Brain cell atlases reveal neuronal diversity peaks in subcortical steering structures
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Whole-brain cell atlases across mammals show that neuronal cell type diversity peaks not in the neuron-rich cortex and cerebellum but in deep subcortical structures such as the hypothalamus and brainstem. A framework arising from this finding, published in Cell, divides the vertebrate brain into two subsystems: a learning subsystem that scales by replicating repetitive modules, analogous to adding parameters in machine learning, and a steering subsystem that scales by diversifying bespoke cell types to encode innate drives as a biological reward function. The framework is proposed as a unified account spanning brain architecture, the etiology of brain disease, and possible design principles for artificial intelligence models. Whether it holds across additional species and how it translates into disease mechanisms remain open questions.
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- CellCellular scaling laws in the mammalian brain.
Whole-brain cell atlases show that neuronal cell type diversity peaks not in neuron-rich cortex and cerebellum but in deep subcortical structures such as the hypothalamus and brainstem. A proposed framework divides the vertebrate brain into a learning subsystem that scales by replicating repetitive modules, like adding parameters in machine learning, and a steering subsystem that scales by diversifying bespoke cell types to encode innate drives as a biological reward function. The framework offers a unified account of brain architecture, brain disease etiology, and possible artificial intelligence model design.
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