Annalen der Juden in den preußischen Staaten besonders in der Mark Brandenburg

[Anton Balthasar König]

The brain’s default state interacts with working memory processes in a complex and load-dependent manner

Recently, many studies about a network active during rest and deactivated during tasks emerged in the literature: the default mode network (DMN). Spatial and temporal DMN features are important markers for psychiatric diseases. Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects. From these findings, the conclusion can be drawn that an increase in resting state DMN activity may go along with an increase in theta power in high-load WM conditions. We followed this hypothesis in a study on 17 healthy subjects performing a visual Sternberg WM task. The DMN was obtained by a BOLD-ICA approach and its dynamics represented by the percent-strength during pre-stimulus periods. DMN dynamics were temporally correlated with EEG theta spectral power from retention intervals. This so-called covariance mapping yielded the spatial distribution of the theta EEG fluctuations associated with the dynamics of the DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention. However, load-dependent correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance during later retention. Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over the course of the retention period. Since both, WM performance and DMN activity, are markers of mental health, our results could be important for further investigations of psychiatric populations.

The brain’s pre-stimulus default state interacts with working memory in a load-dependent manner

Recently, multiple studies showed that spatial and temporal features of a task-negative default mode network (DMN) (Greicius et al., 2003) are important markers for psychiatric diseases (Balsters et al., 2013). Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG and MEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects (Brookes et al., 2011). Negative correlations between DMN activity and theta amplitude have been found during resting state (Jann et al., 2010) as well as during WM (Michels et al., 2010). Likewise, WM training resulted in higher resting state theta power as well as increased small-worldness of the resting brain (Langer et al., 2013). Further, increased fMRI connectivity between nodes of the DMN correlated with better WM performance (Hampson et al., 2006). Hence, the brain’s default state might influence it’s functioning during task. We therefore hypothesized correlations between pre-stimulus DMN activity and EEG-theta power during WM maintenance, depending on the WM load. 17 healthy subjects performed a Sternberg WM task while being measured simultaneously with EEG and fMRI. Data was recorded within a multicenter-study: 12 subjects were measured in Zurich with a 64-channels MR-compatible system (Brain Products) in a 3T Philips scanner, 5 subjects with a 96-channel MR-compatible system (Brain Products) in a 3T Siemens Scanner in Bern. The DMN components was obtained by a group BOLD-ICA approach over the full task duration (figure 1). The subject-wise dynamics were obtained by back-reconstructed onto each subject’s fMRI data and normalized to percent signal change values. The single trial pre-stimulus-DMN activation was then temporally correlated with the single trial EEG-theta (3-8 Hz) spectral power during retention intervals. This so-called covariance mapping (Jann et al., 2010) yielded the spatial distribution of the theta EEG fluctuations during retention associated with the dynamics of the pre-stimulus DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention (figure 2). However, correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance in the middle of the retention period (TANOVA, p<0.05) (figure 3). Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over time. While at a more global, load-independent view pre-stimulus DMN activity correlated positively with theta power during retention, the correlation was inversed during certain time windows in high-load trials, meaning that in trials with enhanced pre-stimulus DMN activity theta power decreases during retention. Since both WM performance and DMN activity are markers of mental health our results could be important for further investigations of psychiatric populations.

Amplitude, Topographie und Latenz von EKP-Komponenten analysiert mit Hilfe von Randomisierungsstatistiken: Ein anwendungsorientierter Ragu-Workshop

Bei EKP-Experimenten ist oft nicht von vornherein klar, in welchen Zeitfenstern Effekte erwartet werden. Daher müssen Analysen die Daten über mehrere Zeitfenster hinweg explorieren. Darüber hinaus sind statistische Analysen, die alle Elektroden berücksichtigen, wünschenswert, aber nicht trivial. Zur Lösung dieser Probleme präsentieren wir hier das Programm Ragu (Randomization Graphical User interface), das spezifisch für die statistische Auswertung von Mehrkanal EEG-Experimenten eingesetzt werden kann. Ragu soll Wissenschaftlern die Möglichkeit geben, die Signifikanzen von EKP-Effekten global zu untersuchen, ohne die Notwendigkeit von A-Priori-Annahmen. Das Programm basiert auf der Messung von Feldstärke-Differenzen unter Berücksichtigung aller Elektroden. Im ersten Teil dieses Workshops werden wir die Notwendigkeit von topografischen ERP-Analysen angesichts des Volumenleitungsproblems herausarbeiten und Vergleiche zu Einzelelektroden-Ansätzen anstellen. Wir werden an Hand unserer frei erhältlichen in-house Software Ragu das Prinzip von Randomisierungsstatistiken erklären und deren unterschiedliche Anwendungsmöglichkeiten für ERP-Analysen. In einem zweiten Teil haben die Teilnehmenden die Gelegenheit, Ragu an einem Beispielsatz auszuprobieren und Möglichkeiten der Anwendung von Ragu in ihrer eigenen Forschungs zu besprechen.

Ms. Ff. Mus. 1238 - Dominica VI. post Trinit. : Liebet eure Feinde; segnet die euch fluchen ; a canto, alto, tenore, basso con i ripieni, 2 violini, 2 hautbois, viola, violoncello,violono, bassono ed organo

di Telemann

Ms. Ff. Mus. 1246 - Am Neu-Jahrs-Tag : Lobet den Herrn p ; C. A. T. B., 2 violini, viola, 2 oboe, 3 clarini, tympano, violoncello, organo

del S. Telemann

Geschichte der alttestamentlichen Religion

von Eduard König

Einige Worte über die auch seit der Verfassung unglücklichen Verhältnisse der Israeliten in der Provinz Hanau

von [J. D.] Loebenstern

Hemoglobin, iron metabolism and angiographic coronary artery disease (The Ludwigshafen Risk and Cardiovascular Health Study).

BACKGROUND Anemia has been shown to be a risk factor for coronary artery disease and mortality. The involvement of body iron stores in the development of CAD remains controversial. So far, studies that examined hemoglobin and parameters of iron metabolism simultaneously do not exist. METHODS AND RESULTS Hemoglobin and iron status were determined in 1480 patients with stable angiographic coronary artery disease (CAD) and in 682 individuals in whom CAD had been ruled out by angiography. The multivariate adjusted odds ratios (OR) for CAD in the lowest quartiles of hemoglobin and iron were 1.62 (95%CI: 1.22-2.16), and 2.05 (95%CI: 1.51-2.78), respectively compared to their highest gender-specific quartiles. The fully adjusted ORs for CAD in the lowest quartiles of transferrin saturation, ferritin (F) and soluble transferrin receptor (sTfR)/log10F index were 1.69 (95%CI: 1.25-2.27), 1.98 (95%CI: 1.48-2.65), and 1.64 (95%CI: 1.23-2.18), respectively compared to their highest gender-specific quartiles. When adjusting in addition for iron and ferritin the OR for CAD in the lowest quartiles of hemoglobin was still 1.40 (95%CI: 1.04-1.90) compared to the highest gender-specific quartiles. Thus, the associations between either iron status or low hemoglobin and CAD appeared independent from each other. The sTfR was only marginally associated with angiographic CAD. CONCLUSIONS Both low hemoglobin and iron depletion are independently associated with angiographic CAD.