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Moerel D, Psihoyos J, Carlson TA. The Time-Course of Food Representation in the Human Brain. J Neurosci 2024; 44:e1101232024. [PMID: 38740441 PMCID: PMC11211715 DOI: 10.1523/jneurosci.1101-23.2024] [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] [Received: 06/12/2023] [Revised: 03/29/2024] [Accepted: 03/29/2024] [Indexed: 05/16/2024] Open
Abstract
Humans make decisions about food every day. The visual system provides important information that forms a basis for these food decisions. Although previous research has focused on visual object and category representations in the brain, it is still unclear how visually presented food is encoded by the brain. Here, we investigate the time-course of food representations in the brain. We used time-resolved multivariate analyses of electroencephalography (EEG) data, obtained from human participants (both sexes), to determine which food features are represented in the brain and whether focused attention is needed for this. We recorded EEG while participants engaged in two different tasks. In one task, the stimuli were task relevant, whereas in the other task, the stimuli were not task relevant. Our findings indicate that the brain can differentiate between food and nonfood items from ∼112 ms after the stimulus onset. The neural signal at later latencies contained information about food naturalness, how much the food was transformed, as well as the perceived caloric content. This information was present regardless of the task. Information about whether food is immediately ready to eat, however, was only present when the food was task relevant and presented at a slow presentation rate. Furthermore, the recorded brain activity correlated with the behavioral responses in an odd-item-out task. The fast representation of these food features, along with the finding that this information is used to guide food categorization decision-making, suggests that these features are important dimensions along which the representation of foods is organized.
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Affiliation(s)
- Denise Moerel
- School of Psychology, University of Sydney, Sydney, New South Wales 2050, Australia
| | - James Psihoyos
- School of Psychology, University of Sydney, Sydney, New South Wales 2050, Australia
| | - Thomas A Carlson
- School of Psychology, University of Sydney, Sydney, New South Wales 2050, Australia
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Bougou V, Vanhoyland M, Bertrand A, Van Paesschen W, Op De Beeck H, Janssen P, Theys T. Neuronal tuning and population representations of shape and category in human visual cortex. Nat Commun 2024; 15:4608. [PMID: 38816391 PMCID: PMC11139926 DOI: 10.1038/s41467-024-49078-3] [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: 06/28/2023] [Accepted: 05/22/2024] [Indexed: 06/01/2024] Open
Abstract
Object recognition and categorization are essential cognitive processes which engage considerable neural resources in the human ventral visual stream. However, the tuning properties of human ventral stream neurons for object shape and category are virtually unknown. We performed large-scale recordings of spiking activity in human Lateral Occipital Complex in response to stimuli in which the shape dimension was dissociated from the category dimension. Consistent with studies in nonhuman primates, the neuronal representations were primarily shape-based, although we also observed category-like encoding for images of animals. Surprisingly, linear decoders could reliably classify stimulus category even in data sets that were entirely shape-based. In addition, many recording sites showed an interaction between shape and category tuning. These results represent a detailed study on shape and category coding at the neuronal level in the human ventral visual stream, furnishing essential evidence that reconciles human imaging and macaque single-cell studies.
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Affiliation(s)
- Vasiliki Bougou
- Research Group of Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven and the Leuven Brain Institute, Leuven, Belgium
- Laboratory for Neuro-and Psychophysiology, Research Group Neurophysiology, Department of Neurosciences, KU Leuven and the Leuven Brain Institute, Leuven, Belgium
| | - Michaël Vanhoyland
- Research Group of Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven and the Leuven Brain Institute, Leuven, Belgium
- Laboratory for Neuro-and Psychophysiology, Research Group Neurophysiology, Department of Neurosciences, KU Leuven and the Leuven Brain Institute, Leuven, Belgium
- Department of Neurosurgery, University Hospitals Leuven, Leuven, Belgium
| | | | - Wim Van Paesschen
- Department of Neurology, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Epilepsy Research, KU Leuven, Leuven, Belgium
| | - Hans Op De Beeck
- Laboratory Biological Psychology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Peter Janssen
- Laboratory for Neuro-and Psychophysiology, Research Group Neurophysiology, Department of Neurosciences, KU Leuven and the Leuven Brain Institute, Leuven, Belgium.
