Watson, David M and Andrews, Timothy J orcid.org/0000-0001-8255-9120 (2025) A data-driven analysis of the perceptual and neural responses to natural objects reveals organising principles of human visual cognition. The Journal of neuroscience : the official journal of the Society for Neuroscience. e1318242024. ISSN 1529-2401
Abstract
A key challenge in understanding the functional organisation of visual cortex stems from the fact that only a small proportion of the objects experienced during natural viewing can be presented in a typical experiment. This constraint often leads to experimental designs that compare responses to objects from experimenter-defined stimulus conditions, potentially limiting the interpretation of the data. To overcome this issue, we used images from the THINGS initiative, which provides a systematic sampling of natural objects. A data-driven analysis was then applied to reveal the functional organisation of the visual brain, incorporating both perceptual and neural responses to these objects. Perceptual properties of the objects were taken from an analysis of similarity judgements, and neural properties were taken from whole brain fMRI responses to the same objects. Partial least squares regression (PLSR) was then used to predict neural responses across the brain from the perceptual properties while simultaneously applying dimensionality reduction. The PLSR model accurately predicted neural responses across visual cortex using only a small number of components. These components revealed smooth, graded neural topographies, which were similar in both hemispheres, and captured a variety of object properties including animacy, real-world size, and object category. However, they did not accord in any simple way with previous theoretical perspectives on object perception. Instead, our findings suggest that visual cortex encodes information in a statistically efficient manner, reflecting natural variability among objects. Significance statement The ability to recognise objects is fundamental to how we interact with our environment, yet the organising principles underlying neural representations of visual objects remain contentious. In this study, we sought to address this question by analysing perceptual and neural responses to a large, unbiased sample of objects. Using a data-driven approach, we leveraged perceptual properties of objects to predict neural responses using a small number of components. This model predicted neural responses with a high degree of accuracy across visual cortex. The components did not directly align with previous explanations of object perception. Instead, our findings suggest the organisation of the visual brain is based on the statistical properties of objects in the natural world.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 Watson and Andrews. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Psychology (York) |
Depositing User: | Pure (York) |
Date Deposited: | 21 Jan 2025 18:16 |
Last Modified: | 17 Mar 2025 00:11 |
Published Version: | https://doi.org/10.1523/JNEUROSCI.1318-24.2024 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1523/JNEUROSCI.1318-24.2024 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:222108 |
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Description: A Data-Driven Analysis of the Perceptual and Neural Responses to Natural Objects Reveals Organizing Principles of Human Visual Cognition
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