Cognitive science is the interdisciplinary, scientific study of the mind and its processes.It examines the nature, the tasks, and the functions of cognition (in a broad sense). Cognitive scientists study intelligence and behavior, with a focus on how nervous systems represent, process, and transform information. Mental faculties of concern to cognitive scientists include language, perception, memory, attention, reasoning, and emotion; to understand these faculties, cognitive scientists borrow from fields such as linguistics, psychology, artificial intelligence, philosophy, neuroscience, and anthropology. The typical analysis of cognitive science spans many levels of organization, from learning and decision to logic and planning; from neural circuitry to modular brain organization. One of the fundamental concepts of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures."
Cognitive science is the interdisciplinary study of cognition in humans, animals, and machines. It encompasses the traditional disciplines of psychology, computer science, neuroscience, anthropology, linguistics and philosophy. The goal of cognitive science is to understand the principles of intelligence with the hope that this will lead to better comprehension of the mind and of learning and to develop intelligent devices. The cognitive sciences began as an intellectual movement in the 1950s often referred to as the cognitive revolution.
A central tenet of cognitive science is that a complete understanding of the mind/brain cannot be attained by studying only a single level. An example would be the problem of remembering a phone number and recalling it later. One approach to understanding this process would be to study behavior through direct observation, or naturalistic observation. A person could be presented with a phone number and be asked to recall it after some delay of time; then the accuracy of the response could be measured. Another approach to measure cognitive ability would be to study the firings of individual neurons while a person is trying to remember the phone number. Neither of these experiments on its own would fully explain how the process of remembering a phone number works. Even if the technology to map out every neuron in the brain in real-time were available and it were known when each neuron fired it would still be impossible to know how a particular firing of neurons translates into the observed behavior. Thus an understanding of how these two levels relate to each other is imperative. The Embodied Mind: Cognitive Science and Human Experience says “the new sciences of the mind need to enlarge their horizon to encompass both lived human experience and the possibilities for transformation inherent in human experience.”This can be provided by a functional level account of the process. Studying a particular phenomenon from multiple levels creates a better understanding of the processes that occur in the brain to give rise to a particular behavior. Marr gave a famous description of three levels of analysis:
Cognitive science is an interdisciplinary field with contributors from various fields, including psychology, neuroscience, linguistics, philosophy of mind, computer science, anthropology and biology. Cognitive scientists work collectively in hope of understanding the mind and its interactions with the surrounding world much like other sciences do. The field regards itself as compatible with the physical sciences and uses the scientific method as well as simulation or modeling, often comparing the output of models with aspects of human cognition. Similarly to the field of psychology, there is some doubt whether there is a unified cognitive science, which have led some researchers to prefer 'cognitive sciences' in plural.
Many, but not all, who consider themselves cognitive scientists hold a functionalist view of the mind—the view that mental states and processes should be explained by their function — what they do. According to the multiple realizability account of functionalism, even non-human systems such as robots and computers can be ascribed as having cognition.
The term "cognitive" in "cognitive science" is used for "any kind of mental operation or structure that can be studied in precise terms" (Lakoff and Johnson, 1999). This conceptualization is very broad, and should not be confused with how "cognitive" is used in some traditions of analytic philosophy, where "cognitive" has to do only with formal rules and truth conditional semantics.
The earliest entries for the word "cognitive" in the OED take it to mean roughly "pertaining to the action or process of knowing". The first entry, from 1586, shows the word was at one time used in the context of discussions of Platonic theories of knowledge. Most in cognitive science, however, presumably do not believe their field is the study of anything as certain as the knowledge sought by Plato.[ citation needed ]
Cognitive science is a large field, and covers a wide array of topics on cognition. However, it should be recognized that cognitive science has not always been equally concerned with every topic that might bear relevance to the nature and operation of minds. Among philosophers, classical cognitivists have largely de-emphasized or avoided social and cultural factors, emotion, consciousness, animal cognition, and comparative and evolutionary psychologies. However, with the decline of behaviorism, internal states such as affects and emotions, as well as awareness and covert attention became approachable again. For example, situated and embodied cognition theories take into account the current state of the environment as well as the role of the body in cognition. With the newfound emphasis on information processing, observable behavior was no longer the hallmark of psychological theory, but the modeling or recording of mental states.
