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Zhu H, Ge Y, Bratch A, Yuille A, Kay K, Kersten D. Natural scenes reveal diverse representations of 2D and 3D body pose in the human brain. Proc Natl Acad Sci U S A 2024; 121:e2317707121. [PMID: 38830105 PMCID: PMC11181088 DOI: 10.1073/pnas.2317707121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 04/25/2024] [Indexed: 06/05/2024] Open
Abstract
Human pose, defined as the spatial relationships between body parts, carries instrumental information supporting the understanding of motion and action of a person. A substantial body of previous work has identified cortical areas responsive to images of bodies and different body parts. However, the neural basis underlying the visual perception of body part relationships has received less attention. To broaden our understanding of body perception, we analyzed high-resolution fMRI responses to a wide range of poses from over 4,000 complex natural scenes. Using ground-truth annotations and an application of three-dimensional (3D) pose reconstruction algorithms, we compared similarity patterns of cortical activity with similarity patterns built from human pose models with different levels of depth availability and viewpoint dependency. Targeting the challenge of explaining variance in complex natural image responses with interpretable models, we achieved statistically significant correlations between pose models and cortical activity patterns (though performance levels are substantially lower than the noise ceiling). We found that the 3D view-independent pose model, compared with two-dimensional models, better captures the activation from distinct cortical areas, including the right posterior superior temporal sulcus (pSTS). These areas, together with other pose-selective regions in the LOTC, form a broader, distributed cortical network with greater view-tolerance in more anterior patches. We interpret these findings in light of the computational complexity of natural body images, the wide range of visual tasks supported by pose structures, and possible shared principles for view-invariant processing between articulated objects and ordinary, rigid objects.
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Affiliation(s)
- Hongru Zhu
- Department of Cognitive Science, Johns Hopkins University, Baltimore, MD21218
| | - Yijun Ge
- Department of Psychology, University of Minnesota, Minneapolis, MN55455
- Laboratory for Consciousness, Riken Center for Brain Science, Wako, Saitama3510198, Japan
| | - Alexander Bratch
- Department of Psychology, University of Minnesota, Minneapolis, MN55455
| | - Alan Yuille
- Department of Cognitive Science, Johns Hopkins University, Baltimore, MD21218
| | - Kendrick Kay
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN55455
| | - Daniel Kersten
- Department of Psychology, University of Minnesota, Minneapolis, MN55455
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2
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Abassi E, Papeo L. Category-Selective Representation of Relationships in the Visual Cortex. J Neurosci 2024; 44:e0250232023. [PMID: 38124013 PMCID: PMC10860595 DOI: 10.1523/jneurosci.0250-23.2023] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 09/29/2023] [Accepted: 10/14/2023] [Indexed: 12/23/2023] Open
Abstract
Understanding social interaction requires processing social agents and their relationships. The latest results show that much of this process is visually solved: visual areas can represent multiple people encoding emergent information about their interaction that is not explained by the response to the individuals alone. A neural signature of this process is an increased response in visual areas, to face-to-face (seemingly interacting) people, relative to people presented as unrelated (back-to-back). This effect highlighted a network of visual areas for representing relational information. How is this network organized? Using functional MRI, we measured the brain activity of healthy female and male humans (N = 42), in response to images of two faces or two (head-blurred) bodies, facing toward or away from each other. Taking the facing > non-facing effect as a signature of relation perception, we found that relations between faces and between bodies were coded in distinct areas, mirroring the categorical representation of faces and bodies in the visual cortex. Additional analyses suggest the existence of a third network encoding relations between (nonsocial) objects. Finally, a separate occipitotemporal network showed the generalization of relational information across body, face, and nonsocial object dyads (multivariate pattern classification analysis), revealing shared properties of relations across categories. In sum, beyond single entities, the visual cortex encodes the relations that bind multiple entities into relationships; it does so in a category-selective fashion, thus respecting a general organizing principle of representation in high-level vision. Visual areas encoding visual relational information can reveal the processing of emergent properties of social (and nonsocial) interaction, which trigger inferential processes.
