Cognitive science
Cognitive science is the
History
The cognitive sciences began as an intellectual movement in the 1950s, called the
while mostly having never read Aristotle, and 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
Another precursor was the early development of the
The first instance of cognitive science experiments being done at an academic institution took place at
The term cognitive science was coined by
In the 1970s and early 1980s, as access to computers increased,
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
Recent developments in
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. Francisco Varela, in The Embodied Mind: Cognitive Science and Human Experience, argues that "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".[22] On the classic cognitivist view, 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.
- The computational theory, specifying the goals of the computation;
- Representation and algorithms, giving a representation of the inputs and outputs and the algorithms which transform one into the other; and
- 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
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" (
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. [26]
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. Classical cognitivists have largely de-emphasized or avoided social and cultural factors, embodiment, 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
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.
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 artificial intelligence. 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.
The psychological construct of Attention is sometimes confused with the concept of Intentionality due to some degree of semantic ambiguity in their definitions. At the beginning of experimental research on Attention, Wilhelm Wundt defined this term as "that psychical process, which is operative in the clear perception of the narrow region of the content of consciousness."[28] His experiments showed the limits of Attention in space and time, which were 3-6 letters during an exposition of 1/10 s.[28] Because this notion develops within the framework of the original meaning during a hundred years of research, the definition of Attention would reflect the sense when it accounts for the main features initially attributed to this term – it is a process of controlling thought that continues over time.[29] While Intentionality is the power of minds to be about something, Attention is the concentration of awareness on some phenomenon during a period of time, which is necessary to elevate the clear perception of the narrow region of the content of consciousness and which is feasible to control this focus in mind.
The significance of knowledge about the scope of attention for studying cognition is that it defines the intellectual functions of cognition such as apprehension, judgment, reasoning, and working memory. The development of attention scope increases the set of faculties responsible for the mind relies on how it perceives, remembers, considers, and evaluates in making decisions.[30] The ground of this statement is that the more details (associated with an event) the mind may grasp for their comparison, association, and categorization, the closer apprehension, judgment, and reasoning of the event are in accord with reality.[31] According to Latvian professor Sandra Mihailova and professor Igor Val Danilov, the more elements of the phenomenon (or phenomena ) the mind can keep in the scope of attention simultaneously, the more significant number of reasonable combinations within that event it can achieve, enhancing the probability of better understanding features and particularity of the phenomenon (phenomena).[31] For example, three items in the focal point of consciousness yield six possible combinations (3 factorial) and four items – 24 (4 factorial) combinations. The number of reasonable combinations becomes significant in the case of a focal point with six items with 720 possible combinations (6 factorial).[31]
Embodied cognition approaches to cognitive science emphasize the role of body and environment in cognition. This includes both neural and extra-neural bodily processes, and factors that range from affective and emotional processes,[32] to posture, motor control, proprioception, and kinaesthesis,[33] to autonomic processes that involve heartbeat[34] and respiration,[35] to the role of the enteric gut microbiome.[36] It also includes accounts of how the body engages with or is coupled to social and physical environments. 4E (embodied, embedded, extended and enactive) cognition[37][38] includes a broad range of views about brain-body-environment interaction, from causal embeddedness to stronger claims about how the mind extends to include tools and instruments, as well as the role of social interactions, action-oriented processes, and affordances. 4E theories range from those closer to classic cognitivism (so-called "weak" embodied cognition[39]) to stronger extended[40] and enactive versions that are sometimes referred to as radical embodied cognitive science.[41][42]
Knowledge and processing of language
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.
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.[44] 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
A major question in the study of cognitive development is the extent to which certain abilities are
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.
Cognitive scientists study memory just as psychologists do, but tend to focus more on how memory bears on
Perception and action
Perception is the ability to take in information via the
The study of
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 of experiences within oneself. This helps the mind with having the ability to experience or 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 & Strohmetz (2009) reviewed a collection of innovative uses of behavioral measurement in psychology including behavioral traces, behavioral observations, and behavioral choice.[46] 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.[47]
Brain imaging
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
- Symbolic modeling evolved from the computer science paradigms using the technologies of socio-cognitiveapproach, including social and organizational cognition, interrelated with a sub-symbolic non-conscious layer.
- Subsymbolic modeling includes Neural netsare 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) hybrid intelligent systems), and (3) and Bayesian models, which are often drawn from machine learning.
All the above approaches tend either to be generalized to the form of integrated computational models of a synthetic/abstract intelligence (i.e.
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.
