Kevin Niall Dunbar grew up in Bray, County Wicklow, Ireland. He attended University College, Dublin, obtaining a B.A. in Logic and Psychology in 1977, where he conducted research on the development of spatial reasoning in children. In 1979 he received an M.A. for his research on the ways that everyday categories influence memory. In 1980 he began his PhD. at the Department of Psychology of the University of Toronto and worked with Professor Colin MacLeod on the roles of Executive functions involved in the allocation of attention. They developed a continuum of automaticity account of controlled and automatic processes, using the Stroop task.
He conducted his postdoctoral work at Carnegie Mellon University in Pittsburgh under Professor David Klahr, researching the development of scientific thinking in both Children and Adults. They proposed the Scientific Discovery as Dual Search model of of Scientific Thinking (SDDS). The model shows the sequence of mental processes that children and adults go through when designing experiments and testing hypotheses and accounts for developmental differences in Scientific thinking using a problem solving framework. While at Carnegie Mellon, Dunbar also collaborated with Jonathan Cohen and James McClelland and they developed an influential Parallel Distributed Processing model of Attention and Automaticity that modeled Dunbar's earlier work on the Stroop task. This type of Neural Network model underlies many contemporary models of Executive functions and automaticity that involve the concepts of inhibition and cognitive control.
In 1988 he moved to McGill University in Montreal to become Assistant professor of Psychology. He continued his work on scientific thinking and discovery applying it to an important scientific domain- Molecular Biology. At McGill he pioneered a new method for delineating the reasoning and learning processes involved in real-world Science. He recorded and analyzed the thinking and reasoning patterns of world renowned scientists as they worked at their lab meetings. This "invivo-invitro approach" has been used to study complex thinking in many different domains and is important for understanding the ways that people learn. While at McGill he also pursued an interest in joining his thinking and reasoning research with his Executive function research, collaborating with Professor Daniel Bub, who was then a professor at the Montreal Neurological Institute. Prof. Dunbar was promoted to Associate and then Full professor at McGill University.
He was recruited by Dartmouth College in 2001 and appointed Professor of Education as well as Professor of Psychological and Brain Sciences. Here he conducted behavioral and neuroimaging research on Analogical, Scientific, and Causal Reasoning, as well as the executive functions underlying these reasoning processes. At Dartmouth, Professor Laura-Ann Petitto and he initiated the field of Educational Neuroscience and established the Center for Cognitive & Educational Neuroscience - an NSF funded Science of Learning Center (with co-founders Michael Gazzaniga, Scott Grafton, & Todd Heatherton). Dunbar also co-wrote (with Professors Petitto and Gazzaniga) and obtained a large grant from the Dana foundation on the effects of a performing arts education on the brain.
He was at the University of Toronto from 2008-2011 and is now Professor of Human Development & Quantitative Methodology at the University of Maryland College Park, just outside Washington DC. He directs the Laboratory for Thinking, Reasoning, Creativity & Educational Neuroscience. His current projects involve the exploration of the mental processes underlying Learning in many domains. He has been focusing on the roles of Analogy, Causal Reasoning, Categorization, in the domains Scientific Thinking and Creativity. He uses multiple methodologies ranging from Observational studies of students and scientists to Cognitive experiments and Neuroimaging studies.
His current work is both observational and experimental. He works closely with undergraduate and graduate students on the ways that we Learn, think and reason in both Science and the Arts. Volunteers, graduate students and postdoctoral fellows are also welcome in the lab.
He was also awarded a Visiting Research Professorship in the Faculty of Education at the University of Hong Kong in 2015 where he collaborates with faculty members conducting research on the Science of Learning in the Faculty of Education.
Psychologie: Kreativität mit wenig Hirnschmalz kann jeder
Mar 10, 2016
Manche wollten schon immer aus Eisblöcken eiskalte Minions formen – andere möchten einfach flottere Ideen haben. Dafür gibt es mehrere ...
«¿De dónde vienen las buenas ideas?»
Steven Johnson. Gràffica
Oct 23, 2016
Hace unos años un gran investigador llamado Kevin Dunbar .... en Laurel, Maryland, en el laboratorio de física aplicada en conjunto con la ...
Ini cara mudah untuk tingkatkan kreativitas
Mar 1, 2016
... sebuah penelitian di University of Maryland menyebutkan bahwa ... Dalam penelitian, Denis Dumas dan Kevin Dunbar selaku peneliti ...
