A Highly Selective Response to Food in Human Visual Cortex Revealed by Hypothesis-Free Voxel Decomposition

Abstract

Prior work has identified cortical regions selectively responsive to specific categories of visual stimuli. However, this hypothesis-driven work cannot reveal how prominent these category selectivities are in the overall functional organization of visual cortex, or what others might exist that scientists have not thought to look for. Further, standard voxel-wise tests cannot detect distinct neural selectivities that coexist within voxels. To overcome these limitations, we used data-driven voxel decomposition methods to identify the main components underlying fMRI responses to thousands of complex photographic images (Allen et al 2021). Our hypothesis-neutral analysis rediscovered components selective for faces, places, bodies, and words, validating our method and showing that these selectivities are dominant features of the ventral visual pathway. The analysis also revealed an unexpected component with a distinct anatomical distribution that responded highly selectively to images of food. Alternative accounts based on low to mid-level visual features like color, shape or texture failed to account for the food selectivity of this component. High-throughput testing and control experiments with matched stimuli on a highly accurate computational model of this component confirm its selectivity for food. We registered our methods and hypotheses before replicating them on held-out participants and in a novel dataset. These findings demonstrate the power of data-driven methods, and show that the dominant neural responses of the ventral visual pathway include not only selectivities for faces, scenes, bodies, and words, but also the visually heterogeneous category of food, thus constraining accounts of when and why functional specialization arises in the cortex.

Selectivity for food in human ventral visual cortex

“…From a theoretical standpoint, in that food is incontrovertibly an ecologically critical category, our finding of a food-selective region (confirmed in 17, 18 ) is consistent with earlier findings of selectivity in the perception of faces, bodies, places, and words. Building on this result, principal component analyses across food-selective voxels provides a finer-grained view into the rich organization of food-relevant information within visual cortex, possibly reflecting gradients along which food is combined with other ecologically relevant categories.…”

“…Using more sensitive experimental designs and statistical methods across two experiments, we were able to spatially localize food selective regions at a much more fine-grained level within individuals, thereby providing a strong test of the relationship between food-selective and other category-selective regions. Notably, two other studies 17,18 based on the same Natural Scenes Dataset (NSD) 19 we used in Experiment 1, both identify distinct food-selective regions consistent with our results (although relying on somewhat different analysis methods). We will return to these studies in the Discussion.…”

“…Similarly, the two recent papers that likewise identified food selectivity using the same dataset we used here included several analyses that help to rule out a variety of low-or mid-level features as the basis for the observed selectivity. 17,18 Of note, both papers reported an intriguing overlap between food selectivity and color-biased brain regions. While Pennock et.…”

“…One possible reason for this variability may be that voxels processing food are interleaved with voxels processing other object related properties. 18 Another possible reason for individual variability is the complexity of building a food processing area due to the visual heterogeneity of food. Indeed, this latter point has been raised as one reason why a food-selective visual region seemed unlikely – in contrast to visually-homogeneous categories such as faces and written words, foods vary dramatically in shape, texture, and color.…”

Low-level tuning biases in higher visual cortex reflect the semantic informativeness of visual features

“…Cortical responses to visual inputs demonstrate organization according to both high-level and low-level stimulus properties. High-level information about images, such as their membership in semantic categories, is reflected in the activation of spatially localized areas of the ventral visual cortex selective for categories such as faces, body parts, places, food, and words [1,2,3,4,5,6,7,8]. At the same time, low-and mid-level visual features also elicit topographically regular patterns of activation in visual cortex, such as retinotopic maps of spatial position [9,10,11] and large-scale maps of selectivity for orientation [12,13,14], spatial frequency [15,16], color [17,18], and curvature [19,20].…”