Author J. Martinerie
Adam C., Le van Quyen M., Martinerie J., Clemenceau S., Baulac M., Renault B. & Varela F. J. (1999) Interactions entre réseau épileptique et fonctionnement cérébral: Approche par analyse non-lineaire de l’EEG intracrânien. Revue Neurologique 155: 489–494.
Adam C., Le van Quyen M., Martinerie J., Clemenceau S., Baulac M., Renault B. & Varela F. J.
(
1999)
Interactions entre réseau épileptique et fonctionnement cérébral: Approche par analyse non-lineaire de l’EEG intracrânien.
Revue Neurologique 155: 489–494.
Baulac M., Le van Quyen M., Martinerie J., Clemeceau S., Adam C. & Varela F. J. (1999) Pre-ictal changes of the EGG dynamics in epileptic patients: clinical and neurobiological implications. In: Grassberger P. & Lehnertz K. (eds.) Chaos in the Brain?. World Scientific, Singapore: 77–86.
Baulac M., Le van Quyen M., Martinerie J., Clemeceau S., Adam C. & Varela F. J.
(
1999)
Pre-ictal changes of the EGG dynamics in epileptic patients: clinical and neurobiological implications.
In: Grassberger P. & Lehnertz K. (eds.) Chaos in the Brain?. World Scientific, Singapore: 77–86.
Cosmelli D., David O., Lachaux J.-P., Martinerie J., Garnero L., Renault B. & Varela F. J. (2004) Waves of consciousness: Ongoing cortical patterns during binocular rivalry. Neuroimage 23: 128–140. https://cepa.info/7750
Cosmelli D., David O., Lachaux J.-P., Martinerie J., Garnero L., Renault B. & Varela F. J.
(
2004)
Waves of consciousness: Ongoing cortical patterns during binocular rivalry.
Neuroimage 23: 128–140.
Fulltext at https://cepa.info/7750
We present here ongoing patterns of distributed brain synchronous activity that correlate with the spontaneous flow of perceptual dominance during binocular rivalry. Specific modulation of the magnetoencephalographic (MEG) response evoked during conscious perception of a frequency-tagged stimulus was evidenced throughout rivalry. Estimation of the underlying cortical sources revealed, in addition to strong bilateral striate and extrastriate visual cortex activation, parietal, temporal pole and frontal contributions. Cortical activity was significantly modulated concomitantly to perceptual alternations in visual cortex, medial parietal and left frontal regions. Upon dominance, coactivation of occipital and frontal regions, including anterior cingulate and medial frontal areas, was established. This distributed cortical network, as measured by phase synchrony in the frequency tag band, was dynamically modulated in concert with the perceptual dominance of the tagged stimulus. While the anteroposterior pattern was recurrent through subjects, individual variations in the extension of the network were apparent.
Lachaux J. P., Lutz A., Rudrauf D., Cosmelli D., Le Van Quyen M., Martinerie J. & Varela F. J. (2002) Estimating the time-course of coherence between single-trial brain signals: an introduction to wavelet coherence. Neurophysiologie Clinique 32(3): 157–174.
Lachaux J. P., Lutz A., Rudrauf D., Cosmelli D., Le Van Quyen M., Martinerie J. & Varela F. J.
(
2002)
Estimating the time-course of coherence between single-trial brain signals: an introduction to wavelet coherence.
Neurophysiologie Clinique 32(3): 157–174.
This paper introduces the use of wavelet analysis to follow the temporal variations in the coupling between oscillatory neural signals. Coherence, based on Fourier analysis, has been commonly used as a first approximation to track such coupling under the assumption that neural signals are stationary. Yet, stationary neural processing may be the exception rather than the rule. In this context, the recent application to physical systems of a wavelet-based coherence, which does not depend on the stationarity of the signals, is highly relevant. This paper fully develops the method of wavelet coherence and its statistical properties so that it can be practically applied to continuous neural signals. In realistic simulations, we show that, in contrast to Fourier coherence, wavelet coherence can detect short, significant episodes of coherence between non-stationary neural signals. This method can be directly applied for an ‘online’ quantification of the instantaneous coherence between two signals.