To be more creative, a study suggests imagining yourself as an ...
Mar 7, 2016
In the first experiment, study authors Denis Dumas and Kevin Dunbar from the University of Maryland recruited 96 American undergraduate ...
How to be more creative - it's surprisingly simple
Mar 4, 2016
Study authors Denis Dumas and Kevin Dunbar, from the university's Department of Human Development and Quantitative Methodology, asked ..
A Simple Way to Spark Creativity
Mar 1, 2016
To determine if creativity can be similarly impacted by this form of identification, Dumas and Dunbar conducted two experiments. The first ...
Where Do New Ideas Come From?
by Annie Murphy Paul, ATD (blog)
Aug 15, 2015
Analogies are still frequently used by scientists working today, as University of Maryland professor Kevin Dunbar discovered when he observed ..
What does this allow us to do? The scientists Kevin Dunbar studied used analogies, first, to formulate hypotheses that they could then test. Their thought process went something like this: “If we know that X does Y when Z, is it possible that A does Y when Z, too? Let’s find out.” That’s often how innovations get their start, in the lab and elsewhere—by taking a familiar starting point and using it as a launch pad to explore new territory. Psychologist and author Steven Pinker, who has composed many illuminating analogies himself, notes that “carefully interpreted, analogies are not just alluring frames but actual theories, which make testable predictions and can prompt new discoveries.” Case in Point Dunbar’s scientists found analogies useful as sense-making tools when they encountered anomalies or unexpected findings in the course of their work. This was also the case for another group of scientists whose use of analogy became the subject of study: scientists working on the Mars Rover mission.
The Key To Innovation: Making Smart Analogies
Mar 29, 2014
Analogies are still frequently used by scientists working today, as University of Maryland professor Kevin Dunbar discovered when he observed ...
In a 2003 study, Kevin Dunbar, a psychologist at the University of Maryland, showed undergraduates a few short videos of two different-sized ...
Comment le cerveau apprend-il?
Pauline Gravel, Science et technologie
Le Devoir, 23 avril 2011
La neuroéducation, qui vise à savoir ce qui se passe dans le cerveau, à l'aide des techniques d'imagerie cérébrale, lors de l'apprentissage, a permis de mieux comprendre ce phénomène et d'imaginer des pistes d'intervention qui favorisent davantage l'apprentissage.
C'est ainsi que l'un des pionniers de la neuroéducation, le psychologue Kevin Dunbar de l'Université de Toronto, a présenté à des étudiants deux courts films mettant en scène deux balles de tailles différentes: dans le premier film, les balles tombaient à une vitesse identique — comme l'avait expérimenté Galilée en laissant tomber des boulets de canon de grosseurs différentes du sommet de la tour de Pise; dans le second film, elles tombaient à des vitesses différentes, la plus grosse atteignant le sol en premier. L'équipe de M. Dunbar a enregistré l'activité du cerveau des étudiants à l'aide d'un appareil de résonance magnétique fonctionnelle, tandis que ceux-ci visionnaient les films et devaient déterminer laquelle des deux séquences respectait la loi de la gravitation de Newton, selon laquelle la vitesse de chute de corps de masses différentes est identique. Comme prévu, la plupart des étudiants qui n'avaient reçu qu'une formation minimale en physique au secondaire ont trouvé irréaliste la séquence où les deux balles tombent à la même vitesse et ont opté pour celle où la grosse balle était plus rapide que la petite.
Le visionnement du film newtonien qui leur apparaissait aberrant a induit chez eux l'activation du cortex cingulaire antérieur (CCA), un collier de tissu nerveux situé dans le centre du cerveau qui s'active lorsque nous détectons une anomalie, une erreur, ou lorsque nous sommes confrontés à une information qui contredit nos propres théories.
Étrangement, les quelques novices en physique qui avaient identifié correctement la séquence en accord avec la loi de Newton présentaient également une activation du CCA. «Cette activation nous indique que, même si ces étudiants ont donné la bonne réponse, ils n'y croient pas vraiment», explique Kevin Dunbar. L'activation du CCA signifie probablement que leur cerveau n'a pas complètement intégré et compris cette notion. Ces étudiants n'avaient pas «réalisé le changement conceptuel» qu'ont effectué les experts.
