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Maria Loconsole

Researcher at University of Padua

Publications -  21
Citations -  110

Maria Loconsole is an academic researcher from University of Padua. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 3, co-authored 10 publications receiving 50 citations. Previous affiliations of Maria Loconsole include University of Tübingen & University of Cambridge.

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Neurons in the Endbrain of Numerically Naive Crows Spontaneously Encode Visual Numerosity

TL;DR: The data show that numerosity-selective neuronal responses are spontaneously present in the distinct endbrains of diverge vertebrate taxa, and suggests that endbrain circuitries that evolved based on convergent evolution, such as the avian endbrain, give rise to the same numerosity code.
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A strategy to improve arithmetical performance in four day-old domestic chicks (Gallus gallus).

TL;DR: The results suggest that in some cases, the limits reported for numerical performance in animals do not depend on cognitive limitations but on attentional or motivational factors, which can be overcome employing simple procedural adjustments.
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Multi-modal cue integration in the black garden ant.

TL;DR: The results showed the capability of black garden ants to code apparently redundant contextual information and to create and rely on conditional relationships between the information available and it is argued that future studies should deepen the inquiry on the timing and progression of multi-modal cue learning.
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Jays are sensitive to cognitive illusions.

TL;DR: In a previous study as mentioned in this paper, we found that Jays hide food caches, steal them from conspecifics and use tactics to minimize cache theft, and are sensitive to the content of their own caches, retrieving items depending on their preferences.
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Individually distinctive features facilitate numerical discrimination of sets of objects in domestic chicks

TL;DR: The results support the claim that numerical discrimination in 3 vs 4 comparison benefits from the presence of distinctive features that enhance object individuation due to individual processing and suggest that in humans similar strategies aimed at improving performance at the non-symbolic level may have positive effects on symbolic mathematical abilities.