- Single-unit recording
- Direct brain stimulation
- Animal models
- Postmortem studies
Key findings
Cognitive science has given rise to models of human
Notable researchers
This section needs additional citations for verification. (August 2012) |
Name | Year of birth | Year of contribution | Contribution(s) |
---|---|---|---|
David Chalmers | 1966[50] | 1995[51] | Dualism, hard problem of consciousness
|
Daniel Dennett | 1942[52] | 1987 | Offered a computational systems perspective (Multiple drafts model) |
John Searle | 1932[53] | 1980 | Chinese room |
Douglas Hofstadter | 1945 | 1979[54] | Gödel, Escher, Bach[55] |
Jerry Fodor | 1935[56] | 1968, 1975 | Functionalism |
Alan Baddeley | 1934[57] | 1974 | Baddeley's model of working memory |
Marvin Minsky | 1927[58] | 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[59] | 1973 | Coined the term cognitive science |
Noam Chomsky | 1928[60] | 1959 | Published a review of B.F. Skinner's book Verbal Behavior which began cognitivism against then-dominant behaviorism[5] |
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[61] | Established MIT Sloan School of Management | |
Lila R. Gleitman | 1929 | 1970s-2010s | Wide-ranging contributions to understanding the cognition of language acquisition, including syntactic bootstrapping theory[62] |
Eleanor Rosch | 1938 | 1976 | Development of the Prototype Theory of categorisation[63] |
Philip N. Johnson-Laird
|
1936 | 1980 | Introduced the idea of mental models in cognitive science[64] |
Dedre Gentner | 1944 | 1983 | Development of the analogical reasoning[65]
|
Allen Newell | 1927 | 1990 | Development of the field of Cognitive architecture in cognitive modelling and artificial intelligence[66]
|
Annette Karmiloff-Smith | 1938 | 1992 | Integrating computational modelling into theories of cognitive development[67]
|
David Marr (neuroscientist) | 1945 | 1990 | Proponent of the Three-Level Hypothesis of levels of analysis of computational systems[68] |
Peter Gärdenfors | 1949 | 2000 | Creator of the conceptual space framework used in cognitive modelling and artificial intelligence. |
Linda B. Smith | 1951 | 1993 | Together with Esther Thelen, created a dynamical systems approach to understanding cognitive development[69] |
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,[70] John Searle, known for his controversial Chinese room argument,[71] and Jerry Fodor, who advocates functionalism.[72]
Others include
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
Computational theories (with models and simulations) have also been developed, by David Rumelhart, James McClelland and Philip Johnson-Laird.
Epistemics
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."[73]
In his 1978 essay "Epistemics: The Regulative Theory of Cognition",
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
Binding problem in cognitive science
One of the core aims of cognitive science is to achieve an integrated theory of cognition. This requires integrative mechanisms explaining how the information processing that occurs simultaneously in spatially segregated (sub-)cortical areas in the brain is coordinated and bound together to give rise to coherent perceptual and symbolic representations. One approach is to solve this "
However, despite significant advances in understanding the integrated theory of cognition (specifically the Binding problem), the debate on this issue of beginning cognition is still in progress. From the different perspectives noted above, this problem can be reduced to the issue of how organisms at the simple reflexes stage of development overcome the threshold of the environmental chaos of sensory stimuli: electromagnetic waves, chemical interactions, and pressure fluctuations.[86] The so-called Primary Data Entry (PDE) thesis poses doubts about the ability of such an organism to overcome this cue threshold on its own.[87] In terms of mathematical tools, the PDE thesis underlines the insuperable high threshold of the cacophony of environmental stimuli (the stimuli noise) for young organisms at the onset of life.[87] It argues that the temporal (phase) synchronization of neural activity based on dynamical self-organizing processes in neural networks, any dynamical bound together or integration to a representation of the perceptual object by means of a synchronization mechanism can not help organisms in distinguishing relevant cue (informative stimulus) for overcome this noise threshold.[87]
See also
- Affective science
- Cognitive anthropology
- Cognitive biology
- Cognitive computing
- Cognitive ethology
- Cognitive linguistics
- Cognitive neuropsychology
- Cognitive neuroscience
- Cognitive psychology
- Cognitive science of religion
- Computational neuroscience
- Computational-representational understanding of mind
- Concept mining
- Decision field theory
- Decision theory
- Dynamicism
- Educational neuroscience
- Educational psychology
- Embodied cognition
- Embodied cognitive science
- Enactivism
- Epistemology
- Folk psychology
- Heterophenomenology
- Human Cognome Project
- Human–computer interaction
- Indiana Archives of Cognitive Science
- Informatics (academic field)
- List of cognitive scientists
- List of psychology awards
- Malleable intelligence
- Neural Darwinism
- Personal information management (PIM)
- Qualia
- Quantum cognition
- Simulated consciousness
- Situated cognition
- Society of Mind theory
- Spatial cognition
- Speech–language pathology
- 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.
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- ^ Treisman A. (1999). "Solutions to the binding problem: progress through controversy and convergence." Neuron, 1999, 24(1):105-125.
- ^ .
External links
- Media related to Cognitive science at Wikimedia Commons
- Quotations related to Cognitive science at Wikiquote
- Learning materials related to Cognitive science at Wikiversity
- "Cognitive Science" on the Stanford Encyclopedia of Philosophy
- Cognitive Science Society
- Cognitive Science Movie Index: A broad list of movies showcasing themes in the Cognitive Sciences Archived 4 September 2015 at the Wayback Machine
- List of leading thinkers in cognitive science