Studies on the hydride formation of Zintl-phases of the alkaline earth metals with aluminium, gallium and silicon

Die vorliegende Arbeit beschäftigt sich mit der Untersuchung der Hydridbildung von Zintl-Phasen einiger Erdalkalimetalle (Calcium, Strontium, Barium) sowie Europium und Ytterbium mit den elektronegativeren Bindungspartnern Aluminium, Gallium und Silicium. Der Fokus lag dabei auf der Strukturaufklärung mittels Röntgenbeugung, sowie (in situ-)Neutronenbeugung und der damit verbundenen Möglichkeit, Reaktionswege aufzuklären. Hiervon wurde bei CaSi und SrGa2 Gebrauch gemacht, die ex situ bereits gut charakterisiert sind. Für das Gallid wurde eine direkte Hydridbildung ohne Zwischenstufen festgestellt. Beim Silicid konnte dagegen ein Intermediat beobachtet werden, dessen Bildung reversibel ist und das nur unter Wasserstoffdruck stabil ist. Für das Intermediat wurde ein vorläufiges Strukturmodell (Pnma, a = 10,998(2) Å, b = 3,8897(6) Å, c = 13,527(3) Å) gefunden, das Ähnlichkeiten zum bekannten CaSiDx (x ≈ 1,0 - 1,3) aufweist, jedoch nur etwa ein Drittel des Wasserstoffgehalts besitzt. Die anschließende weitere Aufnahme von Wasserstoff erfolgt in gewissen Grenzen kontinuierlich. Ex situ-Untersuchungen an den Verbindungen EuGa2 und YbGa2 zeigten im Gegensatz zu den strukturell verwandten Verbindungen SrGa2 und SrAl2 keinerlei Bestreben für eine Hydridbildung. Die Strukturmodelle von YbGa6 (PuGa6-Typ), sowie die der Hydride und Deuteride von SrSi, BaSi und EuSi (ähnlich dem CaSiDx-Typ) konnten verbessert und zum Teil um Wasserstoffpositionen ergänzt werden.In this work the hydride formation of Zintl-phases of alkaline earth metals (calcium, strontium, barium) as well as europium and ytterbium with the more electronegative partners aluminium, gallium and silicon are investigated. It is focused on the structural characterization by the use of x-ray powder diffraction and (in situ) neutron powder diffraction (NPD), enabling the identification of reaction pathways. In situ-NPD was used for the well-known compounds CaSi and SrGa2. For the gallide no extra steps in the hydride formation were found. In contrast, the silicide seems to form an intermediate phase in a reversible process. This intermediate is only stable under hydrogen pressure. A preliminary structure model (Pnma, a = 10,998(2) Å, b = 3,8897(6) Å, c = 13,527(3) Å) has been found that shows similarity to the already known CaSiDx phase (x ≈ 1,0 - 1,3) but has only about one third of the hydrogen content. The compound then takes up hydrogen nearly continuously to form the already known phase. Ex situ investigations on EuGa2 and YbGa2 show (contrary to the structural related compounds SrGa2 and SrAl2) no hydride formation. The structure models for YbGa6 (PuGa6 structure type) and both the hydrides and deuterides of SrSi, BaSi and EuSi (similar to the CaSiDx structure type) were improved and updated concerning the hydrogen positions

Finger somatotopy is preserved after tetraplegia but deteriorates over time

Previous studies showed reorganised and/or altered activity in the primary sensorimotor cortex after a spinal cord injury (SCI), suggested to reflect abnormal processing. However, little is known about whether somatotopically specific representations can be activated despite reduced or absent afferent hand inputs. In this observational study, we used functional MRI and a (attempted) finger movement task in tetraplegic patients to characterise the somatotopic hand layout in primary somatosensory cortex. We further used structural MRI to assess spared spinal tissue bridges. We found that somatotopic hand representations can be activated through attempted finger movements in the absence of sensory and motor hand functioning, and no spared spinal tissue bridges. Such preserved hand somatotopy could be exploited by rehabilitation approaches that aim to establish new hand-brain functional connections after SCI (e.g. neuroprosthetics). However, over years since SCI the hand representation somatotopy deteriorated, suggesting that somatotopic hand representations are more easily targeted within the first years after SCI

