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The spinal cord is not only the first part of the central nervous system where somatosensory information is processed, but also plays a substantial role in both acute and chronic forms of pain. Imaging this structure with fMRI faces several unique challenges, but has recently become feasible. Here, I will present several studies that investigate the spinal cord’s resting-state organization, its evoked responses to noxious stimulation and a modulation thereof due to cognitive manipulations. Having laid this ground-work, I will present current and planned studies that are based on the theory of predictive coding and aim to deconstruct the spinal cord pain response into prediction and prediction error signals. My hope is that this will allow for a more mechanistically informed understanding of pain in both its healthy and pathological form. [mehr]

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Deep brain stimulation treatment allows for the recording of local field potentials in the subthalamic nucleus of patients with Parkinson’s disease. This has revealed that beta band oscillations (13-30Hz) are a hallmark of the disease. In this presentation, I will first show how beta band oscillations relate to Parkinsonian symptoms. Their coupling with high-frequency oscillations (HFO, 150-400Hz) might be an important clue in order to understand how they lead to movement impairment. However, little is known about the neuronal origin of these HFO. We investigated whether they are likely to arise from the same cell populations as beta oscillations using intra-operative recordings. This involved localization of electrode contacts on post-operative MRI scans and warping to MNI space for group-level results. Finally, in the last part of the talk I will present our efforts to study the effect of dopaminergic medication on synaptic coupling strengths within the cortico-basal ganglia circuit using dynamic causal modelling. [mehr]

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Over the last couple of years, the public fascination about colorful brain images seems to have a little waned and also expectations that social neuroscience will soon replace psychology. In this situation, the availability of in-vivo histology – in itself certainly a highly valuable method to validate imaging data and to search for objective pathological criteria – may have a problematic sociopolitical effect: Offering in-vivo anatomical information of new quality may foster unjustified trust in more problematic applications of neuroimaging. The talk will discuss this issue in light of shifting trends over the last decades: The availability of new technologies for visualizing brain activity generated some 25 years ago expectations to identify the centers responsible for all psychic states and to “reduce” mental processes to neuronal states – a project spurring harsh critiques from philosophy and cultural studies. With the visualization of more sophisticated phenomena, social and cultural neuroscience emerged, replacing overstated reductionist claims by integrating sociocultural aspects into neuroimaging but kindling “critical neuroscience” to question implicit essentialist assumptions. The new realism of in-vivo histology poses the question whether it will undermine concerns about the societal applications of neuroimaging. [mehr]

There is an increasing number of research studies that are based on quantitative MR imaging (qMRI) techniques for the direct mapping of brain tissue properties. The parameters most frequently mapped are the water content or proton density (PD) and the relaxation times (T1, T2, T2*). An important application of qMRI is the construction of synthetic anatomical data sets with novel contrasts. In clinical studies, the careful evaluation of qMRI data allows for the detection of diffuse pathologies in normal appearing brain tissue. However, the design of reliable mapping methods is technically challenging as various secondary effects have to be compensated for to avoid a residual bias in the data. In the presentation, some of the most prominent qMRI techniques will be shortly described. There will be a special focus on the application of qMRI in clinical research, in particular for Tumour Imaging, in Multiple Sclerosis (MS) and in Epilepsy. [mehr]

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The arrangement, length, and microstructural properties of long-range connections in the central nervous system determine how information is distributed across the brain. To date, diffusion magnetic resonance imaging (dMRI)-based tractography is the only in vivo technique for mapping structural connections in the human brain. However, mapping from diffusion to fiber pathways is still ill-posed. As a result, tractography algorithms can take "wrong turns" and produce false positive and/or false negative connections. To address this problem, microstructure-informed tractography has been suggested. It is an emerging computational framework that associates each computed fiber tract with microstructural properties, e.g., metrics for axon diameter or density, using the dMRI technique. Our highly inter-disciplinary project with the above title is funded by the German Research Foundation (DFG) under the Priority Programme "Computational Connectomics" (SPP 2041). Four Principal Investigators (Siawoosh Mohammadi, Univ. Hamburg; Alfred Anwander & Stefan Geyer, MPI CBS Leipzig; Markus Morawski, Univ. Leipzig) plan to develop a computational framework for microstructure-informed tractography that addresses these limitations using multi-modal quantitative MRI at ultra-high spatial resolution. Moreover, we will develop an advanced ex vivo histology analysis strategy based on complementary 2-D (high-resolution semithin and ultrathin sectioning) and 3-D (CLARITY) techniques. We will combine histology with MRI ex vivo to validate the model at central junctions of long-range fiber pathways within the well characterized human voluntary motor control network. Our project aims at innovative new insights into MRI-based computational models for in vivo tractography. Funding started in May 2018. In this Institute Colloquium I will elaborate on the conceptual background from a neuroanatomical point of view and present first microstructural results. [mehr]

