Joint encoding of facial identity, orientation, gaze, and expression in the middle dorsal face area

The last two decades have established that a network of face-selective areas in the temporal lobe of macaque monkeys supports the visual processing of faces. Each area within the network contains a large fraction of face-selective cells. And each area encodes facial identity and head orientation differently. A recent brain-imaging study discovered an area outside of this network selective for naturalistic facial motion, the middle dorsal (MD) face area. This finding offers the opportunity to determine whether coding principles revealed inside the core network would generalize to face areas outside the core network. We investigated the encoding of static faces and objects, facial identity, and head orientation, dimensions which had been studied in multiple areas of the core face-processing network before, as well as facial expressions and gaze. We found that MD populations form a face-selective cluster with a degree of selectivity comparable to that of areas in the core face-processing network. MD encodes facial identity robustly across changes in head orientation and expression, it encodes head orientation robustly against changes in identity and expression, and it encodes expression robustly across changes in identity and head orientation. These three dimensions are encoded in a separable manner. Furthermore, MD also encodes the direction of gaze in addition to head orientation. Thus, MD encodes both structural properties (identity) and changeable ones (expression and gaze) and thus provides information about another animal’s direction of attention (head orientation and gaze). MD contains a heterogeneous population of cells that establish a multidimensional code for faces.

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Attentional Weighting in the Face Processing Network: A Magnetic Response Image-guided Magnetoencephalography Study Using Multiple Cyclic Entrainments

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_01428 ◽

2019 ◽

Vol 31 (10) ◽

pp. 1573-1588 ◽

Cited By ~ 2

Author(s):

Eelke de Vries ◽

Daniel Baldauf

Keyword(s):

Face Processing ◽

Visual Processing ◽

Magnetic Response ◽

Fusiform Face Area ◽

Facial Identity ◽

Image Guided ◽

Face Area ◽

The Face ◽

Occipital Face Area ◽

Processing Network

We recorded magnetoencephalography using a neural entrainment paradigm with compound face stimuli that allowed for entraining the processing of various parts of a face (eyes, mouth) as well as changes in facial identity. Our magnetic response image-guided magnetoencephalography analyses revealed that different subnodes of the human face processing network were entrained differentially according to their functional specialization. Whereas the occipital face area was most responsive to the rate at which face parts (e.g., the mouth) changed, and face patches in the STS were mostly entrained by rhythmic changes in the eye region, the fusiform face area was the only subregion that was strongly entrained by the rhythmic changes in facial identity. Furthermore, top–down attention to the mouth, eyes, or identity of the face selectively modulated the neural processing in the respective area (i.e., occipital face area, STS, or fusiform face area), resembling behavioral cue validity effects observed in the participants' RT and detection rate data. Our results show the attentional weighting of the visual processing of different aspects and dimensions of a single face object, at various stages of the involved visual processing hierarchy.

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Beyond the core face-processing network: intracerebral stimulation of a face-selective area in the right anterior fusiform gyrus elicits transient prosopagnosia

Frontiers in Neuroscience ◽

10.3389/conf.fnins.2015.89.00087 ◽

2015 ◽

Vol 9 ◽

Author(s):

Jonas Jacques ◽

Rossion Bruno

Keyword(s):

Face Processing ◽

Fusiform Gyrus ◽

The Core ◽

Selective Area ◽

The Right ◽

Processing Network ◽

Stimulation Of

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Altered bold response within the core face processing network in congenital prosopagnosia

Ideggyógyászati Szemle ◽

10.18071/isz.68.0199 ◽

2015 ◽

Vol 68 (5-6) ◽

pp. 199-215 ◽

Cited By ~ 1

Author(s):

Kornél Németh ◽

Márta Zimmer ◽

Krisztina Nagy ◽

Éva Bankó ◽

Zoltán Vidnyánszky ◽

...

Keyword(s):

Face Processing ◽

Bold Response ◽

The Core ◽

Congenital Prosopagnosia ◽

Processing Network

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Sensitivity to Faces with Typical and Atypical Part Configurations within Regions of the Face-processing Network: An fMRI Study

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_01255 ◽

2018 ◽

Vol 30 (7) ◽

pp. 963-972 ◽

Cited By ~ 3

Author(s):

Andrew D. Engell ◽

Na Yeon Kim ◽

Gregory McCarthy

Keyword(s):

