Human shape perception spontaneously discovers the biological origin of novel, but natural, stimuli

TL;DR

Humans can instinctively group unfamiliar natural shapes based on their biological origins, revealing hidden patterns in cell structures.

Contribution

Demonstrates that humans can spontaneously detect biological systematicities in novel natural shapes without prior knowledge.

Findings

Participants consistently grouped 3D-printed cell models by similarity, reflecting their biological classes.

Human perceptual organization aligns with the underlying biological processes shaping cell forms.

Findings suggest potential for integrating human perceptual strategies into automated biological analysis systems.

Abstract

Humans excel at categorizing objects by shape. This facility involves identifying shape features that objects have in common with other members of their class and relies—at least in part—on semantic/cognitive constructs. For example, plants sprout branches, fish grow fins, shoes are moulded to our feet. Can humans parse shapes according to the processes that give shapes their key characteristics, even when such processes are hidden? To answer this, we investigated how humans perceive the shape of cells from the olfactory system of Xenopus laevis tadpoles. These objects are novel to most humans yet occur in nature and cluster into classes following their underlying biological function. We reconstructed three-dimensional (3D) cell models through 3D microscopy and photogrammetry, then conducted psychophysical experiments. Human participants performed two tasks: they arranged 3D-printed cell models by similarity and rated them along eight visual dimensions. Participants were highly consistent in their arrangements and ratings and spontaneously grouped stimuli to reflect the cell classes, unwittingly revealing the underlying processes shaping these forms. Our findings thus demonstrate that human perceptual organization mechanisms spontaneously parse the biological systematicities of never-before-seen, natural shapes. Integrating such human perceptual strategies into automated systems may enhance morphology-based analysis in biology and medicine.

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