Cognitive science

Cognitive science is the interdisciplinary, scientific study of the mind and its processes.[2] 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.[3] 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. The fundamental concept 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."[3]

Simply put: 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.

Cognitive Science Hexagon
Figure illustrating the fields that contributed to the birth of cognitive science, including linguistics, neuroscience, artificial intelligence, philosophy, anthropology, and psychology[1]

Principles

Levels of analysis

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.”[4] 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[5] gave a famous description of three levels of analysis:

  1. The computational theory, specifying the goals of the computation;
  2. Representation and algorithms, giving a representation of the inputs and outputs and the algorithms which transform one into the other; and
  3. The hardware implementation, or how algorithm and representation may be physically realized.

Interdisciplinary nature

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.[6][7]

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.

Cognitive science: the term

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.[1]

Scope

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

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.[8] (See § Computational modeling.)

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

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.

Knowledge and processing of language

Cgisf-tgg
A well known example of a Phrase structure tree. This is one way of representing human language that shows how different components are organized hierarchically.

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.[9]

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.[10] 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

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)[11] 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

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. "Who was the first president of the U.S.A.?", 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 and action

Necker cube
The Necker cube, an example of an optical illusion
Checker shadow illusion
An optical illusion. The square A is exactly the same shade of gray as square B. See checker shadow illusion.

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

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.

Research methods

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.

Behavioral experiments

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 and Strohmetz (2009) review a collection of innovative uses of behavioral measurement in psychology including behavioral traces, behavioral observations, and behavioral choice.[12] 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).

  • Reaction time. The time between the presentation of a stimulus and an appropriate response can indicate differences between two cognitive processes, and can indicate some things about their nature. For example, if in a search task the reaction times vary proportionally with the number of elements, then it is evident that this cognitive process of searching involves serial instead of parallel processing.
  • Psychophysical responses. Psychophysical experiments are an old psychological technique, which has been adopted by cognitive psychology. They typically involve making judgments of some physical property, e.g. the loudness of a sound. Correlation of subjective scales between individuals can show cognitive or sensory biases as compared to actual physical measurements. Some examples include:
    • sameness judgments for colors, tones, textures, etc.
    • threshold differences for colors, tones, textures, etc.
  • Eye tracking. This methodology is used to study a variety of cognitive processes, most notably visual perception and language processing. The fixation point of the eyes is linked to an individual's focus of attention. Thus, by monitoring eye movements, we can study what information is being processed at a given time. Eye tracking allows us to study cognitive processes on extremely short time scales. Eye movements reflect online decision making during a task, and they provide us with some insight into the ways in which those decisions may be processed.

Brain imaging

Hypothalamus
Image of the human head with the brain. The arrow indicates the position of the hypothalamus.

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.

  • Single photon emission computed tomography and Positron emission tomography. SPECT and PET use radioactive isotopes, which are injected into the subject's bloodstream and taken up by the brain. By observing which areas of the brain take up the radioactive isotope, we can see which areas of the brain are more active than other areas. PET has similar spatial resolution to fMRI, but it has extremely poor temporal resolution.
  • Electroencephalography. EEG measures the electrical fields generated by large populations of neurons in the cortex by placing a series of electrodes on the scalp of the subject. This technique has an extremely high temporal resolution, but a relatively poor spatial resolution.
  • Functional magnetic resonance imaging. fMRI measures the relative amount of oxygenated blood flowing to different parts of the brain. More oxygenated blood in a particular region is assumed to correlate with an increase in neural activity in that part of the brain. This allows us to localize particular functions within different brain regions. fMRI has moderate spatial and temporal resolution.
  • Optical imaging. This technique uses infrared transmitters and receivers to measure the amount of light reflectance by blood near different areas of the brain. Since oxygenated and deoxygenated blood reflects light by different amounts, we can study which areas are more active (i.e., those that have more oxygenated blood). Optical imaging has moderate temporal resolution, but poor spatial resolution. It also has the advantage that it is extremely safe and can be used to study infants' brains.
  • Magnetoencephalography. MEG measures magnetic fields resulting from cortical activity. It is similar to EEG, except that it has improved spatial resolution since the magnetic fields it measures are not as blurred or attenuated by the scalp, meninges and so forth as the electrical activity measured in EEG is. MEG uses SQUID sensors to detect tiny magnetic fields.

