Local Jekyll and Global Hyde

2011 ◽  
Vol 22 (12) ◽  
pp. 1518-1526 ◽  
Author(s):  
Sébastien Miellet ◽  
Roberto Caldara ◽  
Philippe G. Schyns
Keyword(s):  
Visual System ◽  
Face Processing ◽  
Information Gathering ◽  
Local Information ◽  
Face Identification ◽  
Main Concern ◽  
Global Information ◽  
Tracking Data ◽  
Identification Performance ◽  
Complementary Information

The main concern in face-processing research is to understand the processes underlying the identification of faces. In the study reported here, we addressed this issue by examining whether local or global information supports face identification. We developed a new methodology called “ iHybrid.” This technique combines two famous identities in a gaze-contingent paradigm, which simultaneously provides local, foveated information from one face and global, complementary information from a second face. Behavioral face-identification performance and eye-tracking data showed that the visual system identified faces on the basis of either local or global information depending on the location of the observer’s first fixation. In some cases, a given observer even identified the same face using local information on one trial and global information on another trial. A validation in natural viewing conditions confirmed our findings. These results clearly demonstrate that face identification is not rooted in a single, or even preferred, information-gathering strategy.

scholarly journals Initial eye gaze to faces and its functional consequence on face identification abilities in autism spectrum disorder

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Kimberly B. Schauder ◽  
Woon Ju Park ◽  
Yuliy Tsank ◽  
Miguel P. Eckstein ◽  
Duje Tadin ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Eye Movement ◽  
Face Perception ◽  
Face Processing ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Face Identification ◽  
Identification Performance ◽  
Functional Consequence ◽  
The Face

Abstract Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder defined and diagnosed by core deficits in social communication and the presence of restricted and repetitive behaviors. Research on face processing suggests deficits in this domain in ASD but includes many mixed findings regarding the nature and extent of these differences. The first eye movement to a face has been shown to be highly informative and sufficient to achieve high performance in face identification in neurotypical adults. The current study focused on this critical moment shown to be essential in the process of face identification. Methods We applied an established eye-tracking and face identification paradigm to comprehensively characterize the initial eye movement to a face and test its functional consequence on face identification performance in adolescents with and without ASD (n = 21 per group), and in neurotypical adults. Specifically, we presented a series of faces and measured the landing location of the first saccade to each face, while simultaneously measuring their face identification abilities. Then, individuals were guided to look at specific locations on the face, and we measured how face identification performance varied as a function of that location. Adolescent participants also completed a more traditional measure of face identification which allowed us to more fully characterize face identification abilities in ASD. Results Our results indicate that the location of the initial look to faces and face identification performance for briefly presented faces are intact in ASD, ruling out the possibility that deficits in face perception, at least in adolescents with ASD, begin with the initial eye movement to the face. However, individuals with ASD showed impairments on the more traditional measure of face identification. Conclusion Together, the observed dissociation between initial, rapid face perception processes, and other measures of face perception offers new insights and hypotheses related to the timing and perceptual complexity of face processing and how these specific aspects of face identification may be disrupted in ASD.

Do You Want to See the Tree? Ignore the Forest

2014 ◽  
Vol 61 (3) ◽  
pp. 205-214 ◽  
Author(s):  
Nicolas Poirel ◽  
Claire Sara Krakowski ◽  
Sabrina Sayah ◽  
Arlette Pineau ◽  
Olivier Houdé ◽  
...  
Keyword(s):  
Visual Recognition ◽  
Local Level ◽  
Local Information ◽  
Visual Environment ◽  
Global Information ◽  
Focus Attention ◽  
Global Level ◽  
Hierarchical Stimuli ◽  
Priming Paradigm ◽  
The One

The visual environment consists of global structures (e.g., a forest) made up of local parts (e.g., trees). When compound stimuli are presented (e.g., large global letters composed of arrangements of small local letters), the global unattended information slows responses to local targets. Using a negative priming paradigm, we investigated whether inhibition is required to process hierarchical stimuli when information at the local level is in conflict with the one at the global level. The results show that when local and global information is in conflict, global information must be inhibited to process local information, but that the reverse is not true. This finding has potential direct implications for brain models of visual recognition, by suggesting that when local information is conflicting with global information, inhibitory control reduces feedback activity from global information (e.g., inhibits the forest) which allows the visual system to process local information (e.g., to focus attention on a particular tree).

