解釋來源：https://mne.tools/stable/glossary.html
1、epoch
Epochs (sometimes called “trials” in other software packages) are equal-length spans of data extracted from raw continuous data. Usually, epochs are extracted around stimulus events or subject responses, though sometimes sequential or overlapping epochs are extracted (e.g., for analysis of resting-state activity).
In order to answer your question in a simple way, imagine we have a signal x with length of 60-s and our sampling frequency is 1 Hz.The matrix representation of your EEG signal would be 1*60 array or matrix, so if you divide your main signal to some 2-s signals, you would have 30 epoch(each 2s of your main signal would be an epoch).
You could done this by a simple for loop in matlab and at the end you would have a new matrix which size is 30*1*2.
2、events
Events correspond to specific time points in raw data; e.g., triggers, experimental condition events, etc. MNE represents events with integers that are stored in numpy arrays of shape (n_events, 3). Such arrays are classically obtained from a trigger channel, also referred to as stim channel.
3、evoked
Evoked data are obtained by averaging epochs. Typically, an evoked object is constructed for each subject and each condition, but it can also be obtained by averaging a list of evoked over different subjects. See EvokedArray for the API of the corresponding object class, and The Evoked data structure: evoked/averaged data for a narrative overview.
4、info
Also called measurement info, it is a collection of metadata regarding a Raw, Epochs or Evoked object; e.g., channel locations and types, sampling frequency, preprocessing history such as filters …
2、腦電系統和文件格式
來源：https://mne.tools/stable/auto_tutorials/io/plot_20_reading_eeg_data.html#general-data-format-gdf
