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  1. Implicit memory: theoretical issues.D. L. Schacter, J. S. Bowers, J. Booker, S. Lewandowsky, J. C. Dunn & K. Kirsner - 1989 - In S. Lewandowsky, J. M. Dunn & K. Kirsner (eds.), Implicit Memory: Theoretical Issues. Lawrence Erlbaum.
  2.  34
    Deep problems with neural network models of human vision.Jeffrey S. Bowers, Gaurav Malhotra, Marin Dujmović, Milton Llera Montero, Christian Tsvetkov, Valerio Biscione, Guillermo Puebla, Federico Adolfi, John E. Hummel, Rachel F. Heaton, Benjamin D. Evans, Jeffrey Mitchell & Ryan Blything - 2023 - Behavioral and Brain Sciences 46:e385.
    Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more accurate than any other model in classifying images taken from various datasets, (2) DNNs do the best job in predicting the pattern of human errors in classifying objects taken from various behavioral datasets, and (3) DNNs do the best job in predicting (...)
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  3. Towards a universal model of reading.Ram Frost, Christina Behme, Madeleine El Beveridge, Thomas H. Bak, Jeffrey S. Bowers, Max Coltheart, Stephen Crain, Colin J. Davis, S. Hélène Deacon & Laurie Beth Feldman - 2012 - Behavioral and Brain Sciences 35 (5):263.
    In the last decade, reading research has seen a paradigmatic shift. A new wave of computational models of orthographic processing that offer various forms of noisy position or context-sensitive coding have revolutionized the field of visual word recognition. The influx of such models stems mainly from consistent findings, coming mostly from European languages, regarding an apparent insensitivity of skilled readers to letter order. Underlying the current revolution is the theoretical assumption that the insensitivity of readers to letter order reflects the (...)
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  4.  74
    A Teleological Answer to the Special Composition Question.Jason Bowers - 2019 - Dialectica 73 (1-2):231-246.
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  5.  19
    On the biological plausibility of grandmother cells: Implications for neural network theories in psychology and neuroscience.Jeffrey S. Bowers - 2009 - Psychological Review 116 (1):220-251.
    A fundamental claim associated with parallel distributed processing theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts, that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations learned (...)
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  6.  50
    The practical and principled problems with educational neuroscience.Jeffrey S. Bowers - 2016 - Psychological Review 123 (5):600-612.
  7. Intention, awareness, and implicit memory: The retrieval intentionality criterion.Daniel L. Schacter, J. Bowers & J. Booker - 1989 - In S. Lewandowsky, J. M. Dunn & K. Kirsner (eds.), Implicit Memory: Theoretical Issues. Lawrence Erlbaum.
  8.  22
    Interfering neighbours: The impact of novel word learning on the identification of visually similar words.Jeffrey S. Bowers, Colin J. Davis & Derek A. Hanley - 2005 - Cognition 97 (3):B45-B54.
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  9.  20
    Why do some neurons in cortex respond to information in a selective manner? Insights from artificial neural networks.Jeffrey S. Bowers, Ivan I. Vankov, Markus F. Damian & Colin J. Davis - 2016 - Cognition 148 (C):47-63.
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  10.  31
    Neither Mereology nor Magic, but Teleology.Jason Bowers - 2017 - Southern Journal of Philosophy 55 (2):177-195.
    Contemporary theories of universals have two things in common: first, they are unable to account for necessary connections between universals that form a structure. Second, they leave teleology out of their accounts of instantiation. These facts are not unrelated; the reason why contemporary theories have such trouble is they neglect the ancient idea that universals are ends at which nature aims. If we want a working theory of universals, however, we must return to this idea. Despite its unpopularity among realists, (...)
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  11.  49
    Neural networks learn highly selective representations in order to overcome the superposition catastrophe.Jeffrey S. Bowers, Ivan I. Vankov, Markus F. Damian & Colin J. Davis - 2014 - Psychological Review 121 (2):248-261.
  12. The Haecceitic Euthyphro problem.Jason Bowers & Meg Wallace - 2018 - Analysis 78 (1):13-22.
    Haecceitism is the thesis that, necessarily, in addition to its qualities, each thing has a haecceity or individual essence. The purpose of this paper is to expose a flaw in haecceitism: it entails that familiar cases of fission and fusion either admit of no explanation or else only admit of explanations too bizarre to warrant serious consideration. Because the explanatory problem we raise for haecceitism closely resembles the Euthyphro problem for divine command theory, we refer to our objection as the (...)
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  13.  7
    Priming is not all bias: Commentary on Ratcliff and McKoon (1997).Jeffrey S. Bowers - 1999 - Psychological Review 106 (3):582-596.