Face Processing ◽

Brain Regions ◽

Domain Specific ◽

Face Area ◽

Fmri Study ◽

The Face ◽

Occipital Face Area ◽

Typical Configuration ◽

The Brain ◽

Processing Network

Perception of faces has been shown to engage a domain-specific set of brain regions, including the occipital face area (OFA) and the fusiform face area (FFA). It is commonly held that the OFA is responsible for the detection of faces in the environment, whereas the FFA is responsible for processing the identity of the face. However, an alternative model posits that the FFA is responsible for face detection and subsequently recruits the OFA to analyze the face parts in the service of identification. An essential prediction of the former model is that the OFA is not sensitive to the arrangement of internal face parts. In the current fMRI study, we test the sensitivity of the OFA and FFA to the configuration of face parts. Participants were shown faces in which the internal parts were presented in a typical configuration (two eyes above a nose above a mouth) or in an atypical configuration (the locations of individual parts were shuffled within the face outline). Perception of the atypical faces evoked a significantly larger response than typical faces in the OFA and in a wide swath of the surrounding posterior occipitotemporal cortices. Surprisingly, typical faces did not evoke a significantly larger response than atypical faces anywhere in the brain, including the FFA (although some subthreshold differences were observed). We propose that face processing in the FFA results in inhibitory sculpting of activation in the OFA, which accounts for this region's weaker response to typical than to atypical configurations.

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Frontal contributions to face processing differences in autism: Evidence from fMRI of inverted face processing

Journal of the International Neuropsychological Society ◽

10.1017/s135561770808140x ◽

2008 ◽

Vol 14 (6) ◽

pp. 922-932 ◽

Cited By ~ 73

Author(s):

SUSAN Y. BOOKHEIMER ◽

A. TING WANG ◽

ASHLEY SCOTT ◽

MARIAN SIGMAN ◽

MIRELLA DAPRETTO

Keyword(s):

Face Processing ◽

Visual Processing ◽

Visual Information ◽

Functional Neuroimaging ◽

Autism Spectrum ◽

Fusiform Face Area ◽

Social Significance ◽

Inverted Position ◽

Face Area ◽

Reduced Activity

AbstractFunctional neuroimaging studies of face processing deficits in autism have typically focused on visual processing regions, such as the fusiform face area (FFA), which have shown reduced activity in autism spectrum disorders (ASD), though inconsistently. We recently reported reduced activity in the inferior frontal region in ASD, implicating impaired mirror-neuron systems during face processing. In the present study, we used fMRI during a face processing task in which subjects had to match faces presented in the upright versus inverted position. Typically developing (TD) children showed a classic behavioral inversion effect, increased reaction time for inverted faces, while this effect was significantly reduced in ASD subjects. The fMRI data showed similar responses in the fusiform face area for ASD and TD children, with both groups demonstrating increased activation for inverted faces. However, the groups did differ in several brain regions implicated in social cognition, particularly prefrontal cortex and amygdala. These data suggest that the behavioral differences in processing upright versus inverted faces for TD children are related not to visual information processing but to the social significance of the stimuli. Our results are consistent with other recent studies implicating frontal and limbic dysfunction during face processing in autism. (JINS, 2008, 14, 922–932.)

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Multi-Connection Pattern Analysis: Decoding the Representational Content of Neural Communication

10.1101/046441 ◽

2016 ◽

Author(s):

Yuanning Li ◽

R. Mark Richardson ◽

Avniel Singh Ghuman

Keyword(s):

Visual Processing ◽

Pattern Analysis ◽

Activity Patterns ◽

Representational Content ◽

Neural Population ◽

Face Area ◽

Neural Communication ◽

Information Transformation ◽

Connection Pattern ◽

Processing Network

AbstractThe lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. Applying MCPA to fMRI data shows that interactions between visual cortex regions are sensitive to information that distinguishes individual natural images, suggesting that image individuation occurs through interactive computation across the visual processing network. MCPA-based representational similarity analyses (RSA) results support models of error coding in interactions among regions of the network. Further RSA analyses relate the non-linear information transformation operations between layers of a computational model (HMAX) of visual processing to the information transformation between regions of the visual processing network. Additionally, applying MCPA to human intracranial electrophysiological data demonstrates that the interaction between occipital face area and fusiform face area contains information about individual faces. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions.

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Face categorization in visual scenes may start in a higher order area of the right fusiform gyrus: evidence from dynamic visual stimulation in neuroimaging

Journal of Neurophysiology ◽

10.1152/jn.00672.2010 ◽

2011 ◽

Vol 106 (5) ◽

pp. 2720-2736 ◽

Cited By ~ 33

Author(s):

Fang Jiang ◽

Laurence Dricot ◽

Jochen Weber ◽

Giulia Righi ◽

Michael J. Tarr ◽

...

