Abstract The Human Connectome Project (HCP) was launched in 2010 as an ambitious
effort to accelerate advances in human neuroimaging, particularly for measures of brain …

The rapid advancements in machine learning, graphics processing technologies and the
availability of medical imaging data have led to a rapid increase in the use of deep learning …

Considerable progress has recently been made in natural language processing: deep
learning algorithms are increasingly able to generate, summarize, translate and classify …

Extensive sampling of neural activity during rich cognitive phenomena is critical for robust
understanding of brain function. Here we present the Natural Scenes Dataset (NSD), in …

Deep learning algorithms trained to predict masked words from large amount of text have
recently been shown to generate activations similar to those of the human brain. However …

The sharing of research data is essential to ensure reproducibility and maximize the impact
of public investments in scientific research. Here, we describe OpenNeuro, a BRAIN …

Gene expression fundamentally shapes the structural and functional architecture of the
human brain. Open-access transcriptomic datasets like the Allen Human Brain Atlas provide …

Data analysis workflows in many scientific domains have become increasingly complex and
flexible. Here we assess the effect of this flexibility on the results of functional magnetic …

Brain atlases are fundamental to understanding the topographic organization of the human
brain, yet many contemporary human atlases cover only the cerebral cortex, leaving the …

Precisely how the anatomical structure of the brain gives rise to a repertoire of complex
functions remains incompletely understood. A promising manifestation of this map** from …