Cell assemblies in the cerebral cortex

Donald Hebb’s concept of cell assemblies is a physiology-based idea for a distributed neural representation of behaviorally relevant objects, concepts, or constellations. In the late 70s Valentino Braitenberg started the endeavor to spell out the hypothesis that the cerebral cortex is the structure where cell assemblies are formed, maintained and used, in terms of neuroanatomy (which was his main concern) and also neurophysiology. This endeavor has been carried on over the last 30 years corroborating most of his findings and interpretations. This paper summarizes the present state of cell assembly theory, realized in a network of associative memories, and of the anatomical evidence for its location in the cerebral cortex.

[1]  A. Turing On Computable Numbers, with an Application to the Entscheidungsproblem. , 1937 .

[2]  S C Kleene,et al.  Representation of Events in Nerve Nets and Finite Automata , 1951 .

[3]  E. G. Gray,et al.  Electron Microscopy of Synaptic Contacts on Dendrite Spines of the Cerebral Cortex , 1959, Nature.

[4]  D. Hubel,et al.  Receptive fields of single neurones in the cat's striate cortex , 1959, The Journal of physiology.

[5]  V. Braitenberg,et al.  A note on myeloarchitectonics , 1962, The Journal of comparative neurology.

[6]  D. Hubel,et al.  Binocular interaction in striate cortex of kittens reared with artificial squint. , 1965, Journal of neurophysiology.

[7]  D. Hubel,et al.  Comparison of the effects of unilateral and bilateral eye closure on cortical unit responses in kittens. , 1965, Journal of neurophysiology.

[8]  K. Uchizono Characteristics of Excitatory and Inhibitory Synapses in the Central Nervous System of the Cat , 1965, Nature.

[9]  Charles R. Legéndy,et al.  On the scheme by which the human brain stores information , 1967 .

[10]  M. Colonnier Synaptic patterns on different cell types in the different laminae of the cat visual cortex. An electron microscope study. , 1968, Brain research.

[11]  E. Evans Upper and Lower Levels of the Auditory System: A Contrast of Structure and Function , 1968 .

[12]  D. Marr A theory of cerebellar cortex , 1969, The Journal of physiology.

[13]  D. Marr A theory for cerebral neocortex , 1970, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[14]  D Marr,et al.  Simple memory: a theory for archicortex. , 1971, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[15]  G. F. Cooper,et al.  Modification of the visual cortex by experience. , 1971, Brain research.

[16]  D. Hubel,et al.  Uniformity of monkey striate cortex: A parallel relationship between field size, scatter, and magnification factor , 1974, The Journal of comparative neurology.

[17]  C R Legéndy Three principles of brain function and structure. , 1975, The International journal of neuroscience.

[18]  A. C. Webb,et al.  The spontaneous activity of neurones in the cat’s cerebral cortex , 1976, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[19]  A. Peters,et al.  The projection of the lateral geniculate nucleus to area 17 of the rat cerebral cortex. I. General description , 1976, Journal of neurocytology.

[20]  J. Wolff Quantitative Analysis of Topography and Development of Synapses in the Visual Cortex , 1976 .

[21]  D. Hubel,et al.  Ferrier lecture - Functional architecture of macaque monkey visual cortex , 1977, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[22]  T. Wiesel,et al.  Functional architecture of macaque monkey visual cortex , 1977 .

[23]  V. Braitenberg Cell Assemblies in the Cerebral Cortex , 1978 .

[24]  Jeffrey D. Ullman,et al.  Introduction to Automata Theory, Languages and Computation , 1979 .

[25]  K. Rockland,et al.  Laminar origins and terminations of cortical connections of the occipital lobe in the rhesus monkey , 1979, Brain Research.

[26]  守屋 悦朗,et al.  J.E.Hopcroft, J.D. Ullman 著, "Introduction to Automata Theory, Languages, and Computation", Addison-Wesley, A5変形版, X+418, \6,670, 1979 , 1980 .

