Distinct Functional Connectivity Signatures of Impaired Social Cognition in Multiple Sclerosis

Objective: Multiple sclerosis (MS) is characterized by impairments in basic cognitive functions such as information processing speed as well as in more complex, higher-order domains such as social cognition. However, as these deficits often co-occur, it has remained challenging to determine whether they have a specific pathological basis or are driven by shared biology. Methods: To identify neural signatures of social cognition deficits in MS, data were analyzed from n = 29 patients with relapsing-remitting MS and n = 29 healthy controls matched for age, sex, and education. We used neuropsychological assessments of information processing speed, attention, learning, working memory, and relevant aspects of social cognition (theory of mind, emotion recognition (ER), empathy) and employed neuroimaging of CNS networks using resting-state functional connectivity. Results: MS patients showed significant deficits in verbal learning and memory, as well as implicit ER. Performance in these domains was uncorrelated. Functional connectivity analysis identified a distinct network characterized by significant associations between poorer ER and lower connectivity of the fusiform gyrus (FFG) with the right lateral occipital cortex, which also showed lower connectivity in patients compared to controls. Moreover, while ER was correlated with MS symptoms such as fatigue and motor/sensory functioning on a behavioral level, FFG connectivity signatures of social cognition deficits showed no overlap with these symptoms. Conclusions: Our analyses identify distinct functional connectivity signatures of social cognition deficits in MS, indicating that these alterations may occur independently from those in other neuropsychological functions

Coulomb dissociation of N 20,21

Neutron-rich light nuclei and their reactions play an important role in the creation of chemical elements. Here, data from a Coulomb dissociation experiment on N20,21 are reported. Relativistic N20,21 ions impinged on a lead target and the Coulomb dissociation cross section was determined in a kinematically complete experiment. Using the detailed balance theorem, the N19(n,γ)N20 and N20(n,γ)N21 excitation functions and thermonuclear reaction rates have been determined. The N19(n,γ)N20 rate is up to a factor of 5 higher at

Monitoring of Calcite Precipitation in Hardwater Lakes with Multi-Spectral Remote Sensing Archives

Calcite precipitation is a common phenomenon in calcium-rich hardwater lakes during spring and summer, but the number and spatial distribution of lakes with calcite precipitation is unknown. This paper presents a remote sensing based method to observe calcite precipitation over large areas, which are an important prerequisite for a systematic monitoring and evaluation of restoration measurements. We use globally archived satellite remote sensing data for a retrospective systematic assessment of past multi-temporal calcite precipitation events. The database of this study consists of 205 data sets that comprise freely available Landsat and Sentinel 2 data acquired between 1998 and 2015 covering the Northeast German Plain. Calcite precipitation is automatically identified using the green spectra and the metric BGR area, the triangular area between the blue, green and red reflectance value. The validation is based on field measurements of CaCO3 concentrations at three selected lakes, Feldberger Haussee, Breiter Luzin and Schmaler Luzin. The classification accuracy (0.88) is highest for calcite concentrations ≥0.7 mg/L. False negative results are caused by the choice of a conservative classification threshold. False positive results can be explained by already increased calcite concentrations. We successfully transferred the developed method to 21 other hardwater lakes in Northeast Germany. The average duration of lakes with regular calcite precipitation is 37 days. The frequency of calcite precipitation reaches from single time detections up to detections nearly every year. False negative classification results and gaps in Landsat time series reduce the accuracy of frequency and duration monitoring, but in future the image density will increase by acquisitions of Sentinel-2a (and 2b). Our study tested successfully the transfer of the classification approach to Sentinel-2 images. Our study shows that 15 of the 24 lakes have at least one phase of calcite precipitation and all events occur between May and September. At the lakes Schmaler Luzin and Feldberger Haussee, we illustrated the influence of ecological restoration measures aiming at nutrient reduction in the lake water on calcite precipitation. Our study emphasizes the high variance of calcite precipitation in hardwater lakes: each lake has to be monitored individually, which is feasible using Landsat and Sentinel-2 time series

