EG_EEGPart1AnalyticA-- - Note on a simple method to measure ---

By Derek Lawrence,2014-08-09 03:38
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EG_EEGPart1AnalyticA-- - Note on a simple method to measure ---

Background EEG analytic amplitude 1 Walter J Freeman

    Origin, structure, and role of background EEG activity.

    Part 1. Analytic amplitude;

    Walter J Freeman

    Clinical Neurophysiology (2004) 115: 2077-2088.

    Department of Molecular & Cell Biology, LSA 142

    University of California

    Berkeley CA 94720-3200 USA

    Tel. 1-510-642-4220 Fax 1-510-643-6791

    Running title: Background EEG analytic amplitude

    Key words: analytic amplitude, gamma EEG oscillations, Hilbert transform, information, order

    parameter, stability, synchrony


    This study was supported by grant MH 06686 from the National Institute of Mental Health, grant NCC 2-1244 from the National Aeronautics and Space Administration, and grant 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, as well as discussions of theory with Harald Atmanspacher, Giuseppe Vitiello, and Ichiro Tsuda.

Background EEG analytic amplitude 2 Walter J Freeman


Objective: To explain the neural mechanisms of spontaneous EEG by measuring the

    spatiotemporal patterns of synchrony among beta-gamma oscillations during perception.

    Methods: EEGs were measured from 8x8 (5.6x5.6 mm) arrays fixed on the surfaces of primary sensory areas in rabbits that were trained to discriminate visual, auditory or tactile conditioned stimuli (CSs) eliciting conditioned responses (CRs). EEG preprocessing was by (i) band pass filtering to extract the beta-gamma range (deleting theta-alpha); (ii) low-pass spatial filtering (not high-pass Laplacians used for localization), (iii) spatial averaging (not time averaging used for evoked potentials), and (iv) close spacing of 64 electrodes for simultaneous recording in each area (not sampling single signals from several areas); (v) novel algorithms were devised to measure synchrony and spatial pattern stability by calculating variances among patterns in 64-space derived from the 8x8 arrays (not by fitting equivalent dipoles). These methodological differences are crucial for the proposed new perspective on EEG.

    Results: Spatial patterns of beta-gamma EEG emerged following sudden jumps in cortical activity called ―state transitions‖. Each transition began with an abrupt phase re-setting to a new

    value on every channel, followed sequentially by re-synchronization, spatial pattern stabilization, and a dramatic increase in pattern amplitude. State transitions recurred at varying intervals in the theta range. A novel parameter was devised to estimate the perceptual information in the beta-gamma EEG, which disclosed 2 to 4 patterns with high information content in the CS-CR interval on each trial; each began with a state transition and lasted ~.1 s.

    Conclusions: The function of each primary sensory neocortex was discontinuous; discrete spatial patterns occurred in frames like those in cinema. The frames before and after the CS-CR interval had low content.

    Significance: Derivation and interpretation of unit data in studies of perception might benefit from using multichannel EEG recordings to define distinctive epochs that are demarcated by state transitions of neocortical dynamics in the CS-CR intervals, particularly in consideration of the possibility that EEG may reveal recurring episodes of exchange and sharing of perceptual information among multiple sensory cortices. Simultaneously recorded, multichannel beta-gamma EEG might assist in the interpretation of images derived by fMRI, since high beta-gamma EEG amplitudes imply high rates of energy utilization. The spatial pattern intermittency provides a tag to distinguish gamma bursts from contaminating EMG activity in scalp recording in order to establish beta-gamma recording as a standard clinical tool. Finally, EEG cannot fail to have a major impact on brain theory.

Background EEG analytic amplitude 3 Walter J Freeman

    Cover Figure Legend: The EEG shows that neocortex processes information in frames like a cinema. The perceptual content is found in the phase plateaus from rabbit EEG; similar content is predicted to be found in the plateaus of human scalp EEG. The phase jumps show the shutter. The resemblance across a 33-fold difference in width of the zones of coordinated activity reveals the self-similarity of the global dynamics that may form Gestalts (multisensory percepts). Upper frame: coordinated analytic phase differences (CAPD) calculated from human EEG in the beta band (12-30 Hz) with 3 mm spacing of 64 electrodes in a linear 189 mm array digitized at 1 ms intervals.

    Lower frame: CAPD calculated from rabbit EEG in the gamma band (20-50 Hz) with 8x8 0.79 mm spacing 5.6x5.6 mm array digitized at 2 ms intervals.

    The human EEG data from a normal subject awake with eyes closed were provided by Mark D. Holmes in the EEG & Clinical Neurophysiology Laboratory, Harborview Medical Center, University of Washington, Seattle WA and Sampsa Vanhatalo, Department of Clinical Neurophysiology, University of Helsinki, Finland, using 64 of the 256-channel recording System 200 provided by Don Tucker, Electrical Geodesics Incorporated, Riverfront Research Park, Eugene OR.

Background EEG analytic amplitude 4 Walter J Freeman