Clinical Reasoning: A 62-Year-Old Woman With Transient Vision Loss.

Transient visual loss (TVL) is a common complaint in the emergency department, with numerous possible etiologies. Prompt evaluation and management of TVL can potentially prevent progression to permanent visual loss. In this case, a 62-year-old woman presented with acute, painless, unilateral TVL.

Source-sink connectivity: a novel interictal EEG marker for seizure localization.

Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist.

Antiseizure Medications for Adults With Epilepsy: A Review.

Importance: Epilepsy affects approximately 65 million people worldwide. Persistent seizures are associated with a 20% to 40% risk of bodily injuries (eg, fractures, burns, concussions) over 12-month follow-up. The primary goal of epilepsy treatment is to eliminate seizures while minimizing adverse effects of antiseizure drugs (ASDs).

Long-term seizure and psychiatric outcomes following laser ablation of mesial temporal structures.

Objective: Postsurgical seizure outcome following laser interstitial thermal therapy (LiTT) for the management of drug-resistant mesial temporal lobe epilepsy (MTLE) has been limited to 2 years. Furthermore, its impact on presurgical mood and anxiety disorders has not been investigated. The objectives of this study were (1) to identify seizure outcome changes over a period ranging from 18 to 81 months; (2) to investigate the seizure-free rate in the last follow-up year; (3) to identify the variables associated with seizure freedom; and (4) to identify the impact of LiTT on presurgical mood and anxiety disorders.

Deep learning for robust detection of interictal epileptiform discharges.

Automatic detection of interictal epileptiform discharges (IEDs, short as 'spikes') from an epileptic brain can help predict seizure recurrence and support the diagnosis of epilepsy. Developing fast, reliable and robust detection methods for IEDs based on scalp or intracranial electroencephalogram (iEEG) may facilitate online seizure monitoring and closed-loop neurostimulation.We developed a new deep learning approach, which employs a long short-term memory network architecture ('IEDnet') and an auxiliary classifier generative adversarial network (AC-GAN), to train on both expert-annotated and augmented spike events from iEEG recordings of epilepsy patients.