Generation of High Frequency Oscillations (80–500Hz) in different anatomical structures and their relation to the seizure onset zone
Notice bibliographique
Résumé
Introduction: High frequency oscillations (HFOs) known as ripples (80–250Hz) and fast ripples (250–500Hz) can be recorded from macroelectrodes inserted in patients with intractable focal epilepsy. Although ripples may occur physiologically in the hippocampus, both events are also most likely linked to epileptogenesis and have been found in the seizure onset zone (SOZ) of human ictal and interictal recordings. HFOs have been mainly described in the mesial temporal structures (MTS), but they were also found in neocortical areas (NC). We investigated the variability of HFOs in different anatomical structures and whether HFOs can help identify epileptogenic areas in spite of this variability. Methods: Intracerebral EEGs of 12 patients with intractable focal epilepsy were studied using macro-electrodes with 9 contacts of 0.8mm 2 surface. The EEG was filtered at 500Hz and sampled at 2000Hz. In each patient, up to 23 channels were selected according to their anatomical localisation and relationship to the SOZ. HFOs were visually marked. Rates and durations of ripples and fast ripples were calculated for each channel. Channels were then grouped according to their anatomical localisation (amygdala, anterior hippocampus, parahippocampus, neocortex) and relationship to the SOZ, and compared using one-way ANOVA. Results: 163 Channels were analyzed (amygdala (A): 15, hippocampus (HC): 27, parahippocampus (PHC): 10, NC areas: 111/SOZ: 95, outside SOZ: 68). Ripples and fast ripples were significantly more frequent in the HC, followed by the A and the PHC. HFOs were significantly less frequent in NC areas. The duration of ripples was significantly longer in the A while fast ripples were longest in the HC; both events were significantly shorter in NC areas (Fig 1). In each anatomical structure, rates of HFOs were significantly higher in the SOZ than outside, but in PHC only fast ripples and in A only ripples showed significant differences (Fig.2). Conclusion: HFOs in general are more frequent and longer in duration in the MTS than in NC areas. While previously described high rates of ripples in the HC may include physiological ripples, HFOs were also frequent in the A and PHC. In NC areas, the events were significantly less frequent and shorter. This might indicate that these areas are less prone to generate HFOs or better in termi-nating and inhibiting them. Despite the variability in HFOs between anatomical regions, rates of HFOs, either ripples or fast ripples, were higher in the SOZ than outside in each structure. However, rates of HFOs in non-SOZ areas in the MTS were still higher than in SOZ areas in the NC. This has to be taken into account when examining rates of HFOs to identify seizure onset channels and for this pur-pose it might be necessary to distinguish between patients with mesial temporal and neocortical seizure onset. Fig. 1 Fig. 2 Ripple Rates Significance Fast Ripple Rates Significance SOZ Non-SOZ SOZ Non-SOZ Mesial Temporal Structures 29.2 14.2 <0.001 21.8 3.0 <0.001 Neocortex 9.7 4.9 <0.001 5.1 2.1 0.05 Amygdala 24.2 14.2 0.003 12.5 7.6 n.s. Hippocampus 34.5 15.6 <0.001 27.1 1.2 <0.001 Parahippocampus 18 14.2 n.s. 22.7 1.9 <0.001
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».