Daniel Hanus

Dr. Daniel Hanus


Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2007 in Journal of Comparative Psychology
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Journal Article
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DHDaniel Hanus
Daniel Hanus
JCJosep Call
Josep Call
The authors examined quantity-based judgments for up to 10 items for simultaneous and sequential whole sets as well as for sequentially dropped items in chimpanzees (Pan troglodytes), gorillas (Gorilla gorilla), bonobos (Pan paniscus), and orangutans (Pongo pygmaeus). In Experiment 1, subjects had to choose the larger of 2 quantities presented in 2 separate dishes either simultaneously or 1 dish after the other. Representatives of all species were capable of selecting the larger of 2 quantities in both conditions, even when the quantities were large and the numerical distance between them was small. In Experiment 2, subjects had to select between the same food quantities sequentially dropped into 2 opaque cups so that none of the quantities were ever viewed as a whole. The authors found some evidence (albeit weaker) that subjects were able to select the larger quantity of items. Furthermore, the authors found no performance breakdown with the inclusion of certain quantities. Instead, the ratio between quantities was the best performance predictor. The authors conclude that quantity-based judgments rely on an analogical system, not a discrete object file model or perceptual estimation mechanism, such as subitizing.

8 June 2011 in PLOS ONE
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Journal Article
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DHDaniel Hanus
Daniel Hanus
NMNatacha Mendes
Natacha Mendes
CTClaudio Tennie
Claudio Tennie
JCJosep Call
Josep Call
Recently, Mendes et al. [1] described the use of a liquid tool (water) in captive orangutans. Here, we tested chimpanzees and gorillas for the first time with the same “floating peanut task.” None of the subjects solved the task. In order to better understand the cognitive demands of the task, we further tested other populations of chimpanzees and orangutans with the variation of the peanut initially floating or not. Twenty percent of the chimpanzees but none of the orangutans were successful. Additional controls revealed that successful subjects added water only if it was necessary to obtain the nut. Another experiment was conducted to investigate the reason for the differences in performance between the unsuccessful (Experiment 1) and the successful (Experiment 2) chimpanzee populations. We found suggestive evidence for the view that functional fixedness might have impaired the chimpanzees' strategies in the first experiment. Finally, we tested how human children of different age classes perform in an analogous experimental setting. Within the oldest group (8 years), 58 percent of the children solved the problem, whereas in the youngest group (4 years), only 8 percent were able to find the solution.

2 July 2020 in Journal of Intelligence
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JBJuliane Braeuer
Juliane Braeuer
DHDaniel Hanus
Daniel Hanus
SPSimone Pika
Simone Pika
RGRussell Gray
Russell Gray
NUNatalie Uomini
Natalie Uomini
Using the comparative approach, researchers draw inferences about the evolution of cognition. Psychologists have postulated several hypotheses to explain why certain species are cognitively more flexible than others, and these hypotheses assume that certain cognitive skills are linked together to create a generally “smart” species. However, empirical findings suggest that several animal species are highly specialized, showing exceptional skills in single cognitive domains while performing poorly in others. Although some cognitive skills may indeed overlap, we cannot a priori assume that they do across species. We argue that the term “cognition” has often been used by applying an anthropocentric viewpoint rather than a biocentric one. As a result, researchers tend to overrate cognitive skills that are human-like and assume that certain skills cluster together in other animals as they do in our own species. In this paper, we emphasize that specific physical and social environments create selection pressures that lead to the evolution of certain cognitive adaptations. Skills such as following the pointing gesture, tool-use, perspective-taking, or the ability to cooperate evolve independently from each other as a concrete result of specific selection pressures, and thus have appeared in distantly related species. Thus, there is not “one cognition”. Our argument is founded upon traditional Darwinian thinking, which—although always at the forefront of biology—has sometimes been neglected in animal cognition research. In accordance with the biocentric approach, we advocate a broader empirical perspective as we are convinced that to better understand animal minds, comparative researchers should focus much more on questions and experiments that are ecologically valid. We should investigate nonhuman cognition for its own sake, not only in comparison to the human model.

1 May 2008 in Current Biology
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Journal Article
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DHDaniel Hanus
Daniel Hanus
JCJosep Call
Josep Call

7 June 2011 in Animal Cognition
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Journal Article
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DHDaniel Hanus
Daniel Hanus
JCJosep Call
Josep Call

1 December 2014 in Biology Letters
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Journal Article
Open access
PDF file
DHDaniel Hanus
Daniel Hanus
JCJosep Call
Josep Call
When searching for hidden food, do chimpanzees take into account both the number of hidden items and the number of potential hiding locations? We presented chimpanzees with two trays, each of them containing a different food/cup ratio and therefore a different likelihood of finding a baited cup among empty alternatives. Subjects' performance was directly influenced by the relative difference (probability ratio (PR)) between the two given probabilities. Interestingly, however, they did not appreciate the special value of a truly safe option (with P = 1.0). Instead, they seemed to ‘blindly’ rely on the PR between the two options, systematically preferring the more likely one once a certain threshold had been reached. A control condition ruled out the possibility of low-level learning explanations for the observed performance.