vicar_char

A dataset containing the parameter estimates from
the anatomical mask of the left nucleus accumbens (Harvard-Oxford subcortical atlas;
thresholded at 40%; center-of-mass coordinates x = -10, y = 12, z = -7; 28 voxels included),
with one value for the mean activation during gaining for self and one value for the mean
activation during no-gain for self and charity for all participants.

datasets

Calculate the precision in mean differences (raw or Cohen's D) and
correlation coefficients for different sample sizes. Uses permutations of the
collected functional magnetic resonance imaging (fMRI) region of interest data.
Method described in Klapwijk, Jongerling, Hoijtink and Crone (2024)
<doi:10.31234/osf.io/cz32t>.

Eduard Klapwijk

neuroUp

Plan Sample Size for Task fMRI Research using Bayesian Updating

Herbert Hoijtink

Joran Jongerling

vicar_char function

A data frame with 156 rows and 4 variables:<dl>
<dt>participant_id</dt>
<dd>unique id for every participant</dd><dt>age</dt>
<dd>age in years (11.00-21.17)</dd><dt>nacc_selfgain</dt>
<dd>parameter estimates for the left nucleus accumbens during
gaining for self (-5.66-3.05)</dd><dt>nacc_bothnogain</dt>
<dd>parameter estimates for the left nucleus accumbens during
no-gain for self and charity (-6.44-2.97)</dd>
</dl>

Format

Vicarious Charity task fMRI region of interest data — vicar_char

A data frame with 156 rows and 4 variables:<dl>
<dt>participant_id</dt>
<dd>unique id for every participant</dd>

<dt>age</dt>
<dd>age in years (11.00-21.17)</dd>

<dt>nacc_selfgain</dt>
<dd>parameter estimates for the left nucleus accumbens during
gaining for self (-5.66-3.05)</dd>

<dt>nacc_bothnogain</dt>
<dd>parameter estimates for the left nucleus accumbens during
no-gain for self and charity (-6.44-2.97)</dd>


</dl>

vicar_char: Vicarious Charity task fMRI region of interest data

Description

Usage

Arguments

Format