Progressive neurodegeneration following spinal cord injury: Implications for clinical trials.

OBJECTIVE: To quantify atrophy, demyelination, and iron accumulation over 2 years following acute spinal cord injury and to identify MRI predictors of clinical outcomes and determine their suitability as surrogate markers of therapeutic intervention. METHODS: We assessed 156 quantitative MRI datasets from 15 patients with spinal cord injury and 18 controls at baseline and 2, 6, 12, and 24 months after injury. Clinical recovery (including neuropathic pain) was assessed at each time point. Between-group differences in linear and nonlinear trajectories of volume, myelin, and iron change were estimated. Structural changes by 6 months were used to predict clinical outcomes at 2 years. RESULTS: The majority of patients showed clinical improvement with recovery stabilizing at 2 years. Cord atrophy decelerated, while cortical white and gray matter atrophy progressed over 2 years. Myelin content in the spinal cord and cortex decreased progressively over time, while cerebellar loss decreases decelerated. As atrophy progressed in the thalamus, sustained iron accumulation was evident. Smaller cord and cranial corticospinal tract atrophy, and myelin changes within the sensorimotor cortices, by 6 months predicted recovery in lower extremity motor score at 2 years. Whereas greater cord atrophy and microstructural changes in the cerebellum, anterior cingulate cortex, and secondary sensory cortex by 6 months predicted worse sensory impairment and greater neuropathic pain intensity at 2 years. CONCLUSION: These results draw attention to trauma-induced neuroplastic processes and highlight the intimate relationships among neurodegenerative processes in the cord and brain. These measurable changes are sufficiently large, systematic, and predictive to render them viable outcome measures for clinical trials

Coherent, time-shifted patterns of microstructural plasticity during motor-skill learning

Motor skill learning relies on neural plasticity in the motor and limbic systems. However, the spatial and temporal characteristics of these changes-and their microstructural underpinnings-remain unclear. Eighteen healthy males received 1 hour of training in a computer-based motion game, 4 times a week, for 4 consecutive weeks, while 14 untrained participants underwent scanning only. Performance improvements were observed in all trained participants. Serial myelin- and iron-sensitive multiparametric mapping at 3T during this period of intensive motor skill acquisition revealed temporally and spatially distributed, performance-related microstructural changes in the grey and white matter across a corticospinal-cerebellar-hippocampal circuit. Analysis of the trajectory of these transient changes suggested time-shifted cascades of plasticity from the dominant sensorimotor system to the contralateral hippocampus. In the cranial corticospinal tracts, changes in myelin-sensitive metrics during training in the posterior limb of the internal capsule were of greater magnitude in those who trained their upper limbs vs. lower limb trainees. Motor skill learning is associated with waves of grey and white matter plasticity, across a broad sensorimotor network

Coherent, time-shifted patterns of microstructural plasticity during motor-skill learning

Motor skill learning relies on neural plasticity in the motor and limbic systems. However, the spatial and temporal characteristics of these changes-and their microstructural underpinnings-remain unclear. Eighteen healthy males received 1 h of training in a computer-based motion game, 4 times a week, for 4 consecutive weeks, while 14 untrained participants underwent scanning only. Performance improvements were observed in all trained participants. Serial myelin- and iron-sensitive multiparametric mapping at 3T during this period of intensive motor skill acquisition revealed temporally and spatially distributed, performance-related microstructural changes in the grey and white matter across a corticospinal-cerebellar-hippocampal circuit. Analysis of the trajectory of these transient changes suggested time-shifted cascades of plasticity from the dominant sensorimotor system to the contralateral hippocampus. In the cranial corticospinal tracts, changes in myelin-sensitive metrics during training in the posterior limb of the internal capsule were of greater magnitude in those who trained their upper limbs vs. lower limb trainees. Motor skill learning is associated with waves of grey and white matter plasticity, across a broad sensorimotor network

What Determines the Efficiency of Regional Innovation Systems?

