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40Cortical dynamics of three-dimensional figure–ground perception of two-dimensional picturesPsychological Review 104 (3): 618-658. 1997.
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74Self-organizing neural models of categorization, inference and synchronyBehavioral and Brain Sciences 16 (3): 460-461. 1993.
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72Bring ART into the ACTBehavioral and Brain Sciences 26 (5): 610-611. 2003.ACT is compared with a particular type of connectionist model that cannot handle symbols and use nonbiological operations which do not learn in real time. This focus continues an unfortunate trend of straw man debates in cognitive science. Adaptive Resonance Theory, or ART-neural models of cognition can handle both symbols and subsymbolic representations, and meet the Newell criteria at least as well as connectionist models.
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208Neural substrates of visual percepts, imagery, and hallucinationsBehavioral and Brain Sciences 25 (2): 194-195. 2002.Recent neural models clarify many properties of mental imagery as part of the process whereby bottom-up visual information is influenced by top-down expectations, and how these expectations control visual attention. Volitional signals can transform modulatory top-down signals into supra-threshold imagery. Visual hallucinations can occur when the normal control of these volitional signals is lost.
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57How the venetian blind percept emerges from the laminar cortical dynamics of 3D visionFrontiers in Psychology 5. 2014.
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57Neural dynamics of form perception: Boundary completion, illusory figures, and neon color spreadingPsychological Review 92 (2): 173-211. 1985.
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72Hippocampal modulation of recognition, conditioning, timing, and space: Why so many functions?Behavioral and Brain Sciences 17 (3): 479-480. 1994.
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41Do all neural models really look alike? A comment on Anderson, Silverstein, Ritz, and JonesPsychological Review 85 (6): 592-596. 1978.
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64The microscopic analysis of behavior: Toward a synthesis of instrumental, perceptual, and cognitive ideasBehavioral and Brain Sciences 7 (4): 594-595. 1984.
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67Classical conditioning: The role of interdisciplinary theoryBehavioral and Brain Sciences 12 (1): 144-145. 1989.
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102Representations need self-organizing top-down expectations to fit a changing worldBehavioral and Brain Sciences 21 (4): 473-474. 1998.“Chorus embodies an attempt to find out how far a mostly bottom-up approach to representation can be taken.” Models that embody both bottom-up and top-down learning have stronger computational properties and explain more data about representation than feedforward models do.
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69Attention and recognition learning by adaptive resonanceBehavioral and Brain Sciences 13 (2): 241-242. 1990.
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77Neural Facades: Visual Representations of Static and Moving Form‐And‐Color‐And‐DepthMind and Language 5 (4): 411-456. 1990.
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59Laminar cortical dynamics of cognitive and motor working memory, sequence learning and performance: Toward a unified theory of how the cerebral cortex worksPsychological Review 115 (3): 677-732. 2008.
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100From working memory to long-term memory and back: Linked but distinctBehavioral and Brain Sciences 26 (6): 737-738. 2003.Neural models have proposed how short-term memory (STM) storage in working memory and long-term memory (LTM) storage and recall are linked and interact, but are realized by different mechanisms that obey different laws. The authors' data can be understood in the light of these models, which suggest that the authors may have gone too far in obscuring the differences between these processes.
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23Binding of object representations by synchronous cortical dynamics explains temporal order and spatial pooling dataIn Ashwin Ram & Kurt Eiselt (eds.), Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society: August 13 to 16, 1994, Georgia Institute of Technology, Erlbaum. pp. 387--391. 1994.
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Conscious ExperiencesIn Christian Kaernbach, Erich Schröger & Hermann Müller (eds.), Psychophysics Beyond Sensation: Laws and Invariants of Human Cognition, Psychology Press. pp. 417. 2004.
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65Stable self-organization of sensory recognition codes: Is chaos necessary?Behavioral and Brain Sciences 10 (2): 179-180. 1987.
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108Brain feedback and adaptive resonance in speech perceptionBehavioral and Brain Sciences 23 (3): 332-333. 2000.The brain contains ubiquitous reciprocal bottom-up and top-down intercortical and thalamocortical pathways. These resonating feedback pathways may be essential for stable learning of speech and language codes and for context-sensitive selection and completion of noisy speech sounds and word groupings. Context-sensitive speech data, notably interword backward effects in time, have been quantitatively modeled using these concepts but not with purely feedforward models.
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98Principles of cortical synchronizationBehavioral and Brain Sciences 20 (4): 689-690. 1997.Functional roles for cortical synchronization in self-organizing neural networks are described. These properties are best understood by models that link brain to behavior. Synchrony can express itself differently in cortical circuits that perform different behavioral tasks. Cortical temporal properties that seem inexplicable by synchrony are also mentioned.
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Adaptative Resonance TheoryIn Michael A. Arbib (ed.), The Handbook of Brain Theory and Neural Networks, Second Edition, Mit Press. pp. 87. 2002.
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62Neural dynamics of decision making under risk: Affective balance and cognitive-emotional interactionsPsychological Review 94 (3): 300-318. 1987.
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67Interdisciplinary aspects of perceptual dynamicsBehavioral and Brain Sciences 6 (4): 676-692. 1983.
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112The quantized geometry of visual space: The coherent computation of depth, form, and lightnessBehavioral and Brain Sciences 6 (4): 625-657. 1983.A theory is presented of how global visual interactions between depth, length, lightness, and form percepts can occur. The theory suggests how quantized activity patterns which reflect these visual properties can coherently fill-in, or complete, visually ambiguous regions starting with visually informative data features. Phenomena such as the Cornsweet and Craik–O'Brien effects, phantoms and subjective contours, binocular brightness summation, the equidistance tendency, Emmert's law, allelotropi…Read more
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223STaRT: A bridge between emotion theory and neurobiology through dynamic system modelingBehavioral and Brain Sciences 28 (2): 207-208. 2005.Lewis proposes a “reconceptualization” of how to link the psychology and neurobiology of emotion and cognitive-emotional interactions. His main proposed themes have actually been actively and quantitatively developed in the neural modeling literature for more than 30 years. This commentary summarizes some of these themes and points to areas of particularly active research in this area.
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48A neural theory of attentive visual search: Interactions of boundary, surface, spatial, and object representationsPsychological Review 101 (3): 470-489. 1994.
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115Neural models of reachingBehavioral and Brain Sciences 20 (2): 310-310. 1997.Plamondon & Alimi (P&A) have unified much data on speed/accuracy trade-offs during reaching movements using a delta-lognormal form factor that describes notably neuromuscular systems. Their approach raises questions about whether a large number of systems is needed, whether they are linear, and whether the results disclose the neural design principles that control reaching behaviors. The authors admit that (sect. 6, para. 4)
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122Linking visual cortex to visual perception: An alternative to the gestalt bubbleBehavioral and Brain Sciences 26 (4): 412-413. 2003.Lehar's lively discussion builds on a critique of neural models of vision that is incorrect in its general and specific claims. He espouses a Gestalt perceptual approach rather than one consistent with the “objective neurophysiological state of the visual system” (target article, Abstract). Contemporary vision models realize his perceptual goals and also quantitatively explain neurophysiological and anatomical data.
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Boston UniversityRegular Faculty
Boston, Massachusetts, United States of America
Areas of Interest
| Philosophy of Mind |
| Philosophy of Cognitive Science |