Coupling between pecking and heart beat in pigeons

Delius, Juan D.; Lindenblatt, Ulrike; Lombardi, Celia M.

doi:10.1080/09291018609359917

Cited by 1 publication

(1 citation statement)

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“…But the seed-by-seed discrimination was still a very fast process that we could not properly track. As we now know, pigeons customarily peck grains out of a small pattern, or a small heap, at the rate of about 3 pecks per second 9–11 . For adequate resolution, their seed (and grit) choice behaviour has to be high-speed video recorded and slow-speed reviewed, a procedure that unless automated, is too time- and labour-consuming for routine use.…”

Section: Introductionmentioning

confidence: 99%

Systematic Analysis of Pigeons’ Discrimination of Pixelated Stimuli: A Hierarchical Pattern Recognition System Is Not Identifiable

Delius

2019

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Pigeons learned to discriminate two different patterns displayed with miniature light-emitting diode arrays. They were then tested with 84 interspersed, non-reinforced degraded pattern pairs. Choices ranged between 100% and 50% for one or other of the patterns. Stimuli consisting of few pixels yielded low choice scores whereas those consisting of many pixels yielded a broad range of scores. Those patterns with a high number of pixels coinciding with those of the rewarded training stimulus were preferred and those with a high number of pixels coinciding with the non-rewarded training pattern were avoided; a discrimination index based on this correlated 0.74 with the pattern choices. Pixels common to both training patterns had a minimal influence. A pixel-by-pixel analysis revealed that eight pixels of one pattern and six pixels of the other pattern played a prominent role in the pigeons’ choices. These pixels were disposed in four and two clusters of neighbouring locations. A summary index calculated on this basis still only yielded a weak 0.73 correlation. The individual pigeons’ data furthermore showed that these clusters were a mere averaging mirage. The pigeons’ performance depends on deep learning in a midbrain-based multimillion synapse neuronal network. Pixelated visual patterns should be helpful when simulating perception of patterns with artificial networks.

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Section: Introductionmentioning

confidence: 99%