A neurobiological theory of meaning in perception . Part 1 .

The aim of this tutorial is to document a novel approach to brain function, in which the key to understanding is the capacity of brains for self-organization. The property that distinguishes animals from plants is the capacity for directed movement through the environment, which requires an organ capable of organizing information about the environment and predicting the consequences of self-initiated actions. The operations of predicting, planning acting, detecting, and learning comprise the process of intentionality by which brains construct meaning. The currency of brains is primarily meaning and only secondarily information. The information processing metaphor has dominated neurocognitive research for half a century. Brain certainly process information for input and output. They pre-process sensory stimuli before constructing meaning, and they post-process cognitive read-out to control appropriate action and express meaning. Neurobiologists have thoroughly documented sensory information processing bottom-up, and neuropsychologists have analyzed the later stages of cognition top-down, as they are expressed in behavior. However, a grasp of the intervening process of perception in which meaning forms requires detailed analysis and modeling of neural activity that is observed in brains during meaningful behavior of humans and other animals. Unlike computers brains function hierarchically. Sensory and motor information is inferred from pulses of microscopic axons. Meaning is inferred from local mean fields of dendrites in mesoscopic and macroscopic populations. This tutorial is aimed to introduce engineers to an experimental basis for a theory of meaning, in terms of the nonlinear dynamics of the mass actions of large neural populations that construct meaning. The focus is on the higher frequency ranges of cortical oscillations. Part 1 introduces background on information, meaning and oscillatory activity (EEG). Part 2 details the properties of wave packets. Part 3 describes the covariance structure of the oscillations. Part 4 addresses the amplitude modulations, and Part 5 deals with the phase modulations. The significance of a theory of meaning lies in applications using population neurodynamics, to open new approaches for treatment of clinical brain disorders, and to devise new machines with capacities for autonomy and intelligence that might approach those of simpler free-living animals. Information, meaning and perception 3 Walter J Freeman

[1]  R. Llinás,et al.  Human oscillatory brain activity near 40 Hz coexists with cognitive temporal binding. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[2]  D. Lindley,et al.  Boltzmann’s Atom: The Great Debate That Launched a Revolution in Physics , 2001 .

[3]  P. Robinson,et al.  Modal analysis of corticothalamic dynamics, electroencephalographic spectra, and evoked potentials. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  A Aertsen,et al.  Propagation of synchronous spiking activity in feedforward neural networks , 1996, Journal of Physiology-Paris.

[5]  W S McCulloch,et al.  A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.

[6]  K. Pribram Languages of the Brain: Experimental Paradoxes and Principles in Neuropsychology , 1971 .

[7]  B. Baars In the theater of consciousness : the workspace of the mind , 1997 .

[8]  R. Desimone,et al.  Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention , 2001, Science.

[9]  P. Bailey,et al.  Organization of the cerebral cortex. , 1948, The Proceedings of the Institute of Medicine of Chicago.

[10]  E. G. Walsh,et al.  THE NEUROPSYCHOLOGY OF LASHLEY , 1961 .

[11]  J Barham,et al.  A dynamical model of the meaning of information. , 1996, Bio Systems.

[12]  S. Rossitti Introduction to Functional Magnetic Resonance Imaging, Principles and Techniques , 2002 .

[13]  Christopher R. Stambaugh,et al.  Simultaneous encoding of tactile information by three primate cortical areas , 1998, Nature Neuroscience.

[14]  J Y Lettvin,et al.  Speculations on smell. , 1965, Cold Spring Harbor symposia on quantitative biology.

[15]  W. Freeman,et al.  Analysis of spatial patterns of phase in neocortical gamma EEGs in rabbit. , 2000, Journal of neurophysiology.

[16]  Péter Érdi,et al.  The KIV model - nonlinear spatio-temporal dynamics of the primordial vertebrate forebrain , 2003, Neurocomputing.

[17]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[18]  A. Wolters,et al.  Dynamics in Psychology , 1943, Nature.

[19]  S. Bressler Interareal synchronization in the visual cortex , 1996, Behavioural Brain Research.

[20]  Walter J. Freeman,et al.  Local Homeostasis Stabilizes a Model of the Olfactory System Globally in Respect to Perturbations by Input During Pattern Classification , 1998 .

[21]  M. Steriade Corticothalamic resonance, states of vigilance and mentation , 2000, Neuroscience.

