Visual Word Recognition 1 Flashcards
what are the 3 features of visual word recognition?
- fast & automatic: 250-300 words/minute. Within 200 ms the brain distinguishes between words and nonwords
- flexible: : different scripts, case, fonts, handwriting
- Precise: able to distinguish words that are similar
Event-Related Potentials (ERP) Megastudy (Dufau et al., 2015)
- 960 words and 140 nonwords presented to 75 participants
- go/no-go lexical decision task (go for nonwords).
- data shows we pick up word features very rapidly, if its a word/non-word and semantic meaning etc.
what a lexical decision task?
a participant is presented with a single word, usually visually in the center of a computer screen. The participant’s task is to decide, as quickly and as accurately as possible, whether the word is a real word of his or her language
what did the stroop (1935) test find about fast and automatic visual recognition?
- no difference between reading words in incompatible colours vs. reading words in black ink
- naming ink colours: slower responses for ink of incompatible words than for solid squares
- Impossible to ignore the word in a colour-naming Stroop task
what is masked priming?
- Present two words in succession, first word (prime) is presented briefly, task focuses on the second (target) word
- then a lexical decision task to work out id the target was a word or a nonword
what is a orthographically related word?
a way that is connected with the accepted way of spelling and writing words
what is a phonological related word?
sounds similar
what are the effects of mask priming and relatedness?
A masked orthographically related nonword prime generally speeds up (facilitates) target word processing relative to an orthographically unrelated prime (e.g. Forster et al., 1987).
Flexible letter order effect, Rawlinson (1999)
It doesn’t matter what order the letters in a sentence are as long as the first and last letter are the same, letters in the middle don’t make much difference.
Case Alteration, Perea et al., (2015)
when the there are inconsistencies in the case in a word (e.g. case alternation vs. cAsE aLtErNaTiOn) can affect reading e.g. the word BeAsT could read as beast or BAT
do different fonts have advantages? Moret-Tatay et al, (2011)
Do serifs provide an advantage in the recognition of written words?
- 160 (5 and 8-letters) words and 160 nonwords.
- Lexical decision task.
- Pure and mixed blocks
- Results: Sans serif words 19 ms faster than words written in serif font (effect found for 80% of the participants).
Is orthographic processing unique to humans?
- Grainger et al., (2012) looked at orthographic processing in Baboons
- Baboons trained to discriminate English words from nonwords
1. test computers
2. free access 25x30 m enclosure with various climbing structures and stories and housing areas
3. word-nonword classification. single printed stimulus (word or nonword), binary choice (accuracu measured), blank screen and reward if correct - results show that baboons were able to differentiate between words and nonwords
Orthographic input coding
- Invariant letter and word recognition: a = A ≠ b
- How to distinguish between anagrams such as: LEAP PALE PEAL PLEA
what is the interactive activation model?
- Representations: visual features, letters, and words.
- There are pools of representations for each letter position at the feature and letter levels.
- Inhibition and excitation connections between levels.
- Within-level inhibition (lateral inhibition) at the word level
- Strength (weights) of excitation and inhibition are fixed.
- Word nodes at the word level have resting-level activations that reflect word frequencies.
- At each time step the activation of each node in the network is calculated based on the amount of excitation and inhibition it receives from other nodes.
- Word recognition is assumed to take place when a node reaches a certain amount of activation (word recognition threshold)
what are the types of position specific letter coding?
- Interactive Activation (IA) model (McClelland & Rumelhart, 1981; Rumelhart & McClelland, 1982)
- Dual-Route Cascaded (DRC) model (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001)
- Multiple Read-Out Model (Grainger & Jacobs, 1996)
