Mini review: Individual differences and domain-general mechanisms in object recognition

Gauthier, Isabel; Cha, Oakyoon; Chang, Ting-Yun

doi:10.3389/fcogn.2022.1040994

Cited by 3 publications

(2 citation statements)

References 92 publications

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“…The study of domain-general high-level visual abilities is an emerging research area (Gauthier, 2018 ; Gauthier et al, 2022 ), and the extent to which these abilities can explain variability in performance on real-world tasks is still unclear. As diagnostic imaging has a heavy visual component, it is plausible that visual abilities may influence performance on these tasks.…”

Section: Introductionmentioning

confidence: 99%

Object recognition ability predicts category learning with medical images

Smithson

Eichbaum²,

Gauthier³

2023

Cogn. Research

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We investigated the relationship between category learning and domain-general object recognition ability (o). We assessed this relationship in a radiological context, using a category learning test in which participants judged whether white blood cells were cancerous. In study 1, Bayesian evidence negated a relationship between o and category learning. This lack of correlation occurred despite high reliability in all measurements. However, participants only received feedback on the first 10 of 60 trials. In study 2, we assigned participants to one of two conditions: feedback on only the first 10 trials, or on all 60 trials of the category learning test. We found strong Bayesian evidence for a correlation between o and categorisation accuracy in the full-feedback condition, but not when feedback was limited to early trials. Moderate Bayesian evidence supported a difference between these correlations. Without feedback, participants may stick to simple rules they formulate at the start of category learning, when trials are easier. Feedback may encourage participants to abandon less effective rules and switch to exemplar learning. This work provides the first evidence relating o to a specific learning mechanism, suggesting this ability is more dependent upon exemplar learning mechanisms than rule abstraction. Object-recognition ability could complement other sources of individual differences when predicting accuracy of medical image interpretation.

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Section: Introductionmentioning

confidence: 99%

Object recognition ability predicts category learning with medical images

Smithson

Eichbaum²,

Gauthier³

2023

Cogn. Research

Self Cite

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“…Vision science has tended to focus on effects at the group level, often neglecting the value of variation between individuals. However, in recent years there has been an increase in interest in individual differences in high-level vision, particularly in the area of object recognition (Dennett et al, 2012;Gauthier et al, 2022;McGugin et al, 2012;Richler et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Measuring object recognition ability: Reliability, validity, and the aggregate z-score approach

Smithson,

Chow,

Chang

et al. 2024

Behav Res

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Measurement of domain-general object recognition ability (o) requires minimization of domainspecific variance. One approach is to model o as a latent variable explaining performance on a battery of tests which differ in task demands and stimuli; however, time and sample requirements may be prohibitive. Alternatively, an aggregate measure of o can be obtained by averaging z-scores across tests. Using data from Sunday et al., Journal of Experimental Psychology: General, 151, 676-694, (2022), we demonstrated that aggregate scores from just two such object recognition tests provide a good approximation (r = .79) of factor scores calculated from a model using a much larger set of tests. Some test combinations produced correlations of up to r = .87 with factor scores. We then revised these tests to reduce testing time, and developed an odd one out task, using a unique object category on nearly every trial, to increase task and stimuli diversity. To validate our measures, 163 participants completed the object recognition tests on two occasions, one month apart.Providing the first evidence that o is stable over time, our short aggregate o measure demonstrated good test-retest reliability (r = .77). The stability of o could not be completely accounted for by intelligence, perceptual speed, and early visual ability. Structural equation modeling suggested that our tests load significantly onto the same latent variable, and revealed that as a latent variable, o is highly stable (r = .93). Aggregation is an efficient method for estimating o, allowing investigation of individual differences in object recognition ability to be more accessible in future studies.

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Objects, Faces, and Spaces: Organizational Principles of Visual Object Perception as Evidenced by Individual Differences in Behavior

Sigurdardottir,

Ólafsdóttir

2023

Preprint

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What are the diagnostic dimensions on which objects truly differ visually, and do these dimensions provide the foundation for the organizational principles of visual object perception as evidenced by individual differences in behavior? Using data-driven methods, we utilized a deep convolutional neural network to construct a visual object space extracted from deep layer activations for a reference set of objects. The first two dimensions of object space capture attributes that distinguish one object from another and may map onto the anatomical organization of the ventral visual stream of non-human primates, but its existence in humans is unclear. If object space underlies human visual cognition, this should have a measurable effect on people’s object discrimination. We focused on the so-called face quadrant of object space, as there are considerable individual differences in face discrimination abilities, and a lively debate has revolved around whether such abilities are specific to faces. In this preregistered study, we collected data from a large (N=511) heterogeneous sample to amplify individual differences in visual discrimination. We primarily targeted people with self-declared face recognition abilities on opposite sides of the spectrum, ranging from poor to excellent face recognizers. We then administered a visual foraging task where faces and other objects had to be discriminated. Stimuli were carefully picked out of tens of thousands of images to either match or not match with the coordinates of faces in object space. Results showed that face discrimination did not rely on completely domain-specific abilities but also tapped into mechanisms that supported other object discrimination. Specifically, people who struggled with telling apart faces also had difficulties with discriminating other objects from the face quadrant of object space. To the best of our knowledge, the current study provides the first behavioral evidence for the existence of an object space in human visual cognition.

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Mini review: Individual differences and domain-general mechanisms in object recognition

Cited by 3 publications

References 92 publications

Object recognition ability predicts category learning with medical images

Object recognition ability predicts category learning with medical images

Measuring object recognition ability: Reliability, validity, and the aggregate z-score approach

Objects, Faces, and Spaces: Organizational Principles of Visual Object Perception as Evidenced by Individual Differences in Behavior

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