We assess the efficiency of regional innovation systems (RIS) in Germany by means of a knowledge production function. This function relates private sector research and development (R&D) activity in a region to the number of inventions that have been registered by residents of that region. Different measures and estimation approaches lead to rather similar assessments. We find that both spillovers within the private sector as well as from universities and other public research institutions have a positive effect on the efficiency of private sector R&D in the respective region. It is not the mere presence and size of public research institutions, but rather the intensity of interactions between private and public sector R&D that leads to high RIS efficiency. We find that relationship between the diversity of a regions industry structure and the efficiency of its innovation system is inversely u-shaped. Regions dominated by large establishments tend to be less efficient than regions with a lower average establishment size

Relationship between brainstem neurodegeneration and clinical impairment in traumatic spinal cord injury

Background: Brainstem networks are pivotal in sensory and motor function and in recovery following experimental spinal cord injury (SCI). Objective: To quantify neurodegeneration and its relation to clinical impairment in major brainstem pathways and nuclei in traumatic SCI. Methods: Quantitative MRI data of 30 chronic traumatic SCI patients (15 with tetraplegia and 15 with paraplegia) and 23 controls were acquired. Patients underwent a full neurological examination. We calculated quantitative myelin-sensitive (magnetisation transfer saturation (MT) and longitudinal relaxation rate (R1)) and iron-sensitive (effective transverse relaxation rate (R2*)) maps. We constructed brainstem tissue templates using a multivariate Gaussian mixture model and assessed volume loss, myelin reductions, and iron accumulation across the brainstem pathways (e.g. corticospinal tracts (CSTs) and medial lemniscus), and nuclei (e.g. red nucleus and periaqueductal grey (PAG)). The relationship between structural changes and clinical impairment were assessed using regression analysis. Results: Volume loss was detected in the CSTs and in the medial lemniscus. Myelin-sensitive MT and R1 were reduced in the PAG, the CSTs, the dorsal medulla and pons. No iron-sensitive changes in R2* were detected. Lower pinprick score related to more myelin reductions in the PAG, whereas lower functional independence was related to more myelin reductions in the vestibular and pontine nuclei. Conclusion: Neurodegeneration, indicated by volume loss and myelin reductions, is evident in major brainstem pathways and nuclei following traumatic SCI; the magnitude of these changes relating to clinical impairment. Thus, quantitative MRI protocols offer new targets, which may be used as neuroimaging biomarkers in treatment trials

Quantized State Systems in System Simulation - Analysis of Algorithms and Implementation in MATLAB/Simulink

Abweichender Titel laut Übersetzung der Verfasserin/des VerfassersZsfassung in engl. SpracheIn der heutigen Zeit ist MATLAB/Simulink wohl eine der meist benutzten Simulationsumgebungen. Sowohl im Umfang der Bibliothek als auch in der Vielseitigkeit der numerischen Verfahren bietet Simulink sehr viele Möglichkeiten, Modelle einfach und effizient zu simulieren. Ein wichtiger Bestandteil von Simulink sind numerische Differentialgleichungslöser. Sie haben die Aufgabe die Lösung von kontinuierlichen Systemen approximativ zu berechnen, da zumeist keine Möglichkeit besteht diese auf analytischem Weg zu ermittelt. Diese Verfahren müssen aufgrund begrenzter Ressourcen (Computersystem) entweder die Zeit oder den Zustand des kontinuierlichen Systems diskretisieren. Tatsache ist, dass jeder in Simulink integrierter Differentialgleichungslöser die Zeit diskretisiert. In dieser Arbeit werden wir sehen, dass es eine Vielzahl von Systemen gibt, bei denen diese Löser Schwächen aufweisen. Ein Beispiel dafür sind Modelle, in denen die jeweiligen Parameter einen Zeitpunkt definieren, in welchem es zu einer unstetigen Änderung des Zustandes kommt. Dieser Zeitpunkt wird künftig auch als Diskontinuität bezeichnet. Modelle mit dieser Eigenschaft werden in dieser Arbeit öfter herangezogen. Damit Simulink auch mit dieser Problemstellung in Zukunft besser umgehen kann, wurde im Laufe dieser Arbeit ein Differentialgleichungslöser nach dem Quantized State System (kurz: QSS) Formalismus implementiert. Dieser unterscheidet sich ganz wesentlich von den in Simulink zur Verfügung stehenden Lösern, da beim QSS-Verfahren nicht die Zeit, sondern der Zustand diskretisiert wird. Anders als bei zeitorientierten Verfahren werden hier Diskontinuitäten immer auf direktem Weg erkannt. Diese Arbeit beschäftigt sich im Wesentlichen mit der Umsetzung und Anwendung des QSS-Verfahrens. Die ausgewählten Beispiele in dieser Arbeit sollen einen Eindruck schaffen, wie sehr sich das Verhalten des QSS-Verfahrens von dem Verhalten zeitdiskreter Verfahren unterscheidet. Außerdem beinhaltet diese Arbeit einen theoretischen Abschnitt, der den Fehler und die Stabilität des QSS-Verfahrens untersucht.Nowadays MATLAB/Simulink is probably one of the most used simulation software. Simulink provides a large library of blocks and many capabilities of numerical tools for a simple and efficient simulation. An important part of Simulink are the numerical differential solvers. Their task is to solve continuous systems in an approximatelly way, because in most cases there exists no analytical methode to get the solution of this systems. Numerical solvers are always faced with finite ressources (like a computersystem). This is the reason, that they have to discretise the time or the state. The fact is, that all in Simulink integrated solvers discretise the time. But not always this method leads to good results. Later we will see, that there exists many continuous systems, where these solvers get in trouble. One example are models, which have discontinuities. To deal with this problem this master thesis presents a solver based on the Quantized State System (QSS) which solves such systems by discretising the state rather then the time. The big advantage of this approach is that the solver handles discontinuities in a direct way. This master thesis contains the implementation of this solver and its usage with some selected models. This models show the difference in the behaviour between the QSS method and the conventional time-discrete methods. Beneath that this master thesis encloses a theoretical part where the error and the stability of the QSS method are discussed.6

