Application Of Models In Cld.docx

APPLICATION OF MODELS IN CHILD LANGUAGE DISORDERS CONTENTS: 1. 2. 3. 4. 5.

Introduction Duel route cascaded model The Hierarchical model The connectionist models Article

INTRODUCTION Language processing refers to the way humans use words to communicate ideas and feelings, and how such communications are processed and understood. Thus, it is how the brain creates and understands language (Tomesello, 2004). Traditional approaches to language processing have been based on explicit, discrete representations that can be accessed, retrieved or manipulated by different means. Researchers have sought to discover exactly what kinds of information-processing activities go on in our minds when we read; to discover what the structure and organization is of the cognitive system skilled readers have acquired from learning to read. Little is known about how the most elaborate aspects of this system work, but much has been learned about its basic building blocks such as letter identification, visual word recognition and knowledge of letter-sound rules. These have been explained over the years by various models of language processing. With growing technology, most of these models are now computational i.e., they can be run using written codes on computer systems to evidence the theorization of how language processing occurs in the human brain. A disruption in language processing could lead to various reading, writing or spoken language impairment. Hence to understand such disorders, a knowledge of language processing is important. The three most widely accepted models proposed to explain language processing are: 1. Duel route cascaded model 2. The Hierarchical model 3. The connectionist models I. DUEL ROUTE CASCADED MODEL (DRC)

1.1 DCM The DRC is a computational model of reading that was proposed early in the 1970s and developed extensively by Coltheart et.al in 1990s. It attempted to explain how skilled readers perform certain basic reading tasks. Cognitive psychology views reading as an information processing activity: reading aloud is transforming print into speech, and reading comprehension is transforming print into meaning. Hence there are two separate mental mechanisms/Cognitive routes involved, both of which contribute to the output resulting in the pronunciation of a written stimulus. One of the two mechanisms, termed the lexical route, is the process whereby skilled readers can recognize known words by sight alone, through a "dictionary" lookup procedure. According to this model, every word a reader has learned is represented in a mental database of words and their pronunciations that resembles a dictionary, or internal lexicon. When a skilled reader sees and visually recognizes a written word, he or she is then able to access the dictionary entry for the word and retrieve the information about its pronunciation. The internal lexicon encompasses every learned word, even irregular words like 'colonel' or 'pint' that don't follow letter-to-sound rules. This route doesn't enable reading of nonwords or novel words that are not present in the particular individual’s mental lexicon.

Visual Recognition

Access Internal Lexicon

Retrieve Pronunciation

The non-lexical or sub-lexical route, on the other hand, is the process whereby the reader can "sound out" a written word. This is done by identifying the word's constituent parts

(letters, phonemes, graphemes) and, applying knowledge of how these parts are associated with each other. This mechanism applies the phoneme-grapheme correspondence rule system which allows the reader to actively build a phonological representation and read the word aloud. The non-lexical route allows the correct reading of nonwords as well as regular words that follow spelling-sound rules, but not exception/irregular words. The dual-route hypothesis of reading helps explain and understand various facts about normal and abnormal reading abilities. Two ways in which the units of different layers interact: • One is through inhibition, where the activation of a unit makes it more difficult for the activation of other units to rise. • Other is through excitation, where the activation of a unit contributes to the activation of other units. • The lexical route is faster than the non-lexical route (Colhert.et.al, 2001)

CLINICAL APPLICATION: Reading Disorders:  Children with reading disorders rely primarily on the non-lexical route while reading  Research shows that children can decode non-words, letter by letter, accurately but with slow speed.  Children with reading disorders (RD) have both slow reading speeds and impaired lexical routes, there are suggestions that the same processes are involved in fast naming of words. Developmental Surface Dyslexia:  Damage to the Left temporal/parietal lobe in a previously literate person (Sherman, 2000)  Pronunciation errors that indicate impairment of the lexical route.  Cannot recognize words as a single unit  Patients can accurately read words and nonwords that comply with the letter-sound rules of the sub-lexical system but mistakenly pronounce irregular words. Ex: No silent “t” in “Listen” Developmental Deep/Phonological Dyslexia:  Inability to read non-words aloud and identify the sounds of single letters.

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Patients can read and correctly pronounce words (as a whole), regardless of length, meaning, or how common they are, as long as they are stored in memory. Caused by damage in the non-lexical route, while the lexical route, that allows reading familiar words, remains intact.

II. HIERARCHICAL MODEL Most modern models of semantic memory are predicated on the idea that words are arranged in networks and that concepts are linked on a variety of levels. The Hierarchical model attempts to explain how words are associated with each other and how we access words in the mental lexicon.

2.1 Hierarchical Model a. Collins and Quillian (1969) proposed that semantic knowledge is underpinned by a set of nodes, each representing a specific feature or concept, which are all connected to one another. Nodes that related in some way, such as often coincident in time, are more strongly connected. They suggested three basic ideas: 1. Information is stored in categories. 2. Categories are logically related to each other in a hierarchy: Broad categories of information, like “animal”, are subdivided into narrower categories, like “bird” and “fish”, which in turn are subdivided into still narrower categories. 3. “Cognitive Economy”: Information stored at one level of the hierarchy is not repeated at other levels. A fact is stored at the highest level to which it applies. For example, the fact that birds breathe is stored in the ANIMAL category, not the BIRD category.

b. Collins and Loftus (1975) then refined this model. They weighted the connections to explain the typicality effect-the finding that typical instantiations of a category are recognized more rapidly. Nevertheless, this model cannot explain a finding, observed by Glass, Holyoak and Kiger (1979), that individuals can readily respond to questions that are patently false, like "Is a chicken a meteor". In this instance, the nodes are far apart, but the responses are rapid. Later, more sophisticated network models were developed (Cravo & Martins, 1993). These models are similar to the propositions proposed by Collins and Loftus (1975). However, each node might represent some other element, like a concept or feature, rather than merely a word. Furthermore, the links or connections can represent a variety of relationships, not just hierarchy. c. Lexical network model (Bock and Levelt, 1994,1997)

2.2 LNM (Concept, Lemma and Lexeme) This is a dual-stage access model is proposed in which the first stage involves the selection of semantically and syntactically specified, modality-specific lexical forms, and the second stage involves the selection of specific phonological (orthographic) content for the selected lexemes. When we produce a word, we are essentially turning our thoughts into sounds, a process known as lexicalisation. In many psycholinguistic models this is considered to be at least a twostage process. The first stage deals with semantics and syntax (concept); the result of the first stage is an abstract notion of a word that represents a meaning and contains information about how the word can be used in a sentence. It does not, however, contain information about how the word is pronounced. The second stage deals with the phonology of the word; it attaches information about the sounds that will have to be uttered. The result of the first stage is the lemma in this model; the result of the second stage is referred to as the lexeme.

d. Revised Hierarchical Model (Kroll and Stewart, 1995)

2.3 RHM The Revised Hierarchical Model (Kroll and Stewart, 1994), was initially proposed to account for observed asymmetries in translation performance by late bilinguals who acquired the second language (L2) after early childhood and their first language (L1) remained the dominant language. The RHM effectively merged the alternative models of word association and concept mediation described into a single developmental model. It explained longer translation latencies from L1 to L2 (forward translation) than from L2 to L1 (backward translation) as an underlying asymmetry in the strength of the links between words and concepts in each of the bilingual's languages. The L1 was hypothesized to have privileged access to meaning, whereas the L2 was thought to be more likely to require mediation via the L1 translation equivalent until the bilingual acquired sufficient skill in the L2 to access meaning directly. On this account, translation from L2 to L1 could be accomplished lexically, without semantic access, if the L2 word enabled lexically mediated retrieval of the translation. In contrast, L1 to L2 translation would necessarily be semantically mediated because of the strong L1 link to meaning.

CLINICAL APPLICATION: Cromer's (1983) claimed that children with language impairments have a hierarchical planning deficit that affects language as well as performance on complex construction tasks.

SLI (Kamhi et.al,1995) •Delayed language skills (Cromer,1981) •Bilinguals with CLD (Ramos et.al,1985) 2.4 Disorders as a result of hierarchical planning deficits

III. THE CONNECTIONIST MODELS: Traditional approaches are explicit and discrete representations that are difficult to learn from a reasonable linguistic environment. Structure of language is highly complex ranging from acoustic processing to semantic analysis with a set of symbolic rules. Language processing operations operate extremely rapidly, requiring a highly parallel, co-operative style of computation. Thus, language processing appears to represent a very difficult challenge for neural network modelling. Hence the connectionist model: 

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Attempts to help bridge the gulf between psycholinguistics and neuroscience and note what could be learned from the environment in the absence of detailed innate knowledge. Consist of several interconnected neurons like processing units modified by learning association between input (Stimulus) and output (response). Is a distributed model which assumes that information is not localized in specific nodes and thus rely on patterns of activation across models in the network, particularly through inter- connections between nodes as in real biological synapses. Attempts to understand how the neural computation is conducted in the brain by simulating the cognitive and neural processes of language, memory and learning. Theorizes that performance is not an imperfect reflection of some abstract competence, but rather the behavioral manifestation of the internal representations and processes of actual language users Postulates that there are 3 layers: o Input layer – Receives information from input patterns (eg: representations of alphabetic features) o Output layer – Provides output patterns produced by the network.

