The COMET (COherent Muon to Electron Transition) experiment, currently being built in Tokai, Japan, will search for the coherent neutrinoless transition of muons to electrons in the coulomb field of ...atomic nuclei. The process is highly suppressed in the Standard Model and therefore provides a promising channel to probe new physics. The experiment will be carried out in a staged approach. Phase-I of COMET aims to search for the process with a single event sensitivity of (10
−15
). Additionally, precise measurements of muon beam dynamics and detector prototyping for Phase-II will be conducted. Utilizing a much higher intensity proton beam, a more complex and longer muon/electron transport system, and gained experience from Phase-I, an improvement of at least four orders of magnitude over the current best branching ratio limit up to (10
−17
) is envisioned for Phase-II. This article will give a status report for Phase-I of COMET.
The suitability of different gelling agents as MRI phantoms was evaluated in terms of homogeneity, gel stability and reproducibility. Time and effort for preparation were also taken into account. The ...relaxation times of various gel compositions were estimated. Carbomer-980 and Carbopol-974P were determined to be promising novel phantom materials. These gelling agents are readily available, inexpensive and easy to handle given that thermal treatment is not required. Furthermore, the viscoelasticity of their polymer network is pH-dependent. With such characteristics, it was even possible to embed sensitive objects and retrieve them after testing. This was demonstrated with a fiber phantom for Diffusion Weighted MRI applications. Since Carbomer-980 and Carbopol-974P are non-hazardous, they are also suitable for multimodal setups (e.g., MRI as well as ultrasonic imaging).
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Humans integrate information communicated by speech and gestures. Functional magnetic resonance imaging (fMRI) studies suggest that the posterior superior temporal sulcus (STS) and adjacent gyri are ...relevant for multisensory integration. However, a connectivity model representing this essential combinatory process is still missing. Here, we used dynamic causal modeling for fMRI to analyze the effective connectivity pattern between middle temporal gyrus (MTG), occipital cortex (OC) and STS associated with auditory verbal, visual gesture-related, and integrative processing, respectively, to unveil the neural mechanisms underlying integration of intrinsically meaningful gestures (e.g., “Thumbs-up gesture”) and corresponding speech.
20 participants were presented videos of an actor either performing intrinsic meaningful gestures in the context of German or Russian sentences, or speaking a German sentence without gesture, while performing a content judgment task.
The connectivity analyses resulted in a winning model that included bidirectional intrinsic connectivity between all areas. Furthermore, the model included modulations of both connections to the STS (OC→STS; MTG→STS), and non-linear modulatory effects of the STS on bidirectional connections between MTG and OC. Coupling strength in the occipital pathway (OC→STS) correlated with gesture related advantages in task performance, whereas the temporal pathway (MTG→STS) correlated with performance in the speech only condition. Coupling between MTG and OC correlated negatively with subsequent memory performance for sentences of the Gesture-German condition.
Our model provides a first step towards a better understanding of speech-gesture integration on network level. It corroborates the importance of the STS during audio-visual integration by showing that this region inhibits direct auditory-visual coupling.
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•Humans integrate information communicated by speech and gestures.•The superior temporal sulcus (STS) is relevant for multisensory integration.•We used dynamic causal modeling to unveil the neural mechanisms of integration.•The STS received auditory/visual input and reduced direct auditory-visual coupling.•Better understanding of speech-gesture integration on network level.
Large, longitudinal, multi-center MR neuroimaging studies require comprehensive quality assurance (QA) protocols for assessing the general quality of the compiled data, indicating potential ...malfunctions in the scanning equipment, and evaluating inter-site differences that need to be accounted for in subsequent analyses.
We describe the implementation of a QA protocol for functional magnet resonance imaging (fMRI) data based on the regular measurement of an MRI phantom and an extensive variety of currently published QA statistics. The protocol is implemented in the MACS (Marburg-Münster Affective Disorders Cohort Study, http://for2107.de/), a two-center research consortium studying the neurobiological foundations of affective disorders. Between February 2015 and October 2016, 1214 phantom measurements have been acquired using a standard fMRI protocol. Using 444 healthy control subjects which have been measured between 2014 and 2016 in the cohort, we investigate the extent of between-site differences in contrast to the dependence on subject-specific covariates (age and sex) for structural MRI, fMRI, and diffusion tensor imaging (DTI) data.
