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SARS-CoV-2 secondary structure shapes mutation frequencies, constraining viral evolution models predicting fitness can benefit from integrating secondary structure data.

This frontostriatal neural network model links the source of working memory capacity limitations to challenges in learning resource management, and mitigates this challenge by learning a 'chunking' strategy.

Combining biologically-plausible neural network models of vision with traditional decision-making models enables a detailed characterization of how the visual system extracts representations that guide decisions from raw sensory inputs.

Common principles of white matter microstructure and pathway organisation was revealed using diffusion MRI and x-ray synchrotron imaging across resolutions, and employing diffusion tensor, micro-tensor, multi-fiber, and structure tensor models.

3D electron microscopy provides the first extensive quantitative ultrastructural dataset of synapses of the human entorhinal cortex.