Habituation of the Visually Evoked Potential and Its Vascular Response: Implications for Neurovascular Coupling in the Healthy Adult

Obrig, Hellmuth; Israel, Heike; Kohl‐Bareis, Matthias; Uludağ, Kâmil; Wenzel, Rüdiger; Müller, Bianca; Arnold, G.; Villringer, Arno

doi:10.1006/nimg.2002.1177

Cited by 124 publications

(83 citation statements)

References 71 publications

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“…This negative trend in the response can be explained as habituation or nerve fatigue effects. Obrig et al [2] recently demonstrated that similar effects are also present during visual stimulation, both in EEG and near infra red spectroscopy data. To extract these effects from the EEG data, the responses were averaged over 15 trials (of .33 s), and trends were computed over 12 of these subsequent averages.…”

Section: Discussionmentioning

confidence: 83%

“…On the other hand, it is known from experiments that the constant response assumption is false in general. Examples of trial-to-trial variations in human EEG are habituation effects [1], [2], P300 effects and event-related synchronization and de-synchronization effects [3], [4]. However, because these effects are generally small, it is not straightforward to prove that these effects are really present in the data, and to distinguish them from the background noise.…”

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confidence: 99%

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A Maximum-Likelihood Estimator for Trial-to-Trial Variations in Noisy MEG/EEG Data Sets

Munck

Bijma

Gaura

et al. 2004

IEEE Trans. Biomed. Eng.

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Abstract-The standard procedure to determine the brain response from a multitrial evoked magnetoencephalography (MEG) or electroencephalography (EEG) data set is to average the individual trials of these data, time locked to the stimulus onset. When the brain responses vary from trial-to-trial this approach is false. In this paper, a maximum-likelihood estimator is derived for the case that the recorded data contain amplitude variations. The estimator accounts for spatially and temporally correlated background noise that is superimposed on the brain response.The model is applied to a series of 17 MEG data sets of normal subjects, obtained during median nerve stimulation. It appears that the amplitude of late component (30-120 ms) shows a systematic negative trend indicating a weakening response during stimulation time. For the early components (20-35 ms) no such a systematic effect was found. The model is furthermore applied on a MEG data set consisting of epileptic spikes of constant spatial distribution but varying polarity. For these data, the advantage of applying the model is that positive and negative spikes can be processed with a single model, thereby reducing the number of degrees of freedom and increasing the signal-to-noise ratio.

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Section: Discussionmentioning

confidence: 83%

mentioning

confidence: 99%

A Maximum-Likelihood Estimator for Trial-to-Trial Variations in Noisy MEG/EEG Data Sets

Munck

Bijma

Gaura

et al. 2004

IEEE Trans. Biomed. Eng.

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“…More than a century after the seminal work of Roy and Sherrington (1890), neurovascular coupling and its underlying physiological and metabolic processes are still incompletely understood; however, their exploration is accelerating Magistretti, 1994, 2004;Villringer and Dirnagl, 1995;Obrig et al, 2002;Caesar et al, 2003a,b;Chatton et al, 2003;Parri and Crunelli, 2003). Part of this growing interest might be explained by the increasing use of hemodynamic-based functional brain mapping techniques such as optical imaging, positron emission tomography, and functional magnetic resonance imaging (fMRI), on one hand, whereas on the other hand, our understanding of the hemodynamic signals with respect to the underlying neuronal activity in terms of input, output, and local processing (Logothetis, 2003) is still incomplete.…”

Section: Introductionmentioning

confidence: 99%

Compartment-Resolved Imaging of Activity-Dependent Dynamics of Cortical Blood Volume and Oximetry

