Functional integration and inference in the brain
暂无分享,去创建一个
[1] C. Price. The functional anatomy of word comprehension and production , 1998, Trends in Cognitive Sciences.
[2] T. Shallice,et al. Deep Dyslexia: A Case Study of , 1993 .
[3] Joseph J. Atick,et al. Towards a Theory of Early Visual Processing , 1990, Neural Computation.
[4] C. Koch,et al. Constraints on cortical and thalamic projections: the no-strong-loops hypothesis , 1998, Nature.
[5] Kenji Kawano,et al. Global and fine information coded by single neurons in the temporal visual cortex , 1999, Nature.
[6] Erkki Oja,et al. Neural Networks, Principal Components, and Subspaces , 1989, Int. J. Neural Syst..
[7] W. Singer,et al. In search of common foundations for cortical computation , 1997, Behavioral and Brain Sciences.
[8] Karl J. Friston,et al. Attentional modulation of effective connectivity from V2 to V5/MT in humans. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[9] Karl J. Friston,et al. The colour centre in the cerebral cortex of man , 1989, Nature.
[10] Richard S. J. Frackowiak,et al. Cerebral Oxygen Metabolism and Blood Flow in Human Cerebral Ischemic Infarction , 1982, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[11] Terrence J. Sejnowski,et al. An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.
[12] John H. R. Maunsell,et al. Attentional modulation of visual motion processing in cortical areas MT and MST , 1996, Nature.
[13] Rajesh P. N. Rao,et al. An optimal estimation approach to visual perception and learning , 1999, Vision Research.
[14] P. Schiller,et al. Effect of cooling area 18 on striate cortex cells in the squirrel monkey. , 1982, Journal of neurophysiology.
[15] Karl J. Friston,et al. Psychophysiological and Modulatory Interactions in Neuroimaging , 1997, NeuroImage.
[16] R Linsker,et al. Perceptual neural organization: some approaches based on network models and information theory. , 1990, Annual review of neuroscience.
[17] Karl J. Friston,et al. Principal component analysis learning algorithms: a neurobiological analysis , 1993, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[18] Colin Blakemore,et al. Vision: Coding and Efficiency , 1991 .
[19] D. Benson,et al. Disconnection syndromes , 1993, Neurology.
[20] A. Clark,et al. Trading spaces: Computation, representation, and the limits of uninformed learning , 1997, Behavioral and Brain Sciences.
[21] Anthony Randal McIntosh,et al. Towards a network theory of cognition , 2000, Neural Networks.
[22] Karl J. Friston. Functional and effective connectivity in neuroimaging: A synthesis , 1994 .
[23] C. G. Phillips,et al. Localization of function in the cerebral cortex. Past, present and future. , 1984, Brain : a journal of neurology.
[24] Mark S. Seidenberg,et al. Category-Specific Semantic Deficits in Focal and Widespread Brain Damage: A Computational Account , 1998, Journal of Cognitive Neuroscience.
[25] L. Abbott,et al. Synaptic Depression and Cortical Gain Control , 1997, Science.
[26] P. Goldman-Rakic,et al. Preface: Cerebral Cortex Has Come of Age , 1991 .
[27] S. Zeki. Vision: The motion pathways of the visual cortex , 1991 .
[28] P M Grasby,et al. Brain systems for encoding and retrieval of auditory-verbal memory. An in vivo study in humans. , 1995, Brain : a journal of neurology.
[29] Jan de Leeuw,et al. Nonlinear Principal Component Analysis , 1982 .
[30] Karl J. Friston,et al. The Trouble with Cognitive Subtraction , 1996, NeuroImage.
[31] Juha Karhunen,et al. Representation and separation of signals using nonlinear PCA type learning , 1994, Neural Networks.
[32] Peter Dayan,et al. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems , 2001 .
[33] Danny Keogan,et al. Distributed hierarchical processing , 2002, Photomask Japan.
[34] K. Rockland,et al. Laminar origins and terminations of cortical connections of the occipital lobe in the rhesus monkey , 1979, Brain Research.
[35] C. Gilbert,et al. Synaptic physiology of horizontal connections in the cat's visual cortex , 1991, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[36] Jim Kay,et al. Activation Functions, Computational Goals, and Learning Rules for Local Processors with Contextual Guidance , 1997, Neural Computation.
[37] Geoffrey E. Hinton,et al. The Helmholtz Machine , 1995, Neural Computation.
[38] J. Pearl. Causality: Models, Reasoning and Inference , 2000 .
[39] Mitsuo Kawato,et al. A forward-inverse optics model of reciprocal connections between visual cortical areas , 1993 .
[40] D. Mackay. The Epistemological Problem for Automata , 1956 .
[41] M. Posner,et al. Positron Emission Tomographic Studies of the Processing of Singe Words , 1989, Journal of Cognitive Neuroscience.
[42] C. Büchel,et al. Modulation of connectivity in visual pathways by attention: cortical interactions evaluated with structural equation modelling and fMRI. , 1997, Cerebral cortex.
[43] E. Warrington,et al. Categories of knowledge. Further fractionations and an attempted integration. , 1987, Brain : a journal of neurology.
[44] Geoffrey E. Hinton,et al. The "wake-sleep" algorithm for unsupervised neural networks. , 1995, Science.
[45] Karl J. Friston,et al. Dynamic Diaschisis: Anatomically Remote and Context-Sensitive Human Brain Lesions , 2001, Journal of Cognitive Neuroscience.
