fMRI data were analyzed using SPM12 (v771). The anatomical image was segmented and normalized to the Statistical Paremetric Mapping (SPM12) Montreal Neurological Institute (MNI) template. Preprocessing of the functional data involved slice-time correction, realignment to the mean image and co-registration of the functional images (mean and others) to the anatomical image. The co-registered functional data were normalized to MNI space, resampled to 3 mm3 voxels and smoothed with a Gaussian kernel with a full-width-at-half-maximum of 8 × 8 × 8 mm. Volumes affected by small movement artifacts were identified with the Artifact Detection Tools toolbox (http://www.nitrc.org/projects/artifact_detect ; parameters: framewise displacement >0.5 mm, image intensity change z > 4 and exclusion criterion for a measurement: >25% affected volumes).
Of the original 86 fMRI measurements, we had to exclude nine from the activation analysis of the send paradigm (resulting in N = 77) and seven measurements from the activation analysis of the receive paradigm (resulting in N = 79) due to excessive head motion, technical problems or aborted measurements due to time constraints. In total, this resulted in 14 participants having to be excluded from the comparison of the receive paradigm with the self-compliment paradigm (N = 72).
First, we analyzed the task-related activation in the individuals’ brains by means of general linear modeling. A first-level model with three sessions for the three separate conditions of the experiment was set up to allow for both within-session and across-session contrasts. With the conditions, the individual phases (waiting for and receiving a compliment, as well as selecting and observing shared compliments) were modeled as blocks. Signals from cerebrospinal fluid and white matter, 24 movement parameters (six standard parameters, their backward derivatives and their squared versions) and ART dummy regressors were included as nuisance regressors. A high-pass filter with a frequency cutoff of 128 s was applied, as well first-degree autoregression.
In the group analyses, age, sex and scanner were included as covariates. Analyses were conducted using one-sample t-tests over the respective contrasts. Contrasts of interests were [Receiving > Waiting] within blocks (partner compliment and self-compliment) and [Receiving > Waiting] compared between blocks (partner compliment and self-compliment) as well as a contrast between the active block [Choosing compliment > Observing sent compliment] and the passive block [Receiving > Waiting]. All activation results are reported with P < 0.05 whole-brain familywise error (FWE)–corrected significance. Beta estimates were additionally extracted, only for visualization of the activity of the ventral striatum (anatomical region-of-interest from the Automatic Anatomic Labeling-90 atlas) during conditions (Figure 4 ).
Questionnaire data were analyzed using SPSS 27 (IBM).
Of the original 86 fMRI measurements, we had to exclude nine from the activation analysis of the send paradigm (resulting in N = 77) and seven measurements from the activation analysis of the receive paradigm (resulting in N = 79) due to excessive head motion, technical problems or aborted measurements due to time constraints. In total, this resulted in 14 participants having to be excluded from the comparison of the receive paradigm with the self-compliment paradigm (N = 72).
First, we analyzed the task-related activation in the individuals’ brains by means of general linear modeling. A first-level model with three sessions for the three separate conditions of the experiment was set up to allow for both within-session and across-session contrasts. With the conditions, the individual phases (waiting for and receiving a compliment, as well as selecting and observing shared compliments) were modeled as blocks. Signals from cerebrospinal fluid and white matter, 24 movement parameters (six standard parameters, their backward derivatives and their squared versions) and ART dummy regressors were included as nuisance regressors. A high-pass filter with a frequency cutoff of 128 s was applied, as well first-degree autoregression.
In the group analyses, age, sex and scanner were included as covariates. Analyses were conducted using one-sample t-tests over the respective contrasts. Contrasts of interests were [Receiving > Waiting] within blocks (partner compliment and self-compliment) and [Receiving > Waiting] compared between blocks (partner compliment and self-compliment) as well as a contrast between the active block [Choosing compliment > Observing sent compliment] and the passive block [Receiving > Waiting]. All activation results are reported with P < 0.05 whole-brain familywise error (FWE)–corrected significance. Beta estimates were additionally extracted, only for visualization of the activity of the ventral striatum (anatomical region-of-interest from the Automatic Anatomic Labeling-90 atlas) during conditions (
Questionnaire data were analyzed using SPSS 27 (IBM).
