Metabolic alkalosis: a new red flag in status epilepticus.

BACKGROUND: Status epilepticus (SE) is a heterogeneous neurological emergency with significant variability in prognosis, influenced by underlying disease and pathophysiological context. Acid-base disturbances are common in critically ill patients, yet their distribution and impact in SE patients remain poorly understood. METHODS: This was an observational cohort study including non-hypoxic SE patients with available blood gas analysis within the first 24 h of SE, treated at the University Hospital of Geneva, Switzerland between 2015 and 2023. Acid-base disturbances were classified using the Henderson-Hasselbalch equation, with prevalent metabolic alkalosis confirmed through the Stewart approach. Primary outcomes were in-hospital mortality, Glasgow Outcome Scale (GOS) at discharge, and return to premorbid neurologic function. FINDINGS: Among 540 SE patients, 365 were included. Half of patients exhibited acid-base disturbances within the initial 24 h of SE, with metabolic and respiratory acidosis being the most prevalent, though not prognostically significant. After correction for possible confounders, metabolic alkalosis (6%) was associated with increased in-hospital mortality (P = 0.011; OR = 4.87, 95% CI = 1.29-7.84), worse GOS (P = 0.012; OR = 3.18, 95% CI = 1.29-7.84), and reduced likelihood of returning to premorbid function (P = 0.017; OR = 3.30, CI95% = 1.24-8.80). Following the Stewart approach, 9% of patients had predominant metabolic alkalosis, associated with worse GOS (P = 0.005; OR:3.37, 95%CI = 1.45-7.82), and reduced chance of returning to baseline (P = 0.012; OR = 3.29, CI95% = 1.30-8.32). Metabolic alkalosis was related to hypoalbuminemia and lower serum potassium. CONCLUSION: Metabolic alkalosis strongly predicts mortality and adverse functional outcome in SE patients. Prospective studies should assess whether early detection and correction of metabolic alkalosis and related electrolyte imbalances can improve SE prognosis.

Altered correlation of concurrently recorded EEG-fMRI connectomes in temporal lobe epilepsy.

Whole-brain functional connectivity networks (connectomes) have been characterized at different scales in humans using EEG and fMRI. Multimodal epileptic networks have also been investigated, but the relationship between EEG and fMRI defined networks on a whole-brain scale is unclear. A unified multimodal connectome description, mapping healthy and pathological networks would close this knowledge gap. Here, we characterize the spatial correlation between the EEG and fMRI connectomes in right and left temporal lobe epilepsy (rTLE/lTLE). From two centers, we acquired resting-state concurrent EEG-fMRI of 35 healthy controls and 34 TLE patients. EEG-fMRI data was projected into the Desikan brain atlas, and functional connectomes from both modalities were correlated. EEG and fMRI connectomes were moderately correlated. This correlation was increased in rTLE when compared to controls for EEG-delta/theta/alpha/beta. Conversely, multimodal correlation in lTLE was decreased in respect to controls for EEG-beta. While the alteration was global in rTLE, in lTLE it was locally linked to the default mode network. The increased multimodal correlation in rTLE and decreased correlation in lTLE suggests a modality-specific lateralized differential reorganization in TLE, which needs to be considered when comparing results from different modalities. Each modality provides distinct information, highlighting the benefit of multimodal assessment in epilepsy.

The relationship between resting-state hemodynamic (fMRI) and electrophysiological (EEG) connectivity has been investigated in healthy subjects, but this relationship is unknown in patients with left and right temporal lobe epilepsies (l/rTLE). Does the magnitude of the relationship differ between healthy subjects and patients? What role does the laterality of the epileptic focus play? What are the spatial contributions to this relationship? Here we use concurrent EEG-fMRI recordings of 65 subjects from two centers (35 controls, 34 TLE patients), to assess the correlation between EEG and fMRI connectivity. For all datasets, frequency-specific changes in cross-modal correlation were seen in lTLE and rTLE. EEG and fMRI connectivities do not measure perfectly overlapping brain networks and provide distinct information on brain networks altered in TLE, highlighting the benefit of multimodal assessment to inform about normal and pathological brain function.

