Various lead-free (K x Na 1Àx ) 0.98 Li 0.02 (Nb 0.82Ày Ta 0.18 Sb y )O 3 ceramics with x 5 0.50, y 5 0.00-0.07 or x 5 0.40-0.60, y 5 0.05 were prepared by the conventional solid-state reaction method. Systematic investigation on the microstructures, crystalline structures, and dielectric and piezoelectric properties was carried out. Remarkably strong piezoelectricity has been achieved in (K 0.45 Na 0.55 ) 0.98 Li 0.02 (Nb 0.77 Ta 0.18 Sb 0.05 )O 3 ceramic, which shows the excellent piezoelectric properties of d 33 5 413 pC/N, d 31 5 À153 pC/N, k p 5 0.50, and k 33 5 0.62. It is considered that the observed strong piezoelectricity should be ascribed to several combined decisive factors, such as the phase coexistence due to an orthorhombic-tetragonal polymorphic phase transition near room temperature, the high electronegativity of Sb 51 ions as compared with those of Nb 51 ions and Ta 51 ions, and the relatively ideal microstructure with high density, large average grain size and narrow grain-size distribution.

Significance: Functional near-infrared spectroscopy (fNIRS) has been widely used to probe human brain function during task state and resting state. However, the existing analysis toolboxes mainly focus on task activation analysis, few software packages can assist resting-state fNIRS studies. Aim:We aimed to provide a versatile and easy-to-use toolbox to perform analysis for both resting state and task fNIRS.Approach: We developed a MATLAB toolbox called NIRS-KIT that works for both restingstate analysis and task activation detection.Results: NIRS-KIT implements common and necessary processing steps for performing fNIRS data analysis, including data preparation, quality control, preprocessing, individual-level analysis, group-level statistics with several popular statistical models, and multiple comparison correction methods, and finally results visualization. For resting-state fNIRS analysis, functional connectivity analysis, graph theory-based network analysis, and amplitude of low-frequency fluctuations analysis are provided. Additionally, NIRS-KIT also supports activation analysis for task fNIRS.Conclusions: NIRS-KIT offers an open source tool for researchers to analyze resting-state and/ or task fNIRS data in one suite. It contains several key features: (1) good compatibility, supporting multiple fNIRS recording systems, data formats of NIRS-SPM and Homer2, and the shared near-infrared spectroscopy format data format recommended by the fNIRS society; (2) flexibility, supporting customized preprocessing scripts; (3) ease-to-use, allowing processing fNIRS signals in batch manner with user-friendly graphical user interfaces; and (4) feature-packed data viewing and result visualization. We anticipate that this NIRS-KIT will facilitate the development of the fNIRS field.

A transcranial brain atlas is a new kind of brain atlas specialized for transcranial noninvasive brain stimulation/imaging techniques.

The mirror neuron system (MNS), mainly including the premotor cortex (PMC), inferior frontal gyrus (IFG), superior parietal lobule (SPL), and rostral inferior parietal lobule (IPL), has attracted extensive attention as a possible neural mechanism of social interaction. Owing to high ecological validity, functional near-infrared spectroscopy (fNIRS) has become an ideal approach for exploring the MNS. Unfortunately, for the feasibility of fNIRS to detect the MNS, none of the four dominant regions were found in previous studies, implying a very limited capacity of fNIRS to investigate the MNS. Here, we adopted an experimental paradigm in a real-life situation to evaluate whether the MNS activity, including four dominant regions, can be detected by using fNIRS. Specifically, 30 right-handed subjects were asked to complete a table-setting task that included action execution and action observation. A double density probe configuration covered the four regions of the MNS in the left hemisphere. We used a traditional channel-based group analysis and also a ROI-based group analysis to find which regions are activated during both action execution and action observation. The results showed that the IFG, adjacent PMC, SPL, and IPL were involved in both conditions, indicating the feasibility of fNIRS to detect the MNS. Our findings provide a foundation for future research to explore the functional role of the MNS in social interaction and various disorders using fNIRS.