Back

The Effective Visual Acuity of Butterflies in Flight

Supple, J. A.; Li, W.; Ilic, M.; Kos, M.; Lin, H.-T.; Belusic, G.; Krapp, H. G.

2026-10-08 neuroscience
10.64898/2026.09.30.755797 bioRxiv
Show abstract

The spatial visual acuity of an eye is determined by both the spatial sampling density of the retina and the angular sensitivity of individual photoreceptors. In insect compound eyes, these are respectively characterised by the interommatidial angle, {Delta}{varphi}, and photoreceptor acceptance angle, {Delta}{rho}. During movement, however, finite photoreceptor integration times cause retinal image motion to broaden the effective acceptance angle, potentially degrading spatial resolution beyond its anatomical limit. This problem is especially acute in flying insects, which experience large rotational velocities during locomotion and must actively stabilise gaze to limit retinal image motion. Butterflies present a particularly demanding case because their flight is characterised by large, wingbeat-coupled thoracic oscillations. Here, we quantify how gaze stabilisation limits motion blur in freely flying Monarch butterflies Danaus plexippus by combining free-flight kinematic reconstruction of the head and thorax with separate intracellular measurements of photoreceptor acceptance angles and integration times from quiescent butterflies. We found that, without head compensation, thoracic oscillations would broaden the effective photoreceptor acceptance angle from its quiescent value of 2.17{degrees} to 9.38{degrees} during take-off. Compensatory head movements substantially reduced this motion-induced broadening, limiting the effective acceptance angle to 5.28{degrees}. Nevertheless, this 2.4-fold broadening of effective photoreceptor acceptance angle represents a substantial degradation of spatial acuity in flight, highlighting motion blur as an important constraint on the visual ecology of flying butterflies.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.