On the computational architecture of the neocortex

This paper is a sequel to an earlier paper which proposed an active role for the thalamus, integrating multiple hypotheses formed in the cortex via the thalamo-cortical loop. In this paper, I put forward a hypothesis on the role of the reciprocal, topographic pathways between two cortical areas, one often a ‘higher’ area dealing with more abstract information about the world, the other ‘lower’, dealing with more concrete data. The higher area attempts to fit its abstractions to the data it receives from lower areas by sending back to them from its deep pyramidal cells a template reconstruction best fitting the lower level view. The lower area attempts to reconcile the reconstruction of its view that it receives from higher areas with what it knows, sending back from its superficial pyramidal cells the features in its data which are not predicted by the higher area. The whole calculation is done with all areas working simultaneously, but with order imposed by synchronous activity in the various top-down, bottom-up loops. Evidence for this theory is reviewed and experimental tests are proposed. A third part of this paper will deal with extensions of these ideas to the frontal lobe.

[1]  Patrick Henry Winston,et al.  Learning structural descriptions from examples , 1970 .

[2]  J. Bransford,et al.  Sentence memory: A constructive versus interpretive approach ☆ ☆☆ , 1972 .

[3]  Martin A. Fischler,et al.  The Representation and Matching of Pictorial Structures , 1973, IEEE Transactions on Computers.

[4]  E. Evarts Motor Cortex Reflexes Associated with Learned Movement , 1973, Science.

[5]  Marvin Minsky,et al.  A framework for representing knowledge , 1974 .

[6]  Marvin Minsky,et al.  A framework for representing knowledge" in the psychology of computer vision , 1975 .

[7]  Victor Lesser,et al.  IN THE HEARSAY-II SPEECH UNDERSTANDING SYSTEM , 1976 .

[8]  P. H. Lindsay Human Information Processing , 1977 .

[9]  G. Shepherd The Synaptic Organization of the Brain , 1979 .

[10]  E. Yund,et al.  Responses of striate cortex cells to grating and checkerboard patterns. , 1979, The Journal of physiology.

[11]  T. Powell,et al.  The basic uniformity in structure of the neocortex. , 1980, Brain : a journal of neurology.

[12]  T. Powell,et al.  An electron microscopic study of the types and proportions of neurons in the cortex of the motor and visual areas of the cat and rat. , 1980, Brain : a journal of neurology.

[13]  Victor R. Lesser,et al.  The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty , 1980, CSUR.

[14]  J. Kaas,et al.  Cortical and Subcortical Connections of Visual Cortex in Primates , 1981 .

[15]  D. B. Bender,et al.  Retinotopic organization of macaque pulvinar. , 1981, Journal of neurophysiology.

[16]  Ann M. Graybiel,et al.  Families of Related Cortical Areas in the Extrastriate Visual System , 1981 .

[17]  E. Harth Windows on the mind , 1981 .

[18]  R. Shepard,et al.  Mental Images and Their Transformations , 1982 .

[19]  T. P. S. Powell,et al.  The organization of the connections between the cortex and the claustrum in the monkey , 1982, Brain Research.

[20]  G. Ojemann Ojemann's data: Provocative but mysterious , 1983, Behavioral and Brain Sciences.

[21]  R. Llinás,et al.  Electrophysiological properties of guinea‐pig thalamic neurones: an in vitro study. , 1984, The Journal of physiology.

[22]  F. Crick Function of the thalamic reticular complex: the searchlight hypothesis. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[23]  S. Ullman Visual routines , 1984, Cognition.

[24]  伊藤 正男 The cerebellum and neural control , 1984 .

[25]  T. Stephenson Image analysis , 1992, Nature.

[26]  W. Freeman,et al.  Spatial EEG patterns, non-linear dynamics and perception: the neo-sherringtonian view , 1985, Brain Research Reviews.

[27]  John H. R. Maunsell,et al.  The projections from striate cortex (V1) to areas V2 and V3 in the macaque monkey: Asymmetries, areal boundaries, and patchy connections , 1986, The Journal of comparative neurology.

[28]  M. Steriade,et al.  Reticularis thalami neurons revisited: activity changes during shifts in states of vigilance , 1986, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[29]  H. Kennedy,et al.  Topography of the afferent connectivity of area 17 in the macaque monkey: A double‐labelling study , 1986, The Journal of comparative neurology.

[30]  E Harth,et al.  The inversion of sensory processing by feedback pathways: a model of visual cognitive functions. , 1987, Science.

[31]  S. Zucker,et al.  Endstopped neurons in the visual cortex as a substrate for calculating curvature , 1987, Nature.

[32]  Stephen Grossberg,et al.  A massively parallel architecture for a self-organizing neural pattern recognition machine , 1988, Comput. Vis. Graph. Image Process..

[33]  Paris science museum under attack , 1987, Nature.

[34]  J. Fodor,et al.  Connectionism and cognitive architecture: A critical analysis , 1988, Cognition.

[35]  O. G. Selfridge,et al.  Pandemonium: a paradigm for learning , 1988 .

[36]  S. Cajal Cajal on the cerebral cortex , 1988 .

[37]  T. P. S. Powell,et al.  The organization of the cortico-cortical connections between the walls of the lower part of the superior temporal sulcus and the inferior parietal lobule in the monkey , 1988, Brain Research.

[38]  R. Llinás,et al.  The functional states of the thalamus and the associated neuronal interplay. , 1988, Physiological reviews.

[39]  J. T. Massey,et al.  Mental rotation of the neuronal population vector. , 1989, Science.

[40]  K. Rockland,et al.  Terminal arbors of individual “Feedback” axons projecting from area V2 to V1 in the macaque monkey: A study using immunohistochemistry of anterogradely transported Phaseolus vulgaris‐leucoagglutinin , 1989, The Journal of comparative neurology.

[41]  P. Anandan,et al.  Optimization in Model Matching and Perceptual Organization , 1989, Neural Computation.

[42]  Adam N. Mamelak,et al.  Dream Bizarreness as the Cognitive Correlate of Altered Neuronal Behavior in REM Sleep , 1989, Journal of Cognitive Neuroscience.

[43]  W. Singer,et al.  Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[44]  Ina Ruck,et al.  USA , 1969, The Lancet.

[45]  Barbara Moore,et al.  Theory of networks for learning , 1990, Defense, Security, and Sensing.

[46]  Edmund T. Rolls,et al.  THE REPRESENTATION OF INFORMATION IN THE TEMPORAL LOBE VISUAL CORTICAL AREAS OF MACAQUES , 1990 .

[47]  T Poggio,et al.  Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks , 1990, Science.

[48]  C. Koch,et al.  Towards a neurobiological theory of consciousness , 1990 .

[49]  C. Cherniak The Bounded Brain: Toward Quantitative Neuroanatomy , 1990, Journal of Cognitive Neuroscience.

[50]  James J. Clark,et al.  Data Fusion for Sensory Information Processing Systems , 1990 .

[51]  T. Poggio A theory of how the brain might work. , 1990, Cold Spring Harbor symposia on quantitative biology.

[52]  A. Yuille Deformable Templates for Face Recognition , 1991, Journal of Cognitive Neuroscience.

[53]  Patrick Cavanagh,et al.  What's up in top-down processing? , 1991 .

[54]  D. J. Felleman,et al.  Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.

[55]  R. Desimone Face-Selective Cells in the Temporal Cortex of Monkeys , 1991, Journal of Cognitive Neuroscience.

[56]  Zenon W. Pylyshyn,et al.  Connectionism and cognitive architecture , 1993 .

[57]  C. Koch,et al.  The control of retinogeniculate transmission in the mammalian lateral geniculate nucleus , 2004, Experimental Brain Research.

[58]  B. Ripley,et al.  Robust Statistics , 2018, Encyclopedia of Mathematical Geosciences.

[59]  K. Sasaki,et al.  Cortical field potentials preceding visually initiated hand movements in the monkey , 2004, Experimental Brain Research.