Cognitive Science


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Cognitive Science. Home Academics Majors Cognitive Science. Cognitive Science How does the mind work? Real World Outcomes:. Department Website Detailed Major Requirements. Advisor Name:. Advising Center. Advisor Email:.

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Interest Groups:. Biological and Life Sciences. Health Professions. Social Sciences. Theoretical neuroscience is the attempt to develop mathematical and computational theories and models of the structures and processes of the brains of humans and other animals. It differs from connectionism in trying to be more biologically accurate by modeling the behavior of large numbers of realistic neurons organized into functionally significant brain areas. Computational models of the brain have become biologically richer, both with respect to employing more realistic neurons such as ones that spike and have chemical pathways, and with respect to simulating the interactions among different areas of the brain such as the hippocampus and the cortex.

These models are not strictly an alternative to computational accounts in terms of logic, rules, concepts, analogies, images, and connections, but should mesh with them and show how mental functioning can be performed at the neural level. The explanatory schema for theoretical neuroscience is:. From the perspective of theoretical neuroscience, mental representations are patterns of neural activity, and inference is transformation of such patterns.

Bayesian models are prominent in cognitive science, with applications to such psychological phenomena as learning, vision, motor control, language, and social cognition. They have also had effective applications in robotics. The explanatory schema for Bayesian cognition is:.

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Although Bayesian methods have had impressive applications to a wide range of phenomena, their psychological plausibility is debatable because of assumptions about optimality and computations based on probability theory. Artificial intelligence has been a central part of cognitive since the s, and the most dramatic recent advances in AI have come from the approach of deep learning, which has produced major breakthroughs in fields that include game playing, object recognition, and translation.

Deep learning builds on ideas from connectionism and theoretical neuroscience, but uses neural networks with more layers and improved algorithms, benefitting from faster computers and large data bases of examples. Ideas from deep learning are spreading back into neuroscience and also beginning to influence research in cognitive psychology. The explanatory schema for deep learning is:. Although deep learning has produced dramatic improvements in some AI systems, it is not clear how it can be applied to aspects of human thought that include imagery, emotion, and analogy.

Some philosophy, in particular naturalistic philosophy of mind, is part of cognitive science. But the interdisciplinary field of cognitive science is relevant to philosophy in several ways. First, the psychological, computational, and other results of cognitive science investigations have important potential applications to traditional philosophical problems in epistemology, metaphysics, and ethics. Second, cognitive science can serve as an object of philosophical critique, particularly concerning the central assumption that thinking is representational and computational.

Third and more constructively, cognitive science can be taken as an object of investigation in the philosophy of science, generating reflections on the methodology and presuppositions of the enterprise. Much philosophical research today is naturalistic, treating philosophical investigations as continuous with empirical work in fields such as psychology.

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From a naturalistic perspective, philosophy of mind is closely allied with theoretical and experimental work in cognitive science. Metaphysical conclusions about the nature of mind are to be reached, not by a priori speculation, but by informed reflection on scientific developments in fields such as psychology, neuroscience, and computer science. Similarly, epistemology is not a stand-alone conceptual exercise, but depends on and benefits from scientific findings concerning mental structures and learning procedures.

Ethics can benefit by using greater understanding of the psychology of moral thinking to bear on ethical questions such as the nature of deliberations concerning right and wrong. Here are some philosophical problems to which ongoing developments in cognitive science are highly relevant. Links are provided to other relevant articles in this Encyclopedia. Additional philosophical problems arise from examining the presuppositions of current approaches to cognitive science.

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The claim that human minds work by representation and computation is an empirical conjecture and might be wrong. Although the computational-representational approach to cognitive science has been successful in explaining many aspects of human problem solving, learning, and language use, some philosophical critics have claimed that this approach is fundamentally mistaken. Critics of cognitive science have offered such challenges as:. The first five challenges are increasingly addressed by advances that explain emotions, consciousness, action, and embodiment in terms of neural mechanisms.

The social challenge is being met by the development of computational models of interacting agents. Cognitive science raises many interesting methodological questions that are worthy of investigation by philosophers of science. What is the nature of representation? What role do computational models play in the development of cognitive theories? What is the relation among apparently competing accounts of mind involving symbolic processing, neural networks, and dynamical systems?

What is the relation among the various fields of cognitive science such as psychology, linguistics, and neuroscience? Are psychological phenomena subject to reductionist explanations via neuroscience? Are levels of explanation best characterized in terms of ontological levels molecular, neural, psychological, social or methodological ones computational, algorithmic, physical?

The increasing prominence of neural explanations in cognitive, social, developmental, and clinical psychology raises important philosophical questions about explanation and reduction. Anti-reductionism, according to which psychological explanations are completely independent of neurological ones, is becoming increasingly implausible, but it remains controversial to what extent psychology can be reduced to neuroscience and molecular biology.

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Crucial to answering questions about the nature of reduction are answers to questions about the nature of explanation. Explanations in psychology, neuroscience, and biology in general are plausibly viewed as descriptions of mechanisms , which are combinations of connected parts that interact to produce regular changes. In psychological explanations, the parts are mental representations that interact by computational procedures to produce new representations.


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  • In neuroscientific explanations, the parts are neural populations that interact by electrochemical processes to produce new neural activity that leads to actions. If progress in theoretical neuroscience continues, it should become possible to tie psychological to neurological explanations by showing how mental representations such as concepts are constituted by activities in neural populations, and how computational procedures such as spreading activation among concepts are carried out by neural processes.

    The increasing integration of cognitive psychology with neuroscience provides evidence for the mind-brain identity theory according to which mental processes are neural, representational, and computational. Other philosophers dispute such identification on the grounds that minds are embodied in biological systems and extended into the world.

    However, moderate claims about embodiment are consistent with the identity theory because brain representations operate in several modalities e. Another materialist alternative to mind-brain identity comes from recognizing that explanations of mind employ molecular and social mechanisms as well as neural and representational ones. History 2. Methods 3. Representation and Computation 4.

    Theoretical Approaches 4. Philosophical Relevance 5. History Attempts to understand the mind and its operation go back at least to the Ancient Greeks, when philosophers such as Plato and Aristotle tried to explain the nature of human knowledge. Methods Cognitive science has unifying theoretical ideas, but we have to appreciate the diversity of outlooks and methods that researchers in different fields bring to the study of mind and intelligence.

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