Timing of repetition suppression of event-related potentials to unattended objects

Abstract

Current theories of object perception emphasize the automatic nature of perceptual inference. Repetition suppression (RS), the successive decrease of brain responses to repeated stimuli, is thought to reflect the optimization of perceptual inference through neural plasticity. While functional imaging studies revealed brain regions that show suppressed responses to the repeated presentation of an object, little is known about the intra-trial time course of repetition effects to everyday objects. Here, we used event-related potentials (ERPs) to task-irrelevant line-drawn objects, while participants engaged in a distractor task. We quantified changes in ERPs over repetitions using three general linear models that modeled RS by an exponential, linear, or categorical "change detection" function in each subject. Our aim was to select the model with highest evidence and determine the within-trial time-course and scalp distribution of repetition effects using that model. Model comparison revealed the superiority of the exponential model indicating that repetition effects are observable for trials beyond the first repetition. Model parameter estimates revealed a sequence of RS effects in three time windows (86-140, 322-360, and 400-446 ms) and with occipital, temporoparietal, and frontotemporal distribution, respectively. An interval of repetition enhancement (RE) was also observed (320-340 ms) over occipitotemporal sensors. Our results show that automatic processing of task-irrelevant objects involves multiple intervals of RS with distinct scalp topographies. These sequential intervals of RS and RE might reflect the short-term plasticity required for optimization of perceptual inference and the associated changes in prediction errors and predictions, respectively, over stimulus repetitions during automatic object processing.

Keywords: event-related potential; general linear modeling; object recognition; predictive coding; repetition enhancement.

Figure 1

Paradigm and 1st‐level design matrix. (a) We used a simple stimulus repetition paradigm where line drawings of everyday objects were repeated 6–10 times. Between the 6th–10th presentations, a change in the viewing angle was introduced, after which the original picture was repeated two times. Note that our analysis focused on the first six presentations where stimuli did not change over repetitions. (b) Covariates plotted over the 1st‐level design matrix. Image number corresponds to images for mean event‐related potentials (ERPs) to the 1–6 presentations in four blocks (x axis). ERPs were modeled with a parametric modulator and a main regressor for each block (y axis right). The exponential function (mean centered) used for modeling repetition effects for the first block is plotted in blue over the design matrix (y axis left). (c and d) Covariates plotted over the 1st‐level design matrix for the change detection and the linear models, respectively.

Figure 2

Histograms of ΔLME. (a) Histograms over the voxels within a mask defined by the “logical AND” conjunction of significant voxels under any of the three models, and (b) over all voxels in the whole 3D space‐time volume. LME: log model evidence.

Figure 3

Statistical parametric maps (SPMs) and time course of repetition effects. (a) Main effect of stimulus repetition (pooled across the four experimental blocks), F‐values thresholded at p < 0.05 family‐wise error (whole‐scalp corrected), overlaid on the contrast images. Asterisks mark scalp locations for electrodes shown in (b) and (c). Numbers show activations as indicated in Table 2. Panels from top to bottom show observed intervals of repetition suppression (RS) in the 86–140 ms, repetition enhancement (RE) in the 320–340 ms, and RS in the 322–360 ms and 400–446 ms time windows, with occipital, occipitotemporal, temporoparietal, and frontotemporal distribution, respectively. Note that activation #4 is not plotted separately as it showed a similar dynamics and temporal topography to that of activation #2 peaking at 346 ms. (b) Box plots of event‐related potential (ERP) amplitudes for each stimulus presentation. Red lines represent the mean; points (subjects) shown together with the 95% confidence interval of the mean (1.96 SEM) in red and a 1 SD interval in blue. Time windows of significant repetition effects are indicated in each subplot at the electrode sites closest to corresponding cluster maxima. (c) Grand mean ERP waveforms elicited by the 1st and 6th stimulus presentation with 95% confidence interval are shown for illustration purposes. Note that statistics were carried out on 3D scalp space‐time parameter estimates which were based on ERPs for the 1st, 2nd, 3rd, 4th, 5th, and 6th stimulus presentation. Black horizontal bars mark intervals of significant repetition effects.