Alterations in gamma frequency oscillations correlate with cortical tau deposition in Alzheimer's disease.

We assessed the relationship of gamma oscillations with tau deposition in Alzheimer's disease (AD) and other cognitive diseases, as both are altered during the disease course and relate to neurodegeneration. We retrospectively analyzed data from 7 AD, tau positive patients and 9 tau negative patients, who underwent cerebral amyloid PET and tau PET, and EEG within 12 months. Relative gamma power was higher in tau positive (AD) patients than in tau negative patients (p < .05). In tau positive AD patients, tau burden was associated with a linear increase in gamma power (p < .05), while no association was present in the tau negative group nor with amyloid-ß burden in either group. Thus, increase in the gamma power might represent a novel biomarker for tau driven neurodegeneration.

High-density electroencephalographic functional networks in genetic generalized epilepsy: Preserved whole-brain topology hides local reorganization.

OBJECTIVE: Genetic generalized epilepsy (GGE) accounts for approximately 20% of adult epilepsy cases and is considered a disorder of large brain networks, involving both hemispheres. Most studies have not shown any difference in functional whole-brain network topology when compared to healthy controls. Our objective was to examine whether this preserved global network topology could hide local reorganizations that balance out at the global network level. METHODS: We recorded high-density electroencephalograms from 20 patients and 20 controls, and reconstructed the activity of 118 regions. We computed functional connectivity in windows free of interictal epileptiform discharges in broad, delta, theta, alpha, and beta frequency bands, characterized the network topology, and used the Hub Disruption Index (HDI) to quantify the topological reorganization. We examined the generalizability of our results by reproducing a 25-electrode clinical system. RESULTS: Our study did not reveal any significant change in whole-brain network topology among GGE patients. However, the HDI was significantly different between patients and controls in all frequency bands except alpha (p < .01, false discovery rate [FDR] corrected, d < -1), and accompanied by an increase in connectivity in the prefrontal regions and default mode network. This reorganization suggests that regions that are important in transferring the information in controls were less so in patients. Inversely, the crucial regions in patients are less so in controls. These findings were also found in delta and theta frequency bands when using 25 electrodes (p < .001, FDR corrected, d < -1). SIGNIFICANCE: In GGE patients, the overall network topology is similar to that of healthy controls but presents a balanced local topological reorganization. This reorganization causes the prefrontal areas and default mode network to be more integrated and segregated, which may explain executive impairment associated with GGE. Additionally, the reorganization distinguishes patients from controls even when using 25 electrodes, suggesting its potential use as a diagnostic tool.

Yield of non-invasive imaging in MRI-negative focal epilepsy.

OBJECTIVE: The absence of MRI-lesion reduces considerably the probability of having an excellent outcome (International League Against Epilepsies [ILAE] class I-II) after epilepsy surgery. Surgical success in magnetic-resonance imaging (MRI)-negative cases relies therefore mainly on non-invasive techniques such as positron-emission tomography (PET), subtraction ictal/inter-ictal single-photon-emission-computed-tomography co-registered to MRI (SISCOM), electric source imaging (ESI) and morphometric MRI analysis (MAP). We were interested in identifying the optimal imaging technique or combination to achieve post-operative class I-II in patients with MRI-negative focal epilepsy. METHODS: We identified 168 epileptic patients without MRI lesion. Thirty-three (19.6%) were diagnosed with unifocal epilepsy, underwent surgical resection and follow-up ⩾ 2 years. Sensitivity, specificity, predictive values, and diagnostic odds ratio (OR) were calculated for each technique individually and in combination (after co-registration). RESULTS: 23/33 (70%) were free of disabling seizures (75.0% with temporal and 61.5% extratemporal lobe epilepsy). None of the individual modalities presented an OR > 1.5, except ESI if only patients with interictal epileptiform discharges (IEDs) were considered (OR 3.2). On a dual combination, SISCOM with ESI presented the highest outcome (OR = 6). MAP contributed to detecting indistinguishable focal cortical dysplasia in particular in extratemporal epilepsies with a sensitivity of 75%. Concordance of PET, ESI on interictal epileptic discharges, and SISCOM was associated with the highest chance for post-operative seizure control (OR = 11). CONCLUSION: If MRI is negative, the chances to benefit from epilepsy surgery are almost as high as in lesional epilepsy, provided that multiple established non-invasive imaging tools are rigorously applied and co-registered together.

