Search

The language comprehension system preferentially assumes that agents come first during incremental processing. While this might reflect a biologically fixed bias, shared with other domains and other species, the evidence is limited to languages that place agents first, and so the bias could also be learned from usage frequency. Here, we probe the bias with electroencephalography (EEG) in Äiwoo, a language that by default places patients first, but where sentence‐initial nouns are still locally ambiguous between patient or agent roles. Comprehenders transiently interpreted nonhuman nouns as patients, eliciting a negativity when disambiguation was toward the less common agent‐initial order. By contrast and against frequencies, human nouns were transiently interpreted as agents, eliciting an N400‐like negativity when the disambiguation was toward patient‐initial order. Consistent with the notion of a fixed property, the agent bias is robust against usage frequency for human referents. However, this bias can be reversed by frequency experience for nonhuman referents. [ABSTRACT FROM AUTHOR]

Purpose: In image‐guided radiation therapy, fiducial markers or clips are often used to determine the position of the tumor. These markers lead to streak artifacts in cone‐beam CT (CBCT) scans. Standard inpainting‐based metal artifact reduction (MAR) methods fail to remove these artifacts in cases of large motion. We propose two methods to effectively reduce artifacts caused by moving metal inserts. Methods: The first method (MMAR) utilizes a coarse metal segmentation in the image domain and a refined segmentation in the rawdata domain. After an initial reconstruction, metal is segmented and forward projected giving a coarse metal mask in the rawdata domain. Inside the coarse mask, metal is segmented by utilizing a 2D Sobel filter. Metal is removed by linear interpolation in the refined metal mask. The second method (MoCoMAR) utilizes a motion compensation (MoCo) algorithm [Med Phys. 2013;40:101913] that provides us with a motion‐free volume (3D) or with a time series of motion‐free volumes (4D). We then apply the normalized metal artifact reduction (NMAR) [Med Phys. 2010;37:5482–5493] to these MoCo volumes. Both methods were applied to three CBCT data sets of patients with metal inserts in the thorax or abdomen region and a 4D thorax simulation. The results were compared to volumes corrected by a standard MAR1 [Radiology. 1987;164:576–577]. Results: MMAR and MoCoMAR were able to remove all artifacts caused by moving metal inserts for the patients and the simulation. Both new methods outperformed the standard MAR1, which was only able to remove artifacts caused by metal inserts with little or no motion. Conclusions: In this work, two new methods to remove artifacts caused by moving metal inserts are introduced. Both methods showed good results for a simulation and three patients. While the first method (MMAR) works without any prior knowledge, the second method (MoCoMAR) requires a respiratory signal for the MoCo step and is computationally more demanding and gives no benefit over MMAR, unless MoCo images are desired. [ABSTRACT FROM AUTHOR]

Purpose: Cardiac in vivo micro-CT imaging of small animals typically requires double gating due to long scan times and high respiratory rates. The simultaneous respiratory and cardiac gating can either be done prospectively or retrospectively. In any case, for true 5D imaging, i.e., three spatial dimensions plus one respiratory-temporal dimension plus one cardiac temporal dimension, the amount of information corresponding to a given respiratory and cardiac phase is orders of magnitude lower than the total amount of information acquired. Achieving similar image quality for 5D than for usual 3D investigations would require increasing the amount of data and thus the applied dose to the animal. Therefore, the goal is phase-correlated imaging with high image quality but without increasing the dose level. Methods: To achieve this, the authors propose a new image reconstruction algorithm that makes use of all available projection data, also of that corresponding to other motion windows. In particular, the authors apply a motion-compensated image reconstruction approach that sequentially compensates for respiratory and cardiac motion to decrease the impact of sparsification. In that process, all projection data are used no matter which motion phase they were acquired in. Respiratory and cardiac motion are compensated for by using motion vector fields. These motion vector fields are estimated from initial phase-correlated reconstructions based on a deformable registration approach. To decrease the sensitivity of the registration to sparse-view artifacts, an artifact model-based approach is used including a cyclic consistent nonrigid registration algorithm. Results: The preliminary results indicate that the authors' approach removes the sparse-view artifacts of conventional phase-correlated reconstructions while maintaining temporal resolution. In addition, it achieves noise levels and spatial resolution comparable to that of nongated reconstructions due to the improved dose usage. By using the proposed motion estimation, no sensitivity to streaking artifacts has been observed. Conclusions: Using sequential double gating combined with artifact model-based motion estimation allows to accurately estimate respiratory and cardiac motion from highly undersampled data. No sensitivity to streaking artifacts introduced by sparse angular sampling has been observed for the investigated dose levels. The motion-compensated image reconstruction was able to correct for both, respiratory and cardiac motion, by applying the estimated motion vector fields. The administered dose per animal can thus be reduced for 5D imaging allowing for longitudinal studies at the highest image quality. [ABSTRACT FROM AUTHOR]

Speech planning is a sophisticated process. In dialog, it regularly starts in overlap with an incoming turn by a conversation partner. We show that planning spoken responses in overlap with incoming turns is associated with higher processing load than planning in silence. In a dialogic experiment, participants took turns with a confederate describing lists of objects. The confederate's utterances (to which participants responded) were pre‐recorded and varied in whether they ended in a verb or an object noun and whether this ending was predictable or not. We found that response planning in overlap with sentence‐final verbs evokes larger task‐evoked pupillary responses, while end predictability had no effect. This finding indicates that planning in overlap leads to higher processing load for next speakers in dialog and that next speakers do not proactively modulate the time course of their response planning based on their predictions of turn endings. The turn‐taking system exerts pressure on the language processing system by pushing speakers to plan in overlap despite the ensuing increase in processing load. [ABSTRACT FROM AUTHOR]