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PBS4 > Language > Flashcards

Language Flashcards

1
Q

What are the building blocks of language? (state)

A

Words

Phonemes (sound units)

Morphemes (smallest units of language)

Syllables (rhythmic units)

Stress (relative emphasis of syllables)

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2
Q

Words (language building blocks)

A

Representations stored in mental lexicon:

  • catalogue of words - mental dictionary
  • average person has 40,000-50,000 words
  • ML contains spelling, pronunciation, meaning, grammar category
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3
Q

Phonemes (language building blocks)

A
  • sound units of language - smallest units of speech that allow word discrimination
  • ~100 phonemes across world - ~40 in English
  • words not monolithic units of info - there are subcomponents
  • Spoonerisms (William Spooner)
    • in toast the the queen: ‘queer old dean’ not ‘dear old queen’
    • shows you can replace sound units
    • phonemes are cognitively real
  • Kuhl et al., (1992) - infants can distinguish between most phonemes
    • tune in to native language by age 1
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4
Q

Morphemes (language building blocks)

A
  • Smallest units that carry meaning
  • ’s’, ‘ing’, ‘ly’, ‘ness’, ‘er’
  • words can be morphologically complex or simple
    • complex = has multiple morphemes
  • morphological overlap (share morpheme)
    • will be faster to recognise the second
    • stored in ML somewhere?
  • morphological stranding = speech error where morphemes stay in the same place even if words swap
    • ‘a geek for books’ –> ‘a book for geeks’
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5
Q

Syllables (language building blocks)

A
  • rhythmic units - one vowel with or without surrounding consonants
  • expletive infixiation rule
    • can only insert expletive if there is a certain syllabic structure
    • ‘fan-fucking-tastic’
    • McCarthy (1982) - multiple syllables, word has main stress preceded by secondary stress
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6
Q

Stress (language building blocks)

A
  • relative emphasis of certain syllables - can alter meaning (CON-tent vs con-TENT)
  • Cappa et al., (1997) - aphasic CV
    • can produce individual phonemes but the stress is wrong
    • produces speech errors when stress fell on wrong syllables
    • dissociates phonemes from stress
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7
Q

Cognitive neuroscience of language:

  • Broca’s area
  • Wernicke’s area
A

Broca (1824-1880)

  • impaired language production, relatively intact comprehension (patient Tan)
  • left inferior frontal gyrus

Wernicke (1848-1905)

  • fluent (but disordered) production, impaired comprehenaion
  • left posterial temporal lobe
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8
Q

Classical language model

  • Wernicke-Geschwind model
A

Proposed by Wernicke (1874), extended by Geschwind (1970)

spoken word –> area 41 (auditory cortex) –> Wernicke’s area –> hear + comprehend word

cognition –> Wernicke’s area –> Broca’s area –> facial area of motor cortex –> cranial nerves –> speak

written word –> area 17 (V1) –> areas 18+19 (V2) –> area 39 (angular gyrus) –> Wernicke’s area –> read

(NB: typically left-lateralised)

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9
Q

Current views of language model

(neurobiological architecture)

A

Commonly activated regions:

  • left inferior frontal gyrus (Broca’s area)
  • superior, medial, inferior temporal gyri (L+R)
  • frontal regions in L hemisphere

White-matter tracts:

  • arcuate fasiculus –> links temporal + frontal regions (dorsal stream)
    • sound –> articulatory representations
    • L more prominent
  • extreme capsule –> links frontal to temporal regions (ventral stream)
    • speech –> conceptual representations
  • Hickok & Poeppel, 2004
    • some degree of bidirectionality in D+V streams

Vigneau et al., (2006) - meta-analysis of 128 imaging studies

  • prominent L frontotemporal network (also significant R hemisphere involvement)
  • highly interconnected regions - LH dominant but RH too
  • different parts of network activated based on task + input modality
  • phonological clusters, semantic clusters, sentence clusters
    • all partially overlapping
  • no strict modularity - interactions are key
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10
Q

Properties of written language

  • writing systems
  • role of regularity
A

Writing systems:

  • logographic = unique symbol per word/morpheme (Chinese)
  • syllabic = symbol for syllable (Japanese)
  • alphabetic = unique unit for each phoneme (english)
  • Dehaene (2009) –> diverse but all share visual features
    • recurring shapes, contrasting contours, average of 3 strokes per character

Role of regularity

  • Deep orthography (English/Hebrew)
    • letters/groups of letters have different sounds in different contexts
  • Shallow orthography (Finnish/Spanish)
    • consistent correspondence between letters and phonemes
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11
Q

Visual word recognition process:

  • Process
  • state components
A

Process:

  1. extract from visual input
  2. letter recognition
  3. orthographic lexicon AND/OR grapheme –> phoneme conversion

Components:

  • Eye movements
  • Letter recognition
  • Orthographic lexicon
  • Grapheme –> phoneme conversion
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12
Q

Eye movements (visual word recognition)

A
  • fixation and saccades
    • fixation brings text into foveal vision
      • high concentration of photoreceptors
      • average fixation = 200-250ms
    • average saccase length = 8 letter hop
      • 10-15% of time they move backwards
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13
Q

Letter recognition (visual word recognition)

A
  • recognise visual characteristics THEN identify
  • Miozzo & Carmazza (1998) - alexic patient RV
    • fine with visual characteristics
    • impaired at identifying words
  • alexic patients with lesions in L posterior regions - issue with identity
  • Visual word form area (L fusiform gyrus)
    • extracts identity of letter string
    • regardless of size/shape/position/language
  • Dehaene et al., (2001): visual priming
    • if prime with target word - reaction time decreases
    • subconscious early processing (implicit memory)
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14
Q

Orthographic lexicon (visual word recognition)

A

stores representation of spelling

  • activated when we read a familiar word
  • then obtain meaning from semantic systems
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15
Q

Grapheme to phoneme conversion (visual word recognition)

A

When reading novel words or pseudowords –> need to assemble the pronunciation from its letters

  • suggests word-processing models need partially distinctive mechanisms for regular vs irregular vs pseudowords
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16
Q

Dual-route model of written language processing

  • Coltheart et al., (2001)
  • evidence for separate systems
  • problems
A

Lexical route

  • faster for words
  • frequency-weighted
  • faster for regular words

Non-lexical route

  • faster for pseudowords and irregular words
  • assemble from letters and rules
  • if issue: problem with assembly
    • so retrieve closes real world word instead

Evidence for separate:

  • Patterson (1982) - AM –> problems with pseudowords
    • lexicalisation –> read it like closest legical item
    • 83-95% accuracy on normal words
    • 0-37% accuracy on pseudowords
  • Shallice et al., (1983) - HTR –> problems with irregular words
    • surface dyslexia
    • 79% accuracy on regular, 84% on pseudo, 48% on irregular

PROBLEM:

  • DRC fully hardwired –> can’t learn new rules (for non-lexical)
  • focus on English
  • doesn’t explain HOW implemented in brain
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17
Q

Triangle models (written word processing)

  • overview
  • pseudowords
  • irregular words
  • experimental data
A

Seidenberg & McClelland (1989); Harm & Seidenberg (2004)

  • orthography (letters); meaning (semantic units); phonology (sounds)
  • visual input –> O –> M/P
    • P –> output
  • same mechanism for words + pseudowords; irregular words + regular words
  • system picks up correspondences between specific orthographic units and phonological units
    • strong connections between units more often co-activated

Pseudowords –> O + P (no M because not real) –> if P damaged, need to rely on O-M correspondence –> so lexicalisation

Irregular words –> O + M (no P because irregular) –> if O damaged, need to reply on P-M (phonology) - so regularisation

BUT: focus on English AND doesn’t explain HOW implemented in brain

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18
Q

Written word processing in the brain

A

Marinkovic et al., (2003): MEG

  • activation starts in occipital lobe, spreads temporally
    • occipital-temporal junction
    • spreads temporally down ventral route (meaning) + frontal (top-down processing)

Dehaene et al., (2009):

  • ventral stream:
    • frontotemporal network (meaning)
      • bidirectional (top-down, bottom-up)
  • dorsal stream:
    • occipital –> parietal –> articulation/pronunciation
  • occipital lobe activation - low-level processing visual input
  • VWFA - binds lower-level processing to language network
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19
Q

Neuronal recycling hypothesis

A

Dehaene et al., (2009)

  • really high correlation between naturally-occuring image fragments + their frequency of occurence in written symbols
  • maybe we use visual image processing for language
  • reading co-opted evolutionarily-older brain functions - for visual object processing
    • explains why symbols are what they are
    • explains why we’re so good at reading even though evolutionarily new
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20
Q

Properties of spoken language

  • problems to solve
A
  • speech recognition - extracting invariant representations from continuous variable input
  • speech signal = continuous, distributed in time, fast-fading and variable (IDs)
  • word-segmentation problem - where do words start + end
  • word co-articulation problem - blending of sounds from one word to the next
  • child’s paradox - how do children separate words if they don’t know them
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21
Q

Major elements of speech recognition (state them)

A
  1. word segmentation
  2. lexical selection
  3. access to meaning
  4. context effects
22
Q

Word segmentation (speech recognition)

  • MSS
    • evidence
    • evaluation
A
  • Cutler & Norris (1988) - metrical segmentation strategy
    • stressed syllables at onset of words
    • continuous speech segmented at stress syllables
    • stressed syllables more likely to be content words (have full vowels)
    • unstressed syllables more likely to be grammatical words
  • Cutler & Carter (1987) - evidence supporting MSS:
    • English syllable distribution
    • 3/4 of time: stressed = content, unstresses = grammatical

Evaluation:

  • not infallible - just a strategy
    • need other sources of info to supplement
  • language-specific
  • solves child’s paradox
23
Q

Lexical selection (speech recognition)

  • shadowing paradigm
  • gating paradigm
  • cohorts
  • salience of onset
  • late activation
A
  • Searching process - determine best fit between input + lexical representations
  • fast - words in context can be recognised 175-200ms from onset (only part of content presented)
  • Marslen-Wilson (1975) - shadowing paradigm
    • hear sentence + repeat
    • sentence has some mispronunciations
    • people correct when repeating even before full presentation
    • not just representation
  • Tyler & Wessels (1983) - gating paradigm
    • presented with parts of a word - get progressively longer
    • decreasing cohorts of possible endings as word gets longer
    • uniqueness point = point at which the word can be disambiguated from all others in the cohort
  • Marslen-Wilson & Welsh (1978) - cohort models
    • when we hear a word we start a parallel search consistent with the onset
    • as more info comes in, words drop off + cohort gets narrower
  • Tyler (1984) - set size decrease happens faster in context
  • Marslen-Wilson (1980) - ~150ms needed to set up a cohort
  • Cole & Jakimik (1980) - salience of onset makes it more likely to detect mispronunciation at start of word than end
    • lexical search starts immediately
  • Allopenna et al., (1998) - additional late actication - info at later points can still activate lexical selection
    • increase in fixation probability for word that rhymes
24
Q

Access to meaning (speech recognition)

A

Deciding which meaning of a word is correct

  • Swinney (1979) - ambiguous vs disambiguous context - bug = ant or spying device
    • for early target - both dominant + non-dominant meanings activated by the prime
    • for later (200ms) target - dominant meaning is only one activated –> has had time to disambiguate
  • different meanings initially activated but context helps select
25
Q

Context effects (speech recognition)

A

Important for noisy environments

  • Warren (2008) –> phoneme restoration effect
    • if cough sound over one phoneme, still hear word intact
  • Pollack & Pickett (1964) –> spoken word recognition decreases significantly if presented out of context + alone
  • Tyler (1984) –> context effect in gating
    • set size decrease happens faster in context
    • faster recognition
26
Q

Speech processing in the brain

A

Hickok & Poeppel (2007) - dual-stream model

  • ventral stream –> maps sound to meaning
    • for comprehension
    • bilateral activity in Heschl’s gyrus, superior+ medial temporal areas
  • Dorsal stream –> maps sound to articulation
    • for more complex input like sentences
    • left-lateralised, particularly left inferior frontal gyrus (Broca’s area)

Gil-da-costa et al., (2006) –> looked at sound-meaning mapping in evolutionary context

  • rhesus macaques - exchange meaningful calls - stimulates comparable activity to humans
  • PET –> activity in homologs of human language areas for salient vs non-salient stimuli

Rillig et al., (2008)

  • left inferior frontal gyrus activation for complex input (sentences) –> dorsal stream
  • temporal + frontal connection is unique to humans
    • for grammatical + syntactic processes
  • temporal lobe projection of human arcuate fasiculus is absent/smaller in non-human primates
    • may be relevant for language evolution
27
Q

Sentence processing

  • outline:
    • sentence
    • syntactic rules
    • syntactic parsing
  • state main 4 theories of sentence processing
A

Sentences = not stored, need rapid mechanisms for parsing + extracting information