Antiseizure medication ≤48 hours portends better prognosis in new-onset epilepsy.

BACKGROUND: Several studies found that patients with new-onset epilepsy (NOE) have higher seizure recurrence rates if they presented already prior seizures. These observations suggest that timing of antiseizure medication (ASM) is crucial and should be offered immediately after the first seizure. Here, we wanted to assess whether immediate ASM is associated with improved outcome. METHODS: Single-center study of 1010 patients (≥16 years) who presented with a possible first seizure in the emergency department between 1 March 2010 and 1 March 2017. A comprehensive workup was launched upon arrival, including routine electroencephalography (EEG), brain computed tomography/magnetic resonance imaging, long-term overnight EEG and specialized consultations. We followed patients for 5 years comparing the relapse rate in patients treated within 48 h to those with treatment >48 h. RESULTS: A total of 487 patients were diagnosed with NOE. Of the 416 patients (162 female, age: 54.6 ± 21.1 years) for whom the treatment start could be retrieved, 80% (333/416) were treated within 48 h. The recurrence rate after immediate treatment (32%; 107/333) was significantly lower than in patients treated later (56.6%; 47/83; p < 0.001). For patients for whom a complete 5-year-follow-up was available (N = 297, 123 female), those treated ≤48 h (N = 228; 76.8%) had a significantly higher chance of remaining seizure-free compared with patients treated later (N = 69; 23.2%; p < 0.001). CONCLUSIONS: In this retrospective study, immediate ASM therapy (i.e., within 48 h) was associated with better prognosis up to 5 years after the index event. Prospective studies are required to determine the value of immediate workup and drug therapy in NOE patients.

Long-term outcome of alcohol withdrawal seizures.

BACKGROUND AND PURPOSE: Alcohol withdrawal seizures (AWS) are a well-known complication of chronic alcohol abuse, but there is currently little knowledge of their long-term relapse rate and prognosis. The aims of this study were to identify risk factors for AWS recurrence and to study the overall outcome of patients after AWS. METHODS: In this retrospective single-center study, we included patients who were admitted to the Emergency Department after an AWS between January 1, 2013 and August 10, 2021 and for whom an electroencephalogram (EEG) was requested. AWS relapses up until April 29, 2022 were researched. We compared history, treatment with benzodiazepines or antiseizure medications (ASMs), laboratory, EEG and computed tomography findings between patients with AWS relapse (r-AWS) and patients with no AWS relapse (nr-AWS). RESULTS: A total of 199 patients were enrolled (mean age 53 ± 12 years; 78.9% men). AWS relapses occurred in 11% of patients, after a median time of 470.5 days. Brain computed tomography (n = 182) showed pathological findings in 35.7%. Risk factors for relapses were history of previous AWS (p = 0.013), skull fractures (p = 0.004) at the index AWS, and possibly epileptiform EEG abnormalities (p = 0.07). Benzodiazepines or other ASMs, taken before or after the index event, did not differ between the r-AWS and the nr-AWS group. The mortality rate was 2.9%/year of follow-up, which was 13 times higher compared to the general population. Risk factors for death were history of AWS (p < 0.001) and encephalopathic EEG (p = 0.043). CONCLUSIONS: Delayed AWS relapses occur in 11% of patients and are associated with risk factors (previous AWS >24 h apart, skull fractures, and pathological EEG findings) that also increase the epilepsy risk, that is, predisposition for seizures, if not treated. Future prospective studies are mandatory to determine appropriate long-term diagnostic and therapeutic strategies, in order to reduce the risk of relapse and mortality associated with AWS.