scholarly journals A Study of OWA Operators Learned in Convolutional Neural Networks

2021 ◽  
Vol 11 (16) ◽  
pp. 7195
Author(s):  
Iris Dominguez-Catena ◽  
Daniel Paternain ◽  
Mikel Galar
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Practical Method ◽  
Local Information ◽  
Weighted Averaging ◽  
Global Information ◽  
Owa Operator ◽  
Owa Operators ◽  
Ordered Weighted Averaging

Ordered Weighted Averaging (OWA) operators have been integrated in Convolutional Neural Networks (CNNs) for image classification through the OWA layer. This layer lets the CNN integrate global information about the image in the early stages, where most CNN architectures only allow for the exploitation of local information. As a side effect of this integration, the OWA layer becomes a practical method for the determination of OWA operator weights, which is usually a difficult task that complicates the integration of these operators in other fields. In this paper, we explore the weights learned for the OWA operators inside the OWA layer, characterizing them through their basic properties of orness and dispersion. We also compare them to some families of OWA operators, namely the Binomial OWA operator, the Stancu OWA operator and the exponential RIM OWA operator, finding examples that are currently impossible to generalize through these parameterizations.

scholarly journals A Self-Orgnizing Model for Peer-to-Peer Systems using Trust Relations

2014 ◽  
Vol 14 (1) ◽  
pp. 5394-5397
Author(s):  
Sourabh S. Mahajan ◽  
S.K. Pathan
Keyword(s):  
Peer To Peer ◽  
Local Information ◽  
Global Information ◽  
Trust Network ◽  
Trust Relationship ◽  
The Past ◽  
Trust Relationships ◽  
Peer To Peer Systems ◽  
Information Trustworthiness

Peer-to-Peer systems enables the interactions of peers to accomplish tasks. Attacks of peers with malicious can be reduced by establishing trust relationship among peers. In this paper we presents algorithms which helps a peer to reason about trustworthiness of other peers based on interactions in the past and recommendations. Local information is used to create trust network of peers and does not need to deal with global information. Trustworthiness of peers in providing services can be describedby Service metric and recommendation metric. Parameters considered for evaluating interactions and recommendations are Recentness, Importance and Peer Satisfaction. Trust relationships helps a good peer to isolate malicious peers.

Processing of global and local information in memory

1989 ◽  
Vol 41 (1) ◽  
pp. 167-181 ◽  
Author(s):  
Rino Rumiati ◽  
Roberto Nicoletti ◽  
Remo Job
Keyword(s):  
Local Level ◽  
Memory System ◽  
Local Information ◽  
Global Information ◽  
Global Level ◽  
Capital Letter ◽  
Global And Local

The experiments reported in this paper were designed to test how global and local information are processed by the memory system. When subjects are required to match a given letter with either a previously presented large capital letter or the small capital letters comprising it, (1) responses to the global level (i.e. the big letter) are faster than responses to the local level (i.e. the small letters), and (2) responses to the latter level only are affected by the consistency between the large and the small letters (Experiment 2), a pattern similar to that obtained in perception (Experiment 1). Such results obtain when subjects are required to attend to only one level with a short ISI between the first and second stimulus, but not when a longer ISI is used (Experiment 5) or when subjects are required to attend to both levels at the same time (Experiments 3 and 4). The results are discussed in the light of a model that postulates a temporal precedence of the global information over the local one at the perceptual level.

Dissociating Face Processing Skills: Decisions about Lip read Speech, Expression, and Identity

1996 ◽  
Vol 49 (2) ◽  
pp. 295-314 ◽  
Author(s):  
Ruth Campbell ◽  
Barbara Brooks ◽  
Edward de Haan ◽  
Tony Roberts
Keyword(s):  
Face Processing ◽  
Face Identification ◽  
Speech Sounds ◽  
Manual Responses ◽  
Lip Reading ◽  
Identity Matching ◽  
Unfamiliar Face ◽  
Identity Based ◽  
Series Of Experiments

