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Verbal cognition: vector
space analysis
Chuluundorj. B
University of the Humanities, Mongolia
THE 11TH INTERNATIONAL
CON...
Quantum brain – Quantum mind
Brain energy transmission – wave/particle duality
Human mental space – quantum semantic space...
Mental lexicon – semantic organization of vocabulary –
human semantic memory
Research question:
Universal principles of me...
4
5
qEEG and ERP
(quantitative electro-encephalo-graphy and event related potentials)
Assess: amount, time, frequency, localiz...
7
Brain electric waves involved in verbal thinking:
P300 – word and object recognition, working memory,
semantic congruity...
8Some examples from our study:
Raw qEEG data
9
Word recognition
“Алим” (correct word)
“Лийр” (close meaning)
“Aяга” (distant meaning)
10
Correct word Close meaning Distant meaning
Some results from our study:
P300 wave in brain mapping
Broca’s
expressive
a...
11
Correct word Close meaning Distant meaning
Conclusion:
P300 wave in brain mapping
Word processing & expression - active...
12
Correct word Close meaning Distant meaning
Some results from our study:
N400 wave in brain mapping
Broca’s
expressive
a...
13
Correct word Close meaning Distant meaning
Some results from our study:
N400 wave in brain mapping
14
Correct word Close meaning Distant meaning
Conclusion:
N400 wave in brain mapping
Confusion by word’s close meaning act...
15Some results from our study:
Response time (behavioral data)
 Correct and distant noun meanings activated Broca’s area,
 Close noun activated frontal lobe (confusing noun)
16Some re...
 Correct noun - processed fast in most areas,
 Close noun – fast in left temporal area,
 Distant noun – slow in most ar...
 Correct verb meaning activated frontal,
 Close verb – right occipital,
 Distant verb – frontal, left parietal areas
18...
 Correct verb meaning – fastest in left parietal,
 Close verb – slow in most,
 Distant verb – fast in most, slow in tem...
20Some results from our study:
Noun and verb: P300 power
“Шил”
“Толь”
“Дуулах”
“Унтах” “Хѳгжимдѳх”
“Арал”
Broca’s expressi...
21Some results from our study:
Noun and verb: Reaction time (sec)
“Шил”
“Толь”
“Дуулах”
“Унтах” “Хѳгжимдѳх”
“Арал”
Broca’s...
22
Object, action (event) tectonics and its characteristics -
Sequence regularities - Neural recurrent networks
Research ques...
Assumptions
 Semantic relationships between nouns, verbs and
adjectives are a reflection of knowledge sequence
represente...
25
Word
Sentence
Number processing is similar to syntactic processing.
In numeral grammar, some words combine additively - fo...
27
“Төмөр хаалгатай модон хашаа”
Same direction, but different magnitude – vector addition
28
Complex scalar field – perceptual geometry.
High diving – прыжок в воду.
Complex scalar field – vector dot or cross produc...
Semantic + Pragmatic values – Complex effect
Mental blending (mental syntax):
“хар цамц (black shirt)” – vector dot produc...
Non-linear thinking - Non-linearity in mental syntax
Superposition and semantic transformation - metaphor
Complex effect o...
ном (book) – weak cohesion, linear association
санаа (idea) – strong cohesion, non-linear association
засах no semantic ch...
Complex effect of semantic/pragmatic forces - Vector cross
product – torque
“ширээ булаалдах (ширээ – албан тушаал)”
“толг...
Typologically different languages –
Coordinates of verbal cognition (perceptual geometry) –
mental superposition in multi-...
Conclusions
 Vector analysis method in combination with
experimental study is a powerful tool for modeling of
localizatio...
References:
1. Chuluundorj, B. 2013. Mathematical Approaches to
Cognitive Linguistics. International Journal of Applied
Li...
Thank you!
37
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Verbal cognition: vector space analysis by Chuluundorj.B /University of the Humanities/

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Neuro-cognitive and psychological linguistics present important area of multidisciplinary research.
In this paper we have described some possible applications of mathematical methods to neuro-cognitive linguistics. In neuro-cognitive study of language, neural architecture and neuropsychological mechanism of verbal cognition are basis of a vector–based modeling. A comparison of human mental space to a vector space is an effective way of analyzing of human semantic vocabulary, mental representations and rules of clustering and mapping in typologically different languages.
Euclidean and non-Euclidean spaces can be applied for a description of human semantic vocabulary and high order structures reflecting internal and external features of object and action (event). Vector analysis of word meaning and basic syntax structures offers new methodological opportunities to interpret effect of semantic and pragmatic forces at morphology and syntax levels.
Non-linear and metaphoric transformations present specific complex phenomenon to be described in 3D and other N-dimensional spaces in the framework of quantum semantics.

