19,131 research outputs found
Computational Creativity
In: Encyclopedia of Systems Biology, W. Dubitzky, O. Wolkenhauer, K-H Cho, H. Yokota (Eds.), Springer 2011Understanding brain processes behind creativity and modeling them using computational means is one of the grand challenges for systems biology. Computational creativity is a new field, inspired by cognitive psychology and neuroscience. In many respects human-level intelligence is far beyond what artificial intelligence can provide now, especially in regard to the high-level functions, involving thinking, reasoning, planning and the use of language. Intuition, insight, imagery and creativity are important aspects of all these functions
Neuron-Glial Interactions
Although lagging behind classical computational neuroscience, theoretical and
computational approaches are beginning to emerge to characterize different
aspects of neuron-glial interactions. This chapter aims to provide essential
knowledge on neuron-glial interactions in the mammalian brain, leveraging on
computational studies that focus on structure (anatomy) and function
(physiology) of such interactions in the healthy brain. Although our
understanding of the need of neuron-glial interactions in the brain is still at
its infancy, being mostly based on predictions that await for experimental
validation, simple general modeling arguments borrowed from control theory are
introduced to support the importance of including such interactions in
traditional neuron-based modeling paradigms.Comment: 43 pages, 2 figures, 1 table. Accepted for publication in the
"Encyclopedia of Computational Neuroscience," D. Jaeger and R. Jung eds.,
Springer-Verlag New York, 2020 (2nd edition
Creativity and the Brain
Neurocognitive approach to higher cognitive functions that bridges the gap between psychological and neural level of description is introduced. Relevant facts about the brain, working memory and representation of symbols in the brain are summarized. Putative brain processes responsible for problem solving, intuition, skill learning and automatization are described. The role of non-dominant brain hemisphere in solving problems requiring insight is conjectured. Two factors seem to be essential for creativity: imagination constrained by experience, and filtering that selects most interesting solutions. Experiments with paired words association are analyzed in details and evidence for stochastic resonance effects is found. Brain activity in the process of invention of novel words is proposed as the simplest way to understand creativity using experimental and computational means. Perspectives on computational models of creativity are discussed
Formulating Consciousness: A Comparative Analysis of Searle’s and Dennett’s Theory of Consciousness
This research will argue about which theory of mind between
Searle’s and Dennett’s can better explain human consciousness. Initially,
distinctions between dualism and materialism will be discussed ranging from
substance dualism, property dualism, physicalism, and functionalism. In this
part, the main issue that is tackled in various theories of mind is revealed. It
is the missing connection between input stimulus (neuronal reactions) and
behavioral disposition: consciousness. Then, the discussion will be more
specific on Searle’s biological naturalism and Dennett’s multiple drafts
model as the two attempted to answer the issue. The differences between
them will be highlighted and will be analyzed according to their relation to
their roots: dualism and materialism. The two theories will be examined on
how each answer the questions on consciousness
Outline of a new approach to the nature of mind
I propose a new approach to the constitutive problem of psychology ‘what is mind?’ The first section introduces modifications of the received scope, methodology, and evaluation criteria of unified theories of cognition in accordance with the requirements of evolutionary compatibility and of a mature science. The second section outlines the proposed theory. Its first part provides empirically verifiable conditions delineating the class of meaningful neural formations and modifies accordingly the traditional conceptions of meaning, concept and thinking. This analysis is part of a theory of communication in terms of inter-level systems of primitives that proposes the communication-understanding principle as a psychological invariance. It unifies a substantial amount of research by systematizing the notions of meaning, thinking, concept, belief, communication, and understanding and leads to a minimum vocabulary for this core system of mental phenomena. Its second part argues that written human language is the key characteristic of the artificially natural human mind. Overall, the theory both supports Darwin’s continuity hypothesis and proposes that the mental gap is within our own species
Robot Consciousness: Physics and Metaphysics Here and Abroad
Interest has been renewed in the study of consciousness, both theoretical and applied, following developments in 20th and early 21st-century logic, metamathematics, computer science, and the brain sciences. In this evolving narrative, I explore several theoretical questions about the types of artificial intelligence and offer several conjectures about how they affect possible future developments in this exceptionally transformative field of research. I also address the practical significance of the advances in artificial intelligence in view of the cautions issued by prominent scientists, politicians, and ethicists about the possible dangers of such sufficiently advanced general intelligence, including by implication the search for extraterrestrial intelligence
A Deflationary Account of Mental Representation
Among the cognitive capacities of evolved creatures is the capacity to represent. Theories in cognitive neuroscience typically explain our manifest representational capacities by positing internal representations, but there is little agreement about how these representations function, especially with the relatively recent proliferation of connectionist, dynamical, embodied, and enactive approaches to cognition. In this talk I sketch an account of the nature and function of representation in cognitive neuroscience that couples a realist construal of representational vehicles with a pragmatic account of mental content. I call the resulting package a deflationary account of mental representation and I argue that it avoids the problems that afflict competing accounts
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