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4Do all neural models really look alike? A comment on Anderson, Silverstein, Ritz, and JonesPsychological Review 85 (6): 592-596. 1978.
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45Representations 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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18Classical conditioning: The role of interdisciplinary theoryBehavioral and Brain Sciences 12 (1): 144-145. 1989.
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21Attention and recognition learning by adaptive resonanceBehavioral and Brain Sciences 13 (2): 241-242. 1990.
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18Neural Facades: Visual Representations of Static and Moving Form‐And‐Color‐And‐DepthMind and Language 5 (4): 411-456. 1990.
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20Laminar 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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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, Erlbaum. pp. 387--391. 1994.
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40From 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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10Stable self-organization of sensory recognition codes: Is chaos necessary?Behavioral and Brain Sciences 10 (2): 179-180. 1987.
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Conscious ExperiencesIn Christian Kaernbach, Erich Schroger & Hermann Müller (eds.), Psychophysics Beyond Sensation: Laws and Invariants of Human Cognition, Psychology Press. pp. 417. 2004.
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16Brain 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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35Principles 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 M. Arbib (ed.), The Handbook of Brain Theory and Neural Networks, Mit Press. pp. 87. 2002.
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18Neural dynamics of decision making under risk: Affective balance and cognitive-emotional interactionsPsychological Review 94 (3): 300-318. 1987.
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18The quantized geometry of visual space: The coherent computation of depth, form, and lightnessBehavioral and Brain Sciences 6 (4): 625. 1983.
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107STaRT: 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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15A neural theory of attentive visual search: Interactions of boundary, surface, spatial, and object representationsPsychological Review 101 (3): 470-489. 1994.
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26Neural 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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59Linking 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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14Cortical dynamics of contextually cued attentive visual learning and search: Spatial and object evidence accumulationPsychological Review 117 (4): 1080-1112. 2010.
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8Human and computer rules and representations are not equivalentBehavioral and Brain Sciences 3 (1): 136-138. 1980.
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64The Art of Seeing and PaintingTechnical Report. 2006.The human urge to represent the three-dimensional world using two-dimensional pictorial representations dates back at least to Paleolithic times. Artists from ancient to modern times have struggled to understand how a few contours or color patches on a flat surface can induce mental representations of a three-dimensional scene. This article summarizes some of the recent breakthroughs in scientifically understanding how the brain sees that shed light on these struggles. These breakthroughs i…Read more
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46Competitive Learning: From Interactive Activation to Adaptive ResonanceCognitive Science 11 (1): 23-63. 1987.
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23Processing of expected and unexpected events during conditioning and attention: A psychophysiological theoryPsychological Review 89 (5): 529-572. 1982.
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842Depth perception from pairs of overlapping cues in pictorial displaysSpatial Vision 15 255-276. 2002.The experiments reported herein probe the visual cortical mechanisms that control near–far percepts in response to two-dimensional stimuli. Figural contrast is found to be a principal factor for the emergence of percepts of near versus far in pictorial stimuli, especially when stimulus duration is brief. Pictorial factors such as interposition (Experiment 1) and partial occlusion Experiments 2 and 3) may cooperate, as generally predicted by cue combination models, or compete with contrast factor…Read more
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11Neural dynamics of word recognition and recall: Attentional priming, learning, and resonancePsychological Review 93 (1): 46-74. 1986.
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Boston UniversityRegular Faculty
Boston, Massachusetts, United States of America
Areas of Interest
Philosophy of Mind |
Philosophy of Cognitive Science |