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  14.  18
    A fundamental limitation of the conjunctive codes learned in PDP models of cognition: Comment on Botvinick and Plaut (2006).Jeffrey S. Bowers, Markus F. Damian & Colin J. Davis - 2009 - Psychological Review 116 (4):986-995.
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  15.  17
    Learning Representations of Wordforms With Recurrent Networks: Comment on Sibley, Kello, Plaut, & Elman (2008).Jeffrey S. Bowers & Colin J. Davis - 2009 - Cognitive Science 33 (7):1183-1186.
    Sibley et al. (2008) report a recurrent neural network model designed to learn wordform representations suitable for written and spoken word identification. The authors claim that their sequence encoder network overcomes a key limitation associated with models that code letters by position (e.g., CAT might be coded as C‐in‐position‐1, A‐in‐position‐2, T‐in‐position‐3). The problem with coding letters by position (slot‐coding) is that it is difficult to generalize knowledge across positions; for example, the overlap between CAT and TOMCAT is lost. Although we (...)
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  16.  18
    Adjectives and adverbs in English.John S. Bowers - 1975 - Foundations of Language 13 (4):529-562.
  17.  33
    Age-of-acquisition effects in visual word recognition: evidence from expert vocabularies.Hans Stadthagen-Gonzalez, Jeffrey S. Bowers & Markus F. Damian - 2004 - Cognition 93 (1):B11-B26.
  18.  8
    Clarifying status of DNNs as models of human vision.Jeffrey S. Bowers, Gaurav Malhotra, Marin Dujmović, Milton L. Montero, Christian Tsvetkov, Valerio Biscione, Guillermo Puebla, Federico Adolfi, John E. Hummel, Rachel F. Heaton, Benjamin D. Evans, Jeffrey Mitchell & Ryan Blything - 2023 - Behavioral and Brain Sciences 46:e415.
    On several key issues we agree with the commentators. Perhaps most importantly, everyone seems to agree that psychology has an important role to play in building better models of human vision, and (most) everyone agrees (including us) that deep neural networks (DNNs) will play an important role in modelling human vision going forward. But there are also disagreements about what models are for, how DNN–human correspondences should be evaluated, the value of alternative modelling approaches, and impact of marketing hype in (...)
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  19.  52
    A Simple Dialogue.Jason Bowers - 2017 - Thought: A Journal of Philosophy 6 (2):122-128.
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  20. Documenting the Learning Process from a Constructionist Perspective.J. Bowers - 2015 - Constructivist Foundations 10 (3):348-349.
    Open peer commentary on the article “Elementary Students’ Construction of Geometric Transformation Reasoning in a Dynamic Animation Environment” by Alan Maloney. Upshot: This commentary assumes a constructionist perspective to discuss the choice of methods, conclusions and design goals that Panorkou and Maloney make in their study of students’ activities with the Graph ’n Glyphs microworld.
     
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  21.  37
    Further arguments in support of localist coding in connectionist networks.Jeffrey S. Bowers - 2000 - Behavioral and Brain Sciences 23 (4):471-471.
    Two additional sources of evidence are provided in support of localist coding within connectionist networks. First, only models with localist codes can currently represent multiple pieces of information simultaneously or represent order among a set of items on-line. Second, recent priming data appear problematic for theories that rely on distributed representations. However, a faulty argument advanced by Page is also pointed out.
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  22.  20
    Grossberg and colleagues solved the hyperonym problem over a decade ago.Jeffrey S. Bowers - 1999 - Behavioral and Brain Sciences 22 (1):38-39.
    Levelt et al. describe a model of speech production in which lemma access is achieved via input from nondecompositional conceptual representations. They claim that existing decompositional theories are unable to account for lexical retrieval because of the so-called hyperonym problem. However, existing decompositional models have solved a formally equivalent problem.
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  23.  21
    How do forward models work? And why would you want them?Jeffrey Bowers - 2013 - Behavioral and Brain Sciences 36 (4):349-350.
    The project of coordinating perception, comprehension, and motor control is an exciting one, but I found it hard to follow some of Pickering & Garrod's (P&G's) arguments as presented. Consequently, my comment is not so much a disagreement with P&G but a query about the logic of forward models: It is not clear how they are supposed to work, nor why they are needed in this (or many other) contexts, and toward that end I present an alternative idea.
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  24.  18
    More varieties of Bayesian theories, but no enlightenment.Jeffrey S. Bowers & Colin J. Davis - 2011 - Behavioral and Brain Sciences 34 (4):193-194.
    We argue that Bayesian models are best categorized as methodological or theoretical. That is, models are used as tools to constrain theories, with no commitment to the processes that mediate cognition, or models are intended to approximate the underlying algorithmic solutions. We argue that both approaches are flawed, and that the Enlightened Bayesian approach is unlikely to help.