[22]  M. Steriade Impact of network activities on neuronal properties in corticothalamic systems. , 2001, Journal of neurophysiology.

[23]  W. Freeman,et al.  Spatial patterns of visual cortical fast EEG during conditioned reflex in a rhesus monkey , 1987, Brain Research.

[24]  N. Spruston,et al.  Diversity and dynamics of dendritic signaling. , 2000, Science.

[25]  W. Freeman,et al.  Fine temporal resolution of analytic phase reveals episodic synchronization by state transitions in gamma EEGs. , 2002, Journal of neurophysiology.

[26]  W. Freeman,et al.  COMPARISON OF EEG TIME SERIES FROM RAT OLFACTORY SYSTEM WITH MODEL COMPOSED OF NONLINEAR COUPLED OSCILLATORS , 1995 .

[27]  Eilon Vaadia,et al.  Cognitive neuroscience: Learning how the brain learns , 2000, Nature.

[28]  W. Singer,et al.  Visuomotor integration is associated with zero time-lag synchronization among cortical areas , 1997, Nature.

[29]  Catherine Tallon-Baudry,et al.  Induced γ-Band Activity during the Delay of a Visual Short-Term Memory Task in Humans , 1998, The Journal of Neuroscience.

[30]  R. Fischer,et al.  From transmission of signals' to self-creation of meaning' transformations in the concept of information , 1993 .

[31]  R. Passingham The hippocampus as a cognitive map J. O'Keefe & L. Nadel, Oxford University Press, Oxford (1978). 570 pp., £25.00 , 1979, Neuroscience.

[32]  Walter J. Freeman,et al.  Characteristics of the Synchronization of Brain Activity imposed by Finite conduction Velocities of axons , 2000, Int. J. Bifurc. Chaos.

[33]  Y Miyashita,et al.  How the brain creates imagery: projection to primary visual cortex. , 1995, Science.

[34]  J. Pernier,et al.  Induced gamma-band activity during the delay of a visual short-term memory task in humans. , 1998, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[35]  E. Izhikevich,et al.  Thalamo-cortical interactions modeled by weakly connected oscillators: could the brain use FM radio principles? , 1998, Bio Systems.

[36]  W. Freeman,et al.  Relation of olfactory EEG to behavior: time series analysis. , 1986, Behavioral neuroscience.

[37]  Walter J. Freeman,et al.  A Neurobiological Theory of Meaning in Perception Part IV: Multicortical Patterns of amplitude Modulation in Gamma EEG , 2003, Int. J. Bifurc. Chaos.

[38]  Ad Aertsen,et al.  Stable propagation of synchronous spiking in cortical neural networks , 1999, Nature.

[39]  Walter J. Freeman,et al.  Neurodynamics: An Exploration in Mesoscopic Brain Dynamics , 2000, Perspectives in Neural Computing.

[40]  Alan MacLennan,et al.  The artificial life route to artificial intelligence: Building embodied, situated agents , 1996 .

[41]  J. Cowan,et al.  Excitatory and inhibitory interactions in localized populations of model neurons. , 1972, Biophysical journal.

[42]  W J Freeman,et al.  Relation of olfactory EEG to behavior: factor analysis. , 1987, Behavioral neuroscience.

[43]  John R. Searle,et al.  The Rediscovery of the Mind , 1995, Artif. Intell..

[44]  W. Freeman,et al.  Spatial spectral analysis of human electrocorticograms including the alpha and gamma bands , 2000, Journal of Neuroscience Methods.

[45]  W. Freeman,et al.  Spatial spectra of scalp EEG and EMG from awake humans , 2003, Clinical Neurophysiology.

[46]  Walter J. Freeman,et al.  A Neurobiological Theory of Meaning in Perception. , 2022 .

[47]  W. Freeman,et al.  Spatiotemporal analysis of prepyriform, visual, auditory, and somesthetic surface EEGs in trained rabbits. , 1996, Journal of neurophysiology.

[48]  M. Steriade The Electroencephalogram: Its Patterns and Origins by John S. Barlow, MIT Press, 1993. $95.00 (456 pages) ISBN 0 262023547 , 1994, Trends in Neurosciences.

[49]  A. Clark Being There: Putting Brain, Body, and World Together Again , 1996 .

[50]  John G. Taylor,et al.  Neural networks for consciousness , 1997, Neural Networks.