Implantation and reimplantation of intracranial EEG electrodes in patients considering epilepsy surgery.

In patients with drug-resistant epilepsy who are considering surgery, intracranial EEG (iEEG) helps delineate the putative epileptogenic zone. In a minority of patients, iEEG fails to identify seizure onsets. In such cases, it might be worthwhile to reimplant more iEEG electrodes. The consequences of such a strategy for the patient are unknown. We matched 12 patients in whom the initially implanted iEEG electrodes did not delineate the seizure onset zone precisely enough to offer resective surgery, and in whom additional iEEG electrodes were implanted during the same inpatient stay, to controls who did not undergo reimplantation. Seven cases and eight controls proceeded to resective surgery. No intracranial infection occurred. One control suffered an intracranial hemorrhage. Three cases and two controls suffered from a post-operative neurological or neuropsychological deficit. We found no difference in post-operative seizure control between cases and controls. Compared to an ILAE score of 5 (ie, stable seizure frequency in the absence of resective surgery), cases showed significant improvement. Reimplantation of iEEG electrodes can offer the possibility of resective epilepsy surgery to patients in whom the initial iEEG investigation was inconclusive, without compromising on the risk of complications or seizure control.

Added value of advanced workup after the first seizure: A 7-year cohort study.

OBJECTIVE: This study was undertaken to establish whether advanced workup including long-term electroencephalography (LT-EEG) and brain magnetic resonance imaging (MRI) provides an additional yield for the diagnosis of new onset epilepsy (NOE) in patients presenting with a first seizure event (FSE). METHODS: In this population-based study, all adult (≥16 years) patients presenting with FSE in the emergency department (ED) between March 1, 2010 and March 1, 2017 were assessed. Patients with obvious nonepileptic or acute symptomatic seizures were excluded. Routine EEG, LT-EEG, brain computed tomography (CT), and brain MRI were performed as part of the initial workup. These examinations' sensitivity and specificity were calculated on the basis of the final diagnosis after 2 years, along with the added value of advanced workup (MRI and LT-EEG) over routine workup (routine EEG and CT). RESULTS: Of the 1010 patients presenting with FSE in the ED, a definite diagnosis of NOE was obtained for 501 patients (49.6%). Sensitivity of LT-EEG was higher than that of routine EEG (54.39% vs. 25.5%, p < .001). Similarly, sensitivity of MRI was higher than that of CT (67.98% vs. 54.72%, p = .009). Brain MRI showed epileptogenic lesions in an additional 32% compared to brain CT. If only MRI and LT-EEG were considered, five would have been incorrectly diagnosed as nonepileptic (5/100, 5%) compared to patients with routine EEG and MRI (25/100, 25%, p = .0001). In patients with all four examinations, advanced workup provided an overall additional yield of 50% compared to routine workup. SIGNIFICANCE: Our results demonstrate the remarkable added value of the advanced workup launched already in the ED for the diagnosis of NOE versus nonepileptic causes of seizure mimickers. Our findings suggest the benefit of first-seizure tracks or even units with overnight EEG, similar to stroke units, activated upon admission in the ED.

Sex-related differences in adult patients with status epilepticus: a seven-year two-center observation.

