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1 tional structure, and the neural dynamics of face processing.
2 ine face-training program targeting holistic face processing.
3 ces, particularly in regions associated with face processing.
4 ipital gyrus (lIOC), regions associated with face processing.
5 gyrus compared with the control group during face processing.
6 reased activity in brain regions involved in face processing.
7 pped into two relatively disparate stages of face processing.
8 face-sensitive N170 component and configural face processing.
9 ggesting links between the N170 and holistic face processing.
10 he ERP signatures of featural and configural face processing.
11 ecognition as well as hierarchical models of face processing.
12 rgely bilaterally distributed model for self-face processing.
13 buted cortical network that subserves normal face processing.
14 y an artificial deep neural network model of face processing.
15 ngs of a low-spatial frequency advantage for face processing.
16 unctional imaging of orientation, motion and face processing.
17 fusiform face area, that is specialized for face processing.
18 le of early experience in the development of face processing.
19 ses from human visual cortex specialized for face processing.
20 augmented in regions involved in emotion and face processing.
21 atial deficits and enhanced emotionality and face processing.
22 e provide a challenge for existing models of face processing.
23 is unique to language or might also apply to face processing.
24 rior temporal regions are involved in visual face processing.
25 ntradictory modular and distributed modes of face processing.
26 d to the functional specialization of normal face processing.
27 dies have implicated other cortical areas in face processing.
28 a specific gene may cause ASD-like atypical face processing.
29 shed from other temporal regions involved in face processing.
30 t with an activation pattern associated with face processing.
31 ng genetic associations of ASD-like atypical face processing.
32 e ensembles and its relationship with single-face processing.
33 e species may differ in the details of their face processing.
34 arching effects than neurotype on configural face processing.
35 f inferotemporal (IT) cortex specialized for face processing.
36 speech and whether this affects simultaneous face processing.
37 s, and amygdala, enables rapid and automatic face processing.
38 at face-selective brain areas are central to face processing.
39 inhibitor (SSRI), on brain activation during face processing.
40 fferences within brain regions that subserve face processing.
41 and neural activity in response to emotional face processing.
42 Schizophrenia is associated with impaired face processing.
43 in both humans and monkeys, with a focus on face processing.
44 gen level-dependent responses during fearful faces processing.
45 more prominent in unfamiliar versus familiar face processing?
47 methodological concern in the measurement of face processing abilities in schizophrenia, namely, that
49 amygdala-related connectivity during fearful face processing after the placebo treatment in heroin-de
50 eurocognitive model with three core streams; face processing along these streams occurs in a parallel
51 ral correlates of adult social phobia during face processing also manifest in adolescent social phobi
53 um disorder (ASD) is associated with altered face processing and decreased activity in brain regions
54 ASD and suggest that oxytocin might promote face processing and eye contact in individuals with ASD
56 t sex and neurotype influence longer latency face processing and implicates cognitive rather than per
57 ropeptide oxytocin has been shown to promote face processing and modulate brain activity in healthy a
58 ption is to identify brain areas involved in face processing and simultaneously understand the timing
60 d in WS, despite abnormalities in aspects of face processing and structural alterations in the fusifo
61 o computations associated with both central (face processing) and peripheral (scene processing) visua
62 ith view-point changes, measures of holistic face processing, and a 5-day diary to quantify potential
65 duals with 22q11.22DS, while motor feedback, face processing, and emotional memory processes are more
66 ity is generated in participants with normal face processing, and how functional abnormalities associ
67 ose elicited by social cognition rather than face processing, and included regions at the prefrontal
68 categorical emotional perception, configural face processing, and perceptual organization in mental i
69 e occipital face area (OFA), a key region in face processing, and the lateral occipital (LO) cortex,
71 and recognition; is compatible with holistic face processing; and constitutes the first quantitative
72 Thus, abnormal amygdala activation during face processing appears to be more pervasive in children
73 orted effects of gaze direction on emotional face processing are likely to occur once the face is det
75 Two of the most robust markers for "special" face processing are the behavioral face-inversion effect
77 s, brain alterations in social, language and face processing areas enhance the prediction of the chil
78 in regions including associative visual and face processing areas was strongly correlated with the c
79 ghlighting that the functional properties of face-processing areas conform to the principles of predi