Neurodegeneration in the spinal ventral horn prior to motor impairment in cervical spondylotic myelopathy

Remote grey matter pathology has been suggested rostral to the compression site in cervical spondylotic myelopathy (CSM). We used computational neuroimaging to assess in-vivo the extent and functional relevance of neurodegeneration in ventral and dorsal horns above the site of compression in the cervical cord of CSM patients. Twenty patients with CSM and eighteen healthy subjects underwent a high-resolution structural and diffusion MRI protocol at vertebra C2/C3. Patients received comprehensive clinical assessments. T2*-weighted data were used to segment the cross-sectional area of the grey matter into the ventral and dorsal horns. Within the ventral and dorsal horns mean diffusivity (MD) and fractional anisotropy (FA) derived from diffusion tensor imaging data determined the underlying microstructural integrity. Finally, the relationships between neurodegeneration occurring in the grey and white matter and clinical impairment were investigated. Patients suffered from mild to moderate CSM with mainly sensory impairment. The cross-sectional area of the ventral horns was not reduced (p=0.863) when compared to controls, but MD was increased (p=0.045). Greater increases in MD within the ventral horn were associated with white matter diffusivity changes (increased MD: p=0.013; decreased FA: p=0.028) within the lateral corticospinal tract. In contrast, dorsal horn cross-sectional area was reduced by 16.0% (p<0.001) without alterations in diffusivity indices when compared to controls. No associations between neurodegeneration and clinical impairment were evident. Grey matter atrophy and microstructural changes are evident remote to the compression site in CSM patients. Prior to marked motor impairment, pathophysiological changes in the ventral horns (e.g. motoneurons) related to white matter changes within the corticospinal tract. Thus, neuroimaging biomarkers of cord grey matter integrity reveal focal neurodegeneration prior to marked clinical impairment and thus could serve as predictors of ensuing impairment in CSM patients

Quantitative MRI of rostral spinal cord and brain regions is predictive of functional recovery in acute spinal cord injury

Objective: To reveal the immediate extent of trauma-induced neurodegenerative changes rostral to the level of lesion and determine the predictive clinical value of quantitative MRI (qMRI) following acute spinal cord injury (SCI). Methods: Twenty-four acute SCI patients and 23 healthy controls underwent a high-resolution T1-weighted protocol. Eighteen of those patients and 20 of controls additionally underwent a multi-parameter mapping (MPM) MRI protocol sensitive to the content of tissue structure, including myelin and iron. Patients were examined clinically at baseline, 2, 6, 12, and 24 months post-SCI. We assessed volume and microstructural changes in the spinal cord and brain using T1-weighted MRI, magnetization transfer (MT), longitudinal relaxation rate (R1), and effective transverse relaxation rate (R2*) maps. Regression analysis determined associations between acute qMRI parameters and recovery. Results: At baseline, cord area and its anterior-posterior width were decreased in patients, whereas MT, R1, and R2* parameters remained unchanged in the cord. Within the cerebellum, volume decrease was paralleled by increases of MT and R2* parameters. Early grey matter changes were observed within the primary motor cortex and limbic system. Importantly, early volume and microstructural changes of the cord and cerebellum predicted functional recovery following injury. Conclusions: Neurodegenerative changes rostral to the level of lesion occur early in SCI, with varying temporal and spatial dynamics. Early qMRI markers of spinal cord and cerebellum are predictive of functional recovery. These neuroimaging biomarkers may supplement clinical assessments and provide insights into the potential of therapeutic interventions to enhance neural plasticity. Keywords: Spinal cord injury, Quantitative neuroimaging, Acute micro-structural changes, Brain and spinal cord atrophy, Voxel-based morphometry and quantificatio