Cognitive science: Difference between revisions
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::*Chapter 13 - Executive Function | ::*Chapter 13 - Executive Function | ||
::*Chapter 14 - The Social Brain (by Jennifer S. Beer) | ::*Chapter 14 - The Social Brain (by Jennifer S. Beer) | ||
::*Chapter 15 - Evolutionary Perspectives (with Jeff Hutsler) </ref> | ::*Chapter 15 - Evolutionary Perspectives (with Jeff Hutsler)</ref> <ref cash>Cash J. [http://www.indiana.edu/~wanthro/cog.htm Cognitive Anthropology] Indiana University | ||
*'''<u>From the website:</u>’''' | |||
:* Cognitive anthropology generally focuses on the intellectual and rational aspects of culture, particularly through studies of language use. The centrality of language to cognitive anthropology is related to the origins of the sub-field. Cognitive anthropology is distinguished most by its methodology, which originated in attempts to fit formal linguistic methods into linguistic and social anthropology. This methodology also assumes that semantic categories marked by linguistic forms are related to meaningful cultural categories. | |||
:*Cognitive anthropology's methods for revealing meaningful cultural categories in language have also been expanded to more general ethnographic methods (e.g. Duane and Metzger (1963)), and some recent work has focused on emotions and culture. Cognitive anthropology has ties to linguistic and psychological anthropology, linguistics, cognitive linguistics, psycholinguistics, cognitive psychology, and other cognitive sciences. | |||
:*Cognitive anthropology's beginnings in the 1950's developed out of linguistic anthropology's ongoing dialogue with formal linguistics and anthropology, but its emergence paralleled a general interest in cognitive phenomena across the social and biological sciences. In behavioral psychology, interest in cognition increased in conjunction with the development and use of computers (D'Andrade 1995:10). | |||
:*Cognitive anthropology has increasingly used computer modeling, and Colby (1996: 214-215) recommends that aspiring cognitive anthropologists learn a variety of skills transferable across the cognitive sciences: knowledge systems, text comprehension systems, and parallel distribution processes from computer sciences; text analysis and narrative structure from cognitive psychology; symbolic logic from philosophy; and multi-dimensional scaling and clustering techniques from statistics.</ref> | |||
:*Conceptual Change | :*Conceptual Change | ||
:*Conceptual Organization | :*Conceptual Organization |
Revision as of 16:54, 6 January 2009
Note: Text in font-color Blue link to articles in Citizendium; text in font-color Light-Maroon link to articles not yet started; |
Template:TOC-right In its broadest and most ambitious goal, the academic discipline of cognitive science aims to explain the physiological activity of thinking and feeling, of speaking and other ways humans process symbols, of imagining and remembering, of learning and knowing, of experiencing events of reality consciously, non-consciously and unconsciously, of reasoning and problem-solving, of dreaming, and a host of other physiological activities that we associate with the human living system and refer to as mind.
The University of California at Berkeley offers an undergraduate degree-granting major in ‘Cognitive Science’, and explains the discipline as follows:
Cognitive Science is an interdisciplinary field that has arisen during the past decade at the intersection of a number of existing disciplines, including psychology, linguistics, computer science, philosophy, and physiology. The shared interest that has produced this coalition is understanding the nature of the mind. This quest is an old one, dating back to antiquity in the case of philosophy, but new ideas are emerging from the fresh approach of Cognitive Science. Previously, each discipline sought to understand the mind from its own perspective, benefiting little from progress in other fields because of different methods employed. With the advent of Cognitive Science, however, common interests and theoretical ideas have overcome methodological differences, and interdisciplinary interaction has become the hallmark of this field.[1] [2]
Notably, though the "….shared interest that has produced this coalition is understanding the nature of the mind", the complete webpage purporting to answer the question, “What is Cognitive Science?”, presumes comprehension of the word (or concept of) "mind".
William Bechtel and George Graham, in the introduction to their multi-authored text, A Companion to Cognitive Science,[3] define cognitive science as follows:
The expression 'cognitive science' names a broadly integrated class of approaches to the study of mental activities and processes, broad not just in the sense of including disciplines as varied as philosophy, cognitive psychology, linguistics, computer science, anthropology, and neuroscience, but in the sense that cognitive scientists tend to adopt certain basic, general assumptions about mind and intelligent thought and behavior. These include assumptions that the mind is (1) an information processing system, (2) a representational device, and (3) [in some sense] a computer. Various relations are possible among each of these assumptions; further, they are not shared by all who dub themselves cognitive scientists. Partly because of such relations and failures of uniformity, cognitive science has generated vigorous dialogues concerning the nature of mental activities and processes as well as over the nature of science and the structure of disciplines.[3]
Harvard University offers a webpage promoting a book by cognitive scientist, Phillip Johnson-LairdCite error: Invalid <ref>
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The mind, he says, depends on the brain in the same way as the execution of a program of symbolic instructions depends on a computer, and can thus be understood by anyone willing to start with basic principles of computation and follow his step-by-step explanations.[4]
Margaret Boden’s 2006 book, Mind as Machine: A History of Cognitive Science,[5] views the mind as a machine, though a special one.
In my view, the best way to think about it [cognitive science] is as the study of mind as machine....however, more than one type of machine is relevant here. In a nutshell: some for digital computing, some for cybernetic self-organization or dynamical control. Much of the theoretical—and historical—interest in the field lies in the tension that follows from that fact.[5]
If a 'special' machine, perhaps because mind "emerged" from the interaction of molecular subsystems. Noam Chomsky has stated that "....the evolution of language may involve 'emergence' — the appearance of a qualitatively different phenomenon at a specific stage of complexity of organization."
If so, [Chomsky continues] it would be an interesting, but by no means novel, case of evolution. A similar view is widely held by evolutionary biologists and paleoanthropologists, for example, Ian Tattersall, who suggests more generally that human intelligence is an "emergent quality, the result of a chance combination of factors, rather than a product of Nature's patient and gradual engineering over the eons" [citation]. Still more generally, neuroscientist Vernon Mountcastle, introducing an American Academy of Arts and Sciences collection of essays on the state of the art at the conclusion of "the decade of the brain" that ended the last century, formulates the leading principle of these contributions as the thesis that "Things mental, indeed minds, are emergent properties of brains [my emphasis], . . . produced by principles . . . we do not yet understand" -- and that might derive from laws of nature [citation].[6]
The Stanford Encyclopedia of Philosophy offers these introductory words: Cognitive science is the interdisciplinary study of mind and intelligence, embracing philosophy, psychology, artificial intelligence, neuroscience, linguistics, anthropology, artificial intelligence, artificial life, and control engineering. Its intellectual origins are in the mid-1950s when researchers in several fields began to develop theories of mind based on complex representations and computational procedures. Its organizational origins are in the mid-1970s when the Cognitive Science Society was formed and the journal Cognitive Science began. Since then, more than sixty universities in North America, Europe, Asia, and Australia have established cognitive science programs, and many others have instituted courses in cognitive science.[7] |
Cognitive neuroscientists, George Lakoff and Mark Johnson, emphasize the role of the unconscious mind:
Cognitive science is the scientific discipline that studies conceptual systems. It is a relatively new discipline, having been founded in the 1970s. Yet in a short time it has made startling discoveries. It has discovered, first of all, that most of our thought is unconscious, not in the Freudian sense of being repressed, but in the sense that it operates beneath the level of cognitive awareness, inaccessible to consciousness and operating too quickly to be focused on.[8]
It seems that like many other sciences, cognitive science requires a multi-disciplinary approach to try to explain the workings of what we commonly recognize as 'mind'. Each discipline includes scholars interested in mental processes, or how the mind/brain works, or how the mind/brain/body works. Cognitive science centrally focuses on explaining exactly what we mean by mind, how we view it, what theories we have about it.
Whatever theories we come up with, it seems that we come up with them with our minds. If minds operate as machines, then as living machines, to explain their workings we must take both a reductionist approach — looking at its parts — and a holistic approach — looking at it as a whole — and integrating the two approaches to yield a satisfying explanation that has explanatory and predictive power, and ultimately controlling power — self-controling power.
We begin, then, with an exploration of the concepts of mind that minds have proposed.
