Steady state visually evoked potential correlates of static and dynamic emotional face processing

While the neural regions associated with facial identity recognition are considered to be well defined, the neural correlates of non-moving and moving images of facial emotion processing are less clear. This study examined the brain electrical activity changes in 26 participants (14 males M = 21.64, SD = 3.99; 12 females M = 24.42, SD = 4.36), during a passive face viewing task, a scrambled face task and separate emotion and gender face discrimination tasks. The steady state visual evoked potential (SSVEP) was recorded from 64-electrode sites. Consistent with previous research, face related activity was evidenced at scalp regions over the parieto-temporal region approximately 170 ms after stimulus presentation. Results also identified different SSVEP spatio-temporal changes associated with the processing of static and dynamic facial emotions with respect to gender, with static stimuli predominately associated with an increase in inhibitory processing within the frontal region. Dynamic facial emotions were associated with changes in SSVEP response within the temporal region, which are proposed to index inhibitory processing. It is suggested that static images represent non-canonical stimuli which are processed via different mechanisms to their more ecologically valid dynamic counterparts.

Dynamics of contour, object and face processing in the human visual cortex

The neural basis of visual perception can be understood only when the sequence of cortical activity underlying successful recognition is known. The early steps in this processing chain, from retina to the primary visual cortex, are highly local, and the perception of more complex shapes requires integration of the local information. In Study I of this thesis, the progression from local to global visual analysis was assessed by recording cortical magnetoencephalographic (MEG) responses to arrays of elements that either did or did not form global contours. The results demonstrated two spatially and temporally distinct stages of processing: The first, emerging 70 ms after stimulus onset around the calcarine sulcus, was sensitive to local features only, whereas the second, starting at 130 ms across the occipital and posterior parietal cortices, reflected the global configuration. To explore the links between cortical activity and visual recognition, Studies II III presented subjects with recognition tasks of varying levels of difficulty. The occipito-temporal responses from 150 ms onwards were closely linked to recognition performance, in contrast to the 100-ms mid-occipital responses. The averaged responses increased gradually as a function of recognition performance, and further analysis (Study III) showed the single response strengths to be graded as well. Study IV addressed the attention dependence of the different processing stages: Occipito-temporal responses peaking around 150 ms depended on the content of the visual field (faces vs. houses), whereas the later and more sustained activity was strongly modulated by the observers attention. Hemodynamic responses paralleled the pattern of the more sustained electrophysiological responses. Study V assessed the temporal processing capacity of the human object recognition system. Above sufficient luminance, contrast and size of the object, the processing speed was not limited by such low-level factors. Taken together, these studies demonstrate several distinct stages in the cortical activation sequence underlying the object recognition chain, reflecting the level of feature integration, difficulty of recognition, and direction of attention.

Estimation of Pose and Illuminant Direction for Face Processing

In this paper three problems related to the analysis of facial images are addressed: the illuminant direction, the compensation of illumination effects and, finally, the recovery of the pose of the face, restricted to in-depth rotations. The solutions proposed for these problems rely on the use of computer graphics techniques to provide images of faces under different illumination and pose, starting from a database of frontal views under frontal illumination.

Electrophysiological constituents of the P100 and N170 ERP complex: De-constructing of face processing using independent component analysis and robust estimation.

