Differential selectivity for dynamic versus static information in face-selective cortical regions

Pitcher, David; Dilks, Daniel D.; Saxe, Rebecca; Triantafyllou, Christina; Kanwisher, Nancy

doi:10.1016/j.neuroimage.2011.03.067

Cited by 412 publications

(472 citation statements)

References 53 publications

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“…S1), he lost the upper left visual field and a large part of his upper right visual field and became severely prosopagnosic. All core face areas (the FFA, occipital face area, and face area in posterior superior temporal sulcus) were found bilaterally (except left occipital face area, which could not be identified), using a contrast of dynamic faces greater than dynamic objects (52). These face-selective areas, however, showed lower percentage signal changes to faces in Herschel than in controls (39).…”

Section: Methodsmentioning

confidence: 82%

Normal acquisition of expertise with greebles in two cases of acquired prosopagnosia

Rezlescu

Barton

Pitcher

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

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Face recognition is generally thought to rely on different neurocognitive mechanisms than most types of objects, but the specificity of these mechanisms is debated. One account suggests the mechanisms are specific to upright faces, whereas the expertise view proposes the mechanisms operate on objects of high withinclass similarity with which an observer has become proficient at rapid individuation. Much of the evidence cited in support of the expertise view comes from laboratory-based training experiments involving computer-generated objects called greebles that are designed to place face-like demands on recognition mechanisms. A fundamental prediction of the expertise hypothesis is that recognition deficits with faces will be accompanied by deficits with objects of expertise. Here we present two cases of acquired prosopagnosia, Herschel and Florence, who violate this prediction: Both show normal performance in a standard greeble training procedure, along with severe deficits on a matched face training procedure. Herschel and Florence also meet several response time criteria that advocates of the expertise view suggest signal successful acquisition of greeble expertise. Furthermore, Herschel's results show that greeble learning can occur without normal functioning of the right fusiform face area, an area proposed to mediate greeble expertise. The marked dissociation between face and greeble expertise undermines greeble-based claims challenging face-specificity and indicates face recognition mechanisms are not necessary for object recognition after laboratorybased training.

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Section: Methodsmentioning

confidence: 82%

Normal acquisition of expertise with greebles in two cases of acquired prosopagnosia

Rezlescu

Barton

Pitcher

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

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“…Empirical evidence indicates that the task could elicit reliable activations of FSRs across subjects (Fox et al, 2009;Pitcher et al, 2011a). Specifically, the dynamic face localizer data were acquired over three blocked-design functional runs, each of which lasted 198 s. Each run contained two block sets, intermixed with three 18-s rest blocks at the beginning, middle and end of the run.…”

Section: Localizer Paradigmmentioning

confidence: 99%

“…Among them, the most reliable regions are located in the occipitotemporal cortex. Specifically, one FSR is in the inferior occipital gyrus (IOG, or occipital face area, OFA) (Gauthier et al, 2000;Liu et al, 2010); three FSRs are in the fusiform gyrus (FG, or fusiform face area, FFA), located in the posterior, middle and anterior parts of the FG (i.e., pFFA, mFFA, and aFFA) (Engell and McCarthy, 2013;Gauthier et al, 1999;Kanwisher et al, 1997;Nestor et al, 2011;Weiner and Grill-Spector, 2010), and three FSRs are in the superior temporal sulcus (STS), located at the posterior continuation of the STS, the posterior STS, and the anterior STS (i.e., pcSTS, pSTS, and aSTS) (Pinsk et al, 2009;Pitcher et al, 2011a;Puce et al, 1998). These regions are thought to process different aspects of faces : the region located in the IOG is involved in early perception of facial features; those regions located in the FG analyze the invariant aspects of faces that underlie recognition of individuals (Kanwisher et al, 1997;McCarthy et al, 1997;Pitcher et al, 2011b) and those regions located in the STS process the changeable aspects of faces such as expressions (Phillips et al, 1997), direction of eye gaze, and lip movements, for facilitating social communication (Allison et al, 2000;Hoffman and Haxby, 2000;Lahnakoski et al, 2012;Puce et al, 1998).…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, to capture reliably the variability of the FSRs, 202 subjects were scanned with a robust dynamic face localizer (Fox et al, 2009;Pitcher et al, 2011a) in the same scanner and with the same MR protocol. First, the six well-studied FSRs, the OFA, pFFA, aFFA, pcSTS, pSTS, and aSTS, were delineated in each individual using a semi-automated procedure.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying interindividual variability and asymmetry of face-selective regions: A probabilistic functional atlas