Computational modeling

Multi-Layer Neural Network-Vector
An artificial neural network with two layers.

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.

  • Symbolic modeling evolved from the computer science paradigms using the technologies of knowledge-based systems, as well as a philosophical perspective, see for example "Good Old-Fashioned Artificial Intelligence" (GOFAI). They are developed by the first cognitive researchers and later used in information engineering for expert systems . Since the early 1990s it was generalized in systemics for the investigation of functional human-like intelligence models, such as personoids, and, in parallel, developed as the SOAR environment. Recently, especially in the context of cognitive decision making, symbolic cognitive modeling has been extended to the socio-cognitive approach, including social and organization cognition, interrelated with a sub-symbolic non-conscious layer.
  • Subsymbolic modeling includes connectionist/neural network models. Connectionism relies on the idea that the mind/brain is composed of simple nodes and its problem-solving capacity derives from the connections between them. Neural nets are textbook implementations of this approach. Some critics of this approach feel that while these models approach biological reality as a representation of how the system works these models lack explanatory powers because, even in systems endowed with simple connection rules, the emerging high complexity makes them less interpretable at the connection-level than they apparently are at the macroscopic level.
  • Other approaches gaining in popularity include (1) dynamical systems theory, (2) mapping symbolic models onto connectionist models (Neural-symbolic integration or hybrid intelligent systems), and (3) Bayesian models, often drawn from machine learning.

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.[13]

Neurobiological methods

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.

Key findings

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, 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.

History

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.[14]

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.[15] In the same decade, the journal Cognitive Science and the Cognitive Science Society were founded.[16] 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.[17] 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.[18] In 1986, the first Cognitive Science Department in the world was founded at the University of California, San Diego.[17]

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.[19][20] 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.[21][22][23][24][25][26][27] 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.[28]

Notable researchers

Name Year of Birth Year of Contribution Contribution(s)
Daniel Dennett 1942[29] 1987 Offered a computational systems perspective
John Searle 1932[30] 1980 Chinese room
Jerry Fodor 1935[31] 1968, 1975 Functionalism
David Chalmers 1966[32] 1995[33] Dualism, hard problem of consciousness
Douglas Hofstadter 1945 1979[34] Gödel, Escher, Bach[35]
Marvin Minsky 1927[36] 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[37] 1973 Coined the term cognitive science
McCulloch and Pitts 1930s–1940s Developed early artificial neural networks
J. C. R. Licklider 1915[38] Established MIT Sloan School of Management
Noam Chomsky 1928[39] 1959 Published a review of B.F. Skinner's book Verbal Behavior which began cognitivism against then-dominant behaviorism.

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,[40] John Searle, known for his controversial Chinese room argument,[41] and Jerry Fodor, who advocates functionalism.[42]

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 the likes of David Rumelhart, James McClelland, Philip Johnson-Laird, and so on.

Other contributions have been made by Marvin Minsky and Noam Chomsky.

See also

Outlines
  • Outline of human intelligence - topic tree presenting the traits, capacities, models, and research fields of human intelligence, and more.
  • Outline of thought - topic tree that identifies many types of thoughts, types of thinking, aspects of thought, related fields, and more.

References

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External links

Behavioural sciences

Behavioural sciences explore the cognitive processes within organisms and the behavioural interactions between organisms in the natural world. It involves the systematic analysis and investigation of human and animal behavior through the study of the past, controlled and naturalistic observation of the present, and disciplined scientific experimentation and modeling. It attempts to accomplish legitimate, objective conclusions through rigorous formulations and observation. Examples of behavioral sciences include psychology, psychobiology, anthropology, and cognitive science. Generally, behavior science deals primarily with human action and often seeks to generalize about human behavior as it relates to society.