Classification and monitoring of reed belts using dual-polarimetric TerraSAR-X time series

Synthetic aperture radar polarimetry (PolSAR) and polarimetric decomposition techniques have proven to be useful tools for wetland mapping. In this study we classify reed belts and monitor their phenological changes at a natural lake in northeastern Germany using dual-co-polarized (HH, VV) TerraSAR-X time series. The time series comprises 19 images, acquired between August 2014 and May 2015, in ascending and descending orbit. We calculated different polarimetric indices using the HH and VV intensities, the dual-polarimetric coherency matrix including dominant and mean alpha scattering angles, and entropy and anisotropy (normalized eigenvalue difference) as well as combinations of entropy and anisotropy for the analysis of the scattering scenarios. The image classifications were performed with the random forest classifier and validated with high-resolution digital orthophotos. The time series analysis of the reed belts revealed significant seasonal changes for the double-bounce–sensitive parameters (intensity ratio HH/VV and intensity difference HH-VV, the co-polarimetric coherence phase and the dominant and mean alpha scattering angles) and in the dual-polarimetric coherence (amplitude), anisotropy, entropy, and anisotropy-entropy combinations; whereas in summer dense leaves cause volume scattering, in winter, after leaves have fallen, the reed stems cause predominately double-bounce scattering. Our study showed that the five most important parameters for the classification of reed are the intensity difference HH-VV, the mean alpha scattering angle, intensity ratio HH/VV, and the coherence (phase). Due to the better separation of reed and other vegetation (deciduous forest, coniferous forest, meadow), winter acquisitions are preferred for the mapping of reed. Multi-temporal stacks of winter images performed better than summer ones. The combination of ascending and descending images also improved the result as it reduces the influence of the sensor look direction. However, in this study, only an accuracy of ~50% correct classified reed areas was reached. Whereas the shorelines with reed areas (>10 m broad) could be detected correctly, the actual reed areas were significantly overestimated. The main source of error is probably the challenging data geocoding causing geolocation inaccuracies, which need to be solved in future studies

Langzeitmonitoring von Seen im nördlichen mitteleuropäischen Tiefland mit optischen und Radar-Fernerkundungsbildern

