In recent years, ultra-high field functional MRI has allowed researchers to study cortical activity at high spatiotemporal resolution. Advancements in technology have made it possible to perform fMRI of cortical laminae, which is crucial for understanding and mapping of local circuits and overall brain function. Unlike invasive electrophysiology, fMRI provides a non-invasive approach to studying human and animal brain function. However, achieving high spatial resolution has often meant sacrificing temporal resolution. In contrast, line-scanning fMRI maintains both high spatial and temporal resolution, and has been successfully applied to animals to detect laminar differences of the hemodynamic response. Although this method has been extended to human brain imaging in initial studies, staying within SAR safety limits while maintaining a well-defined saturation profile at a short TR is a major challenge. We present a method for gradient-echo-based human line-scanning that uses four saturation regions to achieve a line with narrow FWHM (3.9 mm) at high spatiotemporal resolution (voxel size 0.39 x 3.0 x 3.0 mm 3 , TR = 250 ms). We demonstrate its use for laminar fMRI by measuring laminar time courses in the hand knob of the primary human motor cortex during a finger-tapping task. Our findings indicate differences in the onset and temporal characteristics of the hemodynamic response across cortical layers. Deeper layers exhibited distinct temporal dynamics compared with the gray matter near the cortical surface. Specifically, the BOLD response reached 95% of the maximum amplitude earlier than the superficial layers, and demonstrated a faster return to baseline after stimulus offset. We demonstrate that line-scanning fMRI offers a valuable tool for investigating recordings at a very high temporal and spatial resolution and could help advance our understanding of the mechanistic nature of the BOLD response.

In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales—from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration, and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges. The aims of this paper are to: develop a concept for the coming decade of digital brain research, discuss this new concept with the research community at large, identify points of convergence, and derive therefrom scientific common goals; provide a scientific framework for the current and future development of EBRAINS, a research infrastructure resulting from the HBP’s work; inform and engage stakeholders, funding organisations and research institutions regarding future digital brain research; identify and address the transformational potential of comprehensive brain models for artificial intelligence, including machine learning and deep learning; outline a collaborative approach that integrates reflection, dialogues, and societal engagement on ethical and societal opportunities and challenges as part of future neuroscience research.