Reconsolidation of motor memories is a time-dependent process

Reconsolidation is observed when a consolidated stable memory is recalled, which renders it transiently labile and requires re-stabilization. Motor memory reconsolidation has previously been demonstrated using a three-day design: on day 1 the memory is encoded, on day 2 it is reactivated and experimentally manipulated, and on day 3 memory strength is tested. The aim of the current study is to determine specific boundary conditions in order to consistently degrade motor memory through reconsolidation paradigms. We investigated a sequence tapping task (n = 48) with the typical three-day design and confirmed that reactivating the motor sequence briefly (10 times tapping the learned motor sequence) destabilizes the memory trace and makes it susceptible to behavioral interference. By systematically varying the time delay between memory reactivation and interference while keeping all other aspect constant we found that a short delay (i.e., 20 s) significantly decreased performance on day 3, whereas performance was maintained or small (but not significant) improvements were observed for longer delays (i.e., 60 s). We also tested a statistical model that assumed a linear effect of the different time delays (0 s, 20 s, 40 s, 60 s) on the performance changes from day 2 to day 3. This linear model revealed a significant effect consistent with the interpretation that increasing time delays caused a gradual change from performance degradation to performance conservation across groups. These findings indicate that re-stabilizing motor sequence memories during reconsolidation does not solely rely on additional motor practice but occurs with the passage of time. This study provides further support for the hypothesis that reconsolidation is a time-dependent process with a transition phase from destabilization to re-stabilization

Effects of Transcranial Direct Current Stimulation on the Recognition of Bodily Emotions from Point-Light Displays

Perceiving human motion, recognizing actions and interpreting emotional body language are tasks we perform daily and which are supported by a network of brain areas including the human posterior superior temporal sulcus (pSTS). Here, we applied transcranial direct current stimulation with anodal (excitatory) or cathodal (inhibitory) electrodes mounted over right pSTS (target) and orbito-frontal cortex (reference) while healthy participants performed a bodily emotion recognition task using biological motion point light displays (PLDs). Performance (accuracy and reaction times) was also assessed on a control task which was matched to the emotion recognition task in terms of cognitive and motor demands. Each subject participated in two experimental sessions, receiving either anodal or cathodal stimulation, which were separated by one week to avoid residual effects of previous stimulations.Overall, tDCS brain stimulation did not affect the recognition of emotional states from PLDs. However, when emotions with a negative or positive-neutral emotional valence were analyzed separately, effects of stimulation were shown for recognizing emotions with a negative emotional valence (sadness & anger), indicating increased recognition performance when receiving anodal (excitatory) stimulation compared to cathodal (inhibitory) stimulation over pSTS. No stimulation effects were shown for the recognition of emotions with positive-neutral emotional valences. These findings extend previous studies showing structure-function relationships between STS and biological motion processing from PLDs and provide indications that stimulation effects may be modulated by the emotional valence of the stimuli

Finger somatotopy is preserved after tetraplegia but deteriorates over time

Previous studies showed reorganised and/or altered activity in the primary sensorimotor cortex after a spinal cord injury (SCI), suggested to reflect abnormal processing. However, little is known about whether somatotopically specific representations can be activated despite reduced or absent afferent hand inputs. In this observational study, we used functional MRI and a (attempted) finger movement task in tetraplegic patients to characterise the somatotopic hand layout in primary somatosensory cortex. We further used structural MRI to assess spared spinal tissue bridges. We found that somatotopic hand representations can be activated through attempted finger movements in the absence of sensory and motor hand functioning, and no spared spinal tissue bridges. Such preserved hand somatotopy could be exploited by rehabilitation approaches that aim to establish new hand-brain functional connections after SCI (e.g. neuroprosthetics). However, over years since SCI the hand representation somatotopy deteriorated, suggesting that somatotopic hand representations are more easily targeted within the first years after SCI.ISSN:2050-084

Hand and face somatotopy shown using MRI-safe vibrotactile stimulation with a novel soft pneumatic actuator (SPA)-skin interface

The exact somatotopy of the human facial representation in the primary somatosensory cortex (S1) remains debated. One reason that progress has been hampered is due to the methodological challenge of how to apply automated vibrotactile stimuli to face areas in a manner that is: (1) reliable despite differences in the curvatures of face locations; and (2) MR-compatible and free of MR-interference artefacts when applied in the MR head-coil. Here we overcome this challenge by using soft pneumatic actuator (SPA) technology. SPAs are made of a soft silicon material and can be in- or deflated by means of airflow, have a small diameter, and are flexible in structure, enabling good skin contact even on curved body surfaces (as on the face). To validate our approach, we first mapped the well-characterised S1 finger layout using this novel device and confirmed that tactile stimulation of the fingers elicited characteristic somatotopic finger activations in S1. We then used the device to automatically and systematically deliver somatosensory stimulation to different face locations. We found that the forehead representation was least distant from the representation of the hand. Within the face representation, we found that the lip representation is most distant from the forehead representation, with the chin represented in between. Together, our results demonstrate that this novel MR compatible device produces robust and clear somatotopic representational patterns using vibrotactile stimulation through SPA-technology