[46] L. Optican,et al. Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. III. Information theoretic analysis. , 1987, Journal of neurophysiology.
[47] 福島 邦彦. A Neural Network Model for Selective Attention in Visual Pattern Recognition , 1987 .
[48] G. Kane. Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol 1: Foundations, vol 2: Psychological and Biological Models , 1994 .
[49] Geoffrey E. Hinton,et al. Lesioning an attractor network: investigations of acquired dyslexia. , 1991, Psychological review.
[50] Christian Jutten,et al. Nonlinear source separation: the post-nonlinear mixtures , 1997, ESANN.
[51] Karl J. Friston,et al. How the brain learns to see objects and faces in an impoverished context , 1997, Nature.
[52] M. Tovée,et al. Information encoding and the responses of single neurons in the primate temporal visual cortex. , 1993, Journal of neurophysiology.
[53] David J. Field,et al. Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.
[54] B. Efron,et al. Stein's Estimation Rule and Its Competitors- An Empirical Bayes Approach , 1973 .
[55] M. Kramer. Nonlinear principal component analysis using autoassociative neural networks , 1991 .
[56] H. Spitzer,et al. Temporal encoding of two-dimensional patterns by single units in primate inferior temporal cortex. I. Response characteristics. , 1987, Journal of neurophysiology.
[57] Karl J. Friston,et al. Value-dependent selection in the brain: Simulation in a synthetic neural model , 1994, Neuroscience.
[58] TJ Gawne,et al. How independent are the messages carried by adjacent inferior temporal cortical neurons? , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[59] Gary G. R. Green,et al. Calculation of the Volterra kernels of non-linear dynamic systems using an artificial neural network , 1994, Biological Cybernetics.
[60] D. Perkel,et al. Simultaneously Recorded Trains of Action Potentials: Analysis and Functional Interpretation , 1969, Science.
[61] E. Warrington,et al. Category specific access dysphasia. , 2002, Brain : a journal of neurology.
[62] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..
[63] R. Kass,et al. Approximate Bayesian Inference in Conditionally Independent Hierarchical Models (Parametric Empirical Bayes Models) , 1989 .
[64] Localisation of function. , 1898 .
[65] P. Földiák,et al. Forming sparse representations by local anti-Hebbian learning , 1990, Biological Cybernetics.
[66] S. Shipp,et al. The functional logic of cortical connections , 1988, Nature.
[67] Rajesh P. N. Rao,et al. Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. , 1999 .
[68] Richard S. Sutton,et al. Time-Derivative Models of Pavlovian Reinforcement , 1990 .
[69] H Preißl,et al. Dynamics of activity and connectivity in physiological neuronal networks , 1991 .
[70] J. Bullier,et al. Visual activity in area V2 during reversible inactivation of area 17 in the macaque monkey. , 1989, Journal of neurophysiology.
[71] T. Shallice,et al. Category specific semantic impairments , 1984 .
[72] Geoffrey E. Hinton,et al. Parallel visual computation , 1983, Nature.
[73] Karl J. Friston,et al. Entropy and cortical activity: information theory and PET findings. , 1992, Cerebral cortex.
[74] G. Edelman,et al. A measure for brain complexity: relating functional segregation and integration in the nervous system. , 1994, Proceedings of the National Academy of Sciences of the United States of America.
[75] M. Gabriel,et al. Learning and Computational Neuroscience: Foundations of Adaptive Networks , 1990 .
[76] D. J. Felleman,et al. Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.
[77] David C. Plaut,et al. Deep Dyslexia: A Case Study of , 1993 .
[78] Christopher C. Pack,et al. Temporal dynamics of a neural solution to the aperture problem in visual area MT of macaque brain , 2001, Nature.
[79] David Mumford,et al. On the computational architecture of the neocortex , 2004, Biological Cybernetics.
[80] G. Edelman. Neural Darwinism: Selection and reentrant signaling in higher brain function , 1993, Neuron.
[81] Françoise Lamnabhi-Lagarrigue,et al. An algebraic approach to nonlinear functional expansions , 1983 .
[82] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[83] Gustavo Deco,et al. Predictive Coding in the Visual Cortex by a Recurrent Network with Gabor Receptive Fields , 2001, Neural Processing Letters.
[84] James L. McClelland,et al. A computational model of semantic memory impairment: modality specificity and emergent category specificity. , 1991, Journal of experimental psychology. General.
[85] R. Nebes. Semantic memory in Alzheimer's disease. , 1989, Psychological bulletin.
[86] P A Salin,et al. Corticocortical connections in the visual system: structure and function. , 1995, Physiological reviews.
[87] Karl J. Friston,et al. Statistical parametric maps in functional imaging: A general linear approach , 1994 .
[88] Karl J. Friston,et al. The labile brain. III. Transients and spatio-temporal receptive fields. , 2000, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[89] Geoffrey E. Hinton,et al. Lesioning an attractor network: investigations of acquired dyslexia , 1991 .
[90] T. McAvoy,et al. Nonlinear principal component analysis—Based on principal curves and neural networks , 1996 .
[91] W. Freeman,et al. Chaotic Oscillations and the Genesis of Meaning in Cerebral Cortex , 1994 .
[92] D Mumford,et al. On the computational architecture of the neocortex. II. The role of cortico-cortical loops. , 1992, Biological cybernetics.
[93] W. Singer,et al. Temporal Coding in the Brain , 1994, Research and Perspectives in Neurosciences.
[94] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .