Oct 16, 2015

Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares.

BioRxiv : the Preprint Server for Biology
Kamila M JozwikMarieke Mur

Abstract

Object similarity, in brain representations and conscious perception, must reflect a combination of the visual appearance of the objects on the one hand and the categories the objects belong to on the other. Indeed, visual object features and category membership have each been shown to contribute to the object representation in human inferior temporal (IT) cortex, as well as to object-similarity judgments. However, the explanatory power of features and categories has not been directly compared. Here, we investigate whether the IT object representation and similarity judgments are best explained by a categorical or a feature-based model. We use rich models (> 100 dimensions) generated by human observers for a set of 96 real-world object images. The categorical model consists of a hierarchically nested set of category labels (such as 'human', 'mammal', 'animal'). The feature model includes both object parts (such as 'eye', 'tail', 'handle') and other descriptive features (such as 'circular', 'green', 'stubbly'). We used non-negative least squares to fit the models to the brain representations (estimated from functional magnetic resonance imaging data) and to similarity judgments. Model performance was estimated on held-out images...Continue Reading

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Mentioned in this Paper

Cortex Bone Disorders
Adrenal Cortex Diseases
Gait, Drop Foot
Magnetic Resonance Imaging
Eye Specimen
Vision
Brain
Objective (Goal)
FMRI
Calculi

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