Lachaux J.-P., Pezard L., Pelt C., Garneiro L., Renault B., Varela F. J. & Martinerie J. (1997) Spatial extension of brain activity fools the single-channel reconstruction of EEG dynamics. Human Brain Mapping 5(1): 26–47. https://cepa.info/2006
Lachaux J.-P., Pezard L., Pelt C., Garneiro L., Renault B., Varela F. J. & Martinerie J.
(
1997)
Spatial extension of brain activity fools the single-channel reconstruction of EEG dynamics.
Human Brain Mapping 5(1): 26–47.
Fulltext at https://cepa.info/2006
We report here on a first attempt to settle the methodological controversy between advocates of two alternative reconstruction approaches for temporal dynamics in brain signals: the single‐channel method (using data from one recording site and reconstructing by time‐lags), and the multiple‐channel method (using data from a spatially distributed set of recordings sites and reconstructing by means of spatial position). For the purpose of a proper comparison of these two techniques, we computed a series of EEG‐like measures on the basis of well‐known dynamical systems placed inside a spherical model of the head. For each of the simulations, the correlation dimension estimates obtained by both methods were calculated and compared, when possible, with the known (or estimated) dimension of the underlying dynamical system. We show that the single‐channel method fails to reliably quantify spatially extended dynamics, while the multichannel method performs better. It follows that the latter is preferable, given the known spatially distributed nature of brain processes. Hum. Brain Mapping 5:26–47, 1997. © 1997 Wiley‐Liss, Inc.
Lachaux J.-P., Rodriguez E., Le Van Quyen M., Lutz A., Martinerie J. & Varela F. J. (2000) Studying single-trials of phase-synchronous activity in the brain. International Journal of Bifurcation and Chaos 10(10): 2429–2439. https://cepa.info/2083
Lachaux J.-P., Rodriguez E., Le Van Quyen M., Lutz A., Martinerie J. & Varela F. J.
(
2000)
Studying single-trials of phase-synchronous activity in the brain.
International Journal of Bifurcation and Chaos 10(10): 2429–2439.
Fulltext at https://cepa.info/2083
This paper introduces a new method, single-trial phase locking statistics (S-PLS) to estimate phase locking in single trials of brain signals between two electrodes. The possibility of studying single trials removes an important limitation in the study of long-range synchrony in brain signals. S-PLS is closely related to our previous method, phase locking statistics (PLS) that estimates phase locking over a set of trials. The S-PLS method is described in detail and applied to human surface recordings during the task of face-recognition. We compare these results with those provided by PLS and show that they are qualitatively very similar, although S-PLS provides better discrimination of synchronic episodes.
Lachaux J.-P., Rodriguez E., Martinerie J. & Varela F. J. (1999) Measuring phase synchrony in brain signals. Human Brain Mapping 8(4): 194–208.
Lachaux J.-P., Rodriguez E., Martinerie J. & Varela F. J.
(
1999)
Measuring phase synchrony in brain signals.
Human Brain Mapping 8(4): 194–208.
This article presents, for the first time, a practical method for the direct quantification of frequency-specific synchronization (i.e., transient phase-locking) between two neuroelectric signals. The motivation for its development is to be able to examine the role of neural synchronies as a putative mechanism for long-range neural integration during cognitive tasks. The method, called phase-locking statistics (PLS), measures the significance of the phase covariance between two signals with a reasonable time-resolution (<100 ms). Unlike the more traditional method of spectral coherence, PLS separates the phase and amplitude components and can be directly interpreted in the framework of neural integration. To validate synchrony values against background fluctuations, PLS uses surrogate data and thus makes no a priori assumptions on the nature of the experimental data. We also apply PLS to investigate intracortical recordings from an epileptic patient performing a visual discrimination task. We find large-scale synchronies in the gamma band (45 Hz), e.g., between hippocampus and frontal gyrus, and local synchronies, within a limbic region, a few cm apart. We argue that whereas long-scale effects do reflect cognitive processing, short-scale synchronies are likely to be due to volume conduction. We discuss ways to separate such conduction effects from true signal synchrony.
