Local discriminability determines the strength of holistic processing for faces in the fusiform face area

Abstract

Recent evidence suggests that the Fusiform Face Area (FFA) is not exclusively dedicated to the interactive processing of face features, but also contains neurons sensitive to local features. This suggests the existence of both interactive and local processing modes, consistent with recent behavioral findings that the strength of interactive feature processing (IFP) engages most strongly when similar features need to be disambiguated. Here we address whether the engagement of the FFA into interactive versus featural representational modes is governed by local feature discriminability. We scanned human participants while they matched target features within face pairs, independently of the context of distracter features. IFP was operationalized as the failure to match the target without being distracted by distracter features. Picture-plane inversion was used to disrupt IFP while preserving input properties. We found that FFA activation was comparably strong, irrespective of whether similar target features were embedded in dissimilar contexts(i.e., inducing robust IFP) or dissimilar target features were embedded in the same context (i.e., engaging local processing). Second, inversion decreased FFA activation to faces most robustly when similar target features were embedded in dissimilar contexts, indicating that FFA engages into IFP mainly when features cannot be disambiguated at a local level. Third, by means of Spearman rank correlation tests, we show that the local processing of feature differences in the FFA is supported to a large extent by the Occipital Face Area, the Lateral Occipital Complex, and early visual cortex, suggesting that these regions encode the local aspects of face information. The present findings confirm the co-existence of holistic and featural representations in the FFA. Furthermore, they establish FFA as the main contributor to the featural/holistic representational mode switches determined by local discriminability.

Keywords: FFA; face perception; feature discriminability; holistic; interactive.

Figure 1

Example of face pairs in the congruency task. Subjects had to discriminate a target feature (same/different matching task), i.e., the eyes and eyebrows, while ignoring the context of other features (i.e., distracters: nose and mouth). In congruent conditions, both the target and distracter features lead to an identical decision, while they call for opposite responses in incongruent conditions.

Figure 2

(A) Matching accuracy. Error bars represent standard error of the means. (B) The size of the congruency effect is plotted for upright and inverted faces as a function of target feature similarity.

Figure 3

Activation peak grand averages in bilateral FFA, OFA, LOC, and EVC ROIs are shown in congruent-same, congruent-different, incongruent-same, and incongruent-different conditions, at upright and inverted orientation separately. Activation peaks (error bars represent mean intra-subject variance) are expressed in percent signal change (PSC) relative to fixation baseline activity (baseline interval: from −2 TR to cue onset).

Figure 4

The functional relationships between FFA on the one side and the other ROIs (OFA, LOC, and EVC) on the other side were explored by means of two-sided Spearman’s rho correlation analyses (alpha level corrected for multiple analyses: 0.002). Spearman rho coefficients are color-coded for each condition separately. We performed a standard two-sided test on Spearman’s rho to determine whether inter-ROI correlations of activation were significantly different from expected by chance. Correlation coefficients differed significantly from 0 at p < 0.002 except when labeled “n.s.”