We show that most of the presented QA statistics differ severely not only between the two scanners used for the cohort but also between experimental settings (e.g. hardware and software changes), demonstrate that some of these statistics depend on external variables (e.g. time of day, temperature), highlight their strong dependence on proper handling of the MRI phantom, and show how the use of a phantom holder may balance this dependence. Site effects, however, do not only exist for the phantom data, but also for human MRI data. Using T1-weighted structural images, we show that total intracranial (TIV), grey matter (GMV), and white matter (WMV) volumes significantly differ between the MR scanners, showing large effect sizes. Voxel-based morphometry (VBM) analyses show that these structural differences observed between scanners are most pronounced in the bilateral basal ganglia, thalamus, and posterior regions. Using DTI data, we also show that fractional anisotropy (FA) differs between sites in almost all regions assessed. When pooling data from multiple centers, our data show that it is a necessity to account not only for inter-site differences but also for hardware and software changes of the scanning equipment. Also, the strong dependence of the QA statistics on the reliable placement of the MRI phantom shows that the use of a phantom holder is recommended to reduce the variance of the QA statistics and thus to increase the probability of detecting potential scanner malfunctions.
•Quality assurance (QA) protocol for large, longitudinal, multi-center MR neuroimaging studies.•Dependence of QA statistics on MR-scanner type, hardware and software changes and external variables (e.g., time of day, temperature).•Consequences of phantom data variations for human MRI data.•Dependence of MR phantom placement on QA statistics.
The classical core system of face perception consists of the occipital face area (OFA), fusiform face area (FFA), and posterior superior temporal sulcus (STS). The functional interaction within this ...network, more specifically the effective connectivity, was first described by Fairhall and Ishai (2007) using functional magnetic resonance imaging and dynamic causal modeling. They proposed that the core system is hierarchically organized; information is processed in a parallel and predominantly feed-forward fashion from the OFA to downstream regions such as the FFA and STS, with no lateral connectivity, i.e., no connectivity between the two downstream regions (FFA and STS). Over a decade later, we conducted a conceptual replication of their model using four different functional magnetic resonance imaging data sets. The effective connectivity within the core system was assessed with contemporary versions of dynamic causal modeling.
The resulting model of the core system of face perception was densely interconnected. Using hierarchical linear modeling, we identified several significant forward, backward, and lateral connections in the core system of face perception across the data sets. Face perception increased the forward connectivity from the OFA to the FFA and OFA to the STS and increased the inhibitory backward connectivity from the FFA to the OFA, as well as the lateral connectivity between the FFA and STS. Emotion perception increased forward connectivity between the OFA and STS and decreased the lateral connectivity between the FFA and STS. Face familiarity did not significantly alter these connections.
Our results revise the 2007 model of the core system of face perception. We discuss the potential meaning of the resulting model parameters and propose that our revised model is a suitable working model for further studies assessing the functional interaction within the core system of face perception. Our work further emphasizes the general importance of conceptual replications.
•We revised an early connectivity model of face perception using multiple data sets.•Connectivity estimates were highly similar across different data sets.•The core system of face perception is highly interconnected.
Studies on social cognition often use complex visual stimuli to asses neural processes attributed to abilities like “mentalizing” or “Theory of Mind” (ToM). During the processing of these stimuli, ...eye gaze, however, shapes neural signal patterns. Individual differences in neural operations on social cognition may therefore be obscured if individuals’ gaze behavior differs systematically. These obstacles can be overcome by the combined analysis of neural signal and natural viewing behavior. Here, we combined functional magnetic resonance imaging (fMRI) with eye-tracking to examine effects of unconstrained gaze on neural ToM processes in healthy individuals with differing levels of emotional awareness, i.e. alexithymia. First, as previously described for emotional tasks, people with higher alexithymia levels look less at eyes in both ToM and task-free viewing contexts. Further, we find that neural ToM processes are not affected by individual differences in alexithymia per se. Instead, depending on alexithymia levels, gaze on critical stimulus aspects reversely shapes the signal in medial prefrontal cortex (MPFC) and anterior temporoparietal junction (TPJ) as distinct nodes of the ToM system. These results emphasize that natural selective attention affects fMRI patterns well beyond the visual system. Our study implies that, whenever using a task with multiple degrees of freedom in scan paths, ignoring the latter might obscure important conclusions.
