scholarly journals Critical information thresholds underlying concurrent face recognition functions

2020 ◽  
Author(s):  
Genevieve L. Quek ◽  
Bruno Rossion ◽  
Joan Liu-Shuang
Keyword(s):  
Face Recognition ◽  
Human Brain ◽  
Sensory Input ◽  
Right Hemisphere ◽  
Individual Variability ◽  
Recognition Threshold ◽  
Large Set ◽  
Sensory Thresholds ◽  
Human Face ◽  
Familiar Face

AbstractHumans rapidly and automatically recognise faces on multiple different levels, yet little is known about how the brain achieves these manifold categorisations concurrently. We bring a new perspective to this emerging issue by probing the relative informational dependencies of two of the most important aspects of human face processing: categorisation of the stimulus as a face (generic face recognition) and categorisation of its familiarity (familiar face recognition). Recording electrophysiological responses to a large set of natural images progressively increasing in image duration (Expt. 1) or spatial frequency content (Expt. 2), we contrasted critical sensory thresholds for these recognition functions as driven by the same face encounters. Across both manipulations, individual observer thresholds were consistently lower for distinguishing faces from other objects than for distinguishing familiar from unfamiliar faces. Moreover, familiar face recognition displayed marked inter-individual variability compared to generic face recognition, with no systematic relationship evident between the two thresholds. Scalp activation was also more strongly right-lateralised at the generic face recognition threshold than at the familiar face recognition threshold. These results suggest that high-level recognition of a face as a face arises based on minimal sensory input (i.e., very brief exposures/coarse resolutions), predominantly in right hemisphere regions. In contrast, the amount of additional sensory evidence required to access face familiarity is highly idiosyncratic and recruits wider neural networks. These findings underscore the neurofunctional distinctions between these two recognition functions, and constitute an important step forward in understanding how the human brain recognises various dimensions of a face in parallel.Significance StatementThe relational dynamics between different aspects of face recognition are not yet well understood. We report relative informational dependencies for two concurrent, ecologically relevant face recognition functions: distinguishing faces from objects, and recognising people we know. Our electrophysiological data show that for a given face encounter, the human brain requires less sensory input to categorise that stimulus as a face than to recognise whether the face is familiar. Moreover, where sensory thresholds for distinguishing faces from objects are remarkably consistent across observers, they vary widely for familiar face recognition. These findings shed new light on the multifaceted nature of human face recognition by painting a more comprehensive picture of the concurrent evidence accumulation processes initiated by seeing a face.

scholarly journals The neural dynamics of familiar face recognition

2018 ◽  
Author(s):  
Géza Gergely Ambrus ◽  
Daniel Kaiser ◽  
Radoslaw Martin Cichy ◽  
Gyula Kovács
Keyword(s):  
Face Recognition ◽  
Visual Processing ◽  
Right Hemisphere ◽  
Temporal Cortex ◽  
Real Life ◽  
Same Sex ◽  
Identity Information ◽  
Face Identity ◽  
Familiar Face ◽  
Invariant Representations

AbstractIn real-life situations, the appearance of a person’s face can vary substantially across different encounters, making face recognition a challenging task for the visual system. Recent fMRI decoding studies have suggested that face recognition is supported by identity representations located in regions of the occipito-temporal cortex. Here, we used EEG to elucidate the temporal emergence of these representations. Human participants (both sexes) viewed a set of highly variable face images of four highly familiar celebrities (two male, two female), while performing an orthogonal task. Univariate analyses of event-related EEG responses revealed a pronounced differentiation between male and female faces, but not between identities of the same sex. Using multivariate representational similarity analysis, we observed a gradual emergence of face identity representations, with an increasing degree of invariance. Face identity information emerged rapidly, starting shortly after 100ms from stimulus onset. From 400ms after onset and predominantly in the right hemisphere, identity representations showed two invariance properties: (1) they equally discriminated identities of opposite sexes and of the same sex, and (2) they were tolerant to image-based variations. These invariant representations may be a crucial prerequisite for successful face recognition in everyday situations, where the appearance of a familiar person can vary drastically.Significance StatementRecognizing the face of a friend on the street is a task we effortlessly perform in our everyday lives. However, the necessary visual processing underlying familiar face recognition is highly complex. As the appearance of a given person varies drastically between encounters, for example across viewpoints or emotional expressions, the brain needs to extract identity information that is invariant to such changes. Using multivariate analyses of EEG data, we characterize how invariant representations of face identity emerge gradually over time. After 400ms of processing, cortical representations reliably differentiated two similar identities (e.g., two famous male actors), even across a set of highly variable images. These representations may support face recognition under challenging real-life conditions.

