Phase synchronization of the ongoing EEG and auditory EP generation

Jansen, Ben H.; Agarwal, G.; Hegde, A.; Boutros, Nashaat N.

doi:10.1016/s1388-2457(02)00327-9

Cited by 113 publications

(74 citation statements)

References 21 publications

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“…Conversely, when activity is high, single-trial responses do not show any amplitude modulation and yet still produce an ERP on averaging. This is consistent with the observations of Jansen et al (2003) and Makeig et al (2002).…”

Section: Stochastic Simulationssupporting

confidence: 93%

“…This dependency on ongoing activity is revealed by variation in the evoked responses with high input levels. In conclusion, the apparently contradictory results presented in Arieli et al (1996), Jansen et al (2003), Makeig et al (2002) and Shah et al (2004) can be reproduced in most part and reconciled within the same framework. With high activity levels, the ongoing and stimulusdependent components interact, through nonlinearities in the population dynamics, to produce phase-resetting and a classical ERP on averaging.…”

Section: Testing For Interactionssupporting

confidence: 51%

“…However, several groups (Jansen et al, 2003;Klimesch et al, 2004;Kolev and Yordanova, 1997;Makeig et al, 2002) have suggested that some ERP/ERF components might be generated by stimulus-induced changes in ongoing brain dynamics. This is consistent with views emerging from several neuroscientific fields, suggesting that phase-synchronisation, of ongoing rhythms, across different spatio-temporal scales mediates the functional integration necessary to perform higher cognitive tasks Varela et al, 2001).…”

Section: Mechanisms Of Erp/erf Generation; Linear or Nonlinear?mentioning

confidence: 99%

“…In this scheme, the variability at the single-trial level is due to, and only to, ongoing activity, which is removed after averaging to estimate the impulse response. On the other hand, it has been hypothesised that eventrelated waveforms, obtained after averaging, could be due to a phase-resetting of ongoing activity with no necessary change in the amplitude (i.e., power) of any stimulus locked transient (Jansen et al, 2003;Makeig et al, 2002). Although mathematically well defined, the neural mechanisms that could instantiate phaseresetting of ongoing activity are unknown.…”

Section: Phase-resetting and Nonlinear Interactionsmentioning

confidence: 99%

“…Some authors (Arieli et al, 1996;Shah et al, 2004) have argued that ERPs/ERFs can be considered as the impulse response function of a linear system, despite the huge variability at the single-trial level. In contrast, it has been proposed (Duzel et al, 2003;Jansen et al, 2003;Klimesch et al, 2004;Makeig et al, 2002) that ERPs/ERFs could be due to a phase-resetting process that does not require the notion of a linear impulse response. This induces some hypothetical neural mechanism that can implement a phase-resetting of ongoing activity.…”

Section: Stochastic Simulationsmentioning

confidence: 99%

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Modelling event-related responses in the brain

2005

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The aim of this work was to investigate the mechanisms that shape evoked electroencephalographic (EEG) and magneto-encephalographic (MEG) responses. We used a neuronally plausible model to characterise the dependency of response components on the models parameters. This generative model was a neural mass model of hierarchically arranged areas using three kinds of inter-area connections (forward, backward and lateral). We investigated how responses, at each level of a cortical hierarchy, depended on the strength of connections or coupling. Our strategy was to systematically add connections and examine the responses of each successive architecture. We did this in the context of deterministic responses and then with stochastic spontaneous activity. Our aim was to show, in a simple way, how event-related dynamics depend on extrinsic connectivity. To emphasise the importance of nonlinear interactions, we tried to disambiguate the components of event-related potentials (ERPs) or event-related fields (ERFs) that can be explained by a linear superposition of trial-specific responses and those engendered nonlinearly (e.g., by phase-resetting). Our key conclusions were; (i) when forward connections, mediating bottom-up or extrinsic inputs, are sufficiently strong, nonlinear mechanisms cause a saturation of excitatory interneuron responses. This endows the system with an inherent stability that precludes nondissipative population dynamics. (ii) The duration of evoked transients increases with the hierarchical depth or level of processing. (iii) When backward connections are added, evoked transients become more protracted, exhibiting damped oscillations. These are formally identical to late or endogenous components seen empirically. This suggests that late components are mediated by reentrant dynamics within cortical hierarchies. (iv) Bilateral connections produce similar effects to backward connections but can also mediate zero-lag phase-locking among areas. (v) Finally, with spontaneous activity, ERPs/ERFs can arise from two distinct mechanisms: For low levels of (stimulus related and ongoing) activity, the systems response conforms to a quasi-linear superposition of separable responses to the fixed and stochastic inputs. This is consistent with classical assumptions that motivate trial averaging to suppress spontaneous activity and disclose the ERP/ ERF. However, when activity is sufficiently high, there are nonlinear interactions between the fixed and stochastic inputs. This interaction is expressed as a phase-resetting and represents a qualitatively different explanation for the ERP/ERF. D 2004 Elsevier Inc. All rights reserved.Keywords: Electroencephalography; Magnetoencephalography; Neural networks; Nonlinear dynamics; Causal modelling IntroductionClassical event-related potentials (ERPs) and event-related fields (ERFs) have been used for decades as putative electrophysiological correlates of perceptual and cognitive operations. However, the exact neurobiological mechanisms underlying their generation are largely unk...

