Model-driven CT reconstruction algorithm for nano-resolution x-ray phase contrast imaging

The low-density imaging performance of a zone plate-based nano-resolution hard x-ray computed tomography(CT)system can be significantly improved by incorporating a grating-based Lau interferometer. Due to the diffraction, however,the acquired nano-resolution phase signal may suffer splitting problem, which impedes the direct reconstruction of phase contrast CT(nPCT) images. To overcome, a new model-driven nPCT image reconstruction algorithm is developed in this study. In it, the diffraction procedure is mathematically modeled into a matrix B, from which the projections without signal splitting can be generated invertedly. Furthermore, a penalized weighted least-square model with total variation(PWLSTV) is employed to denoise these projections, from which nPCT images with high accuracy are directly reconstructed.Numerical experiments demonstrate that this new algorithm is able to work with phase projections having any splitting distances. Moreover, results also reveal that nPCT images of higher signal-to-noise-ratio(SNR) could be reconstructed from projections having larger splitting distances. In summary, a novel model-driven nPCT image reconstruction algorithm with high accuracy and robustness is verified for the Lau interferometer-based hard x-ray nano-resolution phase contrast imaging.

Theory and verification of moiréfringes for x-ray three-phase grating interferometer

Dual-phase and three-phase grating x-ray interference is a promising new technique for grating-based x-ray differential phase contrast imaging.Dual-phase grating interferometers have been relatively completely studied and discussed.In this paper,the corresponding imaging fringe formula of the three-phase grating interferometer is provided.At the same time,the similarities and differences between the three-phase grating interferometer and the dual-phase grating interferometer are investigated and verified,and that the three-phase grating interferometer can produce large-period moiréfringes without using the analyzing grating is demonstrated experimentally.Finally,a simple method of designing three-phase grating and multi-grating imaging systems from geometric optics based on the thin-lens theory of gratings is presented.These theoretical formulas and experimental results provide optimization tools for designing three-phase grating interferometer systems.

Probing the processing of facial expressions in monkeys via time perception and eye tracking

Accurately recognizing facial expressions is essential for effective social interactions.Non-human primates(NHPs)are widely used in the study of the neural mechanisms underpinning facial expression processing,yet it remains unclear how well monkeys can recognize the facial expressions of other species such as humans.In this study,we systematically investigated how monkeys process the facial expressions of conspecifics and humans using eye-tracking technology and sophisticated behavioral tasks,namely the temporal discrimination task(TDT)and face scan task(FST).We found that monkeys showed prolonged subjective time perception in response to Negative facial expressions in monkeys while showing longer reaction time to Negative facial expressions in humans.Monkey faces also reliably induced divergent pupil contraction in response to different expressions,while human faces and scrambled monkey faces did not.Furthermore,viewing patterns in the FST indicated that monkeys only showed bias toward emotional expressions upon observing monkey faces.Finally,masking the eye region marginally decreased the viewing duration for monkey faces but not for human faces.By probing facial expression processing in monkeys,our study demonstrates that monkeys are more sensitive to the facial expressions of conspecifics than those of humans,thus shedding new light on inter-species communication through facial expressions between NHPs and humans.

X-ray phase-sensitive microscope imaging with a grating interferometer:Theory and simulation

A general theoretical framework is presented to explain the formation of the phase signal in an x-ray microscope integrated with a grating interferometer,which simultaneously enables the high spatial resolution imaging and the improved image contrast.By using this theory,several key parameters of phase contrast imaging can be predicted,for instance,the fringe visibility and period,and the conversion condition from the differential phase imaging(DPI)to the phase difference imaging(PDI).Additionally,numerical simulations are performed with certain x-ray optical components and imaging geometry.Comparison with the available experimental measurement[Appl.Phys.Lett.113063105(2018)]demonstrates the accuracy of this developed quantitative analysis method of x-ray phase-sensitive microscope imaging.