Carleton University

Carleton University is a public comprehensive university in Ottawa, Ontario, Canada. Founded in 1942 as Carleton College, a private, non-denominational evening college to serve veterans returning from World War II, the institution was chartered as a university by the provincial government in 1952 through the The Carleton University Act. The legislation was subsequently amended in 1957 to give the institution its current name. The university moved to its current campus in 1959, and would expand rapidly throughout the 1960s amid broader efforts by the provincial government to increase support to post-secondary institutions and expand access to higher education.

Carleton, which has produced more than 140,000 alumni, is reputed for its strength in a variety of fields such as humanities, international business, engineering, physics, entrepreneurship, computer science, and many of the disciplines housed in its Faculty of Public Affairs (including international affairs, journalism, political science, political economy, political management, public policy and administration, and legal studies). As well as having excellent student accommodation facilities (Paul-Menton Centre, MacEntyre Centre).

The university is named for the now-dissolved Carleton County, which included the city of Ottawa at the time the university was founded. Carleton County, in turn, was named in honour of Guy Carleton, 1st Baron Dorchester, who served as Governor General of Canada of The Canadas from 1786 to 1796. As of 2017, Carleton has enrolment of more than 25,000 undergraduate and more than 4,000 postgraduate students. Its campus is located west of Old Ottawa South, within close proximity to The Glebe and Confederation Heights, and is bounded to the north by the Rideau Canal and Dow's Lake and to the south by the Rideau River.Carleton competes in the U Sports league as the Carleton Ravens. The university is renowned for the strong performance of its men's basketball team, which won seven consecutive Canadian national championships between 2006 and 2017, in addition to 13 of the 15 championships since 2003.

Cognition

Cognition is "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.

The processes are analyzed from different perspectives within different contexts, notably in the fields of linguistics, anesthesia, neuroscience, psychiatry, psychology, education, philosophy, anthropology, biology, systemics, logic, and computer science. These and other different approaches to the analysis of cognition are synthesised in the developing field of cognitive science, a progressively autonomous academic discipline.

Cognitive Science Society

The Cognitive Science Society is a professional society for the interdisciplinary field of cognitive science. It brings together researchers from many fields who hold the common goal of understanding the nature of the human mind. The society promotes scientific interchange among researchers in disciplines comprising the field of cognitive science, including artificial intelligence, linguistics, anthropology, psychology, neuroscience, philosophy, and education. The Society is a member of the Federation of Associations in Behavioral & Brain Sciences.

Cognitive anthropology

Cognitive anthropology is an approach within cultural anthropology and biological anthropology in which scholars seek to explain patterns of shared knowledge, cultural innovation, and transmission over time and space using the methods and theories of the cognitive sciences (especially experimental psychology and cognitive psychology) often through close collaboration with historians, ethnographers, archaeologists, linguists, musicologists and other specialists engaged in the description and interpretation of cultural forms. Cognitive anthropology is concerned with what people from different groups know and how that implicit knowledge, in the sense of what they think subconsciously, changes the way people perceive and relate to the world around them.

Cognitive ethology

Cognitive ethology is a branch of ethology concerned with the influence of conscious awareness and intention on the behaviour of an animal. Donald Griffin, a zoology professor in the United States, set up the foundations for researches in the cognitive awareness of animals within their habitats.The fusion of cognitive science and classical ethology into cognitive ethology "emphasizes observing animals under more-or-less natural conditions, with the objective of understanding the evolution, adaptation (function), causation, and development of the species-specific behavioral repertoire" (Niko Tinbergen 1963).

