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Abstract Concerted developmental programming may constrain changes in component structures of the brain, thus limiting the ability of selection to form an adaptive mosaic of size‐variable brain compartments independent of total brain size or body size. Measuring patterns of gene expression underpinning brain scaling in conjunction with anatomical brain atlases can aid in identifying influences of concerted and/or mosaic evolution. Species exhibiting exceptional size and behavioral polyphenisms provide excellent systems to test predictions of brain evolution models by quantifying brain gene expression. We examined patterns of brain gene expression in a remarkably polymorphic and behaviorally complex social insect, the leafcutter antAtta cephalotes. The majority of significant differential gene expression observed among three morphologically, behaviorally, and neuroanatomically differentiated worker size groups was attributable to body size. However, we also found evidence of differential brain gene expression unexplained by worker morphological variation and transcriptomic analysis identified patterns not linearly correlated with worker size but sometimes mirroring neuropil scaling. Additionally, we identified enriched gene ontology terms associated with nucleic acid regulation, metabolism, neurotransmission, and sensory perception, further supporting a relationship between brain gene expression, brain mosaicism, and worker labor role. These findings demonstrate that differential brain gene expression among polymorphic workers underpins behavioral and neuroanatomical differentiation associated with complex agrarian division of labor inA. cephalotes. 

Human brain reduction from the Late Pleistocene/Holocene to the modern day is a longstanding anthropological observation documented with numerous lines of independent evidence. In a recent study (DeSilva et al., 2021;Front. Ecol. Evol.), we analyzed a large compilation of fossil and recent human crania and determined that this reduction was surprisingly recent, occurring rapidly within the past 5,000 to 3,000 years of human history. We attributed such a change as a consequence of population growth and cooperative intelligence and drew parallels with similar evolutionary trends in eusocial insects, such as ants. In a reply to our study, Villmoare and Grabowski (2022;Front. Ecol. Evol.) reassessed our findings using portions of our dataset and were unable to detect any reduction in brain volume during this time frame. In this paper, responding to Villmoare and Grabowski’s critique, we reaffirm recent human brain size reduction in the Holocene, and encourage our colleagues to continue to investigate both the timing and causes of brain size reduction in humans in the past 10,000 years. 

Current methods used to quantify brain size and compartmental scaling relationships in studies of social insect brain evolution involve manual annotations of images from histological samples, confocal microscopy or other sources. This process is susceptible to human bias and error and requires time-consuming effort by expert annotators. Standardized brain atlases, constructed through 3D registration and automatic segmentation, surmount these issues while increasing throughput to robustly sample diverse morphological and behavioral phenotypes. Here we design and evaluate three strategies to construct statistical brain atlases, or templates, using ants as a model taxon. The first technique creates a template by registering multiple brains of the same species. Brain regions are manually annotated on the template, and the labels are transformed back to each individual brain to obtain an automatic annotation, or to any other brain aligned with the template. The second strategy also creates a template from multiple brain images but obtains labels as a consensus from multiple manual annotations of individual brains comprising the template. The third technique is based on a template comprising brains from multiple species and the consensus of their labels. We used volume similarity as a metric to evaluate the automatic segmentation produced by each method against the inter- and intra-individual variability of human expert annotators. We found that automatic and manual methods are equivalent in volume accuracy, making the template technique an extraordinary tool to accelerate data collection and reduce human bias in the study of the evolutionary neurobiology of ants and other insects.