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  25.  22
    Position-invariant letter identification is a key component of any universal model of reading.Jeffrey S. Bowers - 2012 - Behavioral and Brain Sciences 35 (5):281-282.
    A universal property of visual word identification is position-invariant letter identification, such that the letter is coded in the same way in CAT and ACT. This should provide a fundamental constraint on theories of word identification, and, indeed, it inspired some of the theories that Frost has criticized. I show how the spatial coding scheme of Colin Davis can, in principle, account for contrasting transposed letter priming effects, and at the same time, position-invariant letter identification.
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  26.  14
    Postscript: More problems with Botvinick and Plaut’s (2006) PDP model of short-term memory.Jeffrey S. Bowers, Markus F. Damian & Colin J. Davis - 2009 - Psychological Review 116 (4):995-997.
  27.  6
    Postscript: Some final thoughts on grandmother cells, distributed representations, and PDP models of cognition.Jeffrey Bowers - 2010 - Psychological Review 117 (1):306-308.
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  28. Radical Constructivism: A Theory of Individual and Collective Change?J. Bowers, J. Gruver & V. Trang - 2014 - Constructivist Foundations 9 (3):310-312.
    Open peer commentary on the article “Constructing Constructivism” by Hugh Gash. Upshot: Gash’s retrospective analysis suggests a number of different roles for RC over the past thirty years. We outline three of these roles and then conduct a thought experiment to argue that while RC itself could be seen as a living theory that accommodates new ideas, its strongest contributions remain when it stays true to its roots and serves as a milestone along the path of educational paradigm shifts.
     
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  29.  15
    Researchers Keep Rejecting Grandmother Cells after Running the Wrong Experiments: The Issue Is How Familiar Stimuli Are Identified.Jeffrey S. Bowers, Nicolas D. Martin & Ella M. Gale - 2019 - Bioessays 41 (8):1800248.
    There is widespread agreement in neuroscience and psychology that the visual system identifies objects and faces based on a pattern of activation over many neurons, each neuron being involved in representing many different categories. The hypothesis that the visual system includes finely tuned neurons for specific objects or faces for the sake of identification, so‐called “grandmother cells”, is widely rejected. Here it is argued that the rejection of grandmother cells is premature. Grandmother cells constitute a hypothesis of how familiar visual (...)
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  30. Terrence M. barnhardt.Jennifer Dorfman Bowers, Elizabeth Glisky, Martha Glisky, Lori Marchese, Susan McGovern, Sheila Mulvaney, Robin Pennington, Michael Polster, Barbara Routhieux & Victor Shames - 1993 - In Daniel M. Wegner & J. Pennebaker (eds.), Handbook of Mental Control. Prentice-Hall.
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  31. The Theory of Grammatical Relations.J. S. BOWERS - 1981
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  32.  29
    The visual categories for letters and words reside outside any informationally encapsulated perceptual system.Jeffrey S. Bowers - 1999 - Behavioral and Brain Sciences 22 (3):368-369.
    According to Pylyshyn, the early visual system is able to categorize perceptual inputs into shape classes based on visual similarity criteria; it is also suggested that written words may be categorized within early vision. This speculation is contradicted by the fact that visually unrelated exemplars of a given letter (e.g., a/A) or word (e.g., read/READ) map onto common visual categories.
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  33.  19
    Engelbert Kaempfer's first report of the torpedo fish of the Persian Gulf in the late seventeenth century.RobertW Carrubba & JohnZ Bowers - 1982 - Journal of the History of Biology 15 (2):263 - 274.
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  34.  4
    Psychology, not educational neuroscience, is the way forward for improving educational outcomes for all children: Reply to Gabrieli (2016) and Howard-Jones et al. (2016). [REVIEW]Jeffrey S. Bowers - 2016 - Psychological Review 123 (5):628-635.
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  35.  13
    More on grandmother cells and the biological implausibility of PDP models of cognition: A reply to Plaut and McClelland (2010) and Quian Quiroga and Kreiman (2010). [REVIEW]Jeffrey Bowers - 2010 - Psychological Review 117 (1):300-306.
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  36.  10
    John Lydgate, The Siege of Thebes, ed. Robert R. Edwards. Kalamazoo, Mich.: Medieval Institute Publications, Western Michigan University, for TEAMS in association with the University of Rochester, 2001. Paper. Pp. x, 190. [REVIEW]John M. Bowers - 2003 - Speculum 78 (3):949-950.
  37.  58
    Making Things Up. [REVIEW]Jason Bowers - 2019 - Australasian Journal of Philosophy 97 (2):411-414.
    Volume 97, Issue 2, June 2019, Page 411-414.
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