The initial timing of face-specific effects in event-related potentials (ERPs) is a point of contention in face processing research. Although effects during the time of the N170 are robust in the literature, inconsistent effects during the time of the P100 challenge the interpretation of the N170 as being the initial face-specific ERP effect. The interpretation of the early P100 effects are often attributed to low-level differences between face stimuli and a host of other image categories. Research using sophisticated controls for low-level stimulus characteristics (Rousselet, Husk, Bennett, & Sekuler, 2008) report robust face effects starting at around 130 ms following stimulus onset. The present study examines the independent components (ICs) of the P100 and N170 complex in the context of a minimally controlled low-level stimulus set and a clear P100 effect for faces versus houses at the scalp. Results indicate that four ICs account for the ERPs to faces and houses in the first 200ms following stimulus onset. The IC that accounts for the majority of the scalp N170 (icNla) begins dissociating stimulus conditions at approximately 130 ms, closely replicating the scalp results of Rousselet et al. (2008). The scalp effects at the time of the P100 are accounted for by two constituent ICs (icP1a and icP1b). The IC that projects the greatest voltage at the scalp during the P100 (icP1a) shows a face-minus-house effect over the period of the P100 that is less robust than the N 170 effect of icN 1 a when measured as the average of single subject differential activation robustness. The second constituent process of the P100 (icP1b), although projecting a smaller voltage to the scalp than icP1a, shows a more robust effect for the face-minus-house contrast starting prior to 100 ms following stimulus onset. Further, the effect expressed by icP1 b takes the form of a larger negative projection to medial occipital sites for houses over faces partially canceling the larger projection of icP1a, thereby enhancing the face positivity at this time. These findings have three main implications for ERP research on face processing: First, the ICs that constitute the face-minus-house P100 effect are independent from the ICs that constitute the N170 effect. This suggests that the P100 effect and the N170 effect are anatomically independent. Second, the timing of the N170 effect can be recovered from scalp ERPs that have spatio-temporally overlapping effects possibly associated with low-level stimulus characteristics. This unmixing of the EEG signals may reduce the need for highly constrained stimulus sets, a characteristic that is not always desirable for a topic that is highly coupled to ecological validity. Third, by unmixing the constituent processes of the EEG signals new analysis strategies are made available. In particular the exploration of the relationship between cortical processes over the period of the P100 and N170 ERP complex (and beyond) may provide previously unaccessible answers to questions such as: Is the face effect a special relationship between low-level and high-level processes along the visual stream?

Electrophysiological investigations of the timing of face processing

As important social stimuli, faces playa critical role in our lives. Much of our interaction with other people depends on our ability to recognize faces accurately. It has been proposed that face processing consists of different stages and interacts with other systems (Bruce & Young, 1986). At a perceptual level, the initial two stages, namely structural encoding and face recognition, are particularly relevant and are the focus of this dissertation. Event-related potentials (ERPs) are averaged EEG signals time-locked to a particular event (such as the presentation of a face). With their excellent temporal resolution, ERPs can provide important timing information about neural processes. Previous research has identified several ERP components that are especially related to face processing, including the N 170, the P2 and the N250. Their nature with respect to the stages of face processing is still unclear, and is examined in Studies 1 and 2. In Study 1, participants made gender decisions on a large set of female faces interspersed with a few male faces. The ERP responses to facial characteristics of the female faces indicated that the N 170 amplitude from each side of the head was affected by information from eye region and by facial layout: the right N 170 was affected by eye color and by face width, while the left N 170 was affected by eye size and by the relation between the sizes of the top and bottom parts of a face. In contrast, the P100 and the N250 components were largely unaffected by facial characteristics. These results thus provided direct evidence for the link between the N 170 and structural encoding of faces. In Study 2, focusing on the face recognition stage, we manipulated face identity strength by morphing individual faces to an "average" face. Participants performed a face identification task. The effect of face identity strength was found on the late P2 and the N250 components: as identity strength decreased from an individual face to the "average" face, the late P2 increased and the N250 decreased. In contrast, the P100, the N170 and the early P2 components were not affected by face identity strength. These results suggest that face recognition occurs after 200 ms, but not earlier. Finally, because faces are often associated with social information, we investigated in Study 3 how group membership might affect ERP responses to faces. After participants learned in- and out-group memberships of the face stimuli based on arbitrarily assigned nationality and university affiliation, we found that the N170 latency differentiated in-group and out-group faces, taking longer to process the latter. In comparison, without group memberships, there was no difference in N170 latency among the faces. This dissertation provides evidence that at a neural level, structural encoding of faces, indexed by the N170, occurs within 200 ms. Face recognition, indexed by the late P2 and the N250, occurs shortly afterwards between 200 and 300 ms. Social cognitive factors can also influence face processing. The effect is already evident as early as 130-200 ms at the structural encoding stage.