Chez les experts, qui avaient réussi au moins cinq cours de physique de niveau universitaire, c'est la projection du film présentant la version erronée de la réalité qui a induit dans leur cerveau l'activation du CCA. Cette séquence a également provoqué l'activation du cortex préfrontal dorsolatéral, qui joue un rôle dans la suppression des représentations non désirées. «L'activation simultanée de ces deux régions cérébrales est un signe que la personne est en train d'inhiber l'information», explique M. Dunbar.
TheScientist: Innovations 'R' Us
by Sarah Greene
Decemeber 01, 2010
"Then there’s the story of psychologist Kevin Dunbar, who visited labs around the world, videotaping scientists as they worked—with the goal of understanding how they formulated their important ideas. He concluded that the wide majority of breakthrough concepts originated not in solitary moments at the lab bench, but rather at weekly lab meetings when scientists shared data, findings, errors, and conflicting results."
Canadian Business Magazine: Book review: Why Eureka! is a Myth
by CB Online
November 22, 2010
" Observing four of the world's top molecular biology labs, Dunbar tracked the scientists' actions and interactions, and conducted extensive interviews with the scientists throughout the study to overcome people's tendency to condense the origins of their best ideas into pat little stories. Eureka moments were thin on the ground; Dunbar instead discovered that great ideas are born of something more complex.”
The Huffington Post: How Not to Save the World
by Harry Roman
October 22, 2010
" Dunbar talked about risk aversion and how a lack of diversity of thought held research scientists back from explaining unexpected findings. From Schulz we learned about error blindness and that believing that we are right can be dangerous in how we approach problem solving.”
Inc.: Where Good Ideas Come From
by Jack Covert
October 21, 2010
" Dunbar's study showed that those isolated eureka moments were rarities. Instead, most important ideas emerged during regular lab meetings, where a dozen or so researchers would gather and informally present and discuss their latest work. If you looked at the map of idea formation that Dunbar created, the ground zero of innovation was not the microscope. It was the conference table.”
Reuters: Poptech 2010
October 21, 2010
" Up Next: Kevin Dunbar, Psychologist who studies the impact of failure on our brains. #poptech
National Post: How Ideas are Born
by Kathryn Carlson
October 09, 2010
" In the early 1990s, McGill University psychologist Kevin Dunbar watched scientists as they worked — a Big Brother approach to observation. He watched as they worked in the laboratory, questioned one another, and met for brainstorming sessions. He found that the most important good ideas could not be traced back to the lab itself, but rather to those regular lab meetings. “If you looked at the map of idea formation that Dunbar created, the Ground Zero of innovation was not the microscope,” Mr. Johnson writes. “It was the conference table.”
Wired Magazine: Accept Defeat: The Neuroscience of Screwing Up
by Jonah Lehrer
December 21, 2009
"Dunbar came away from his in vivo studies with an unsettling insight: Science is a deeply frustrating pursuit. Although the researchers were mostly using established techniques, more than 50 percent of their data was unexpected. (In some labs, the figure exceeded 75 percent.) “The scientists had these elaborate theories about what was supposed to happen,” Dunbar says. “But the results kept contradicting their theories. It wasn’t uncommon for someone to spend a month on a project and then just discard all their data because the data didn’t make sense.” Perhaps they hoped to see a specific protein but it wasn’t there. Or maybe their DNA sample showed the presence of an aberrant gene. The details always changed, but the story remained the same: The scientists were looking for X, but they found Y."
The Toronto Star: Searching the frontiers of science
by Peter Calamai
November 30, 2008
"...Kevin Dunbar and Laura-Ann Petitto found that artists had a much higher incidence of variants of two genes involved in novelty- seeking, attention, memory and problem-solving than people with little involvement in the arts. These particular genes regulate the flow of dopamine, a key chemical messenger in the brain..."
Science News: Creativity may have genetic roots
by Bruce Bower
November 19, 2008
"A study comparing performing artists to people with little or no experience in the arts found that many of the artists inherited variants of two genes involved in novelty-seeking, attention, memory and problem solving. The variants appeared in only one of the non-artists.
"These particular genes may influence the development of creative achievement in at least some individuals, across a variety of fields, proposes a team led by Kevin Dunbar and Laura Petitto, both of the University of Toronto.
"Variants of the two genes were found in 15 of 58 professional dancers, musicians and actors—about one-quarter of them—versus only one of 36 comparison individuals. The genes, called DRD4 and COMT, influence transmission of dopamine, a chemical messenger in the brain.