Vanzetta¹,

Hildesheim²,

Grinvald³

2005

J. Neurosci.

114

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Optical imaging, positron emission tomography, and functional magnetic resonance imaging (fMRI) all rely on vascular responses to image neuronal activity. Although these imaging techniques are used successfully for functional brain mapping, the detailed spatiotemporal dynamics of hemodynamic events in the various microvascular compartments have remained unknown. Here we used highresolution optical imaging in area 18 of anesthetized cats to selectively explore sensory-evoked cerebral blood-volume (CBV) changes in the various cortical microvascular compartments. To avoid the confounding effects of hematocrit and oximetry changes, we developed and used a new fluorescent blood plasma tracer and combined these measurements with optical imaging of intrinsic signals at a near-isosbestic wavelength for hemoglobin (565 nm). The vascular response began at the arteriolar level, rapidly spreading toward capillaries and venules. Larger veins lagged behind. Capillaries exhibited clear blood-volume changes. Arterioles and arteries had the largest response, whereas the venous response was smallest. Information about compartment-specific oxygen tension dynamics was obtained in imaging sessions using 605 nm illumination, a wavelength known to reflect primarily oximetric changes, thus being more directly related to electrical activity than CBV changes. Those images were radically different: the response began at the parenchyma level, followed only later by the other microvascular compartments. These results have implications for the modeling of fMRI responses (e.g., the balloon model). Furthermore, functional maps obtained by imaging the capillary CBV response were similar but not identical to those obtained using the early oximetric signal, suggesting the presence of different regulatory mechanisms underlying these two hemodynamic processes.

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“…(Franceschini et al, 2000;Kennan et al, 2002;Colier et al, 2001;Obrig et al, 2002;Sato et al, 1999;Hoshi et al, 2000) The compatibility of optical imaging with other neuroimaging methods has received wide interest. Optical measurements have been successfully combined with fMRI (Kleinschmidt et al, 1996;Toronov et al, 2001), MEG (Mackert et al, 2002), EEG (Kennan et al, 2002;Israel et al, 2002) and TMS (Oliviero et al, 1999;Iwata et al, 2000;Nissilä et al, 2002b). Figure 13.…”

Section: 31d Practical Applicationsmentioning

confidence: 99%

Diffuse Optical Imaging

Nissilä

Noponen

Heino

et al.

Advances in Electromagnetic Fields in Living Systems

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Diffuse optical imaging is a functional medical imaging modality which takes advantage of the relatively low attenuation of near-infrared light to probe the internal optical properties of tissue. The optical properties are affected by parameters related to physiology such as the concentrations of oxy-and deoxyhemoglobin. Instrumentation that is used for optical imaging is generally able to measure changes in the attenuation of light at several wavelengths, and in the case of time-and frequency-domain instrumentation, the time-of-flight of the photons in tissue.Light propagation in tissue is generally dominated by scattering. Models for photon transport in tissue are generally based on either stochastic approaches or approximations derived from the radiative transfer equation. If a numerical forward model which describes the physical situation with sufficient accuracy exists, inversion methods may be used to determine the internal optical properties based on boundary measurements.Optical imaging has applications in, e.g., functional brain imaging, breast cancer detection, and muscle imaging. It has the important advantages of transportable instrumentation, relatively high tolerance for external electromagnetic interference, non-invasiveness, and applicability for neonatal studies. The methods are not yet in clinical use, and further research is needed to improve the reliability of the experimental techniques, and the accuracy of the models used. In this chapter, we describe the interaction between light and tissue, light propagation models and inversion methods used in optical tomography, and instrumentation and experimental techniques used in optical imaging. The main applications of optical imaging are described in detail, with results from recent literature.

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Habituation of the Visually Evoked Potential and Its Vascular Response: Implications for Neurovascular Coupling in the Healthy Adult

Cited by 124 publications

References 71 publications

A Maximum-Likelihood Estimator for Trial-to-Trial Variations in Noisy MEG/EEG Data Sets

A Maximum-Likelihood Estimator for Trial-to-Trial Variations in Noisy MEG/EEG Data Sets

Compartment-Resolved Imaging of Activity-Dependent Dynamics of Cortical Blood Volume and Oximetry

Diffuse Optical Imaging

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