Epilepsy damages lives of suffering patients and their families and if we can diagnose, predict, and prevent it, that would be a game changer for mental health. Anti-epileptic medicines have several side-effects. Imagine a world where epileptic patient had to take fewer medications or simply could have an implant which could prevent epileptic seizure. All of that would require few tiny sensors on skull, hidden underneath patients' hair and a smart phone which receives and processes the information, either offline or online, and activates a probe to prevent seizure. Well we have obviously oversimplified here but we want you to get the picture without getting lost in technical jargon first. We at Khurana group have a team working on it day and night out. While we are very proud of our efforts but there are other friends (or if you prefer to call them competitors) who are doing commendable job in the same direction for years. In this article, we would take you through what products are already out there but before that let us take you through some basics of epilepsy.
One of the toughest aspects of having epilepsy is not knowing when the next seizure will strike. A wearable warning system that detects pre-seizure brain activity and alerts people of its onset could alleviate some of that stress and make the disorder more manageable. To that end, IBM researchers say they have developed a portable chip that can do the job; they described their invention today in the Lancet's open access journal eBioMedicine.
There are 2 aspects of this research that are worth highlighting: (1) we showed that micro-structural extra-hippocampal abnormalities are consistent enough across medial temporal lobe epilepsy (TLE) patients that they can be used to predict TLE, and (2) we obtained regularization values for the models trained on this sparse data in an unusual but effective manner.
For patients with epilepsy, or cancerous brain lesions, sometimes the only way to forward is down. Down past the scalp and into the skull, down through healthy grey matter to get at a tumor or the overactive network causing seizures. At the end of the surgery, all that extra white and grey matter gets tossed in the trash or an incinerator. For the last few years, doctors at a number of hospitals in the Emerald City have been saving those little bits and blobs of brain, sticking them on ice, and rushing them off in a white van across town to the Allen Institute for Brain Science. Scientists there have been keeping the tissue on life support long enough to tease out how individual neurons look, act, and communicate.
Using brain scans and direct neuron recording from macaque monkeys, the team found specialized "face patches" that respond to specific combinations of facial features. In the early 2000s, while recording from epilepsy patients with electrodes implanted into their brains, Quian Quiroga and colleagues found that face cells are particularly picky. In a stroke of luck, Tsao and team blew open the "black box" of facial recognition while working on a different problem: how to describe a face mathematically, with a matrix of numbers. In macaque monkeys with electrodes implanted into their brains, the team recorded from three "face patches"--brain areas that respond especially to faces--while showing the monkeys the computer-generated faces.
Sponsored by MathWorks, the National Institutes of Health (NINDS), the American Epilepsy Society, and the University of Melbourne, the competition attracted 478 teams and 646 competitors from around the world. The algorithms I developed in MATLAB scored highest among individual participants and third highest in the competition overall. The EEG data came from a long-term study conducted by the University of Melbourne. In this study, intracranial EEG recordings were collected from 15 epileptic patients via 16 surgically implanted electrodes sampled at 400 Hz for several months. In the original study, researchers were unable to reliably predict seizures for about 50% of the test subjects.