Abstract

Spatial frequency (SF) components encode a portion of the affective value expressed in face images. The aim of this study was to estimate the relative weight of specific frequency spectrum bandwidth on the discrimination of anger and fear facial expressions. The general paradigm was a classification of the expression of faces morphed at varying proportions between anger and fear images in which SF adaptation and SF subtraction are expected to shift classification of facial emotion. A series of three experiments was conducted. In Experiment 1 subjects classified morphed face images that were unfiltered or filtered to remove either low (<8 cycles/face), middle (12–28 cycles/face), or high (>32 cycles/face) SF components. In Experiment 2 subjects were adapted to unfiltered or filtered prototypical (non-morphed) fear face images and subsequently classified morphed face images. In Experiment 3 subjects were adapted to unfiltered or filtered prototypical fear face images with the phase component randomized before classifying morphed face images. Removing mid frequency components from the target images shifted classification toward fear. The same shift was observed under adaptation condition to unfiltered and low- and middle-range filtered fear images. However, when the phase spectrum of the same adaptation stimuli was randomized, no adaptation effect was observed. These results suggest that medium SF components support the perception of fear more than anger at both low and high level of processing. They also suggest that the effect at high-level processing stage is related more to high-level featural and/or configural information than to the low-level frequency spectrum.

Highlights

  • Face perception includes the integration of complex visual input across a spectrum of varying spatial frequencies (SFs) (Sowden and Schyns, 2006)

  • The opposite effect is observed when low frequency components are removed from the face images, where there is an increase in the reported perception of fear

  • GENERAL DISCUSSION The experiments reported in this study examined the effect of specific SF bandwidth manipulation on the classification of facial expressions under two alternative paradigms: SF subtraction and SF adaptation

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Summary

Introduction

Face perception includes the integration of complex visual input across a spectrum of varying spatial frequencies (SFs) (Sowden and Schyns, 2006). Low spatial frequency (LSF) information is encoded through faster, more direct networks in subcortical and early visual areas and communicates rapid, coarse signals concerning the configuration or spatial relationship between facial features (for an overview, see Ruiz-Soler and Beltran, 2006). Subsequent outputs from these pathways typically converge in higher-level regions, including the amygdala, fusiform gyrus, and orbitofrontal cortex (Vuilleumier et al, 2003; Bar et al, 2006; Rotshtein et al, 2007).

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