News Excerpt:

A century after the EEG was discovered, it remains a crucial tool for understanding the brain.

A history of EEG:

• The story of EEG is colorful and littered with fables. 
• By the mid-1930s, researchers had observed the striking differences between the awake and asleep EEG. 
• The EEGs of patients with brain disease turned up a variety of unprecedented observations.
• In December 1934, a group of Boston physicians observed the rhythmic EEG spike-wave appearance of seizures in patients with “petit mal” epilepsy. 
• Petit mal is an anachronistic term for a type of epilepsy where a patient’s flow of thought, speech or action momentarily freezes during seizures. 
• For the first time, the symptoms and behavior of patients during seizures were correlated to a brain signal occurring in lockstep.
• EEG quickly evolved from a scientific curiosity to a mainstream clinical tool. 
• The first clinical EEG laboratory was set up at Massachusetts General Hospital in 1937. 
• The practice grew in the ensuing decades into the specialized services that institutions like ours have offered since the 1970s.

 What is the EEG?

• An EEG monitors and records brainwave patterns. Small flat metal discs called electrodes are attached to your scalp with wires.
• The electrodes evaluate electrical impulses in your brain and transfer them to a computer, which records the results.
• The electrical impulses in an EEG recording appear as wavy lines with peaks and valleys. 
• These lines allow doctors to swiftly determine if there are any odd patterns. Irregularities may indicate seizures or other brain problems.

How do electrical patterns arise in the brain? 

• Electrical patterns arise in the brain due to the natural repetitive activity, or oscillations, of neurons. 
• This oscillatory activity is a result of the way neurons are connected and how they interact through excitation and inhibition, creating push-pull effects.
•  These local oscillations serve as fundamental building blocks, contributing to the overall EEG (electroencephalogram) activity across the brain. 
• Interestingly, these oscillations can synchronize, or coalesce, into a common rhythm, leading to patterns observed in EEG, including seizure-like patterns in patients.

Key Points Related to EEG, AI, and the Mind:

• Neural networks, initially proposed by Warren McCulloch and Walter Pitts in 1943, have evolved to become the hardware backbone of modern AI systems. 
• Their inspiration stemmed from the structure and function of the brain's neurons, as observed through electroencephalography (EEG).
• Over decades, the foundational concepts of neural networks evolved into deep learning, a subset of AI that employs complex neural network architectures. 
• These deep learning networks, inspired by the brain's structure, are now integral to various AI applications.
• Deep learning AI has permeated diverse fields of biomedicine, including neurology.
• AI systems are proficient in tasks like interpreting brain scans and analyzing EEG data.
• Recent advancements in deep learning AI have demonstrated the potential to decode aspects of mental activity from EEG signals. 
• This suggests that AI systems can infer certain thoughts or cognitive processes from brain activity patterns.
• AI laid the groundwork for understanding complex phenomena like thought processes, recent research hints at AI's potential to approach Berger's quest for telepathy.
•  By decoding EEG signals, 
• AI systems may gain insights into human cognition and potentially infer thoughts or intentions.

Way forward:

In 2024, EEG turns 100. What windows will it open into the brain and mind in the future? Doubtless, clinical applications will grow. Surely, brain pattern generation will be better understood. Perhaps EEG will glimpse the content of the mind. And for neurologists like me surveying the AI revolution, there’s the quiet pride that EEG was really at the start of it all.