具有超压防护功能的机动手术舱室污染物运动扩散的仿真研究

目的:对具有超压防护功能的机动手术舱室污染物运动扩散进行仿真研究,通过空气过滤净化和气流组织设计等方式减少生化污染物的危害,为患者和医生提供安全的舱室环境.方法:应用计算流体动力学方法对具有超压防护功能的机动手术舱室污染物运动扩散进行了仿真研究,分析了在超压防护系统工作前后两种状态下,污染物在室内的运动扩散及其对舱室内人员的影响.结果:在外部气态污染物浓度为5 mg/L的条件下,超压防护系统工作前,在10 s时呼吸区污染物达到最大浓度0.21 mg/L;超压防护系统工作后,在125 s时呼吸区污染物最大浓度达到0.01 mg/L的安全阈值.在整个计算过程中,污染物最大浓时积为0.1 mg·min/L,最小浓时积为0.011 mg·min/L.结论:机动手术舱室超压防护系统可以有效地将其工作前扩散到室内的气态污染物进行稀释,使室内人员周围不产生局部高浓度区,减小污染物对室内人员的影响.     

Molecular-Dynamics Simulations of the Emergence of Surface Roughness in a Polymer under Compression

Roughness of surfaces is both surprisingly ubiquitous on all length scales and extremely relevant practically. The appearance of multi-scale roughness has been linked to avalanches and plastic deformation in metals. However, other, more-complex materials have mechanisms of plasticity that are significantly different from those of metals. We investigated the emergence of roughness in a polymer under compression. We performed molecular-dynamics simulations of a slab of solid polyvinyl alcohol that was compressed bi-axially, and we characterised the evolution of the surface roughness. We found significantly different behaviour than what was previously observed in similar simulations of metals. We investigated the differences and argue that the visco-elasticity of the material plays a crucial role.     

Encoding and retrieval of episodic memories: Role of cholinergic and GABAergic modulation in the hippocampus

This research focuses on linking episodic memory function to the cellular physiology of hippocampal neurons, with a particular emphasis on modulatory effects at cholinergic and γ-aminobutyric acid B receptors. Drugs which block acetylcholine receptors (e.g., scopolamine) have been shown to impair encoding of new information in humans, nonhuman primates, and rodents. Extensive data have been gathered about the cellular effects of acetylcholine in the hippocampus. In this research, models of individual hippocampal subregions have been utilized to understand the significance of particular features of modulation, and these hippocampal subregions have been combined in a network simulation which can replicate the selective encoding impairment produced by scopolamine in human subjects. © 1997 Wiley-Liss, Inc.     

Noninvasive extraction of microsecond‐scale dynamics from human motor cortex

State‐of‐the‐art noninvasive electromagnetic recording techniques allow observing neuronal dynamics down to the millisecond scale. Direct measurement of faster events has been limited to in vitro or invasive recordings. To overcome this limitation, we introduce a new paradigm for transcranial magnetic stimulation. We adjusted the stimulation waveform on the microsecond scale, by varying the duration between the positive and negative phase of the induced electric field, and studied corresponding changes in the elicited motor responses. The magnitude of the electric field needed for given motor‐evoked potential amplitude decreased exponentially as a function of this duration with a time constant of 17 µs. Our indirect noninvasive measurement paradigm allows studying neuronal kinetics on the microsecond scale in vivo.     

Task‐related effective connectivity reveals that the cortical rich club gates cortex‐wide communication

Higher cognition may require the globally coordinated integration of specialized brain regions into functional networks. A collection of structural cortical hubs—referred to as the rich club—has been hypothesized to support task‐specific functional integration. In the present paper, we use a whole‐cortex model to estimate directed interactions between 68 cortical regions from functional magnetic resonance imaging activity for four different tasks (reflecting different cognitive domains) and resting state. We analyze the state‐dependent input and output effective connectivity (EC) of the structural rich club and relate these to whole‐cortex dynamics and network reconfigurations. We find that the cortical rich club exhibits an increase in outgoing EC during task performance as compared with rest while incoming connectivity remains constant. Increased outgoing connectivity targets a sparse set of peripheral regions with specific regions strongly overlapping between tasks. At the same time, community detection analyses reveal massive reorganizations of interactions among peripheral regions, including those serving as target of increased rich club output. This suggests that while peripheral regions may play a role in several tasks, their concrete interplay might nonetheless be task‐specific. Furthermore, we observe that whole‐cortex dynamics are faster during task as compared with rest. The decoupling effects usually accompanying faster dynamics appear to be counteracted by the increased rich club outgoing EC. Together our findings speak to a gating mechanism of the rich club that supports fast‐paced information exchange among relevant peripheral regions in a task‐specific and goal‐directed fashion, while constantly listening to the whole network.     

Spatio‐temporal dynamics of resting‐state brain networks improve single‐subject prediction of schizophrenia diagnosis

Correlation in functional MRI activity between spatially separated brain regions can fluctuate dynamically when an individual is at rest. These dynamics are typically characterized temporally by measuring fluctuations in functional connectivity between brain regions that remain fixed in space over time. Here, dynamics in functional connectivity were characterized in both time and space. Temporal dynamics were mapped with sliding‐window correlation, while spatial dynamics were characterized by enabling network regions to vary in size (shrink/grow) over time according to the functional connectivity profile of their constituent voxels. These temporal and spatial dynamics were evaluated as biomarkers to distinguish schizophrenia patients from controls, and compared to current biomarkers based on static measures of resting‐state functional connectivity. Support vector machine classifiers were trained using: (a) static, (b) dynamic in time, (c) dynamic in space, and (d) dynamic in time and space characterizations of functional connectivity within canonical resting‐state brain networks. Classifiers trained on functional connectivity dynamics mapped over both space and time predicted diagnostic status with accuracy exceeding 91%, whereas utilizing only spatial or temporal dynamics alone yielded lower classification accuracies. Static measures of functional connectivity yielded the lowest accuracy (79.5%). Compared to healthy comparison individuals, schizophrenia patients generally exhibited functional connectivity that was reduced in strength and more variable. Robustness was established with replication in an independent dataset. The utility of biomarkers based on temporal and spatial functional connectivity dynamics suggests that resting‐state dynamics are not trivially attributable to sampling variability and head motion.     

Detecting sub-second changes in brain activation patterns during interictal epileptic spike using simultaneous EEG-fMRI

Objective

Epileptic spikes are associated with rapidly changing brain activation involving the epileptic foci and other brain regions in the “epileptic network”. We aim to resolve these activation changes using simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings.