Background EEG analytic phase 1 Walter J Freeman http://sulcus.berkeley.edu/wjf/EH_EEGPart2AnalyticPhase.pdf Origin, structure, and role of background EEG activity. Part 2. Analytic phase Walter J Freeman Clinical Neurophysiology (2004) 115: 2089-2107. Department of Molecular & Cell Biology, LSA142 University of California Berkeley CA 94720-3200 USA Tel. 1-510-642-4220 Fax 1-510-643-6791 [email protected] http://sulcus.berkeley.edu Running title: Background EEG analytic phase Key Words: analytic phase, basis function, phase cone, phase gradient, self-organized criticality, spatial EEG pattern, spontaneous cortical activity Acknowledgments This study was supported by grant MH 06686 from the National Institute of Mental Health, and by grants NCC 2-1244 from the National Aeronautics and Space Administration EIA-0130352 from the National Science Foundation to Robert Kozma. Programming was by Brian C. Burke. Essential contributions to surgical preparation and training of animals, data acquisition, and data analysis by John Barrie, Gyöngyi Gaál, and Linda Rogers are gratefully acknowledged.Background EEG analytic phase 2 Walter J Freeman http://sulcus.berkeley.edu/wjf/EH_EEGPart2AnalyticPhase.pdf Abstract Objective: To explain spontaneous EEG through measurements of spatiotemporal patterns of phase among beta-gamma oscillations. Methods: High-density 8x8 intracranial arrays were fixed over sensory cortices of rabbits. EEGs were spatially low pass filtered, temporally band pass filtered and segmented in overlapping windows stepped at 2 ms. Phase was measured with the cosine as the temporal basis function, using both Fourier and Hilbert transforms to compensate for their respective limitations. Spatial patterns in 2-D phase surfaces were measured with the geometric form of the cone as the spatial basis function. Results: Two fundamental state variables were measured at each digitizing step in the 64 EEGs: the rate of change in phase with time (frequency) and the rate of change in phase with distance (gradient). The parameters of location, diameter, duration, and phase velocity of the cone of phase were derived from these two state variables. Parameter distributions including recurrence intervals extending into the low theta range were fractal; the mean values varied with window duration and interelectrode distance. Conclusions: The formation of spatial amplitude patterns began with state transitions that were documented by phase discontinuities and phase cones. The multiplicity of overlapping cones indicated that sensory neocortices maintained a scale-free state of self-organized criticality (SOC) in each hemisphere as the basis for its rapid integration of sensory input with prior learning stored in cortical synaptic webs. Further evidence came from the fractal properties of the phase parameters and the self-similarity of phase patterns in the ms/mm to m/s ranges. Significance: These EEG data suggest that neocortical dynamics is analogous to the dynamics of self-stabilizing systems, such as a sand pile that maintains its critical angle by avalanches, and a pan of boiling water that maintains its critical temperature by bubbles that release heat. Beta-gamma oscillations stem from the ability of neocortex to maintain its stability under continuous sensory bombardment. Modeling implies that the critical parameter of neocortex (analogous to angle of repose or temperature) is the mean firing rates of neurons that are homeostatically regulated by refractory periods everywhere at all times in cortex. The advantage of SOC in perception may be the ability it gives neocortex to generate instantaneous global state transitions (avalanches, bubbles) large enough to include the multiple sensory areas that are necessary to form Gestalts (multisensory percepts).Background EEG analytic phase 3 Walter J Freeman http://sulcus.berkeley.edu/wjf/EH_EEGPart2AnalyticPhase.pdf 1. Introduction 1.1. Sudden changes in EEG occur simultaneously over large distances: state transitions Human perception takes place in rapid frames that engage voluminous sensory input in situations, such as a feeling about the shoulders when trying on a new coat, an understanding that a friend is angry or frightened, a flash of recognition of the identity and state of mind of a parent with one word on the telephone, and so on. Brains are usually in states of arousal and expectancy before the arrival of stimuli. These states are normally prerequisite for perception. EEG and MEG from humans and animals in such states give evidence of background spatiotemporal waves of potential that flicker ceaselessly all over the head, like the background noise of traffic, wind and surf. How might neurons create these background oscillations through interactions, and how might these waves contribute to phenomenological experiences before, during and after expected stimuli? Recent efforts to open background activity to exploration have included recording scalp EEG with a high-density electrode array (Freeman et al., 2003) and analyzing the signals with the Hilbert transform (Freeman, Burke and Holmes, 2003). The unprecedented spatial and temporal resolution afforded by these new techniques, which were developed from research on rabbit brains, revealed remarkably detailed patterns in the seemingly featureless chaotic oscillations in electrical potential found everywhere over the scalp. Most striking was the widespread synchrony in oscillations at frequencies broadly distributed over the beta-gamma range that were aperiodically re-initialized at intervals corresponding to rates in the theta-alpha range. The distances across which the waves were synchronized varied among subjects and across samples, ranging up to 189 mm (the length of the array). Evidence was found for textures of amplitude at the scale of the gyri, 1 to 3 cm in length, indicating synchrony that extended across multiple gyri and sulci. Temporally the synchrony was interrupted but then re-established in phase jumps. Each jump lasted only a few ms and recurred at irregular intervals, yet successive jumps were nearly simultaneous, even over long distances. In subjects at rest with