Areas of study by cognitive scientists
The interdisciplinary and multidisciplinary character of modern cognitive science reveals itself in even a greatly abbreviated list of definable 'areas of study' engaged in by cognitive scientists:[3]
- Analogy
- Animal Cognition
- Attention
- Brain Mapping
- Cognitive Anthropology[9]
- Cognitive and Linguistic Development
- Cognitive Neuroscience[10] Cite error: Invalid
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tag; invalid names, e.g. too many - Conceptual Change
- Conceptual Organization
- Consciousness
- Decision Making
- Emotions
- Imagery and Spatial Representation
- Language Evolution and Neuromechanisms
- Language Processing
- Linguistic Theory
- Machine Learning
- Memory
- Perception
- Problem Solving
- Reasoning
- Social Cognition
- Unconscious Intelligence
- Understanding Texts
- Word Meaning
Theories of mind
Mind as machine
Once we had the concept of machine and built automata that performed manual activities, we had 'machine as man'. As we built more and more complicated machines, machines that could locomote, manipulate objects, compute, operate in response to logical rules, recognize our speech — we began developing, and advancing developement of, the concept of 'man as machine'. Modern biology continually works out the molecular mechanisms of diverse physiological activities. How could the mind of man exist except as a manifestation of physiological processes. Destroy the brain, destroy the mind. "Mind as machine' entailed by 'man as machine'.
Man as a machine that can think and cummunicate with itself and other machines like it.
Not just think, but show emotion, social skill, and personality; recognize itself; recognize that it recognizes itself. An automously functioning cognition and metacognition machine, intospective and constructive of a detailed representation of aspects of the spatial and temporal reality embedding it.
Some philosophers of mind believe the mind's ability to recognize itself requires a component of reality in addition to those recognized by physicists, specifically something called 'consciousness', fundamental as energy and matter. The conscious mind, a physical machine, but only if physical reality includes 'consciousness' as a fundamental constituent. Perhaps a natural "organizing principle informing matter", call it 'soul'. Descartes came close to that notion, seeing the mind as immaterial and separate from the body, influencing the body through a strategy designed and owned by God.
Others explain cognition as adaptations to achieve fitness for survival, implemented by neurophyiological processes. We learn more and more about the neurophysiology of cognitive processes. We can detect cognitive and emotional adaptations occuring in real-time in the lifetime of individual organisms. The neurophysiology of conscious awareness remains undiscovered, however, explained by competing proposals.
Mechanisms of cognition
Holding refs: [11]
Applied cognitive science and engineering
One of the lesser-known branches of psychology, cognitive psychology deals, significantly, with people not in distress, but trying to move to a higher level of functioning. The discipline deals with how people interact with new concepts in their environment, especially with respect to learning, or the mental processes involved in building skills. These topics are also the foundation on which human factors engineering, instructional technology, and user interface design are built.
Much of the discipline deals with the conscious processes involved in learning, and in processing information that comes from existing and new sources. Bruning defined the cognitive movement as going beyond Skinner's stimulus-response, reflexive behaviorism into conscious learning.[12]
Cognitive psychology is a theoretical perspective that focuses on the realms of human perception, thought, and memory. It portrays learners as active processors of information--a metaphor borrowed from the computer world--and assigns critical roles to the knowledge and perspective students bring to their learning. What learners do to enrich information, in the view of cognitive psychology, determines the level of understanding they ultimately achieve. — Roger H. Bruning[13]
While Hofstetter describes a fundamental paradigm shift, experience in gaining certain skills may also draw from the behaviorists. "If faculty members can learn to shift their pedagogical paradigm from teacher-dominated to learner-centered, students will become more actively involved in the teaching and learning process. At the end of a course, instead of having been trained in the digestion of existing knowledge, students will have become able to continue finding, judging, critiquing, synthesizing, and constructing new knowledge... students will have become truly educated, not just trained." [12] Nevertheless, to take the quite different example of flying an advanced combat aircraft, developing the eye-hand coordination to merge the pilot's vision outside supplemented heads-up displays and pilot-selected "glass cockpit" displays, which are controlled from buttons and switches on controls operated without looking at them, can take a year increasingly of simulator and aircraft experience. While this may have behaviorist aspects, it is complemented by highly interactive classroom work on alternative tactics, emergency procedures, and the theory of one's aircrft and weapons. In contrast, cognitive psychologists involved in automobile safety suggest that adding heads-up displays to cars, without a very explicit training program, may cause information overload in the untrained driver.