BACKGROUND: Conflicting findings exist regarding the influence of sex on the development, treatment, course, and outcome of status epilepticus (SE). Our study aimed to investigate sex-related disparities in adult SE patients, focusing on treatment, disease course, and outcome at two Swiss academic medical centers. METHODS: In this retrospective study, patients treated for SE at two Swiss academic care centers from Basel and Geneva from 2015 to 2021 were included. Primary outcomes were return to premorbid neurologic function, death during hospital stay and at 30 days. Secondary outcomes included characteristics of treatment and disease course. Associations with primary and secondary outcomes were assessed using multivariable logistic regression. Analysis using propensity score matching was performed to account for the imbalances regarding age between men and women. RESULTS: Among 762 SE patients, 45.9% were women. No sex-related differences were found between men and women, except for older age and lower frequency of intracranial hemorrhages in women. Compared to men, women had a higher median age (70 vs. 66, p = 0.003), had focal nonconvulsive SE without coma more (34.9% vs. 25.5%; p = 0.005) and SE with motor symptoms less often (52.3% vs. 63.6%, p = 0.002). With longer SE duration (1 day vs. 0.5 days, p = 0.011) and a similar proportion of refractory SE compared to men (36.9% vs. 36.4%, p = 0.898), women were anesthetized and mechanically ventilated less often (30.6% vs. 42%, p = 0.001). Age was associated with all primary outcomes in the unmatched multivariable analyses, but not female sex. In contrast, propensity score-matched multivariable analyses revealed decreased odds for return to premorbid neurologic function for women independent of potential confounders. At hospital discharge, women were sent home less (29.7% vs. 43.7%, p < 0.001) and to nursing homes more often (17.1% vs. 10.0%, p = 0.004). CONCLUSIONS: This study identified sex-related disparities in the clinical features, treatment modalities, and outcome of adult patients with SE with women being at a disadvantage, implying that sex-based factors must be considered when formulating strategies for managing SE and forecasting outcomes.

Clinical Evaluation of a Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis.

OBJECTIVE: To evaluate the influence of quantitative reports (QReports) on the radiological assessment of hippocampal sclerosis (HS) from MRI of patients with epilepsy in a setting mimicking clinical reality. METHODS: The study included 40 patients with epilepsy, among them 20 with structural abnormalities in the mesial temporal lobe (13 with HS). Six raters blinded to the diagnosis assessed the 3T MRI in two rounds, first using MRI only and later with both MRI and the QReport. Results were evaluated using inter-rater agreement (Fleiss' kappa [Formula: see text]) and comparison with a consensus of two radiological experts derived from clinical and imaging data, including 7T MRI. RESULTS: For the primary outcome, diagnosis of HS, the mean accuracy of the raters improved from 77.5% with MRI only to 86.3% with the additional QReport (effect size [Formula: see text]). Inter-rater agreement increased from [Formula: see text] to [Formula: see text]. Five of the six raters reached higher accuracies, and all reported higher confidence when using the QReports. CONCLUSION: In this pre-use clinical evaluation study, we demonstrated clinical feasibility and usefulness as well as the potential impact of a previously suggested imaging biomarker for radiological assessment of HS.

Asymmetry of sleep electrophysiological markers in patients with focal epilepsy.

