Global perception in small brains: Topological pattern recognition in honey bees

Abstract

A series of experiments with honey bees demonstrate that their small brains nevertheless possess the ability for topological perception. Bees rapidly learned to discriminate patterns that are topologically different, and they generalized the learned cue to other novel patterns. By contrast, discrimination of topologically equivalent patterns was learned much more slowly and not as well. Thus, although the global nature of topological properties makes their computation difficult, topology may be a fundamental component of the vocabulary by which visual systems represent and characterize objects.

Time-course of perceptual processing of “hole” and “no-hole” figures: An ERP study

“…The form of the first pair of stimuli ("hole") and ("nohole") was identical to previous research on "hole" [2,[25][26][27] .…”

“…The P1 component is also sensitive to some of the same visual stimulus properties as the N1, and can be similarly influenced by the same variations [28] . on the other hand, a major challenge to interpretation of our experiments is that there seem to be, in principle, no two geometric figures that differ only in the "hole" without any differences in local features [25] . in other words, the presence or absence of closure is never the only difference between "hole" and "no-hole" stimuli.…”

“…in order to be comparable to previous research, we used the same stimuli: an -like figure and an -like figure (hereafter referred to as and ) as in our previous masking experiment [12] and experiments by Chen on humans [2,24] and honey bees [25] . our previous study [26] , using triangles and arrows with different orientations as stimuli, showed more not able effects of orientation than topological categories.…”

DGCC: data-driven granular cognitive computing

“…7. There is a human cognition law called ''global precedence'' developed by Chen, a cognitive scientist, in 1980s (Han andChen 1996;Chen et al 2003;Chen 1982). As shown in Fig.…”

“…2. It integrates the traditional data-driven bottom-up information computing mechanism of machine learning/data mining systems and an important top-down human cognition law of ''global precedence'' (Han and Chen 1996;Chen et al 2003). The triangular structure of DGCC will be further analyzed in the Sect.…”