Cultural Differences in the Time Course of Configural and Featural Processing for Own-race Faces

Rigid facial motion at study facilitates the holistic processing of own-race faces during the structural encoding stage

Holistic processing is a fundamental element of face-recognition studies. Some behavioral studies have investigated the impact of rigid facial motion on holistic face processing, yet it is still unclear how rigid motion affects the time course of holistic face processing for different face races. The current study investigated this issue, using the composite face effect (CFE) as a direct measure of holistic processing. Participants were asked to match the identity of the top half of a static composite face with the study face during the test stage, where the study face was either static or rigidly-moving. ERP results showed that rigidly-moving study faces elicited a larger CFE relative to static study faces in the N170 component when recognizing own-race faces. The amplitude of P1, N170 and P2 components indicated that rigid motion facilitated holistic face processing, with differences observed between the hemispheres over time. Specifically, the CFE was only observed after exposure to rigidly-moving faces in the P1 and P2 components of the right hemisphere. Additionally, a greater CFE was observed following exposure to rigidly-moving faces compared to static faces, particularly in the N170 component of the left hemisphere. This study suggests that holistic processing is a fundamental aspect of face perception that applies to both static and moving faces, not just static ones. Furthermore, rigid facial motion improves holistic processing of own-race faces during the structural encoding stage. These findings provide evidence of distinct neural mechanisms underlying the holistic processing of static and moving faces.

The speed of race

When asked to categorize faces according to 'race', people typically categorize other-race faces faster than faces belonging to their own race. This 'Other Race Categorization Advantage' is thought to reflect enhanced sensitivity to early visual signals characteristic of other-race faces, and can manifest within 200 ms of face presentation. However, recent research has highlighted the importance of signal intensity in this effect, where visual-degradation of the face images significantly enhances the effect and exposes a behavioural threshold at very low levels of visual quality where other-race visual signals are able to be perceived while same-race signals are not. The current study investigated the effect of signal intensity in race categorization processes in the brain through electroencephalography and in accuracy/reaction times. While replicating the previously observed enhancement of the other-race categorization advantage, we also found enhanced sensitivity to other-race faces in early P1 peaks, as well as later N170 and N250 peaks. These effects, however, related to the varying levels of signal intensity in the face stimuli, suggesting that race categorization may involve different types of perceptual and neural processes rather than one discrete process. The speed at which race is perceived depends on the intensity of the face signal.

The overgeneralization of pain-related fear in individuals with higher pain sensitivity: A behavioral and event-related potential study

Fear generalization contributes to the development and maintenance of pain. Pain sensitivity has been proposed to predict the strength of fear responses to aversive stimuli. However, whether individual variation in pain sensitivity affects pain-related fear generalization and its underlying cognitive processing remains unclear. To address this gap, we recorded behavioral and event-related potential (ERP) data among 22 high pain sensitivity (HPS) and 22 low pain sensitivity (LPS) healthy adults when exposed to a fear generalization paradigm. The behavioral results indicate that the HPS group displayed higher unconditioned stimulus expectancy and greater fear, arousal, and anxiety ratings to conditioned stimulus and generalization stimulus than the LPS group (all p values < 0.05). The ERP results showed that the HPS group exhibited a larger late positive potential evoked by GS2, GS3 and CS- (all p < 0.005) but a smaller N1 evoked by all CS and GSs (all p values < 0.05) relative to the LPS group. These findings suggest that individuals with a high level of pain sensitivity allocate more attention resources to pain-related threatening stimuli, which contributes to an overgeneralization of pain-related fear.

Face motion form at learning influences the time course of face spatial frequency processing during test

Studies that use static faces suggest that facial processing follows a coarse-to-fine sequence; i.e., holistic precedes featural processing, due to low and high spatial frequencies (LSF, HSF) transmitting holistic/global and featural/local information respectively. Although recent studies have focused on the role of facial movement in holistic facial processing, it is unclear whether moving faces have the same processing mechanism as static ones, especially in the time course of processing. The current study uses the event-related potential technique to investigate this issue by manipulating the facial format at study and face spatial frequency during the test. ERP results showed that the P1 amplitude was increased by LSF faces relative to HSF ones, using both moving and static study faces, with the former larger than the latter. The N170 amplitude was more sensitive to HSF than LSF faces when only static study faces were used, while the P2 amplitude was more sensitive to LSF faces regardless of the facial study format. The above results were not modulated by the race of the faces. These results favor the view that regardless of face race, moving study faces promote holistic processing during the earliest stage of face recognition. Furthermore, holistic processing is observed to be the same for both static and moving study faces at a later stage associated with more in-depth processing. It is evident that facial motion should be factored into further studies of face recognition, given the distinctions between holistic and featural processing for moving and static study faces.

Neural timing of the other-race effect across the lifespan: A review

Face race influences the way we process faces, so that faces of a different ethnic group are processed for identity less efficiently than faces of one's ethnic group - a phenomenon known as the Other-Race Effect (ORE). Although widely replicated, the ORE is still poorly characterized in terms of its development and the underlying mechanisms. In the last two decades, the Event-Related Potential (ERP) technique has brought insight into the mechanisms underlying the ORE and has demonstrated potential to clarify its development. Here, we review the ERP evidence for a differential neural processing of own-race and other-race faces throughout the lifespan. In infants, race-related processing differences emerged at the N290 and P400 (structural encoding) stages. In children, race affected the P100 (early processing, attention) perceptual stage and was implicitly encoded at the N400 (semantic processing) stage. In adults, processing difficulties for other-race faces emerged at the N170 (structural encoding), P200 (configuration processing) and N250 (accessing individual representations) perceptual stages. Early in processing, race was implicitly encoded from other-race faces (N100, P200 attentional biases) and in-depth processing preferentially applied to own-race faces (N200 attentional bias). Encoding appeared less efficient (Dm effects) and retrieval less recollection-based (old/new effects) for other-race faces. Evidence admits the contribution of perceptual, attentional, and motivational processes to the development and functioning of the ORE, offering no conclusive support for perceptual or socio-cognitive accounts. Cross-racial and non-cross-racial studies provided convergent evidence. Future research would need to include less represented ethnic populations and the developmental population.

The role of task demands in racial face encoding

People more accurately remember faces of their own racial group compared to faces of other racial groups; this phenomenon is called the other-race effect. To date, numerous researchers have devoted themselves to exploring the reasons for this other-race effect, and they have posited several theoretical explanations. One integrated explanation is the categorization-individuation model, which addresses two primary ways (categorization and individuation) of racial face processing and emphasizes the emergence of these two ways during the encoding stage. Learning-recognition and racial categorization tasks are two classical tasks used to explore racial face processing. Event-related potentials can facilitate investigation of the encoding differences of own- and other-race faces under these two typical task demands. Unfortunately, to date, results have been mixed. In the current study, we investigated whether categorization and individuation differ for own- and other-race faces during the encoding stage by using racial categorization and learning-recognition tasks. We found that task demands not only influence the encoding of racial faces, but also have a more profound effect in the encoding stage of recognition tasks for other-race faces. More specifically, own-race faces demonstrate deeper structural encoding than other-race faces, with less attentional involvement. Moreover, recognitions tasks might ask for more individual-level encoding, requiring more attentional resources in the early stage that may be maintained until relatively late stages. Our results provide some evidence concerning task selection for future racial face studies and establish a groundwork for a unified interpretation of racial face encoding.

The Time Sequence of Face Spatial Frequency Differs During Working Memory Encoding and Retrieval Stages

Previous studies have found that P1 and P2 components were more sensitive to configural and featural face processing, respectively, when attentional resources were sufficient, suggesting that face processing follows a coarse-to-fine sequence. However, the role of working memory (WM) load in the time course of configural and featural face processing is poorly understood, especially whether it differs during encoding and retrieval stages. This study employed a delayed recognition task with varying WM load and face spatial frequency (SF). Our behavioral and ERP results showed that WM load modulated face SF processing. Specifically, for the encoding stage, P1 and P2 were more sensitive to broadband SF (BSF) faces, while N170 was more sensitive to low SF (LSF) and BSF faces. For the retrieval stage, P1 on the right hemisphere was more sensitive to BSF faces relative to HSF faces, N170 was more sensitive to LSF faces than HSF faces, especially under the load 1 condition, while P2 was more sensitive to high SF (HSF) faces than HSF faces, especially under load 3 condition. These results indicate that faces are perceived less finely during the encoding stage, whereas face perception follows a coarse-to-fine sequence during the retrieval stage, which is influenced by WM load. The coarse and fine information were processed especially under the low and high load conditions, respectively.

Configural but Not Featural Face Information Is Associated With Automatic Processing

Configural face processing precedes featural face processing under the face-attended condition, but their temporal sequence in the absence of attention is unclear. The present study investigated this issue by recording visual mismatch negativity (vMMN), which indicates the automatic processing of visual information under unattended conditions. Participants performed a central cross size change detection task, in which random sequences of faces were presented peripherally, in an oddball paradigm. In Experiment 1, configural and featural faces (deviant stimuli) were presented infrequently among original faces (standard stimuli). In Experiment 2, configural faces were presented infrequently among featural faces, or vice versa. The occipital-temporal vMMN emerged in the 200–360 ms latency range for configural, but not featural, face information. More specifically, configural face information elicited a substantial vMMN component in the 200–360 ms range in Experiment 1. This result was replicated in the 320–360 ms range in Experiment 2, especially in the right hemisphere. These results suggest that configural, but not featural, face information is associated with automatic processing and provides new electrophysiological evidence for the different mechanisms underlying configural and featural face processing under unattended conditions.