Honeybees foraging for numbers

Giurfa, Martín

doi:10.1007/s00359-019-01344-2

Cited by 20 publications

(21 citation statements)

References 77 publications

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“…The honeybee has become an important model in research aiming at an understanding of how a miniature brain can process information (Giurfa 2007 , 2019 ; Srinivasan 2020 ). At the same time, there has been considerable interest in potentially bio-inspired solutions for the design of efficient computers (Merolla et al 2014 ) with reduced energy consumption (Masanet et al 2020 ).…”

Section: Advanced Understanding Of Bee Cognition Underlines Einstein’s Foresightmentioning

confidence: 99%

“…Bees have demonstrated their capacity to perform many cognitive-like tasks including maze navigation (Zhang et al 2000 ), face processing (Avarguès-Weber et al 2018 ) and multimodal processing (Giurfa et al 2001 ; Ravi et al 2016 ; Solvi et al 2020 ), analogous to what large brained primates can achieve (Chittka and Niven 2009 ; Avarguès-Weber et al 2020 ). The publication of two recent studies showing that bees can learn to understand the mathematical concept of zero (Howard et al 2018 ) and also perform basic arithmetic (Giurfa 2019 ; Howard et al 2019 ) received wide media coverage around the world (Dyer et al 2020 ). Judith Davys, the wife of the late Glyn Davys, heard a BBC radio coverage about what bees can do, including these two studies, and recalled the letter written to her husband by Einstein that has remained all this time in the possession of the family.…”

Section: Advanced Understanding Of Bee Cognition Underlines Einstein’s Foresightmentioning

confidence: 99%

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Einstein, von Frisch and the honeybee: a historical letter comes to light

et al. 2021

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The work of the Nobel Laureate Karl von Frisch, the founder of this journal, was seminal in many ways. He established the honeybee as a key animal model for experimental behavioural studies on sensory perception, learning and memory, and first correctly interpreted its famous dance communication. Here, we report on a previously unknown letter by the Physicist and Nobel Laureate Albert Einstein that was written in October 1949. It briefly addresses the work of von Frisch and also queries how understanding animal perception and navigation may lead to innovations in physics. We discuss records proving that Einstein and von Frisch met in April 1949 when von Frisch visited the USA to present a lecture on bees at Princeton University. In the historical context of Einstein’s theories and thought experiments, we discuss some more recent discoveries of animal sensory capabilities alien to us humans and potentially valuable for bio-inspired design improvements. We also address the orientation of animals like migratory birds mentioned by Einstein 70 years ago, which pushes the boundaries of our understanding nature, both its biology and physics.

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Section: Advanced Understanding Of Bee Cognition Underlines Einstein’s Foresightmentioning

confidence: 99%

Section: Advanced Understanding Of Bee Cognition Underlines Einstein’s Foresightmentioning

confidence: 99%

Einstein, von Frisch and the honeybee: a historical letter comes to light

et al. 2021

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“…It is not known whether numerical abilities have similar selective advantages in other phyla and whether numerical systems are widespread outside the vertebrate group. To date, this issue has been investigated only in a handful of species, and there is convincing evidence of a true numerical system for only one of them, the honeybee [28][29][30] . Honeybees, Apis mellifera, can be trained to discriminate different numbers of dots to obtain a food reward 31,32 .…”

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confidence: 99%

Continuous versus discrete quantity discrimination in dune snail (Mollusca: Gastropoda) seeking thermal refuges

Bisazza

Gatto

2021

Sci Rep

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The ability of invertebrates to discriminate quantities is poorly studied, and it is unknown whether other phyla possess the same richness and sophistication of quantification mechanisms observed in vertebrates. The dune snail, Theba pisana, occupies a harsh habitat characterised by sparse vegetation and diurnal soil temperatures well above the thermal tolerance of this species. To survive, a snail must locate and climb one of the rare tall herbs each dawn and spend the daytime hours in an elevated refuge position. Based on their ecology, we predicted that dune snails would prefer larger to smaller groups of refuges. We simulated shelter choice under controlled laboratory conditions. Snails’ acuity in discriminating quantity of shelters was comparable to that of mammals and birds, reaching the 4 versus 5 item discrimination, suggesting that natural selection could drive the evolution of advanced cognitive abilities even in small-brained animals if these functions have a high survival value. In a subsequent series of experiments, we investigated whether snails used numerical information or based their decisions upon continuous quantities, such as cumulative surface, density or convex hull, which co-varies with number. Though our results tend to underplay the role of these continuous cues, behavioural data alone are insufficient to determine if dune snails were using numerical information, leaving open the question of whether gastropod molluscans possess elementary abilities for numerical processing.

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“…The honey bee's recognition system is based on spatial configurations (18,19,23,25,26) that allow both fine discrimination among similar visual objects, such as human faces (21,22), and efficient object recognition despite perceptual modifications, such as rotations (27). In addition, bees demonstrate high-level performance in categorization tasks based not only on perceptual regularities (15,28,29) but also on abstract relations, showing capacity to manipulate relational concept learning, such as "above/below" (30)(31)(32)(33)(34) or numerosity (35)(36)(37)(38)(39)(40)(41)(42).…”

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confidence: 99%

Different mechanisms underlie implicit visual statistical learning in honey bees and humans

Avarguès‐Weber

Finke

Nagy³

et al. 2020

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

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The ability of developing complex internal representations of the environment is considered a crucial antecedent to the emergence of humans’ higher cognitive functions. Yet it is an open question whether there is any fundamental difference in how humans and other good visual learner species naturally encode aspects of novel visual scenes. Using the same modified visual statistical learning paradigm and multielement stimuli, we investigated how human adults and honey bees (Apis mellifera) encode spontaneously, without dedicated training, various statistical properties of novel visual scenes. We found that, similarly to humans, honey bees automatically develop a complex internal representation of their visual environment that evolves with accumulation of new evidence even without a targeted reinforcement. In particular, with more experience, they shift from being sensitive to statistics of only elemental features of the scenes to relying on co-occurrence frequencies of elements while losing their sensitivity to elemental frequencies, but they never encode automatically the predictivity of elements. In contrast, humans involuntarily develop an internal representation that includes single-element and co-occurrence statistics, as well as information about the predictivity between elements. Importantly, capturing human visual learning results requires a probabilistic chunk-learning model, whereas a simple fragment-based memory-trace model that counts occurrence summary statistics is sufficient to replicate honey bees’ learning behavior. Thus, humans’ sophisticated encoding of sensory stimuli that provides intrinsic sensitivity to predictive information might be one of the fundamental prerequisites of developing higher cognitive abilities.

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Honeybees foraging for numbers

Cited by 20 publications

References 77 publications

Einstein, von Frisch and the honeybee: a historical letter comes to light

Einstein, von Frisch and the honeybee: a historical letter comes to light

Continuous versus discrete quantity discrimination in dune snail (Mollusca: Gastropoda) seeking thermal refuges

Different mechanisms underlie implicit visual statistical learning in honey bees and humans

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