VERBAL COGNITION VECTOR SPACE ANALYSIS BY CHULUUNDORJ B

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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 space

Deep 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

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

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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 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

8Some examples from our study:

Raw qEEG data

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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

Broca’s

expressive

area

Wernicke’s

perceptive

area

Broca’s

area

Wernicke’s

area

Broca’s

area

Wernicke’s

area

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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

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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

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Conclusion:


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

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)


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

Correct noun - processed fast in most areas, Close noun – fast in left temporal area, Distant noun – slow in most areas


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

Correct verb meaning activated frontal, Close verb – right occipital, Distant verb – frontal, left parietal areas


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

Correct verb meaning – fastest in left parietal, Close verb – slow in most, Distant verb – fast in most, slow in temporal & frontal areas


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


Noun and verb: P300 power

“Шил”

“Толь”

“Дуулах”

“Унтах” “Хѳгжимдѳх”

“Арал”

Broca’s expressive area

Wernicke’s perceptive area


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 interpretationLexicon, morphology (word value/meaning)→ 2𝐷Human 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

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)

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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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𝑅𝑥=𝐴𝑥+𝐵𝑥𝑅𝑦=𝐴𝑦+𝐵𝑦

Magnitude of resultant:

𝑅 = 𝑅𝑥2 + 𝑅𝑦

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Direction of resultant:

𝜃𝑅= 𝑡𝑎𝑛−1𝑅𝑦

𝑅𝑥

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 syntax

Superposition and semantic transformation - metaphor

Complex effect of semantic pragmatic forces – vector dot

product

ном

авах оноо

санаа

хар

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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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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.

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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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