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Verbal cognition: vector space analysis
Chuluundorj. B University of the Humanities, Mongolia
THE 11TH INTERNATIONAL CONGRESS OF MONGOLISTS
ULAANBAATAR, 2016
Quantum brain – Quantum mind Brain energy transmission – wave/particle duality Human mental space – quantum semantic spaceDeep structures – Mental structures (Chomsky. N 2000. New horizons in the
study of language and mind. Cambridge)
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Mental lexicon – semantic organization of vocabulary – human semantic memory Research question: Universal principles of mental lexicon – embedding in neural associative sets
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qEEG and ERP (quantitative electro-encephalo-graphy and event related potentials)
Assess: amount, time, frequency, localization of brain activation and behavioral responses during verbal thinkingAssumptions: Connection of different classes of words with
different regions of the brainNeural networks – different classes of words
N – static features V – dynamic features Open class of words Closed class of words
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Brain electric waves involved in verbal thinking:P300 – word and object recognition, working memory, semantic congruity, decision making, novelty processing, lie detectionP600 – word and semantic memory, syntactic congruityN100 – cognitive flexibility, stimuli matching, expectancyN200 - word and object recognition, semantic congruity, cognitive inhibition N400 – semantic congruity, semantic memory, word decision, comprehension P200 – working memory, verbal memory
8Some examples from our study: Raw qEEG data
P – positive wave
N – negative wave
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Word recognition
“Алим” (correct word)“Лийр” (close meaning)“Aяга” (distant meaning)
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Correct word
Close meaning
Distant meaning
Some results from our study: P300 wave in brain mapping
P300
P300
P300
Broca’s expressive area
Wernicke’s perceptive area
Broca’s area
Wernicke’s area
Broca’s area
Wernicke’s area
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Correct word
Close meaning
Distant meaning
Conclusion: P300 wave in brain mapping
P300
P300
P300
Word processing & expression - active in distant word recognition
Max P300 in Broca’s area
Broca’s expressive area
Wernicke’s perceptive area
Broca’s area
Wernicke’s area
Broca’s area
Wernicke’s area
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Correct word
Close meaning
Distant meaning
Some results from our study: N400 wave in brain mapping
N400
N400
N400
Broca’s expressive area
Wernicke’s perceptive area
Broca’s area
Wernicke’s area
Broca’s area
Wernicke’s area
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Correct word Close meaning Distant meaning
Some results from our study: N400 wave in brain mapping
N400 N400N400Amplitude (μV)
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Correct word
Close meaning
Distant meaning
Conclusion: N400 wave in brain mapping
N400
N400
N400
Confusion by word’s close meaning activates frontal area
Broca’s expressive area
Wernicke’s perceptive area
Max N400 in frontal area
Broca’s area
Wernicke’s area
Broca’s area
Wernicke’s area
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 results from our study: NOUN: max power (μV)
“Шил” correct meaning
“Толь” close meaning “Арал” distant meaningBroca’s
expressive area
Wernicke’s perceptive area
Broca’s area
Wernicke’s area
Broca’s area
Wernicke’s area
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 meaningBroca’s
expressive area
Wernicke’s perceptive area
Broca’s area
Wernicke’s area
Broca’s area
Wernicke’s area
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” distantBroca’s expressive area
Wernicke’s perceptive area
Broca’s area
Wernicke’s area
Broca’s area
Wernicke’s area
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” distantBroca’s expressive area
Wernicke’s perceptive area
Broca’s area
Wernicke’s area
Broca’s area
Wernicke’s area
20Some results from our study:Noun and verb: P300 power
“Шил” “Толь”
“Дуулах”
“Унтах” “Хѳгжимдѳх”
“Арал”
Broca’s expressive area
Wernicke’s perceptive area
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
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Vector-based interpretation Lexicon, morphology (word value/meaning)Human mental space - semantic space – metric space – similarity, distance between words
Object, action (event) tectonics and its characteristics - Sequence regularities - Neural recurrent networks
Research question: Mental syntax primitives - Universality in mental mechanism of blending
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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.
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Vector based interpretation: Syntax, discourse (semantic/pragmatic values/forces) scalar 2D and vector 3D
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Word SentenceNumber 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)
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structure - mental blending 40+3 7x100
Similar features of object (noun reference) – scalar multiplication “Шар, улаан, ногоон бөмбөлөг”
Same direction, but different distances (magnitude)Main reason intrinsic and extrinsic features differ in terms of strength of the association
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“Төмөр хаалгатай модон хашаа”
Same direction, but different magnitude – vector addition
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=+=+Magnitude of resultant: Direction of resultant:
Complex scalar field – perceptual geometry.High diving – прыжок в воду.
Complex scalar field – vector dot or cross product
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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)
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Non-linear thinking - Non-linearity in mental syntaxSuperposition and semantic transformation - metaphor Complex effect of semantic pragmatic forces – vector dot product
ном авах оноо
санаахар
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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)
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авах
ширээ (table)
catch
Complex effect of semantic/pragmatic forces - Vector cross product – torque
“ширээ булаалдах (ширээ – албан тушаал)”“толгой угаах (толгой-бодол санаа)”
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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
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ConclusionsVector 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.
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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.
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Thank you!
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