Published in Nature [1], 'A Somato-Cognitive Action Network Alternates with Effector Regions in Motor Cortex' found that "the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternative with effector-specific (foot, hand and mouth) areas" ([1], p351). The authors propose a dual-system of inter-effector and effector-isolating regions: the former coordinate whole-organism action and the later fine motor regions are "organised somatotopically as three concentric functional zones, with distal parts of the effector at the centre and proximal ones on the perimeter" ([1], p356).

Published in 2017 by Google Brain, 'Attention Is All You Need' [1] established the Transformer neural network architecture, which parallelised previously serial computation through their multi-head, self-attention mechanism - described by the language of linear algebra.

Published in Nature Communications Biology (2025) [1], R. Kessler, A. Enge & M.A. Skeide explored 'How EEG Preprocessing Shapes Decoding Performance'. The authors systematically varied each preprocessing step in a standardised EEG data processing pipeline, resulting in 2593 replications across unique forking paths. This was executed as a SLURM job submission to a HPC cluster.