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The observation of the living body by the magnetic resonance imaging (MRI) depends on the spatial resolution and signal noise ratio (SNR), as well as relaxation time and contrast which is a tissue parameter. The advent of 7 tesla (T) ultra high field MR technology provides unprecedented capabilities for non-invasive imaging of human and animal model brain. This technical ability encompasses a range of functional and structural domains, as well as new opportunities for quantifying neurochemicals using spectroscopic techniques. In addition, increasing the static magnetic field strength promotes signal phase dispersion and shift. Predicted benefits included a stronger Blood Oxygenation Level Dependent (BOLD) effect which is used for detecting brain activity, improved signal and contrast-to-noise (CNR) ratio. By using optimal measurement techniques, improved CNR provides the delineation of the brain microstructure including laminar structure in cortex in vivo. In this talk, I'd like to present our experiences of 7T human brain imaging, especially in high resolution susceptibility imaging and somatotopic fMRI studies. [mehr]

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Organizers are Prof. Nikolaus Weiskopf, Prof. Harald Moeller, Dr Esther Kuehn, Dr Robert Trampel, and Daniel Haenelt. [mehr]

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In this talk I will introduce epilepsy treatment using surgery in children, which can be highly effective when drug therapy fails. Many of these patients have cortical abnormalities that are termed focal cortical dysplasia's. In this context, the identification and classification of abnormal tissue that is performed using MRI has important implications for treatment. However, there is also a unique scientific opportunity to validate MRI measures by comparison to tissue samples obtained during surgery. In this talk I show some of our results using diffusion-based MRI maps and some preliminary analysis of MPM maps. Sara Lorio will then describe our work using quantitative susceptibility maps to characterise abnormalities in cortical structure in focal cortical dysplasia. [mehr]

The first part of the presentation deals with an improvement of the central SNR of human head array at ultra-high magnetic fields (UHF, > 7T). Increasing the number of surface loops in a human head receive (Rx) array improves the peripheral signal-to-noise ratio (SNR), while SNR near the brain center doesn’t substantially change. Recent theoretical works demonstrated that an optimal central SNR at UHF requires contribution of two current patterns associated with a combination of surface loops and dipole antennas. Use of various dipole antennas as MRI RF detectors has been recently introduced and successfully implemented mostly for imaging human body sized objects. In this work, we evaluated and compared several Rx dipole-like elements for use within human head UHF Rx-array. We constructed and characterized novel single-row and double-row phased arrays, which consisted of transceiver (TxRx) surface loops and Rx-dipoles. We demonstrated that combining surface loops and dipole-like elements substantially (> 30%) improve SNR near the brain center as compare to arrays consisted of surface loops only. The second part of the presentation discusses an improvement of the transmit (Tx) coverage of the human head array coils. Due to a substantial shortening of the RF wave length (below 15 cm at 7 T), RF magnetic field at UHF has a specific Tx excitation pattern with strongly decreased (more than 2 times) values at the periphery of a human head. This effect is seen not only in the transversal slice but also in the coronal and sagittal slices, which considerably limits the longitudinal Tx-coverage (along the magnet’s axis) of conventional surface loop head arrays. In this work, we developed a novel human head UHF array consisted of 8 TxRx folded dipole antennas circumscribing a head. Due to an asymmetrical shape of dipole elements, the array couples to the intrinsic “dielectric resonance” mode of the head. Due to this interaction, firstly, the new array provides for a simple way of minimizing the maximum local SAR. Secondly, it provides for a longitudinal coverage better than that achieved by a similar array consisted of unfolded dipoles as well as by an 8-element single-row and 16-element double-row surface loop arrays. [mehr]