Sleep can modulate epileptic activities, but our knowledge of sleep perturbation by epilepsy remains sparse. Interestingly, epilepsy and sleep both present with defining electrophysiological features in the form of specific graphoelements on EEG. This raises the possibility to identify, within ongoing EEG activity, how epilepsy impacts and disrupts sleep. Here, we asked whether the presence of a lateralized epileptic focus interferes with the expression of the dominant electrophysiological hallmarks of sleep: slow oscillations, slow waves and spindles. To this aim, we conducted a cross-sectional study and analysed sleep recordings with surface EEG from 69 patients with focal epilepsy (age range at EEG: 17-61 years, 29 females, 34 left focal epilepsy). Comparing patients with left and right focal epilepsy, we assessed inter-hemispheric asymmetry of sleep slow oscillations power (delta range, 0.5-4 Hz); sleep slow wave density; amplitude, duration and slope; and spindle density, amplitude, duration as well as locking to slow oscillations. We found significantly different asymmetries in slow oscillation power (P < 0.01); slow wave amplitude (P < 0.05) and slope (P < 0.01); and spindle density (P < 0.0001) and amplitude (P < 0.05). To confirm that these population-based differences reflect actual patient-by-patient differences, we then tested whether asymmetry of sleep features can classify laterality of the epileptic focus using a decision tree and a 5-fold cross-validation. We show that classification accuracy is above chance level (accuracy of 65%, standard deviation: 5%) and significantly outperforms a classification based on a randomization of epileptic lateralization (randomization data accuracy: 50%, standard deviation 7%, unpaired t-test, P < 0.0001). Importantly, we show that classification of epileptic lateralization by the canonical epileptic biomarker, i.e. interictal epileptiform discharges, improves slightly but significantly when combined with electrophysiological hallmarks of physiological sleep (from 75% to 77%, P < 0.0001, one-way ANOVA + Sidak's multiple comparisons test). Together, we establish that epilepsy is associated with inter-hemispheric perturbation of sleep-related activities and provide an in-depth multi-dimensional profile of the main sleep electrophysiological signatures in a large cohort of patients with focal epilepsy. We provide converging evidence that the underlying epileptic process interacts with the expression of sleep markers, in addition to triggering well-known pathological activities, such as interictal epileptiform discharges.

Spike-microstates correlate with interictal epileptogenic discharges: a marker for hidden epileptic activity.

Objectively estimating disease severity and treatment success is a main problem in outpatient managing of epilepsy. Self-reported seizures diaries are well-known to underestimate the actual seizure count, and repeated EEGs might not show interictal epileptiform discharges (IEDs), although patients suffer from seizures. In this prospective study, we investigate the potential of microstate analysis to monitor epilepsy patients independently of their IED count. From our databank of candidates for epilepsy surgery, we included 18 patients who underwent controlled resting EEG sessions (with eyes closed, 30 min), at around the same time of the day, during at least four days (range: 4-8 days; mean: 5). Nine patients with temporal foci, six with extratemporal foci, and three with generalized epilepsy were included. Each patient's IEDs were marked and the topographic voltage maps of the IED peaks were averaged, and an individual average spike topography (AST) was created. The AST was then backfitted to each timepoint of the whole EEG resulting in the Spike-Microstate (SMS). The presence of the SMS in the residual EEG outside of the short IEDs epochs was determined for each recording session in each patient and correlated with the occurrence of the IEDs across all recording session, as well as with the drug charge of each day. Overall, SMS was much more represented in the routine EEG than the IEDs: they were identified 262 times more often than IEDs. The SMS time coverage correlated significantly with the IED occurrence rate (rho = 0.56; P < 0.001). If only patients with focal epilepsy were considered, this correlation was even higher rho = 0.69 (P < 0.001). Drug charge per day did not correlate with SMS. In this proof-of-concept study, the time coverage of SMS correlated strongly with the occurrence rate of the IEDs, they can be retrieved in the scalp EEG at a much higher occurrence rate. We conclude that SMS, once obtained for a given patient, are a more abundant marker of hidden epileptic activity than IEDs, in particular in focal epilepsy, and can be used also in absence of IEDs. Future larger studies are needed to verify its potential as monitoring tool and to determine cut-off values when drug protection becomes imperfect.

Early timing of anesthesia in status epilepticus is associated with complete recovery: A 7-year retrospective two-center study.

