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Human face preference in gamma-frequency EEG activity.

ABSTRACT: 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.

SUBMITTER: Zion-Golumbic E

PROVIDER: S-EPMC2268116 | biostudies-other | 2008 Feb

REPOSITORIES: biostudies-other

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Human face preference in gamma-frequency EEG activity.

Zion-Golumbic Elana E Golan Tal T Anaki David D Bentin Shlomo S

NeuroImage 20071107 4

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 exper ...[more]

PMID: 18083564

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Project description:High-frequency oscillations are markers of epileptic tissue. Recently, different patterns of EEG background activity were described from which high-frequency oscillations occur: high-frequency oscillations with continuously oscillating background were found to be primarily physiological, those from quiet background were linked to epileptic tissue. It is unclear, whether these interactions remain stable over several days and during different sleep-wake stages. High-frequency oscillation patterns (oscillatory vs. quiet background) were analysed in 23 patients implanted with depth and subdural grid electrodes. Pattern scoring was performed on every channel in 10 s intervals in three separate day- and night-time EEG segments. An entropy value, measuring variability of patterns per channel, was calculated. A low entropy value indicated a stable occurrence of the same pattern in one channel, whereas a high value indicated pattern instability. Differences in pattern distribution and entropy were analysed for 143 280 10 s intervals with allocated patterns from inside and outside the seizure onset zone, different electrode types and brain regions. We found a strong association between high-frequency oscillations out of quiet background activity, and channels of the seizure onset zone (35.2% inside versus 9.7% outside the seizure onset zone, P < 0.001), no association was found for high-frequency oscillations from continuous oscillatory background (P = 0.563). The type of background activity remained stable over the same brain region over several days and was independent of sleep stage and recording technique. Stability of background activity was significantly higher in channels of the seizure onset zone (entropy mean value 0.56 ± 0.39 versus 0.64 ± 0.41; P < 0.001). This was especially true for the presumed epileptic high-frequency oscillations out of quiet background (0.57 ± 0.39 inside versus 0.72 ± 0.37 outside the seizure onset zone; P < 0.001). In contrast, presumed physiological high-frequency oscillations from continuous oscillatory backgrounds were significantly more stable outside the seizure onset zone (0.72 ± 0.45 versus 0.48 ± 0.53; P < 0.001). The overall low entropy values suggest that interactions between high-frequency oscillations and background activity are a stable phenomenon specific to the function of brain regions. High-frequency oscillations occurring from a quiet background are strongly linked to the seizure onset zone whereas high-frequency oscillations from an oscillatory background are not. Pattern stability suggests distinct underlying mechanisms. Analysing short time segments of high-frequency oscillations and background activity could help distinguishing epileptic from physiologically active brain regions.

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Human face preference in gamma-frequency EEG activity.

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Human face preference in gamma-frequency EEG activity.

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