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Description of the Module Subject Name Linguistics Paper Name Psycho-Neurolinguistics Module Name /Title Module#20-Modularity Vs Description of the module Subject name Linguistics Paper name Psycho-neurolinguistics Module name /Title Module#20-Modularity vs. Connectionism Pre-requisites Modules 1-20 psycholinguistics Objectives To explain the concepts of modularity and connectionism in relation to speech and language processing Key words Bottom-up Vs. Topdown processing, Connectionism, constructivism, Mentalism, Nativism, 1. Introduction According to classical cognitive science, cognition is (1) computational, meaning that the mind /brain deals with real and intentional mental states that are symbolic representations; (2) symbols and rules interact with each other; (3) not only mind „holds‟ these symbolic representations but that it‟s processes are explainable as rule governed interactions between representations. Considerable debate exists today on how language acquisition and its use could be best explained by appeal to mental representations of linguistic rules, and concepts as entities independent of linguistic experience. Nativists like Chomsky have held that at least some mental representations are endogenously specified (innate), and therefore present before any learning or experience has taken place. Thus, concepts such as mentalism, nativism, and modularity are interconnected. The issue of modularity has dominated much of the research aimed at finding answers to questions such as, how language is represented in the brain, how children acquire and use it, and how brain damage interferes with language knowledge and use, and therefore, it has had considerable influence on the theories / models and applications in disciplines as varied as Psycholinguistics, neurolinguistics, developmental psychology, neuropsychology, and articficial intelligence. As discussed in the module on innateness, synchrony of language learning milestones, the speed with which we are able to perform linguistic computations to parse complex sentences in order to comprehend their meanings, and the fact that brain damage can selectively spare / impair language processes are some of the arguments offered to defend modularity of the language faculty. Linguistic theories of generative persuasion propounded by Noam Chomsky presuppose modularity. Chomsky viewed language as an autonomous system insulated from other cognitive systems. According to him, speech is a manifestation of human mind, the roots of which lie in the innate knowledge in the form of modules containing mental representations. Within such symbolic or modular perspective, mind is like a digital computational device separable from the environment, and it manipulates internal amodal symbols according to logical rules. Modular theorists like Jerry Fodor (1983) argued that knowledge about words never influences perception of phonemes involving bottom-up processing. The initial stages of word or sentence comprehension for instance are not influenced by knowledge representations from higher levels (top-down processing). It is only after initial linguistic processing in specialized modules that information about context or other factors from the real world might play a role in the interpretation of meanings. Connectionist models on the other hand are based primarily on learning theories in Psychology and concepts such as neural net works in computer science. These models (some are referred to as Parallel Distributed Processing or PDP models) challenge the idea that mental processes are basically algorithmic symbol manipulations. Connectionist models such as those proposed by Rumelhart and McClelland propose existence of processing units akin to neurons with trainable connections (like synapses) that have sub-symbolic numeric representations. The analysis doesn‟t stop with computational and algorithmic levels (as envisaged by modular theories) but go on to include implementation level as well. Feedback from environment can influence learning. The process of visual word recognition within a connectionist framework for instance involves a network in which there are at least three different hierarchically organized units such as feature detectors, letter detectors and word detectors. By adjusting weights to the connections between the units, one can induce training. Most excited units send inhibitory connections to dampen activity in competing units. Within the connectionist frameworks, frequency / probability of occurrence of words, linguistic context and world knowledge (top-down processing) play a role in the comprehension of the meaning of words. An attempt is made in this unit to synthesize current thinking about modularity and connectionism with a view to provide frameworks for characterizing adult language disorders in the subsequent units. Since there is no consensus among cognitive scientists about the terminology relating to the notions, modularity or module, Seok (2006) discussed different uses of the term, „modularity‟ and listed some the defining properties and features of modular cognitive architectures. 2. Types of Modularity Anatomical modularity: Module is conceived as a specific anatomical structure (group of cells) in the brain, a typical neuroscience perspective Design modularity: Modularity is seen as a specific design principle, the way components in a system are organized. Individual assemblies with distinct functions come together to form a system as in vision research Neuropsychological modularity: Modules are functionally independent units in the brain that can dissociate; they have independent cognitive functions with dedicated groups of brain cells. Aphasiological research makes use of this view of modularity Chomskian modularity: Modularity according to Chomsky is a special property of an organized body of symbolic knowledge, what he called competence. Computational modularity or the Fodorian modularity: Mind is treated as a computational system that processes information by manipulating signals that represent things in the external world. It refers to specific mode of information processing. Developmental modularity: A module develops along a specific pre-determined path following domain specific developmental trajectory. Modularity within this view is the endpoint of active interaction between the mind and its environment, what Karmiloff- Smith calls the process of modularization endorsed by notions such as neuroconstructivism and emergentism. Darwinian or evolutionary modularity: sees modularity as a property of an innate and domain specific cognitive mechanism that comes to exist by natural selection, a popular view in evolutionary psychology. According to Seok, there are at least five defining properties of modular cognitive systems, viz., physical structure, cognitive function performed, type of computation, type of information handled, and development. These features interact with the below listed characteristic features of modularity endorsed by many theorists including Fodor (1983): Domain Specificity (modules are dedicated to processing of single information type) Mandatoriness (modules operate reflexively) Limited central access (modules have limited to mental representations at higher levels) Speed (modules process data very fast) Information Encapsulation(It is difficult to interfere with the inner workings of a module) Fixed neural architecture (modules are innately specified and hard-wired) Specific breakdown patterns (modules breakdown in a characteristic & predictable way) Specific ontogeny (modules develop in a specific sequence) According to Fodor, every cognitive system has three tiers: the first level is the transducer level that transforms environmental signals into a form that can be used by the organism; at the second level the input systems perform basic recognition and description functions; the third and final level there are higher cognitive functions (e.g. thinking, reasoning, problem solving etc) performed by central systems. In Fodor‟s view only input (vertical) systems in the second tier are modular and the higher level cognitive processes (the third level) are not modular. These were termed, horizontal or domain-general systems which are not content-specific like the vertical modules. Dimensions What do they specify? Features Physical structure How a cognitive system is physically Fixed neural architecture, specific assembled breakdown pattern Cognitive function What a cognitive system does Functional specialization Computation The way a cognitive Speed, mandatoriness, limited central access, information system processes information encapsulation Information The type of information employed in Domain specificity carrying out its cognitive function Development How a cognitive system comes to exists Specific development pattern, specific ontogeny Table 1: Dimensions and features of modularity Thus, object perception might be modular in that it doesn‟t need to connect with the language module or music module and so on. The higher level processes on the other hand can have access to all kinds of information contained in the entire cognitive system when performing a given operation. One of the best evidence of modularity, in particular, for the features of information encapsulation and mandatoriness cited by many researchers in the field of vision is the Muller-Lyer illusion (see figure-1 below). Even when we know that the two vertical lines are the same length, we continue to perceive the first (the left side) line as longer. The visual system is making an inference that goes beyond the stimulus in interpreting the input. Such powerful inferences
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