80 not retinotopically organized, as with human face-processing areas, showing foveal bias but lacking a
82 that the well-known right lateralization of face processing arises from imbalanced intra- and interh
83 s to examine brain function during emotional face processing as a predictor of response to treatment
84 high-spatial frequency information in early face processing, as indexed by the N170 face-sensitive E
85 dimension in unfamiliar relative to familiar face processing, both in early perceptual stages as well
87 firm the amygdala's pivotal role in abnormal face processing by people with ASD at the cellular level
88 eye movements play a functional role during face processing by providing the neural system with the
89 ial cognition in autism [3], we investigated face processing by using the "bubbles" method [4] to mea
90 How this information is exchanged between face-processing centers and brain areas supporting socia
92 the magnitude of activation within emotional face processing circuitry; and (ii) functional connectiv
93 isual cortex, and subcortex during emotional face processing (cluster-level P corrected for familywis
94 ical gaze, aberrant amygdala activity during face processing compared with neurotypically developed (
95 ess activation in neural networks related to face processing, compared with healthy subjects, and to
100 ght fusiform gyral activity during emotional face processing, diagnosis of major depressive disorder,
103 alization for upright (compared to inverted) face processing emerges in the visual system, the presen
104 n coefficient = 0.57), specific to emotional face processing (F = 17.97, P < .001), and independent o
106 se results reveal differential influences on face processing from attention and emotion, with the amy
109 ace space, and other key properties of human face processing have been identified at the single neuro
110 age features, behavioral and fMRI studies of face processing have been interpreted as incompatible wi
113 intermediate representation of a three-level face-processing hierarchy in the brain: mirror-symmetric
114 FA) is thought to be a computational hub for face processing; however, temporal dynamics of face info
115 ion, we examined neural mechanisms mediating face processing in 22 youths (mean age 14.21 +/- 3.11 yr
116 e effects of oxytocin on the neural basis of face processing in adults with Asperger syndrome (AS).
117 circuit coupling during fearful versus happy face processing in anxious, but not healthy, participant
118 em-wide circuits are selectively altered for face processing in ASD and enhance our understanding of
122 ral lobe served as the major network hub for face processing in controls, this was not the case for t
125 findings start to reveal the time course of face processing in humans, and provide powerful new cons
127 facial features found in the middle patch of face processing in IT as documented by Freiwald, Tsao, a
128 ception task, none of the regions supporting face processing in normals were found to be significantl
129 cortical topology of the neural circuit for face processing in participants with an impairment in fa
131 inspired by electrophysiological evidence on face processing in primates, is able to generate represe
134 ntials that have been studied in relation to face processing in schizophrenia, but the results have b
137 le of facial features in the middle patch of face processing in the macaque IT cortex may be closely
140 the state of the somatosensory system during face processing, in 50% of trials we evoked somatosensor
141 tensive network of brain regions involved in face processing including the fusiform gyrus (FFG) and p
142 al areas known to participate in emotion and face processing, including the amygdala, orbital and med
144 illnesses such as autism, in which atypical face processing is a hallmark of social dysfunction.
147 umans and macaque monkeys, socially relevant face processing is accomplished via a distributed functi
150 lography (M/EEG) studies have suggested that face processing is extremely rapid, indeed faster than a
153 on and instead argue that the development of face processing is guided by the same ubiquitous rules t
156 at the functional-division-of-labor model on face processing is over-simplified, and that coding stra
158 ural systems that underlie both language and face processing is revealed through studies using event-
159 behavior and brain responses have shown that face processing is tuned to selective orientation ranges
161 dy, we investigated age-dependent changes in face processing lateralization from infancy to adulthood
162 a visual-limbic subnetwork during emotional face processing may be a functional connectomic intermed
163 on has suggested that the systems underlying face processing may be similarly sculpted by experience
165 he OFA is the first stage in two influential face-processing models, both of which suggest that it co
168 pathways, suggests that core elements of the face processing network were present in the common anthr
169 imaging modalities within key regions of the face processing network, such as the fusiform gyrus (FFG
172 d been studied in multiple areas of the core face-processing network before, as well as facial expres
173 s known to comprise the distributed cortical face-processing network in humans, including superior te
174 hus, two temporal lobe areas extend the core face-processing network into a familiar face-recognition
175 personally familiar faces engage the macaque face-processing network more than unfamiliar faces.
