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Fast periodic presentation of natural images reveals a robust face-selective electrophysiological response in the human brain

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TLDR
This fast periodic visual stimulation approach provides a direct signature of natural face categorization and opens an avenue for efficiently measuring categorization responses of complex visual stimuli in the human brain.
Abstract
We designed a fast periodic visual stimulation approach to identify an objective signature of face categorization incorporating both visual discrimination (from nonface objects) and generalization (across widely variable face exemplars). Scalp electroencephalographic (EEG) data were recorded in 12 human observers viewing natural images of objects at a rapid frequency of 5.88 images/s for 60 s. Natural images of faces were interleaved every five stimuli, i.e., at 1.18 Hz (5.88/5). Face categorization was indexed by a high signal-to-noise ratio response, specifically at an oddball face stimulation frequency of 1.18 Hz and its harmonics. This face-selective periodic EEG response was highly significant for every participant, even for a single 60-s sequence, and was generally localized over the right occipitotemporal cortex. The periodicity constraint and the large selection of stimuli ensured that this selective response to natural face images was free of low-level visual confounds, as confirmed by the absence of any oddball response for phase-scrambled stimuli. Without any subtraction procedure, time-domain analysis revealed a sequence of differential face-selective EEG components between 120 and 400 ms after oddball face image onset, progressing from medial occipital (P1-faces) to occipitotemporal (N1-faces) and anterior temporal (P2-faces) regions. Overall, this fast periodic visual stimulation approach provides a direct signature of natural face categorization and opens an avenue for efficiently measuring categorization responses of complex visual stimuli in the human brain

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Citations
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Journal ArticleDOI

The steady-state visual evoked potential in vision research: A review.

TL;DR: The purpose of this article is to describe the fundamental stimulation paradigms for steady-state visual evoked potentials and to illustrate these principles through research findings across a range of applications in vision science.
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Rapid categorization of natural face images in the infant right hemisphere

TL;DR: The findings indicate that right lateralized face-selective processes emerge well before reading acquisition in the infant brain, which can perform figure-ground segregation and generalize face- selective responses across changes in size, viewpoint, illumination as well as expression, age and gender.
Journal ArticleDOI

Uncovering the neural magnitude and spatio-temporal dynamics of natural image categorization in a fast visual stream.

TL;DR: Uncovering the neural spatio-temporal dynamics of category-selectivity in a rapid stream of natural images goes well beyond previous evidence obtained from spatially and temporally isolated stimuli, opening an avenue for understanding human vision and its relationship to categorization behavior.
Journal ArticleDOI

A face-selective ventral occipito-temporal map of the human brain with intracerebral potentials.

TL;DR: A comprehensive quantification of selective brain responses to faces throughout the ventral visual stream with direct recordings in the gray matter is provided, offering the first supporting evidence of two decades of neuroimaging observations with direct neural measures.
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Neural tracking of the musical beat is enhanced by low-frequency sounds.

TL;DR: It is found that cortical activity at the frequency of the perceived beat is selectively enhanced compared with other frequencies in the EEG spectrum when rhythms are conveyed by bass sounds, and was particularly pronounced for the complex rhythm requiring endogenous generation of the beat.
References
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Robust Real-Time Face Detection

TL;DR: In this paper, a face detection framework that is capable of processing images extremely rapidly while achieving high detection rates is described. But the detection performance is limited to 15 frames per second.
Proceedings ArticleDOI

Robust real-time face detection

TL;DR: A new image representation called the “Integral Image” is introduced which allows the features used by the detector to be computed very quickly and a method for combining classifiers in a “cascade” which allows background regions of the image to be quickly discarded while spending more computation on promising face-like regions.
Journal ArticleDOI

The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception

TL;DR: The data allow us to reject alternative accounts of the function of the fusiform face area (area “FF”) that appeal to visual attention, subordinate-level classification, or general processing of any animate or human forms, demonstrating that this region is selectively involved in the perception of faces.
Journal ArticleDOI

The distributed human neural system for face perception.

TL;DR: A model for the organization of this system that emphasizes a distinction between the representation of invariant and changeable aspects of faces is proposed and is hierarchical insofar as it is divided into a core system and an extended system.
Journal ArticleDOI

Detecting faces in images: a survey

TL;DR: In this article, the authors categorize and evaluate face detection algorithms and discuss relevant issues such as data collection, evaluation metrics and benchmarking, and conclude with several promising directions for future research.
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