Integration Challenge provides a fresh perspective and a framework for exploring the problem of "cognition" and what it inherently encompasses. The mere notion of progressing from a 2-dimensional model to a 3-dimensional one at face value might not seem that great of a leap when in reality it is an almost infinite one. Such progression gives us an insight into the "volume" it creates, much of which remains empty. The dimensions of this space do not only make up the potentiality but rather in a sense, also set up the rules by which it exists. The hierarchy moving from molecules to neurons, to functional units, to ultimately the brain makes up one of these 3 dimensions. This, in turn, creates the need to use different modalities and methodologies to study, record, and measure all of the respective inputs and outputs, the second dimension. Though an overlap of these investigative techniques exists, the demand for a different way of looking at each step of the hierarchy of organization highlights the breadth of this dimension alone. The things we think and feel, do and say make up the third dimension, it's in one sense the "outcome" of the activity that has undergone within the levels of organization but also stands as an input to that very hierarchy. This entanglement is what the Integration Challenge lays the groundwork for tackling. It is a space within which many hidden bridges and hallways exist, that is to say, drawing associations will ultimately give us a greater insight into the process of cognition.
Bermudez further explores the complexity of the cognitive integration challenge through a level of contrast exhibited by the multiple interdisciplinary approaches in psychology and neuroscience (Bermudez, 2014). On a wider comparison scale, psychology views the aspects of cognition from a particular benchmark that links the entire aspects of cognition. The approach applicable is purely dependent on the behavioral perspective providing an integration of brain functioning and the observable outwards characteristics portrayed by the organism under investigation. Conversely, neuroscience provides a scientific and a more valid approach defining the notion of cognition to a level beyond questioning. The fundamental aspect is the complexity in network existing among the neurons molecules, and that connect at a high cognitive level to a significant low baseline of brain functioning with a drive to communicate a particular behavior as far as cognition is related. In the struggle to bridge the gap identified by the two disciplines, Bermudez asserts the fact that, despite the severity in the unification of cognitive science disciplines, humans tend to exhibit a bigger challenge about abstract conditions, but with laws the opposite is true (Bermudez, 2014).
Secondly, just as the Integration challenge itself presents the notion that the process of cognition is greater than the sum of its parts, so does the mental architecture model for Bermudez. It is a broader, more generalized design in blueprint form of a bare-bones sketch of the brain as a global integrated functional unit. The organization of the mind under that description would lay down a set of "laws" that are mutually inclusive with all of the cognitive architectures that are integrated into it. This also means that a hybrid theory can exist which takes into account different information processing models such as the PSSH in the computational sense and the Connectionist artificial neural networks. The diversity in approach given about the mental and cognitive architecture questions the particular nature of information to be passed by the neural networks. It applies a critical thinking and scientific hypothetical questioning criteria that view the nature or format that a particular element of a cognitive system relays information. At a different level, Bermudez, critically assesses the mode and organization of the mind in determining the ability of the brain to act as a processor of the various strands of information relayed (Bermudez, 2014). The deepened breadth of vision applied at this level provides a unity in the multidisciplinary approaches encountered including the aspect of technology and networks of interrelated functional units.
Thirdly, Bermudez defines the first key question as what the format of information would be for a particular cognitive system. From this question one can assume that this format might be different for different cognitive systems, this is also supported by the second key question which inquires as to how the format of such information transformed. These two questions are important if we are to think about information processing in terms of the modularity theory. Since for domain-general system (i.e., memory and attention), information can be of any kind, which is not the case for a domain-specific system, such as the early perceptive systems (i.e., color and shape). The third question for Bermudez deals with the organization of the mind as an information processor as a whole. Understanding the mental architecture requires that you answer all of the three questions not just the last. The questioning criteria applicable as per the highlighted premises justifies his attempt to unify the entire aspects of the modern cognitive science. He summarized the whole interrogation criteria as a pillar that justifies cognitive science as a single unified field.
