The Construction of an Integrative, Multi-Level Model for Cognition: The Function of Semantic Networks

Authors
1 -
2 Psychology Faculty
Abstract
Integrated approaches try to connect different constructs in different theories and reinterpret them using a common conceptual framework. In this research, using the concept of processing levels, an integrated, three-level model of the cognitive systems has been proposed. In order to build an integrative framework for systematic interpretation of cognitive tests results, processing levels are divided into three categories of Feature-Oriented, Semantic and Conceptual Level. Since nervous system picks stimuli based on their features, processing levels in this framework is categorized based on the volume of stimuli's information, while Semantic network relates Feature-Oriented and Self-Oriented levels. To assessment the model quantitatively, 207 participants with impaired valance system from psychological clinics in Mashhad were selected by available sampling method. Participants' cognitive function was measured by The Beck Depression Inventory II, Semantic Distance Test, Verbal Fluency Test, Dot Probe Test, Stroop Test, Implicit Association Test and Wisconsin Card Sorting Test. Tets scores were organized as predictive variables, and the three processing levels were considered as mediating variables. The model's structure was analyzed through Structural Equation Model method with an exploratory approach. The best fitted model of data confirmed the three-level division of the research data. In this model, the path coefficient between semantic and conceptual constructions obtained 0.4. These results suggest that Feature-Oriented, Semantic, and Conceptual levels of cognition are differently processed, and cognitive tests results could be compared just in similar level according to the information volume of stimuli used. In previous studies, the relationship between Verbal Fluency test scores and the severity of Beck depressive score has often been controversial. Using the concept of processing levels, the relationship between these two variables have been reinterpreted.
Keywords

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