What Can Synergetics Contribute to the Understanding of Brain Functioning?

Haken, Hermann

doi:10.1007/978-3-642-60007-4_2

Cited by 28 publications

(43 citation statements)

References 26 publications

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“…However, one can easily envision cell assemblies (e.g., neural networks) operating within a background environment of synaptic action fields [Nunez, 2000a[Nunez, , 2000b. In this picture, neural networks may be defined in terms of strong preferential connections, strengthened by Hebbian mechanisms, and continuously reformed on millisecond time scales Cutillo, 1986, 1995;Silberstein, 1995b;Ingber, 1995aIngber, , 1995bNunez, 1995Nunez, , 2000aJirsa and Haken, 1997;Haken, 1999;Edelman and Tononi, 2000]. However, such networks are likely to remain partly (functionally) connected to other tissue not part of the same network.…”

Section: Synaptic Action Is Imperfectly Related To Measured Potentialsmentioning

confidence: 98%

“…The (generally unknown) functions p lm (t) are determined by the dynamic properties of neocortical sources. These are known as order parameters in the field of complex systems theory or, more specifically, the field of synergetics [Haken, 1983[Haken, , 1999. The general idea of synergetics is that many disparate complex [Friedrick et al, 1992;Fuchs et al, 1992;Kelso, 1995].…”

Section: Dipole Moment Per Unit Volume At Mesoscopic Scalesmentioning

confidence: 99%

“…However, given the extreme complexity and interconnectedness of brains, it appears wise to consider them in attempts to find the physiological bases for EEG [Ingber, 1982[Ingber, , 1995Freeman and Skarda, 1985;Nunez, 1995Nunez, , 1999Nunez, , 2000aNunez, , 2000bTononi et al, 1994;Friston et al, 1995;Tononi and Edelman, 1998;Haken, 1999;Kelso et al, 1999].…”

Section: Possible Physiological Bases For Alpha Rhythmsmentioning

confidence: 99%

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Spatial‐temporal structures of human alpha rhythms: Theory, microcurrent sources, multiscale measurements, and global binding of local networks

Nunez¹,

Wingeier²,

Silberstein³

2001

Human Brain Mapping

472

356

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A theoretical framework supporting experimental measures of dynamic properties of human EEG is proposed with emphasis on distinct alpha rhythms. Robust relationships between measured dynamics and cognitive or behavioral conditions are reviewed, and proposed physiological bases for EEG at cellular levels are considered. Classical EEG data are interpreted in the context of a conceptual framework that distinguishes between locally and globally dominated dynamic processes, as estimated with coherence or other measures of phase synchronization. Macroscopic (scalp) potentials generated by cortical current sources are described at three spatial scales, taking advantage of the columnar structure of neocortex. New EEG data demonstrate that both globally coherent and locally dominated behavior can occur within the alpha band, depending on narrow band frequency, spatial measurement scale, and brain state. Quasi-stable alpha phase structures consistent with global standing waves are observed. At the same time, alpha and theta phase locking between cortical regions during mental calculations is demonstrated, consistent with neural network formation. The brain-binding problem is considered in the context of EEG dynamic behavior that generally exhibits both of these local and global aspects. But specific experimental designs and data analysis methods may severely bias physiological interpretations in either local or global directions.

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Section: Synaptic Action Is Imperfectly Related To Measured Potentialsmentioning

confidence: 98%

Section: Dipole Moment Per Unit Volume At Mesoscopic Scalesmentioning

confidence: 99%

Section: Possible Physiological Bases For Alpha Rhythmsmentioning

confidence: 99%

See 1 more Smart Citation

Spatial‐temporal structures of human alpha rhythms: Theory, microcurrent sources, multiscale measurements, and global binding of local networks

Nunez¹,

Wingeier²,

Silberstein³

2001

Human Brain Mapping

472

356

View full text Add to dashboard Cite

show abstract

“…Long axons of excitatory neurons with high conduction velocities support synchronization over large areas of cortex (Freeman, 2003b), creating small-world effects (Watts and Strogatz, 1998;Wang and Chen, 2003) in analogy to the rapid dissemination of information through social contacts. The importance of long-distance correlations has been emphasized by numerous brain theorists (e.g., Ingber, 1995;Hoppenstaedt and Izhkevich, 1998;Haken, 1999;Friston, 2000;LinkenkaerHansen et al, 2001;Vitiello, 2001;Kaneko and Tsuda, 2001;Kozma, Freeman and Erdí, 2003;Stam et al, 2003).…”

Section: A Hypothesis On Cortical Function Based In Background Activitymentioning

confidence: 99%

Origin, structure, and role of background EEG activity. Part 1. Analytic amplitude

Freeman

2004

Clinical Neurophysiology

230

240

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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 betagamma 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 betagamma EEG might assist in the interpretation of images derived by fMRI, since high betagamma 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 3Walter J Freeman http://sulcus.berkeley.edu/wjf/EG_EEGPart1AnalyticAmplitude.pdf Cover Figure Legend:The EEG shows that neocortex processes information in frames like a cinema. The perceptual content is foun...

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“…The ␤ and ␥ oscillations that are detected at the scalp require coordinated activity of millions of neurons. The order parameter that they create and that "enslaves" [Haken, 1999] their firing patterns must permeate throughout the populations. Suppose that a sensory stimulus excites the activity of a collection of feature detector neurons [Singer and Gray, 1995] forming a cloud of action potentials like molecules in a gas.…”

Section: Self-organized Criticality and Anomalous Dispersionmentioning

confidence: 99%

Aperiodic phase re‐setting in scalp EEG of beta–gamma oscillations by state transitions at alpha–theta rates

Freeman

Burke

Holmes

2003

Human Brain Mapping

189

153

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Abstract:We evaluated the rapid changes in regional scalp EEG synchronization in normal subjects with spatial and temporal resolution exceeding prior art 10-fold with a high spatial density array and the Hilbert transform. A curvilinear array of 64 electrodes 3 mm apart extending 18.9 cm across the scalp was used to record EEG at 200/sec. Analytic amplitude (AA) and phase (AP) were calculated at each time step for the 64 traces in the analog pass band of 0.5-120 Hz. AP differences approximated the AP derivative (instantaneous frequency). The AP from unfiltered EEG revealed no reproducible patterns. Filtering was necessary in the ␤ and gamma ranges according to a technique that optimized the correlation of the AP differences with the activity band pass filtered in the alpha range. The sizes of temporal AP differences were usually within Ϯ0.5 radian from the average step corresponding to the center frequency of the pass band. Large AP differences were often synchronized over distances of 6 to 19 cm. An optimal pass band to detect and measure these recurring jumps in AP in the ␤ and ␥ ranges was found by maximizing the ␣ peak in the cospectrum of the correlation between unfiltered EEG and the band pass AP differences. Synchronized AP jumps recurred in clusters (CAP) at ␣ and theta rates in resting subjects and with EMG. Cortex functions by serial changes in state. The Hilbert transform of EEG from high-density arrays can visualize these state transitions with high temporal and spatial resolution and should be useful in relating EEG to cognition.

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What Can Synergetics Contribute to the Understanding of Brain Functioning?

Cited by 28 publications

References 26 publications

Spatial‐temporal structures of human alpha rhythms: Theory, microcurrent sources, multiscale measurements, and global binding of local networks

Spatial‐temporal structures of human alpha rhythms: Theory, microcurrent sources, multiscale measurements, and global binding of local networks

Origin, structure, and role of background EEG activity. Part 1. Analytic amplitude

Aperiodic phase re‐setting in scalp EEG of beta–gamma oscillations by state transitions at alpha–theta rates

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