Intracerebral electrical stimulation to understand the neural basis of human face identity recognition

AbstractThe effects of transcutaneous electrical stimulation on deficits of tactile perception contralateral to a hemispheric lesion were investigated in 10 right brain-damaged patients and in four left brain-damaged patients. The somatosensory deficit recovered, transiently and in part, after stimulation of the side of the neck contralateral to the side of the lesion, in all 10 patients with lesions in the right hemisphere, both with (six cases) and without (four cases) left visuo-spatial hemineglect, and in one left brain-damaged patient with right hemineglect. In three left brain-damaged patients without hemineglect, the treatment had no detectable effects. In one right brain-damaged patient, the stimulation of the side of the neck ipsilateral to the side of the lesion temporarily worsened the somatosensory deficit. These effects of transcutaneous electrical stimulation are similar to those of vestibular stimulation. The suggestion is made that these treatments modulate, through afferent sensory pathways, higher-order spatial representations of the body, which are pathologically distorted toward the side of the lesion. The modulatory effect is direction-specific: the defective internal representation of the contralesional side may be either partly restored, improving the disorder of tactile perception, or further impoverished, worsening the deficit. The possible neural basis of this modulation is discussed. (JINS, 1996, 2, 452–459.)

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Own- and other-race face identity recognition in children: The effects of pose and feature composition.

Developmental Psychology ◽

10.1037/a0033166 ◽

2014 ◽

Vol 50 (2) ◽

pp. 469-481 ◽

Cited By ~ 19

Author(s):

Gizelle Anzures ◽

David J. Kelly ◽

Olivier Pascalis ◽

Paul C. Quinn ◽

Alan M. Slater ◽

...

Keyword(s):

Identity Recognition ◽

Face Identity

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An objective, sensitive and ecologically valid neural measure of rapid human individual face recognition

Royal Society Open Science ◽

10.1098/rsos.181904 ◽

2019 ◽

Vol 6 (6) ◽

pp. 181904 ◽

Cited By ~ 10

Author(s):

Friederike G. S. Zimmermann ◽

Xiaoqian Yan ◽

Bruno Rossion

Keyword(s):

Face Recognition ◽

Visual Stimulation ◽

Natural Images ◽

Neural Basis ◽

Face Identity ◽

Familiar Face ◽

Recognition Response ◽

Human Individual ◽

The Individual ◽

Unfamiliar Faces

Humans may be the only species able to rapidly and automatically recognize a familiar face identity in a crowd of unfamiliar faces, an important social skill. Here, by combining electroencephalography (EEG) and fast periodic visual stimulation (FPVS), we introduce an ecologically valid, objective and sensitive neural measure of this human individual face recognition function. Natural images of various unfamiliar faces are presented at a fast rate of 6 Hz, allowing one fixation per face, with variable natural images of a highly familiar face identity, a celebrity, appearing every seven images (0.86 Hz). Following a few minutes of stimulation, a high signal-to-noise ratio neural response reflecting the generalized discrimination of the familiar face identity from unfamiliar faces is observed over the occipito-temporal cortex at 0.86 Hz and harmonics. When face images are presented upside-down, the individual familiar face recognition response is negligible, being reduced by a factor of 5 over occipito-temporal regions. Differences in the magnitude of the individual face recognition response across different familiar face identities suggest that factors such as exposure, within-person variability and distinctiveness mediate this response. Our findings of a biological marker for fast and automatic recognition of individual familiar faces with ecological stimuli open an avenue for understanding this function, its development and neural basis in neurotypical individual brains along with its pathology. This should also have implications for the use of facial recognition measures in forensic science.

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Unconstrained Face Recognition

Computer Vision ◽

10.4018/978-1-5225-5204-8.ch068 ◽

2018 ◽

pp. 1640-1661

Author(s):

Stefanos Zafeiriou ◽

Irene Kotsia ◽

Maja Pantic

Keyword(s):

Computer Vision ◽

Face Recognition ◽

Partial Occlusion ◽

Human Face ◽

Facial Analysis ◽

Identity Recognition ◽

Unconstrained Face Recognition ◽

Fully Automatic ◽

Unconstrained Face ◽

Appearance Changes

The human face is the most well-researched object in computer vision, mainly because (1) it is a highly deformable object whose appearance changes dramatically under different poses, expressions, and, illuminations, etc., (2) the applications of face recognition are numerous and span several fields, (3) it is widely known that humans possess the ability to perform, extremely efficiently and accurately, facial analysis, especially identity recognition. Although a lot of research has been conducted in the past years, the problem of face recognition using images captured in uncontrolled environments including several illumination and/or pose variations still remains open. This is also attributed to the existence of outliers (such as partial occlusion, cosmetics, eyeglasses, etc.) or changes due to age. In this chapter, the authors provide an overview of the existing fully automatic face recognition technologies for uncontrolled scenarios. They present the existing databases and summarize the challenges that arise in such scenarios and conclude by presenting the opportunities that exist in the field.

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Unconstrained Face Recognition

Face Recognition in Adverse Conditions - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-4666-5966-7.ch002 ◽

2014 ◽

pp. 16-37 ◽

Cited By ~ 1

Author(s):

Stefanos Zafeiriou ◽

Irene Kotsia ◽

Maja Pantic

Keyword(s):

Computer Vision ◽

Face Recognition ◽

Partial Occlusion ◽

Human Face ◽

Facial Analysis ◽

Identity Recognition ◽

Unconstrained Face Recognition ◽

Fully Automatic ◽

Unconstrained Face ◽

Appearance Changes

The human face is the most well-researched object in computer vision, mainly because (1) it is a highly deformable object whose appearance changes dramatically under different poses, expressions, and, illuminations, etc., (2) the applications of face recognition are numerous and span several fields, (3) it is widely known that humans possess the ability to perform, extremely efficiently and accurately, facial analysis, especially identity recognition. Although a lot of research has been conducted in the past years, the problem of face recognition using images captured in uncontrolled environments including several illumination and/or pose variations still remains open. This is also attributed to the existence of outliers (such as partial occlusion, cosmetics, eyeglasses, etc.) or changes due to age. In this chapter, the authors provide an overview of the existing fully automatic face recognition technologies for uncontrolled scenarios. They present the existing databases and summarize the challenges that arise in such scenarios and conclude by presenting the opportunities that exist in the field.

Download Full-text