READING
1. READING MODEL
The Logogen Model Proposed by Morton (1969, 1970), the Logogen model
assumes units called logogens which are used to understand words that are heard
and read. Logogens are specialized recognition units that are used for word
recognition. Logogen is from the Greek λόγος (logos, word) and γένος (genos, origin).
So, every word we know has its own logogen which contains phonemic and graphemic
information about that word. As we encounter a word, the logogen for that word
accumulates activation until a given threshold is reached upon which the word is
recognized. An important issue to remember is that the logogen itself doesn’t contain
the word. Rather, it contains information that can be used to retrieve the word.
Accessing words is direct and parallel for all words. Each logogen has a resting
activation level. As it receives more evidence that corresponds to its word, this
activation level increases up to a threshold. For example, if the input contains the
grapheme then all logogens containing that visual input get an increase in activation.
Once enough graphemes are there to fully activate the logogen it fires and word
recognition occurs. The model is particularly good as including contextual information
in recognizing words. One of the problems with this model was that it equated visual
and auditory input for a word as using the same logogen process. A prediction of this
model would be that a spoken prime should facilitate a written word just as much as a
visual prime. However, experimental evidence contradicted this prediction (Winnick &
Daniel, 1970). Following his own observation that confirms these findings, Morton
divided the model into different sets of logogens.
While the logogen model is quite successful in explaining word recognition in
terms of semantics, there are some limitations to this model. There have been
challenges to the existence of the logogen as a unit of recognition. Given that different
pathways process information on the way to word recognition, is it really necessary to
have such centralized units? The model’s limited scope for word recognition that
ignores innate syntactic rules and grammatical construction is also a limitation.
1.1 Interactive Activation Model
McClelland and Rumelhart (1981) and Rumelhart and McClelland (1982)
developed the Interactive activation and competition (IAC) model. The model
accounted for word context effects. This means that letters are easier to
recognize if they are in words rather than as isolated letters (also known as the
word superiority effect). As seen in Figure 8.3, the model consists of three
levels: visual feature units, indivudla letter units, and word units. Each unit is
connected to units in the level immediately before and after it with connections
that are excitatory (if appropriate) or inhibitory (if inappropriate). For example,
the vertical line feature excites, and but combined with the horizontal line
feature, it only excites . All the letter units in turn excite words that contain them,
but the words that do not contain the letters act as inhibitory signals in the
opposite direction. Once enough letter units have accumulated activation of the
word , then that word is recognized. The inhibition of units lower down the model
if a positive recognition is not made accounts for the word superiority effect.
Obviously, if no words are activated (if the letter is on its own), they will act as
inhibitors in letter recognition. However, if the letter is within a word, then the
words facilitate recognition.
1.2 Seidenberg and McClelland’s Model of Reading
Seidenberg and McClelland (1989) proposed a model (also known as
SM) that accounts for letter recognition and pronunciation. Reading and
speaking involve three features: orthographic, semantic and phonological
coding. In the SM model, these features are connected with feedback
connections. As seen in Figure 8.2, the model is captured in a triangular shape.
There is a route from orthography to phonology via semantics. However, there
are no routes for grapheme-to-phonemes correspondence. The model has
three levels containing a number of simple units. These are the input, hidden
and output layers. Each unit has an activation level and is connected to other
units by weighted connections which can excite or inhibit activation. The main
feature of these connections is that they are not set by anyone, but learned
through back-propagation. This is an algorithmic method whereby the
discrepancy between the actual output and the desired output is reduced by
changing the weights between the connections. This model also does not have
lexical entries for individual words. They are connections between phoneme or
grapheme units.
Coltheart et al. (1993) criticized the SM model for not accounting for how
people read exception words, and non-words. They also stated that the model
doesn’t account for how people perform visual lexical decision tasks as well as
failing to account for data from reading disorders such as dyslexia. Forster
(1994) pointed out that just because a model can successfully replicate reading
data using connectionist modelling doesn’t mean that it reflects how reading
occurs in human beings. Norris (1994) argued that the model doesn’t reflect
how readers can shift strategically between lexical and non-lexical information
when reading.
1.3 Dual-Route Model
The dual-route model is perhaps the most widely studied model for
reading aloud. It assumes two separate mechanisms for reading: the lexical
route and the non-lexical route. This is like looking for words in a dictionary.
When a reader sees a word, they access the word in their mental lexicon and
retrieve information about its meaning and pronunciation. However, this route
cannot provide any help if you come across a new word for which there is not
entry in the mental lexicon. For this you would need to use the non-lexical route.
The non-lexical or sub-lexical route is a mechanism for decoding novel words
using existing grapheme-to-phoneme rules in a language. This mechanism
operates through the identification of a word’s constituent parts (such as
graphemes) and applying linguistic rules to decoding. For example, the
grapheme would be pronounced as /tʃ/ in English. This route can be used to
read non-words or regular words (that have regular spelling).
2. READING DISORDER
Reading models can often be informed by data from people with reading
disorders. In studying such disorders, we must differentiate between acquired
disorders (those that arise from brain trauma, stroke or injury), and developmental
disorders (those that may arise from disruption to the developmental of reading
faculties). These dyslexias generally result from injury to the left hemisphere. If the
dual-route model is accurately capturing the reading process, then we should be able
to find patients who have damaged one route without impairing the other. The
evidence for such double disassociations in reading aloud task shows strong support
for dual-route models.
2.1 Surface Dyslexia
Patients with surface dyslexia have an impairment in reading irregular
words. For example, they would have difficulty reading “quay” but can read
regularly spelled words such as “dog.” They often over-regularize when reading
aloud but can read regular words and regularly spelled non-words easily. In
other words, the dual-route model would predict that their lexical route is
impaired while the nonlexical route is intact.
2.2 Phonological Dyslexia
Patients with phonological dyslexia are unable to read regularly spelled
nonwords. However, they are able to read equivalent words. This suggests an
impairment with the non-lexical (grapheme-tophoneme) route.
2.3 Deep Dyslexia
Deep dyslexics often resemble phonological dyslexics in that these
patients have difficulty with nonwords. However, they also make semantic
errors where they produce words that are related in meaning with the word they
were supposed to read. Coltheart (1980) lists 12 characteristics of this disorder:
1. Semantic errors
2. Visual errors
3. Substitution of incorrect function words
4. Derivational errors
5. Inability to pronounce non-words
6. Imageability effect
7. Ability to read nouns more easily than adjectives
8. Ability to read adjectives more easily than verbs
9. Ability to read content words more easily than function words
10. Writing impairment
11. Impaired auditory short-term memory
12. Context-dependant reading ability
2.4 Reading in Other Languages
Languages with transparent scripts, such as Italian and Spanish, exhibit
phonological and deep dyslexia but not surface dyslexia (Patterson, Marshall,
& Coltheart, 1985a, 1985b). However, interesting observations can be made in
language that have more than one script. Take Japanese, for instance, which
has a syllabary (kana) and a logographic script (kanji). In the latter, no
information is available about pronunciation as the symbols stand for the word.
As seen in Figure 8.5, while kana can allow for non-lexical grapheme-to-
phoneme processing, kanji would only access the lexical route. Therefore, a
type of surface dyslexia is found in Japanese where patients cannot read kanji
but can process kana. Phonological dyslexia in Japanese results in patients
being able to read both kana and kanji but bot able to process non-words written
in kana. This suggests that while the neuropsychological mechanisms for
reading are common to all human beings, there may be contextual differences
brought out by the features inherent in a particular language’s writing system.
