hpf_param

internal

Implements Bayesian brain mapping models, including the prior
ICA (independent components analysis) model proposed in Mejia et al. (2020)
<doi:10.1080/01621459.2019.1679638> and the spatial prior ICA model
proposed in proposed in Mejia et al. (2022)
<doi:10.1080/10618600.2022.2104289>. Both models estimate subject-level
brain as deviations from known population-level networks, which are
estimated using standard ICA algorithms. Both models employ an
expectation-maximization algorithm for estimation of the latent brain
networks and unknown model parameters. Includes direct support for 'CIFTI',
'GIFTI', and 'NIFTI' neuroimaging file formats.

Amanda Mejia

BayesBrainMap

Estimate Brain Networks and Connectivity with Population-Derived
Priors

Damon Pham

Daniel Spencer

Mary Beth Nebel

hpf_param function

<dl><dt>hpf</dt>
<dd>The frequency at which to apply a highpass filter to the data
during pre-processing, in Hertz. Default: <code>0</code> Hz (disabled). If the
data has not already been highpass filtered, a recommended filter value is
<code>.01</code> Hz.
The highpass filter serves to detrend the data, since low-frequency
variance is associated with noise. Highpass filtering is accomplished by
nuisance regression of discrete cosine transform (DCT) bases.
Note the <code>TR</code> argument is required for highpass filtering. If
<code>TR</code> is not provided, <code>hpf</code> will be ignored.</dd></dl>

Arguments

hpf — hpf_param

<dl>

<dt>hpf</dt>
<dd>The frequency at which to apply a highpass filter to the data
during pre-processing, in Hertz. Default: <code>0</code> Hz (disabled). If the
data has not already been highpass filtered, a recommended filter value is
<code>.01</code> Hz.
The highpass filter serves to detrend the data, since low-frequency
variance is associated with noise. Highpass filtering is accomplished by
nuisance regression of discrete cosine transform (DCT) bases.
Note the <code>TR</code> argument is required for highpass filtering. If
<code>TR</code> is not provided, <code>hpf</code> will be ignored.</dd>

</dl>

hpf_param: hpf

Description

Arguments