Oscillatory Brain Dynamics, Wavelet Analysis, and Cognition

Başar, Erol; Demiralp, Tamer; Schürmann, Martin; Başar-Eroğlu, Canan; Ademoğlu, Ahmet

doi:10.1006/brln.1998.2029

Cited by 105 publications

(47 citation statements)

References 57 publications

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“…Although not calculating the correlation between P300 amplitude and power or phase synchrony, others have observed theta power increases following a target tone (Basar et al, 1999;Basar et al, 2001;Demiralp and Basar, 1992) and gamma power increases (Lee et al, 2007) or decreases (Fell et al, 1997;Marshall et al, 1996). Ours may be the first correlational analysis showing a correlation between auditory target P300s and gamma cross-trial phase synchrony.…”

Section: Correlational Analysesmentioning

confidence: 66%

The dependence of P300 amplitude on gamma synchrony breaks down in schizophrenia

et al. 2008

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Introduction-Auditory P300 amplitude reduction in schizophrenia is canonical and may be explained by poor synchronization or reduced power of the underlying neural activity. We asked if patients have reduced synchrony and power, and whether together with P300 amplitude, they make unique or overlapping contributions to the discrimination between patients and controls. We also asked whether people who have large P300s have higher power and greater synchrony of neural activity, and if the relationships between P300 and power and synchrony are different in patients and healthy controls.Methods-We recorded EEG data from 22 controls and 21 patients with schizophrenia (DSM-IV) while they performed an auditory target (p=.10) detection task. We used wavelet analyses to estimate total power and synchrony of delta, theta, alpha, beta, and gamma activity in a 50ms window around the peak of the P300 to the target from the single trial data. We measured P300 amplitude from the average of the single trials, in a 50ms window around its peak.Results and Conclusions-P300 amplitude and delta and theta synchrony were reduced in patients; delta power and synchrony better distinguished between groups than P300 amplitude. In healthy controls, but not patients, gamma synchrony predicted P300 amplitude, but delta did not. In patients, P300 and gamma synchrony are affected by independent factors; the relationship between them is attenuated by an additional pathophysiological process.

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Section: Correlational Analysesmentioning

confidence: 66%

The dependence of P300 amplitude on gamma synchrony breaks down in schizophrenia

et al. 2008

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“…These resonant communication networks (distributed oscillatory systems) may provide a general communication framework parallel to the morphology of distributed sensory networks [150]. Indeed, almost all brain areas are tuned to be activated or resonate with the EEG frequencies [26,130,242,243].…”

Section: Gamma Activity (Indexed By Gamma Spectral Components)mentioning

confidence: 99%

Short-Term EEG Spectral Pattern as a Single Event in EEG Phenomenology~!2009-11-10~!2010-02-22~!2010-09-08~!

Fingelkurts¹

2010

TONIJ

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Spectral decomposition, to this day, still remains the main analytical paradigm for the analysis of EEG oscillations. However, conventional spectral analysis assesses the mean characteristics of the EEG power spectra averaged out over extended periods of time and/or broad frequency bands, thus resulting in a "static" picture which cannot reflect adequately the underlying neurodynamic. A relatively new promising area in the study of EEG is based on reducing the signal to elementary short-term spectra of various types in accordance with the number of types of EEG stationary segments instead of using averaged power spectrum for the whole EEG. It is suggested that the various perceptual and cognitive operations associated with a mental or behavioural condition constitute a single distinguishable neurophysiological state with a distinct and reliable spectral pattern. In this case, one type of short-term spectral pattern may be considered as a single event in EEG phenomenology. To support this assumption the following issues are considered in detail: (a) the relations between local EEG short-term spectral pattern of particular type and the actual state of the neurons in underlying network and a volume conduction; (b) relationship between morphology of EEG short-term spectral pattern and the state of the underlying neurodynamical system i.e. neuronal assembly; (c) relation of different spectral pattern components to a distinct physiological mechanism; (d) relation of different spectral pattern components to different functional significance; (e) developmental changes of spectral pattern components; (f) heredity of the variance in the individual spectral pattern and its components; (g) intra-individual stability of the sets of EEG short-term spectral patterns and their percent ratio; (h) discrete dynamics of EEG short-term spectral patterns. Functional relevance (consistency) of EEG short-term spectral patterns in accordance with the changes of brain functional state, cognitive task and with different neuropsychopathologies is demonstrated.

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“…This bursts are local oscillatory events, present in single trials, and appearing as transient oscillatory synchronizations (TOS) or transient oscillatory desynchronizations (TOD). These synchronizations and desynchronizations correspond to the presence or absence of a coherent neural assembly, respectively (Başar et al 1999). EEG activities are usually analyzed using either time or frequency representations of event related potentials (ERP), which can be interpreted as the reorganization of the spontaneous brain oscillations in response to the stimulus (Başar 1980;Başar et al 1999).…”

Section: Introductionmentioning

confidence: 99%

On the synchrony of steady state visual evoked potentials and oscillatory burst events

et al. 2009

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In this paper, we investigate the large-scale synchrony of EEG oscillatory bursts, during stimulation by a flickering square of light. Whereas most studies focus on averaged raw EEG responses, this study considers oscillatory events within EEG of single trials, which leads to various new insights. We recorded EEG signals before, during and after stimulation by a flickering square of light in medium (16 Hz) and high frequency (32 Hz) ranges. Similar oscillatory bursts, to those observed in spontaneous EEG, can be found in single-trial synchrony of steady state visual evoked potentials (SSVEP). These bursts are extracted from the EEG of single trials using bump modeling. Stochastic event synchrony method is applied to those events, which quantifies synchronies of oscillatory bursts on a large-scale basis. Those oscillatory patterns have a significantly higher degree of co-occurrence during SSVEP, uncorrelated with ongoing signal synchrony. It means that EEG oscillatory patterns are presumably an outcome of brain activity, rather than a mere side effect of ongoing EEG. They undergo a consistent reorganization during visual stimulation, preferentially along the visual pathway, depending on magno or parvo stimulations. Flickering stimuli may induce some cognitive side-effects depending on the stimulation frequency.

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Oscillatory Brain Dynamics, Wavelet Analysis, and Cognition

Cited by 105 publications

References 57 publications

The dependence of P300 amplitude on gamma synchrony breaks down in schizophrenia

The dependence of P300 amplitude on gamma synchrony breaks down in schizophrenia

Short-Term EEG Spectral Pattern as a Single Event in EEG Phenomenology~!2009-11-10~!2010-02-22~!2010-09-08~!

On the synchrony of steady state visual evoked potentials and oscillatory burst events

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