The separability of different subcomponents of face processing has been regularly affirmed, but not always so clearly demonstrated. In particular, the ability to extract speech from faces (lip-reading) has been shown to dissociate doubly from face identification in neurological but not in other populations. In this series of experiments with undergraduates, the classification of speech sounds (lip-reading) from personally familiar and unfamiliar face photographs was explored using speeded manual responses. The independence of lip-reading from identity-based processing was confirmed. Furthermore, the established pattern of independence of expression-matching from, and dependence of identity-matching on, face familiarity was extended to personally familiar faces and “difficult”-emotion decisions. The implications of these findings are discussed.

scholarly journals Effects of aging on face identification and holistic face processing

2013 ◽  
Vol 88 ◽  
pp. 38-46 ◽  
Author(s):  
Yaroslav Konar ◽  
Patrick J. Bennett ◽  
Allison B. Sekuler
Keyword(s):  
Face Processing ◽  
Face Identification ◽  
Holistic Face Processing ◽  
Effects Of Aging

scholarly journals Fusiform Gyrus Face Selectivity Relates to Individual Differences in Facial Recognition Ability

2011 ◽  
Vol 23 (7) ◽  
pp. 1723-1740 ◽  
Author(s):  
Nicholas Furl ◽  
Lúcia Garrido ◽  
Raymond J. Dolan ◽  
Jon Driver ◽  
Bradley Duchaine
Keyword(s):  
Individual Differences ◽  
Face Processing ◽  
Statistical Parametric Mapping ◽  
Fusiform Gyrus ◽  
Face Identification ◽  
Functional Responses ◽  
Temporal Lobes ◽  
Repetition Suppression ◽  
Recognition Ability ◽  
Face Selectivity

Regions of the occipital and temporal lobes, including a region in the fusiform gyrus (FG), have been proposed to constitute a “core” visual representation system for faces, in part because they show face selectivity and face repetition suppression. But recent fMRI studies of developmental prosopagnosics (DPs) raise questions about whether these measures relate to face processing skills. Although DPs manifest deficient face processing, most studies to date have not shown unequivocal reductions of functional responses in the proposed core regions. We scanned 15 DPs and 15 non-DP control participants with fMRI while employing factor analysis to derive behavioral components related to face identification or other processes. Repetition suppression specific to facial identities in FG or to expression in FG and STS did not show compelling relationships with face identification ability. However, we identified robust relationships between face selectivity and face identification ability in FG across our sample for several convergent measures, including voxel-wise statistical parametric mapping, peak face selectivity in individually defined “fusiform face areas” (FFAs), and anatomical extents (cluster sizes) of those FFAs. None of these measures showed associations with behavioral expression or object recognition ability. As a group, DPs had reduced face-selective responses in bilateral FFA when compared with non-DPs. Individual DPs were also more likely than non-DPs to lack expected face-selective activity in core regions. These findings associate individual differences in face processing ability with selectivity in core face processing regions. This confirms that face selectivity can provide a valid marker for neural mechanisms that contribute to face identification ability.

scholarly journals An Integration Model for Text Classification using Graph Convolutional Network and BERT

2021 ◽  
Vol 2137 (1) ◽  
pp. 012052
Author(s):  
Bingxin Xue ◽  
Cui Zhu ◽  
Xuan Wang ◽  
Wenjun Zhu
Keyword(s):  
Neural Network ◽  
Text Classification ◽  
Semantic Information ◽  
Contextual Information ◽  
Local Information ◽  
Data Sets ◽  
Global Information ◽  
Convolutional Network ◽  
Integration Model ◽  
Classification Tasks

Abstract Recently, Graph Convolutional Neural Network (GCN) is widely used in text classification tasks, and has effectively completed tasks that are considered to have a rich relational structure. However, due to the sparse adjacency matrix constructed by GCN, GCN cannot make full use of context-dependent information in text classification, and cannot capture local information. The Bidirectional Encoder Representation from Transformers (BERT) has been shown to have the ability to capture the contextual information in a sentence or document, but its ability to capture global information about the vocabulary of a language is relatively limited. The latter is the advantage of GCN. Therefore, in this paper, Mutual Graph Convolution Networks (MGCN) is proposed to solve the above problems. It introduces semantic dictionary (WordNet), dependency and BERT. MGCN uses dependency to solve the problem of context dependence and WordNet to obtain more semantic information. Then the local information generated by BERT and the global information generated by GCN are interacted through the attention mechanism, so that they can influence each other and improve the classification effect of the model. The experimental results show that our model is more effective than previous research reports on three text classification data sets.

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