohl. Cortical Midline Structures and the Self. – Trends in Cognitive Sciences, Vol. 8, 2004, No 3, pp. 102-107.10.1016/j.tics.2004.01.00415301749
Search in Google Scholar Back to article
34. Pendl, S. L., et al. Emergence of a Hierarchical Brain during Infancy Reflected by Stepwise Functional Connectivity. – Human Brain Mapping, Vol. 38, 2017, No 5, pp. 2666-2682.10.1002/hbm.23552606464928263011
Search in Google Scholar Back to article
35. Piattelli-Palmarini, M., G. Vitiello. Quantum Field Theory and the Linguistic Minimalist Program: A Remarkable Isomorphism. – Journal of Physics: Conference Series, Vol. 880, 2017, No 1, pp. 12-16. IOP Publishing.10.1088/1742-6596/880/1/012016
Search in Google Scholar Back to article
36. Pinker, S. The Bootstrapping Problem in Language Acquisition. – In: B. MacWhinney, Ed. Mechanisms of language Acquisition, Lawrence Erlbaum Associates. 1987, pp. 399-441.
Search in Google Scholar Back to article
37. Ploux, S., et al. Structural Stability of Lexical Semantic Spaces: Nouns in Chinese and French. – arXiv preprint arXiv:1710.04173, 2017.
Search in Google Scholar Back to article
38. Seth, A. K. Interoceptive Inference, Emotion, and the Embodied Self. – Trends in Cognitive Sciences, Vol. 17, 2013, No 11, pp. 565-573.10.1016/j.tics.2013.09.00724126130
Search in Google Scholar Back to article
39. Shabalkin, I. P., E. Yu Grigor’eva, M. V. Gudkova, P. I. Shabalkin. Fibonacci Sequence and Supramolecular Structure of DNA. – Bulletin of Experimental Biology and Medicine, Vol. 161, 2016, No 1, pp. 193-196.10.1007/s10517-016-3374-627265133
Search in Google Scholar Back to article
40. Slavova, V. Data Collection for Studying Language Acquisition. – In: Proc. of 12th International Conference on Computer Science and Education in C. Sc., 2016, pp. 105-113.
Search in Google Scholar Back to article
41. Slavova, V. On Native Semantic Roles – Comparative Study Based on Data from Child Language-Acquisition of English and French. – International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE), Vol. 5, 2017, No 2, pp. 1-18.10.5937/ijcrsee1702001S
Search in Google Scholar Back to article
42. Slavova, V., K. Atanasov, A Generalized Net for Modeling Working Memory and Language Processing. – In: Proc. of the 7th International Conference Cognitive Modeling in linguistics, V. Text Processing and Cognitive Technologies, No 9, 2004, pp. 90-101.
Search in Google Scholar Back to article
43. Slavova, V., A. Soschen. A Fibonacci-Tree Model of Cognitive Processes Underlying Language Faculty. – In: Proc. of 3rd International Conference in Computer Science, NBU, University of Fulda, Boston University, 2007, pp. 196-205.
Search in Google Scholar Back to article
44. Slavova, V., A. Soschen. Experimental Support of Syntactic Computation Based on Semantic Merge of Concepts. – International Journal Information Theories & Applications, International Journal Information Technologies & Knowledge, Vol. 3, 2009, pp. 5-23.
Search in Google Scholar Back to article
45. Slavova, V., A. Soschen. On Mental Representations: Language Structure and Meaning Revised. – International Journal of Information Theories & Applications, Vol. 2, 2015, No 4, pp. 316-325.
Search in Google Scholar Back to article
46. Slavova, V., A. Soschen. Syntactic Operations – Modelling Language Faculty, International Journal of Information Theories & Applications, Vol. 2, 2015, No 4, pp. 326-337.
Search in Google Scholar Back to article
47. Smith, S. L., I. Smith, T. Branco, M. Häusser. Dendritic Spikes Enhance Stimulus Selectivity in Cortical Neurons in Vivo. – Nature, Vol. 503, 2013, No 7474, pp. 115-120.10.1038/nature12600631960624162850
Search in Google Scholar Back to article
48. Tardif, T. Nouns Are Not Always Learned Before Verbs: Evidence from Mandarin Speakers Early Vocabularies. – Developmental Psychology, Vol. 32, 1996, No 3, p. 492.10.1037/0012-1649.32.3.492
Search in Google Scholar Back to article
49. van Gend, R. The Fibonacci Sequence and the Golden Ratio in Music. – Notes on Number Theory and Discrete Mathematics, Vol. 20, 2014, No 1, pp. 72-77.
Search in Google Scholar Back to article
50. Velmans, M. When Perception Becomes Conscious. – British Journal of Psychology, Vol. 90, 1999, No 4, pp. 543-566.10.1348/000712699161620
Search in Google Scholar Back to article
51. Virtala, P., M. Huotilainen, E Partanen, V. Fellman, M. Tervaniemi. Newborn Infants’ Auditory System is Sensitive to Western Music Chord Categories. – Frontiers in Psychology, Vol. 4, 2013.10.3389/fpsyg.2013.00492373598023966962
Search in Google Scholar Back to article
52. Wang, J., V. Cerkassky, M. A. Just. Predicting the Brain Activation Pattern Associated with the Propositional Content of a Sentence: Modeling Neural Representations of Events and States. – Human Brain Mapping, Vol. 38, 2017, No 10, pp. 4865-4881.10.1002/hbm.23692686714428653794
Search in Google Scholar Back to article
53. Wille, J. J. Occurrence of Fibonacci Numbers in Development and Structure of Animal Forms: Phylogenetic Observations and Epigenetic Significance. – Natural Science, Vol. 4, 2012, No 4, p. 216.10.4236/ns.2012.44033
Search in Google Scholar Back to article
54. Woldenberg, M. J., M. P. O’Neill, L. J. Quackenbush, R. J. Pentney. Models for Growth, Decline and Regrowth of the Dendrites of Rat Purkinje Cells Induced from Magnitude and Link-Length Analysis. – Journal of Theoretical Biology, Vol. 162, 1993, No 4, pp. 403-429.10.1006/jtbi.1993.10978412232
Search in Google Scholar Back to article
55. Yang, Y., et al. Commonalities and Differences in the Neural Representations of English, Portuguese, and Mandarin Sentences: When Knowledge of the Brain-Language Mappings for Two Languages is Better than One. – Brain and Language, Vol. 175, 2017, pp. 77-85.10.1016/j.bandl.2017.09.00729045921
Search in Google Scholar Back to article
56. CHILDES – The Child Language Component of the TalkBank – System for Sharing and Studying Conversational Interactions. Online Resource. http://childes.psy.cmu.edu/
Search in Google Scholar Back to article

Information-Processing Model of Concept Formation – Is First Language Acquisition Universal?

Abstract

Paradigm

My account