"'Combinations of genetic variants, rather than specific genetic variants, may be linked to pursuing and achieving expertise in creative activities,' Petitto says.
"Brain imaging studies of the same participants indicate that, relative to the comparison group, performing artists display much more activity in a frontal brain region critical for remembering and manipulating different pieces of information at once. This disparity may partly result from intense, long-term practice of creative endeavors by performing artists, in addition to any genetic advantage, Petitto says.
"The Toronto researchers plan to look for additional gene variants linked to creative expertise. They also hope to include acclaimed creative virtuosos in their experiments."
The Infinite Mind public radio show: How We Think
by Dr. Fred Goodwin
March 13, 2007
"...Dr. Goodwin interviews Dr. Kevin Dunbar of Dartmouth, who studies how people think, reason, and solve problems. Dr. Dunbar has been investigating how scientists' minds work and what actually happens when they make discoveries. He says we have an image of the lone, white, male scientist working under a lightbulb, shouting out, 'Eureka! I've found it!' Scientists tend to reinforce this image, often crediting their discoveries to chance. In reality, as Dr. Dunbar learned by studying actual lab meetings for a year, discoveries are made through collaborative thinking and reasoning..."
New Scientist: Bad habits...that could help you get ahead
by Helen Phillips
March 24, 2006
"...According to a study by Fugelsang and colleague Kevin Dunbar of Dartmouth College in Hanover, New Hampshire, our brains are predisposed to learn information consistent with our convictions. When they showed people information that fitted with a theory they believed in, the areas of the brain devoted to learning became active, and the information was effectively assimilated into their views..."
Monitor on Psychology: Psychological science branches out
by Sadie F. Dingfelder
"...In the spirit of collaboration, CCEN researchers will work with educators at the nearby Montshire Museum of Science. They will use the museum to test new ways to display information while also helping museum staff apply new research on the learning. For example, an as-yet-unpublished, NASA-funded study by Dartmouth psychology professor Kevin Dunbar, PhD, recently found that the usual way textbooks and videotapes illustrate the Earth's tilt and the resulting seasons--with two-dimensional models showing the earth half in shadow--leaves many people confused and misinformed.... Under the new CCEN grant, Dunbar will collaborate with education experts and museum officials to design an exhibit on seasons that does a better job illustrating the astronomy--perhaps using a three-dimensional model...."
Financial Times: Dartmouth College: Dartmouth wins grant for neuroscience center
by Kelsey Blodget
February 4, 2005
"A team of Dartmouth researchers headed by former Dean of the Faculty and cognitive neuroscience pioneer Michael Gazzaniga beat out dozens of colleges across the nation Tuesday to receive the National Science Foundation's $21.8 million grant, the largest peer-reviewed grant ever awarded to the College, to establish a new Center for Cognitive and Educational Neuroscience...
"'For years, someone would come up with an idea for teaching something, find out the method doesn't work five years later, and then move onto the next fad,' education and psychology professor Kevin Dunbar, one of the CCEN's co-principal investigators, said. 'But there was no science underlying it.' Dartmouth spearheaded the creation of educational neuroscience, a new academic field, in response to this problem. The study of how the brain learns will shed light on how best to instruct children in science, math, reading and language..."
New Scientist: Why is physics so difficult?
October 23, 2004
"If you struggled with physics as a teenager, it might be because your brain was clinging to misconceptions about science.
"Kevin Dunbar, a cognitive scientist at Dartmouth University in Hanover, New Hampshire, and his colleagues scanned the brains of students while they watched a video demonstrating either classical Newtonian physics, in which a large and a small ball fall to the ground at the same speed, or the naive scenario, in which the larger ball drops faster..."
Washington Post: Researchers Go From A to B to Discovery
by Rick Weiss
January 26, 1998
"...This more nuanced, if less cinematic, view of science has emerged in part from a remarkable series of studies led by a psychologist who spent two full years directly observing scientists at work in their laboratories. That effort, by Kevin Dunbar of McGill University in Montreal, suggests that scientists themselves often are surprisingly deluded about how they and their colleagues work. Many scientists are even mistaken about how they arrived at their own discoveries.
"'There are all these myths and stories,' Dunbar said. "But no one has really watched [scientists] to see what they really do. No one has asked, 'What are the mental processes that scientists use when they think and reason every day, and how do they make discoveries?'..."
