Spatial attention modulates the temporal sequence of hemispheric asymmetry in configural and featural face processing

Asymmetries in event-related potentials part 1: A systematic review of face processing studies

The human brain shows distinct lateralized activation patterns for a range of cognitive processes. One such function, which is thought to be lateralized to the right hemisphere (RH), is human face processing. Its importance for social communication and interaction has led to a plethora of studies investigating face processing in health and disease. Temporally highly resolved methods, like event-related potentials (ERPs), allow for a detailed characterization of different processing stages and their specific lateralization patterns. This systematic review aimed at disentangling some of the contradictory findings regarding the RH specialization in face processing focusing on ERP research in healthy participants. Two databases were searched for studies that investigated left and right electrodes while participants viewed (mostly neutral) facial stimuli. The included studies used a variety of different tasks, which ranged from passive viewing to memorizing faces. The final data selection highlights, that strongest lateralization to the RH was found for the N170, especially for right-handed young male participants. Left-handed, female, and older participants showed less consistent lateralization patterns. Other ERP components like the P1, P2, N2, P3, and the N400 were overall less clearly lateralized. The current review highlights that many of the assumed lateralization patterns are less clear than previously thought and that the variety of stimuli, tasks, and EEG setups used, might contribute to the ambiguous findings.

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.

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.

Reconfiguration of Cortical Brain Network from Searching to Spotting for Dynamic Visual Targets

BACKGROUND

Detecting dynamic targets from complex visual scenes is an important problem in real world. However, the cognitive mechanism accounting for dynamic visual target detection remains unclear.

NEW METHOD

Herein, we aim to explore the cognitive process of dynamic visual target detection from searching to spotting and provide more concrete evidence for cognitive studies related to target detection. Cortical source responses with high spatiotemporal resolution were reconstructed from scalp EEG signals. Then, time-varying cortical networks were built using adaptive directed transfer function to explore the cognitive processes while detecting the dynamic visual target.

RESULTS

The experimental results demonstrated that the dynamic visual target detection enhanced the activation in both the visual and attention networks. Specially, the information flow from the middle occipital gyrus (MOG) mainly contributed to the position function, whereas the activation of the prefrontal cortex (PFC) reflected spatial attention maintenance.

CONCLUSION

The left "frontal-central-parietal" network played as a leading information source in dynamic target detection tasks. These findings provide new insights into cognitive processes of dynamic visual target detection.

DATA AVAILABILITY STATEMENT

The datasets in this study are available on request to the corresponding author.

The spatiotemporal characteristics of N170s for faces and words: A meta-analysis study

N170 is a negative event-related potential (ERP) component in response to visual stimuli, such as faces. It remains controversial whether N170 reflects the specific processing of faces or can also be elicited by objects of expertise (e.g., words). In this research, we conducted a meta-analysis for the spatiotemporal characteristics of N170 of face and word stimuli from 24 studies in which both stimuli were presented for each subject. We observed that (1) both face and word stimuli can elicit conspicuous N170s and that there was no difference between the amplitude of face-N170 and word-N170; (2) there is no difference in the latencies between the two N170s; and (3) both N170s are distributed in the occipitotemporal regions but with a reversed hemispheric distribution pattern-face-N170 is more negative in the right than left occipitotemporal regions, while word-N170 is the opposite. These results showed that the face- and word-N170s are qualitatively the same but have different hemispheric lateralization advantages-N170 might be a general neural index of the expertise-dependent object-recognition process in occipitotemporal regions.

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

Previous research suggests that East Asians pay more attention than Caucasian Westerners to configural information in faces, while the latter group pays more attention to featural information. However, it is unclear whether this cultural variation in attention produces a different time course of the processing bias for configural and featural information. This was examined using event-related potentials in a spatial attention paradigm. Chinese and Westerners were instructed to attend to the locations of two face images or houses. Although the race-related difference was absent in behavioral performance and N170 component, Chinese participants exhibited a configural processing bias on P1 component in the case of both own- and other-race faces and a featural processing bias on P2 component for own-race faces. In contrast, Westerners exhibited a featural processing bias for own-race faces and a configural processing bias for other-race faces on P1 component, whereas a configural processing bias was observed on P2 component for both own- and other-race faces. These results demonstrate that there are important differences between East Asians and Westerners in their relative preferences for configural versus featural processing of own-race faces, but not other-race faces. The relative roles of configural and featural information processing for faces are thus dependent on both who is looking (the culture or race of the observer) and what they are looking at (the race of the face): Easterners enjoy an early global/configural processing bias and a late local/featural processing bias for own-race faces, while Westerners benefit from an early local/featural processing bias and a late global/configural processing bias for own-race faces; both of the groups have an early and late global/configural processing bias for other-race faces.