According to Jamieson & Bekoff (1993), "Tinbergen's four questions about the evolution, adaptation, causation and development of behavior can be applied to the cognitive and mental abilities of animals." Allen & Bekoff (1997, chapter 5) attempt to show how cognitive ethology can take on the central questions of cognitive science, taking as their starting point the four questions described by Barbara Von Eckardt in her 1993 book What is Cognitive Science?, generalizing the four questions and adding a fifth. Kingstone, Smilek & Eastwood (2008) suggested that cognitive ethology should include human behavior. They proposed that researchers should firstly study how people behave in their natural, real world environments and then move to the lab. Anthropocentric claims for the ways non-human animals interact in their social and non-social worlds are often used to influence decisions on how the non-human animals can or should be used by humans.

Cognitive neuroscience

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.Parts of the brain play an important role in this field. Neurons play the most vital role, since the main point is to establish an understanding of cognition from a neural perspective, along with the different lobes of the cerebral cortex.

Methods employed in cognitive neuroscience include experimental procedures from psychophysics and cognitive psychology, functional neuroimaging, electrophysiology, cognitive genomics, and behavioral genetics.

Studies of patients with cognitive deficits due to brain lesions constitute an important aspect of cognitive neuroscience. The damages in lesioned brains provide a comparable basis with regards to healthy and fully functioning brains.

These damages change the neural circuits in the brain and cause it to malfunction during basic cognitive processes, such as memory or learning. With the damage, we can compare how the healthy neural circuits are functioning, and possibly draw conclusions about the basis of the affected cognitive processes.

Also, cognitive abilities based on brain development are studied and examined under the subfield of developmental cognitive neuroscience. This shows brain development over time, analyzing differences and concocting possible reasons for those differences.

Theoretical approaches include computational neuroscience and cognitive psychology.

Cognitive psychology

Cognitive psychology is the scientific study of mental processes such as "attention, language use, memory, perception, problem solving, creativity, and thinking". Much of the work derived from cognitive psychology has been integrated into various other modern disciplines such as Cognitive Science and of psychological study, including educational psychology, social psychology, personality psychology, abnormal psychology, developmental psychology, linguistics, and economics.

Cognitive science of religion

Cognitive science of religion is the study of religious thought and behavior from the perspective of the cognitive and evolutionary sciences. The field employs methods and theories from a very broad range of disciplines, including: cognitive psychology, evolutionary psychology, cognitive anthropology, artificial intelligence, neurotheology, developmental psychology, and archaeology. Scholars in this field seek to explain how human minds acquire, generate, and transmit religious thoughts, practices, and schemas by means of ordinary cognitive capacities.

Concept

Concepts are mental representations, abstract objects or abilities that make up the fundamental building blocks of thoughts and beliefs. They play an important role in all aspects of cognition.In contemporary philosophy, there are at least three prevailing ways to understand what a concept is:

Concepts as mental representations, where concepts are entities that exist in the mind (mental objects)

Concepts as abilities, where concepts are abilities peculiar to cognitive agents (mental states)

Concepts as Fregean senses (see sense and reference), where concepts are abstract objects, as opposed to mental objects and mental statesConcepts can be organized into a hierarchy, higher levels of which are termed "superordinate" and lower levels termed "subordinate". Additionally, there is the "basic" or "middle" level at which people will most readily categorize a concept. For example, a basic-level concept would be "chair", with its superordinate, "furniture", and its subordinate, "easy chair".

A concept is instantiated (reified) by all of its actual or potential instances, whether these are things in the real world or other ideas.

Concepts are studied as components of human cognition in the cognitive science disciplines of linguistics, psychology and, philosophy, where an ongoing debate asks whether all cognition must occur through concepts. Concepts are used as formal tools or models in mathematics, computer science, databases and artificial intelligence where they are sometimes called classes, schema or categories. In informal use the word concept often just means any idea.