Information and decision flow in the OODA paradigm
John Boyd, one of the pioneers of high-speed decisionmaking in the modern military, has a cognitive model at the core of his theories, the decision cycle or OODA Loop, the process by which an entity (either an individual or an organization) reacts to an event. According to this idea, the key to victory is to be able to create situations wherein one can make appropriate decisions more quickly than one's opponent.
Boyd theorized that multilevel contexts, such as the tactical, operational, and strategic levels of war, can be modeled with a hierarchy of OODA loops (see below).[14] He also argued that fast OODA loops require a highly decentralized command and control using mission-type orders, or directive control (i.e., what the commander wants to see happen) as opposed to detailed control (i.e., how the commander wants things done. Such a structure, according to Boyd, would create a flexible "organic whole" that would be quicker to adapt to rapidly changing situations. He noted, however, that any such highly decentralized organization would necessitate a high degree of mutual trust and a common outlook that came from prior shared experiences. Headquarters needs to know that the troops are perfectly capable of forming a good plan for taking a specific objective, and the troops need to know that Headquarters does not direct them to achieve certain objectives without good reason. [14]
The OODA model of decision and action, originally for air-to-air fighter combat, has four phases. This discussion adds interaction with intelligence and command.
- Observe: become aware of a threat or opportunity
- Orient: put the observation into the context of other information; form one's perspective and situational awareness
- Decide: make the best possible action plan that can be carried out in a timely manner
- Act: carry out the decision.
After the action, the actor observes again, to see the effects of the action. If the cycle works properly, the actor has initiative, and can orient, decide, and act even faster in the second and subsequent iterations of the Boyd loop.
Eventually, if the Boyd process works as intended, the actor will "get inside the opponent's loop". When the actor's Boyd cycle dominates the opponent's, the actor is acting repeatedly, based on reasoned choices, while the opponent is still trying to understand what is happening.
Modes of learning
Individual human beings differ in the way they best learn new information. One common distinction uses:
- visual: accepting input through vision, testing action through writing and drawing
- auditory: receiving spoken input and refining it through discussion
- tactile: absorbing information through highly eye-hand interactive interfaces or developing physical skills, improving the skill by interaction.
There is an unfortunate trend, in areas such as industry-specific skills and certification training, to overemphasize the tactile, and insisting that as much learning as possible be "hands on". That may be realistic for computer configuration and troubleshooting, but design skills tend to be visual and collaborative, expressed through drawings, drafting documents, and discussion.
Another unfortunate trend is to recognize that some people learn from all these methods, so, whether individual remote instruction or the classroom, multimedia presentation is important -- but, ideally, it should be possible to select the delivery mode. Auditory or visual input may be useless to people with disorders of the ears or eyes.
Depending on the topic, however, the learner may need a theoretical base for what is presented in the multimedia experience, but, even there, the learning should be participatory. Lecturers who frequently turn to the class with questions and followup discussion, using their expertise to stay on track, encourage original thought. Such thought is reinforced with frequent individual and team exercises that require synthesis of concepts, often with multimedia or interpersonal interaction.
Patterns of creating knowledge
Sometimes called a trend to "big science", many fundamental research problems are sufficiently complex to need a team effort. In areas such as particle physics and space science, it will take a mixture of skills simply to conduct the experiments.
Collaboration, however, may be a key part of learning and creating. As mentioned above, some classroom experiences deliberately include team exercises. A review of scientific publication showed the greatest growth in research by three authors [15]
Cognitive traps
Within the United States intelligence community and other areas where decisions must be made on incomplete knowledge, there is ever-growing awareness that cognitive errors come from poorly structured cognition and lack of collaboration. [16]
References
- ↑ Cognitive Science: What is Cognitive Science? University of California at Berkeley.
- ↑ Note: The interdisciplinary nature of the discipline at Berkeley reveals itself in the various areas of expertise of its core faculty, which include: Psychology; Education; Computer Science; Optometry; Integrative Biology; Philosophy Gender and Women's Studies; Cognitive Science & Electrical Engineering; Anthropology; Psychology, Neuroscience; Linguistics; Information; Cognitive Science and Psychology; Molecular and Cell Biology; Sociology.
- ↑ 3.0 3.1 3.2 Bechtel W., Graham G. (editors) (1998) A Companion to Cognitive Science. Malden, Mass: Blackwell. ISBN 1557865426 (hardcover).
