Ashael Raveh’s research while affiliated with University of Haifa and other places

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Publications (1)


Figure 1. Apparatus and procedure. (A) A computer monitor is placed on a glass shelf about 50 cm from the water level. The fish respond by shooting a jet of water at one of the targets. The stimuli in this Figure are illustrations. (B) Procedure: a trial starts with three rapid flashes of squares in the fish's preferred color, to attract the fish's attention to the location where the targets will appear. Then the stimuli appear until response or until 15,000 ms have passed. Then in a 10,000 ms break, the fish is rewarded with a food pellet for responding, and the water is wiped from the glass. (C) The experiment was recorded by two synced high speed (120 Hz) video cameras, one camera records the fish, and the other records the screen. Part (C) was modified from Karoubi, Leibovich, and Segev, 2017 25 .
Non-numerical magnitudes influence magnitude-related decisions. (A) Examples for each congruity level and combination of non-numerical magnitudes. Please see Table 1 for reference as to the different combinations. (B) Results—the proportion of selecting the larger numerical quantity as a function of congruity level. The x-axis represents the congruity level between non-numerical magnitudes and numerical quantity. Congruity level one; only one out of five non-numerical magnitudes positively correlated with numerical quantity. The other four non-numerical magnitudes are negatively correlated with numerical quantity. Congruity level five: full congruity: all five non-numerical magnitudes positively correlated with numerical quantity. Each dot color represents one fish, and the black thick line represents the mean across fish. The gray area in the plot represents performance below chance level (for selecting the larger numerical quantity).
Magnitude integration in the Archerfish
  • Article
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August 2021

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84 Reads

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9 Citations

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Ashael Raveh

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Dana Vilker

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We make magnitude-related decisions every day, for example, to choose the shortest queue at the grocery store. When making such decisions, which magnitudes do we consider? The dominant theory suggests that our focus is on numerical quantity, i.e., the number of items in a set. This theory leads to quantity-focused research suggesting that discriminating quantities is automatic, innate, and is the basis for mathematical abilities in humans. Another theory suggests, instead, that non-numerical magnitudes, such as the total area of the compared items, are usually what humans rely on, and numerical quantity is used only when required. Since wild animals must make quick magnitude-related decisions to eat, seek shelter, survive, and procreate, studying which magnitudes animals spontaneously use in magnitude-related decisions is a good way to study the relative primacy of numerical quantity versus non-numerical magnitudes. We asked whether, in an animal model, the influence of non-numerical magnitudes on performance in a spontaneous magnitude comparison task is modulated by the number of non-numerical magnitudes that positively correlate with numerical quantity. Our animal model was the Archerfish, a fish that, in the wild, hunts insects by shooting a jet of water at them. These fish were trained to shoot water at artificial targets presented on a computer screen above the water tank. We tested the Archerfish's performance in spontaneous, untrained two-choice magnitude decisions. We found that the fish tended to select the group containing larger non-numerical magnitudes and smaller quantities of dots. The fish selected the group containing more dots mostly when the quantity of the dots was positively correlated with all five different non-numerical magnitudes. The current study adds to the body of studies providing direct evidence that in some cases animals’ magnitude-related decisions are more affected by non-numerical magnitudes than by numerical quantity, putting doubt on the claims that numerical quantity perception is the most basic building block of mathematical abilities.

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Citations (1)


... failing to preferentially rely on numerical cues to make their decisions), together with the successful performance in the Size task (in the conditions where they had to rely on item size), suggests that individuals were at least as likely to rely on non-numerical magnitudes (i.e., item size) as on numerical ones (i.e., number of items). This in line with the "sense of magnitude theory", according to which continuous magnitudes are extracted earlier and more automatically than numerical ones (Leibovich, Katzin, Harel, & Henik, 2017;Leibovich-Raveh, Raveh, Vilker, & Gabay, 2021). Notably, as both number of items and overall food size could indicate the correct choice in the Numerosity task, it is also possible that subjects in this task relied on non-numerical magnitudes (rather than, or as well as, numerical ones). ...

Reference:

Quantity discrimination in 9 ungulate species: Individuals take item number and size into account to discriminate quantities
Magnitude integration in the Archerfish