Fusion of simultaneous fMRI/EEG data based on the electro-metabolic coupling

Lahaye, Pierre-Jean; Baillet, Sylvain; Poline, Jean‐Baptiste; Garnero, Line

doi:10.1109/isbi.2004.1398675

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…A promising advance is to use the information from continuous EEG as a marker for fMRI analysis. This can be done for single‐event variations in EEG amplitude (118) or continuous fluctuations in the power of some EEG bands (99, 119, 120).…”

Section: Combining Eeg and Fmri Resultsmentioning

confidence: 99%

Combining EEG and fMRI: A multimodal tool for epilepsy research

Gotman

Kobayashi

Bagshaw

et al. 2006

Magnetic Resonance Imaging

252

174

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Patients with epilepsy often present in their electroencephalogram (EEG) short electrical potentials (spikes or spikewave bursts) that are not accompanied by clinical manifestations but are of important diagnostic significance. They result from a population of abnormally hyperactive and hypersynchronous neurons. It is not easy to determine the location of the cerebral generators and the other brain regions that may be involved as a result of this abnormal activity. The possibility to combine EEG recording with functional MRI (fMRI) scanning opens the opportunity to uncover the regions of the brain showing changes in the fMRI signal in response to epileptic spikes seen in the EEG. These regions are presumably involved in the abnormal neuronal activity at the origin of epileptic discharges. This paper reviews the methodology involved in performing such studies, particularly the challenge of recording a good quality EEG inside the MR scanner while scanning is taking place, and the methods required for the statistical analysis of the combined EEG and fMRI time series. We review the results obtained in patients with different types of epileptic disorders and discuss the difficult theoretical problems raised by the interpretation of an increase (activation) and decrease (deactivation) in blood oxygen level dependent (BOLD) signal, both frequently seen in response to spikes.

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Section: Combining Eeg and Fmri Resultsmentioning

confidence: 99%

Combining EEG and fMRI: A multimodal tool for epilepsy research

Gotman

Kobayashi

Bagshaw

et al. 2006

Magnetic Resonance Imaging

252

174

View full text Add to dashboard Cite

show abstract

“…The existence of regions wherein the fMRI signal correlates with features of an EEG wave would then suggest their involvement in the generation or in the modulation of the wave. Such findings would also improve our understanding of the links between electrophysiological and fMRI signals, a topic that is currently raising much interest for the interpretation of fMRI results [Logothetis and Pfeuffer, 2004] or for the fusion of modalities [Dale et al, 2000;Lahaye et al, 2004;Trujillo-Barreto et al, 2001].…”

Section: Introductionmentioning

confidence: 99%

Single‐trial analysis of oddball event‐related potentials in simultaneous EEG‐fMRI

Bénar¹,

Schön²,

Grimault³

et al. 2007

Human Brain Mapping

171

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There has recently been a growing interest in the use of simultaneous electroencephalography (EEG) and functional MRI (fMRI) for evoked activity in cognitive paradigms, thereby obtaining functional datasets with both high spatial and temporal resolution. The simultaneous recording permits obtaining event-related potentials (ERPs) and MR images in the same environment, conditions of stimulation, and subject state; it also enables tracing the joint fluctuations of EEG and fMRI signals. The goal of this study was to investigate the possibility of tracking the trial-to-trial changes in event-related EEG activity, and of using this information as a parameter in fMRI analysis. We used an auditory oddball paradigm and obtained single-trial amplitude and latency features from the EEG acquired during fMRI scanning. The single-trial P300 latency presented significant correlation with parameters external to the EEG (target-to-target interval and reaction time). Moreover, we obtained significant fMRI activations for the modulation by P300 amplitude and latency, both at the single-subject and at the group level. Our results indicate that, in line with other studies, the EEG can bring a new dimension to the field of fMRI analysis by providing fine temporal information on the fluctuations in brain activity.

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“…Examples include models based on mean field theory (David and Friston 2003; Kiebel et al 2006; Coombes et al 2007; Liley et al 2002) and physiologically inspired models, based on a single or few functionally representative neurons, each representing a neural subpopulation (Riera et al 2006, 2007). Parsimonious models that still include a sufficient level of representation of physiology to be open to physiological interpretation, and to manipulation by such factors as biochemical or sensory stimuli, have the potential to be key components of joint representations of electrical and hemodynamic activities, relating EEG and fMRI or optical measurements in a unified set of source models (Daunizeau et al 2007; Horwitz and Poeppel 2002; Lahaye et al 2004). …”

Section: Introductionmentioning

confidence: 99%

Modeling habituation in rat EEG-evoked responses via a neural mass model with feedback

et al. 2011

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Habituation is a generic property of the neural response to repeated stimuli. Its strength often increases as inter-stimuli relaxation periods decrease. We propose a simple, broadly applicable control structure that enables a neural mass model of the evoked EEG response to exhibit habituated behavior. A key motivation for this investigation is the ongoing effort to develop model-based reconstruction of multimodal functional neuroimaging data. The control structure proposed here is illustrated and validated in the context of a biophysical neural mass model, developed by Riera et al. (Hum Brain Mapp 27(11):896–914, 2006; 28(4):335–354, 2007), and of simplifications thereof, using data from rat EEG response to medial nerve stimuli presented at frequencies from 1 to 8 Hz. Performance was tested by predictions of both the response to the next stimulus based on the current one, and also of continued stimuli trains over 4-s time intervals based on the first stimulus in the interval, with similar success statistics. These tests demonstrate the ability of simple generative models to capture key features of the evoked response, including habituation.

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Fusion of simultaneous fMRI/EEG data based on the electro-metabolic coupling

Cited by 5 publications

References 8 publications

Combining EEG and fMRI: A multimodal tool for epilepsy research

Combining EEG and fMRI: A multimodal tool for epilepsy research

Single‐trial analysis of oddball event‐related potentials in simultaneous EEG‐fMRI

Modeling habituation in rat EEG-evoked responses via a neural mass model with feedback

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