Multisensory integration does not only recruit higher-level association cortex, but also primary sensory cortices like A1 (auditory), S1 (somatosensory), and V1 (visual). The underlying anatomical pathways, which might preferentially serve short-latency integration processes, include direct thalamocortical and corticocortical connections across the senses. We investigated how these multisensory connections develop over the individual’s lifespan and how early sensory deprivation alters them. Using tracer injections into A1, S1, and V1 of a rodent model (Mongolian gerbil) we could show that multisensory thalamocortical connections emerge before corticocortical connections but mostly disappear towards the end of the critical sensory period. Early auditory, somatosensory, or visual deprivation increases multisensory connections via axonal reorganization processes mediated by non-lemniscal thalamic nuclei and the primary areas themselves. Functional imaging reveals a mostly reduced stimulus-induced activity but a higher functional connectivity specifically between primary areas in deprived animals. In adult animals, primary sensory cortices receive substantial inputs from thalamic nuclei and cortical areas of non-matched sensory modalities. In very old animals, these multisensory connections strongly decrease in number or vanish entirely. This is likely due to a retraction of the projection neuron axonal branches and is accompanied by changes in anatomical correlates of inhibition and excitation in the sensory thalamus and cortex. Together, we show that during early development, intracortical multisensory connections are formed as a consequence of sensory driven multisensory thalamocortical activity and that during aging, multisensory processing is probably shifted from primary cortices towards other sensory brain areas. [mehr]

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Iron plays a central role in brain development and brain aging. Transmission of neuronal signals, optimization and maintenance of brain structure demand substantial energy and require iron as co-factor for energy supply, myelination and neurotransmitter synthesis. However, iron turns toxic and harmful when present in certain chemical forms and at high concentrations. Increased iron accumulation in age leads to faster brain decline, diminished cognitive abilities and increased risk of neurodegenerative diseases. Understanding these mechanisms and following iron trajectories both on the cellular and the whole brain level is key to an in-depth understanding of brain development, plasticity and aging. Magnetic Resonance Imaging (MRI) is the method of choice for in vivo studies of the iron distribution in the human brain. Relaxation rates and susceptibility measurements provide a wealth of information on both the quantity and distribution of iron. It can potentially access iron dispersion down to the cellular level and provide unique information on the iron chemistry. I propose an innovative approach that combines multimodal quantitative MRI at 3T and 7T with biophysical modeling informed by quantitative iron histology. Thereby, brain tissue composition and cellular iron distribution can be linked to quantitative MRI measures. Two applications are selected to demonstrate how knowledge on MR contrast mechanisms can be employed to create sensitive and specific biomarkers of cellular iron distribution. The first example is a study in superficial white matter, where iron is accumulated in oligodendrocytes and potentially in the short association fibres. It is shown that iron in superficial white matter is not homogeneously distributed across the brain, but accumulated in iron deposits in U-fibre-rich frontal, temporal and parietal association areas. This observation is assigned to higher fibre density or late myelination. In the second study, dopaminergic neurons in substantia nigra are mapped. This information is a first step towards a specific in vivo biomarker for the density of dopaminergic neurons and may therefore provide a future diagnostic for Parkinson’s disease. [mehr]

Quantitative MRI offers the potential to characterize human brain microstructure. Mapping of several MR parameters can be efficiently done using the multi-parameter mapping (MPM) protocol, which allows for quantification of PD, R2*, R1 and MT contrasts, reflecting respectively water content, iron concentration, myelin and macromolecular content. Even small improvements in the reliability of parameter maps are relevant in the context of quantifying myelination changes (for example in disease), which are typically in the order of a couple of percent. Therefore, we investigated correction of physiological artifacts caused by breathing and head motion, which are especially prominent at 7T and in long high resolution acquisitions, and applied the corrections in an elderly cohort including Alzheimer patients. Additionally, we modified the MPM protocol to measure an inhomogenous MT (ihMT) metric that has been shown to have higher specificity to myelin than simple MT contrast, and optimized the measurement protocol at our 3T scanners. [mehr]

