Individual faces elicit distinct response patterns in human anterior temporal cortex

Kriegeskorte, Nikolaus; Formisano, Elia; Sorger, Bettina; Goebel, Rainer

doi:10.1073/pnas.0705654104

Cited by 470 publications

(477 citation statements)

References 84 publications

(181 reference statements)

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“…Regions exhibiting RS receive predominantly bottom-up information concerning low-level physical stimulus properties (Kriegeskorte, Formisano, Sorger, & Goebel, 2007), whereas regions exhibiting RE receive both bottom-up and topdown information to strengthen object representation and establish perceptual expectations (de Gardelle et al, 2013). The clusters we found in HG and STG were both contained within the TVA.…”

Section: Discussionmentioning

confidence: 56%

Amygdala and auditory cortex exhibit distinct sensitivity to relevant acoustic features of auditory emotions

Pannese

Grandjean

Frühholz

2016

Cortex

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Amygdala Temporal voice area Auditory emotions fMRI a b s t r a c tDiscriminating between auditory signals of different affective value is critical to successful social interaction. It is commonly held that acoustic decoding of such signals occurs in the auditory system, whereas affective decoding occurs in the amygdala. However, given that the amygdala receives direct subcortical projections that bypass the auditory cortex, it is possible that some acoustic decoding occurs in the amygdala as well, when the acoustic features are relevant for affective discrimination. We tested this hypothesis by combining functional neuroimaging with the neurophysiological phenomena of repetition suppression (RS) and repetition enhancement (RE) in human listeners. Our results show that both amygdala and auditory cortex responded differentially to physical voice features, suggesting that the amygdala and auditory cortex decode the affective quality of the voice not only by processing the emotional content from previously processed acoustic features, but also by processing the acoustic features themselves, when these are relevant to the identification of the voice's affective value. Specifically, we found that the auditory cortex is sensitive to spectral high-frequency voice cues when discriminating vocal anger from vocal fear and joy, whereas the amygdala is sensitive to vocal pitch when discriminating between negative vocal emotions (i.e., anger and fear). Vocal pitch is an instantaneously recognized voice feature, which is potentially transferred to the amygdala by direct subcortical projections. These results together provide evidence that, besides the auditory cortex, the amygdala too processes acoustic information, when this is relevant to the discrimination of auditory emotions.© 2016 Elsevier Ltd. All rights reserved. Available online at www.sciencedirect.com ScienceDirectJournal homepage: www.elsevier.com/locate/cortex c o r t e x 8 5 ( 2 0 1 6 ) 1 1 6 e1 2 5http://dx

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Section: Discussionmentioning

confidence: 56%

Amygdala and auditory cortex exhibit distinct sensitivity to relevant acoustic features of auditory emotions

Pannese

Grandjean

Frühholz

2016

Cortex

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“…In this study, the cross‐validated LDC (Kriegeskorte, Formisano, Sorger, & Goebel, 2007; Walther et al, 2016) between the responses to the two different orientations is used as the metric for investigating multivariate effects. Similar to a univariate test, the LDC is effectively a contrast between two conditions measured on a discriminant.…”

Section: Methodsmentioning

confidence: 99%

Prospective motion correction improves the sensitivity of fMRI pattern decoding

Huang

Carlin

Alink

et al. 2018

Human Brain Mapping

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We evaluated the effectiveness of prospective motion correction (PMC) on a simple visual task when no deliberate subject motion was present. The PMC system utilizes an in‐bore optical camera to track an external marker attached to the participant via a custom‐molded mouthpiece. The study was conducted at two resolutions (1.5 mm vs 3 mm) and under three conditions (PMC On and Mouthpiece On vs PMC Off and Mouthpiece On vs PMC Off and Mouthpiece Off). Multiple data analysis methods were conducted, including univariate and multivariate approaches, and we demonstrated that the benefit of PMC is most apparent for multi‐voxel pattern decoding at higher resolutions. Additional testing on two participants showed that our inexpensive, commercially available mouthpiece solution produced comparable results to a dentist‐molded mouthpiece. Our results showed that PMC is increasingly important at higher resolutions for analyses that require accurate voxel registration across time.

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“…Some reports suggest, based on activity in the ventral visual pathway, that brainreading algorithms have weak but above-chance classification performance on withincategory discriminations (for example, for pigeons versus seagulls or for fearful versus happy faces) [32][33][34] . Conversely, even high-resolution scans have so far failed to find abovechance classification performance for discriminating the identity of faces based on activity in the FFA 35 , or for discriminating different body parts (for example, hands versus legs) from activity in the EBA (R. F. Schwarzlose and N.G.K., unpublished observations). nevertheless, future studies using high-resolution scans and/or multi-voxel pattern analyses might find further evidence for functional organization of object properties other than category membership.…”

Section: Box 1 | Recent Advances Through Functional Mrimentioning

confidence: 99%

Interpreting fMRI data: maps, modules and dimensions

2008

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Neuroimaging research over the past decade has revealed a detailed picture of the functional organization of the human brain. Here we focus on two fundamental questions that are raised by the detailed mapping of sensory and cognitive functions and illustrate these questions with findings from the object-vision pathway. First, are functionally specific regions that are located close together best understood as distinct cortical modules or as parts of a larger-scale cortical map? Second, what functional properties define each cortical map or module? We propose a model in which overlapping continuous maps of simple features give rise to discrete modules that are selective for complex stimuli.Advances in brain imaging technology (especially functional MRI (fMRI)) have radically improved our understanding of the functional organization of the human brain (BOX 1). In this Review we describe the organization of the ventral visual pathway, which is characterized by strong selectivity for particular object categories (for example, faces and bodies) at the level of both individual neurons and larger cortical regions. We then consider two central questions: whether this organization reflects maps or modules, and what properties are mapped. In each case we derive clues from the literature on the primary sensory cortex, in which cortical maps have been studied extensively using electrophysiology in animals. We find that apparently modular cortical regions, such as orientation columns and face-selective regions, might be parts of larger maps, and show that it is a substantial challenge to determine the basic properties and dimensions that describe functional organization most parsimoniously. We then propose a new framework that reconciles the existence of graded cortical maps and distinct functional modules. In this framework, the strong category selectivity that exists for faces and other objects might arise from the nonlinear combination of multiple correlated maps for simpler stimulus properties. The ventral visual pathwayThe ventral visual pathway comprises a large cortical region that occupies the ventral and lateral surfaces of the occipital and temporal lobes (FIG. 1). A substantial proportion of fMRI voxels in this pathway are 'object-selective' -that is, they respond more strongly when people view images of objects than when people view scrambled versions of these objects or texture patterns. This object-selective region is often referred to as the lateral occipital complex (LOC) 1 . The LOC has little selectivity for particular stimulus categories 2-4 , but several regions of NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript cortex near the LOC are selective for particular object categories: they respond at least twice as strongly to their 'preferred' stimuli than to other stimuli. For example, in essentially all humans cortical regions can be found that respond selectively to faces (the fusiform face area (FFA) 5,6 and, in many individuals, the occipital face area (OFA)) 7,8 , to pl...

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Individual faces elicit distinct response patterns in human anterior temporal cortex

Cited by 470 publications

References 84 publications

Amygdala and auditory cortex exhibit distinct sensitivity to relevant acoustic features of auditory emotions

Amygdala and auditory cortex exhibit distinct sensitivity to relevant acoustic features of auditory emotions

Prospective motion correction improves the sensitivity of fMRI pattern decoding

Interpreting fMRI data: maps, modules and dimensions

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