Below are some of the main topics that cognitive science is concerned with. This is not an exhaustive list. See List of cognitive science topics for a list of various aspects of the field.
Artificial intelligence (AI) involves the study of cognitive phenomena in machines. One of the practical goals of AI is to implement aspects of human intelligence in computers. Computers are also widely used as a tool with which to study cognitive phenomena. Computational modeling uses simulations to study how human intelligence may be structured. Computational modeling.)(See §
There is some debate in the field as to whether the mind is best viewed as a huge array of small but individually feeble elements (i.e. neurons), or as a collection of higher-level structures such as symbols, schemes, plans, and rules. The former view uses connectionism to study the mind, whereas the latter emphasizes symbolic computations. One way to view the issue is whether it is possible to accurately simulate a human brain on a computer without accurately simulating the neurons that make up the human brain.
Attention is the selection of important information. The human mind is bombarded with millions of stimuli and it must have a way of deciding which of this information to process. Attention is sometimes seen as a spotlight, meaning one can only shine the light on a particular set of information. Experiments that support this metaphor include the dichotic listening task (Cherry, 1957) and studies of inattentional blindness (Mack and Rock, 1998). In the dichotic listening task, subjects are bombarded with two different messages, one in each ear, and told to focus on only one of the messages. At the end of the experiment, when asked about the content of the unattended message, subjects cannot report it.
The ability to learn and understand language is an extremely complex process. Language is acquired within the first few years of life, and all humans under normal circumstances are able to acquire language proficiently. A major driving force in the theoretical linguistic field is discovering the nature that language must have in the abstract in order to be learned in such a fashion. Some of the driving research questions in studying how the brain itself processes language include: (1) To what extent is linguistic knowledge innate or learned?, (2) Why is it more difficult for adults to acquire a second-language than it is for infants to acquire their first-language?, and (3) How are humans able to understand novel sentences?
The study of language processing ranges from the investigation of the sound patterns of speech to the meaning of words and whole sentences. Linguistics often divides language processing into orthography, phonetics, phonology, morphology, syntax, semantics, and pragmatics. Many aspects of language can be studied from each of these components and from their interaction. [ better source needed ]
The study of language processing in cognitive science is closely tied to the field of linguistics. Linguistics was traditionally studied as a part of the humanities, including studies of history, art and literature. In the last fifty years or so, more and more researchers have studied knowledge and use of language as a cognitive phenomenon, the main problems being how knowledge of language can be acquired and used, and what precisely it consists of.Linguists have found that, while humans form sentences in ways apparently governed by very complex systems, they are remarkably unaware of the rules that govern their own speech. Thus linguists must resort to indirect methods to determine what those rules might be, if indeed rules as such exist. In any event, if speech is indeed governed by rules, they appear to be opaque to any conscious consideration.
Learning and development are the processes by which we acquire knowledge and information over time. Infants are born with little or no knowledge (depending on how knowledge is defined), yet they rapidly acquire the ability to use language, walk, and recognize people and objects. Research in learning and development aims to explain the mechanisms by which these processes might take place.
A major question in the study of cognitive development is the extent to which certain abilities are innate or learned. This is often framed in terms of the nature and nurture debate. The nativist view emphasizes that certain features are innate to an organism and are determined by its genetic endowment. The empiricist view, on the other hand, emphasizes that certain abilities are learned from the environment. Although clearly both genetic and environmental input is needed for a child to develop normally, considerable debate remains about how genetic information might guide cognitive development. In the area of language acquisition, for example, some (such as Steven Pinker)have argued that specific information containing universal grammatical rules must be contained in the genes, whereas others (such as Jeffrey Elman and colleagues in Rethinking Innateness) have argued that Pinker's claims are biologically unrealistic. They argue that genes determine the architecture of a learning system, but that specific "facts" about how grammar works can only be learned as a result of experience.