et al. 2015

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Face-selective regions (FSRs) are among the most widely studied functional regions in the human brain. However, individual variability of the FSRs has not been well quantified. Here we use functional magnetic resonance imaging (fMRI) to localize the FSRs and quantify their spatial and functional variabilities in 202 healthy adults. The occipital face area (OFA), posterior and anterior fusiform face areas (pFFA and aFFA), posterior continuation of the superior temporal sulcus (pcSTS), and posterior and anterior STS (pSTS and aSTS) were delineated for each individual with a semi-automated procedure. A probabilistic atlas was constructed to characterize their interindividual variability, revealing that the FSRs were highly variable in location and extent across subjects. The variability of FSRs was further quantified on both functional (i.e., face selectivity) and spatial (i.e., volume, location of peak activation, and anatomical location) features. Considerable interindividual variability and rightward asymmetry were found in all FSRs on these features. Taken together, our work presents the first effort to characterize comprehensively the variability of FSRs in a large sample of healthy subjects, and invites future work on the origin of the variability and its relation to individual differences in behavioral performance. Moreover, the probabilistic functional atlas will provide an adequate spatial reference for mapping the face network.

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“…An fMRI localizer using dynamic stimuli was used to individually identify the TMS target sites (rOFA and rEBA) in each participant (Pitcher et al, 2011a). Functional data were acquired over four blocked-design functional runs each lasting 234 s. Scanning was performed in a 3.0 T Siemens Trio scanner at the A.…”

Section: Brain Imagingmentioning

confidence: 99%

Two Critical and Functionally Distinct Stages of Face and Body Perception

et al. 2012

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Cortical regions that respond preferentially to particular object categories, such as faces and bodies, are essential for visual perception of these object categories. However, precisely when these regions play a causal role in recognition of their preferred categories is unclear. Here we addressed this question using transcranial magnetic stimulation (TMS). Across a series of experiments, TMS was delivered over the functionally localized right occipital face area (rOFA) or right extrastriate body area (rEBA) at different latencies, up to 150 ms, after stimulus onset while adult human participants performed delayed match-to-sample tasks on face and body stimuli. Results showed that TMS disrupted task performance during two temporally distinct time periods after stimulus onset, the first at 40/50 ms and the second at 100/110 ms. These two time periods exhibited functionally distinct patterns of impairment: TMS delivered during the early time period (at 40/50 ms) disrupted task performance for both preferred (faces at rOFA and bodies at rEBA) and nonpreferred (bodies at rOFA and faces at rEBA) categories. In contrast, TMS delivered during the later time period (at 100/110 ms) disrupted task performance for the preferred category only of each area (faces at rOFA and bodies at rEBA). These results indicate that category-selective cortical regions are critical for two functionally distinct stages of visual object recognition: an early, presumably preparatory stage that is not category selective occurring almost immediately after stimulus onset, followed by a later stage of category-specific perceptual processing.

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Differential selectivity for dynamic versus static information in face-selective cortical regions

Cited by 412 publications

References 53 publications

Normal acquisition of expertise with greebles in two cases of acquired prosopagnosia

Normal acquisition of expertise with greebles in two cases of acquired prosopagnosia

Quantifying interindividual variability and asymmetry of face-selective regions: A probabilistic functional atlas

Two Critical and Functionally Distinct Stages of Face and Body Perception

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