The glacial landscape of the northern Central European lowlands in Germany and Poland is characterized by a large number of lakes. These lakes fulfill important ecosystem services, however, they are sensitive to climate change, land use changes, and human impact. Very few of them are regularly monitored in situ. This thesis tests the potential of remote sensing imagery for the long-term monitoring of lakes in northern Central European lowlands, because remote sensing imagery enables an area wide monitoring with the possibility of multi-temporal observations. The thesis comprises the results of four scientific papers aiming at the development and evaluation of new remotely-sensed lake monitoring methods, in combination with instrument and proxy-based monitoring. The monitoring is focused on 1) the reconstruction of lake levels and the monitoring of 2) shoreline vegetation and 3) calcite precipitation as part of the Helmholtz Virtual Institute for Integrated Climate and Landscape Evolution Analyses (ICLEA). The lakes are characterized by seasonal and long-term lake level changes, which affect the shoreline vegetation (reed belts). In this thesis, lake levels are reconstructed by intersecting water-land borders that were derived from remote sensing imagery together with topographic data. Aerial photos are tested for a long-term monitoring approach. High-resolution multi-spectral satellite imagery is utilized for the monitoring of short-term lake level changes. The accuracy of the reconstructed levels is high. However, there are very strict prerequisites that need to be met by the image data and the lakes to achieve this accuracy. The greatest challenge is vegetation at the shorelines that covers the water-land border. The optical images are also affected by low solar angles or clouds. Synthetic aperture radar (SAR) imagery enables a regular lake monitoring: thus, high-resolution dual-co-polarized SAR imagery is used for the monitoring of reed belts. Polarimetric decomposition techniques allow the discrimination of different scattering scenarios and show the phenological changes in the reed belts: in summer dense leaves cause volume scattering, whereas in winter, the deciduous reed stems cause predominately double-bounce scattering. Thus, double-bounce-sensitive polarimetric parameters and winter images are preferred for a classification of reed. However, the application of this method for long-term lake monitoring is limited, because of a lack of polarimetric archive data and its geocoding. The third monitoring subject is calcite precipitation. Calcite precipitation is an extensive limnological process that dyes the lake water a milky turquoise. This allows the use of medium-resolution optical satellite images: the Landsat archives and new Sentinel-2 imagery enable a long-term and large scale monitoring of calcite precipitation. The most accurate classification is hereby based on a ratio of the blue, green, and red spectral bands, because calcite precipitation enhances the reflectance in the green band. The approach is evaluated with field measurements and then propagated to 21 lakes to monitor frequency and duration of calcite precipitation events. The monitoring results of this thesis emphasizes the temporal heterogeneity within lakes and the spatial heterogeneity between the lakes. They confirm the importance of remotely-sensed monitoring for large scale monitoring. It is shown that the success of the developed monitoring approaches is limited by their demands on remote sensing data: long time series, and high temporal and spatial resolution. The main limitations are spatial and temporal resolution, specifically in the beginning of Earth observation with data from very few satellites. Thus, the potential of remote sensing archives for the long-term monitoring of lakes is best exploited if the lake parameter is detectable in medium-resolution imagery, as in case of the monitoring of calcite precipitation.Die Seenlandschaft Nordostdeutschlands und Polens ist Teil des eiszeitlich geprägten mitteleuropäischen Tieflandes. Die Seen sind wichtig für das Ökosystem, sie sind allerdings auch gefährdet durch menschliche Eingriffe und beeinflusst durch Landnutzung- und Klimaänderungen. Hier besteht Forschungsbedarf, denn bisher wurden nur vereinzelt Seen wissenschaftlich untersucht. Dieser Dissertation prüft, inwiefern Fernerkundung (FE) das Monitoring von Seen unterstützen kann, denn FE-Daten erfassen große Gebiete und Archivbilder dokumentieren vergangene Zustände. Ziel der Arbeit ist die Entwicklung und Bewertung neuer fernerkundlicher Monitoringverfahren für Seen in Kombination mit in situ Untersuchungen. Das Monitoring der Seen zielt dabei speziell auf 1) die Rekonstruktion von Seespiegeln sowie das Monitoring von 2) Ufervegetation und 3) Kalzitfällungen ab. Die Arbeit umfasst dabei die Ergebnisse von vier wissenschaftlichen Veröffentlichungen und ist Teil des Virtuellen Instituts zur Integrierten Klima- und Landschaftsentwicklungsanalyse (ICLEA). Langfristige und saisonale Seespiegeländerungen sind typisch für die Seen, aber schnelle oder starke Veränderungen beeinträchtigen beispielsweise die Vegetation an den Ufern und in den Flachwasserbereichen. Mithilfe hochaufgelöster Luftbilder und optischer Satellitenbilder können frühere Uferlinien der Seen bestimmt werden. Verknüpft man diese Uferlinien nun mit topographischen Daten, ergeben sich die dazugehörigen Seespiegel. Luftbilder reichen dabei weit länger in die Vergangenheit als Satellitenbilder. Sie haben dafür aber eine viel geringere zeitliche Auflösung. Trotz guter Ergebnisse ist die Übertragbarkeit der Methode schwierig, da die Anforderungen an die FE-Daten und die Seen sehr hoch sind. Problematisch ist zum Beispiel Vegetation, die die Uferlinie in den Bildern verdeckt. Regelmäßige Aufnahmen sind bei optischen Satellitenbildern aufgrund von Wolken oder niedrigem Sonnenstand ebenfalls nicht möglich. Hier helfen Synthetic Aperture Radar (SAR) Zeitreihen: In dieser Arbeit werden hochaufgelöste, dual-co-polarimetrische SAR Bilder für die Beobachtung von Schilf herangezogen. Durch polarimetrische Entmischung können verschiedene Streuungsmechanismen unterschieden werden und es zeigen sich phänologische Unterschiede des Schilfes: Im Sommer, wenn das Schilf dichte Blätter hat, überwiegt Volumenstreuung, wohingegen es im Winter, ohne Laub, zwischen der Wasserfläche und den Schilfstängeln vermehrt zu Zweifachreflektionen kommt. Eine Kombination aus Winterbildern und polarimetrischen Parametern, die diese Zweifachreflektionen anzeigen, eignet sich daher am besten für die Klassifizierung von Schilf. Leider ist auch hier die großflächige Anwendung der Methode eingeschränkt, da polarimetrische Bilder noch recht selten sind. Kalzitfällungen färben den See trüb Türkis. Diese Färbung ist auch in optischen Satellitenbildern mit mittlerer Auflösung zu sehen. Das bedeutet, dass das Landsat-Archiv und Bilder vom neuen Sentinel-2 Satelliten hier eine langfristige und großflächige Beobachtung erlauben. Die Türkisfärbung geht mit einem Anstieg der Reflexion im grünen Wellenlängenbereich einher, wobei die neuentwickelte Klassifikation die Reflexionen im blauen, grünen und roten Wellenlängenbereich nutzt. Die Übertragbarkeit der Methode wurde nach gründlichen Vergleichen mit Feldmessungen an weiteren 21 Seen getestet. Die Ergebnisse dieser Arbeit zeigen die zeitlichen und räumlichen Unterschiede von Seen und verdeutlichen, wie wichtig FE für ein langfristiges und großflächiges Seenmonitoring ist. Ob die neuen Monitoringverfahren dabei erfolgreich sind, liegt an ihren Voraussetzungen an die FE: Welche räumliche und zeitliche Auflösung ist nötig und welcher Zeitraum muss abgedeckt werden? Hohe räumliche und zeitliche Auflösung ist aber vor allem zu Beginn der FE selten, das heißt das Potential von FE-Archiven wird dann am besten ausgeschöpft, wenn eine mittlere räumliche Auflösung der Daten genügt, wie hier im Falle der Kalzitfällung

