Sawtooth waves (STW) are bursts of frontocentral slow oscillations recorded in the scalp electroencephalogram (EEG) during rapid eye movement (REM) sleep. Little is known about their cortical generators and functional significance. Stereo-EEG performed for presurgical epilepsy evaluation offers the unique possibility to study neurophysiology in situ in the human brain. We investigated intracranial correlates of scalp-detected STW in 26 patients (14 women) undergoing combined stereo-EEG/polysomnography. We visually marked STW segments in scalp EEG and selected stereo-EEG channels exhibiting normal activity for intracranial analyses. Channels were grouped in 30 brain regions. The spectral power in each channel and frequency band was computed during STW and non-STW control segments. Ripples (80-250 Hz) were automatically detected during STW and control segments. The spectral power in the different frequency bands and the ripple rates were then compared between STW and control segments in each brain region. An increase in 2-4 Hz power during STW segments was found in all brain regions, except the occipital lobe, with large effect sizes in the parietotemporal junction, the lateral and orbital frontal cortex, the anterior insula, and mesiotemporal structures. A widespread increase in high-frequency activity, including ripples, was observed concomitantly, involving the sensorimotor cortex, associative areas, and limbic structures. This distribution showed a high spatiotemporal heterogeneity. Our results suggest that STW are associated with widely distributed, but locally regulated REM sleep slow oscillations. By driving fast activities, STW may orchestrate synchronized reactivations of multifocal activities, allowing tagging of complex representations necessary for REM sleep-dependent memory consolidation.SIGNIFICANCE STATEMENT Sawtooth waves (STW) present as scalp electroencephalographic (EEG) bursts of slow waves contrasting with the low-voltage fast desynchronized activity of REM sleep. Little is known about their cortical origin and function. Using combined stereo-EEG/polysomnography possible only in the human brain during presurgical epilepsy evaluation, we explored the intracranial correlates of STW. We found that a large set of regions in the parietal, frontal, and insular cortices shows increases in 2-4 Hz power during scalp EEG STW, that STW are associated with a strong and widespread increase in high frequencies, and that these slow and fast activities exhibit a high spatiotemporal heterogeneity. These electrophysiological properties suggest that STW may be involved in cognitive processes during REM sleep.

• MeSH
• dospělí MeSH
• elektrokortikografie * MeSH
• lidé středního věku MeSH
• lidé MeSH
• mapování mozku MeSH
• mladý dospělý MeSH
• mozková kůra fyziologie   MeSH
• polysomnografie MeSH
• spánek REM fyziologie   MeSH
• stadia spánku fyziologie   MeSH
• vlnková analýza MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

OBJECTIVE: Interictal epileptiform anomalies such as epileptiform discharges or high-frequency oscillations show marked variations across the sleep-wake cycle. This study investigates which state of vigilance is the best to localize the epileptogenic zone (EZ) in interictal intracranial electroencephalography (EEG). METHODS: Thirty patients with drug-resistant epilepsy undergoing stereo-EEG (SEEG)/sleep recording and subsequent open surgery were included; 13 patients (43.3%) had good surgical outcome (Engel class I). Sleep was scored following standard criteria. Multiple features based on the interictal EEG (interictal epileptiform discharges, high-frequency oscillations, univariate and bivariate features) were used to train a support vector machine (SVM) model to classify SEEG contacts placed in the EZ. The performance of the algorithm was evaluated by the mean area under the receiver-operating characteristic (ROC) curves (AUCs) and positive predictive values (PPVs) across 10-minute sections of wake, non-rapid eye movement sleep (NREM) stages N2 and N3, REM sleep, and their combination. RESULTS: Highest AUCs were achieved in NREM sleep stages N2 and N3 compared to wakefulness and REM (P < .01). There was no improvement when using a combination of all four states (P > .05); the best performing features in the combined state were selected from NREM sleep. There were differences between good (Engel I) and poor (Engel II-IV) outcomes in PPV (P < .05) and AUC (P < .01) across all states. The SVM multifeature approach outperformed spikes and high-frequency oscillations (P < .01) and resulted in results similar to those of the seizure-onset zone (SOZ; P > .05). SIGNIFICANCE: Sleep improves the localization of the EZ with best identification obtained in NREM sleep stages N2 and N3. Results based on the multifeature classification in 10 minutes of NREM sleep were not different from the results achieved by the SOZ based on 12.7 days of seizure monitoring. This finding might ultimately result in a more time-efficient intracranial presurgical investigation of focal epilepsy.

• MeSH
• akční potenciály fyziologie   MeSH
• bdění fyziologie   MeSH
• dospělí MeSH
• elektrokortikografie metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• refrakterní epilepsie diagnóza   patofyziologie   MeSH
• stadia spánku fyziologie   MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

In contrast to scalp EEG, our knowledge of the normal physiological intracranial EEG activity is scarce. This multicentre study provides an atlas of normal intracranial EEG of the human brain during wakefulness. Here we present the results of power spectra analysis during wakefulness. Intracranial electrodes are placed in or on the brain of epilepsy patients when candidates for surgical treatment and non-invasive approaches failed to sufficiently localize the epileptic focus. Electrode contacts are usually in cortical regions showing epileptic activity, but some are placed in normal regions, at distance from the epileptogenic zone or lesion. Intracranial EEG channels defined using strict criteria as very likely to be in healthy brain regions were selected from three tertiary epilepsy centres. All contacts were localized in a common stereotactic space allowing the accumulation and superposition of results from many subjects. Sixty-second artefact-free sections during wakefulness were selected. Power spectra were calculated for 38 brain regions, and compared to a set of channels with no spectral peaks in order to identify significant peaks in the different regions. A total of 1785 channels with normal brain activity from 106 patients were identified. There were on average 2.7 channels per cm3 of cortical grey matter. The number of contacts per brain region averaged 47 (range 6-178). We found significant differences in the spectral density distributions across the different brain lobes, with beta activity in the frontal lobe (20-24 Hz), a clear alpha peak in the occipital lobe (9.25-10.25 Hz), intermediate alpha (8.25-9.25 Hz) and beta (17-20 Hz) frequencies in the parietal lobe, and lower alpha (7.75-8.25 Hz) and delta (0.75-2.25 Hz) peaks in the temporal lobe. Some cortical regions showed a specific electrophysiological signature: peaks present in >60% of channels were found in the precentral gyrus (lateral: peak frequency range, 20-24 Hz; mesial: 24-30 Hz), opercular part of the inferior frontal gyrus (20-24 Hz), cuneus (7.75-8.75 Hz), and hippocampus (0.75-1.25 Hz). Eight per cent of all analysed channels had more than one spectral peak; these channels were mostly recording from sensory and motor regions. Alpha activity was not present throughout the occipital lobe, and some cortical regions showed peaks in delta activity during wakefulness. This is the first atlas of normal intracranial EEG activity; it includes dense coverage of all cortical regions in a common stereotactic space, enabling direct comparisons of EEG across subjects. This atlas provides a normative baseline against which clinical EEGs and experimental results can be compared. It is provided as an open web resource (https://mni-open-ieegatlas. RESEARCH: mcgill.ca).

• MeSH
• bdění MeSH
• dospělí MeSH
• elektrody MeSH
• elektrokortikografie metody   MeSH
• epilepsie diagnostické zobrazování   patologie   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mapování mozku * MeSH
• mladý dospělý MeSH
• mozková kůra diagnostické zobrazování   patofyziologie   MeSH
• neurozobrazování MeSH
• spektrální analýza MeSH
• Check Tag
• dospělí MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH
• práce podpořená grantem MeSH