Research on resting spontaneous brain activity and functional connectivity of acupuncture at uterine acupoints

Objective The resting-state functional magnetic resonance imaging(rs-f MRI)method was used to observe brain activity and its functional connection upon electroacupuncture stimulation at bilateral uterine acupoints(EX-CA1),as well as to investigate the mechanism of acupuncture in the treatment of gynecological diseases.Methods Twenty-two healthy female subjects were stimulated by electroacupuncture at bilateral uterine acupoints;rs-f MRI data of the brain were acquired and standardized.Degree centrality(DC),amplitude of low-frequency fluctuation(ALFF),and regional homogeneity(ReHo)were used to analyze local spontaneous brain activity via acupuncture.An independent component analysis was used to evaluate the functional connectivity of the resting brain networks after acupuncture.Results Analytical results showed that the neural activity intensity of the precuneus lobe,orbitofrontal cortex,lingual gyrus,amygdala,and posterior central gyrus decreased after acupuncture(voxel P<0.001,cluster P<0.05).Functional connectivity analysis revealed weakened auditory and right frontal-parietal networks(voxel P<0.001,cluster P<0.05),enhanced visual network(voxel P<0.001,cluster P<0.05),and synergistic auditory network and hypothalamic-pituitary system.Conclusion Significant differences in neural activity and functional connectivity in specific brain regions were observed after acupuncture intervention at uterine acupoints;the hypothalamic-pituitary system also showed various active states in different brain regions.It is speculated that the effective mechanism of acupuncture at uterine acupoints is related to the regulation of reproductive hormones,emotional changes,and somatic sensations.Therefore,the methods used in this study could clarify the neural mechanism of uterine-point acupuncture in the treatment of gynecological diseases and may serve as a reference for other studies pertaining to acupuncture.

The Role of Occipitotemporal Network for Speed-Reading:An fMRI Study

The activity of occipitotemporal regions involved in linguistic reading processes,such as the ventral occipitotemporal cortex(vOT),is believed to exhibit strong interactions during higher-order language processing,specifically in the connectivity between the occipital gyrus and the temporal gyrus.In this study,we utilized functional magnetic resonance imaging(fMRI)with psychophysiological interaction(PPI)and dynamic causal modeling(DCM)to investigate the functional and effective connectivity in the occipitotemporal network during speed reading.We conducted the experiment with native Japanese speakers who underwent and without speed-reading training and subsequently performed established reading tasks at different speeds(slow,medium,and fast)while undergoing 3-Tesla Siemens fMRI.Our activation analyses revealed significant changes in occipital and temporal regions as reading speed increased,indicating functional connectivity within the occipitotemporal network.DCM results further demonstrated more intricate effective connections and high involvement within the occipitotemporal pathway:(1)reading signals originated from the inferior occipital gyrus(iO),distributed to the vOT and the posterior superior temporal sulcus(pSTS),and then gathered in the anterior superior temporal sulcus(aSTS);(2)reading speed loads had modulation effects on the pathways from the aSTS to vOT and from the iO to vOT.These findings highlight the complex connectivity and dynamic interactions within the occipitotemporal network during speed-reading processes.

The Mechanism for Allocating Limited Working Memory Resources in Multitasking

Working memory plays an important role in many complex cognitive activities such as thinking,reasoning,decisionmaking,and language comprehension.Working memory refers to a mechanism involving both the temporary storage and the manipulation of information.As an important approach toward understanding the mechanisms of working memory,visual working memory has attracted attention since the 1990s.

The altered network complexity of resting-state functional brain activity in schizophrenia and bipolar disorder patients

Schizophrenia(SZ)and bipolar disorder(BD)are two of themost frequent mental disorders.These disorders exhibit similarpsychotic symptoms,making diagnosis challenging and leadingto misdiagnosis.Yet,the network complexity changes drivingspontaneous brain activity in SZ and BD patients are still unknown.Functional entropy(FE)is a novel way of measuring the dispersion(or spread)of functional connectivities inside the brain.The FE wasutilized in this study to examine the network complexity of the resting-state fMRI data of SZ and BD patients at three levels,including global,modules,and nodes.At three levels,the FE of SZand BD patients was considerably lower than that of normal control(NC).At the intra-module level,the FE of SZ was substantially higher than that of BD in the cingulo-opercular network.Moreover,a strong negative association between FE and clinical measureswas discovered in patient groups.Finally,we classified using theFE features and attained an accuracy of 66.7%(BD vs.SZ vs.NC)and an accuracy of 75.0%(SZ vs.BD).These findings proposed that network connectivity’s complexity analyses using FE can provideimportant insights for the diagnosis of mental illness.