Back

Behavioral performance requirements for division of labor influence adaptive brain mosaicism in a socially complex ant

Muratore, I. B.; Fandozzi, E. M.; Traniello, J. F. A.

2021-07-04 animal behavior and cognition
10.1101/2021.07.03.450997 bioRxiv
Show abstract

Brain evolution is hypothesized to be driven by neuroarchitectural requirements for behavioral performance. Assessments of such needs should be informed by the nature of sensory and motor processes underpinning behavior. We developed a novel metric to estimate the relative neuroanatomical investments required to perform tasks varying in sensorimotor and processing demands across polymorphic and polyethic workers of the leafcutter ant Atta cephalotes and quantified brain size and structure to examine their correspondence with our computational approximations. Investment in multi-sensory integration and motor requirements for task performance was estimated to be greatest for media workers whose leaf-harvesting repertoire involves the most diverse and demanding sensory and motor processes, including plant discrimination, leaf cutting, and fragment transportation. Volumetric analysis of confocal brain images revealed that absolute brain size increased with worker size and compartmental scaling allometries among functionally specialized brain compartments differed among polymorphic workers. The mushroom bodies, centers of sensory integration and learning, and the antennal lobes, which process olfactory inputs, were significantly larger in medias than in minim workers (fungal gardeners) and major workers ("soldiers"), which had lower estimated task-related neural demands. Minims had a proportionally larger central complex, perhaps to control navigation in subterranean fungal garden chambers. These results indicate that variation in task performance requirements has selected for adaptive variation in brain size and mosaic scaling.

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.