Realty Times: Transforming Tomorrow
by Kathy Lamancusa
October 18, 2000
"...Kevin Dunbar, a psychologist at McGill University in Montreal, extends this finding by pointing out that the more creative scientific laboratories thrive in the presence of colleagues with dissimilar backgrounds and specialties. Dunbar argues that this diversity of researchers allows reasoning from analogous situations. Analogous situations suggest novel approaches, whereas the laboratories staffed with researchers who have similar backgrounds and specialties lack the insights provided by many..."
Chemical Engineering Progress: How discoveries are really made
March 1, 1998
"The folklore of science is rife with tales of a lone scientist making a dramatic discovery due to a flash of insight. But, is this how scientific breakthroughs are typically made?
"Not according to a study by Kevin Dunbar of McGill University in Montreal, a cognitive psychologist who spent two years directly observing scientists at work. Dunbar's study found that most discoveries are collaborative affairs involving many participants with varying backgrounds. And, he found that, many times, the scientists themselves are often surprisingly deluded about how they and their colleagues work, even how they arrive at their discoveries..."
Dumas, D., & Dunbar, K.N. (2016). The Creative Stereotype Effect. PLOS ONE | DOI:10.1371/journal.pone.0142567 February 10, 2016
Dumas D., Dunbar K. N. (2014). Understanding fluency and originality: A latent variable perspective. Thinking Skills and Creativity, 14, 56–67
Byrnes, J.P., & Dunbar, K.N. (2014). The nature and development of Critical-Analytic Thinking, Educational Psychology Review. DOI 10.1007/s10648-014-9284-0
Dumas, D., Dunbar, K. N. (2014). Understanding fluency and originality: A latent variable perspective. Thinking Skills and Creativity, 14, 56–67.
Dumas, D., Alexander, P. A., Baker, L. M., Jablansky, S., Dunbar, K. N. (2014). Relational Reasoning in medical education: patterns in discourse and diagnosis. Journal of Educational Psychology. 106, 1021-1035.
Dunbar, K.N. and Forster, E.A. Scientific Thinking. (2013). Encyclopedia of the Mind. Thousand Oaks, CA: Sage
Green, A., Kraemer, D.J.M., Fugelsang, J., Gray, J.R., & Dunbar, K.N (2012). Mapping Across Semantic Distance in Creative Analogical Solution Generation. Journal of Experimental Psychology: Learning, Memory, and Cognition
Bassok, M., Dunbar, K. N., & Holyoak, K. J. (2012). Neural substrate of analogical reasoning and metaphor comprehension: Introduction to the special section. Journal of Experimental Psychology: Learning, Memory, and Cognition.
Dunbar K. N. (2012). Educational Neuroscience: Applying the Klahrian Method to Science Education. In S. Carver & J. Shrager (Eds.), The journey from child to scientist: Integrating cognitive development and the education sciences. Washington, D.C.: American Psychological Association.
Dunbar, K. N. & Klahr, D. (2012). Scientific Thinking & Reasoning. K.J. Holyoak, R. Morrison (Eds.) Oxford Handbook of Thinking & Reasoning.
Green, A.E., & Dunbar, K.N. (2012). Mental Function as Genetic Expression: Emerging Insights from Cognitive Neurogenetics. In K.J. Holyoak, R. Morrison (Eds.) Oxford Handbook of Thinking & Reasoning.
Green, A., Kraemer, D., Fugelsang, J., Gray, J., & Dunbar, K. (2010). Connecting long distance: semantic distance in analogical reasoning modulates frontopolar cortex activity. Cerebral Cortex, 20(1), 70-76. PDF
Fischer, K.W., Goswami, U., Geake, J. & Task Force on the Future of Educational Neuroscience. Members of the Task Force: Daniel Bullock, James Byrnes, Kevin Dunbar, Guineviere Eden, Julie Fiez, Kurt Fischer (co-chair), Daniel J. Franklin, John Geake (co-chair), Usha Goswami (co-chair), Sharon Griffin, Patricia Kuhl, Bruce McCandliss, Vinod Menon, Ennio Mingolla, Nora Newcombe, Tomas Paus, Kevin Pelphrey, Russ Poldrack, L. Todd Rose, Reed Stevens, Rosemary Tannock, Jennifer Thomson, and Lee A. Thompson (2010). The future of educational neuroscience Mind Brain and Education, 4, 68-80.