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The loss of dopaminergic neurons in the substantia nigra leads to the primary motor symptoms of Parkinson’s disease but starts more than ten years before diagnosis. Dopaminergic neurons contain iron in the pigment neuromelanin. Thus, iron-sensitive MRI promises to map these neurons and their loss. However, the exact mechanisms of MRI contrast in the substantia nigra are not well understood, hindering the development of robust biomarkers. We propose and validate a biophysical model of iron-induced transverse MRI relaxation in the substantia nigra, combining quantitative 3D iron histology with ultra-high-field and -resolution post mortem MRI. We quantify a missing but central parameter of this model, the susceptibility of neuromelanin-bound iron, using quantitative susceptibility mapping at cellular resolution. We demonstrate that iron in dopaminergic neurons, although being only a tiny fraction of all tissue iron, contributes predominantly to iron-induced effective transverse relaxation rate R2* and propose biomarkers of this iron pool. We leverage our understanding of iron-induced transverse relaxation to revisit the interpretation of a potent diagnostic marker of Parkinson’s, the swallow tail sign. Our results provide directions for developing biomarkers for early detection of dopaminergic neuron depletion in Parkinson’s disease. [mehr]

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Magnetic Resonance Fingerprinting (MRF) was introduced in 2013 as an approach for mapping multiple tissue properties simultaneously using MRI. This presentation will provide an overview of the MRF technique, with an emphasis on practical aspects of implementation, and describe how tissue property maps derived from MRF may be leveraged to provide additional information about structure and function in the brain and beyond. [mehr]

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One of the great challenges of neuro-evolutive studies is to build and compare models of the brain connectome between species. The human species is the fruit of a long and complex evolution and its closest phylogenetic living relative among hominids is the chimpanzee. The existence of non-invasive brain microstructure exploration methods, such as magnetic resonance imaging (MRI), has made it possible to explore the differences and commonalities of the chimpanzee and human brain connectivity. Using brain structural and diffusion MRI, two atlases of the superficial and deep white matter connectivity in chimpanzees and humans were created allowing subsequent investigations of their morphology. It allowed to question the singularity of the human brain connectivity with respect to the chimpanzee brain from an hodologic point of view. [mehr]

Magnetic fields are ubiquitous in nature and since a long time also in technology. Yet, there are many open questions, needs for research and emerging new applications. Standards need to be set or refined, and more accurate calibrations are required by industrial adopters of new technologies. A particular challenge and opportunity arise at the lowest end of the spectrum of magnetic fields. With demonstrated measurement sensitivities beyond the femtotesla (per root Hertz) scale, the neuronal activities of the brain following a peripheral nerve stimulus become detectable in a single trial, for example. While even the foundations of physics can be tested at the frontier of lowest metrological noise floors, a current trend is to make magnetic field measurement and imaging viable in application contexts beyond quantum physics laboratories. Here, we will discuss such developments in terms of sensor developments, measurement environments and key use cases. We will focus on atomic gas-based probes of stationary and slowly varying magnetic fields. With trapped ultracold gases, high resolution field mapping can be achieved with relevance to material developments such as indium tin oxide replacements for next-generation touch screens and solar panels. On the other hand, cells containing thermal atomic vapours can provide highest field sensitivities as part of optically pumped magnetometers with use in clinical neurology or current-density imaging in electric vehicle batteries. [mehr]

MRI signal generation is substantially influenced by factors such as water content, iron, myelin, and several other contributors. Iron levels can be directly assessed using mass spectrometry, while the quantitative impacts of myelin's structure and composition remain unknown to a certain extent and are often inferred from theoretical simulations. Additionally, MRI relaxation rates and susceptibility are sensitive to these tissue constituents, but their specificity is limited. In this context, post-mortem investigations utilizing complementary methods such as TEM, LA-ICP-MS, MALDI-MSI, CARS, and SAXS-TT provide unique insights for the validation and understanding of quantitative MRI parameters. However, in-situ post-mortem MRI has to accommodate for factors like variable temperature, deoxygenated blood, and perfusion. Furthermore, the process of formalin fixation introduces a significant confounder, often obstructing direct conclusions. In this presentation, I aim to summarize our work on translating post-mortem MRI findings to in-vivo conditions, outline the analytical methods used to assess brain tissue structure and composition, and discuss potential collaborations with the MPI CBS. [mehr]