- ↑ Cite error: Invalid
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- ↑ 5.0 5.1 Boden M. (2006) Mind as Machine: A History of Cognitive Science. ISBN 9780199241446, ISBN 0199241449.
- From the publisher's description: The key distinguishing characteristic of cognitive science, Boden suggests, compared with older ways of thinking about the mind, is the notion of understanding the mind as a kind of machine....Cognitive science, in Boden's broad conception, covers a wide range of aspects of mind: not just 'cognition' in the sense of knowledge or reasoning, but emotion, personality, social communication, and even action.
- ↑ Chomsky N. (2007) Symposium on Margaret Boden, Mind as Machine: A History of Cognitive Science Artificial Intelligence 171:1094-1103.
- ↑ Science Cognitive Science. The Stanford Encyclopedia of Philosophy. First published Mon Sep 23, 1996; substantive revision Mon Apr 30, 2007.
- ↑ Lakoff G, Johnson M. (1999) Philosophy in the Flesh: The Embodied Mind and Its Challenge to Western Thought. Basic Books ISBN 0465056741, ISBN 9780465056743.
- Publisher's description What are human beings like? How is knowledge possible? What is truth? Where do moral values come from? Questions like these have stood at the center of Western philosophy for centuries. In addressing them, philosophers have made certain fundamental assumptions—that we can know our own minds by introspection, that most of our thinking about the world is literal, and that reason is disembodied and universal—that are now called into question by well-established results of cognitive science. It has been shown empirically that: Most thought is unconscious. We have no direct conscious access to the mechanisms of thought and language. Our ideas go by too quickly and at too deep a level for us to observe them in any simple way. Abstract concepts are mostly metaphorical. Much of the subject matter of philosopy, such as the nature of time, morality, causation, the mind, and the self, relies heavily on basic metaphors derived from bodily experience. What is literal in our reasoning about such concepts is minimal and conceptually impoverished. All the richness comes from metaphor. For instance, we have two mutually incompatible metaphors for time, both of which represent it as movement through space: in one it is a flow past us and in the other a spatial dimension we move along. Mind is embodied. Thought requires a body—not in the trivial sense that you need a physical brain to think with, but in the profound sense that the very structure of our thoughts comes from the nature of the body. Nearly all of our unconscious metaphors are based on common bodily experiences. Most of the central themes of the Western philosophical tradition are called into question by these findings. The Cartesian person, with a mind wholly separate from the body, does not exist. The Kantian person, capable of moral action according to the dictates of a universal reason, does not exist. The phenomenological person, capable of knowing his or her mind entirely through introspection alone, does not exist. The utilitarian person, the Chomskian person, the poststructuralist person, the computational person, and the person defined by analytic philosopy all do not exist. Then what does? Lakoff and Johnson show that a philosopy responsible to the science of mind offers radically new and detailed understandings of what a person is. After first describing the philosophical stance that must follow from taking cognitive science seriously, they re-examine the basic concepts of the mind, time, causation, morality, and the self: then they rethink a host of philosophical traditions, from the classical Greeks through Kantian morality through modern analytic philosopy. They reveal the metaphorical structure underlying each mode of thought and show how the metaphysics of each theory flows from its metaphors. Finally, they take on two major issues of twentieth-century philosopy: how we conceive rationality, and how we conceive language. Philosopy in the Flesh reveals a radically new understanding of what it means to be human and calls for a thorough rethinking of the Western philosophical tradition. This is philosopy as it has never been seen before.
- ↑ Roberston T, Beasley D. [h ttp://www.as.ua.edu/ant/Faculty/murphy/436/coganth.htm Cognitive Antropology] Department of Anthropology College of Arts and Sciences The University of Alabama.
- From the website: Cognitive anthropology is an idealist approach to studying the human condition. The field of cognitive anthropology focuses on the study of the relation between human culture and human thought. In contrast with some earlier anthropological approaches to culture, cultures are not regarded as material phenomena, but rather cognitive organizations of material phenomena (Tyler 1969:3).
- Cognitive anthropologists study how people understand and organize the material objects, events, and experiences that make up their world as the people they study perceive it. It is an approach that stresses how people make sense of reality according to their own indigenous cognitive categories, not those of the anthropologist.
- Cognitive anthropology posits that each culture orders events, material life and ideas, to its own criteria.
- The fundamental aim of cognitive anthropology is to reliably represent the logical systems of thought of other people according to criteria, which can be discovered and replicated through analysis.
- ↑ Gazzaniga,Michael S.; Ivry,Richard B.; Mangun,G.R. (2009) Cognitive Neuroscience: The Biology of the Mind. 3rd edition. W. W. Norton & Company. ISBN 9780393927955 (hbk.)
- Publisher's Overview: Three leading figures in the field of cognitive neuroscience provide an engaging, narrative driven overview of this path-breaking field. Taking a highly interdisciplinary approach, the authors balance cognitive theory, with neuroscientific and neuropsychological evidence to reveal what we currently know about how the human mind works and to encourage students to think like cognitive neuroscientists. The text has been reorganized to move more seamlessly from micro to macro level topics, and its underlying pedagogy strengthened in order to make it an even more effective teaching tool. Maintaining its commitment to highlight the most cutting-edge trends in the field, the third edition includes the first ever standalone chapter of its kind on social neuroscience.
- Contents:
- Part 1: Background and Methods
- Chapter 1 - A Brief History of Cognitive Neuroscience
- Chapter 2 - The Cellular and Molecular Basis of Cognition
- Chapter 3 - Neuroanatomy and Development
- Chapter 4 - The Methods of Cognitive Neuroscience
- Part 2: Core Processes
- Chapter 5 - Sensation and Perception
- Chapter 6 - Object Recognition
- Chapter 7 - Action
- Chapter 8 - Learning and Memory
- Chapter 9 - Emotion
- Chapter 10 - Language (with Tamara Y. Swaab)
- Chapter 11 - Hemispheric Specialization
- Part 3: Control Processes
- Chapter 12 - Attention and Consciousness
- Chapter 13 - Executive Function
- Chapter 14 - The Social Brain (by Jennifer S. Beer)
- Chapter 15 - Evolutionary Perspectives (with Jeff Hutsler)
- ↑ Anderson M. (2007) Massive redeployment, exaptation, and the functional integration of cognitive operations. Synthese 159:329-45.
- Abstract: The massive redeployment hypothesis (MRH) is a theory about the functional topography of the human brain, offering a middle course between strict localization on the one hand, and holism on the other. Central to MRH is the claim that cognitive evolution proceeded in a way analogous to component reuse in software engineering, whereby existing components—originally developed to serve some specific purpose—were used for new purposes and combined to support new capacities, without disrupting their participation in existing programs. If the evolution of cognition was indeed driven by such exaptation, then we should be able to make some specific empirical predictions regarding the resulting functional topography of the brain. This essay discusses three such predictions, and some of the evidence supporting them. Then, using this account as a background, the essay considers the implications of these findings for an account of the functional integration of cognitive operations. For instance, MRH suggests that in order to determine the functional role of a given brain area it is necessary to consider its participation across multiple task categories, and not just focus on one, as has been the typical practice in cognitive neuroscience. This change of methodology will motivate (even perhaps necessitate) the development of a new, domain-neutral vocabulary for characterizing the contribution of individual brain areas to larger functional complexes, and direct particular attention to the question of how these various area roles are integrated and coordinated to result in the observed cognitive effect. Finally, the details of the mix of cognitive functions a given area supports should tell us something interesting not just about the likely computational role of that area, but about the nature of and relations between the cognitive functions themselves. For instance, growing evidence of the role of “motor” areas like M1, SMA and PMC in language processing, and of "language" areas like Broca’s area in motor control, offers the possibility for significantly reconceptualizing the nature both of language and of motor control.
- ↑ 12.0 12.1 Hofstetter, Fred T. (1995), Chapter 4: Cognitive Versus Behavioral Psychology, Multimedia Literacy, McGraw-Hill
- ↑ Roger H. Bruning, Schraw, G. J., and R. R. Ronning (1995), Cognitive Psychology and Instruction, Prentice Hall
- ↑ 14.0 14.1 Hammond, Grant T., The Essential Boyd
- ↑ "Publication Statistics Show Collaboration, Not Competition", Association for Psychologic Science Observer 21 (6), June/July 2008
- ↑ Heuer, Richards J. Jr. (1999). Psychology of Intelligence Analysis. Chapter 2. Perception: Why Can't We See What Is There To Be Seen?. History Staff, Center for the Study of Intelligence, Central Intelligence Agency.