Electronics & Semiconductors

Demonstrating significant energy savings using neuromorphic hardware

For the first time TU Graz's Institute of Theoretical Computer Science and Intel Labs demonstrated experimentally that a large neural network can process sequences such as sentences while consuming four to sixteen times less ...

Computer Sciences

A flexible Bayesian framework for unbiased estimation of timescales

An international team of researchers from Tübingen and Cold Spring Harbor (New York) has found a pioneering way of determining at what pace changes typically happen. The new method avoids previous systematic errors in estimating ...

Robotics

Mind-controlled robots now one step closer

Tetraplegic patients are prisoners of their own bodies, unable to speak or perform the slightest movement. Researchers have been working for years to develop systems that can help these patients carry out some tasks on their ...

Machine learning & AI

Mind and matter: Modeling the human brain with machine learning

We all like to think that we know ourselves best, but given that our brain activity is largely governed by our subconscious mind, it is probably our brain that knows us better. While this is only a hypothesis, researchers ...

Robotics

Brain activity reveals individual attitudes toward humanoid robots

The way humans interpret the behavior of AI-endowed artificial agents, such as humanoid robots, depends on specific individual attitudes that can be detected from neural activity. Researchers at IIT-Istituto Italiano di Tecnologia ...

Computer Sciences

Computational model decodes speech by predicting it

The brain analyzes spoken language by recognizing syllables. Scientists from the University of Geneva (UNIGE) and the Evolving Language National Centre for Competence in Research (NCCR) have designed a computational model ...

Consumer & Gadgets

CES has solutions to show for better paths to sleep

Getting enough sleep is a real issue for many; a Columbia University Department of Neurology info page referred to estimates from The Institute of Medicine, that between 50 and 70 million Americans alone have chronic sleep ...

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Electroencephalography

Electroencephalography (EEG) is the recording of electrical activity along the scalp produced by the firing of neurons within the brain. In clinical contexts, EEG refers to the recording of the brain's spontaneous electrical activity over a short period of time, usually 20–40 minutes, as recorded from multiple electrodes placed on the scalp. In neurology, the main diagnostic application of EEG is in the case of epilepsy, as epileptic activity can create clear abnormalities on a standard EEG study. A secondary clinical use of EEG is in the diagnosis of coma and encephalopathies. EEG used to be a first-line method for the diagnosis of tumors, stroke and other focal brain disorders, but this use has decreased with the advent of anatomical imaging techniques such as MRI and CT.

Derivatives of the EEG technique include evoked potentials (EP), which involves averaging the EEG activity time-locked to the presentation of a stimulus of some sort (visual, somatosensory, or auditory). Event-related potentials refer to averaged EEG responses that are time-locked to more complex processing of stimuli; this technique is used in cognitive science, cognitive psychology, and psychophysiological research.

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