Alterations in regional subcortical brain volumes have been investigated as part of the efforts of an international consortium, ENIGMA, to identify reliable neural correlates of major depressive ...disorder (MDD). Given that subcortical structures are comprised of distinct subfields, we sought to build significantly from prior work by precisely mapping localized MDD‐related differences in subcortical regions using shape analysis. In this meta‐analysis of subcortical shape from the ENIGMA‐MDD working group, we compared 1,781 patients with MDD and 2,953 healthy controls (CTL) on individual measures of shape metrics (thickness and surface area) on the surface of seven bilateral subcortical structures: nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Harmonized data processing and statistical analyses were conducted locally at each site, and findings were aggregated by meta‐analysis. Relative to CTL, patients with adolescent‐onset MDD (≤ 21 years) had lower thickness and surface area of the subiculum, cornu ammonis (CA) 1 of the hippocampus and basolateral amygdala (Cohen's d = −0.164 to −0.180). Relative to first‐episode MDD, recurrent MDD patients had lower thickness and surface area in the CA1 of the hippocampus and the basolateral amygdala (Cohen's d = −0.173 to −0.184). Our results suggest that previously reported MDD‐associated volumetric differences may be localized to specific subfields of these structures that have been shown to be sensitive to the effects of stress, with important implications for mapping treatments to patients based on specific neural targets and key clinical features.
Perceiving human faces constitutes a fundamental ability of the human mind, integrating a wealth of information essential for social interactions in everyday life. Neuroimaging studies have unveiled ...a distributed neural network consisting of multiple brain regions in both hemispheres. Whereas the individual regions in the face perception network and the right-hemispheric dominance for face processing have been subject to intensive research, the functional integration among these regions and hemispheres has received considerably less attention. Using dynamic causal modeling (DCM) for fMRI, we analyzed the effective connectivity between the core regions in the face perception network of healthy humans to unveil the mechanisms underlying both intra- and interhemispheric integration. Our results suggest that the right-hemispheric lateralization of the network is due to an asymmetric face-specific interhemispheric recruitment at an early processing stage — that is, at the level of the occipital face area (OFA) but not the fusiform face area (FFA). As a structural correlate, we found that OFA gray matter volume was correlated with this asymmetric interhemispheric recruitment. Furthermore, exploratory analyses revealed that interhemispheric connection asymmetries were correlated with the strength of pupil constriction in response to faces, a measure with potential sensitivity to holistic (as opposed to feature-based) processing of faces. Overall, our findings thus provide a mechanistic description for lateralized processes in the core face perception network, point to a decisive role of interhemispheric integration at an early stage of face processing among bilateral OFA, and tentatively indicate a relation to individual variability in processing strategies for faces. These findings provide a promising avenue for systematic investigations of the potential role of interhemispheric integration in future studies.
•Effective connectivity analysis of the face perception network using DCM for fMRI•Hemispheric lateralization due to asymmetric interhemispheric recruitment among OFA•OFA gray matter volume correlated with interhemispheric recruitment•Transient pupil constrictions to faces correlated with interhemispheric recruitment•Mechanistic description of lateralized processes in the face perception network
The neural face perception network is distributed across both hemispheres. However, the dominant role in humans is virtually unanimously attributed to the right hemisphere. Interestingly, there are, ...to our knowledge, no imaging studies that systematically describe the distribution of hemispheric lateralization in the core system of face perception across subjects in large cohorts so far. To address this, we determined the hemispheric lateralization of all core system regions (i.e., occipital face area - OFA, fusiform face area - FFA, posterior superior temporal sulcus - pSTS) in 108 healthy subjects using functional magnetic resonance imaging (fMRI). We were particularly interested in the variability of hemispheric lateralization across subjects and explored how many subjects can be classified as right-dominant based on the fMRI activation pattern. We further assessed lateralization differences between different regions of the core system and analyzed the influence of handedness and sex on the lateralization with a generalized mixed effects regression model. As expected, brain activity was on average stronger in right-hemispheric brain regions than in their left-hemispheric homologues. This asymmetry was, however, only weakly pronounced in comparison to other lateralized brain functions (such as language and spatial attention) and strongly varied between individuals. Only half of the subjects in the present study could be classified as right-hemispheric dominant. Additionally, we did not detect significant lateralization differences between core system regions. Our data did also not support a general leftward shift of hemispheric lateralization in left-handers. Only the interaction of handedness and sex in the FFA revealed that specifically left-handed men were significantly more left-lateralized compared to right-handed males. In essence, our fMRI data did not support a clear right-hemispheric dominance of the face perception network. Our findings thus ultimately question the dogma that the face perception network – as measured with fMRI – can be characterized as “typically right lateralized”.
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