A Memory Computational Basis for the Other-Race Effect

Abstract

People often recognize and remember faces of individuals within their own race more easily than those of other races. While behavioral research has long suggested that the Other-Race Effect (ORE) is due to extensive experience with one’s own race group, the neural mechanisms underlying the effect have remained elusive. Predominant theories of the ORE have argued that the effect is mainly caused by processing disparities between same and other-race faces during early stages of perceptual encoding. Our findings support an alternative view that the ORE is additionally shaped by mnemonic processing mechanisms beyond perception and attention. Using a “pattern separation” paradigm based on computational models of episodic memory, we report evidence that the ORE may be driven by differences in successful memory discrimination across races as a function of degree of interference or overlap between face stimuli. In contrast, there were no ORE-related differences on a comparable match-to-sample task with no long-term memory load, suggesting that the effect is not simply attributable to visual and attentional processes. These findings suggest that the ORE may emerge in part due to “tuned” memory mechanisms that may enhance same-race, at the expense of other-race face detection.

Human face-selective cortex does not distinguish between members of a racial outgroup

“…Third, we adopted a subjectspecific ROI selection approach and included exploratory analyses of female faces. Thus, our pre-registered study provides a substantial extension of the existing literature by (i) conceptually replicating prior work (Hughes et al, 2019), thereby bolstering our confidence in the reliability of this effect, and (ii) providing further evidence for representation-based accounts of the otherrace homogeneity effect (see also Yaros et al, 2019). Notably, neither of these findings speak to the developmental origins of the effect.…”

Pattern Separation Contributes to Categorical Face Perception

“…Indeed, BL's results place him at approximately the 34th (i.e., average) percentile, 95% percentile CI [22,47]. Additionally, the steepness of BL's slope at this threshold was within normal limits, t(34) = -0.59, p = .281 (onetailed), 95% percentile CI [17,41]. Clearly, BL and controls showed categorical nonlinearity of response to a continuous linear change in the famous faces continuum 1 .…”

“…For example, the CP task begins with the repeated presentation of morphed faces. In theory, some of these faces with overlapping features (at least the more recognizable ones nearest the endpoints) are sparsely coded by pattern separation processes 17 . The orthogonal episodic representations of each morphed face are then projected from the DG onto the CA3 hippocampal cell layer via the mossy fiber pathway 10,11 .…”

“…These may have helped to shift the representation of faces from being perceptually image-based to being conceptually viewinvariant 38 . Consequently, the faces that he could name using person-identity information offered less interference, facilitating discrimination in between-category decision-making, the same way that pattern separation of morphed faces varies depending upon the relative familiarity and invariance of the faces involved in any particular trial 16,17 .…”

“…The peak RTs correspond to those perceptual decisions which take the longest to resolve. In all likelihood, these decisions rely on the ability to see the prototype masked within the morph, an ability which recruits face memory recognition processes within the dentate gyrus of the hippocampus 14,16,17 .…”