Magnetic resonance (MR) imaging technologies provide unique capabilities to probe the mysteries of biological systems, and have enabled novel insights into anatomy, metabolism, and physiology in both health and disease. However, while MRI is decades old, is associated with multiple Nobel prizes (in physics, chemistry, and medicine), and has already revolutionized fields like medicine and neuroscience, current MRI methods are still very far from achieving the full potential of the MRI signal. In particular, traditional methods are based on classical sampling theory, and suffer from fundamental trade-offs between signal-to-noise ratio, spatial resolution, and data acquisition speed. These issues are exacerbated in high-dimensional applications, due to the curse of dimensionality. Our work addresses the limitations of traditional MR imaging using signal processing approaches that are enabled by modern computational capabilities. These approaches are possible because of certain "blessings of dimensionality," e.g., that high-dimensional data often possess unexpectedly simple structure that can be exploited to alleviate classical barriers to fast high-resolution imaging. This seminar will describe approaches we have developed that use novel constrained imaging models to guide the design of new MR data acquisition and image reconstruction methods, and enable substantial acceleration of both low-dimensional and high-dimensional MR imaging experiments. [mehr]

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Scrutiny of the cortical neuronal circuits underlying human visual perception typically involves the summarization of large-scale recordings of brain activity under different perceptual states, with the combination of various measurement modalities and modeling techniques being critical in revealing organizing principles. In this seminar, we'll delve into the relationship between anatomical structure and evolving patterns of neuronal functional connectivity across the early visual foveal cluster (V1-V2-V3). I will show how we can inform our understanding of visual perception through different recording modalities, combining high-resolution fMRI and laminar electrophysiology with computational modeling. I will present key findings on task-dependent modulation of directed interactions across visual cortical areas in humans and laminar distinctions in visual processing in Macaque, as well as touch on preliminary validation work. Finally, I look forward to discussing new advancements and techniques and to providing a clearer picture of neuronal circuit dynamics at the mesoscopic level. [mehr]

In today's era of computational science, approaches powered by artificial intelligence (AI) have found their way into nearly every scientific domain. From natural sciences to the humanities, especially the emergence of large language models (LLMs) and their general purpose capabilities have opened new ways of processing unstructured data in a scientific context. However, training state-of-the-art AI models, even running them for inference, requires substantial computational resources. High-Performance Computing (HPC) systems, like the ones at the Max Planck Computing and Data Facility (MPCDF), are fitting solutions for executing these demanding AI workloads, and their integration into HPC workflows is increasingly sought after by the scientific community. In this talk we showcase two projects in which such workloads are successfully handled at the MPCDF in close collaboration with the Neurophysics group at the CBS. These projects use AI models to reconstruct and automatically segment high-resolution MRI images. Additionally, we will present a couple of projects revolving around LLMs at the MPCDF and highlight their computational challenges and solutions for HPC systems. [mehr]

Despite the vital role of scientific software, it remains an overlooked part of research, often developed within short funding periods with little support for long-term maintenance. This results in software that is hard to discover and challenging to install. It also lacks interoperability across different computing systems, hindering its reuse and violating the FAIR principles - which advocate for scientific outputs to be Findable, Accessible, Interoperable, and Reusable. In this talk, I will present our attempts at this problem through the Neurodesk.org project, and I will show what we are planning next. [mehr]

Comprehensive description of brain tissue's microstructure is crucial for studying the normal and diseased brain. In the talk I will present an in-vivo biophysical framework for increasing the specificity of quantitative MRI to distinct microstructural features of brain tissue, such as the lipid composition and the iron homeostasis. This non-invasive approach identifies lipidomic-related changes in the aging human brain, and allows to test different aging theories. This approach also reveals the disrupted iron homeostasis in brain tumors, and provides iron-related information inaccessible by conventional MRI approaches. Finally, I will propose a new MRI protocol, for implementing this qMRI approach at the sub-voxel level. By monitoring microstructural processes in living brains, we hope to gain a quantitative and specific description of brain tissue that until now was possible only post-mortem, and may further advance human brain research. [mehr]