Epilepsy impacts around 65 million people globally, and for about one-third of those, traditional treatments don’t work. In such cases, surgery might be considered to remove the brain tissue causing seizures. However, a significant challenge in improving surgical outcomes has been accurately targeting the right areas of the brain. A recent study aimed to refine…
A recent study has tackled the tricky challenge of determining how harmful certain genetic mutations, known as missense variants, can be for individuals with epilepsy. In the world of genetics, especially when it comes to diseases like epilepsy, classifying these mutations accurately is vital for creating personalized treatment plans. However, many of these variants are still labeled as “variants of uncertain significance” (VUS), which complicates things.
In recent advancements in medical technology, researchers have developed an artificial intelligence (AI) system designed to help diagnose a brain condition known as focal cortical dysplasia (FCD). This condition can lead to epilepsy and is classified into various types by the International League Against Epilepsy (ILAE). The goal of this AI classifier is to assist pathologists by analyzing digital images of brain tissue samples and accurately identifying the type of FCD present.
Epilepsy is a neurological disorder that can lead to a range of psychiatric issues, including various types of psychosis. Those with epilepsy may experience preictal, ictal, postictal, and interictal psychoses, which can significantly impact their quality of life. Antipsychotic drugs (APDs), primarily used to treat psychosis and schizophrenia, have been considered for managing these psychiatric symptoms in people with epilepsy. However, there hasn’t been a clear understanding of how effective or safe these medications are for this specific group.
Deep brain stimulation (DBS) is gaining attention as a possible treatment for drug-resistant epilepsy (DRE), a condition where traditional medications just don’t cut it. One innovative approach involves low-frequency stimulation (LFS) targeting specific brain fiber tracts, like the corpus callosum (CC). This method seems to work by suppressing seizure activity across the cortex, but the exact ways it achieves this were still a bit of a mystery.
A recent study has made significant strides in enhancing the efficiency of diagnosing epileptic spikes using a technology called magnetoencephalography (MEG). Traditionally, neurophysiologists have to manually sift through complex data to identify these spikes, which can be a slow and tedious process. To tackle this, researchers developed a deep learning-based model that automates the detection…
A recent study has made significant strides in unraveling the complex genetic underpinnings of epilepsy, a condition known for its diverse presentations and origins. Researchers conducted a massive whole-exome sequencing project involving over 54,000 individuals, including nearly 21,000 patients with various epilepsy types and a control group of over 33,000. This impressive scale makes it…
In a fascinating study, researchers explored the link between biological rhythms in the brain and neurological disorders by analyzing the brain activity of 38 patients with refractory focal epilepsy. By using long-term intracranial EEG recordings that totaled over 6,000 hours, the team examined both circadian (daily) and ultradian (shorter than a day) rhythms in different…
Abstract Loss of parvalbumin (PV) expressing neurons (PV neurons) is relevant to the underlying mechanisms of the pathogenesis of neurological and psychiatric diseases associated with the dysregulation of neuronal excitatory networks and brain metabolism. Although PV modulates mitochondrial morphology, volume and dynamics, it is largely unknown whether mitochondrial dynamics affect PV expression and what the…