Memory allows us to store information for later retrieval. Memory is often thought of as consisting of both a long-term and short-term store. Long-term memory allows us to store information over prolonged periods (days, weeks, years). We do not yet know the practical limit of long-term memory capacity. Short-term memory allows us to store information over short time scales (seconds or minutes).
Memory is also often grouped into declarative and procedural forms. Declarative memory—grouped into subsets of semantic and episodic forms of memory—refers to our memory for facts and specific knowledge, specific meanings, and specific experiences (e.g. "Are apples food?", or "What did I eat for breakfast four days ago?"). Procedural memory allows us to remember actions and motor sequences (e.g. how to ride a bicycle) and is often dubbed implicit knowledge or memory .
Cognitive scientists study memory just as psychologists do, but tend to focus more on how memory bears on cognitive processes, and the interrelationship between cognition and memory. One example of this could be, what mental processes does a person go through to retrieve a long-lost memory? Or, what differentiates between the cognitive process of recognition (seeing hints of something before remembering it, or memory in context) and recall (retrieving a memory, as in "fill-in-the-blank")?
Perception is the ability to take in information via the senses, and process it in some way. Vision and hearing are two dominant senses that allow us to perceive the environment. Some questions in the study of visual perception, for example, include: (1) How are we able to recognize objects?, (2) Why do we perceive a continuous visual environment, even though we only see small bits of it at any one time? One tool for studying visual perception is by looking at how people process optical illusions. The image on the right of a Necker cube is an example of a bistable percept, that is, the cube can be interpreted as being oriented in two different directions.
The study of haptic (tactile), olfactory, and gustatory stimuli also fall into the domain of perception.
Action is taken to refer to the output of a system. In humans, this is accomplished through motor responses. Spatial planning and movement, speech production, and complex motor movements are all aspects of action.
Consciousness is the awareness whether something is an external object or something within oneself. This helps the mind having the ability to experience or to feel a sense of self.
Many different methodologies are used to study cognitive science. As the field is highly interdisciplinary, research often cuts across multiple areas of study, drawing on research methods from psychology, neuroscience, computer science and systems theory.
In order to have a description of what constitutes intelligent behavior, one must study behavior itself. This type of research is closely tied to that in cognitive psychology and psychophysics. By measuring behavioral responses to different stimuli, one can understand something about how those stimuli are processed. Lewandowski & Strohmetz (2009) reviewed a collection of innovative uses of behavioral measurement in psychology including behavioral traces, behavioral observations, and behavioral choice.Behavioral traces are pieces of evidence that indicate behavior occurred, but the actor is not present (e.g., litter in a parking lot or readings on an electric meter). Behavioral observations involve the direct witnessing of the actor engaging in the behavior (e.g., watching how close a person sits next to another person). Behavioral choices are when a person selects between two or more options (e.g., voting behavior, choice of a punishment for another participant).
Brain imaging involves analyzing activity within the brain while performing various tasks. This allows us to link behavior and brain function to help understand how information is processed. Different types of imaging techniques vary in their temporal (time-based) and spatial (location-based) resolution. Brain imaging is often used in cognitive neuroscience.
Computational models require a mathematically and logically formal representation of a problem. Computer models are used in the simulation and experimental verification of different specific and general properties of intelligence. Computational modeling can help us understand the functional organization of a particular cognitive phenomenon. Approaches to cognitive modeling can be categorized as: (1) symbolic, on abstract mental functions of an intelligent mind by means of symbols; (2) subsymbolic, on the neural and associative properties of the human brain; and (3) across the symbolic–subsymbolic border, including hybrid.
All the above approaches tend to be generalized to the form of integrated computational models of a synthetic/abstract intelligence, in order to be applied to the explanation and improvement of individual and social/organizational decision-making and reasoning.
