ADC

As you may know, your brain waves are a continuous process (I would hope so), so we call this an analog signal. When we record brain activity through the EEG, the computer is undergoing a process called digitizing the EEG. This means “the EEG is an analog signal that varies continuously over a range of voltages over time, and it must be converted into a set of discrete samples to be stored on a computer”, (Luck, 2014, Chapter 5). You can think of these samples as a point in time. This is where the principle of sampling rate comes in: “The continuous EEG is converted into these discrete samples by a device called an analog-to-digital converter (ADC)” and “the sampling period is the amount of time between consecutive samples (e.g., 4 ms), and the sampling rate is the number of samples taken per second (e.g., 250 Hz)” (Luck, 2014, Chapter 5). 1 Hz is equivalent to 1 cycle per second, you can do the math! Another important concept to understand when talking about sampling rate is the Nyquist Theorem: “which states that all of the information in an analog signal such as the EEG can be captured digitally as long as the sampling rate is more than twice as great as the highest frequency in the signal” (Luck, 2014, Chapter 5). The reason this is important, is because of aliasing: if you sample at lower rates, you will induce artifactual low frequencies in the digitized data. If this is confusing, think of a real world example of aliasing: car tires turning backward when going fast bc our eyes aren’t sampling fast enough.