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Word recognition in normal reading. Sara C. Sereno. Collaborators : RAs/PGs : Paddy O’Donnell S é bastien Miellet Hartmut Leuthold Graham Scott Christopher Hand. Word Recognition. What factors affect word recognition?
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Word recognitionin normal reading Sara C. Sereno Collaborators: RAs/PGs: Paddy O’Donnell Sébastien Miellet Hartmut Leuthold Graham Scott Christopher Hand
Word Recognition • What factors affect word recognition? • How can word recognition processes be accurately measured? • How can effects be interpreted?
What factors affect word recognition? • Orthography of language • English vs. Hebrew or Japanese • Intraword (sublexical) variables • word-initial bi/tri-grams clown vs. dwarf • spelling-to-sound regularity hint vs. pint • neighborhood consistency made vs. gave • morphemes • prefix vs. pseudo-prefix remind vs. relish • compound vs. pseudo-compound cowboy vs. carpet
What factors affect word recognition? • Word (lexical) variables • word length duke vs. fisherman • word frequency student vs. steward • AoA rabbit vs. violin • expert vocabulary voxel • syntactic class open/closed-class; A,N,V • ambiguity bank vs. edge, brim • concreteness/imagability tree vs. idea • animacy dog vs. cup • affective tone love vs. farm vs. fire
What factors affect word recognition? • Extraword (supralexical) variables • Contextual predictability Neutral He bought a large plant for his garden. Biasing Terry went to the new gardening centre. He bought a large plant for his garden. • Syntactic complexity Trans. Mary took the book VERB Mary knew the book Intrans. Mary hoped the book on the table. was good. on the table. was good. on the table. was good.
stabbed assaulted … The mugger her with his weapon… He threw the knife into the bushes and ran away. What factors affect word recognition? • Extraword (supralexical) variables • Discourse factors Focus The dog chased the cat today. The cat was chased by the dog today. What the dog chased was the cat today. It was the cat that was chased by the dog today. Elaborative inferences & anaphora
What factors affect word recognition? • Language skill • beginning (novice) vs. skilled (expert) readers • normal vs. dyslexic vs. neuropsychological patient How can word recognition processesbe accurately measured?
Measure Task Time Res. “electrical” imagingsingle word presentation ~80-500 ms (EEG, MEG)word-by-word reading (P1,N1,EPN,N400) Eye movements in fixation time, location & ~250 ms normal reading sequence of EM’s Stnd. word recogn. naming ~500 ms ± priming, masking, lexical decision RT ~600 ms lateralized present. categorization ~800 ms “blood flow” imaging single word presentation seconds (PET, fMRI)
Word-by-word reading: 200 ms per word presentation reading-like sentence word word rate. This fast by of at is a a a
Word-by-word reading: 600 ms per word presentation sentence typically studies. word word used ERP slow This rate by of at in is a a a
* This is an approximation of normal reading in real time.
* This is an approximation of normal reading in real time.
* This is an approximation of normal reading in real time.
* This is an approximation of normal reading in real time.
* This is an approximation of normal reading in real time.
* This is an approximation ofnormal reading in real time.
* This is an approximation ofnormalreading in real time.
This is an approximation of normal reading in real time. *
This is an approximation of normal reading in real time. *
This is an approximation of normal reading in real time. *
The importance of making eye movements in normal reading Cond1 There was a box of… Cond2 There was an enormous box of… Cond1 She saw a cat in the… Cond2 She saw a cup in the… The measure affects what is being measured: • Perception of text influences how EMs made. • Location/duration of EMs affect perception.
Context Stimulus Quality Frequency RT RT How can effects be interpreted? • Theoretical approaches • Interactive (top-down) vs. Modular (bottom-up) • Additive factors
How can effects be interpreted? • Modelling
How can effects be interpreted? • Modelling • Repeated measures multiple regression analyses: Oculomotor-related factors launch distance to word location of fixation within word number of fixations on word word length word frequency contextual predictability Language-related factors
Factors Measures Approach orthography bi-/tri-grams regularity neighborhood morphology length frequency jargon word class ambiguity imagability animacy emotionality predictability syntactic prefs. focus inference anaphora skill ERPs + word-by-word (slow) presentation Eye movements + normal reading EM-ERP co-registration? Additive factors Repeated measures multiple regression
lexical humans Distributed hierarchical visual processing in primates higher-level semantics syntax meanings word forms letters features
Why? • Precisely delineate the time course of different levels of linguistic processing. • Help inform a temporally realistic neural circuitry of normal reading.