Research methods borrowed directly from neuroscience and neuropsychology can also help us to understand aspects of intelligence. These methods allow us to understand how intelligent behavior is implemented in a physical system.
Cognitive science has given rise to models of human cognitive bias and risk perception, and has been influential in the development of behavioral finance, part of economics. It has also given rise to a new theory of the philosophy of mathematics,[ specify ] and many theories of artificial intelligence, persuasion and coercion. It has made its presence known in the philosophy of language and epistemology as well as constituting a substantial wing of modern linguistics. Fields of cognitive science have been influential in understanding the brain's particular functional systems (and functional deficits) ranging from speech production to auditory processing and visual perception. It has made progress in understanding how damage to particular areas of the brain affect cognition, and it has helped to uncover the root causes and results of specific dysfunction, such as dyslexia, anopia, and hemispatial neglect.
The cognitive sciences began as an intellectual movement in the 1950s, called the cognitive revolution. Cognitive science has a prehistory traceable back to ancient Greek philosophical texts (see Plato's Meno and Aristotle's De Anima ); and includes writers such as Descartes, David Hume, Immanuel Kant, Benedict de Spinoza, Nicolas Malebranche, Pierre Cabanis, Leibniz and John Locke. However, although these early writers contributed greatly to the philosophical discovery of mind and this would ultimately lead to the development of psychology, they were working with an entirely different set of tools and core concepts than those of the cognitive scientist.
The modern culture of cognitive science can be traced back to the early cyberneticists in the 1930s and 1940s, such as Warren McCulloch and Walter Pitts, who sought to understand the organizing principles of the mind. McCulloch and Pitts developed the first variants of what are now known as artificial neural networks, models of computation inspired by the structure of biological neural networks.
Another precursor was the early development of the theory of computation and the digital computer in the 1940s and 1950s. Kurt Gödel, Alonzo Church, Alan Turing, and John von Neumann were instrumental in these developments. The modern computer, or Von Neumann machine, would play a central role in cognitive science, both as a metaphor for the mind, and as a tool for investigation.
The first instance of cognitive science experiments being done at an academic institution took place at MIT Sloan School of Management, established by J.C.R. Licklider working within the psychology department and conducting experiments using computer memory as models for human cognition.
In 1959, Noam Chomsky published a scathing review of B. F. Skinner's book Verbal Behavior .At the time, Skinner's behaviorist paradigm dominated the field of psychology within the United States. Most psychologists focused on functional relations between stimulus and response, without positing internal representations. Chomsky argued that in order to explain language, we needed a theory like generative grammar, which not only attributed internal representations but characterized their underlying order.
The term cognitive science was coined by Christopher Longuet-Higgins in his 1973 commentary on the Lighthill report, which concerned the then-current state of Artificial Intelligence research.In the same decade, the journal Cognitive Science and the Cognitive Science Society were founded. The founding meeting of the Cognitive Science Society was held at the University of California, San Diego in 1979, which resulted in cognitive science becoming an internationally visible enterprise. In 1972, Hampshire College started the first undergraduate education program in Cognitive Science, led by Neil Stillings. In 1982, with assistance from Professor Stillings, Vassar College became the first institution in the world to grant an undergraduate degree in Cognitive Science. In 1986, the first Cognitive Science Department in the world was founded at the University of California, San Diego.
In the 1970s and early 1980s, as access to computers increased, artificial intelligence research expanded. Researchers such as Marvin Minsky would write computer programs in languages such as LISP to attempt to formally characterize the steps that human beings went through, for instance, in making decisions and solving problems, in the hope of better understanding human thought, and also in the hope of creating artificial minds. This approach is known as "symbolic AI".