The sense of unity come in as a result of the different disciplinary approaches subjected towards the matter. Different disciplines make use of different models in explaining the different dimensions of cognitive science. It ranges from psychology, neuroscience, technology, even those dealing with more complex technical duties. It is the hypothetical questioning criteria which is central and provides a basis through which the challenges affecting the understanding of the linkages between the different elements of cognitive science can be addressed. Through the provision of the answers to the assumptions held regarding systems and theories of the entire conception, understanding of the linkages which is to solve the challenge of design is to be obtained. The convergence and divergence of the many ideas raising challenges to many proponents and experts of science can, therefore, be addressed from a level of understanding(Carruthers, & Chamberlain, 2000).
Fourthly, in cognitive sciences, many challenges arise regarding the question of what concepts can be used as a criterion for the integration of these sciences and information storage, due to its relevance to information processing, is an example of a useful criterion for unifying cognitive sciences. More precisely, for information to be stored, it needs to be broken down into processes governed by formulas (information processing) making the line of distinction between information storage and information processing impossible to clearly define. However, this does not necessarily mean that information storage cannot be used as a unifying criterion in cognitive sciences because information processing is necessary to understand and record in almost all cognitive sciences because it represents one of the start lines in experimental psychology, cognitive neuroscience, behavioral neuroscience, systems neuroscience and molecular neuroscience. An example of a discipline to which information storage is pivotal is the science behind linguistic comprehension. In order to understand a language, an individual must first understand or relate the word (or unit) to a definition (or meaning).
The second dimension to linguistic comprehension, as logician and philosopher Gottlob Frege remarked, is an individual's capability to formulate a logical sentence, which requires interdependent and dependent processes. Most importantly, however, language comprehension requires the breaking down of information in order to comprehend its units (information processing) which then results in information storage. Thus, information processing then helps in the integration of cognitive sciences because it represents a factor that needs to be understood in depth in order to pursue researches and experiments in various fields that are not necessarily similar but that come together as a result of common factors such as information processing. The weakness with this conclusion is that it is almost impossible to absolutely prove that common factors do indeed result in stronger and more binding integration, so it remains a hypothesis. Regarding the consistency and the direction of the information flow, Jerry applies a quote asserting that the degree of confirmation accorded to any assumption is of the characteristics of properties governing the entire belief (Fodor, 1983). The conception of the floated knowledge tends to prove the validity of connectedness that exists in the flow of information. This process covers the entire procedure right from the stimulus detection point, processing, interpretation, storage, and retrieval. It is a system of belief that occurs naturally and cannot be altered easily.
Fifth, cognition, as a whole, must be understood in terms of information processing and how different specialized systems transform information because in all cognitive sciences, the basic understanding of the questions regarding transforming information or processing it is always central. More precisely, to understand cognition, computational analysis marks specific information that a given cognitive system has to begin with and subsequently, the information or data that it must end with. Likely, the algorithmic level, which comes next, shows us how this system has transformed input data or information into output data or information. Also, keeping in mind the two most important models of data processing, which are the physical symbol system hypothesis and the neutrally inspired computing model, it becomes evident that information processing and the ways in which a system transforms information is pivotal in various disciplines. For example, as Chomsky argues, transformational rules are essential to linguistic understanding, which makes it a useful unifying criterion in the linguistic field. Also, in Broadbent's model of selective attention, it is also clear that the question of how a system transforms information using dedicated and specialized systems is equally relevant is important. That said, cognition is a in and of itself a unifying theme in cognitive sciences and the importance of understanding how a system transforms information can thus be said to be a useful criterion for unifying cognitive sciences. The weakness with this conclusion, however, might be the fact that some of the cognitive sciences are less concerned with the question of how systems transform information despite its continued relevance. These different levels of concern thus might hinder the usefulness of this question in unifying cognitive sciences.
On a different aspect, it is imperative to understand the aspect played by the controversies outlined by the various scholars regarding obtaining an in-depth understanding of the entire conception of interdisciplinary unity. Herbert Gintis applies game theory in his experimental and analytical conceptual framework. The notion magnifies the rationale in the use of mathematical laws in games (Rey, 2013). Despite the margin of difficult or costly it may be to abide by the policy, it must be adhered to since it is the tradition. In practical, if all the concerned disciplines maintain ethics, value and close investigation on the aspects of cognition pertaining the issues, could an integration fail? The fact that it is dependent on the cooperation of the experts may act as a stumbling block in meeting the desired objectives.
Finally, like information processing and the question of how a system transforms information, the organi...
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