Face processing in humans is compatible with a simple shape-based model of vision

Understanding how the human visual system recognizes objects is one of the key challenges in neuroscience. Inspired by a large body of physiological evidence (Felleman and Van Essen, 1991; Hubel and Wiesel, 1962; Livingstone and Hubel, 1988; Tso et al., 2001; Zeki, 1993), a general class of recognition models has emerged which is based on a hierarchical organization of visual processing, with succeeding stages being sensitive to image features of increasing complexity (Hummel and Biederman, 1992; Riesenhuber and Poggio, 1999; Selfridge, 1959). However, these models appear to be incompatible with some well-known psychophysical results. Prominent among these are experiments investigating recognition impairments caused by vertical inversion of images, especially those of faces. It has been reported that faces that differ "featurally" are much easier to distinguish when inverted than those that differ "configurally" (Freire et al., 2000; Le Grand et al., 2001; Mondloch et al., 2002) ??finding that is difficult to reconcile with the aforementioned models. Here we show that after controlling for subjects' expectations, there is no difference between "featurally" and "configurally" transformed faces in terms of inversion effect. This result reinforces the plausibility of simple hierarchical models of object representation and recognition in cortex.

Eyes, amygdala, and other models of face processing: Questions for the SIMS model

This commentary raises general questions about the parsimony and generalizability of the SIMS model, before interrogating the specific roles that the amygdala and eye contact play in it. Additionally, this situates the SIMS model alongside another model of facial expression processing, with a view to incorporating individual differences in emotion perception.

Social Cognition, Face Processing, and Oxytocin Receptor Single Nucleotide Polymorphisms in Typically Developing Children

Recent research has provided evidence of a link between behavioral measures of social cognition (SC) and neural and genetic correlates. Differences in face processing and variations in the oxytocin receptor (OXTR) gene have been associated with SC deficits and autism spectrum disorder (ASD) traits. Much work has examined the qualitative differences between those with ASD and typically developing (TD) individuals, but very little has been done to quantify the natural variation in ASD-like traits in the typical population. The present study examines this variation in TD children using a multidimensional perspective involving behavior assessment, neural electroencephalogram (EEG) testing, and OXTR genotyping. Children completed a series of neurocognitive assessments, provided saliva samples for sequencing, and completed a face processing task while connected to an EEG. No clear pattern emerged for EEG covariates or genotypes for individual OXTR single nucleotide polymorphisms (SNPs). However, SNPs rs2254298 and rs53576 consistently interacted such that the AG/GG allele combination of these SNPs was associated with poorer performance on neurocognitive measures. These results suggest that neither SNP in isolation is risk-conferring, but rather that the combination of rs2254298(A/G) and rs53576(G/G) confers a deleterious effect on SC across several neurocognitive measures. Copyright 2014. Published by Elsevier Ltd.

Dissociation between overt and unconscious face processing in fusiform face area

The precise role of the fusiform face area (FFA) in face processing remains controversial. In this study, we investigated to what degree FFA activation reflects additional functions beyond face perception. Seven volunteers underwent rapid event-related functional magnetic resonance imaging while they performed a face-encoding and a face-recognition task. During face encoding, activity in the FFA for individual faces predicted whether the individual face was subsequently remembered or forgotten. However, during face recognition, no difference in FFA activity between consciously remembered and forgotten faces was observed, but the activity of FFA differentiated if a face had been seen previously or not. This demonstrated a dissociation between overt recognition and unconscious discrimination of stimuli, suggesting that physiological processes of face recognition can take place, even if not all of its operations are made available to consciousness.

Functional imbalance of visual pathways indicates alternative face processing strategies in autism

OBJECTIVE: To investigate whether autistic subjects show a different pattern of neural activity than healthy individuals during processing of faces and complex patterns. METHODS: Blood oxygen level-dependent (BOLD) signal changes accompanying visual processing of faces and complex patterns were analyzed in an autistic group (n = 7; 25.3 [6.9] years) and a control group (n = 7; 27.7 [7.8] years). RESULTS: Compared with unaffected subjects, autistic subjects demonstrated lower BOLD signals in the fusiform gyrus, most prominently during face processing, and higher signals in the more object-related medial occipital gyrus. Further signal increases in autistic subjects vs controls were found in regions highly important for visual search: the superior parietal lobule and the medial frontal gyrus, where the frontal eye fields are located. CONCLUSIONS: The cortical activation pattern during face processing indicates deficits in the face-specific regions, with higher activations in regions involved in visual search. These findings reflect different strategies for visual processing, supporting models that propose a predisposition to local rather than global modes of information processing in autism.