| | - Tom Theys
- Research Group of Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven and the Leuven Brain Institute, Leuven, Belgium
- Department of Neurosurgery, University Hospitals Leuven, Leuven, Belgium
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Molloy MF, Saygin ZM, Osher DE. Predicting high-level visual areas in the absence of task fMRI. Sci Rep 2024; 14:11376. [PMID: 38762549 PMCID: PMC11102456 DOI: 10.1038/s41598-024-62098-9] [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] [Received: 01/03/2024] [Accepted: 05/13/2024] [Indexed: 05/20/2024] Open
Abstract
The ventral visual stream is organized into units, or functional regions of interest (fROIs), specialized for processing high-level visual categories. Task-based fMRI scans ("localizers") are typically used to identify each individual's nuanced set of fROIs. The unique landscape of an individual's functional activation may rely in large part on their specialized connectivity patterns; recent studies corroborate this by showing that connectivity can predict individual differences in neural responses. We focus on the ventral visual stream and ask: how well can an individual's resting state functional connectivity localize their fROIs for face, body, scene, and object perception? And are the neural processors for any particular visual category better predicted by connectivity than others, suggesting a tighter mechanistic relationship between connectivity and function? We found, among 18 fROIs predicted from connectivity for each subject, all but one were selective for their preferred visual category. Defining an individual's fROIs based on their connectivity patterns yielded regions that were more selective than regions identified from previous studies or atlases in nearly all cases. Overall, we found that in the absence of a domain-specific localizer task, a 10-min resting state scan can be reliably used for defining these fROIs.
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Affiliation(s)
- M Fiona Molloy
- Department of Psychology, The Ohio State University, 1835 Neil Avenue, Columbus, OH, 43210, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Zeynep M Saygin
- Department of Psychology, The Ohio State University, 1835 Neil Avenue, Columbus, OH, 43210, USA
| | - David E Osher
- Department of Psychology, The Ohio State University, 1835 Neil Avenue, Columbus, OH, 43210, USA.
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Devoto F, Mariano M, Gornetti E, Paulesu E, Zapparoli L. Trait food craving predicts functional connectivity between dopaminergic midbrain and the fusiform food area during eating imagery. Front Psychiatry 2024; 15:1396376. [PMID: 38774434 PMCID: PMC11107427 DOI: 10.3389/fpsyt.2024.1396376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 04/18/2024] [Indexed: 05/24/2024] Open
Abstract
Neurofunctional coupling between the dopaminergic midbrain (i.e., ventral tegmental area, VTA) and higher-order visual regions may contribute to food craving, leading to the onset or maintenance of obesity. We recently showed that the VTA resting-state functional connectivity with the occipitotemporal cortex, at the level of the fusiform gyrus (FFG), was specifically associated with trait food craving and the implicit bias for food images, suggesting that VTA-FFG connectivity may reflect the association between the visual representations of food and its motivational properties. To further test this hypothesis, this time we studied task-based functional connectivity in twenty-eight healthy-weight participants while imagining eating their most liked high-calorie (HC) or least liked low-calorie food (LC) or drinking water (control condition). Trait food craving scores were used to predict changes in task-based functional connectivity of the VTA during imagery of HC compared to LC foods (relative to the control condition). Trait food craving was positively associated with the functional connectivity of the VTA with the left FFG: people with higher trait food craving scores show stronger VTA-FFG connectivity, specifically for the imagery of the liked HC foods. This association was not linked to the quality of imagery nor to state measures of craving, appetite, or thirst. These findings emphasize the contribution of the functional coupling between dopaminergic midbrain and higher-order visual regions to food craving, suggesting a neurofunctional mechanism by which the mental representations of the HC food we like can become much more salient if not irresistible.
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Affiliation(s)
- Francantonio Devoto
- Psychology Department and NeuroMi – Milan Centre for Neuroscience, University of Milano-Bicocca, Milan, Italy
| | - Marika Mariano
- Psychology Department and NeuroMi – Milan Centre for Neuroscience, University of Milano-Bicocca, Milan, Italy
| | - Edoardo Gornetti
- Psychology Department and NeuroMi – Milan Centre for Neuroscience, University of Milano-Bicocca, Milan, Italy
| | - Eraldo Paulesu
- Psychology Department and NeuroMi – Milan Centre for Neuroscience, University of Milano-Bicocca, Milan, Italy
- fMRI Unit, IRCCS Orthopedic Institute Galeazzi, Milan, Italy
| | - Laura Zapparoli
- Psychology Department and NeuroMi – Milan Centre for Neuroscience, University of Milano-Bicocca, Milan, Italy
- fMRI Unit, IRCCS Orthopedic Institute Galeazzi, Milan, Italy
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Contier O, Baker CI, Hebart MN. Distributed representations of behaviorally-relevant object dimensions in the human visual system. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.23.553812. [PMID: 37662312 PMCID: PMC10473665 DOI: 10.1101/2023.08.23.553812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Object vision is commonly thought to involve a hierarchy of brain regions processing increasingly complex image features, with high-level visual cortex supporting object recognition and categorization. However, object vision supports diverse behavioral goals, suggesting basic limitations of this category-centric framework. To address these limitations, we mapped a series of behaviorally-relevant dimensions derived from a large-scale analysis of human similarity judgments directly onto the brain. Our results reveal broadly distributed representations of behaviorally-relevant information, demonstrating selectivity to a wide variety of novel dimensions while capturing known selectivities for visual features and categories. Behaviorally-relevant dimensions were superior to categories at predicting brain responses, yielding mixed selectivity in much of visual cortex and sparse selectivity in category-selective clusters. This framework reconciles seemingly disparate findings regarding regional specialization, explaining category selectivity as a special case of sparse response profiles among representational dimensions, suggesting a more expansive view on visual processing in the human brain.
