A theory of variability discrimination: Finding differences

Young, Michael E.; Wasserman, Edward A.; Ellefson, Michelle R.

doi:10.3758/bf03194106

Cited by 17 publications

(37 citation statements)

References 44 publications

(59 reference statements)

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“…Second, sameness judgment becomes easier with increasing number of stimuli (set size) for both pigeons and baboons (16,17). Third, when stimuli are blurred, pigeons more frequently respond "same" on "different" trials, but performance is more or less unchanged on "same" trials (20).…”

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confidence: 99%

Optimal inference of sameness

Berg

Vogel

Josić

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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Deciding whether a set of objects are the same or different is a cornerstone of perception and cognition. Surprisingly, no principled quantitative model of sameness judgment exists. We tested whether human sameness judgment under sensory noise can be modeled as a form of probabilistically optimal inference. An optimal observer would compare the reliability-weighted variance of the sensory measurements with a set size-dependent criterion. We conducted two experiments, in which we varied set size and individual stimulus reliabilities. We found that the optimal-observer model accurately describes human behavior, outperforms plausible alternatives in a rigorous model comparison, and accounts for three key findings in the animal cognition literature. Our results provide a normative footing for the study of sameness judgment and indicate that the notion of perception as nearoptimal inference extends to abstract relations.Bayesian inference | ideal observer | decision making | vision A ccording to William James, the "sense of sameness is the very keel and backbone of our thinking" (1). Judging whether a set of stimuli are all the same (in one or multiple features) indeed seems to be a fundamental component of perception and cognition. When segmenting a visual scene, we make use of the fact that features such as orientation and color tend to be the same within an object and different between objects (2). Learning to categorize objects requires evaluating the aspects in which they are the same or different. Sameness judgment is also thought to play a role in the development of the abstract notion of equivalence, fundamental to learning mathematics (3). The central role of sameness judgment in perception and cognition is reflected in its prevalence in many psychophysical tasks, including matching to sample (4), change detection (5, 6), oddity search (7,8), and causal inference (9).The ability to judge sameness seems to have a long evolutionary history. In addition to humans, honey bees (10), pigeons (11), parrots (12), dolphins (13), Old World monkeys (5), New World monkeys (14,15), and apes (6, 7) can all learn to report whether pairs of objects are the same or different. This ability extends to larger groups of objects in both humans and nonhuman animals (16-21). It has been suggested that human capacity to recognize sameness at abstract levels is closely linked to the evolution of prefrontal cortex (22).In animal cognition experiments on sameness judgment, several intriguing trends have not yet been fully explained. First, when pigeons are trained to discriminate arrays of identical objects from arrays of different objects, their probability of reporting "different" is found to gradually increase with the amount of variability in the array (23, 24). For example, when an array contained four subsets of four icons each, with icons being identical within a subset, subjects reported "different" more frequently than when two subsets of eight icons were shown. Second, sameness judgment becomes easier with increasing number o...

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confidence: 99%

Optimal inference of sameness

Berg

Vogel

Josić

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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“…Young, Wasserman and Ellefson considered a reasonable model for "finding differences", which judged the sameness by local differences between items. The finding differences model was effective in visual search tasks, and was applicable to investigations involving multidimensional variability [6] and quantitative item differences [7]. Wasserman et al further illustrated discrimination of stimulus variability affected both human and animal action [12].…”

Section: Introductionmentioning

confidence: 99%

“…On this account, researchers put forward many approaches to implement the proposition of the sameness [1][2][3][4][5][6][7][8][9][10][11][12]. Young and Wasserman found the information theoretic measure of categorical variability "entropy" systematically described the functional relationship between stimulus variability and discriminative responding [5,8].…”

Section: Introductionmentioning

confidence: 99%

“…To discriminate the variability exists in a wide range of routine tasks, such as searching for mates, sorting letters in post office, putting goods on store shelves and so on. The prevalent method is to segment a visual scene, and they aggregate localized differences among objects, and comparing these finding differences of the objects [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. As a special case, the same-different judgment attracts many researchers' interests [1][2][3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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Classified Judgment on Same-different Based on Bayesian Inference

Chen¹,

Liu²

2016

Proceedings of the 2016 International Conference on Computer Engineering and Information Systems

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Abstract-The ability to detect objects precisely with the same orientations from random orientations is one of the most remarkable functions of perception and cognition. Many psychophysical evidences imply human's behavior follows near-optimal Bayesian inference in tasks of decision making. We explore the model of bars with the same orientation from the random orientations by the means of theories and experiments. In experiments, the numbers and locations of bars with same orientation are randomly assigned. The performances of subjects depend on the number of bars (set size), the number of bars with same orientations and reliabilities of measurements. We put forward a model based on Bayesian theory in visual search to judge how many bars with same orientation among a mass of orientations. To compare the effect of the model, we design two alternative models. We find our model on this kind of classified judgment matches well the experimental data, is superior to alternative models, and it provides a normative and mathematically quantitative description.

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“…Such factors include the degree of similarity among the items involved in the discrimination (Smith, Redford, Haas, Coutinho, & Couchman, 2008;Young, Wasserman, & Ellefson, 2007) and the spatial distance among the visually presented items (Young et al, 2007). Indeed, Young et al (2007) developed the finding differences model expressly to accommodate the roles that are played by similarity and spatial distance in same-different discrimination performance.…”

Section: Final Considerationsmentioning

confidence: 99%

Variations on variability: effects of display composition on same–different discrimination in pigeons

2012

Self Cite

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Discriminating same from different multiitem arrays can be represented as a discrimination between arrays involving low variability and arrays involving high variability. In the present investigation, we first trained pigeons with the extreme values along the variability continuum (arrays containing 16 identical items vs. 16 nonidentical items), and we later tested the birds with arrays involving intermediate levels of variability; we created these testing arrays either by manipulating the combination of same and different items (mixture testing) or by changing the number of items in the same and different arrays (number testing). According to an entropy account (Young & Wasserman, Journal of Experimental Psychology: Animal Behavior Processes 23:157-170, 1997), the particular means of changing variability should have no effect on same-different discrimination performance: Equivalent variability should yield equivalent performance. In this critical test of an entropy account, we found that entropy could explain a large portion of our data, but not the entire collection of results.

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A theory of variability discrimination: Finding differences

Cited by 17 publications

References 44 publications

Optimal inference of sameness

Optimal inference of sameness

Classified Judgment on Same-different Based on Bayesian Inference

Variations on variability: effects of display composition on same–different discrimination in pigeons

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