Epilepsy


AI brain chips will 'evolve' humanity into 'zombies'

Daily Mail

AI brain chips are set to'evolve' humanity into a'community of zombies', a prominent neuroscientist has claimed. Those implanting AI into their mind risk merging with machines to the point that humans and androids are indistinguishable from one another, the expert said. It was recently revealed that a tech company backed by billionaire Elon Musk is developing a'brain-computer interface' that could give people super intelligence and allow them to communicate telepathically. Dr Mikhail Lebedev, a senior neuroscientist at Duke University in Durham claims AI brain chips are set to'evolve' humanity into a'community of zombies' (stock image) Kernel is currently working on prototypes of a brain implant device for medical use in humans. The firm has started to conduct tests with epilepsy patients in hospitals.


AI brain chips will create a new breed of superhumans

Daily Mail

Humans may soon be able to communicate while in complete silence if a company's new'brain augmentation' technology becomes a reality. A'brain-computer interface' could mean people communicate telepathically - and are able to solve complex problems in as little as a few seconds. Implanting a microchip into your brain may sound like the plot from a science fiction blockbuster, but some claim this technology could be a reality within 15 years. A'brain-computer interface' could mean people communicate telepathically - and could solve complex problems in as little as a few seconds, an expert has claimed (stock image) Kernel is currently working on prototypes of a brain implant device for medical use in humans. The firm has started to conduct tests with epilepsy patients in hospitals.


A Wearable Chip to Predict Seizures

#artificialintelligence

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. The scientists built the system on a mountain of brainwave data collected from epilepsy patients. The dataset, reported by a separate group in 2013, included over 16 years of continuous electroencephalography (EEG) recordings of brain activity, and thousands of seizures, from patients who had had electrodes surgically implanted in their brains.


IBM and University of Melbourne present seizure prediction system

ZDNet

Researchers from IBM and the University of Melbourne have developed a proof-of-concept seizure forecasting system that predicted an average of 69 percent of seizures across 10 epilepsy patients in a dataset. The system, which the scientists claim is "fully automated, patient-specific, and tunable to an individual's needs", uses a combination of deep-learning algorithms and a low-power "brain-inspired" computing chip to predict when seizures might occur, even if patients have no previous prediction indicators. IBM noted that a one-size-fits-all approach is inadequate when it comes to epilepsy management, as the condition manifests itself uniquely in each patient. "Epilepsy is a very unique condition where triggers for seizures are specific to individual patients -- some may be sensitive to heat, others to stress. This is why deep learning is important because it can interpret the data and look for signs and patterns specific to an individual's brain signals," an IBM spokesperson told ZDNet.


Scientists Are Using Machine Learning To Better Predict Epilepsy

#artificialintelligence

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. Our input data consisted of 3 different diffusion imaging modalities: mean diffusivity (MD), fractional anisotropy (FA), and mean kurtosis (MK). Predictive models trained with MK proved to be the most accurate: .82 Also, the highest coefficients of these linear models were located within the inferior medial aspect of the temporal lobes. These locations have complex fiber anatomy with many crossings.


These Neurons are Alive and Firing. And You Can Watch Them In 3-D

WIRED

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.


Forget Police Sketches: Researchers Perfectly Reconstruct Faces by Reading Brainwaves

#artificialintelligence

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.


Using Machine Learning to Predict Epileptic Seizures from EEG Data - MATLAB & Simulink

#artificialintelligence

The algorithms I developed in MATLAB scored highest among individual participants and third highest in the competition overall. In this study, intracranial EEG recordings were collected from 15 epileptic patients via 16 surgically implanted electrodes sampled at 400 Hz for several months. Kaggle competition participants received almost 100 gigabytes of EEG data from three of the test subjects. Each ten-minute-long segment contained either preictal data, recorded before a seizure, or interictal data, recorded during a long period in which no seizures occurred.


Forget Police Sketches: Researchers Perfectly Reconstruct Faces by Reading Brainwaves

#artificialintelligence

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.


How Elon Musk could meld man and machine

Daily Mail

Computers and brains already talk to each other daily in high-tech labs – and they do it better and better. For example, disabled people can now learn to govern robotic limbs by the sheer power of their mind. The hope is that we may one day be able to operate spaceships with our thoughts, upload our brains to computers and, ultimately, create cyborgs. Elon Musk (pictured) has acquired Neuralink, a company aiming to establish a direct link between the mind and the computer. Its'neural lace' technology involves implanting electrodes in the brain to measure signals.