Dual computational systems in the development and evolution of mammalian brains.

Overview

1. School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA, USA
2. Behavioral and Evolutionary Neuroscience Group, Department of Psychology, Cornell University, Ithaca, NY, USA

Abstract

Analyses of brain sizes across mammalian taxonomic groups reveal a consistent pattern of covariation between major brain components, including a robust inverse relationship between the limbic system and the neocortex. To find the functional basis of this relationship, we mapped the multidimensional representations of task-optimized artificial neural networks onto two-dimensional surfaces resembling the forebrain cortices. We found that networks optimized for visual, somatosensory, and auditory representations develop ordered spatiotopic maps where units draw information from localized regions of the sensory input. In contrast, networks optimized for olfactory and relational memory representations develop fractured maps with distributed patterns of information convergence. Evolutionary optimization of multimodal networks for varying task objectives results in inverse covariation between spatiotopic and disordered network components that compete for the representational space. These results suggest that the observed pattern of covariation between brain components reflects an essential computational duality in brain evolution.

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Data

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Data, code, and materials availability

All data and code needed to evaluate and reproduce the results in the paper are present in the paper and/or the Supplementary Materials. The software code for this study is available at https://doi.org/10.5281/zenodo.18158106. This study did not generate new materials.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 4 authors, 8 MeSH terms, 1 funder, 60 references.

Cite

This paper

Imam, N., Kielo, M., Trude, B. M., & Finlay, B. L. (2026). Dual computational systems in the development and evolution of mammalian brains. Science advances, 12(17), eaec6112. https://doi.org/10.1126/sciadv.aec6112

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