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Philosophy of Cognitive Science

Edited by Gualtiero Piccinini (University of Missouri St. Louis)
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  1. Wendy J. Adams (2008). Frames of Reference for the Light-From-Above Prior in Visual Search and Shape Judgements. Cognition 107 (1):137-150.
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  2. Leah E. Adams-Curtis (1989). Does a Piagetian Description Work? Behavioral and Brain Sciences 12 (3):588.
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  3. Elsa Addessi, Francesca Bellagamba, Alexia Delfino, Francesca De Petrillo, Valentina Focaroli, Luigi Macchitella, Valentina Maggiorelli, Beatrice Pace, Giulia Pecora, Sabrina Rossi, Agnese Sbaffi, Maria Isabella Tasselli & Fabio Paglieri (2014). Waiting by Mistake: Symbolic Representation of Rewards Modulates Intertemporal Choice in Capuchin Monkeys, Preschool Children and Adult Humans. Cognition 130 (3):428-441.
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  4. Elsa Addessi, Fabio Paglieri & Valentina Focaroli (2011). The Ecological Rationality of Delay Tolerance: Insights From Capuchin Monkeys. Cognition 119 (1):142-147.
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  5. J. S. Adelman & Z. Estes (2013). Emotion and Memory: A Recognition Advantage for Positive and Negative Words Independent of Arousal. Cognition 129 (3):530-535.
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  6. Edward H. Adelson (1983). What is Iconic Storage Good For? Behavioral and Brain Sciences 6 (1):11.
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  7. Robert Ader & Nicholas Cohen (1986). Conditioned Responses Are Indeed Conditioned. Behavioral and Brain Sciences 9 (4):760.
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  8. Robert Ader & Nicholas Cohen (1985). The Brain and the Immune System: Conditional Responses to Commentator Stimuli. Behavioral and Brain Sciences 8 (3):413-426.
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  9. Tony Ades (1981). Time for a Purge. Cognition 10 (1-3):7-15.
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  10. W. Ross Adey (1979). Hippocampal Theta and Organism-Environment Interaction. Behavioral and Brain Sciences 2 (3):322.
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  11. E. Adi-Japha (2000). Regulation of Division of Labour Between Cognitive Systems Controlling Action. Cognition 76 (1):1-11.
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  12. Matteo Adinolfi (1985). Immunoselection and Male Diseases. Behavioral and Brain Sciences 8 (3):441-442.
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  13. Elizabeth Adkins-Regan (2006). Brain Evolution: Part I. Behavioral and Brain Sciences 29 (1):12-13.
    Striedter's accessible concept-based book is strong on the macroevolution of brains and the developmental principles that underlie how brains evolve on that scale. In the absence of greater attention to microevolution, natural selection, and sexual selection, however, it is incomplete and not fully modern on the evolution side. Greater biological integration is needed.
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  14. Toni Adleberg, Morgan Thompson & Eddy Nahmias (forthcoming). Do Men and Women Have Different Philosophical Intuitions? Further Data. Philosophical Psychology:1-27.
    To address the underrepresentation of women in philosophy effectively, we must understand the causes of the loss of women after their initial philosophy classes. In this paper we challenge one of the few explanations that has focused on why women might leave philosophy at early stages. Wesley Buckwalter and Stephen Stich (2014) offer some evidence that women have different intuitions than men about philosophical thought experiments. We present some concerns about their evidence and we discuss our own study, in which (...)
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  15. Jonathan E. Adler (1994). Fairness to Policies, Distinctions and Intuitions. Behavioral and Brain Sciences 17 (1):10.
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  16. Jonathan E. Adler (1987). Comparisons with Grice. Behavioral and Brain Sciences 10 (4):710.
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  17. Jonathan E. Adler (1984). A Defense of Ignorance. Behavioral and Brain Sciences 7 (4):621.
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  18. Jonathan E. Adler (1983). Human Rationality: Essential Conflicts, Multiple Ideals. Behavioral and Brain Sciences 6 (2):245.
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  19. Jonathan E. Adler (1983). The Rationality of the (Lay) Scientist: Toward Reconciliation. Behavioral and Brain Sciences 6 (3):487.
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  20. Matthew D. Adler (2005). Cognitivism, Controversy, and Moral Heuristics. Behavioral and Brain Sciences 28 (4):542-543.
    Sunstein aims to provide a nonsectarian account of moral heuristics, yet the account rests on a controversial meta-ethical view. Further, moral theorists who reject act consequentialism may deny that Sunstein's examples involve moral mistakes. But so what? Within a theory that counts consequences as a morally weighty feature of actions, the moral judgments that Sunstein points to are indeed mistaken, and the fact that governmental action at odds with these judgments will be controversial doesn't bar such action.
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  21. Roee Admon, Mohammed R. Milad & Talma Hendler (2013). A Causal Model of Post-Traumatic Stress Disorder: Disentangling Predisposed From Acquired Neural Abnormalities. Trends in Cognitive Sciences 17 (7):337-347.
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  22. Edward F. Adolph (1979). Multiple Paths in the Control of Drinking. Behavioral and Brain Sciences 2 (1):102.
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  23. Ralph Adolphs (1999). Index-plan du site Résumé-vulgarisation. Trends in Cognitive Sciences 3:12.
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  24. Ralph Adolphs (1999). Social Cognition and the Human Brain. Trends in Cognitive Sciences 3 (12):469-479.
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  25. Michael Adzema (1993). The Meeting of Science and Spirit: Guidelines for a New Age. Anthropology of Consciousness 4 (2):24-25.