Keywords: Mental mapping, human mental lexicon, embodied and symbolic cognition, verbal cognition, semantic space, scalar, vector space, mental transformation, semantic gravity.


Published in: Science
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Verbal cognition: vector space analysis by Chuluundorj.B /University of the Humanities/

  1. 1. 1 Verbal cognition: vector space analysis Chuluundorj. B University of the Humanities, Mongolia THE 11TH INTERNATIONAL CONGRESS OF MONGOLISTS ULAANBAATAR, 2016
  2. 2. Quantum brain – Quantum mind Brain energy transmission – wave/particle duality Human mental space – quantum semantic space Deep structures – Mental structures (Chomsky. N 2000. New horizons in the study of language and mind. Cambridge) 2
  3. 3. Mental lexicon – semantic organization of vocabulary – human semantic memory Research question: Universal principles of mental lexicon – embedding in neural associative sets 3
  4. 4. 4
  5. 5. 5
  6. 6. qEEG and ERP (quantitative electro-encephalo-graphy and event related potentials) Assess: amount, time, frequency, localization of brain activation and behavioral responses during verbal thinking Assumptions:  Connection of different classes of words with different regions of the brain  Neural networks – different classes of words N – static features V – dynamic features Open class of words Closed class of words 6
  7. 7. 7 Brain electric waves involved in verbal thinking: P300 – word and object recognition, working memory, semantic congruity, decision making, novelty processing, lie detection P600 – word and semantic memory, syntactic congruity N100 – cognitive flexibility, stimuli matching, expectancy N200 - word and object recognition, semantic congruity, cognitive inhibition N400 – semantic congruity, semantic memory, word decision, comprehension P200 – working memory, verbal memory
  8. 8. 8Some examples from our study: Raw qEEG data
  9. 9. 9 Word recognition “Алим” (correct word) “Лийр” (close meaning) “Aяга” (distant meaning)
  10. 10. 10 Correct word Close meaning Distant meaning Some results from our study: P300 wave in brain mapping Broca’s expressive area Wernicke’s perceptive area Broca’s area Wernicke’s area Broca’s area Wernicke’s area
  11. 11. 11 Correct word Close meaning Distant meaning Conclusion: P300 wave in brain mapping Word processing & expression - active in distant word recognition Broca’s expressive area Wernicke’s perceptive area Broca’s area Wernicke’s area Broca’s area Wernicke’s area
  12. 12. 12 Correct word Close meaning Distant meaning Some results from our study: N400 wave in brain mapping Broca’s expressive area Wernicke’s perceptive area Broca’s area Wernicke’s area Broca’s area Wernicke’s area
  13. 13. 13 Correct word Close meaning Distant meaning Some results from our study: N400 wave in brain mapping
  14. 14. 14 Correct word Close meaning Distant meaning Conclusion: N400 wave in brain mapping Confusion by word’s close meaning activates frontal area Broca’s expressive area Wernicke’s perceptive area Broca’s area Wernicke’s area Broca’s area Wernicke’s area
  15. 15. 15Some results from our study: Response time (behavioral data)
  16. 16.  Correct and distant noun meanings activated Broca’s area,  Close noun activated frontal lobe (confusing noun) 16Some results from our study: NOUN: max power (μV) “Шил” correct meaning “Толь” close meaning “Арал” distant meaning Broca’s expressive area Wernicke’s perceptive area Broca’s area Wernicke’s area Broca’s area Wernicke’s area
  17. 17.  Correct noun - processed fast in most areas,  Close noun – fast in left temporal area,  Distant noun – slow in most areas 17Some results from our study: NOUN: Reaction Time (sec) “Шил” correct meaning “Толь” close meaning “Арал” distant meaning Broca’s expressive area Wernicke’s perceptive area Broca’s area Wernicke’s area Broca’s area Wernicke’s area
  18. 18.  Correct verb meaning activated frontal,  Close verb – right occipital,  Distant verb – frontal, left parietal areas 18Some results from our study: VERB: max power (μV) “Дуулах” correct “Хѳгжимдѳх” close “Унтах” distant Broca’s expressive area Wernicke’s perceptive area Broca’s area Wernicke’s area Broca’s area Wernicke’s area