Keyword(s):

Face Processing ◽

Visual Analysis ◽

Visual Stimulation ◽

Fusiform Gyrus ◽

Differential Activation ◽

Face Area ◽

Face Categorization ◽

Visual Scenes ◽

The Right ◽

Processing Network

How a visual stimulus is initially categorized as a face by the cortical face-processing network remains largely unclear. In this study we used functional MRI to study the dynamics of face detection in visual scenes by using a paradigm in which scenes containing faces or cars are revealed progressively as they emerge from visual noise. Participants were asked to respond as soon as they detected a face or car during the noise sequence. Among the face-sensitive regions identified based on a standard localizer, a high-level face-sensitive area, the right fusiform face area (FFA), showed the earliest difference between face and car activation. Critically, differential activation in FFA was observed before differential activation in the more posteriorly located occipital face area (OFA). A whole brain analysis confirmed these findings, with a face-sensitive cluster in the right fusiform gyrus being the only cluster showing face preference before successful behavioral detection. Overall, these findings indicate that following generic low-level visual analysis, a face stimulus presented in a gradually revealed visual scene is first detected in the right middle fusiform gyrus, only after which further processing spreads to a network of cortical and subcortical face-sensitive areas (including the posteriorly located OFA). These results provide further evidence for a nonhierarchical organization of the cortical face-processing network.

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Face Processing Changes in Normal Aging Revealed by fMRI Adaptation

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_00026 ◽

2011 ◽

Vol 23 (11) ◽

pp. 3433-3447 ◽

Cited By ~ 37

Author(s):

Yunjo Lee ◽

Cheryl L. Grady ◽

Claudine Habak ◽

Hugh R. Wilson ◽

Morris Moscovitch

Keyword(s):

Older Adults ◽

Young Adults ◽

Multivariate Analysis ◽

Face Processing ◽

Healthy Aging ◽

Matching Task ◽

High Performing ◽

Facial Identity ◽

The Core ◽

Face Matching

We investigated the neural correlates of facial processing changes in healthy aging using fMRI and an adaptation paradigm. In the scanner, participants were successively presented with faces that varied in identity, viewpoint, both, or neither and performed a head size detection task independent of identity or viewpoint. In right fusiform face area (FFA), older adults failed to show adaptation to the same face repeatedly presented in the same view, which elicited the most adaptation in young adults. We also performed a multivariate analysis to examine correlations between whole-brain activation patterns and behavioral performance in a face-matching task tested outside the scanner. Despite poor neural adaptation in right FFA, high-performing older adults engaged the same face-processing network as high-performing young adults across conditions, except the one presenting a same facial identity across different viewpoints. Low-performing older adults used this network to a lesser extent. Additionally, high-performing older adults uniquely recruited a set of areas related to better performance across all conditions, indicating age-specific involvement of this added network. This network did not include the core ventral face-processing areas but involved the left inferior occipital gyrus, frontal, and parietal regions. Although our adaptation results show that the neuronal representations of the core face-preferring areas become less selective with age, our multivariate analysis indicates that older adults utilize a distinct network of regions associated with better face matching performance, suggesting that engaging this network may compensate for deficiencies in ventral face processing regions.

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Conservation of dynamic characteristics of transcriptional regulatory elements in periodic biological processes

10.1101/2020.10.12.328658 ◽

2020 ◽

Author(s):

Francis C. Motta ◽

Robert C. Moseley ◽

Bree Cummins ◽

Anastasia Deckard ◽

Steven B. Haase

Keyword(s):

Gene Regulatory Networks ◽

Regulatory Networks ◽

Large Fraction ◽

Regulatory Elements ◽

Natural World ◽

Model Systems ◽

Model Organisms ◽

Core Network ◽

The Core ◽

Gene Regulatory

AbstractCell and circadian cycles control a large fraction of cell and organismal physiology by regulating large periodic transcriptional programs that encompass anywhere from 15-80% of the genome. The gene-regulatory networks (GRNs) controlling these programs were largely identified by genetics and chromosome mapping approaches in model systems, yet it is unlikely that we have identified all of the core GRN components. Moreover, large periodic transcriptional programs controlling a variety of processes certainly exist in important non-model organisms where genetic approaches to identifying networks are expensive, time-consuming or intractable. Ideally, the core network components could be identified using data-driven approaches on the transcriptome dynamics data already available. Previous work used dynamic gene expression features to identify sets of genes with periodic behavior; our work goes further to distinguish genes by role: core versus their non-regulatory outputs. Here we present a quantitative approach that can identify nodes of GRNs controlling cell or circadian cycles across taxa. There are practical applications of the approach for network biologists, but our findings reveal something unexpected—that there are quantifiable and fundamental shared features of these unrelated GRNs controlling disparate periodic phenotypes.Author summaryCircadian rhythms, cellular division, and the developmental cycles of a multitude of living creatures, including those responsible for infectious diseases, are among the many dynamic phenomena in the natural world that are known to be the eventual output of gene regulatory networks. Identifying the small number of specialized genes that control these dynamic behaviors is of fundamental importance to our understanding of life, and our treatment of disease, but is difficult because of the sheer size of the genomes. We show that the core genes in organisms separated by millions of years of evolution have remarkable similarities that can be used to identify them.

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