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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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12Stable self-organization of sensory recognition codes: Is chaos necessary?Behavioral and Brain Sciences 10 (2): 179-180. 1987.
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24Brain 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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37Principles 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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20Neural dynamics of decision making under risk: Affective balance and cognitive-emotional interactionsPsychological Review 94 (3): 300-318. 1987.
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22The quantized geometry of visual space: The coherent computation of depth, form, and lightnessBehavioral and Brain Sciences 6 (4): 625. 1983.
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108STaRT: 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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17A neural theory of attentive visual search: Interactions of boundary, surface, spatial, and object representationsPsychological Review 101 (3): 470-489. 1994.
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27Neural 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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63Linking 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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20Cortical dynamics of contextually cued attentive visual learning and search: Spatial and object evidence accumulationPsychological Review 117 (4): 1080-1112. 2010.
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9Human and computer rules and representations are not equivalentBehavioral and Brain Sciences 3 (1): 136-138. 1980.
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55Competitive Learning: From Interactive Activation to Adaptive ResonanceCognitive Science 11 (1): 23-63. 1987.
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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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24Processing of expected and unexpected events during conditioning and attention: A psychophysiological theoryPsychological Review 89 (5): 529-572. 1982.
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895Depth 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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15Neural dynamics of word recognition and recall: Attentional priming, learning, and resonancePsychological Review 93 (1): 46-74. 1986.
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59Localist but distributed representationsBehavioral and Brain Sciences 23 (4): 478-479. 2000.A number of examples are given of how localist models may incorporate distributed representations, without the types of nonlocal interactions that often render distributed models implausible. The need to analyze the information that is encoded by these representations is also emphasized as a metatheoretical constraint on model plausibility.
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19The resonant dynamics of speech perception: Interword integration and duration-dependent backward effectsPsychological Review 107 (4): 735-767. 2000.
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19Cortical dynamics of visual motion perception: Short-range and long-range apparent motionPsychological Review 99 (1): 78-121. 1992.
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23Self-organizing features and categories through attentive resonanceBehavioral and Brain Sciences 21 (1): 27-28. 1998.Because “people create features to subserve the representation and categorization of objects” (abstract) Schyns et al. “provide an account of feature learning in which the components of a representation have close ties to the categorization history of the organism” (sect. 1.1). This commentary surveys self-organizing neural models that clarify this process. These models suggest how “top-down information should constrain the search for relevant dimensions/features of categorization” (sect. 3.4.2)…Read more
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51Adaptive timing, attention, and movement controlBehavioral and Brain Sciences 20 (4): 619-619. 1997.Examples of how LTP and LTD can control adaptively-timed learning that modulates attention and motor control are given. It is also suggested that LTP/LTD can play a role in storing memories. The distinction between match-based and mismatch-based learning may help to clarify the difference.
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48Neural models of development and learningBehavioral and Brain Sciences 20 (4): 566-566. 1997.I agree with Quartz & Sejnowski's points, which are familiar to many scientists. A number of models with the sought-after properties, however, are overlooked, while models without them are highlighted. I will review nonstationary learning, links between development and learning, locality, stability, learning throughout life, hypothesis testing that models the learner's problem domain, and active dendritic processes
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9Neural dynamics of planned arm movements: Emergent invariants and speed-accuracy properties during trajectory formationPsychological Review 95 (1): 49-90. 1988.
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Boston UniversityRegular Faculty
Boston, Massachusetts, United States of America
Areas of Interest
Philosophy of Mind |
Philosophy of Cognitive Science |