Eventually the limits of the symbolic AI research program became apparent. For instance, it seemed to be unrealistic to comprehensively list human knowledge in a form usable by a symbolic computer program. The late 80s and 90s saw the rise of neural networks and connectionism as a research paradigm. Under this point of view, often attributed to James McClelland and David Rumelhart, the mind could be characterized as a set of complex associations, represented as a layered network. Critics argue that there are some phenomena which are better captured by symbolic models, and that connectionist models are often so complex as to have little explanatory power. Recently symbolic and connectionist models have been combined, making it possible to take advantage of both forms of explanation.While both connectionism and symbolic approaches have proven useful for testing various hypotheses and exploring approaches to understanding aspects of cognition and lower level brain functions, neither are biologically realistic and therefore, both suffer from a lack of neuroscientific plausibility. Connectionism has proven useful for exploring computationally how cognition emerges in development and occurs in the human brain, and has provided alternatives to strictly domain-specific / domain general approaches. For example, scientists such as Jeff Elman, Liz Bates, and Annette Karmiloff-Smith have posited that networks in the brain emerge from the dynamic interaction between them and environmental input.
See Criticism of cognitive psychology.
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|Name||Year of Birth||Year of Contribution||Contribution(s)|
|David Chalmers||1966||1995||Dualism, hard problem of consciousness|
|Daniel Dennett||1942||1987||Offered a computational systems perspective (Multiple drafts model)|
|John Searle||1932||1980||Chinese room|
|Douglas Hofstadter||1945||1979||Gödel, Escher, Bach|
|Jerry Fodor||1935||1968, 1975||Functionalism|
|Marvin Minsky||1927||1970s, early 1980s||Wrote computer programs in languages such as LISP to attempt to formally characterize the steps that human beings go through, such as making decisions and solving problems|
|Christopher Longuet-Higgins||1923||1973||Coined the term cognitive science|
|Noam Chomsky||1928||1959||Published a review of B.F. Skinner's book Verbal Behavior which began cognitivism against then-dominant behaviorism|
|George Miller||1920||1956||Wrote about the capacities of human thinking through mental representations|
|Herbert Simon||1916||1956||Co-created Logic Theory Machine and General Problem Solver with Allen Newell, EPAM (Elementary Perceiver and Memorizer) theory, organizational decision-making|
|John McCarthy||1927||1955||Coined the term artificial intelligence and organized the famous Dartmouth conference in Summer 1956, which started AI as a field|
|McCulloch and Pitts||1930s–1940s||Developed early artificial neural networks|
|J. C. R. Licklider||1915||Established MIT Sloan School of Management|
|Dedre Gentner||1983||Development of the Structure-mapping Theory of analogical reasoning|
|Annette Karmiloff-Smith||1938||1992||Integrating neuroscience and computational modelling into theories of cognitive development|
|Eleanor Rosch||1938||1976||Development of the Prototype Theory of categorisation|
Some of the more recognized names in cognitive science are usually either the most controversial or the most cited. Within philosophy, some familiar names include Daniel Dennett, who writes from a computational systems perspective,John Searle, known for his controversial Chinese room argument, and Jerry Fodor, who advocates functionalism.
Others include David Chalmers, who advocates Dualism and is also known for articulating the hard problem of consciousness, and Douglas Hofstadter, famous for writing Gödel, Escher, Bach , which questions the nature of words and thought.
In the realm of linguistics, Noam Chomsky and George Lakoff have been influential (both have also become notable as political commentators). In artificial intelligence, Marvin Minsky, Herbert A. Simon, and Allen Newell are prominent.
Popular names in the discipline of psychology include George A. Miller, James McClelland, Philip Johnson-Laird, and Steven Pinker. Anthropologists Dan Sperber, Edwin Hutchins, and Scott Atran, have been involved in collaborative projects with cognitive and social psychologists, political scientists and evolutionary biologists in attempts to develop general theories of culture formation, religion, and political association.
Computational theories (with models and simulations) have also been developed, by David Rumelhart, James McClelland and Philip Johnson-Laird.
Other contributions have been made by Marvin Minsky and Noam Chomsky.
Epistemics is a term coined in 1969 by the University of Edinburgh with the foundation of its School of Epistemics. Epistemics is to be distinguished from epistemology in that epistemology is the philosophical theory of knowledge, whereas epistemics signifies the scientific study of knowledge.