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Affiliation(s)
- Etienne Abassi
- Institut des Sciences Cognitives-Marc Jeannerod, UMR5229, Centre National de la Recherche Scientifique (CNRS), Université Claude Bernard Lyon 1, Bron 69675, France
| | - Liuba Papeo
- Institut des Sciences Cognitives-Marc Jeannerod, UMR5229, Centre National de la Recherche Scientifique (CNRS), Université Claude Bernard Lyon 1, Bron 69675, France
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3
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Coutanche MN, Sauter J, Akpan E, Buckser R, Vincent A, Caulfield MK. Novel approaches to functional lateralization: Assessing information in activity patterns across hemispheres and more accurately identifying structural homologues. Neuropsychologia 2023; 190:108684. [PMID: 37741550 DOI: 10.1016/j.neuropsychologia.2023.108684] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 05/16/2023] [Accepted: 09/20/2023] [Indexed: 09/25/2023]
Abstract
Functional lateralization is typically measured by comparing activation levels across the right and left hemispheres of the brain. Significant additional information, however, exists within distributed multi-voxel patterns of activity - a format not detectable by traditional activation-based analysis of functional magnetic resonance imaging (fMRI) data. We introduce and test two methods -one anatomical, one functional- that allow hemispheric information asymmetries to be detected. We first introduce and apply a novel tool that draws on brain 'surface fingerprints' to pair every location in one hemisphere with its hemispheric homologue. We use anatomical data to show that this approach is more accurate than the common distance-from-midline method for comparing bilateral regions. Next, we introduce a complementary analysis method that quantifies multivariate laterality in functional data. This new 'multivariate Laterality Index' (mLI) reflects both quantitative and qualitative information-differences across homologous activity patterns. We apply the technique here to functional data collected as participants viewed faces and non-faces. Using the previously generated surface fingerprints to pair-up homologous searchlights in each hemisphere, we use the novel multivariate laterality technique to identify face-information asymmetries across right and left counterparts of the fusiform gyrus, inferior temporal gyrus, superior parietal lobule, and early visual areas. The typical location of the fusiform face area has greater information asymmetry for faces than for shapes. More generally, we argue that the field should consider an information-based approach to lateralization.
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Affiliation(s)
- Marc N Coutanche
- Department of Psychology, University of Pittsburgh, PA, 15260, USA; Learning Research & Development Center, University of Pittsburgh, PA, 15260, USA; Brain Institute, University of Pittsburgh, PA, 15260, USA.
| | - Jake Sauter
- State University of New York at Oswego, Oswego, NY, USA
| | - Essang Akpan
- Department of Psychology, University of Pittsburgh, PA, 15260, USA; Learning Research & Development Center, University of Pittsburgh, PA, 15260, USA
| | - Rae Buckser
- Department of Psychology, University of Pittsburgh, PA, 15260, USA; Learning Research & Development Center, University of Pittsburgh, PA, 15260, USA
| | - Augusta Vincent
- Department of Psychology, University of Pittsburgh, PA, 15260, USA; Learning Research & Development Center, University of Pittsburgh, PA, 15260, USA
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4
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Zhang M, Yu L, Zhang K, Du B, Zhan B, Jia S, Chen S, Han F, Li Y, Liu S, Yi X, Liu S, Luo W. Construction and validation of the Dalian emotional movement open-source set (DEMOS). Behav Res Methods 2023; 55:2353-2366. [PMID: 35931937 DOI: 10.3758/s13428-022-01887-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/24/2022] [Indexed: 11/08/2022]
Abstract
Human body movements are important for emotion recognition and social communication and have received extensive attention from researchers. In this field, emotional biological motion stimuli, as depicted by point-light displays, are widely used. However, the number of stimuli in the existing material library is small, and there is a lack of standardized indicators, which subsequently limits experimental design and conduction. Therefore, based on our prior kinematic dataset, we constructed the Dalian Emotional Movement Open-source Set (DEMOS) using computational modeling. The DEMOS has three views (i.e., frontal 0°, left 45°, and left 90°) and in total comprises 2664 high-quality videos of emotional biological motion, each displaying happiness, sadness, anger, fear, disgust, and neutral. All stimuli were validated in terms of recognition accuracy, emotional intensity, and subjective movement. The objective movement for each expression was also calculated. The DEMOS can be downloaded for free from https://osf.io/83fst/ . To our knowledge, this is the largest multi-view emotional biological motion set based on the whole body. The DEMOS can be applied in many fields, including affective computing, social cognition, and psychiatry.
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Affiliation(s)
- Mingming Zhang
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, China
- Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, 116029, China
| | - Lu Yu
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, China
- Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, 116029, China
| | - Keye Zhang
- School of Social and Behavioral Sciences, Nanjing University, Nanjing, 210023, China
| | - Bixuan Du
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, China
- Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, 116029, China
| | - Bin Zhan
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shuxin Jia
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, China
- Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, 116029, China
| | - Shaohua Chen
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, China
- Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, 116029, China
| | - Fengxu Han
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, China
- Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, 116029, China
| | - Yiwen Li
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, China
- Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, 116029, China
| | - Shuaicheng Liu
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, China
- Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, 116029, China
| | - Xi Yi
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, China
- Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, 116029, China
| | - Shenglan Liu
- School of Innovation and Entrepreneurship, Dalian University of Technology, Dalian, 116024, China.
- Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024, China.
| | - Wenbo Luo
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, 116029, China.
- Key Laboratory of Brain and Cognitive Neuroscience, Liaoning Province, Dalian, 116029, China.
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Marrazzo G, De Martino F, Lage-Castellanos A, Vaessen MJ, de Gelder B. Voxelwise encoding models of body stimuli reveal a representational gradient from low-level visual features to postural features in occipitotemporal cortex. Neuroimage 2023:120240. [PMID: 37348622 DOI: 10.1016/j.neuroimage.2023.120240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 06/16/2023] [Accepted: 06/19/2023] [Indexed: 06/24/2023] Open
Abstract
Research on body representation in the brain has focused on category-specific representation, using fMRI to investigate the response pattern to body stimuli in occipitotemporal cortex without so far addressing the issue of the specific computations involved in body selective regions, only defined by higher order category selectivity. This study used ultra-high field fMRI and banded ridge regression to investigate the coding of body images, by comparing the performance of three encoding models in predicting brain activity in occipitotemporal cortex and specifically the extrastriate body area (EBA). Our results suggest that bodies are encoded in occipitotemporal cortex and in the EBA according to a combination of low-level visual features and postural features.
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Affiliation(s)
- Giuseppe Marrazzo
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Limburg 6200 MD, Maastricht, The Netherlands
| | - Federico De Martino
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Limburg 6200 MD, Maastricht, The Netherlands; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States and Department of NeuroInformatics
| | - Agustin Lage-Castellanos
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Limburg 6200 MD, Maastricht, The Netherlands; Cuban Center for Neuroscience, Street 190 e/25 and 27 Cubanacán Playa Havana, CP 11600, Cuba
| | - Maarten J Vaessen
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Limburg 6200 MD, Maastricht, The Netherlands
| | - Beatrice de Gelder
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Limburg 6200 MD, Maastricht, The Netherlands.
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Wang R, Lu X, Jiang Y. Distributed and hierarchical neural encoding of multidimensional biological motion attributes in the human brain. Cereb Cortex 2023; 33:8510-8522. [PMID: 37118887 PMCID: PMC10786095 DOI: 10.1093/cercor/bhad136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 03/31/2023] [Accepted: 04/01/2023] [Indexed: 04/30/2023] Open
Abstract
The human visual system can efficiently extract distinct physical, biological, and social attributes (e.g. facing direction, gender, and emotional state) from biological motion (BM), but how these attributes are encoded in the brain remains largely unknown. In the current study, we used functional magnetic resonance imaging to investigate this issue when participants viewed multidimensional BM stimuli. Using multiple regression representational similarity analysis, we identified distributed brain areas, respectively, related to the processing of facing direction, gender, and emotional state conveyed by BM. These brain areas are governed by a hierarchical structure in which the respective neural encoding of facing direction, gender, and emotional state is modulated by each other in descending order. We further revealed that a portion of the brain areas identified in representational similarity analysis was specific to the neural encoding of each attribute and correlated with the corresponding behavioral results. These findings unravel the brain networks for encoding BM attributes in consideration of their interactions, and highlight that the processing of multidimensional BM attributes is recurrently interactive.
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Affiliation(s)
- Ruidi Wang
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, China
- Chinese Institute for Brain Research, 26 Science Park Road, Beijing 102206, China
| | - Xiqian Lu
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, China
- Chinese Institute for Brain Research, 26 Science Park Road, Beijing 102206, China
| | - Yi Jiang
- State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, China
- Chinese Institute for Brain Research, 26 Science Park Road, Beijing 102206, China
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7
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Gu L, Li A, Yang R, Yang J, Pang Y, Qu J, Mei L. Category-specific and category-general neural codes of recognition memory in the ventral visual pathway. Cortex 2023; 164:77-89. [PMID: 37207411 DOI: 10.1016/j.cortex.2023.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 03/09/2023] [Accepted: 04/03/2023] [Indexed: 05/21/2023]
Abstract
Researchers have identified category-specific brain regions, such as the fusiform face area (FFA) and parahippocampal place area (PPA) in the ventral visual pathway, which respond preferentially to one particular category of visual objects. In addition to their category-specific role in visual object identification and categorization, regions in the ventral visual pathway play critical roles in recognition memory. Nevertheless, it is not clear whether the contributions of those brain regions to recognition memory are category-specific or category-general. To address this question, the present study adopted a subsequent memory paradigm and multivariate pattern analysis (MVPA) to explore category-specific and category-general neural codes of recognition memory in the visual pathway. The results revealed that the right FFA and the bilateral PPA showed category-specific neural patterns supporting recognition memory of faces and scenes, respectively. In contrast, the lateral occipital cortex seemed to carry category-general neural codes of recognition memory. These results provide neuroimaging evidence for category-specific and category-general neural mechanisms of recognition memory in the ventral visual pathway.