Classification and monitoring of reed belts using dual-polarimetric TerraSAR-X time series

Synthetic aperture radar polarimetry (PolSAR) and polarimetric decomposition techniques have proven to be useful tools for wetland mapping. In this study we classify reed belts and monitor their phenological changes at a natural lake in northeastern Germany using dual-co-polarized (HH, VV) TerraSAR-X time series. The time series comprises 19 images, acquired between August 2014 and May 2015, in ascending and descending orbit. We calculated different polarimetric indices using the HH and VV intensities, the dual-polarimetric coherency matrix including dominant and mean alpha scattering angles, and entropy and anisotropy (normalized eigenvalue difference) as well as combinations of entropy and anisotropy for the analysis of the scattering scenarios. The image classifications were performed with the random forest classifier and validated with high-resolution digital orthophotos. The time series analysis of the reed belts revealed significant seasonal changes for the double-bounce–sensitive parameters (intensity ratio HH/VV and intensity difference HH-VV, the co-polarimetric coherence phase and the dominant and mean alpha scattering angles) and in the dual-polarimetric coherence (amplitude), anisotropy, entropy, and anisotropy-entropy combinations; whereas in summer dense leaves cause volume scattering, in winter, after leaves have fallen, the reed stems cause predominately double-bounce scattering. Our study showed that the five most important parameters for the classification of reed are the intensity difference HH-VV, the mean alpha scattering angle, intensity ratio HH/VV, and the coherence (phase). Due to the better separation of reed and other vegetation (deciduous forest, coniferous forest, meadow), winter acquisitions are preferred for the mapping of reed. Multi-temporal stacks of winter images performed better than summer ones. The combination of ascending and descending images also improved the result as it reduces the influence of the sensor look direction. However, in this study, only an accuracy of ~50% correct classified reed areas was reached. Whereas the shorelines with reed areas (>10 m broad) could be detected correctly, the actual reed areas were significantly overestimated. The main source of error is probably the challenging data geocoding causing geolocation inaccuracies, which need to be solved in future studies