Don Norman

Donald Arthur Norman (born December 25, 1935) is a researcher, professor, and author. Norman is the director of The Design Lab at University of California, San Diego. He is best known for his books on design, especially The Design of Everyday Things. He is widely regarded for his expertise in the fields of design, usability engineering, and cognitive science. He is a co-founder and consultant with the Nielsen Norman Group. He is also an IDEO fellow and a member of the Board of Trustees of IIT Institute of Design in Chicago. He also holds the title of Professor Emeritus of Cognitive Science at the University of California, San Diego. Norman is an active Distinguished Visiting Professor at the Korea Advanced Institute of Science and Technology (KAIST), where he spends two months a year teaching.Much of Norman's work involves the advocacy of user-centered design. His books all have the underlying purpose of furthering the field of design, from doors to computers. Norman has taken a controversial stance in saying that the design research community has had little impact in the innovation of products, and that while academics can help in refining existing products, it is technologists that accomplish the breakthroughs. To this end, Norman named his website with the initialism JND to signify his endeavors to make a difference.

Dynamical systems theory

Dynamical systems theory is an area of mathematics used to describe the behavior of the complex dynamical systems, usually by employing differential equations or difference equations. When differential equations are employed, the theory is called continuous dynamical systems. From a physical point of view, continuous dynamical systems is a generalization of classical mechanics, a generalization where the equations of motion are postulated directly and are not constrained to be Euler–Lagrange equations of a least action principle. When difference equations are employed, the theory is called discrete dynamical systems. When the time variable runs over a set that is discrete over some intervals and continuous over other intervals or is any arbitrary time-set such as a cantor set, one gets dynamic equations on time scales. Some situations may also be modeled by mixed operators, such as differential-difference equations.

This theory deals with the long-term qualitative behavior of dynamical systems, and studies the nature of, and when possible the solutions of, the equations of motion of systems that are often primarily mechanical or otherwise physical in nature, such as planetary orbits and the behaviour of electronic circuits, as well as systems that arise in biology, economics, and elsewhere. Much of modern research is focused on the study of chaotic systems.

This field of study is also called just dynamical systems, mathematical dynamical systems theory or the mathematical theory of dynamical systems.

Franklin Institute Awards

The Franklin Institute Awards (or Benjamin Franklin Medal) is a science and engineering award presented since 1824 by the Franklin Institute, of Philadelphia, Pennsylvania, US. The Franklin Institute Awards comprises the Benjamin Franklin Medals in seven areas of science and engineering, the Bower Awards and Prize for Achievement in Science, and the Bower Award for Business Leadership.

Information processing

Information processing is the change (processing) of information in any manner detectable by an observer. As such, it is a process that describes everything that happens (changes) in the universe, from the falling of a rock (a change in position) to the printing of a text file from a digital computer system. In the latter case, an information processor is changing the form of presentation of that text file.

Information processing may more specifically be defined in terms used by, Claude E. Shannon as the conversion of latent information into manifest information (McGonigle & Mastrian, 2011). Latent and manifest information is defined through the terms of equivocation (remaining uncertainty, what value the sender has chosen), dissipation (uncertainty of the sender what the receiver has received), and transformation (saved effort of questioning – equivocation minus dissipation) (Denning and Bell, 2012).

Justin L. Barrett

Justin L. Barrett (born 1971) is an American experimental psychologist, Director of the Thrive Center for Human Development in Pasadena, California, Thrive Professor of Developmental Science, and Professor of Psychology at Fuller Graduate School of Psychology. He previously was a senior researcher and director of the Centre for Anthropology and Mind and The Institute for Cognitive and Evolutionary Anthropology at Oxford University.

List of psychological schools

The psychological schools are the great classical theories of psychology. Each has been highly influential; however, most psychologists hold eclectic viewpoints that combine aspects of each school.

Mental representation

A mental representation (or cognitive representation), in philosophy of mind, cognitive psychology, neuroscience, and cognitive science, is a hypothetical internal cognitive symbol that represents external reality, or else a mental process that makes use of such a symbol: "a formal system for making explicit certain entities or types of information, together with a specification of how the system does this".Mental representation is the mental imagery of things that are not actually present to the senses. In contemporary philosophy, specifically in fields of metaphysics such as philosophy of mind and ontology, a mental representation is one of the prevailing ways of explaining and describing the nature of ideas and concepts.