Christopher Longuet-Higgins has defined it as "the construction of formal models of the processes (perceptual, intellectual, and linguistic) by which knowledge and understanding are achieved and communicated.In his 1978 essay "Epistemics: The Regulative Theory of Cognition", Alvin J. Goldman claims to have coined the term "epistemics" to describe a reorientation of epistemology. Goldman maintains that his epistemics is continuous with traditional epistemology and the new term is only to avoid opposition. Epistemics, in Goldman's version, differs only slightly from traditional epistemology in its alliance with the psychology of cognition; epistemics stresses the detailed study of mental processes and information-processing mechanisms that lead to knowledge or beliefs.
In the mid-1980s, the School of Epistemics was renamed as The Centre for Cognitive Science (CCS). In 1998, CCS was incorporated into the University of Edinburgh's School of Informatics.
Cognitive psychology is the scientific study of mental processes such as "attention, language use, memory, perception, problem solving, creativity, and thinking".
The mind is the set of faculties including cognitive aspects such as consciousness, imagination, perception, thinking, intelligence, judgement, language and memory, as well as noncognitive aspects such as emotion and instinct. Under the scientific physicalist interpretation, the mind is produced at least in part by the brain. The primary competitors to the physicalist interpretations of the mind are idealism, substance dualism, and types of property dualism, and by some lights eliminative materialism and anomalous monism. There is a lengthy tradition in philosophy, religion, psychology, and cognitive science about what constitutes a mind and what are its distinguishing properties.
Cognitive neuroscience is the scientific field that is concerned with the study of the biological processes and aspects that underlie cognition, with a specific focus on the neural connections in the brain which are involved in mental processes. It addresses the questions of how cognitive activities are affected or controlled by neural circuits in the brain. Cognitive neuroscience is a branch of both neuroscience and psychology, overlapping with disciplines such as behavioral neuroscience, cognitive psychology, physiological psychology and affective neuroscience. Cognitive neuroscience relies upon theories in cognitive science coupled with evidence from neurobiology, and computational modeling.
Cognition refers to "the mental action or process of acquiring knowledge and understanding through thought, experience, and the senses". It encompasses many aspects of intellectual functions and processes such as attention, the formation of knowledge, memory and working memory, judgment and evaluation, reasoning and "computation", problem solving and decision making, comprehension and production of language. Cognitive processes use existing knowledge and generate new knowledge.
Cognitive science is the scientific study either of mind or of intelligence . Practically every formal introduction to cognitive science stresses that it is a highly interdisciplinary research area in which psychology, neuroscience, linguistics, philosophy, computer science, anthropology, and biology are its principal specialized or applied branches. Therefore, we may distinguish cognitive studies of either human or animal brains, mind and brain
The following outline is provided as an overview of and topical guide to neuroscience:
A cognitive model is an approximation to animal cognitive processes for the purposes of comprehension and prediction. Cognitive models can be developed within or without a cognitive architecture, though the two are not always easily distinguishable.
The language of thought hypothesis (LOTH), sometimes known as thought ordered mental expression (TOME), is a view in linguistics, philosophy of mind and cognitive science, forwarded by American philosopher Jerry Fodor. It describes the nature of thought as possessing "language-like" or compositional structure. On this view, simple concepts combine in systematic ways to build thoughts. In its most basic form, the theory states that thought, like language, has syntax.
ACT-R is a cognitive architecture mainly developed by John Robert Anderson and Christian Lebiere at Carnegie Mellon University. Like any cognitive architecture, ACT-R aims to define the basic and irreducible cognitive and perceptual operations that enable the human mind. In theory, each task that humans can perform should consist of a series of these discrete operations.
A cognitive architecture refers to both a theory about the structure of the human mind and to a computational instantiation of such a theory used in the fields of artificial intelligence (AI) and computational cognitive science. One of the main goals of a cognitive architecture is to summarize the various results of cognitive psychology in a comprehensive computer model. However, the results need to be formalized so far as they can be the basis of a computer program. The formalized models can be used to further refine a comprehensive theory of cognition, and more immediately, as a commercially usable model. Successful cognitive architectures include ACT-R and SOAR.