  19. 19.  Correct verb meaning – fastest in left parietal,  Close verb – slow in most,  Distant verb – fast in most, slow in temporal & frontal areas 19Some results from our study: VERB: Reaction Time (sec) “Дуулах” correct “Хѳгжимдѳх” close “Унтах” distant Broca’s expressive area Wernicke’s perceptive area Broca’s area Wernicke’s area Broca’s area Wernicke’s area
  20. 20. 20Some results from our study: Noun and verb: P300 power “Шил” “Толь” “Дуулах” “Унтах” “Хѳгжимдѳх” “Арал” Broca’s expressive area Wernicke’s perceptive area
  21. 21. 21Some results from our study: Noun and verb: Reaction time (sec) “Шил” “Толь” “Дуулах” “Унтах” “Хѳгжимдѳх” “Арал” Broca’s expressive area Wernicke’s perceptive area
  22. 22. 22
  23. 23. Object, action (event) tectonics and its characteristics - Sequence regularities - Neural recurrent networks Research question: Mental syntax primitives - Universality in mental mechanism of blending 23
  24. 24. Assumptions  Semantic relationships between nouns, verbs and adjectives are a reflection of knowledge sequence represented in prefrontal association cortex.  Phrase structure rules are a reflection of knowledge sequence in perisylvian pattern-associator networks. 24
  25. 25. 25
  26. 26. Word Sentence Number processing is similar to syntactic processing. In numeral grammar, some words combine additively - forty- three (40+3), whereas others combine multiplicatively: seven hundred (7x100). (David, L., Naoch, S., & Aleah, 2013. Estimating large number C37). Complex numbers - Complex nouns “Хар бал” (additively), “Хар шөнө” (multiplicatively), “Хар санаа” (multiplicatively) 26 structure - mental blending 40+3 7x100
  27. 27. 27
  28. 28. “Төмөр хаалгатай модон хашаа” Same direction, but different magnitude – vector addition 28
  29. 29. Complex scalar field – perceptual geometry. High diving – прыжок в воду. Complex scalar field – vector dot or cross product 29
  30. 30. Semantic + Pragmatic values – Complex effect Mental blending (mental syntax): “хар цамц (black shirt)” – vector dot product (scalar) “хар шөл (meat soup)” “хар санаа (bad, hostile idea)” – vector cross product (vector) 30
  31. 31. Non-linear thinking - Non-linearity in mental syntax Superposition and semantic transformation - metaphor Complex effect of semantic pragmatic forces – vector dot product ном авах оноо санаа хар 31
  32. 32. ном (book) – weak cohesion, linear association санаа (idea) – strong cohesion, non-linear association засах no semantic change, linear semantically transformed булаалдах no semantic change semantically transformed (linear) a ball (linear) a disease (non-linear) 32 авах ширээ (table) catch
  33. 33. Complex effect of semantic/pragmatic forces - Vector cross product – torque “ширээ булаалдах (ширээ – албан тушаал)” “толгой угаах (толгой-бодол санаа)” 33
  34. 34. Typologically different languages – Coordinates of verbal cognition (perceptual geometry) – mental superposition in multi-dimensional tensor space “од харвах” “звезда упала” “а star is falling” Mental superposition – a phenomenon related to human verbal cognition and object of analysis in quantum semantics 34
  35. 35. Conclusions  Vector analysis method in combination with experimental study is a powerful tool for modeling of localization of different classes of words in semantic memory, and of connections of these classes with different regions of the brain.  Interpretation of word sequences in vector space is an effective way for analysis of basic rules which regulate these sequences in typologically different languages. 35
  36. 36. References: 1. Chuluundorj, B. 2013. Mathematical Approaches to Cognitive Linguistics. International Journal of Applied Linguistics & English literature. Vol. 2 No.4. Australian International Academic Centre. Australia 2. Chuluundorj, B. 2014. Vector-Based Approach to Verbal Cognition. Global Journal of Human-Social Science: Arts & Humanities – Psychology. Vol.14, Issue 3/1.0 Global Journals Inc. USA. 3. Chuluundorj, B. 2016. Vector Field Analysis of Verbal Structures. British Journal of Applied Science & Technology 12(3): 1-7. Science Domain International. UK. 36
  37. 37. Thank you! 37

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