[FieldTrip] zero-padding VS mirror-padding (ft_freqanalysis)

Maris Skujevskis icelandhouse at gmail.com
Fri Sep 18 17:35:45 CEST 2015


Dear Fieldtrip community,

I am currently doing frequency analysis on an EEG dataset.

My question is a general one about the dis/advantages of zero- VS
mirror-padding a finite time series prior to frequency analysis
(ft_freqanalysis).

The way ft_freqanalysis is implemented suggests that zero padding is always
the best option, e.g., ft_freqanalysis does not support mirror padding.

However, it seems to me that mirror padding is also a good and a valid way
to address the 'missing values' issue at the temporal edges of a TFR.
Here is my (intuitive) reasoning:
The disadvantage of zero padding is that it creates a discontinuity at the
edges of the data segment, thus introducing additional frequency content
and distorting the power estimates. Mirror padding might overestimate the
power of the frequencies present, but, to its advantage, it preserves the
frequency content of the actual data. Short summary: both ways of padding
have their strengths and weaknesses, there is no clear winner.


It would be good to hear what other researchers think about the
advantages/disadvantages of the two ways of padding.
Is zero-padding always a better way of padding than mirror- (or any other
type of) padding?
Does the answer depend on some further factors?

Best wishes,
Maris
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