Mental representations (or mental imagery) enable representing things that have never been experienced as well as things that do not exist. Think of yourself traveling to a place you have never visited before, or having a third arm. These things have either never happened or are impossible and do not exist, yet our brain and mental imagery allows us to imagine them. Although visual imagery is more likely to be recalled, mental imagery may involve representations in any of the sensory modalities, such as hearing, smell, or taste. Stephen Kosslyn proposes that images are used to help solve certain types of problems. We are able to visualize the objects in question and mentally represent the images to solve it.Mental representations also allow people to experience things right in front of them—though the process of how the brain interprets the representational content is debated.

Mind

The mind (not to be confused with the brain) is a set of cognitive faculties including consciousness, imagination, perception, thinking, judgement, language and memory. It is usually defined as the faculty of an entity's thoughts and consciousness. It holds the power of imagination, recognition, and appreciation, and is responsible for processing feelings and emotions, resulting in attitudes and actions.There is a lengthy tradition in philosophy, religion, psychology, and cognitive science about what constitutes a mind and what are its distinguishing properties.

One open question regarding the nature of the mind is the mind–body problem, which investigates the relation of the mind to the physical brain and nervous system. Older viewpoints included dualism and idealism, which considered the mind somehow non-physical. Modern views often center around physicalism and functionalism, which hold that the mind is roughly identical with the brain or reducible to physical phenomena such as neuronal activity, though dualism and idealism continue to have many supporters. Another question concerns which types of beings are capable of having minds (New Scientist 8 September 2018 p10). For example, whether mind is exclusive to humans, possessed also by some or all animals, by all living things, whether it is a strictly definable characteristic at all, or whether mind can also be a property of some types of human-made machines.Whatever its nature, it is generally agreed that mind is that which enables a being to have subjective awareness and intentionality towards their environment, to perceive and respond to stimuli with some kind of agency, and to have consciousness, including thinking and feeling.The concept of mind is understood in many different ways by many different cultural and religious traditions. Some see mind as a property exclusive to humans whereas others ascribe properties of mind to non-living entities (e.g. panpsychism and animism), to animals and to deities. Some of the earliest recorded speculations linked mind (sometimes described as identical with soul or spirit) to theories concerning both life after death, and cosmological and natural order, for example in the doctrines of Zoroaster, the Buddha, Plato, Aristotle, and other ancient Greek, Indian and, later, Islamic and medieval European philosophers.

Important philosophers of mind include Plato, Patanjali, Descartes, Leibniz, Locke, Berkeley, Hume, Kant, Hegel, Schopenhauer, Searle, Dennett, Fodor, Nagel, and Chalmers. Psychologists such as Freud and James, and computer scientists such as Turing and Putnam developed influential theories about the nature of the mind. The possibility of nonbiological minds is explored in the field of artificial intelligence, which works closely in relation with cybernetics and information theory to understand the ways in which information processing by nonbiological machines is comparable or different to mental phenomena in the human mind.The mind is also portrayed as the stream of consciousness where sense impressions and mental phenomena are constantly changing.

Thought

Thought encompasses an "aim-oriented flow of ideas and associations that can lead to a reality-oriented conclusion". Although thinking is an activity of an existential value for humans, there is no consensus as to how it is defined or understood.

Because thought underlies many human actions and interactions, understanding its physical and metaphysical origins, and effects has been a longstanding goal of many academic disciplines including philosophy, linguistics, psychology, neuroscience, artificial intelligence, biology, sociology and

cognitive science.

Thinking allows humans to make sense of, interpret, represent or model the world they experience, and to make predictions about that world. It is therefore helpful to an organism with needs, objectives, and desires as it makes plans or otherwise attempts to accomplish those goals.

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