The face-specific N170 component reflects late stages in the structural encoding of faces

Eimer, Martin

doi:10.1097/00001756-200007140-00050

Cited by 541 publications

(485 citation statements)

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“…Since the trend found here is consistent with previous results which found significant differences between the N170 elicited by faces and human hands (e.g. Bentin et al, 1996;Eimer 2000, Onitsuka et al 2006, Kovacs et al 2006, and it was not the focus of the study, we did not investigated further the current null face-hands N170 effect.…”

Section: Resultssupporting

confidence: 90%

Human face preference in gamma-frequency EEG activity

et al. 2008

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Previous studies demonstrated that induced EEG activity in the gamma band (iGBA) plays an important role in object recognition and is modulated by stimulus familiarity and its compatibility with pre-existent representations. In the present study we investigated the modulation of iGBA by the degree of familiarity and perceptual expertise that observers have with stimuli from different categories. Specifically, we compared iGBA in response to human faces versus stimuli which subjects are not expert with (ape faces, human hands, buildings and watches). iGBA elicited by human faces was higher and peaked earlier than that elicited by all other categories, which did not differ significantly from each other. These findings can be accounted for by two characteristics of perceptual expertise. One is the activation of a richer, stronger and, therefore, more easily accessible mental representation of human faces. The second is the more detailed perceptual processing necessary for within-category distinctions, which is the hallmark of perceptual expertise. In addition, the sensitivity of iGBA to human but not ape faces was contrasted with the face-sensitive N170-effect, which was similar for human and ape faces. In concert with previous studies, this dissociation suggests a multi-level neuronal model of face recognition, manifested by these two electrophysiological measures, discussed in this paper.Cognitive neuroscience research has been enriched during the last decade by studies associating high-frequency EEG activity with the generation of unified perceptual representations in both vision and audition, and the activation of pre-stored memory representations (Busch, et al., 2006;Kaiser and Lutzenberger, 2003). Changing the conception that physiologically pertinent EEG frequencies are lower than 20 Hz, studies in animals (Singer and Gray, 1995) and in humans (e.g. Tallon-Baudry et al., 1996, 2003Gruber et al. 2004Gruber et al. , 2005Rodriguez et al. 1999) explored activity in a range of frequencies higher than 20 Hz, which were addressed as "gamma-band". Specifically, many studies have associated between high-level perceptual mechanisms and the so-called "induced" gamma-band activity (iGBA; for review see Bertrand and Tallon-Baudry, 2000).iGBA is a measure for local neural synchronization appearing as bursts of high-frequency EEG activity which is event-related but is not necessarily phase locked to the stimulus onset (and thus may be cancelled out in traditional ERP analysis). The amplitude of these bursts is modulated by physical stimulus attributes such as size, contrast and spatial-frequency spectrum

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Section: Resultssupporting

confidence: 90%

Human face preference in gamma-frequency EEG activity

et al. 2008

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“…Following a similar time course, identity recognition progressively improved into late adolescence before reaching the adult level [73]. Thus face recognition may be a multi-stage process, where the early stage of face categorization is important for later stages of mnemonic processing that are sensitive to face identity [113,120,123].…”

Section: Erp Correlates Of Face Processing In Normal Adults and Childrenmentioning

confidence: 91%

“…Scalp ERPs and intracranial recordings from otherwise healthy epileptic patients have revealed a reliable and selective index of face processing at 150-200 ms latency, namely the scalp N170 [113][114][115]. Similarly, the intracranial N200, has been recorded at discrete locations over the fusiform gyrus, the inferior temporal sulcus (ITS) and the superior temporal sulcus (STS) [116].…”

Section: Erp Correlates Of Face Processing In Normal Adults and Childrenmentioning

confidence: 99%

“…Possibly marking the category-recognition stage, the N170 is sensitive to features usually predictive of faces, such as isolated eyes, nose or mouth [117,118], or back views of the head, or face outlines without features. In contrast, the N170 appears independent of face identity [113,119,120] as it is insensitive to face repetition [119,121], learning [122], familiarity [123,124], or attention [125]. Although the N170 is not dynamically responsive to face identity or memory, comparison among adult subjects suggests that its amplitude and latency may predict general proficiency at face recognition [114].…”

Section: Erp Correlates Of Face Processing In Normal Adults and Childrenmentioning

confidence: 99%

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Autism and the development of face processing

Golarai

Grill-Spector

Reiss

2006

Clinical Neuroscience Research

158

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Autism is a pervasive developmental condition, characterized by impairments in non-verbal communication, social relationships and stereotypical patterns of behavior. A large body of evidence suggests that several aspects of face processing are impaired in autism, including anomalies in gaze processing, memory for facial identity and recognition of facial expressions of emotion. In search of neural markers of anomalous face processing in autism, much interest has focused on a network of brain regions that are implicated in social cognition and face processing. In this review, we will focus on three such regions, namely the STS for its role in processing gaze and facial movements, the FFA in face detection and identification and the amygdala in processing facial expressions of emotion. Much evidence suggests that a better understanding of the normal development of these specialized regions is essential for discovering the neural bases of face processing anomalies in autism. Thus, we will also examine the available literature on the normal development of face processing. Key unknowns in this research area are the neuro-developmental processes, the role of experience and the interactions among components of the face processing system in shaping each of the specialized regions for processing faces during normal development and in autism. Published by Elsevier B.V. on behalf of Association for Research in Nervous and Mental Disease.

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“…Several studies on face recognition using ERPs have demonstrated a difference in the ERPs to faces and objects at between 150-200 ms in bilateral occipito-temporal regions (Eimer, 2000;Rossion, Gauthier, Tarr, Despland, Bruyer, Linotte, & Crommelinck, 2000). Bentin, Allison, Puce, Perez, McCarthy (1996) investigated the response characteristics of the 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 25 N170 using a target detection task in which various pictures of faces and other objects (e.g.…”

Section: Methodsmentioning

confidence: 99%

Perceptual learning and inversion effects: Recognition of prototype-defined familiar checkerboards.

Civile¹,

Zhao²,

Ku³

et al. 2014

Journal of Experimental Psychology: Animal Learning and Cogniti

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The face inversion effect is a defection in performance in recognizing inverted faces compared with faces presented in their usual upright orientation typically believed to be specific for facial stimuli. McLaren (1997) was able to demonstrate that (a) an inversion effect could be obtained with exemplars drawn from a familiar category, such that upright exemplars were better discriminated than inverted exemplars; and (b) that the inversion effect required that the familiar category be prototype-defined. In this article, we replicate and extend these findings. We show that the inversion effect can be obtained in a standard old/new recognition memory paradigm, demonstrate that it is contingent on familiarization with a prototype-defined category, and establish that the effect is made up of two components. We confirm the advantage for upright exemplars drawn from a familiar, prototype-defined category, and show that there is a disadvantage for inverted exemplars drawn from this category relative to suitable controls. We also provide evidence that there is an N170 event-related potential signature for this effect. These results allow us to integrate a theory of perceptual learning originally proposed by McLaren, Kaye, and Mackintosh (1989) with explanations of the face inversion effect, first reported by Yin.

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The face-specific N170 component reflects late stages in the structural encoding of faces

Cited by 541 publications

References 10 publications

Human face preference in gamma-frequency EEG activity

Human face preference in gamma-frequency EEG activity

Autism and the development of face processing

Perceptual learning and inversion effects: Recognition of prototype-defined familiar checkerboards.

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