100th Anniversary of Discovery of Electroencephalogram (EEG) Observed

April 6, 2024

The year 2024 marks the centennial of the discovery of the electroencephalogram (EEG) by German psychiatrist Hans Berger. The EEG, a medical test that measures the electrical activity of the brain, has become a crucial tool for understanding the brain and diagnosing neurological disorders.

History and discovery

In 1924, working in near-isolation and with painstaking tediousness, Hans Berger observed rhythmic electrical activity from the scalp of human subjects in Jena, Germany. Convinced that the activity arose from within the brain, he coined the term “electroencephalogram.” It took another decade for the scientific community to accept Berger’s work, marking the birth of the field of electroencephalography.

Clinical applications

Today, the EEG is widely used as a medical test to measure brain electrical activity in patients with or suspected to have neurological disorders. The procedure can be short, often just a 30-minute recording, but for patients monitored for diagnosis or treatment of brain disease, it can be continued for days or even weeks. Neurologists use EEG on a daily basis to interpret brain activity and diagnose conditions such as epilepsy.

Understanding the EEG

The EEG arises from the excitable nature of nerve cells, or neurons. When neurons fire, action potentials set up local electrical activity in other neurons, causing current to flow within and outside them. The average overall activity is a mix of many different frequencies, with the five main ones called delta, theta, alpha, beta, and gamma waves. The remarkable fact is that EEG tends to spontaneously organize into patterns in time and space, which can be recognized and correlated to specific disease states.

Research on pattern formation in EEG

Beyond clinical applications, scientists are interested in understanding how electrical patterns arise in the brain. Research has shown that activity in the brain is naturally repetitive, or oscillatory, due to the way neurons are connected and interact by excitation and inhibition to produce push-pull effects. By considering local oscillations as fundamental building blocks, researchers have demonstrated that the EEG over the entire brain could be built up from such elementary blocks, and differing frequencies could be made to coalesce, or synchronize, into a common rhythm.

EEG, AI, and the mind

The hardware underlying the majority of today’s artificial intelligence (AI) systems, neural networks, were introduced in 1943 by Warren McCulloch, a physician and electroencephalographer. McCulloch wondered where in the brain’s neurons and EEG lay the capacity to think, and conceived the idea of grouping artificial neuron-like computing units into networks, analogous to how real neurons in the brain interconnected. Recent deep-learning AI research has shown that some aspects of mental activity may be decoded from EEG, raising questions about the possibility of AI approaching Berger’s quest for telepathy.

Additional facts

The first clinical EEG laboratory was set up at Massachusetts General Hospital in 1937.
In December 1934, a group of Boston physicians observed the rhythmic EEG spike-wave appearance of seizures in patients with “petit mal” epilepsy, correlating symptoms and behavior during seizures with a brain signal for the first time.
EEG has been used to study sleep stages, with distinct patterns observed during different stages of sleep, such as rapid eye movement (REM) sleep and non-REM sleep.
EEG has also been employed in brain-computer interfaces (BCIs), which allow individuals to control external devices using brain signals.
In addition to its clinical applications, EEG has been used in research to study cognitive processes, such as attention, memory, and decision-making.
The discovery of EEG has paved the way for other brain imaging techniques, such as magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and positron emission tomography (PET).

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