Sex based differences in functional connectivity during a working memory task: an fNIRS study.

Differences in corticocerebral structure and function between males and females and their effects on behavior and the prevalence of various neuropsychiatric disorders have been considered as a fundamental topic in various fields of neuroscience. Recent studies on working memory (WM) reported the impact of sex on brain connectivity patterns, which reflect the important role of functional connectivity in the sex topic. Working memory, one of the most important cognitive tasks performed by regions of the PFC, can provide evidence regarding the presence of a difference between males and females. The present study aimed to assess sex differences in brain functional connectivity during working memory-related tasks by using functional near-infrared spectroscopy (fNIRS). In this regard, nine males and nine females completed a dual n-back working memory task with two target inputs of color and location stimuli in three difficulty levels (n = 0, 1, 2). Functional connectivity matrices were extracted for each subject for each memory load level. Females made less errors than males while spending more time performing the task for all workload levels except in 0-back related to the color stimulus, where the reaction time of females was shorter than males. The results of functional connectivity reveal the inverse behavior of two hemispheres at different memory workload levels between males and females. In the left hemisphere, males exhibited stronger connectivity compared to the females, while stronger connectivity was observed in the females' right hemisphere. Furthermore, an inverse trend was detected in the channel pairs with significant connectivity in the right hemisphere of males (falling) and females (rising) by enhancing working memory load level. Considering both behavioral and functional results for two sexes demonstrated a better performance in females due to the more effective use of the brain. The results indicate that sex affects functional connectivity between different areas in both hemispheres of the brain during cognitive tasks of varying difficulty levels although the general impression is that spatial capabilities are considered as a performance of the brain's right hemisphere. These results reinforce the presence of a sex effect in the functional imaging studies of hemodynamic function and emphasize the importance of evaluating brain network connectivity for achieving a better scientific understanding of sex differences.

High-Sensitivity 3D ZIF-8/PDA Photonic Crystal-Based Biosensor for Blood Component Recognition.

Optical biosensors are sensitive devices used in bioanalytics detection. Analysis of blood constituents is very important for the detection of major diseases and also performs a significant role in the diagnosis of diabetes, various cancers, and cardiovascular disorders. In this work, a three-dimensional photonic crystal-based biosensor composed of zeolitic imidazolate framework-8 (ZIF-8) nanoarrays are placed on polydopamine (PDA) coated on a silicon substrate. This sensor is designed, simulated, and evaluated for various blood components in the wavelength range of 1.1 to 1.5 µm by the finite-difference time-domain (FDTD) method. The proposed biosensor was used for 10 types of blood components such as biotin-streptavidin, bovine serum albumin (BSA), cytop, glucose (40 mg/100 mL), hemoglobin, blood plasma, Sylgard184, white blood compounds, urethane dimethacrylate, and polyacrylamide. The FDTD technique was used for the performance analysis of the biosensor. The design parameters of the radius, the lattice constant, the thickness of the ZIF-8 arrays, and the PDA layer thickness are chosen to optimize the photonic crystal structure. This study indicates that the thickness of the PDA is the most important parameter for peak wavelength value in comparison to the other physical parameters. The factors for optimizing the photonic crystal-based biosensors such as the peak wavelength value (PWV), sensitivity, full width at half-maximum (FWHM), and figure of merit (FOM) are significant in comparison with pertinent works in this field, which evaluated 171 nm/RIU, 7.62 nm, and 22.5 RIU-1, respectively. A change of 0.01 nm in the refractive index of the constituents of the blood leads to a shift of 80 nm in the maximum peak wavelength, therefore acting as a functional biosensor with a high detection limit of 0.004 RIU.

Diagnosis of Alzheimer's disease using resting-state fMRI and graph theory.

BACKGROUND: The study of the brain network based on the basis of the resting-state functional Magnetic Resonance Imaging (fMRI) provided some promising results to investigate changes in connectivity among different brain regions because of Alzheimer's disease (AD). OBJECTIVE: In addition, the graph theory has been utilized as an efficient tool in diagnosing Alzheimer and in finding the developed differences in the brain as the result of this disease. METHODS: This study considers 16 areas of the brain, which play a major role in the development of AD. Accordingly, the time series and the correlation matrix were yielded for each of these areas. Then, by using threshold we obtained functional connectivity from correlation matrices along with the brain graph parameter for Normal Controls and AD groups were obtained in order to compare the existing differences. RESULTS: The differences of characteristics among healthy individuals and patients suffering from Alzheimer has been investigated in this study through the formation of brain graphs for 16 areas and the utilization of data on Normal Controls (13 persons) and patients suffering from Alzheimer (13 patients). CONCLUSIONS: Some of the properties of the graph are the characteristic path length, the clustering coefficient, the local and global efficiency yield of ability to separate the two groups which may be used to diagnose Alzheimer.

Graph theoretical approach to functional connectivity in prefrontal cortex via fNIRS.

Functional near-infrared spectroscopy (fNIRS) has been proposed as an affordable, fast, and robust alternative to many neuroimaging modalities yet it still has long way to go to be adapted in the clinic. One request from the clinicians has been the delivery of a simple and straightforward metric (a so-called biomarker) from the vast amount of data a multichannel fNIRS system provides. We propose a simple-straightforward signal processing algorithm derived from [Formula: see text] data collected during a modified version of the color-word matching Stroop task that consists of three different conditions. The algorithm starts with a wavelet-transform-based preprocessing, then uses partial correlation analysis to compute the functional connectivity matrices at each condition and then computes the global efficiency values. To this end, a continuous wave 16 channels fNIRS device (ARGES Cerebro, Hemosoft Inc., Turkey) was used to measure the changes in [Formula: see text] concentrations from 12 healthy volunteers. We have considered 10% of strongest connections in each network. A strong Stroop interference effect was found between the incongruent against neutral condition ([Formula: see text]) while a similar significance was observed for the global efficiency values decreased from neutral to congruent to incongruent conditions [[Formula: see text], [Formula: see text]]. The findings bring us closer to delivering a biomarker derived from fNIRS data that can be reliably and easily adopted by the clinicians.

Evaluating the features of the brain waves to quantify ADHD improvement by neurofeedback.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD), as one of the most common neurological disorders in children and adolescents, is characterized by decentralization, slow learning, distraction and hyperactivity. Studies have shown that in addition to medication, neurofeedback training can also be used to partially control the brain activity of these patients. METHODS: In this study, using the brain signals processing before and after the treatment in 10 children treated by neurofeedback, the changes were evaluated by non-parametric statistical analysis and impact of neurofeedback on brain frequency bands was investigated. Finally, the results were compared with the protocols introduced in this paper and before researches. RESULTS: The results of Kruskal-Wallis test showed an approximately significant increase in the relative power of gamma and an approximately significant reduction in the ratio of relative power of alpha/beta. CONCLUSIONS: It represents the emotional response, elicited by the successful learning and diminished ratio of slow learning to active learning respectively.