Bartonmeyer3703

Increased Motor Evoked Potential (MEP) polyphasia was recently described in idiopathic/genetic generalized epilepsy (IGE). Here, we studied the association of MEP polyphasia with treatment response and other clinical characteristics in patients with IGE.

MEPs were recorded from the biceps brachii, flexor carpi radialis and interosseus dorsalis muscles bilaterally during tonic contraction in IGE patients (n=72) and historical controls (n=54) after single pulse transcranial magnetic stimulation. Detailed clinical data was available for all IGE patients; predefined endpoint was the association of MEP polyphasia with treatment response.

The mean number of phases was higher in the interosseus dorsalis muscle (2.33 vs. Omaveloxolone 2.13, p=0.002) in IGE patients as compared to normal controls, as was the proportion of MEPs with more than two phases in at least one test (59.4% vs. 30%, p<0.002). MEP polyphasia did not differ between IGE patients and controls in the biceps brachii or the flexor carpi radialis muscles and was not associated with treatment response. Extensive exploratory analyses unveiled fewer phases under valproic acid treatment (p=0.04) but no additional associations of MEP polyphasia in the interosseous muscle with other clinical characteristics.

MEP polyphasia is a subclinical symptom of IGE patients but is not associated with treatment response or other routinely assessed clinical characteristics.

MEP polyphasia is a fixed feature of IGE not modified by clinical variables.

MEP polyphasia is a fixed feature of IGE not modified by clinical variables.

Transcutaneous low-frequency stimulation (LFS) elicits long-term depression-like effects on human pain perception. However, the neural mechanisms underlying LFS are poorly understood. We investigated cortical activation changes occurring during LFS and if changes were associated with reduced nociceptive processing and increased amplitude of spontaneous cortical oscillations post-treatment.

LFS was applied to the radial nerve of 25 healthy volunteers over two sessions using active (1Hz) or sham (0.02Hz) frequencies. Changes in resting electroencephalography (EEG) and laser-evoked potentials (LEPs) were investigated before and after LFS. Somatosensory-evoked potentials were recorded during LFS and source analysis was carried out.

Ipsilateral midcingulate and operculo-insular cortex source activity declined linearly during LFS. Active LFS was associated with attenuated long-latency LEP amplitude in ipsilateral frontocentral electrodes and increased resting alpha (8-12Hz) and beta (16-24Hz) band power in electrodes overlying operculo-insular, sensorimotor and frontal cortical regions. Reduced ipsilateral operculo-insular cortex source activity during LFS correlated with a smaller post-treatment alpha-band power increase.

LFS attenuated somatosensory processing both during and after stimulation.

Results further our understanding of the attenuation of somatosensory processing both during and after LFS.

Results further our understanding of the attenuation of somatosensory processing both during and after LFS.

Neonatal seizures are often the first symptom of perinatal brain injury. High-frequency oscillations (HFOs) are promising new biomarkers for epileptogenic tissue and can be found in intracranial and surface EEG. To date, we cannot reliably predict which neonates with seizures will develop childhood epilepsy. We questioned whether epileptic HFOs can be generated by the neonatal brain and potentially predict epilepsy.

We selected 24 surface EEGs sampled at 2048Hz with 175 seizures from 16 neonates and visually reviewed them for HFOs. Interictal epochs were also reviewed.

We found HFOs in thirteen seizures (7%) from four neonates (25%). 5025 ictal ripples (rate 10 to 1311/min; mean frequency 135Hz; mean duration 66ms) and 1427 fast ripples (rate 8 to 356/min; mean frequency 298Hz; mean duration 25ms) were marked. Two neonates (13%) showed interictal HFOs (285 ripples and 25 fast ripples). Almost all HFOs co-occurred with sharp transients. We could not find a relationship between neonatal HFOs and outcome yet.

Neonatal HFOs co-occur with ictal and interictal sharp transients.

The neonatal brain can generate epileptic ripples and fast ripples, particularly during seizures, though their occurrence is not common and potential clinical value not evident yet.

The neonatal brain can generate epileptic ripples and fast ripples, particularly during seizures, though their occurrence is not common and potential clinical value not evident yet.

To evaluate the safety and temporal dynamic of the antiepileptic effect of spaced transcranial direct current stimulation (tDCS) in different focal epilepsies.

Cathodal tDCS with individual electrode placement was performed in 15 adults with drug resistant focal epilepsy. An amplitude of 2mA was applied twice for 9 minutes, with an interstimulation interval of 20 minutes. Tolerability was assessed via the Comfort Rating Questionnaire and the frequency of interictal epileptiform discharges (IEDs) was sequentially compared between the 24 hours before and after tDCS.

TDCS led to a significant reduction in the total number of IEDs/24h by up to 68% (mean±SD -30.4±21.1%, p=0.001) as well as in seizure frequency (p=0.041). The maximum IED reduction was observed between the 3rd and 21st hour after stimulation. Favorable clinical response was associated with structural etiology and clearly circumscribed epileptogenic foci but did not differ between frontal and temporal epilepsies. Overall, the tDCS treatment was well tolerated and did not lead to severe adverse events.

The spaced stimulation approach proved to be safe and well-tolerated in patients with drug-resistant unifocal epilepsies, leading to sustained IED and seizure frequency reduction.

Spaced tDCS induces mediate antiepileptic effects with promising therapeutic potential.

Spaced tDCS induces mediate antiepileptic effects with promising therapeutic potential.The electroencephalogram (EEG) is a fundamental tool in the diagnosis and classification of epilepsy. In particular, Interictal Epileptiform Discharges (IEDs) reflect an increased likelihood of seizures and are routinely assessed by visual analysis of the EEG. Visual assessment is, however, time consuming and prone to subjectivity, leading to a high misdiagnosis rate and motivating the development of automated approaches. Research towards automating IED detection started 45 years ago. Approaches range from mimetic methods to deep learning techniques. We review different approaches to IED detection, discussing their performance and limitations. Traditional machine learning and deep learning methods have yielded the best results so far and their application in the field is still growing. Standardization of datasets and outcome measures is necessary to compare models more objectively and decide which should be implemented in a clinical setting.