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

[52]  Alain Destexhe,et al.  Modelling corticothalamic feedback and the gating of the thalamus by the cerebral cortex , 2000, Journal of Physiology-Paris.

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

[54]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[55]  James L. McClelland,et al.  Phenomenology of perception. , 1978, Science.

[56]  Stevan Harnad,et al.  GROUNDING SYMBOLS IN THE ANALOG WORLD WITH NEURAL NETS A Hybrid Model , 1993 .

[57]  D. Amit Modelling Brain Function: The World of Attractor Neural Networks , 1989 .

[58]  J S Kauer,et al.  Mapping of odor-related neuronal activity in the olfactory bulb by high-resolution 2-deoxyglucose autoradiography. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[59]  R. Eckhorn,et al.  Flexible cortical gamma-band correlations suggest neural principles of visual processing , 2001 .

[60]  Erwin H. Ackerknecht,et al.  Mind, Brain and Adaptation in the Nineteenth Century. Cerebral Localization and its Biological Context from Gall to Ferrier , 1971, Medical History.

[61]  R Quian Quiroga,et al.  Performance of different synchronization measures in real data: a case study on electroencephalographic signals. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[62]  C. Campbell,et al.  On Being There , 1965 .

[63]  Frank Rosenblatt,et al.  PRINCIPLES OF NEURODYNAMICS. PERCEPTRONS AND THE THEORY OF BRAIN MECHANISMS , 1963 .

[64]  Peter König,et al.  Binding by temporal structure in multiple feature domains of an oscillatory neuronal network , 1994, Biological Cybernetics.

[65]  Christof Koch,et al.  Coding of Time-Varying Signals in Spike Trains of Integrate-and-Fire Neurons with Random Threshold , 1999, Neural Computation.

[66]  R. Eckhorn,et al.  Amplitude envelope correlation detects coupling among incoherent brain signals , 2000, Neuroreport.

[67]  W. Freeman,et al.  How brains make chaos in order to make sense of the world , 1987, Behavioral and Brain Sciences.

[68]  R. Jindra Mass action in the nervous system W. J. Freeman, Academic Press, New York (1975), 489 pp., (hard covers). $34.50 , 1976, Neuroscience.

[69]  Tom Chen,et al.  Design and implementation , 2006, IEEE Commun. Mag..

[70]  Walter J. Freeman,et al.  Biologically Modeled Noise Stabilizing Neurodynamics for Pattern Recognition , 1998 .

[71]  W Singer,et al.  Visual feature integration and the temporal correlation hypothesis. , 1995, Annual review of neuroscience.

[72]  Walter J. Freeman,et al.  A Neurobiological Theory of Meaning in Perception Part V: Multicortical Patterns of Phase Modulation in Gamma EEG , 2003, Int. J. Bifurc. Chaos.

[73]  Robert Kozma,et al.  Chaotic Resonance - Methods and Applications for Robust Classification of noisy and Variable Patterns , 2001, Int. J. Bifurc. Chaos.

[74]  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.

[75]  Walter J. Freeman,et al.  A Neurobiological Theory of Meaning in Perception Part III: Multiple Cortical Areas Synchronize without Loss of Local Autonomy , 2003, Int. J. Bifurc. Chaos.

[76]  J. Piaget The Child's Conception of Physical Causality , 1927 .

[77]  A. P. Georgopoulos,et al.  Neuronal population coding of movement direction. , 1986, Science.

[78]  Walter J. Freeman,et al.  TUTORIAL ON NEUROBIOLOGY: FROM SINGLE NEURONS TO BRAIN CHAOS , 1992 .

[79]  Christopher J. Bishop,et al.  Pulsed Neural Networks , 1998 .

[80]  W. Freeman,et al.  Aperiodic phase re‐setting in scalp EEG of beta–gamma oscillations by state transitions at alpha–theta rates , 2003, Human brain mapping.

[81]  Tang,et al.  Self-Organized Criticality: An Explanation of 1/f Noise , 2011 .

[82]  J. Panksepp Affective Neuroscience: The Foundations of Human and Animal Emotions , 1998 .

[83]  T. Ferrée,et al.  Fluctuation Analysis of Human Electroencephalogram , 2001, physics/0105029.

[84]  I. Prigogine,et al.  From Being to Becoming: Time and Complexity in the Physical Sciences , 1982 .

[85]  Brian C. Burke,et al.  A neurobiological theory of meaning in perception . Part 4 . Multicortical patterns of amplitude modulation in gamma EEG International Journal of Bifurcation & Chaos [ 2003 ] 13 : in , 2004 .

[86]  R. Traub,et al.  A mechanism for generation of long-range synchronous fast oscillations in the cortex , 1996, Nature.

[87]  R Quian Quiroga,et al.  Event synchronization: a simple and fast method to measure synchronicity and time delay patterns. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[88]  James J. Wright,et al.  Dynamics of the brain at global and microscopic scales: Neural networks and the EEG , 1996, Behavioral and Brain Sciences.

[89]  Tom Stonier,et al.  Information and Meaning , 1997, Springer London.

[90]  William H. Calvin,et al.  The Cerebral Code: Thinking a Thought in the Mosaics of the Mind , 1996 .

[91]  Walter J. Freeman,et al.  NOISE-INDUCED FIRST-ORDER PHASE TRANSITIONS IN CHAOTIC BRAIN ACTIVITY , 1999 .

[92]  W. Freeman How Brains Make Up Their Minds , 1999 .

[93]  B. Baird,et al.  Relation of olfactory EEG to behavior: spatial analysis. , 1987, Behavioral neuroscience.

[94]  F. H. Lopes da Silva,et al.  Anatomic organization and physiology of the limbic cortex. , 1990, Physiological reviews.

[95]  P. Milner,et al.  The functional nature of neuronal oscillations , 1992, Trends in Neurosciences.

[96]  Peter A. Robinson,et al.  Synchronous oscillations in the cerebral cortex , 1998 .

[97]  A. Haig,et al.  Synchronous cortical gamma‐band activity in task‐relevant cognition , 2000, Neuroreport.

[98]  W. Freeman,et al.  Taming chaos: stabilization of aperiodic attractors by noise [olfactory system model] , 1997 .

[99]  W. Freeman,et al.  Change in pattern of ongoing cortical activity with auditory category learning , 2001, Nature.

[100]  Andreas K. Engel,et al.  Temporal Binding, Binocular Rivalry, and Consciousness , 1999, Consciousness and Cognition.

[101]  Leah Edelstein-Keshet,et al.  Do travelling band solutions describe cohesive swarms? An investigation for migratory locusts , 1998 .

[102]  John G. Harris,et al.  Design and implementation of a biologically realistic olfactory cortex in analog VLSI , 2001, Proc. IEEE.

[103]  H. Hendriks-Jansen Catching Ourselves in the Act: Situated Activity, Interactive Emergence, Evolution, and Human Thought , 1996 .

[104]  H. Mayberg Brain Activation , 1994, Neurology.

[105]  R. Traub,et al.  Neuronal fast oscillations as a target site for psychoactive drugs. , 2000, Pharmacology & therapeutics.

[106]  W. J. Nowack Neocortical Dynamics and Human EEG Rhythms , 1995, Neurology.

[107]  R. Freeman,et al.  Intracortical connections are not required for oscillatory activity in the visual cortex: Erratum , 1997, Visual Neuroscience.

[108]  Bard Ermentrout,et al.  Reduction of Conductance-Based Models with Slow Synapses to Neural Nets , 1994, Neural Computation.

[109]  L. Tsitolovsky,et al.  Neurons evaluate both the amplitude and the meaning of signals , 2002, Brain Research.

[110]  W. Freeman,et al.  Changes in spatial patterns of rabbit olfactory EEG with conditioning to odors. , 1982, Psychophysiology.

[111]  P. Nunez,et al.  Spatial filtering and neocortical dynamics: estimates of EEG coherence , 1998, IEEE Transactions on Biomedical Engineering.

[112]  J. Fermaglich Electric Fields of the Brain: The Neurophysics of EEG , 1982 .

[113]  W. Freeman,et al.  Bidirectional processing in the olfactory-limbic axis during olfactory behavior. , 1998, Behavioral neuroscience.

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

[115]  Eugene M. Izhikevich,et al.  Weakly Connected Quasi-periodic Oscillators, FM Interactions, and Multiplexing in the Brain , 1999, SIAM J. Appl. Math..

[116]  L. Ingber Statistical mechanics of multiple scales of neocortical interactions , 1995 .