Dynamics of human neocortex that optimizes its stability and flexibility

The electroencephalogram (EEG) in states of awake, sleep, and seizure in a patient with intractable partial complex seizures was recorded through a 1‐ × 1‐cm microgrid of 64 electrodes on the right inferior temporal gyrus during a week‐long neurosurgical evaluation. Comparisons with a normal intracranial EEG were perforce from animals. Analytic phase and amplitude from the Hilbert transform gave the temporal resolution needed to resolve EEG spatiotemporal structure. The rest state revealed multiple overlapping patterns of high‐frequency coherent oscillations resembling bubbles in boiling water. Bubble diameters gave estimates of the distances across the cortex over which the cortical oscillations were synchronized. Superimposed on these bubbles were large‐sized epochs of phase locking with briefly constant frequency and high amplitude. These coordinated analytic phase differences occurred between short periods of high phase variance. The variance gave evidence for state transitions between transiently stable states with constant phase gradients. In sleep these phase patterns persisted with reduced amplitude, occasionally interrupted by long‐lasting (∼1 s) epochs with no spatial textures in phase and amplitude despite a large increase in amplitude. Seizures had high amplitude 3/s spikes with steep spatial gradients. Onset occurred after pre‐ictal reduction in bubble diameters as evidence for large‐scale cortical disintegration preceding loss of stability. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 881–901, 2006.

[1]  H. Haken.  Synergetics: an Introduction, Nonequilibrium Phase Transitions and Self-organization in Physics, Chemistry, and Biology , 1977 .

[2]  W. Freeman,et al.  Nonlinear brain dynamics as macroscopic manifestation of underlying many-body field dynamics , 2005, q-bio/0511037.

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

[4]  Sampsa Vanhatalo,et al.  Fine spatiotemporal structure of phase in human intracranial EEG , 2006, Clinical Neurophysiology.

[5]  Frank W. Ohl,et al.  Early and late patterns of stimulus-related activity in auditory cortex of trained animals , 2003, Biological Cybernetics.

[6]  Michel Le Van Quyen,et al.  Spatio-temporal dynamics prior to neocortical seizures: amplitude versus phase couplings , 2003, IEEE Transactions on Biomedical Engineering.

[7]  A. Opstal.  Dynamic Patterns: The Self-Organization of Brain and Behavior , 1995 .

[8]  Walter J. Freeman,et al.  A neurobiological theory of meaning in perception , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[9]  J. Martinerie,et al.  The brainweb: Phase synchronization and large-scale integration , 2001, Nature Reviews Neuroscience.

[10]  C. Stam,et al.  Nonlinear synchronization in EEG and whole‐head MEG recordings of healthy subjects , 2003, Human brain mapping.

[11]  Walter J. Freeman,et al.  A Neurobiological Theory of Meaning in Perception Part I: Information and Meaning in Nonconvergent and Nonlocal Brain Dynamics , 2003, Int. J. Bifurc. Chaos.

[12]  Ichiro Tsuda,et al.  Towards an interpretation of dynamic neural activity in terms of chaotic dynamical systems , 2000 .

[13]  Henrik Jeldtoft Jensen,et al.  Self-Organized Criticality: Emergent Complex Behavior in Physical and Biological Systems , 1998 .

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

[15]  M. Weliky,et al.  Small modulation of ongoing cortical dynamics by sensory input during natural vision , 2004, Nature.

[16]  Karl J. Friston.  The labile brain. I. Neuronal transients and nonlinear coupling. , 2000, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[17]  Gyöngyi Gaál,et al.  A neurobiological theory of meaning in perception . Part 3 . Multiple cortical areas synchronize without loss of local autonomy International Journal of Bifurcation & Chaos [ 2003 ] 13 : in press , 2003 .

[18]  Robert T. Knight,et al.  Neurobiology: sleep on it. , 2004 .

[19]  W. Freeman.  Origin, structure, and role of background EEG activity. Part 2. Analytic phase , 2004, Clinical Neurophysiology.

[20]  Donald O. Walter,et al.  Mass action in the nervous system , 1975 .

[21]  P. Maquet.  Sleep on it! , 2000, Nature Neuroscience.

[22]  Walter J. Freeman,et al.  Origin, structure, and role of background EEG activity. Part 3. Neural frame classification , 2005, Clinical Neurophysiology.

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

[24]  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.

[25]  I. Tsuda.  Toward an interpretation of dynamic neural activity in terms of chaotic dynamical systems. , 2001, The Behavioral and brain sciences.

[26]  Walter J. Freeman,et al.  Origin, structure, and role of background EEG activity. Part 1. Analytic amplitude , 2004, Clinical Neurophysiology.

[27]  G. Tononi,et al.  Sleep and synaptic homeostasis: a hypothesis , 2003, Brain Research Bulletin.

[28]  Walter J. Freeman,et al.  Petit mal seizure spikes in olfactory bulb and cortex caused by runaway inhibition after exhaustion of excitation , 1986, Brain Research Reviews.

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

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

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

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

[33]  Henrik Jeldtoft Jensen,et al.  Self-Organized Criticality , 1998 .

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

[35]  G. Tononi,et al.  Local sleep and learning , 2004, Nature.

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

[37]  Karl J. Friston,et al.  Symmetries and itineracy in nonlinear systems with many degrees of freedom , 2001 .

[38]  Mario Rosanova,et al.  Neuronal mechanisms mediating the variability of somatosensory evoked potentials during sleep oscillations in cats , 2005, The Journal of physiology.

[39]  A. Plaza,et al.  Spatial/Spectral analysis of hyperspectral image data , 2003, IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, 2003.