[27]  Stephen Grossberg,et al.  Studies of mind and brain , 1982 .

[28]  Günther Palm Rules for synaptic changes and their relevance for the storage of information in the brain , 1982 .

[29]  Professor Moshe Abeles,et al.  Local Cortical Circuits , 1982, Studies of Brain Function.

[30]  Moshe Abeles Information Codes for Higher Brain Function , 1982 .

[31]  Gèunther Palm,et al.  Neural Assemblies: An Alternative Approach to Artificial Intelligence , 1982 .

[32]  D. Georgescauld Local Cortical Circuits, An Electrophysiological Study , 1983 .

[33]  J. E. Vaughn,et al.  GABA Neurons in the Cerebral Cortex , 1984 .

[34]  E. Geisert The projection of the lateral geniculate nucleus to area 18 , 1985, The Journal of comparative neurology.

[35]  G. Krone,et al.  Spatiotemporal receptive fields: a dynamical model derived from cortical architectonics , 1986, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[36]  G Palm,et al.  Brain Theory , 1986, Springer Berlin Heidelberg.

[37]  R. Miles,et al.  Excitatory synaptic interactions between CA3 neurones in the guinea‐pig hippocampus. , 1986, The Journal of physiology.

[38]  Günther Palm,et al.  On Associative Memories , 1987 .

[39]  Günther Palm,et al.  Associative memory and threshold control in neural networks , 1987 .

[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]  E. White Cortical Circuits: Synaptic Organization of the Cerebral Cortex , 1989 .

[42]  G. Palm,et al.  Density of neurons and synapses in the cerebral cortex of the mouse , 1989, The Journal of comparative neurology.

[43]  Daniel J. Amit,et al.  Modeling brain function: the world of attractor neural networks, 1st Edition , 1989 .

[44]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[45]  Günther Palm,et al.  LOCAL LEARNING RULES AND SPARSE CODING IN NEURAL NETWORKS , 1990 .

[46]  T. M. Mayhew,et al.  Anatomy of the Cortex: Statistics and Geometry. , 1991 .

[47]  Moshe Abeles,et al.  Corticonics: Neural Circuits of Cerebral Cortex , 1991 .

[48]  Günther Palm,et al.  Information capacity in recurrent McCulloch-Pitts networks with sparsely coded memory states , 1992 .

[49]  P. Brodal The Central Nervous System , 1992 .

[50]  A. Aertsen Brain theory : spatio-temporal aspects of brain function , 1993 .

[51]  B. Hellwig How the myelin picture of the human cerebral cortex can be computed from cytoarchitectural data. A bridge between von Economo and Vogt. , 1993, Journal fur Hirnforschung.

[52]  G. Palm,et al.  Cell assemblies, coherence, and corticohippocampal interplay , 1993, Hippocampus.

[53]  R. Malach,et al.  Cortical hierarchy reflected in the organization of intrinsic connections in macaque monkey visual cortex , 1993, The Journal of comparative neurology.

[54]  J. Deuchars,et al.  Temporal and spatial properties of local circuits in neocortex , 1994, Trends in Neurosciences.

[55]  Günther Palm,et al.  Associative Memory Networks and Sparse Similarity Preserving Codes , 1994 .

[56]  William R. Softky,et al.  Simple codes versus efficient codes , 1995, Current Opinion in Neurobiology.

[57]  E. Bienenstock A model of neocortex , 1995 .

[58]  Gully A. P. C. Burns,et al.  The Analysis of Cortical Connectivity , 1995 .

[59]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[60]  L. Cauller Layer I of primary sensory neocortex: where top-down converges upon bottom-up , 1995, Behavioural Brain Research.

[61]  C. Blakemore,et al.  Analysis of connectivity in the cat cerebral cortex , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[62]  Günther Palm,et al.  Iterative Retrieval In Associative Memories By Threshold Control Of Different Neural Models , 1995 .

[63]  Naftali Tishby,et al.  Cortical activity flips among quasi-stationary states. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[64]  Günther Palm,et al.  Iterative retrieval of sparsely coded associative memory patterns , 1996, Neural Networks.

[65]  Christof Koch,et al.  Temporal Precision of Spike Trains in Extrastriate Cortex of the Behaving Macaque Monkey , 1999, Neural Computation.

[66]  Robert Miller,et al.  Cortico-thalamic interplay and the security of operation of neural assemblies and temporal chains in the cerebral cortex , 1996, Biological Cybernetics.

[67]  Günther Palm,et al.  Controlling the Speed of Synfire Chains , 1996, ICANN.

[68]  S. Thorpe,et al.  Speed of processing in the human visual system , 1996, Nature.

[69]  Peter Dayan,et al.  A Neural Substrate of Prediction and Reward , 1997, Science.

[70]  D. Johnston,et al.  Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs , 1997 .

[71]  Richard S. Sutton,et al.  Introduction to Reinforcement Learning , 1998 .

[72]  Prof. Dr. Dr. Valentino Braitenberg,et al.  Cortex: Statistics and Geometry of Neuronal Connectivity , 1998, Springer Berlin Heidelberg.

[73]  G. Bi,et al.  Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type , 1998, The Journal of Neuroscience.

[74]  S. Grossberg How does the cerebral cortex work? Learning, attention, and grouping by the laminar circuits of visual cortex. , 1999, Spatial vision.

[75]  Günther Palm,et al.  How imprecise is neuronal synchronization? , 1999, Neurocomputing.

[76]  A. Borst Seeing smells: imaging olfactory learning in bees , 1999, Nature Neuroscience.

[77]  R. Miller Time and the brain , 2000 .

[78]  E. Callaway,et al.  Laminar sources of synaptic input to cortical inhibitory interneurons and pyramidal neurons , 2000, Nature Neuroscience.

[79]  Andreas Knoblauch,et al.  Pattern separation and synchronization in spiking associative memories and visual areas , 2001, Neural Networks.

[80]  L. Brakel A Universe of Consciousness: How Matter Becomes Imagination , 2001 .

[81]  M. Young,et al.  Advanced database methodology for the Collation of Connectivity data on the Macaque brain (CoCoMac). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[82]  D. Wilkin,et al.  Neuron , 2001, Brain Research.

[83]  Isaac Meilijson,et al.  Distributed synchrony in a cell assembly of spiking neurons , 2001, Neural Networks.

[84]  J. Bullier,et al.  Feedforward and feedback connections between areas V1 and V2 of the monkey have similar rapid conduction velocities. , 2001, Journal of neurophysiology.

[85]  S. Thorpe,et al.  The Time Course of Visual Processing: From Early Perception to Decision-Making , 2001, Journal of Cognitive Neuroscience.

[86]  W. Schultz Getting Formal with Dopamine and Reward , 2002, Neuron.

[87]  J. B. Levitt,et al.  Intrinsic Connections in Mammalian Cerebral Cortex , 2002 .

[88]  J. DeFelipe,et al.  Microstructure of the neocortex: Comparative aspects , 2002, Journal of neurocytology.

[89]  Günther Palm,et al.  Scene segmentation by spike synchronization in reciprocally connected visual areas. II. Global assemblies and synchronization on larger space and time scales , 2002, Biological Cybernetics.

[90]  Günther Palm,et al.  Scene segmentation by spike synchronization in reciprocally connected visual areas. I. Local effects of cortical feedback , 2002, Biological Cybernetics.

[91]  Y. Dan,et al.  Spike-timing-dependent synaptic modification induced by natural spike trains , 2002, Nature.

[92]  Braitenberg,et al.  The Human Cortical White Matter: Quantitative Aspects of Cortico-Cortical Long-Range Connectivity , 2002 .

[93]  Friedemann Pulvermüller,et al.  The Neuroscience of Language: On Brain Circuits of Words and Serial Order , 2003 .

[94]  K. Rockland Feedback Connections: Splitting the Arrow , 2003 .

[95]  Andreas Knoblauch,et al.  Synaptic plasticity, conduction delays, and inter-areal phase relations of spike activity in a model of reciprocally connected areas , 2003, Neurocomputing.

[96]  A. Grinvald,et al.  Spontaneously emerging cortical representations of visual attributes , 2003, Nature.

[97]  Andreas Knoblauch,et al.  Spike-timing-dependent synaptic plasticity can form "zero lag links" for cortical oscillations , 2004, Neurocomputing.

[98]  D. N. Spinelli,et al.  Modification of the distribution of receptive field orientation in cats by selective visual exposure during development , 1971, Experimental Brain Research.

[99]  S. Grossberg,et al.  Adaptive pattern classification and universal recoding: I. Parallel development and coding of neural feature detectors , 1976, Biological Cybernetics.

[100]  Stephen Grossberg,et al.  Adaptive pattern classification and universal recoding: II. Feedback, expectation, olfaction, illusions , 1976, Biological Cybernetics.

[101]  G. Palm,et al.  Towards a theory of cell assemblies , 2004, Biological Cybernetics.

[102]  R. Douglas,et al.  A Quantitative Map of the Circuit of Cat Primary Visual Cortex , 2004, The Journal of Neuroscience.

[103]  Wulfram Gerstner,et al.  Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns , 1993, Biological Cybernetics.

[104]  Rajesh P. N. Rao Hierarchical Bayesian Inference in Networks of Spiking Neurons , 2004, NIPS.

[105]  A. Herz,et al.  Statistische Eigenschaften der Neuronaktivität im ascendierenden visuellen System , 1964, Kybernetik.

[106]  G. Palm,et al.  Associating words to visually recognized objects ∗ , 2004 .

[107]  John R Anderson,et al.  An integrated theory of the mind. , 2004, Psychological review.

[108]  J. Hawkins,et al.  On Intelligence , 2004 .

[109]  G. Palm,et al.  On associative memory , 2004, Biological Cybernetics.

[110]  M. I. Cohen,et al.  Evoked splanchnic potentials produced by electrical stimulation of medullary vasomotor regions , 1971, Experimental Brain Research.

[111]  D. Chklovskii,et al.  Neurogeometry and potential synaptic connectivity , 2005, Trends in Neurosciences.

[112]  Günther Palm,et al.  Biomimetic Neural Learning for Intelligent Robots - Intelligent Systems, Cognitive Robotics, and Neuroscience , 2005, Biomimetic Neural Learning for Intelligent Robots.

[113]  Günther Palm,et al.  Detecting Sequences and Understanding Language with Neural Associative Memories and Cell Assemblies , 2005, Biomimetic Neural Learning for Intelligent Robots.

[114]  José R. Álvarez,et al.  Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach: First International Work-Conference on the Interplay Between Natural ... Part II (Lecture Notes in Computer Science) , 2005 .

[115]  Günther Palm,et al.  What is signal and what is noise in the brain? , 2005, Bio Systems.

[116]  Günther Palm,et al.  An Associative Cortical Model of Language Understanding and Action Planning , 2005, IWINAC.

[117]  Andreas Knoblauch,et al.  An associative model of cortical language and action processing , 2005 .

[118]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[119]  B. Kampa,et al.  Calcium Spikes in Basal Dendrites of Layer 5 Pyramidal Neurons during Action Potential Bursts , 2006, The Journal of Neuroscience.

[120]  A. Schüz,et al.  Quantitative aspects of corticocortical connections: a tracer study in the mouse. , 2006, Cerebral cortex.

[121]  Thomas Wennekers,et al.  Operational Cell Assemblies as a Paradigm for Brain-Inspired Future Computing Architectures , 2006 .

[122]  W. Gerstner,et al.  Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity , 2006, The Journal of Neuroscience.

[123]  C. Koch,et al.  Sparse Representation in the Human Medial Temporal Lobe , 2006, The Journal of Neuroscience.

[124]  Eugene M. Izhikevich,et al.  Polychronization: Computation with Spikes , 2006, Neural Computation.

[125]  Marc-Oliver Gewaltig,et al.  A cell assembly based model for the cortical microcircuitry , 2007, Neurocomputing.

[126]  Markus Diesmann,et al.  Spike-Timing-Dependent Plasticity in Balanced Random Networks , 2007, Neural Computation.

[127]  S. Sherman The thalamus is more than just a relay , 2007, Current Opinion in Neurobiology.

[128]  R. Douglas,et al.  Stereotypical Bouton Clustering of Individual Neurons in Cat Primary Visual Cortex , 2007, The Journal of Neuroscience.

[129]  Robert Hecht-Nielsen Confabulation theory - the mechanism of thought , 2007 .

[130]  Günther Palm,et al.  Modelling of syntactical processing in the cortex , 2007, Biosyst..

[131]  Rolf Kötter,et al.  Online retrieval, processing, and visualization of primate connectivity data from the CoCoMac Database , 2007, Neuroinformatics.

[132]  C. Gray,et al.  Heterogeneity in the responses of adjacent neurons to natural stimuli in cat striate cortex. , 2007, Journal of neurophysiology.

[133]  Topological Effects of Synaptic Time Dependent Plasticity , 2008, 0810.0029.

[134]  W. Denk,et al.  Imaging in vivo: watching the brain in action , 2008, Nature Reviews Neuroscience.

[135]  Alex S. Ferecskó,et al.  Local Potential Connectivity in Cat Primary Visual Cortex , 2008 .

[136]  Günther Palm,et al.  Sentence Understanding and Learning of New Words with Large-Scale Neural Networks , 2008, ANNPR.

[137]  N. Spruston Pyramidal neurons: dendritic structure and synaptic integration , 2008, Nature Reviews Neuroscience.

[138]  Y. Dan,et al.  Spike timing-dependent plasticity: a Hebbian learning rule. , 2008, Annual review of neuroscience.

[139]  Günther Palm,et al.  Word recognition and incremental learning based on neural associative memories and hidden Markov models , 2008, ESANN.

[140]  Evgueniy V. Lubenov,et al.  Decoupling through Synchrony in Neuronal Circuits with Propagation Delays , 2008, Neuron.

[141]  A. Lansner Associative memory models: from the cell-assembly theory to biophysically detailed cortex simulations , 2009, Trends in Neurosciences.

[142]  Günther Palm,et al.  Syntactic sequencing in Hebbian cell assemblies , 2009, Cognitive Neurodynamics.

[143]  Frank C. Hoppensteadt,et al.  Polychronous Wavefront Computations , 2009, Int. J. Bifurc. Chaos.

[144]  Günther Palm,et al.  Coexistence of Cell Assemblies and STDP , 2009, ICANN.

[145]  Günther Palm,et al.  Neural associative memories for the integration of language, vision and action in an autonomous agent , 2009, Neural Networks.

[146]  Nelson Spruston Pyramidal neuron , 2009, Scholarpedia.

[147]  Dileep George,et al.  Towards a Mathematical Theory of Cortical Micro-circuits , 2009, PLoS Comput. Biol..

[148]  H. Neumann,et al.  Extraction of Surface-Related Features in a Recurrent Model of V1-V2 Interactions , 2009, PloS one.

[149]  Botond Szatmáry,et al.  Spike-Timing Theory of Working Memory , 2010, PLoS Comput. Biol..

[150]  Günther Palm,et al.  Simple Constraints for Zero-Lag Synchronous Oscillations under STDP , 2010, ICANN.