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  26. Gyan C. Agarwal (1991). Human Cognition is an Adaptive Process. Behavioral and Brain Sciences 14 (3):485-486.
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  27. Gyan C. Agarwal & Gerald L. Gottlieb (1986). Complexity in Control of Movements. Behavioral and Brain Sciences 9 (4):599.
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  28. Joseph Agassi (2003). Newell's List. Behavioral and Brain Sciences 26 (5):601-602.
    Newell wanted a theory of cognition to abide by some explicit criteria, here called the Newell Test. The test differs from the Turing Test because it is explicit. The Newell Test will include the Turing Test if its characterization of cognition is complete. It is not. Its use here is open-ended: A system that does not pass it well invites improvement.
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  29. Joseph Agassi (1981). Simulation? Behavioral and Brain Sciences 4 (4):535.
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  30. Frank L. Agee & Walter C. Gogel (1967). Equidistance Judgments in the Vicinity of a Binocular Illusion. Journal of Experimental Psychology 74 (1):87-92.
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  31. Rodrigo Agerri (2002). Fixing Unsaid Meanings. Trends in Cognitive Sciences 6 (4):149-150.
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  32. John P. Aggleton & Malcolm W. Brown (2006). Interleaving Brain Systems for Episodic and Recognition Memory. Trends in Cognitive Sciences 10 (10):455-463.
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  33. Salvatore M. Aglioti & Mariella Pazzaglia (2011). Sounds and Scents in (Social) Action. Trends in Cognitive Sciences 15 (2):47-55.
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  34. Rosemary Agonito (1975). Hayek Revisited: Mind as a Process of Classification. Behaviorism 3 (2):162-71.
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  35. Christian Agrillo, Laura Piffer & Angelo Bisazza (2011). Number Versus Continuous Quantity in Numerosity Judgments by Fish. Cognition 119 (2):281-287.
    In quantity discrimination tasks, adults, infants and animals have been sometimes observed to process number only after all continuous variables, such as area or density, have been controlled for. This has been taken as evidence that processing number may be more cognitively demanding than processing continuous variables. We tested this hypothesis by training mosquitofish to discriminate two items from three in three different conditions. In one condition, continuous variables were controlled while numerical information was available; in another, the number was (...)
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  36. Andréa Aguiar & Renée Baillargeon (2003). Perseverative Responding in a Violation-of-Expectation Task in 6.5-Month-Old Infants. Cognition 88 (3):277-316.
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  37. Ehud Ahissar (1995). Are Single-Cell Data Sufficient for Testing Neural Network Models? Behavioral and Brain Sciences 18 (4):626.
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  38. Merav Ahissar (2007). Dyslexia and the Anchoring-Deficit Hypothesis. Trends in Cognitive Sciences 11 (11):458-465.
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  39. Merav Ahissar & Shaul Hochstein (2004). The Reverse Hierarchy Theory of Visual Perceptual Learning. Trends in Cognitive Sciences 8 (10):457-464.
    Perceptual learning can be defined as practice-induced improvement in the ability to perform specific perceptual tasks. We previously proposed the Reverse Hierarchy Theory as a unifying concept that links behavioral findings of visual learning with physiological and anatomical data. Essentially, it asserts that learning is a top-down guided process, which begins at high-level areas of the visual system, and when these do not suffice, progresses backwards to the input levels, which have a better signal-to-noise ratio. This simple concept has proved (...)
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  40. Merav Ahissar & Yulia Oganian (2008). Response to Ziegler: The Anchor is in the Details. Trends in Cognitive Sciences 12 (7):245-246.
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  41. Sven Ahlenius (1985). A Functional Consideration of Anatomical Connections Between the Basal Ganglia and the Thalamus Suggests That Antipsychotic Drugs Inhibit the Initiation of Movement. Behavioral and Brain Sciences 8 (1):173-174.
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  42. Hannah Ahlheim (2013). Governing the World of Wakefulness: The Exploration of Alertness, Performance, and Brain Activity with the Help of “Stay‐Awake‐Men” (1884–1964). [REVIEW] Anthropology of Consciousness 24 (2):117-136.
    In January 1959, famous radio DJ Peter Tripp stayed awake for 200 hours in a glass booth on Times Square, exposing his weakening body and distracted sleepless mind to the public. Tripp's playing with the borderlines of consciousness was a media attraction, but the DJ also served as a guinea pig for scientific research. From the late 19th century on, several experts had tried to explore the world of wakefulness by observing stay-awake-men. With their help, researchers tested methods of measuring (...)
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  43. M. Ahmed & James F. Voss (1969). Serial Acquisition as a Function of Stage of Learning. Journal of Experimental Psychology 82 (2):398-400.
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  44. Serge H. Ahmed (2011). Toward an Evolutionary Basis for Resilience to Drug Addiction. Behavioral and Brain Sciences 34 (6):310-311.
    According to Minstrumentalize” this framework to propose an evolutionary basis for the existence of a biological resilience to drug addiction in people.
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  45. Serge H. Ahmed (2008). The Origin of Addictions by Means of Unnatural Decision. Behavioral and Brain Sciences 31 (4):437-438.
    The unified framework for addiction (UFA) formulated by Redish et al. is a tour de force. It uniquely predicts that there should be multiple addiction syndromes and pathways – a diversity that would reflect the complexity of the mammalian brain decision system. Here I explore some of the evolutionary and developmental ramifications of UFA and derive several new avenues for research.
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