Lachaux J.-P., Rodriguez E., Martinerie J., Adam C., Hasboun D. & Varela F. J. (2000) A quantitative study of gamma-band activity in human intracranial recordings triggered by visual stimuli. European Journal of Neuroscience 12: 2608–2622. https://cepa.info/2040
Lachaux J.-P., Rodriguez E., Martinerie J., Adam C., Hasboun D. & Varela F. J.
(
2000)
A quantitative study of gamma-band activity in human intracranial recordings triggered by visual stimuli.
European Journal of Neuroscience 12: 2608–2622.
Fulltext at https://cepa.info/2040
This paper studies gamma-band responses from two implanted epileptic patients during a simple visual discrimination task. Our main aim was to ascertain, in a reliable manner, whether evoked (stimulus-locked) and induced (triggered by, but not locked to, stimuli) responses are present in intracranial recordings. For this purpose, we introduce new methods adapted to detect the presence of gamma responses at this level of recording, intermediary between EEG-scalp and unicellular responses. The analysis relies on a trial-by-trial time–frequency analysis and on the use of surrogate data for statistical testing. We report that visual stimulation reliably elicits evoked and induced responses in human intracranial recordings. Induced intracranial gamma activity is significantly present in short oscillatory bursts (a few cycles) following visual stimulation. These responses are highly variable from trial to trial, beginning after 200 ms and lasting up to 500 ms. In contrast, intracranial-evoked gamma responses concentrate around 100 ms latencies corresponding to evoked responses observed on the scalp. We discuss our results in relation to scalp gamma response in a similar protocol [Tallon-Baudry et al. (1996) J. Neurosci., 16, 4240–4249] and draw some conclusions for bridging the gap between gamma oscillations observed on the scalp surface and their possible cortical sources.
Le Van Quyen M., Adam C., Baulac M., Martinerie J. & Varela F. J. (1998) Nonlinear interdependencies of EEG signals in human intracranially recorded temporal lobe seizures. Brain Research 792: 24–40.
Le Van Quyen M., Adam C., Baulac M., Martinerie J. & Varela F. J.
(
1998)
Nonlinear interdependencies of EEG signals in human intracranially recorded temporal lobe seizures.
Brain Research 792: 24–40.
Le van Quyen M., Adam C., Martinerie J., Baulac M., Clemenceau S. & Varela F. J. (2000) Spatio-temporal characterizations of non-linear changes in intracranial activities prior to human temporal lobe seizures. European Journal of Neuroscience 12(6): 2124–2134.
Le van Quyen M., Adam C., Martinerie J., Baulac M., Clemenceau S. & Varela F. J.
(
2000)
Spatio-temporal characterizations of non-linear changes in intracranial activities prior to human temporal lobe seizures.
European Journal of Neuroscience 12(6): 2124–2134.
Recent studies have shown that non-linear analysis of intracranial activities can detect a ‘pre-ictal phase’ preceding the epileptic seizure. Nevertheless, the dynamical nature of the underlying neuronal process and the spatial extension of this pre-ictal phase still remain unknown. In this paper, we address these aspects using a new non-linear measure of dynamic similarity between different parts of intracranial recordings of nine patients with medial temporal lobe epilepsy recorded during transitions to seizure. Our results confirm that non-linear changes in neuronal dynamics allow, in most cases (16 out of 17), a seizure anticipation several minutes in advance. Furthermore, we show that the spatial distribution of pre-ictal changes often involves an extended network projecting beyond the limits of the epileptogenic region. Finally, the pre-ictal phase could frequently (13 out of 17) be characterized with a marked shift toward slower frequencies in upper delta or theta frequency range.
Export result page as:
·
·
·
·
·
·
·
·