OBJECTIVE: This study was undertaken to investigate the efficacy, tolerability, and outcome of different timing of anesthesia in adult patients with status epilepticus (SE). METHODS: Patients with anesthesia for SE from 2015 to 2021 at two Swiss academic medical centers were categorized as anesthetized as recommended third-line treatment, earlier (as first- or second-line treatment), and delayed (later as third-line treatment). Associations between timing of anesthesia and in-hospital outcomes were estimated by logistic regression. RESULTS: Of 762 patients, 246 received anesthesia; 21% were anesthetized as recommended, 55% earlier, and 24% delayed. Propofol was preferably used for earlier (86% vs. 55.5% for recommended/delayed anesthesia) and midazolam for later anesthesia (17.2% vs. 15.9% for earlier anesthesia). Earlier anesthesia was statistically significantly associated with fewer infections (17% vs. 32.7%), shorter median SE duration (.5 vs. 1.5 days), and more returns to premorbid neurologic function (52.9% vs. 35.5%). Multivariable analyses revealed decreasing odds for return to premorbid function with every additional nonanesthetic antiseizure medication given prior to anesthesia (odds ratio [OR] = .71, 95% confidence interval [CI] = .53-.94) independent of confounders. Subgroup analyses revealed decreased odds for return to premorbid function with increasing delay of anesthesia independent of the Status Epilepticus Severity Score (STESS; STESS = 1-2: OR = .45, 95% CI = .27-.74; STESS > 2: OR = .53, 95% CI = .34-.85), especially in patients without potentially fatal etiology (OR = .5, 95% CI = .35-.73) and in patients experiencing motor symptoms (OR = .67, 95% CI = .48-.93). SIGNIFICANCE: In this SE cohort, anesthetics were administered as recommended third-line therapy in only every fifth patient and earlier in every second. Increasing delay of anesthesia was associated with decreased odds for return to premorbid function, especially in patients with motor symptoms and no potentially fatal etiology.

EEG biomarker candidates for the identification of epilepsy.

Electroencephalography (EEG) is one of the main pillars used for the diagnosis and study of epilepsy, readily employed after a possible first seizure has occurred. The most established biomarker of epilepsy, in case seizures are not recorded, are interictal epileptiform discharges (IEDs). In clinical practice, however, IEDs are not always present and the EEG may appear completely normal despite an underlying epileptic disorder, often leading to difficulties in the diagnosis of the disease. Thus, finding other biomarkers that reliably predict whether an individual suffers from epilepsy even in the absence of evident epileptic activity would be extremely helpful, since they could allow shortening the period of diagnostic uncertainty and consequently decreasing the risk of seizure. To date only a few EEG features other than IEDs seem to be promising candidates able to distinguish between epilepsy, i.e. > 60 % risk of recurrent seizures, or other (pathological) conditions. The aim of this narrative review is to provide an overview of the EEG-based biomarker candidates for epilepsy and the techniques employed for their identification.

Prestimulus amygdala spectral activity is associated with visual face awareness.

Alpha cortical oscillations have been proposed to suppress sensory processing in the visual, auditory, and tactile domains, influencing conscious stimulus perception. However, it is unknown whether oscillatory neural activity in the amygdala, a subcortical structure involved in salience detection, has a similar impact on stimulus awareness. Recording intracranial electroencephalography (EEG) from 9 human amygdalae during face detection in a continuous flash suppression task, we found increased spectral prestimulus power and phase coherence, with most consistent effects in the alpha band, when faces were undetected relative to detected, similarly as previously observed in cortex with this task using scalp-EEG. Moreover, selective decreases in the alpha and gamma bands preceded face detection, with individual prestimulus alpha power correlating negatively with detection rate in patients. These findings reveal for the first time that prestimulus subcortical oscillations localized in human amygdala may contribute to perceptual gating mechanisms governing subsequent face detection and offer promising insights on the role of this structure in visual awareness.

Submillimeter T1 atlas for subject-specific abnormality detection at 7T.

PURPOSE: Studies at 3T have shown that T1 relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T1 values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T. METHODS: T1 maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template-based brain segmentation algorithm was adapted to ultra-high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T1 values was established by modeling the T1 inter-subject variability. A method for single-subject comparisons restricted to white matter and subcortical structures was developed by computing Z-scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept. RESULTS: The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single-subject comparisons at 7T, and showed greater anatomical details compared with 3T results. CONCLUSION: A high-resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high-resolution single-subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice.