Dielectric properties of urine in relation to bladder cancer.

Many studies have investigated the dielectric properties of human and animal tissues, particularly to differentiate between normal cells and tumors. However, these studies are invasive as tissue samples have to be excised to measure the properties. This study aims to investigate the dielectric properties of urine in relation to bladder cancer, which is safe and non-invasive to patients.

The Application of Sulfonyl Hydrazides in Electrosynthesis: A Review of Recent Studies.

Sulfonyl hydrazides are viewed as alternatives to sulfinic acids and their salts or sulfonyl halides, which are broadly used in organic synthesis or work as active pharmaceutical substances. Generally, sulfonyl hydrazides are considered good building blocks and show powerful value in a diverse range of reactions to construct C-S bonds or C-C bonds, and even C-N bonds as sulfur, carbon, or nitrogen sources, respectively. As a profound synthetic tool, the electrosynthesis method was recently used to achieve efficient and green applications of sulfonyl hydrazides.

A parallel-group study of near-infrared spectroscopy-neurofeedback in children with attention deficit hyperactivity disorder.

The present study aimed to assess the efficacy of Near-infrared spectroscopy (NIRS) real-time neurofeedback (NF) vs. atomoxetine (AT) in children with attention deficit hyperactivity disorder (ADHD). A parallel-group study was conducted to enroll children with ADHD between 8 and 12 years of age.

NIRS-ICA: A MATLAB Toolbox for Independent Component Analysis Applied in fNIRS Studies.

Independent component analysis (ICA) is a multivariate approach that has been widely used in analyzing brain imaging data. In the field of functional near-infrared spectroscopy (fNIRS), its promising effectiveness has been shown in both removing noise and extracting neuronal activity-related sources. The application of ICA remains challenging due to its complexity in usage, and an easy-to-use toolbox dedicated to ICA processing is still lacking in the fNIRS community.

Transcranial brain atlas-based optimization for functional near-infrared spectroscopy optode arrangement: Theory, algorithm, and application.

The quality of optode arrangement is crucial for group imaging studies when using functional near-infrared spectroscopy (fNIRS). Previous studies have demonstrated the promising effectiveness of using transcranial brain atlases (TBAs), in a manual and intuition-based way, to guide optode arrangement when individual structural MRI data are unavailable. However, the theoretical basis of using TBA to optimize optode arrangement remains unclear, which leads to manual and subjective application.

Dyad sex composition effect on inter-brain synchronization in face-to-face cooperation.

Human cooperation behavior based on reciprocal altruism has been a hallmark of ancient and modern societies. Prior studies have indicated that inter-brain synchronization (IBS) between partners could exist during cooperation. However, how the sex composition of dyads influences the neural synchronization is still poorly understood.

Functional near-infrared spectroscopy (fNIRS) as a tool to assist the diagnosis of major psychiatric disorders in a Chinese population.

Advances in neuroimaging have promised the development of specific and objective biomarkers for the diagnosis and treatment of psychiatric disorders. Recently, functional near-infrared spectroscopy (fNIRS) has been used during cognitive tasks to measure cortical dysfunction associated with mental illnesses such as Schizophrenia (SCH), Major-Depressive disorder (MD) and Bipolar Disorder (BD). We investigated the ability of fNIRS as a clinically viable tool to successfully distinguish healthy individuals from those with major psychiatric disorders.

A review on the accuracy of bladder cancer detection methods.

: Bladder cancer is the most common malignant tumour in the urinary system, with a high incidence and recurrence rate. While the incidence of bladder cancer has been rising in recent years, the prevalence of bladder carcinoma is showing an increasing tendency in the younger age group. There are several methods to detect bladder cancer, but different methods have varying degrees of accuracy which intrinsically depends on the method's sensitivity and specificity.

Corrigendum: Feasibility of Functional Near-Infrared Spectroscopy (fNIRS) to Investigate the Mirror Neuron System: An Experimental Study in a Real-Life Situation.

[This corrects the article DOI: 10.3389/fnhum.2018.

Feasibility of Functional Near-Infrared Spectroscopy (fNIRS) to Investigate the Mirror Neuron System: An Experimental Study in a Real-Life Situation.

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.

A Gaussian mixture model based adaptive classifier for fNIRS brain-computer interfaces and its testing via simulation.

Objective: Functional near infra-red spectroscopy (fNIRS) is a promising brain imaging technology for brain-computer interfaces (BCI). Future clinical uses of fNIRS will likely require operation over long time spans, during which neural activation patterns may change. However, current decoders for fNIRS signals are not designed to handle changing activation patterns.

Independent component analysis-based source-level hyperlink analysis for two-person neuroscience studies.

Two-person neuroscience, a perspective in understanding human social cognition and interaction, involves designing immersive social interaction experiments as well as simultaneously recording brain activity of two or more subjects, a process termed “hyperscanning.” Using newly developed imaging techniques, the interbrain connectivity or hyperlink of various types of social interaction has been revealed. Functional near-infrared spectroscopy (fNIRS)-hyperscanning provides a more naturalistic environment for experimental paradigms of social interaction and has recently drawn much attention.

Semi-automatic 10/20 Identification Method for MRI-Free Probe Placement in Transcranial Brain Mapping Techniques.

The International 10/20 system is an important head-surface-based positioning system for transcranial brain mapping techniques, e.g., fNIRS and TMS.

Multiregional functional near-infrared spectroscopy reveals globally symmetrical and frequency-specific patterns of superficial interference.

Linear regression with short source-detector separation channels (S-channels) as references is an efficient way to overcome significant physiological interference from the superficial layer for functional near-infrared spectroscopy (fNIRS). However, the co-located configuration of S-channels and long source-detector separation channels (L-channels) is difficult to achieve in practice. In this study, we recorded superficial interference with S-channels in multiple scalp regions.

Cluster imaging of multi-brain networks (CIMBN): a general framework for hyperscanning and modeling a group of interacting brains.

Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise.

Cross-brain neurofeedback: scientific concept and experimental platform.

The present study described a new type of multi-person neurofeedback with the neural synchronization between two participants as the direct regulating target, termed as "cross-brain neurofeedback." As a first step to implement this concept, an experimental platform was built on the basis of functional near-infrared spectroscopy, and was validated with a two-person neurofeedback experiment. This novel concept as well as the experimental platform established a framework for investigation of the relationship between multiple participants' cross-brain neural synchronization and their social behaviors, which could provide new insight into the neural substrate of human social interactions.

Determination of dominant frequency of resting-state brain interaction within one functional system.

Accumulating evidence has revealed that the resting-state functional connectivity (RSFC) is frequency specific and functional system dependent. Determination of dominant frequency of RSFC (RSFC(df)) within a functional system, therefore, is of importance for further understanding the brain interaction and accurately assessing the RSFC within the system. Given the unique advantages over other imaging techniques, functional near-infrared spectroscopy (fNIRS) holds distinct merits for RSFC(df) determination.

Effects of apolipoprotein E genotype on the off-line memory consolidation.

Spontaneous brain activity or off-line activity after memory encoding is associated with memory consolidation. A few recent resting-state functional magnetic resonance imaging (RS-fMRI) studies indicate that the RS-fMRI could map off-line memory consolidation effects. However, the gene effects on memory consolidation process remain largely unknown.

Quantitative comparison of resting-state functional connectivity derived from fNIRS and fMRI: a simultaneous recording study.

The feasibility of functional near-infrared spectroscopy (fNIRS) to assess resting-state functional connectivity (RSFC) has already been demonstrated. However the validity of fNIRS-based RSFC has rarely been studied. In the present study, fNIRS and fMRI data were simultaneously acquired from 21 subjects during the resting state.

REST: a toolkit for resting-state functional magnetic resonance imaging data processing.

Resting-state fMRI (RS-fMRI) has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST).

Is resting-state functional connectivity revealed by functional near-infrared spectroscopy test-retest reliable?

Recently, resting-state functional near-infrared spectroscopy (rs-fNIRS) research has experienced tremendous progress. Resting-state functional connectivity (RSFC) has been adopted as a pivotal biomarker in rs-fNIRS studies. However, it is yet to be clear if the RSFC derived from rs-fNIRS is reliable.

Test-retest assessment of independent component analysis-derived resting-state functional connectivity based on functional near-infrared spectroscopy.

Recent studies of resting-state functional near-infrared spectroscopy (fNIRS) have emerged as a hot topic and revealed that resting-state functional connectivity (RSFC) is an inherent characteristic of the resting brain. However, it is currently unclear if fNIRS-based RSFC is test-retest reliable. In this study, we utilized independent component analysis (ICA) as an effective RSFC detection tool to address the reliability question.

Detecting resting-state functional connectivity in the language system using functional near-infrared spectroscopy.

Functional connectivity has become one of the important approaches to understanding the functional organization of the human brain. Recently, functional near-infrared spectroscopy (fNIRS) was demonstrated as a feasible method to study resting-state functional connectivity (RSFC) in the sensory and motor systems. However, whether such fNIRS-based RSFC can be revealed in high-level and complex functional systems remains unknown.

Subject order-independent group ICA (SOI-GICA) for functional MRI data analysis.

Independent component analysis (ICA) is a data-driven approach to study functional magnetic resonance imaging (fMRI) data. Particularly, for group analysis on multiple subjects, temporally concatenation group ICA (TC-GICA) is intensively used. However, due to the usually limited computational capability, data reduction with principal component analysis (PCA: a standard preprocessing step of ICA decomposition) is difficult to achieve for a large dataset.

Functional connectivity as revealed by independent component analysis of resting-state fNIRS measurements.

As a promising non-invasive imaging technique, functional near infrared spectroscopy (fNIRS) has recently earned increasing attention in resting-state functional connectivity (RSFC) studies. Preliminary fNIRS-based RSFC studies adopted a seed correlation approach and yielded interesting results. However, the seed correlation approach has several inherent problems, such as neglecting of interactions among multiple regions and a dependence on seed region selection.