Hand and face somatotopy shown using MRI-safe vibrotactile stimulation with a novel soft pneumatic actuator (SPA)-skin interface

The exact somatotopy of the human facial representation in the primary somatosensory cortex (S1) remains debated. One reason that progress has been hampered is due to the methodological challenge of how to apply automated vibrotactile stimuli to face areas in a manner that is: (1) reliable despite differences in the curvatures of face locations; and (2) MR-compatible and free of MR-interference artefacts when applied in the MR head-coil. Here we overcome this challenge by using soft pneumatic actuator (SPA) technology. SPAs are made of a soft silicon material and can be in- or deflated by means of airflow, have a small diameter, and are flexible in structure, enabling good skin contact even on curved body surfaces (as on the face). To validate our approach, we first mapped the well-characterised S1 finger layout using this novel device and confirmed that tactile stimulation of the fingers elicited characteristic somatotopic finger activations in S1. We then used the device to automatically and systematically deliver somatosensory stimulation to different face locations. We found that the forehead representation was least distant from the representation of the hand. Within the face representation, we found that the lip representation is most distant from the forehead representation, with the chin represented in between. Together, our results demonstrate that this novel MR compatible device produces robust and clear somatotopic representational patterns using vibrotactile stimulation through SPA-technology.ISSN:1053-8119ISSN:1095-957

Frequency‐dependent functional connectivity in resting state networks

Functional magnetic resonance imaging studies have documented the resting human brain to be functionally organized in multiple large‐scale networks, called resting‐state networks (RSNs). Other brain imaging techniques, such as electroencephalography (EEG) and magnetoencephalography (MEG), have been used for investigating the electrophysiological basis of RSNs. To date, it is largely unclear how neural oscillations measured with EEG and MEG are related to functional connectivity in the resting state. In addition, it remains to be elucidated whether and how the observed neural oscillations are related to the spatial distribution of the network nodes over the cortex. To address these questions, we examined frequency‐dependent functional connectivity between the main nodes of several RSNs, spanning large part of the cortex. We estimated connectivity using band‐limited power correlations from high‐density EEG data collected in healthy participants. We observed that functional interactions within RSNs are characterized by a specific combination of neuronal oscillations in the alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–80 Hz) bands, which highly depend on the position of the network nodes. This finding may contribute to a better understanding of the mechanisms through which neural oscillations support functional connectivity in the brain

Frequency-dependent functional connectivity in resting state networks

Functional magnetic resonance imaging studies have documented the resting human brain to be functionally organized in multiple large-scale networks, called resting-state networks (RSNs). Other brain imaging techniques, such as electroencephalography (EEG) and magnetoencephalography (MEG), have been used for investigating the electrophysiological basis of RSNs. To date, it is largely unclear how neural oscillations measured with EEG and MEG are related to functional connectivity in the resting state. In addition, it remains to be elucidated whether and how the observed neural oscillations are related to the spatial distribution of the network nodes over the cortex. To address these questions, we examined frequency-dependent functional connectivity between the main nodes of several RSNs, spanning large part of the cortex. We estimated connectivity using band-limited power correlations from high-density EEG data collected in healthy participants. We observed that functional interactions within RSNs are characterized by a specific combination of neuronal oscillations in the alpha (8-13 Hz), beta (13-30 Hz), and gamma (30-80 Hz) bands, which highly depend on the position of the network nodes. This finding may contribute to a better understanding of the mechanisms through which neural oscillations support functional connectivity in the brain.status: publishe

Frequency‐dependent functional connectivity in resting state networks

Functional magnetic resonance imaging studies have documented the resting human brain to be functionally organized in multiple large‐scale networks, called resting‐state networks (RSNs). Other brain imaging techniques, such as electroencephalography (EEG) and magnetoencephalography (MEG), have been used for investigating the electrophysiological basis of RSNs. To date, it is largely unclear how neural oscillations measured with EEG and MEG are related to functional connectivity in the resting state. In addition, it remains to be elucidated whether and how the observed neural oscillations are related to the spatial distribution of the network nodes over the cortex. To address these questions, we examined frequency‐dependent functional connectivity between the main nodes of several RSNs, spanning large part of the cortex. We estimated connectivity using band‐limited power correlations from high‐density EEG data collected in healthy participants. We observed that functional interactions within RSNs are characterized by a specific combination of neuronal oscillations in the alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–80 Hz) bands, which highly depend on the position of the network nodes. This finding may contribute to a better understanding of the mechanisms through which neural oscillations support functional connectivity in the brain