Forster, E., & Dunbar, K. (2009). Creativity evaluation through latent semantic analysis. Proceedings of the Cognitive Science Society 2009 (pp. 602-607). Amsterdam: Cognitive Science Society. PDF
Fugelsang, J., & Dunbar, K. (2009). Brain-based mechanisms underlying causal reasoning. In E. Kraft (Ed.), Neural correlates of thinking (pp. 269-279). Germany: Springer Berlin Heidelberg. PDF
Roser, M., Fugelsang, J., Handy, T., Dunbar, K., & Gazzaniga, M. (2009). Representation of physical plausibility revealed by event-related potentials. Cognitive Neuroscience and Nseuropsychology, 20(12), 1081-1086. PDF
Dunbar, K. N. (2009). The Biology of physics: what the brain reveals about our understanding of the physical world. Proceedings of the Physics Education Research Conference (pp. 15-18). Ann Arbor: AAPT. PDF
Atkins, L. J., Velez, L., Goudy, D., & Dunbar, K. N. (2009). The unintended effects of interactive objects and labels in the science museum. Science Education, 93, 161-184. PDF
Green, A. E., Fugelsang, J. A., Kraemer, D. J., & Dunbar, K. N. (2008). The micro-category account of analogy. Cognition, 106, 1004–1016. PDF
Dunbar, K., Fugelsang, J., & Stein, C. (2007). Do naïve theories ever go away? In M. Lovett, & P. Shah (Eds.), Thinking with Data: 33rd Carnegie Symposium on Cognition. Mahwah, NJ: Erlbaum. PDF
Green, A., Fugelsang, J., Shamosh, N., Kraemer, D., & Dunbar, K.N. (2006). Frontopolar Cortex Mediates Abstract Integration in Analogy. Brain Research. PDF
Green, A., Fugelsang, J., Dunbar, K.N. (2006). Automatic activation of categorical and abstract analogical relations in analogical reasoning. Memory and Cognition. PDF
Dunbar, K., & Fugelsang, J. (2006). Problem solving and reasoning. In E. E. Smith & S. M. Kosslyn (Eds.), Cognitive Psychology: Mind and Brain. New York: Prentice Hall. PDF
Fugelsang, J., Thompson, V., & Dunbar, K. (2006) Examining the representation of causal knowledge. Journal of Thinking and Reasoning, 12, 1-30. PDF
Roser, M., Fugelsang, J., Dunbar, K., Corballis, P., & Gazzaniga, M. (2005). Dissociating processes supporting causal perception and causal inference in the brain. Neuropsychology, 19(5), 591-602. PDF
Dunbar, K., & Fugelsang, J. (2005). Scientific thinking and reasoning. In K. J. Holyoak & R. Morrison (Eds.), Cambridge Handbook of Thinking & Reasoning, Cambridge Univ. Press. Pp. 705-726. PDF
Fugelsang, J., Roser, M., Corballis, P., & Gazzaniga & Dunbar, K., (2005). Brain Mechanisms Underlying Perceptual Causality. Cognitive Brain Research, 24, 41-47. PDF
Fugelsang, J., & Dunbar, K. (2005). Brain-based mechanisms underlying complex causal thinking. Neuropsychologia, 43, 1204-1213. PDF
Dunbar, K., & Fugelsang, J. (2005). Causal thinking in science: How scientists and students interpret the unexpected. In M. E. Gorman, R. D. Tweney, D. Gooding & A. Kincannon (Eds.), Scientific and Technical Thinking. Mahwah, NJ: Lawrence Erlbaum Associates. Pp. 57-80.
Fugelsang, J. & Dunbar, K. (2004). A cognitive neuroscience framework for understanding causal reasoning and the law. Philosophical Transactions of The Royal Society of London. Series B, 359, 1749-1754. PDF
Fugelsang, J., Stein, C., Green, A., & Dunbar, K. (2004). Theory and data interactions of the scientific mind: Evidence from the molecular and the cognitive laboratory. Canadian Journal of Experimental Psychology, 58, 132-141. PDF
Petitto, L.A. and Dunbar, K.N. (2004). New findings from educational neuroscience on bilingual brains, scientific brains, and the educated mind. Chapter in K. Fischer & T. Katzir (Editors), Building Usable Knowledge in Mind, Brain & Education. Cambridge University Press. PDF
Blanchette, I. & Dunbar, K. (2002). Representational Change and Analogy: How Analogical Inferences Alter Target Representations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 672-685.
Dunbar, K. (2002). Science as Category: Implications of InVivo Science for theories of cognitive development, scientific discovery, and the nature of science. In S. Stich & P. Carruthers (Eds.) Cognitive Models of Science. Cambridge University Press.
Colvin, M.K., Dunbar, K. & Grafman, J. (2001). The Effects of Frontal Lobe Lesions on Goal Achievement in the Water Jug Task. Cognitive Neuroscience, 13, 1129-1147. PDF
Dunbar, K. & Blanchette, I. (2001). The invivo/invitro approach to cognition: the case of analogy. Trends in Cognitive Sciences, 5, 334-339. PDF
Blanchette, I & Dunbar, K. (2001) Analogy use in Naturalistic settings: The influence of audience, emotion and goals. Memory and Cognition, 29, 730-735. PDF
Dunbar, K. (2001). The analogical paradox: Why analogy is so easy in naturalistic settings, yet so difficult in the psychology laboratory. In D. Gentner, Holyoak, K.J., ,& Kokinov, B. Analogy: Perspectives from Cognitive Science. MIT press. PDF
Dunbar, K. (2000). What scientific thinking reveals about the nature of cognition. In Crowley, K., Schunn, C.D., & Okada, T. (Eds.) Designing for Science: Implications from Everyday, Classroom, and Professional Settings. LEA. Hillsdale: NJ. PDF
Baker, L.M., & Dunbar, K.(2000). Experimental design heuristics for scientific discovery: The use of baseline and known controls. International Journal of Human Computer Studies, 53, 335-349. PDF
Blanchette, I., & Dunbar, K. (2000). How Analogies are Generated: The Roles of Structural and Superficial Similarity. Memory & Cognition. PDF
Dunbar, K. (1999). The Scientist InVivo: How scientists think and reason in the laboratory. In Magnani, L., Nersessian, N., & Thagard, P. Model-based reasoning in scientific discovery. Plenum Press. PDF
Dunbar, K. (1999). Science. In M. Runco & S. Pritzker (Eds.) The Encyclopedia of Creativity. Academic Press, 1, 1379-1384. PDF
Dunbar K. (1999). Scientific Thinking and its development. In R. Wilson., & F. Keil (Eds.) The MIT Encyclopedia of Cognitive Science. Cambridge, MA: MIT press. pp 730-733. PDF
Dunbar, K. N. (1998). Oltre i miti della scienza [Beyond the myths of science]: come in realtà pensano gli scienziati (R. Trovato, Trans.). Metodologia Della Ricerca, 30-35. PDF
Dunbar, K. (1998). Problem solving. In W. Bechtel, & G. Graham (Eds.). A companion to Cognitive Science. London, England: Blackwell PDF
Dunbar, K. (1997). How scientists think: Online creativity and conceptual change in science. In T.B. Ward, S.M. Smith, & S.Vaid (Eds.) Conceptual structures and processes: Emergence, discovery and Change. APA Press. Washington DC. Also reprinted in Japanese (in 1999). PDF
Schunn, C.D. & Dunbar, K. (1996). Priming, Analogy, & Awareness in complex reasoning. Memory and Cognition, 24, 271-284. pp 289-298. PDF
Dunbar, K. & Sussman, D. (1995) Toward a cognitive account of frontal lobe function: Simulating frontal lobe deficits in normal subjects. Annals of the New York Academy of Sciences, 769, 289-304. PDF
Dunbar, K. (1995). How scientists really reason: Scientific reasoning in real-world laboratories. In R.J. Sternberg, & J. Davidson (Eds.). Mechanisms of insight. Cambridge MA: MIT press. pp 365-395. PDF
Dunbar, K. (1993). Concept Discovery in a Scientific domain. Cognitive Science, 17, 397-434. PDF
Cohen, J.D., Dunbar, K., & McClelland, J. (1990). On the control of automatic Processes: A Parallel Distributed Processing account of the Stroop Effect. Psychological Review, 97, 332-361. PDF
Klahr, D. & Dunbar, K. (1988). Dual Space search during Scientific Reasoning. Cognitive Science, 12, 1-48.
MacLeod, C. M., & Dunbar, K. (1988). Emergence of Stroop interference with training. Journal of Experimental Psychology: Learning, Memory and Cognition, 14, 126-135. PDF
Dunbar, K. & MacLeod C. M. (1984). A horse race of a different color: Stroop interference patterns with transformed words. J of Exp Psych: Human Perception and Performance, 10, 622-639.