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153The link between brain learning, attention, and consciousnessConsciousness and Cognition 8 (1): 1-44. 1999.The processes whereby our brains continue to learn about a changing world in a stable fashion throughout life are proposed to lead to conscious experiences. These processes include the learning of top-down expectations, the matching of these expectations against bottom-up data, the focusing of attention upon the expected clusters of information, and the development of resonant states between bottom-up and top-down processes as they reach an attentive consensus between what is expected and what i…Read more
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12Realizing the Now-or-Never bottleneck and Chunk-and-Pass processing with Item-Order-Rank working memories and masking field chunking networksBehavioral and Brain Sciences 39. 2016.
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10Conscious mind, resonant brain: how each brain makes a mindOxford University Press. 2021.How does your mind work? How does your brain give rise to your mind? These are questions that all of us have wondered about at some point in our lives, if only because everything that we know is experienced in our minds. They are also very hard questions to answer. After all, how can a mind understand itself? How can you understand something as complex as the tool that is being used to understand it? This book provides an introductory and self-contained description of some of the exciting answer…Read more
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187Spatial facilitation by color and luminance edges: boundary, surface, and attentional factorsVision Research 39 (20): 3431-3443. 1995.The thresholds of human observers detecting line targets improve significantly when the targets are presented in a spatial context of collinear inducing stimuli. This phenomenon is referred to as spatial facilitation, and may reflect the output of long-range interactions between cortical feature detectors. Spatial facilitation has thus far been observed with luminance-defined, achromatic stimuli on achromatic backgrounds. This study compares spatial facilitation with line targets and collinear, …Read more
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192Contour Integration Across Gaps: From Local Contrast To GroupingVision Research 7 (37): 913-924. 1997.This article introduces an experimental paradigm to selectively probe the multiple levels of visual processing that influence the formation of object contours, perceptual boundaries, and illusory contours. The experiments test the assumption that, to integrate contour information across space and contrast sign, a spatially short-range filtering process that is sensitive to contrast polarity inputs to a spatially long-range grouping process that pools signals from opposite contrast polarities. Th…Read more
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189Neural Computation of Surface Border Ownership and Relative Surface Depth from Ambiguous Contrast InputsFrontiers in Psychology 7. 2016.The segregation of image parts into foreground and background is an important aspect of the neural computation of 3D scene perception. To achieve such segregation, the brain needs information about border ownership; that is, the belongingness of a contour to a specific surface represented in the image. This article presents psychophysical data derived from 3D percepts of figure and ground that were generated by presenting 2D images composed of spatially disjoint shapes that pointed inward o…Read more
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39Linking brain to mind in normal behavior and schizophreniaBehavioral and Brain Sciences 26 (1): 90-90. 2003.To understand schizophrenia, a linking hypothesis is needed that shows how brain mechanisms lead to behavioral functions in normals, and also how breakdowns in these mechanisms lead to behavioral symptoms of schizophrenia. Such a linking hypothesis is now available that complements the discussion offered by Phillips & Silverstein (P&S).
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32Filling-in the formsBehavioral and Brain Sciences 21 (6): 758-759. 1998.Boundary completion and surface filling-in are computationally complementary processes whose multiple processing stages form processing streams that realize a hierarchical resolution of uncertainty. Such complementarity and uncertainty principles provide a new foundation for philosophical discussions about visual perception, and lead to neural explanations of difficult perceptual data.
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16The role of learning in sensory-motor controlBehavioral and Brain Sciences 8 (1): 155-157. 1985.
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14Cortical dynamics of three-dimensional figure–ground perception of two-dimensional picturesPsychological Review 104 (3): 618-658. 1997.
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32Self-organizing neural models of categorization, inference and synchronyBehavioral and Brain Sciences 16 (3): 460-461. 1993.
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15Bring 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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129Neural 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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11Neural dynamics of form perception: Boundary completion, illusory figures, and neon color spreadingPsychological Review 92 (2): 173-211. 1985.
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15How the venetian blind percept emerges from the laminar cortical dynamics of 3D visionFrontiers in Psychology 5. 2014.
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37Hippocampal modulation of recognition, conditioning, timing, and space: Why so many functions?Behavioral and Brain Sciences 17 (3): 479-480. 1994.
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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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17The 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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19Classical conditioning: The role of interdisciplinary theoryBehavioral and Brain Sciences 12 (1): 144-145. 1989.
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49Representations 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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25Attention and recognition learning by adaptive resonanceBehavioral and Brain Sciences 13 (2): 241-242. 1990.
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6Neural Facades: Visual Representations of Static and Moving Form‐And‐Color‐And‐DepthMind and Language 5 (4): 411-456. 1990.
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24Laminar 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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47From 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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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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Boston UniversityRegular Faculty
Boston, Massachusetts, United States of America
Areas of Interest
Philosophy of Mind |
Philosophy of Cognitive Science |