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Affiliation(s)
- O Contier
- Vision and Computational Cognition Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Max Planck School of Cognition, Leipzig, Germany
| | - C I Baker
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda MD, USA
| | - M N Hebart
- Vision and Computational Cognition Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Medicine, Justus Liebig University Giessen, Giessen, Germany
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Ritchie JB, Andrews S, Vaziri-Pashkam M, Baker CI. Graspable foods and tools elicit similar responses in visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.20.581258. [PMID: 38529495 PMCID: PMC10962699 DOI: 10.1101/2024.02.20.581258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Extrastriatal visual cortex is known to exhibit distinct response profiles to complex stimuli of varying ecological importance (e.g., faces, scenes, and tools). The dominant interpretation of these effects is that they reflect activation of distinct "category-selective" brain regions specialized to represent these and other stimulus categories. We sought to explore an alternative perspective: that the response to these stimuli is determined less by whether they form distinct categories, and more by their relevance to different forms of natural behavior. In this regard, food is an interesting test case, since it is primarily distinguished from other objects by its edibility, not its appearance, and there is evidence of food-selectivity in human visual cortex. Food is also associated with a common behavior, eating, and food consumption typically also involves the manipulation of food, often with the hands. In this context, food items share many properties in common with tools: they are graspable objects that we manipulate in self-directed and stereotyped forms of action. Thus, food items may be preferentially represented in extrastriatal visual cortex in part because of these shared affordance properties, rather than because they reflect a wholly distinct kind of category. We conducted fMRI and behavioral experiments to test this hypothesis. We found that behaviorally graspable food items and tools were judged to be similar in their action-related properties, and that the location, magnitude, and patterns of neural responses for images of graspable food items were similar in profile to the responses for tool stimuli. Our findings suggest that food-selectivity may reflect the behavioral affordances of food items rather than a distinct form of category-selectivity.
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Waraich SA, Victor JD. The Geometry of Low- and High-Level Perceptual Spaces. J Neurosci 2024; 44:e1460232023. [PMID: 38267235 PMCID: PMC10860617 DOI: 10.1523/jneurosci.1460-23.2023] [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: 08/01/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 01/26/2024] Open
Abstract
Low-level features are typically continuous (e.g., the gamut between two colors), but semantic information is often categorical (there is no corresponding gradient between dog and turtle) and hierarchical (animals live in land, water, or air). To determine the impact of these differences on cognitive representations, we characterized the geometry of perceptual spaces of five domains: a domain dominated by semantic information (animal names presented as words), a domain dominated by low-level features (colored textures), and three intermediate domains (animal images, lightly texturized animal images that were easy to recognize, and heavily texturized animal images that were difficult to recognize). Each domain had 37 stimuli derived from the same animal names. From 13 participants (9F), we gathered similarity judgments in each domain via an efficient psychophysical ranking paradigm. We then built geometric models of each domain for each participant, in which distances between stimuli accounted for participants' similarity judgments and intrinsic uncertainty. Remarkably, the five domains had similar global properties: each required 5-7 dimensions, and a modest amount of spherical curvature provided the best fit. However, the arrangement of the stimuli within these embeddings depended on the level of semantic information: dendrograms derived from semantic domains (word, image, and lightly texturized images) were more "tree-like" than those from feature-dominated domains (heavily texturized images and textures). Thus, the perceptual spaces of domains along this feature-dominated to semantic-dominated gradient shift to a tree-like organization when semantic information dominates, while retaining a similar global geometry.
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Affiliation(s)
| | - Jonathan D Victor
- Division of Systems Neurology and Neuroscience, Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York 10065, New York
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