Coarse-to-Fine(r) Automatic Familiar Face Recognition in the Human Brain

2021 ◽  
Author(s):  
Xiaoqian Yan ◽  
Valérie Goffaux ◽  
Bruno Rossion
Keyword(s):  
Face Recognition ◽  
Human Brain ◽  
Spatial Resolution ◽  
Predictive Coding ◽  
Head Width ◽  
Familiar Face ◽  
Visual Inputs ◽  
Electroencephalogram Eeg ◽  
Coarse To Fine ◽  
Unfamiliar Faces

Abstract At what level of spatial resolution can the human brain recognize a familiar face in a crowd of strangers? Does it depend on whether one approaches or rather moves back from the crowd? To answer these questions, 16 observers viewed different unsegmented images of unfamiliar faces alternating at 6 Hz, with spatial frequency (SF) content progressively increasing (i.e., coarse-to-fine) or decreasing (fine-to-coarse) in different sequences. Variable natural images of celebrity faces every sixth stimulus generated an objective neural index of single-glanced automatic familiar face recognition (FFR) at 1 Hz in participants’ electroencephalogram (EEG). For blurry images increasing in spatial resolution, the neural FFR response over occipitotemporal regions emerged abruptly with additional cues at about 6.3–8.7 cycles/head width, immediately reaching amplitude saturation. When the same images progressively decreased in resolution, the FFR response disappeared already below 12 cycles/head width, thus providing no support for a predictive coding hypothesis. Overall, these observations indicate that rapid automatic recognition of heterogenous natural views of familiar faces is achieved from coarser visual inputs than generally thought, and support a coarse-to-fine FFR dynamics in the human brain.

Human face recognition in sheep: lack of configurational coding and right hemisphere advantage

2001 ◽  
Vol 55 (1) ◽  
pp. 13-26 ◽  
Author(s):  
J.W Peirce ◽  
A.E Leigh ◽  
A.P.C daCosta ◽  
K.M Kendrick
Keyword(s):  
Face Recognition ◽  
Right Hemisphere ◽  
Human Face ◽  
Human Face Recognition

Face Familiarity Decisions Take 200 msec in the Human Brain: Electrophysiological Evidence from a Go/No-go Speeded Task

2014 ◽  
Vol 26 (1) ◽  
pp. 81-95 ◽  
Author(s):  
Stephanie Caharel ◽  
Meike Ramon ◽  
Bruno Rossion
Keyword(s):  
Human Brain ◽  
Face Processing ◽  
Brain Function ◽  
Time Course ◽  
Right Hemisphere ◽  
Time Frame ◽  
Familiar Face ◽  
Scalp Eeg ◽  
The Right ◽  
Unfamiliar Faces

Recognizing a familiar face rapidly is a fundamental human brain function. Here we used scalp EEG to determine the minimal time needed to classify a face as personally familiar or unfamiliar. Go (familiar) and no-go (unfamiliar) responses elicited clear differential waveforms from 210 msec onward, this difference being first observed at right occipito-temporal electrode sites. Similar but delayed (by about 40 msec) responses were observed when go response were required to the unfamiliar rather than familiar faces, in a second group of participants. In both groups, a small increase of amplitude was also observed on the right hemisphere N170 face-sensitive component for familiar faces. However, unlike the post-200 msec differential go/no-go effect, this effect was unrelated to behavior and disappeared with repetition of unfamiliar faces. These observations indicate that accumulation of evidence within the first 200 msec poststimulus onset is sufficient for the human brain to decide whether a person is familiar based on his or her face, a time frame that puts strong constraints on the time course of face processing.

Real Time Person Recognition and Attendance Marking Using Holistic Based Approach

2017 ◽  
Vol 7 (7) ◽  
pp. 302
Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
High Accuracy ◽  
Efficient Technique ◽  
Human Face ◽  
Traditional Methods ◽  
Person Recognition ◽  
The Face

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.

scholarly journals Recognising Familiar Faces Out of Context

Perception ◽  
2021 ◽  
Vol 50 (2) ◽  
pp. 174-177
Author(s):  
Sarah Laurence ◽  
Jordyn Eyre ◽  
Ailsa Strathie
Keyword(s):  
Face Recognition ◽  
Recognition Test ◽  
Familiar Face

Expertise in familiar face recognition has been well-documented in several studies. Here, we examined the role of context using a surprise lecturer recognition test. Across two experiments, we found few students recognised their lecturer when they were unexpected, but accuracy was higher when the lecturer was preceded by a prompt. Our findings suggest that familiar face recognition can be poor in unexpected contexts.

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