Domain specificity versus expertise: factors influencing distinct processing of faces

Carmel, David; Bentin, Shlomo

doi:10.1016/s0010-0277(01)00162-7

Cited by 328 publications

(252 citation statements)

References 79 publications

(88 reference statements)

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“…In the current study we found additional evidence for this dissociation. Whereas the current ERP findings replicate the similar N170 effects for ape and human faces reported by Carmel and Bentin (2002) the iGBA significantly distinguished between these two categories. This suggests that during basic-level categorization tasks (such as monitoring for flowers) the mechanism eliciting the N170 is particularly sensitive to stimuli that have a global structure of a face (regardless of whether the face is human, ape face or schematic, cf.…”

Section: Discussionsupporting

confidence: 87%

“…The comparison between iGBA elicited by human and ape faces is of special interest since ape faces share the structure as human faces but are less familiar and, indeed, humans are not experts in identifying ape faces at a subordinate level (Mondloch et al, 2006). This comparison enables us to distinguish between structure-based selectivity for faces (as is exhibited by the face-sensitive N170 component, see Carmel and Bentin, 2002;Itier et al, 2006) and between processes related to the special status of human faces.…”

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confidence: 99%

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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: Discussionsupporting

confidence: 87%

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confidence: 99%

Human face preference in gamma-frequency EEG activity

et al. 2008

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“…However, subsequent studies reported no differences between human and various animal faces when presented in natural scenes (Rousselet et al, 2004) or between human, dog and cat faces presented in close-ups (Shibata et al, 2002). Two studies reported a similar N170 amplitude for ape and human faces with longer latencies for apes (Carmel and Bentin, 2002;Itier et al, 2006) while another reported larger N170 to ape than human faces . Thus, whether the human face is processed in a special way compared to other animal faces early on in the visual pathway remains unclear.…”

Section: Introductionmentioning

confidence: 95%

Species sensitivity of early face and eye processing

2011

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Humans are better at recognizing human faces than faces of other species. However, it is unclear whether this species sensitivity can be seen at early perceptual stages of face processing and whether it involves species sensitivity for important facial features like the eyes. These questions were addressed by comparing the modulations of the N170 ERP component to faces, eyes and eyeless faces of humans, apes, cats and dogs, presented upright and inverted. Although all faces and isolated eyes yielded larger responses than the control object category (houses), the N170 was shorter and smaller to human than animal faces and larger to human than animal eyes. Most importantly, while the classic inversion effect was found for human faces, animal faces yielded no inversion effect or an opposite inversion effect, as seen for objects, suggesting a different neural process involved for humans faces compared to faces of other species. Thus, in addition to its general face and eye categorical sensitivity, the N170 appears particularly sensitive to the human species for both faces and eyes. The results are discussed in the context of a recent model of the N170 response involving face and eye sensitive neurons (Itier et al., 2007) where the eyes play a central role in face perception. The data support the intuitive idea that eyes are what make animal head fronts look face-like and that proficiency for the human species involves visual expertise for the human eyes.

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“…In visual object processing a cascaded categorization and identification process has been proposed beginning with expert object definition (e.g., face) reflected by N 170 , leading to the final identification of a particular familiar item in that category manifesting in N 250 (Scott et al, 2006;Tanaka et al, 2006). In the specific case of face processing, faces evoked an equally prominent N 170 which was significantly larger than the ERPs to non-face categories, regardless of attention (Carmel and Bentin, 2002). Thus,similar to visual N 170 and N 250 , auditory N 100a and SN do not require that the subject attend.…”

Section: Processes Associated With Potentials To Frequency Changementioning

confidence: 99%

Auditory-evoked potentials to frequency increase and decrease of high- and low-frequency tones

Pratt

Starr

Michalewski

et al. 2009

Clinical Neurophysiology

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a b s t r a c tObjective: To define cortical brain responses to large and small frequency changes (increase and decrease) of high-and low-frequency tones. Methods: Event-Related Potentials (ERPs) were recorded in response to a 10% or a 50% frequency increase from 250 or 4000 Hz tones that were approximately 3 s in duration and presented at 500-ms intervals. Frequency increase was followed after 1 s by a decrease back to base frequency. Frequency changes occurred at least 1 s before or after tone onset or offset, respectively. Subjects were not attending to the stimuli. Latency, amplitude and source current density estimates of ERPs were compared across frequency changes. Results: All frequency changes evoked components P 50 , N 100 , and P 200 . N 100 and P 200 had double peaks at bilateral and right temporal sites, respectively. These components were followed by a slow negativity (SN). The constituents of N 100 were predominantly localized to temporo-parietal auditory areas. The potentials and their intracranial distributions were affected by both base frequency (larger potentials to low frequency) and direction of change (larger potentials to increase than decrease), as well as by change magnitude (larger potentials to larger change). The differences between frequency increase and decrease depended on base frequency (smaller difference to high frequency) and were localized to frontal areas. Conclusions: Brain activity varies according to frequency change direction and magnitude as well as base frequency. Significance: The effects of base frequency and direction of change may reflect brain networks involved in more complex processing such as speech that are differentially sensitive to frequency modulations of high (consonant discrimination) and low (vowels and prosody) frequencies.

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Domain specificity versus expertise: factors influencing distinct processing of faces

Cited by 328 publications

References 79 publications

Human face preference in gamma-frequency EEG activity

Human face preference in gamma-frequency EEG activity

Species sensitivity of early face and eye processing

Auditory-evoked potentials to frequency increase and decrease of high- and low-frequency tones

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