Has anyone experienced issues when using nilearn.signal.clean to deconfound resting-state fMRI time series?
By default, the function applies detrending. When I include detrending, the resulting residual time series values are much smaller in magnitude—so much so that they appear nearly mean-centered (though I’m not explicitly doing that and have set standardize=False). I understand that detrending is often beneficial, but in this case, it’s drastically reducing the amplitude of my residuals.
This becomes a problem when I calculate temporal SNR. The tSNR values drop into the single digits, which seems implausible and is a direct consequence of the low residual amplitudes.
I have two related questions:
- Has anyone else observed such a dramatic change in signal amplitude or tSNR when using
signal.cleanwith detrending? - If so, how do you interpret or adjust your tSNR metrics afterward—do you scale them in some way to make them meaningful?
Currently banging my head against a wall, so any insights would be appreciated!