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Brain research has in recent years indisputably entered a new epoch, driven bysubstantialmethodologicaladvances and digitallyenabled data integration and modeling at multiple scales –from molecules to the whole system. Major advances are emerging at theintersection of neurosciencewith technology and computing. This new science of the brain integrates high-quality basic research,systematic data integration across multiple scales, a new culture of large-scale collaboration andtranslation into applications. A systematic approach, as pioneered in Europe’s Human Brain Project(HBP), will be essential in meeting the pressing medical andtechnological challenges of the comingdecade. The aims of this paper are To develop a concept for the coming decade of digital brain research To discuss it with the research community at large, with the aim of identifying points of convergence and common goals To provide a scientific framework for current and future development of EBRAINS To inform and engage stakeholders, funding organizations and research institutions regarding future digital brain research To identify and address key ethical and societal issues While we do not claim that there is a ‘one size fits all’ approach to addressing these aspects, we areconvinced that discussions around the theme of digital brain research will help drive progress in thebroader field of neuroscience. You can submit your comments here and be considered for co-authorship Or become a supporter by clicking here More information below Comments on this manuscript are welcome This manuscriptis a living document that is being further developed in a participatory process. The work has been initiated by the Science and Infrastructure Board of the Human Brain Project (HBP). Now, the entire research community is invited to contribute to shaping the vision by submitting comments.Comments can be submitted via an online commentary form here. All submitted comments will be considered and discussed. The final decision on whether edits or additions will be made to the next version of the manuscript based on an individual comment will be made by the Science and Infrastructure Board (SIB) of the Human Brain Project (HBP) at regular intervals. The final version of the manuscript will be prepared and published in the next months. Comments may be submitted until the end of May, 2023. Every researcher is welcome to provide comment or indicate support for the contents of this paper and jointly shape the future of brain research. Supporters of the paper: Pietro Avanzini, Marc Beyer, Maria Del Vecchio, Jitka Annen, Maurizio Mattia, Steven Laureys, Rosanne Edelenbosch, Rafael Yuste, Jean-Pierre Changeux, Linda Richards, Hye Weon Jessica Kim, Chrysoula Samara, Luis Miguel González de la Garza, Nikoleta Petalidou, Vasudha Kulkarni, Cesar David Rincon, Isabella O'Shea, Munira Tamim Electricwala, Nicola Palomero-Gallagher, Bernd Carsten Stahl, Bahar Hazal Yalcinkaya, Meysam Hashemi, Carola Sales Carbonell, Marcel Carrère, Anthony Randal McIntosh, Hiba Sheheitli, Abolfazl Ziaeemehr, Martin Breyton, Giovanna Ramos Queda, Anirudh NIhalani Vattikonda, Gyorgy Buzsaki George Ogoh, William Knight Torbjørn V Ness, MIchiel van der Vlag, Mu-ming Poo.

Digital Poster presented at the 2022 Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting, London, UK

Age-related cortical perfusion changes and their impact on assessing functional connectivity. Poster presented at the 27th annual meeting of the Organization for Human Brain Mapping (2021).

Presented at: ISMRM Workshop on Ultra High Field MRI: Technological Advances & Clinical Applications, Heidelberg, GermanyAbstract:The increased accessibility of ultra-high field scanners has resulted in an increased interest in studying cortical depth-dependent fMRI. The cortical depths are usually determined on an anatomical image which makes good co-registration with the distorted functional data crucial in such studies. The standard approaches to correct the distorted EPI data using algorithms such as FSL-TOPUP might reduce the laminar information in the high-resolution fMRI data due to smoothing and interpolation. Furthermore, sub-optimal registration of the different images might lead to an erroneous classification of depths. The present study builds upon our previous work to acquire sub-millimetre distortion-matched quantitative T1 image using inversion-recovery EPI (IR-EPI) at 7T and demonstrates the feasibility of using the IR-EPI T1 map to define cortical-depths for fMRI analyses.

Presented at:ISMRM Workshop on Ultrahigh Field Magnetic Resonance: Technological Advances, Translational Research Promises & Clinical Applications, Dubrovnik, CroatiaAbstract:CBV fMRI using Vascular Space Occupancy (VASO) has been shown to perform very well at ultra-high fields of 7T [1] and 9.4T [2] for applications that target laminar and columnar investigations of human motor cortex. Recently, BOLD fMRI at 7T has also been demonstrated to be feasible at ultra-high spatial resolution (0.1 mm) along the laminar or columnar directions, using anisotropic voxels [3]. The present study exploits the benefits of higher SNR at 9.4T together with that of parallel transmission (pTx), advanced contrasts, and readout schemes. We use an ultra-high spatial resolution multi-echo anisotropic voxel FLASH (AVF) for BOLD fMRI and VASO using a finger-tapping paradigm, and demonstrate the feasibility of columnar human fMRI to investigate the physiological underpinnings of the BOLD response at 9.4T.

Presented at:21st Annual Meeting of the Organization for Human Brain Mapping (OHBM) 2015Abstract:In a typical fMRI analysis, the results are displayed overlaid on an anatomical image A good co-registration between the fMRI and anatomical data is essential to achieve accurate localization of function. The differing image properties (contrast, distortions) of both datasets pose a challenge for the registration and often lead to errors. Co-registration between functional and anatomical data is most important, but also most difficult, in high-resolution fMRI at ultra-high field (B0- and B1-inhomogeneities). Ultra-high field (≥ 7 T) offers fMRI substantial benefits due to increases in signal-to-noise ratio and specificity. The problem with co-registration between anatomical and functional data can be circumvented by acquiring distortion-matched anatomical images using inversion-recovery EPI with identical readout parameters. We demonstrate the feasibility of the approach at both 7 and 9.4 Tesla, utilizing recent advances in methods for fast quantitative T1-mapping.

Presented at:OHBM 2016, Geneva, SwitzerlandAbstract:The human cortex (~3 mm thick) typically consists of 6 histological layers with distinct functional roles. Recently, several studies have been published that noninvasively measure layer-specific cortical signal using ultra-high field fMRI (>=7T), typically with a spatial resolution 0.8 mm or lower. A common approach to obtain finer separation of the laminar signals is to resample the functional data to higher spatial resolution [1-4]. However, data resampling can result in spatial blurring and reduced layer specificity. Alternatively, one can unmix the underlying laminar signal with a spatial general linear model (spatial GLM) [5-6], where the model of voxel-partial-volume corresponding to specific cortical layer is introduced. This regression approach is likely to provide higher layer specificity but it is more dependent on number of voxels, SNR, model accuracy, etc. Importantly, both approaches rely on the assumption that laminar signal is homogenous within the analysed segment of the layer. However, in experimental data, variation of signal intensity along laminae is expected, possibly originating from neuronal, vascular sources or segmentation errors. We first use simulated data under the assumption of layer signal homegeneity comparing the resampling approach to spatial GLM. We test their dependence on number of voxels, signal SNR, and voxel size. Next, we introduce ‘cortical laminagram’ to study signal variation along lamina in experimental fMRI data to explore the laminar profiles along smaller segments in the ROI.

In this 7T study, we examined potential causes of apparent absence of perfusion in the rightinferior temporal lobe, by (i) assessing the B1+ distributions on two 1Tx/32Rx head-coils torule out a hardware source, and (ii) optimising the spatial positioning of dielectric pads toachieve a more symmetric B1+ field. We observed that using an optimised dielectric padpositioning allows for a near whole-brain symmetric B1+, thereby, ensuring the adiabaticcondition for the inversion pulse is fulfilled, resulting in the robust measurement of perfusionin the right temporal lobes.

Presented at:Brain-in-depth (BID) 2018 - Symposium on layer-dependent MRIAbstract:Cortical layers occupy a much finer spatial scale than the typical sub-millimetre voxel sizes used at 7T and are inadequate to directly sample the depth-dependent BOLD signal (Fig. 1, red). Existing approaches address this issue by upsampling the depth-specific signal with post-processing algorithms1,2. However, the depth-specific signals lumped together during acquisition cannot be fully recovered. Hence, we propose to forego the voxel isotropicity and acquire fMRI data at a very high spatial resolution along the cortical depths direction (100µm i.e. at a “true” laminar resolution, see Fig. 1, blue), eliminating the need to determine laminar profiles via interpolation and upsampling.

Presented at:Joint Annual Meeting ISMRM-ESMRMB 2018Abstract:Despite the availability of more sophisticated coil-combination methods like Roemer and STARC, ultra-high field fMRI studies still use the conventional sum-of-squares (SoS) method for combining the images of the individual coils from multi-channel RF-coil arrays. Here we use a memory-efficient, CPU/GPU accelerated coil-combine toolbox written in Python to compare and characterise the effect of methods such as covariance-weighted sum-of-squares (CovSoS), Roemer and STARC on sub-millimetre resolution GE-EPI laminar fMRI data acquired at 9.4T, and demonstrate the benefit of using optimised coil-combination for UHF fMRI studies.

Recent developments of ultra-high field (UHF) MRI and high-resolution CBV-sensitive VASO sequences have made it possible to measure activity changes across cortical depths. However, most methods are limited to individual brain areas of large cortical thicknesses (4mm in M1), long repetition times and small matrix sizes. In this study, we developed multiple VASO sequence approaches to achieve: 1.)Whole-brain coverage (104 slices) at sub-millimeter layer resolutions 2.) Sub-second TRs (TR = 650ms) at sub-millimeter layer resolutions 3.) Extra-high 0.5mm isotropic resolutions with matrix sizes of 316 We tested new sequence concepts and validated their applicability for the neuroscientific context. &nbsp

Attention and perception are fundamental components of the brain that have been extensively studied over the years. This thesis aims to advance our understanding how the brain processes attention and perception using advanced imaging techniques like functional magnetic resonance imaging (fMRI) at ultra-high field (UHF). The cholinergic system plays a vital role in attentional control, making the nucleus basalis of Meynert (nbM) an initial focus of the research as it serves as the primary source of cortical acetylcholine. Previous MRI studies that attempted to locate the nbM are critically reflected, by analyzing their methods, limitations, and potential areas for improvement. To explore the neural mechanisms involved in visual perception, the research employs a classic brightness induction paradigm during 7T fMRI scans. Additionally, the development of experimental brightness illusion stimuli is involved, which might prove valuable for future studies using neuroimaging techniques.By delving into these areas, this thesis aims to contribute valuable insights to answer these open questions in modern neuroscience.

We present a comprehensive study on the non-invasive measurement of hippocampal perfusion. Using high-resolution 7 Tesla arterial spin labelling data, we generated robust perfusion maps and observed significant variations in perfusion among hippocampal subfields, with CA1 exhibiting the lowest perfusion levels. Notably, these perfusion differences were robust and detectable even within five minutes and just fifty perfusion-weighted images per subject. To understand the underlying factors, we examined the influence of image quality metrics, various tissue microstructure and morphometry properties, macrovasculature and cytoarchitecture. We observed higher perfusion in regions located closer to arteries, demonstrating the influence of vascular proximity on hippocampal perfusion. Moreover, ex vivo cytoarchitectonic features based on neuronal density differences appeared to correlate stronger with hippocampal perfusion than morphometric measures like gray matter thickness. These findings emphasize the interplay between microvasculature, macrovasculature, and metabolic demand in shaping hippocampal perfusion. Our study expands the current understanding of hippocampal physiology and its relevance to neurological disorders. By providing in vivo evidence of perfusion differences between hippocampal subfields, our findings have implications for diagnosis and potential therapeutic interventions. In conclusion, our study provides a valuable resource for extensively characterising hippocampal perfusion.