[151]  H. Jörntell,et al.  Presynaptic Calcium Signalling in Cerebellar Mossy Fibres , 2009, Front. Neural Circuits.

[152]  Izhikevich Eugene,et al.  Spike-timing theory of working memory , 2010 .

[153]  Damian J. Wallace,et al.  Chasing the cell assembly , 2010, Current Opinion in Neurobiology.

[154]  Heiko Neumann,et al.  A neural model of the temporal dynamics of figure-ground segregation in motion perception , 2010, Neural Networks.

[155]  W. Gerstner,et al.  Connectivity reflects coding: a model of voltage-based STDP with homeostasis , 2010, Nature Neuroscience.

[156]  P. Dayan,et al.  Supporting Online Material Materials and Methods Som Text Figs. S1 to S9 References the Asynchronous State in Cortical Circuits , 2022 .

[157]  Günther Palm,et al.  Memory Capacities for Synaptic and Structural Plasticity G ¨ Unther Palm , 2022 .

[158]  Ad Aertsen,et al.  A modeler's view on the spatial structure of intrinsic horizontal connectivity in the neocortex , 2010, Progress in Neurobiology.

[159]  Guillermo A. Cecchi,et al.  A Theory of Loop Formation and Elimination by Spike Timing-Dependent Plasticity , 2009, Front. Neural Circuits.

[160]  Pulvermuller Friedemann Attention to language: Novel MEG paradigm for registering involuntary language processing in the brain , 2010 .

[161]  Andreas Knoblauch,et al.  Neural Associative Memory with Optimal Bayesian Learning , 2011, Neural Computation.

[162]  K. Deisseroth,et al.  Optogenetic stimulation of a hippocampal engram activates fear memory recall , 2012, Nature.

[163]  H. Neumann,et al.  The Role of Attention in Figure-Ground Segregation in Areas V1 and V4 of the Visual Cortex , 2012, Neuron.

[164]  Florian Hauser,et al.  Formation and stability of spiking cell assemblies with spike-timing-dependent synaptic plasticity , 2012 .

[165]  Markus Diesmann,et al.  CoCoMac 2.0 and the future of tract-tracing databases , 2012, Front. Neuroinform..

[166]  Sue L. Denham,et al.  Spatio-temporal pattern recognizers using spiking neurons and spike-timing-dependent plasticity , 2012, Front. Comput. Neurosci..

[167]  M. Kiefer,et al.  Conceptual representations in mind and brain: Theoretical developments, current evidence and future directions , 2012, Cortex.

[168]  Günther Palm,et al.  Does Spike-Timing-Dependent Synaptic Plasticity Couple or Decouple Neurons Firing in Synchrony? , 2012, Front. Comput. Neurosci..

[169]  R. Nieuwenhuys The myeloarchitectonic studies on the human cerebral cortex of the Vogt–Vogt school, and their significance for the interpretation of functional neuroimaging data , 2013, Brain Structure and Function.

[170]  Günther Palm,et al.  Neural coding in graphs of bidirectional associative memories , 2012, Brain Research.

[171]  Christian Borgelt,et al.  Finding neural assemblies with frequent item set mining , 2013, Front. Neuroinform..

[172]  Günther Palm,et al.  Neural associative memories and sparse coding , 2013, Neural Networks.

[173]  Chris Eliasmith,et al.  How to Build a Brain: A Neural Architecture for Biological Cognition , 2013 .

[174]  Thomas Wennekers,et al.  Synfire graphs: from spike patterns to automata of spiking neurons , 2013 .

[175]  Robert Turner,et al.  Optimizing T1-weighted imaging of cortical myelin content at 3.0T , 2013, NeuroImage.

[176]  C. Huyck,et al.  A review of cell assemblies , 2013, Biological Cybernetics.

[177]  Tobias C. Potjans,et al.  The Cell-Type Specific Cortical Microcircuit: Relating Structure and Activity in a Full-Scale Spiking Network Model , 2012, Cerebral cortex.