Syntactic rules - govern how words can be combined in a language (indepentend of meaning) –> abstract enough for ALL grammatically correct sequences BUT still rule out illegal grammar

4 main theories:

  1. Garden-Path model (Frazier & Rayner, 1982) –> initial parsing is purely syntactic, meaning informs later
  2. Constraint-based theories (MacDonald et al., 1994) –> initial interpretation depends on all available sources of information
  3. Unrestricted race model (Van Gompel et al., 2000) - all sources of info used to identify a syntactic structure
  4. ‘Good enough’ representations (Ferreiva et al., 2002) –> type of information used depends on the task - has to be good enough for context

(1+2 are the main ones)

28
Q

Sentence parsing cues (state)

A
  1. syntactic principles
  2. statistical regularities
  3. grammatical categories
  4. prosodic cues
  5. semantic information
  6. world knowledge
29
Q

Syntactic principles (sentence parsing)

A

Frazier (1987)

  • late closure principle –> new items attached to the phrase/clause most recently processed
    • optimises sentence comprehension
    • decreases cognitive demand
    • decreases STM requirements
  • Minimal attachment –> links each incoming word to existing structure using simplest syntactic structure consistent with the input
    • parsimony
30
Q

Statistical regularities (sentence parsing)

A

Word order: english = SVO; japanese = SOV

Slobin (1966)

  • presented participants with active/passive sentences, either reversible or irriversible (S+O swappable)
    • RT matching sentence to pictures decreased for all active - because more fequently encountered
31
Q

Grammatical categories (sentence parsing)

A
  • individual words provide cues for sentence interpretation
    • e.g. articles, prepositions, pronouns
    • and = new phase node
    • that/which = embedded sentence
32
Q

Prosodic cues (sentence parsing)

A

Relative emphasis of different parts of the sentence

Beach (1991) - sentence completion task –> 2 types of sentence with same verb (‘argued’):

  • Direct object - forcefully short vowel + stable pitch contour
  • Complement - long vowel + fall-rise pitch
  • if DO verb –> completed sentence in a way that had DO characteristics
  • same result no matter how long the segment was
  • prosodic cues define elements of the sentence and how they sit together
33
Q

Semantic information (sentence parsing)

A

Meaning of individual elements

Trueswell et al., (1994) –> 2 sentences, one word changes

  • reaction time longer (slower) if have to read 2 animate things in same sentence - creates more of a conflict in putting the sentence together
34
Q

World knowledge (sentence parsing)

A

Effect of violation of world knowledge are rapid and parallel to those for semantic violations

Hagoort et al., (2004): ERP + fMRI - 3 sentences, 1 true, 1 world violation, 1 semantic violation

  • world knowledge violation + semantic violation produce response at the same time (N400)
  • semantic + world knowledge are equally fast + influence sentence processing in parallel
35
Q

Neurobiology of syntax

A

Vigneau et al., (2011) - meta-analysis of 128 studies of syntactic processing

  • extended frontotemporal processing netword (mainly on L)
  • frontotemporal white matter connections (L) –> dorsal (arcuate fasiculus) + ventral (extreme capsule)

Rolheiser et al., (2011) - white matter tracks + syntactic comprehension

  • worse performance with less white matter density (patients with white matter damage)
36
Q

Neuro-cognitive model (for syntax)

A

Friederici, 2011

  • functional distinction between dorsal + ventral pathways in L hemisphere

Friederici & Gierhan, 2013 (looking at functional brain imaging):

  • ventral pathway (aSTG) for simple syntax
    • putting elements together
    • the uncinate fascile and the inferior fronto-occipital fascile subserve semantic and basic syntactic processes
    • the FC and the TC are connected via at least two pathways
      • the uncinate fascile (UF)
      • extreme capsule fiber system (ECFS)
    • supporting local phrase structure building
    • [also semantic processing]
  • dorsal pathway (pSTG) for complex syntax
    • dependencies/embedding
    • complex computations
    • one pathway connects the temporal cortex and premotor cortex –> for speech repetition,
    • another pathway connects the temporal cortex and posterior Broca’s area –> for complex syntactic processes
    • the tract from the STG to Broca’s area is relevant for complex syntactic processes
    • [also auditory –> motor mapping]
37
Q

Evolutionary context (sentence processing)

A

Rillig et al., (2004) - evolutionary expansion of dorsal frontotemporal pathway in humans (L) –> involved in processing of complex sentences

Fitch & Hausel (2004) - non-human primates aren’t capable of mastering complex syntactic combinations

  • both humans + monkeys can spot simple sequence violations (look/no-look measure)
  • only humans can spot complex sequence violations
38
Q

Bilingualism - history

  • historical costs
  • benefits
  • costs
A

COSTS (historically):

  • Saer (1924) - in rural context, IQ of bilinguals = 86 vs 96 of monolinguals
    • BUT: other factors involved
  • Jesperson (1922) - brain effort required for bilingualism –> reduces ability to learn other things

BENEFITS:

  • Peal & Lambert (1962) - positive correlation between bilingualism and intelligence when other factors controlled
  • EF –> ‘bilingual advantage’
  • metalinguistic knowledge:
    • Ianco-Worrall (1972) - can you call a dog ‘cow’ and a cow ‘dog’ if you were creating a language
      • BL (English-Afrikaans) more likely to say yes
      • by 7-9yrs - 0.59 BL (4-6yrs = .38)
      • English ML = 0.08 (4-6yrs), 0.38 (7-9yrs)

COSTS:

  • Disadvantage in receptive vocabulary in preschool + early school years
    • given word + have to find picture it relates to
    • bilinguals have 2 possible labels - so relative usage of each is less
  • Tip-of-the-tongue –> temporary inability to produce a known name or word
    • Gollan et al., (2005) - TOT higher for bilinguals on objects (2 labels) but no difference on famous or personal names
39
Q

Bilingualism and the brain

  • activation for L1 and L2?
A

Indefrey (2006) - meta-analysis –> only 2/5 showed greater activation for L2 than L1

De Bleser et al (2003) - PET: dutch ML vs Dutch-French BL - latte acquisition (10yrs)

  • cognates (same meaning similar sound in L1+L2)
    • L2 has same activation as L1
  • noncognates
    • greater activation in frontal regions due to increased difficulty + increased cognitive capacity required

Rodriguez-Fornells et al (2005) - early acquisition: German, German-Spanish (L2 by 3yrs)

  • used L2 for work/study
  • activation pretty much the same in both

Indefrey (2006)

  • chinese (L1) tested 3,6,9 months into a Dutch learning program (L2)
    • after 6 months of exposure - identical regions in L frontal areas as in native speakers
40
Q

Hierarchical model of bilingual acquisition

A

Kroll & Stewart (1994):

  • Initial stage:
    • meaning of L2 word accessed via L1 analogue mediator
    • lexical links between L2 –> L1
    • L1 concepts
  • Later stage
    • link directly from L2 –> meaning (direct access withough L1 involved)
    • can translate between L1 + L2
  • Final stage (proficient bilinguals)
    • bidirectional relation between them all

Prediction:

  • in intermediate stage - should be differences in L1–>2 translation vs L2–>L1 (semantic effect)
  • Kroll & Stewart (1994): confirmed with English-Dutch bilinguals:
    • slower to translate L1–>L2 than L2–>L1
      • due to being mediated by meaning
41
Q

Bilingualism - competing for access (in parallel)

A

Green (1998) - suppression hypothesis –> both L1 + L2 constantly competing for access, have to suppress one

Spivey & Marian (1999) - presented with grid, have to follow instructions (Russian-English BLs)

  • distractor present (sounds like a russian word –> phonological overlap)
  • distractor shows some fixation even if instruction in english
  • process in parallel - simultaneously

Meuter & Allport (1999) - code-switching paradigm

  • digit colour indicates the language to name in
  • RT in switching trials is higher (as expected)
  • RT for L2 is higher than L1
  • slower to switch from L2 –> L1 than L1 –> L2 (becuase better at suppressing L2)
  • takes a lot of effort to suppress L1 in L2 trials so there is a spill-over effect (suppression hypothesis)
42
Q

Bilingualism and executive functioning

  • the ‘bilingual advantage’
A

Suggestion that EF of BL is better due to constant inhibition of non-target language

  • Bialystok et al., (2004) - Simon task - overcoming conflicting cues to make a decision
    • interference greater for ML
    • reduced Simon effect + age effect for BL
    • reduced WM cost for BL
    • better prepared to cope with conflicting info?
  • Craik et al., (2010) - Bilingual patients with Alzhiemers
    • diagnosed 4.3yrs later
    • onset of symptoms 5.1yrs later than ML
    • languagr experience may contribute to cognitive reserve - compensating for effects of neuropathology
43
Q

The bilingual advantage - evaluation

A

CRITIQUES (Paap et al., 2015;16):

  • some replication attempts failed
  • some possible methodological problems (SS, SES, cultural differences, immigrant status)
  • publication bias (more likely to publish positive)
  • chicken + egg problem:
    • BL –> better EF or
    • better EF –> aquiring L2/3/4

Beyond bilingual advantage:

  • Olguin et al (2019) - learning/using multiple languages is environmental/cognitive demand
    • brains adapt to environmental demands to maintain/optimise performance
    • even if behavioural performance the same, maybe use different neural mechanisms for ML vs BL
    • BL may trigger adaptive reconfiguration of the system - for optimal performance
44
Q

Gestures (communication)

  • types
  • functions
A

TYPES:

  • Beats = coordinated with speech prosody but no relation to meaning of it
    • simple + repetitive
  • Pointing = simple conventionalised movements referring to spatial locationrs or to bind objects to them
  • Symbolic gesture = movement with conventionalised meaning
    • ok, thumbs up, fingers crossed
  • Lexical gestures = non-repetitive, change in form
    • relate to meaning of accompanying speech

Iverson & Goldin-Meadow (1998) - congenitally blind people gesture as much as sighted people

FUNCTION

  • communicative + informative
  • facilitating word production
    • Morrel-Samuels & Krauss (1992) - onset of gestures: 500ms-1s before words
      • familiar words = closer gesture asynchrony + briefer - less planning/effort
    • Rauscher et al., (1996) - gesture effects on speech fluency
      • fake electrodes to immobilise hands
      • no gesturing when describing spatial-related content = more disfluency
45
Q

Pauses and disfluencies (communication)

A

Breaks/irregularities/utterances not consistent with specific grammatical construction and occur within otherwise fluent speech (~6/100 words) - ‘uh’/’er’/’like’

Informative

  • 60-70% of pauses fall at juncture of sentences
  • disfluencies often at beginning of utterance (planning)

Brennan & Schober (2001): move mouse to square indicated in utterance

  • between word interruptions
    • move to the yellow purple square
      • affects performance most
  • mid-word interruption
    • move to the yel purple square
  • mid-word interruption and filler
    • move to the yel uh purple square
      • speeds up comprehension
  • disfluencies can signal speech repair - tell you to pay attention
46
Q

Conversation convergence (communication)

  • what is it?
  • example
  • reasons behind it
A

Temporary, flexible agreements between speaker and listener to view/name objects a certain way

Metzing & Brennan (2003): task = locate + move object in grid according to speaker’s instructions

  • speaker names object, gives instruction + keeps that name for the rest of time - listener agrees
  • NEW speaker:
    • listener equally fast to detect target if new OR old word used (because no agreement with them)
  • OLD speaker, NEW word:
    • confusion and increased RT - because breaking social agreement
  • Measured by eye movement - time looking at target

Garrod & Pickering (2004) –> speeds up communication

  • coordinate - keep track of who says what
  • distributes processing load between interlocuters
  • maybe relies on simple priming + imitation mechanisms
47
Q

Multimodal integration

  • positives (speech/vision)
  • preceding speech
A

POSITIVES:

  • increases signal:noise ratio - raise up to 20dB
    • Sumby & Pollack (1954)
  • enhances comprehension of speaker if you see them - especially if complex speech/heavy accent
    • Reisberg, McLean & Goldfield (1987)

Precedes speech:

  • prelinguistic children link mouth movement to auditory signals
    • Kuhl & Meltzoff (1982)
  • macaques have highly deveoped audio-visual integration –> to support social interaction
    • make similar eye movements to humans (focus on eye and mouth)
    • single-cell recordings show cells in auditory cortex respond stronger to integrated signals
    • Ghazanfar et al (2008)
48
Q

Neural coupling (communications)

A

Neural coupling hypothesis: Hasson et al., (2012)

  • stimulus-brain coupling –> to retrieve info about world + guide actions
  • brain-to-brain coupling –> coordination among individuals in shared physical/social environment

Stephens et al (2010) –> temporal + spatial coupling of brain activity (speaker + listener in fMRI scanner)

  • coupling in early auditory areas, superior temporal + inferior parietal gyri, insula + inferior frontal gyri
  • synchronous speaker-listener coupling in early auditory cortices
  • predictive anticipatory coupling in frontal lobe (PFC) - activation in listener precedes speaker
  • level of comprehension correlates with degress of coupling in frontal areas
  • neural coupling only in successful communication
49
Q

Social contract in conversations - example (Tomasello)

A

Wyman, Rakoczy, and Tomasello, 2009

  • “No, you can’t eat that. It’s soap!” (Wyman, Rakoczy, and Tomasello, 2009)
    • Both understand and enforce the norms
    • One block = soap
    • Other block = sandwich
    • Kids get mad at breaking the pretence
50
Q

word segmentation

  • phonological bootstrapping
  • distributional learning
  • statistical learning
A
  • Phonological bootstrapping
    • Use phonotactic or prosodic cues (vowel length, pauses, loudness) to help break wall of speech
  • Distributional learning
    • Track how often certain elements appear
  • Statistical learning
    • How often certain elements cooccur with other elements
    • Saffran, Aslin & Newport, 1996
      • 8-month-old infants listened to 2 minute stream of syllables (made-up language – 4 x 3 syllable words)
        • tibudogolatudaropipabikutibudodaropigolatudaropi tibudopabikudaropitibudopabikugolatu
      • Then test words presented (2 types)
      • Transitional probabilities: (between 1st + 2nd and 2nd + 3rd syllables)
        • Test “words” from made-up language (pabiku, tibudo) = 1
          • Only ever occurred together
        • Test “non-words” not from language (tudaro, pigola) = 0.33
          • From final syllable of one word + first 2 of another word
          • String of syllables only occurred if 1st word followed by 2nd word
      • During test phase – infants listened to non-words significantly longer than words  could track transitional probabilities + distinguish between test words
      • Infants learn structural properties of input
        • Powerful learners
        • Non-linguistic cognitive abilities play important role in language learning
  • Once they break wall of sound, they can use distributional + statistical learning to analyse frequency + cooccurrence of certain patterns of sound/words/phrases
    • Phonological bootstrapping to break up sound  then distributional + statistical learning
51
Q

Phoneme experiments

  • categorical perception
  • phonemic tuning
    • head turn
    • MEG
A

Eimas et al. 1971

  • interested in how people perceive sounds on a continuum (e.g. b  p)
    • Do this by varying voice onset time (only way they differ)
    • Sounds were evenly spaced across continuum but there was a noticeable point where b becomes p
      • For adults voice onset time of +20 is heard as ‘ba’ and +40 is heard as ‘pa’
      • +40 - +60 did not have same reaction
  • Used high amplitude sucking technique to test on infants (1-4 months)
    • Infants given special dummy to measure sucking rate
    • Habituated to hearing ‘ba’ first until sucking rate gradually declined
    • 6 stimuli used with VOT from -20 to +80 –> showed significant dishabituation in sucking rate (sped up) between +20 and +40
    • Conclusion –> by age of just 1 years old they perceive sounds categorically in same way as adults
      • Either /b/ or /p/ - cannot be both

Werker and Tees, 1984

  • Young infants have categorical perceptions for sounds in other languages too
  • Used pairs of sounds that sound the same to English adults but in other languages were contrastive phonemes
  • Head turn procedure: Infant rewarded for turning head when sound changed
  • English infants – declined until adult level
  • Tuning in process –> when hear native language, infant becomes adept at discriminating sounds in native language
  • In Japanese – infants born with r/l distinction not important in their language but after 1yr old they can’t tell them apart
  • Specialisation –> restriction of options

Kuhl, Ramírez, Bosseler, Lin and Imada (2014)

  • MEG to show that the ability to discriminate native versus non- native phonetic contrasts that emerges during the first year of life has both acoustic and motor components.
  • tested English learning infants aged 7+ 11– 12 months, contrasting native English phonemes with native Spanish phonemes (via different voicing for / d/ or / t/ sounds).
  • MMR showed that the younger infants could discriminate both native and non- native sounds,
    • showed brain activation in both auditory and motor regions
  • The MMR also showed that the older infants had lost the ability to discriminate the non-native speech sounds.
  • double dissociation between acoustic and motor neural regions for the older infants (also present in adults)
    • For auditory brain areas  there was greater neural activation for the native speech sounds than for the non- native speech sounds
    • for motor brain areas  there was greater neural activation for the non-native speech sounds than for the native speech sounds.
  • Suggested that infants’ increasing ability to form these speech sounds themselves could underpin this developmental dissociation

PBS4 (8 decks)

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