Frequency Tagging
Periodic stimulation
Imagine a light flashing in your eyes at six times per second. If we recorded your brain activity using EEG while this light was flashing, an oscillatory neural response would be detectable at the same frequency as the flashing light (6 Hz) in the occipital region of your brain, which is typically the region associated with visual processing.
If we increased the speed of the flashing light to 10 times per second, the neural response would also increase to 10 Hz. This relationship between periodic stimulation and the neural response at that same frequency is the basis for FPVS experiments. This phenomenon is known as a Steady State Visually Evoked Potential, or SSVEP.
Base and Oddball frequencies
FPVS oddball experiments typically produce two separate frequencies referred to as the Base Frequency and the Oddball Frequency.
The Base Frequency is the frequency at which stimuli are displayed on screen. For example, if a stimulus is displayed six times per second, like the flashing light used in the previous example, the base frequency would be 6 Hz. The Oddball frequency is the frequency at which the oddball stimulus is displayed. For example, if the oddball stimulus is displayed once every five stimuli at a base presentation rate of 6 Hz, the oddball frequency would be 1.2 Hz.
Harmonics
A harmonic is a frequency that is an exact whole-number multiple of a repeating signal’s fundamental frequency, hereafter referred to as F. For example, if a visual stimulus repeats at 6 Hz, its harmonics occur at 12 Hz (2F), 18 Hz (3F), 24 Hz (4F), and so on.
One way to understand harmonics is to imagine building a repeating waveform by combining several smooth sine waves. A single sine wave at F produces a simple, smooth waveform. Real visual stimuli and brain responses are usually more complex. Additional, faster sine waves are needed to reproduce features such as sharper peaks, asymmetry, or abrupt changes. Because the complete waveform repeats at the same regular interval, these additional waves fit a whole number of cycles within each repetition. This places them at integer multiples of F.
A fast Fourier transform (FFT) separates the recorded EEG waveform into these individual frequency components. Harmonics may reflect various properties of the stimulus in question.
Norcia et al. (2015) provide more detailed explanations and illustrations showing how complex repeating responses produce harmonics at F, 2F, 3F, and so on.