177 rvature-processing network to the well-known face-processing network suggests a possible functional l
178 f connectivity from posterior regions of the face-processing network to the lateral ventral prefronta
179 data revealed that although the nodes of the face-processing network were tightly coupled at rest, th
180 ignment was to review the development of the face-processing network, an assignment that carries the
181 ividual faces in core posterior areas of the face-processing network, familiar face recognition emerg
183 ditional regions not known to be part of the face-processing network, suggesting that face motions ma
186 the modulatory effects of gaze on emotional face processing occur also at this level, then the gaze-
187 latory effect of gaze direction on emotional face processing occurs outside of conscious awareness.
191 fusiform region in both early and midlatency face-processing operations, with only the latter showing
193 lvement of somatosensory cortex (SCx) during face processing over and above visual responses, we dire
194 fects on components previously implicated in face processing: P1 (positive component ~100 ms post-sti
197 this frontal network specialized for social face processing predates the separation between Platyrrh
198 tal cortical areas typically associated with face processing predicted individual numerical problem s
200 suggest that separate streams for person and face processing reach anterior temporal areas positioned
201 and reward, affective, salience, memory, and face-processing regions during mother's voice perception
203 ions modulate functional MRI activity in the face-processing regions of the macaque monkey's amygdala
204 hat opponent social categories coactivate in face-processing regions, which compete and may resolve i
205 In boys with autism, language and social/face processing-related regions displayed abnormal asymm
206 f WMS is a dissociation between language and face processing (relative strengths) and spatial cogniti
209 We measured the fast temporal dynamics of face processing simultaneously across the human temporal
210 like individual face recognition, configural face processing, social eavesdropping, and transitive in
211 functional specialization in the domains of face processing, social interaction understanding, and m
212 mic computational role FFA plays in multiple face processing stages and indicate what information is
216 tives but not in controls during threatening face processing, suggesting a compensatory mechanism giv
218 differences in activation in the subcortical face processing system (superior colliculus, pulvinar nu
220 gest less specialization or expertise of the face processing system in autism, particularly in recogn
221 in face memory is dependent on how well the face processing system interacts with other processing n
223 ding at which mechanistic level the autistic face processing system may be particularly different, as
224 hese single-cell recordings within the human face processing system provide vital experimental eviden
225 work identifies a missing link in the human face processing system that specifically processes famil
228 olia in a species known to possess a complex face-processing system [8-10]: the rhesus monkey (Macaca
231 s thus force a rethinking of the role of the face-processing system in representing subject-directed
232 Here, we investigate whether the macaque face-processing system, a three-level hierarchy in the v
234 sed increased fMRI activation throughout the face-processing system; microstimulation of the body pat
235 ubjects completed a well-validated emotional face processing task during functional magnetic resonanc
236 al MRI to compare amygdala activity during a face processing task in children and adults with bipolar
237 ctional magnetic resonance imaging emotional face processing task to replicate the previously reporte
238 the current study, participants engaged in a face processing task while brain responses were recorded
240 ate, and bilateral insula during the emotion face-processing task consistent with effects previously
244 tterns using BOLD fMRI during an (1) emotion face-processing task, (2) inspiratory breathing load tas
246 perceptual, and whether they extend to other face processing tasks (e.g., identifying emotion, age, a
247 of the background tests, on any of the other face processing tasks, and even for recognition of any o
249 o visuospatial tasks, but not during the two face processing tasks, we found bilateral intraparietal
250 y structured fibre tracts, enabling coherent face processing that underpins behaviour and cognition.
251 uli that elicit a well known marker of early face processing, the N170 event-related potential (ERP).
252 eted the three standard measures of holistic face processing: the face inversion, part-whole, and com
254 and showed significantly increased holistic face processing to the point of being similar to that of
257 face recognition algorithms to model primate face processing, we demonstrate that the face patterns o
258 he N170, an event-related potential index of face processing, we find that images that elicit larger
259 ned influences of familiarity and priming on face processing were examined as contrast polarity was m
260 with poorer social sensitivity and emotional face processing while also associated with gene expressi
261 results support a multiple-route network of face processing with nonhierarchical components and shed
262 , supporting dual routes (dorsal-ventral) in face processing within IT cortex as well as between IT c
263 sample to study the cross-modal signature of face processing within the FFG across four imaging modal