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

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

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.5.2.11237288410520150757Search in Google Scholar

3. Barsalou, L. W. Situated Simulation in the Human Conceptual System. – Language and Cognitive Processes, Vol. 18, 2003, No 516, pp. 513-562.10.1080/01690960344000026Search in Google Scholar

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_2Search in Google Scholar

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.2017.04.01128396096Search in Google Scholar

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

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.2017.35.1.118Search in Google Scholar

8. Chomsky, N. The Minimalist Program. Cambridge, MA, MIT Press, 1995.Search in Google Scholar

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.2017.06.009613089328690115Search in Google Scholar

10. Davis, G. B., M. Olson. Management Information Systems: Conceptual Foundations, Methods and Development. New York, McGraw-Hill, 1985.Search in Google Scholar

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/qrpp3Search in Google Scholar

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.2017.10.03529117560Search in Google Scholar

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.0131045449592326154761Search in Google Scholar

14. Eriksson, J. E., et al. Neurocognitive Architecture of Working Memory. – Neuron, Vol. 88, 2015, No 1, pp. 33-46.10.1016/j.neuron.2015.09.020460554526447571Search in Google Scholar

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.2017.10.02129455946Open DOISearch in Google Scholar

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/erq27820813785Search in Google Scholar

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.2016.12.016549137228041786Search in Google Scholar

18. Horibe, Y. An Entropy View of Fibonacci Trees. – The Fibonacci Quarterly, Vol. 20, 1982, No 2, pp. 168-178.Search in Google Scholar

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

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.2012.10.014355648823259955Search in Google Scholar

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/nature17637485230927121839Search in Google Scholar

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/nsu078438123324837477Search in Google Scholar

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.2017.02.03228213115Search in Google Scholar

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.2014.00320421945825408634Search in Google Scholar

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.2015.00373460836326528119Search in Google Scholar

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.2017.00187564130829066962Search in Google Scholar

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.2017.06.033560084428629977Search in Google Scholar

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/nature1863527409816Search in Google Scholar

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

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.2007.06.01317920447Search in Google Scholar

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.pdfSearch in Google Scholar

32. Northoff, G. From Emotions to Consciousness–A Neuro-Phenomenal and Neuro-Relational Approach. – Frontiers in Psychology, Vol. 3, 2012.10.3389/fpsyg.2012.00303343161222969736Search in Google Scholar

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.2004.01.00415301749Search in Google Scholar

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.23552606464928263011Search in Google Scholar

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.10.1088/1742-6596/880/1/012016Search in Google Scholar

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

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

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.2013.09.00724126130Search in Google Scholar

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/s10517-016-3374-627265133Search in Google Scholar

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

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/ijcrsee1702001SSearch in Google Scholar

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

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

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

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

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

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/nature12600631960624162850Search in Google Scholar

48. Tardif, T. Nouns Are Not Always Learned Before Verbs: Evidence from Mandarin Speakers Early Vocabularies. – Developmental Psychology, Vol. 32, 1996, No 3, p. 492.10.1037/0012-1649.32.3.492Search in Google Scholar

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

50. Velmans, M. When Perception Becomes Conscious. – British Journal of Psychology, Vol. 90, 1999, No 4, pp. 543-566.10.1348/000712699161620Search in Google Scholar

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.2013.00492373598023966962Search in Google Scholar

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.23692686714428653794Search in Google Scholar

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.2012.44033Search in Google Scholar

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.1993.10978412232Search in Google Scholar

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.2017.09.00729045921Search in Google Scholar

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