The lower cutoff sets the point below which slow components are progressively attenuated, while the upper cutoff limits higher-frequency content. Together, these boundaries determine whether activity associated with delta, theta, alpha, beta, or gamma is emphasized. Changing either cutoff changes the portion of the recording available for subsequent analysis of oscillatory activity.
Frequency limits are not merely technical settings: they shape which components remain visible. A range that is too broad may retain drift, electrical interference, or unwanted noise, whereas a range that is too narrow may suppress relevant oscillatory activity. Careful selection therefore affects whether apparent changes in brain state or neural communication reflect the recording or the filtering choice.
It addresses two different sources of unwanted signal at once. The high-pass portion reduces slow baseline drift, and the low-pass portion attenuates unwanted high-frequency noise. This combined action can make a targeted oscillatory component easier to examine in electroencephalography, local field potential, or other neural recordings, without treating the entire broadband signal as equally informative.
They should first identify the oscillatory activity relevant to the research question and select lower and upper frequency limits around that component. The choice should also account for unwanted slow drift, electrical interference, and high-frequency noise present in the recording. These decisions determine which neural information is retained and which is attenuated during analysis.
Filtered recordings can support analyses of brain states, sensory processing, and neural communication by isolating activity in a selected oscillatory range. Researchers may focus on delta, theta, alpha, beta, or gamma activity depending on the signal feature under study. The resulting representation is useful when the relevant rhythm would otherwise be obscured by unrelated frequencies or recording contamination.
The same filtering principle can be applied to electroencephalography, local field potential recordings, and other neural signals, but the purpose remains tied to the component being examined. In each case, researchers use frequency limits to reduce unwanted portions of the recording and clarify oscillatory activity relevant to brain states, sensory processing, or neural communication.