The importance of making eye movements in normal reading Cond1 There was a box of… Cond2 There was an enormous box of… Cond1 She saw a cat in the… Cond2 She saw a cup in the… The measure affects what is being measured: • Perception of text influences how EMs made. • Location/duration of EMs affect perception.
Context Stimulus Quality Frequency RT RT How can effects be interpreted? • Theoretical approaches • Interactive (top-down) vs. Modular (bottom-up) • Additive factors
How can effects be interpreted? • Modelling approach
How can effects be interpreted? • Modelling • Repeated measures multiple regression analyses: Oculomotor-related factors launch distance to word location of fixation within word number of fixations on word word length word frequency contextual predictability Language-related factors
How can effects be interpreted? Oculomotor-related factors launch distance to word location of fixation within word number of fixations on word word length word frequency contextual predictability Language-related factors
Why is word recognition important? By precisely delineating the time course of different levels of linguistic processing, it is possible to: • Determine which aspects of processing are Interactive (top-down) or Modular (bottom-up). • Help inform a temporally realistic neural circuitry of normal reading.
This is an approximation of normal reading in slow motion.
Word Recognition • What factors affect word recognition? • How can word recognition processes be accurately measured? • How can effects be interpreted?
Word Recognition • What factors affect word recognition? • How can word recognition processes be accurately measured? • What can accurately measured factors of word recognition tell us?
What factors affect word recognition? • Intraword (sublexical) variables • Word (lexical) variables • Extraword (supralexical) variables
Emotion Word Processing: RTs, Eye Movements, & ERPs Scott, O’Donnell, Leuthold, & Sereno Glasgow Language Processing University of Glasgow
Emotion Words • What are emotion words? • Express an emotional state (e.g., angry, happy) • Elicit an emotional state (e.g., snake, puppy) • 2 traditional dimensions of emotion words • Arousal≈ internal activation • Valence≈ value or worth
war sex nun low (negative) high (positive) high arousal low valence
Early Emotion Word Processing • Lexical Decision (LD) / ERP experiment Eye Movement (EM) reading experiment • Word frequency • High-frequency (HF) words are read more quickly than low-frequency (LF) words. • A word frequency effect (HF<LF) is used as a marker (index) of successful word recognition (lexical access).
Past Behavioural Experiments Stimuli negative vs. neutral words positive vs. neutral words emotional state words In general, stimuli are not well-controlled for psycholinguistic variables such as word length and frequency.
Past Behavioural Experiments TaskManipulations lexical decision masking emotional decision priming recollection mood induction odd-ball paradigms lateralised presentation forced-choice tasks stimulus repetition self-referential judgments blocked presentation
Lexical Decision • Emotion (Pos, Neg, Neut) x Frequency (HF, LF) • 40 words of each type (240 total words) HF: Pos, Neg, Neut LF: Pos, Neg, Neut • 240 length-matched non-words pronounceable pseudowords (blimble)
Lexical Decision • Norms Arousal & Valence: ANEW (1000 words) Frequency: BNC (90 million written words) • Randomised presentation – NO repetition, lateralised presentation, priming, masking, self-referential judgments, mood induction… • 26 participants
LD: Stimulus Specifications (N=40) Arousal Valence Freq Length (lo-hi, 1-9) (neg-pos, 1-9) (per mill) (char) LF Pos 6.7 7.6 8 7 Neut 4.5 5.2 7 7 Neg 6.6 2.4 7 7 HF Pos 6.6 7.8 62 6 Neut 4.3 5.2 67 6 Neg 6.7 2.6 50 6
rage venom detest hawk truck investfame cheer elated destroy jealousy scissors ketchupadmired ecstasy suffocate leprosy pamphlet highwayvalentine treasure shark slap rude muddy cane lumpglory sexy lust ambulance torture lighthouse privacymillionaire miracle fire anger danger book hotel fabricjoke brave pretty cancer divorce manner avenuetravel birthday accident violent reserved villagebeautiful success abuse fear burn bench bowl rockhappy kiss gift suspicious panic concentrate glassexcitement desire