DOI: 10.5061/dryad.x95x69pj3
title: Dataset: Long term fMRI adaptation depends on adapter response in face-selective cortex

description: Repetition suppression (RS) reflects a neural attenuation during repeated
 stimulation. We used fMRI and the subsequent memory paradigm to test the
 predictive coding hypothesis for RS during visual memory processing by
 investigating the interaction between RS and differences due to memory in
 category-selective cortex (FFA, pSTS, PPA, and RSC). Fifty-six
 participants encoded face and house stimuli twice, followed by an
 immediate and delayed (48 h) recognition memory assessment. Linear Mixed
 Model analyses with repetition, subsequent recognition performance, and
 their interaction as fixed effects revealed that absolute RS during
 encoding interacts with probability of future remembrance in
 face-selective cortex. This effect was not observed for relative RS, i.e.
 when controlled for adapter-response. The findings also reveal an
 association between adapter response and RS, both for short and
 long term (48h) intervals, after controlling for the mathematical
 dependence between both measures. These combined findings are challenging
 for predictive coding models of visual memory and are more compatible with
 adapter-related and familiarity accounts.
description: Subjects were recruited via advertisements for participation in
 an fMRI memory experiment. 56 healthy subjects
 participated in our study. The final sample for the main analyses
 consisted of fifty-four subjects [13 males (24 %); mean age ± SD = 34 ± 11
 years, range 21-64].  <strong>Sequence &
 imaging parameters: </strong>Brain imaging was performed on a 3T
 Siemens Achieva scanner, using a 32-channel head coil. Acquisition
 parameters for 45 participants consisted of a high-resolution
 T1-weighted anatomical image (voxel size: 0.98 x 0.98 x 1.20 mm3) using a
 3D turbo field echo sequence (TR:9.6 ms; TE:4.6 ms; matrix size:256 x 256;
 182 slices); a T2*-weighted GE-EPI sequence with the following parameters:
 TR: 2000 ms; TE: 30 ms; matrix size: 80 x 78; FOV: 230 mm; flip angle:
 90˚; slice thickness: 4 mm; no gap; axial slices: 38. For the other 9
 participants, a similar high-resolution T1-weighted anatomical image was
 acquired (voxel size: 1.10 x 1.10 x 1.10 mm3) using a 3D turbo field echo
 sequence (TR:6.9 ms; TE:3.2 ms; matrix size:256 x 256; 208 slices) and a
 T2*-weighted GE-EPI sequence with the following parameters: TR: 2000 ms;
 TE: 30 ms; matrix size: 80 x 78; FOV: 230 mm; flip angle: 90˚; slice
 thickness: 4 mm; no gap; axial slices: 36. Scan acquisition setting was
 included as a nuisance variable in all brain imaging analyses.
 <strong>Preprocessing software: </strong>Imaging data
 were analyzed using BrainVoyager 21.4. Pre-processing of functional data
 consisted of slice scan time correction, temporal high-pass filtering to
 remove low-frequency drifts, realignment to the first image to compensate
 for head motion, and spatial smoothing with a Gaussian filter of 4mm
 FWHM. Functional data were co-registered with the anatomical images and
 normalized into Talairach coordinate space. 
 <strong>Model type and settings: </strong>At first
 level, the statistical analysis was based on the general linear model
 (GLM) with repetition (no, yes), category (face, house), and subsequent
 memory performance (Not, probably yes, and definitely yes) as factors. The
 ‘definitely not’ and ‘probably not’ conditions were pooled as 25
 participants did not use both categories during their experiment in one of
 both categories. Null-events were modelled explicitly. At second level, a
 random effects GLM was performed. <strong>Linear
 Mixed Models </strong>were estimated with the beta-values as
 dependent variable with repetition (2 levels: adapter and test), memory
 performance (3 levels: forgotten, probably remembered or definitely
 remembered), and repetition x memory performance as fixed effects using an
 unstructured variance-covariance matrix (based on a Likelihood test).
 These analyses were performed for every ROI separately. We applied
 Bonferroni-correction for multiple comparisons (‘forgotten’ vs ‘probably
 remembered’, ‘forgotten’ vs ‘definitely remembered’, and ‘probably
 remembered’ vs ‘definitely remembered’). We only focused on
 within-performance category differences. In addition to the main effects
 of performance and repetition, we performed post-hoc analyses to study the
 interaction between performance and region and the interaction between
 repetition and region. 
description: One participant was excluded due to technical failure during fMRI
 acquisition and one participant was excluded due to indication of
 pathology.  The statistical threshold for
 ROI-definition at subject level was set at
 P<sub>height</sub>&lt;.005. Two participants did not show
 any significant results for the right FFA, five for the left FFA, one for
 the right pSTS, two for the left pSTS, and four for the left RSC. These
 participants were excluded from the respective analyses.