Reconstruction of Lake Level Changes of Groundwater-Fed Lakes in Northeastern Germany Using RapidEye Time Series

Groundwater-fed lakes in northeastern Germany are characterized by significant lake level changes, but for only a few lakes are in situ water level measurements available. In this study, we test the potential of RapidEye satellite images for indirectly reconstructing lake level changes. The lake levels are derived by intersecting water-land borders with a high-resolution digital elevation model (DEM). Based on Lake Fürstenseer (LF), we define requirements and limitations of the method. Water-land borders were extracted automatically from the 37 RapidEye images available for the period between 2009 and 2014. Otsu’s threshold was used for the NIR band and for the normalized difference water index (NDWI). The results were validated with in situ gauging, contour lines from the DEM, and in situ Differential Global Positioning System (DGPS) measurements of the shoreline. Using an ideal shoreline subset, the lake levels could be reconstructed with decimeter accuracy using the NIR water-land border, but the levels were systematically underestimated by 0–20 cm. The accuracy of the reconstructed lake level retrieval strongly depends on the precision of the water-land border retrieval, on the accuracy of the DEM, and on the lake level itself. A clear shift of the water-land border with increasing lake level is also essential for the unambiguous reconstruction of different levels. This shift needs to be several times larger than the pixel size. The biggest challenges for lake level reconstruction are the presence of vegetation at the shorelines, the quality of the topographic data in the underwater area, the slope of the shoreline, and shadows in combination with low solar angles

Monitoring of Calcite Precipitation in Hardwater Lakes with Multi-Spectral Remote Sensing Archives

Calcite precipitation is a common phenomenon in calcium-rich hardwater lakes during spring and summer, but the number and spatial distribution of lakes with calcite precipitation is unknown. This paper presents a remote sensing based method to observe calcite precipitation over large areas, which are an important prerequisite for a systematic monitoring and evaluation of restoration measurements. We use globally archived satellite remote sensing data for a retrospective systematic assessment of past multi-temporal calcite precipitation events. The database of this study consists of 205 data sets that comprise freely available Landsat and Sentinel 2 data acquired between 1998 and 2015 covering the Northeast German Plain. Calcite precipitation is automatically identified using the green spectra and the metric BGR area, the triangular area between the blue, green and red reflectance value. The validation is based on field measurements of CaCO3 concentrations at three selected lakes, Feldberger Haussee, Breiter Luzin and Schmaler Luzin. The classification accuracy (0.88) is highest for calcite concentrations ≥0.7 mg/L. False negative results are caused by the choice of a conservative classification threshold. False positive results can be explained by already increased calcite concentrations. We successfully transferred the developed method to 21 other hardwater lakes in Northeast Germany. The average duration of lakes with regular calcite precipitation is 37 days. The frequency of calcite precipitation reaches from single time detections up to detections nearly every year. False negative classification results and gaps in Landsat time series reduce the accuracy of frequency and duration monitoring, but in future the image density will increase by acquisitions of Sentinel-2a (and 2b). Our study tested successfully the transfer of the classification approach to Sentinel-2 images. Our study shows that 15 of the 24 lakes have at least one phase of calcite precipitation and all events occur between May and September. At the lakes Schmaler Luzin and Feldberger Haussee, we illustrated the influence of ecological restoration measures aiming at nutrient reduction in the lake water on calcite precipitation. Our study emphasizes the high variance of calcite precipitation in hardwater lakes: each lake has to be monitored individually, which is feasible using Landsat and Sentinel-2 time series