Evidence opposing opponent facial coding
نویسندگان
چکیده
منابع مشابه
Adaptation modulates the electrophysiological substrates of perceived facial distortion: support for opponent coding.
In two experiments we determined the electrophysiological substrates of figural aftereffects in face adaptation using compressed and expanded faces. In Experiment 1, subjects viewed a series of compressed and expanded faces. Results demonstrated that distortion systematically modulated the peak amplitude of the P250 event-related potential (ERP) component. As the amount of perceived distortion ...
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Many aspects of faces derived from structural information appear to be neurally represented using norm-based opponent coding. Recently, however, Zhao, Seriès, Hancock, and Bednar (2011) have argued that another aspect with a strong structural component, namely face gender, is instead multichannel coded. Their conclusion was based on finding that face gender aftereffects initially increased but ...
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متن کاملEvidence for opponent - channel coding of interaural time differences in human auditory 1 cortex
17 In humans, horizontal sound localisation of low-frequency sounds is mainly based on 18 interaural time differences (ITDs). Traditionally, it was assumed that ITDs are converted into 19 a topographic (or rate-place) code, supported by an array of neurons with parametric tuning 20 to ITDs within the behaviourally relevant range. While this topographic model has been 21 confirmed in owls, its a...
متن کاملEvidence for opponent-channel coding of interaural time differences in human auditory cortex.
In humans, horizontal sound localization of low-frequency sounds is mainly based on interaural time differences (ITDs). Traditionally, it was assumed that ITDs are converted into a topographic (or rate-place) code, supported by an array of neurons with parametric tuning to ITDs within the behaviorally relevant range. Although this topographic model has been confirmed in owls, its applicability ...
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ژورنال
عنوان ژورنال: Journal of Vision
سال: 2011
ISSN: 1534-7362
DOI: 10.1167/11.11.582