R Le Bouquin-Jeannes | Search PubMed

PubMed2003

K-means clustering method for auditory evoked potentials selection.

Surface auditory evoked potentials are generally recorded using a headset of 32, 64 or 128 electrodes, but the quality of the responses is quite heterogeneous on the scalp surface. In some contexts, such as the analysis of auditory evoked potentials recorded in radio-frequency fields, the signal quality is essential, and it appears pertinent to consider only a limited number of electrodes. Therefore, before analysing signals influenced by radio-frequency fields, it is necessary to consider the preliminary step of selecting the channels where auditory activity is strong. This step is often realised by human visual selection and can take a considerable time. In this paper, a simple k-means clustering method is proposed, to select automatically the important channels, and the results are compared with traditional methods of selection. The method detected channels that showed a concordance rate of 86.5% with the visual selection (performed by five individuals) and gave the same final selection (only two extra electrodes in the automatic case). Moreover, the time needed for this automatic selection was 100 times less than that for the visual selection, and also human variability was avoided.

Algorithms↗

PubMed1999

Seizures of temporal lobe epilepsy: identification of subtypes by coherence analysis using stereo-electro-encephalography.

OBJECTIVES: Two subtypes of temporal lobe epilepsy (TLE) according to the structures initially involved during seizures are currently recognized: medial TLE (MTLE) and lateral (or neocortical) TLE (LTLE). A few reports have suggested that the classification of TLE subtypes might be larger according to variations in the interactions between medial structures and the neocortex. In this study, we analyzed these interactions using coherence analysis of stereo-encephalographic (SEEG) signals during spontaneous seizures. METHODS: Twenty-seven patients with drug-resistant TLE, diagnosed from ictal SEEG recordings obtained during pre-surgical evaluation, were studied. Orthogonally implanted depth electrodes with multiple leads according to Talairach's method were used to sample medial and neocortical structures. Coherence analysis of ictal discharges was performed between two SEEG bipolar signals from adjacent leads located either in medial structures (amygdala and hippocampus) or in neocortical regions of the temporal lobe. A new algorithm, which was designed to reduce the bias inherent in coherence estimation, was used to compute the coherence. RESULTS: We were able to classify TLE seizures (TLES) into 4 distinct categories: (1) 'medial' TLES, characterized by medial onset with later involvement of the neocortex in the form of a 'phasic' discharge. High ictal coherence values were observed between medial structures; (2) 'medial-lateral' TLES which started in medial structures with a fast low-voltage discharge (FLVD) which rapidly affects the neocortex (< or = 3 s). High coherence values were observed between medial and lateral structures; (3) 'lateral-medial' TLES, which are different from medial-lateral TLES in that the FLVD starts in the lateral neocortex and involves the amygdala and/or hippocampus almost immediately after; (4) 'lateral' TLES: characterized by a neocortical onset, a delayed involvement of medial structures (when present), and high coherence values between neocortical structures. CONCLUSIONS: These results demonstrate the existence of numerous interactions between medial limbic structures and the neocortex during TLE seizures. Such findings could have implications for surgical strategies and the prognosis of epilepsy surgery, particularly when limited resection is indicated.

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