(eg: classifications of alphabets acc. to shapes) o Hidden Layer – connect the input and output units (eg: similarities between “O” and “Q”)

a. Bottom Up and Top Down Models (Chater & Christiansen, 2001)

b. Semantic Feature models According to feature models, such as the propositions developed by Smith, Shoben, and Rips (1974), semantic memory is assumed to comprise lists of features for each concept. Hence, according to the perspective, the connections between concepts do not represent the relationships between concepts. Instead, to uncover these relationships, individuals must compare the sets of features between two concepts (see also Meyer, 1970& Rips, 1975). c. Lexical Processing: With respect to lexical processing, three aspects can be considered1. Phonological Development (Plaut & Kello, 1998)  Proposed connectionist framework for phonological development in which phonology was considered as a learned behavior.  As an internal representation that mediates among acoustic, articulatory, and semantic representations in the service of both comprehension and production.  The framework instantiates two key assumptions: 1. The first is that both comprehension and production are subserved by the same underlying phonological representations. 2. The second key assumption is that feedback needed to guide the development of speech production is derived from the comprehension.

3.1 CM for Phonological Development 2. Inflectional morphology  Relationship between inputs and outputs is systematic but admits many exceptions.  Connectionist model - All items co-exist within a single system whose representations reflect the degree of mapping for different items.  Provides explanation for the cross-linguistic differences that occur. 3. Sentence Processing (Rhode & David, 2003)  Parsing : (Structural description of sentence from surface form)  Word prediction : (Predict the likelihood of the appearance of a particular word)  Comprehension : (Representation of the meaning of a sentence)  Prediction : (Mapping from intended meaning to sequences of words/sounds) CLINICAL APPLICATION: Seidenberg and McClelland (1989), reported deficits in: •

Orthographic to phonological representation

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Word processing difficulties

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Transferring from basic to skilled reading

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Pronouncing novel items

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Naming and lexical decision tasks

An impairment in the connectionist system of language processing can be seen in the following disorders:

SLI (Seidenberg et.al, 2003) •Delayed language skills (Trevor Harley, 2007) •Bilinguals with CLD (Li et.al, 2016) •Developmental Dyslexia (Seidenberg et.al, 1999) 3.2 Predominantly with respect to Phonology and Syntax References: 1. Stemmmer, B., & Whitaker, HA, (1998). Handbook of Neurolinguistics. 2. Grosjean & Li (2013). The psycholinguistics of bilingualism. 3. Kroll, Judith F., et al. “The Revised Hierarchical Model: A Critical Review and Assessment.” Bilingualism: Language and Cognition, vol. 13, no. 03, Sept. 2010, pp. 373–381., doi:10.1017/s136672891000009x. 4. Coltheart, Max. “Dual Route and Connectionist Models of Reading: An Overview.” London Review of Education, vol. 4, no. 1, 2006, pp. 5–17., doi:10.1080/13603110600574322. 5. Mark S. Seidenberg, James L. McClelland. “A Distributed, Developmental Model of Word Recognition and Naming.” Psychological Review Copyright 1989 by the American Psychological Association, Ire. 1989, Vol. 96, No. 4, 523-568 6. Allan M. Collins; Elizabeth F. Loftus. “A Spreading-Activation Theory of Semantic Processing.” Psychological Review 1975, Vol. 82, No. 6, 407-428 7. Coltheart, Max; Curtis, Brent; Atkins, Paul; Haller, Micheal. "Models of reading aloud: Dual-route and parallel-distributed-processing approaches." Psychological Review,1993, 100 (4): 589–608.doi:10.1037/0033-295X.100.4.589. 8. Pritchard SC, Coltheart M, Palethorpe S, Castles A (October 2012). "Nonword reading: comparing dual-route cascaded and connectionist dual-process, models with human data". J Exp Psychol Hum Percept Perform.38 (5): 1268–88. doi:10.1037/a0026703. 9. Zorzi, Marco; Houghton, George; Butterworth, Brian. "Two routes or one in reading aloud? A connectionist dual-process model.". Journal of Experimental Psychology: Human Perception and Performance, 1998. 10. Onnis, L., et al. “Connectionist Models of Language Processing.” Encyclopedia of Neuroscience, 2009, pp. 83–90., doi:10.1016/b978-008045046-9.01875-1.