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Section: Stochastic Simulationssupporting

confidence: 93%

Section: Testing For Interactionssupporting

confidence: 51%

Section: Mechanisms Of Erp/erf Generation; Linear or Nonlinear?mentioning

confidence: 99%

Section: Phase-resetting and Nonlinear Interactionsmentioning

confidence: 99%

Section: Stochastic Simulationsmentioning

confidence: 99%

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Modelling event-related responses in the brain

2005

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Neural mechanisms of evoked oscillations: Stability and interaction with transient events

Moratti

Clementz

Gao

et al. 2007

Human Brain Mapping

104

100

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There is increasing evidence that early event-related potentials are a result of phase alignment of ongoing background oscillations of the electroencephalogram rather than additive amplitude modulation. Steady state visual-evoked potentials (ssVEPs) can be recorded using an intensity modulated stimulus, resulting in an evoked brain response at a known frequency, i.e. the stimulation frequency. Given this property, the ssVEP is ideally suited for examining the relationship between single-trial fluctuations in phase/amplitude and the evoked brain potential resulting from averaging across trials. To address this issue, the current study investigated the contribution of single trial power and intertrial phase locking to ssVEP generation by presenting a peripheral flicker. Further, transient stimuli were presented during flicker and at three increasing latency lags following flicker offset to examine (1) to what extent a stimulus can disturb the ssVEP oscillation and (2) how phase alignment during P1-N1-P2 time windows is affected during presence of evoked oscillations. The former assessment evaluates the stability of ssVEPs and the latter the phase alignment processes to transient stimuli under experimentally induced background oscillations. We observed that ssVEPs are a result of phase alignment rather than single trial amplitude modulation. In addition, ssVEP oscillations were not disturbed by transient stimuli. Finally, phase alignment in P1-N1-P2 time windows was distorted during and shortly after steady state stimulation. We conclude that ssVEPs represent strongly phase locked oscillations sharing the same generation mechanisms as early evoked potentials.

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Movement gating of beta/gamma oscillations involved in the N30 somatosensory evoked potential

Cebolla

Saedeleer

Bengoetxea

et al. 2008

Human Brain Mapping

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Evoked potential modulation allows the study of dynamic brain processing. The mechanism of movement gating of the frontal N30 component of somatosensory evoked potentials (SEP) produced by the stimulation of the median nerve at wrist remains to be elucidated. At rest, a power enhancement and a significant phase-locking of the electroencephalographic (EEG) oscillation in the beta/gamma range (25-35 Hz) are related to the emergence of the N30. The latter was also perfectly identified in presence of pure phase-locking situation. Here, we investigated the contribution of these rhythmic activities to the specific gating of the N30 component during movement. We demonstrated that concomitant execution of finger movement of the stimulated hand impinges such temporal concentration of the ongoing beta/gamma EEG oscillations and abolishes the N30 component throughout their large topographical extent on the scalp. This also proves that the phase-locking phenomenon is one of the main actors for the N30 generation. These findings could be explained by the involvement of neuronal populations of the sensorimotor cortex and other related areas, which are unable to respond to the phasic sensory activation and to phase-lock their firing discharges to the external sensory input during the movement. This new insight into the contribution of phase-locked oscillation in the emergence of the N30 and in its gating behavior calls for a reappraisal of fundamental and clinical interpretation of the frontal N30 component.

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Phase synchronization of the ongoing EEG and auditory EP generation

Cited by 113 publications

References 21 publications

Modelling event-related responses in the brain

Modelling event-related responses in the brain

Neural mechanisms of evoked oscillations: Stability and interaction with transient events

Movement gating of beta/gamma oscillations involved in the N30 somatosensory evoked potential

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