ANCOVA: VTA/SN RSFC change + CDMB - control-experimental_CDMB

Contributed by stefaniemeliss on Dec. 19, 2022

Collection: Motivated Incidental Consolidation (MIC)

Description: The main analysis focused on FC between aHPC and VTA/SN. However, whole-brain seed-based RSFC analyses were conducted for exploratory purposes. For this, data from pre- and post-learning rest phases from each subject were loaded into ‘3dGroupInCorr’, specifying aHPC and VTA/SN as seeds, respectively, to compute two seed-based FC maps, one for each ROI as seed, while controlling for GCOR to further account for sources of noise at group level, creating two seed-based maps per subject where the value in each voxel represents the Fisher’s z-transformed correlation coefficient with the averaged time series of each seed, respectively. Individual Fisher’s z-transformed maps were extracted for the pre- and post-learning resting phase to compute the RSFC as the difference between post- and pre-learning rest. These individual difference maps were submitted to ANCOVA models, specifying the behavioural measures of learning as covariates in separate models to identify voxels showing a significant difference in slopes with respect to the covariate between the groups. COVARIATES: total # items = the total number of items encoded; CDMB = curiosity-driven memory benefit; The output image has 12 volumes: (1) mean difference in arctanh(correlation), (2) Z score of t-statistic for above difference, (3) difference in slope of arctanh(correlation) vs COVARIATE, (4) Z score of t-statistic for above difference, (5) mean of arctanh(correlation) for control group, (6) Z score of t-statistic for above mean, (7) slope of arctanh(correlation) vs COVARIATE for control group, (8) Z score of t-statistic for above slope, (9) mean of arctanh(correlation) for experimental group, (10) Z score of t-statistic for above mean, (11) slope of arctanh(correlation) vs COVARIATE for experimental group, (12) Z score of t-statistic for above slope

Task View 3D View