Computational cognition is the study of the computational basis of learning and inference by mathematical modeling, computer simulation, and behavioral experiments. In psychology, it is an approach which develops computational models based on experimental results. It seeks to understand the basis behind the human method of processing of information. Early on computational cognitive scientists sought to bring back and create a scientific form of Brentano's psychology
Neurophilosophy or philosophy of neuroscience is the interdisciplinary study of neuroscience and philosophy that explores the relevance of neuroscientific studies to the arguments traditionally categorized as philosophy of mind. The philosophy of neuroscience attempts to clarify neuroscientific methods and results using the conceptual rigor and methods of philosophy of science.
Stephen Grossberg is a cognitive scientist, theoretical and computational psychologist, neuroscientist, mathematician, biomedical engineer, and neuromorphic technologist. He is the Wang Professor of Cognitive and Neural Systems and a Professor Emeritus of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering at Boston University.
In philosophy of mind, the computational theory of mind (CTM), also known as computationalism, is a family of views that hold that the human mind is an information processing system and that cognition and consciousness together are a form of computation. Warren McCulloch and Walter Pitts (1943) were the first to suggest that neural activity is computational. They argued that neural computations explain cognition. The theory was proposed in its modern form by Hilary Putnam in 1967, and developed by his PhD student, philosopher and cognitive scientist Jerry Fodor in the 1960s, 1970s and 1980s. Despite being vigorously disputed in analytic philosophy in the 1990s due to work by Putnam himself, John Searle, and others, the view is common in modern cognitive psychology and is presumed by many theorists of evolutionary psychology. In the 2000s and 2010s the view has resurfaced in analytic philosophy.
Music psychology, or the psychology of music, may be regarded as a branch of both psychology and musicology. It aims to explain and understand musical behaviour and experience, including the processes through which music is perceived, created, responded to, and incorporated into everyday life. Modern music psychology is primarily empirical; its knowledge tends to advance on the basis of interpretations of data collected by systematic observation of and interaction with human participants. Music psychology is a field of research with practical relevance for many areas, including music performance, composition, education, criticism, and therapy, as well as investigations of human attitude, skill, performance, intelligence, creativity, and social behavior.
Embodied cognitive science is an interdisciplinary field of research, the aim of which is to explain the mechanisms underlying intelligent behavior. It comprises three main methodologies: the modeling of psychological and biological systems in a holistic manner that considers the mind and body as a single entity; the formation of a common set of general principles of intelligent behavior; and the experimental use of robotic agents in controlled environments.
The following outline is provided as an overview of and topical guide to thought (thinking):
Some of the research that is conducted in the field of psychology is more "fundamental" than the research conducted in the applied psychological disciplines, and does not necessarily have a direct application. The subdisciplines within psychology that can be thought to reflect a basic-science orientation include biological psychology, cognitive psychology, neuropsychology, and so on. Research in these subdisciplines is characterized by methodological rigor. The concern of psychology as a basic science is in understanding the laws and processes that underlie behavior, cognition, and emotion. Psychology as a basic science provides a foundation for applied psychology. Applied psychology, by contrast, involves the application of psychological principles and theories yielded up by the basic psychological sciences; these applications are aimed at overcoming problems or promoting well-being in areas such as mental and physical health and education.
Cognitive musicology is a branch of cognitive science concerned with computationally modeling musical knowledge with the goal of understanding both music and cognition.
Embodied cognition is the theory that many features of cognition, whether human or otherwise, are shaped by aspects of the entire body of the organism. The features of cognition include high level mental constructs and performance on various cognitive tasks. The aspects of the body include the motor system, the perceptual system, bodily interactions with the environment (situatedness), and the assumptions about the world that are built into the structure of the organism.
Cognitive science is an interdisciplinary field of researchers from Linguistics, psychology, neuroscience, philosophy, computer science, and anthropology that seek to understand the mind.