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Affiliation(s)
- Lala Gu
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Aqian Li
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Rui Yang
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Jiayi Yang
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Yingdan Pang
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Jing Qu
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Leilei Mei
- Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents (South China Normal University), Ministry of Education, China; School of Psychology, South China Normal University, Guangzhou, China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China.
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8
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Revsine C, Gonzalez-Castillo J, Merriam EP, Bandettini PA, Ramírez FM. A unifying model for discordant and concordant results in human neuroimaging studies of facial viewpoint selectivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.08.527219. [PMID: 36945636 PMCID: PMC10028835 DOI: 10.1101/2023.02.08.527219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
Our ability to recognize faces regardless of viewpoint is a key property of the primate visual system. Traditional theories hold that facial viewpoint is represented by view-selective mechanisms at early visual processing stages and that representations become increasingly tolerant to viewpoint changes in higher-level visual areas. Newer theories, based on single-neuron monkey electrophysiological recordings, suggest an additional intermediate processing stage invariant to mirror-symmetric face views. Consistent with traditional theories, human studies combining neuroimaging and multivariate pattern analysis (MVPA) methods have provided evidence of view-selectivity in early visual cortex. However, contradictory results have been reported in higher-level visual areas concerning the existence in humans of mirror-symmetrically tuned representations. We believe these results reflect low-level stimulus confounds and data analysis choices. To probe for low-level confounds, we analyzed images from two popular face databases. Analyses of mean image luminance and contrast revealed biases across face views described by even polynomials-i.e., mirror-symmetric. To explain major trends across human neuroimaging studies of viewpoint selectivity, we constructed a network model that incorporates three biological constraints: cortical magnification, convergent feedforward projections, and interhemispheric connections. Given the identified low-level biases, we show that a gradual increase of interhemispheric connections across network layers is sufficient to replicate findings of mirror-symmetry in high-level processing stages, as well as view-tuning in early processing stages. Data analysis decisions-pattern dissimilarity measure and data recentering-accounted for the variable observation of mirror-symmetry in late processing stages. The model provides a unifying explanation of MVPA studies of viewpoint selectivity. We also show how common analysis choices can lead to erroneous conclusions.
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Affiliation(s)
- Cambria Revsine
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
- Department of Psychology, University of Chicago, Chicago, IL
| | - Javier Gonzalez-Castillo
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
| | - Elisha P Merriam
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
| | - Peter A Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
- Functional MRI Core, National Institutes of Health, Bethesda, MD
| | - Fernando M Ramírez
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
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9
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Foster C. A Distributed Model of Face and Body Integration. Neurosci Insights 2022; 17:26331055221119221. [PMID: 35991808 PMCID: PMC9386443 DOI: 10.1177/26331055221119221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 07/26/2022] [Indexed: 11/17/2022] Open
Abstract
Separated face- and body-responsive brain networks have been identified that show strong responses when observers view faces and bodies. It has been proposed that face and body processing may be initially separated in the lateral occipitotemporal cortex and then combined into a whole person representation in the anterior temporal cortex, or elsewhere in the brain. However, in contrast to this proposal, our recent study identified a common coding of face and body orientation (ie, facing direction) in the lateral occipitotemporal cortex, demonstrating an integration of face and body information at an early stage of face and body processing. These results, in combination with findings that show integration of face and body identity in the lateral occipitotemporal, parahippocampal and superior parietal cortex, and face and body emotional expression in the posterior superior temporal sulcus and medial prefrontal cortex, suggest that face and body integration may be more distributed than previously considered. I propose a new model of face and body integration, where areas at the intersection of face- and body-responsive regions play a role in integrating specific properties of faces and bodies, and distributed regions across the brain contribute to high-level, abstract integration of shared face and body properties.
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Affiliation(s)
- Celia Foster
- Biopsychology and Cognitive Neuroscience, Faculty of Psychology and Sports Science, Bielefeld University, Bielefeld, Germany
- Center of Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
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