Small world properties of schizophrenia and OCD patients derived from fNIRS based functional brain network connectivity metrics.

Individuals suffering from obsessive compulsive disorder (OCD) and schizophrenia (SCZ) frequently exhibit symptoms of cognitive disassociations, which are linked to poor functional integration among brain regions. The loss of functional integration can be assessed using graph metrics computed from functional connectivity matrices (FCMs) derived from neuroimaging data. A healthy brain at rest is known to exhibit small-world features with high clustering coefficients and shorter path lengths in contrast to random networks.

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.

Awareness and level of digital literacy among students receiving health-based education.

Background: Being digitally literate allows health-based science students to access reliable, up-to-date information efficiently and expands the capacity for continuous learning. Digital literacy facilitates effective communication and collaboration among other healthcare providers. It helps to navigate the ethical implications of using digital technologies and aids the use of digital tools in managing healthcare processes.

fNIRS-derived neurocognitive ratio as a biomarker for neuropsychiatric diseases.

Clinical use of fNIRS-derived features has always suffered low sensitivity and specificity due to signal contamination from background systemic physiological fluctuations. We provide an algorithm to extract cognition-related features by eliminating the effect of background signal contamination, hence improving the classification accuracy. The aim in this study is to investigate the classification accuracy of an fNIRS-derived biomarker based on global efficiency (GE).

Identification of impulsive adolescents with a functional near infrared spectroscopy (fNIRS) based decision support system.

The gold standard for diagnosing impulsivity relies on clinical interviews, behavioral questionnaires and rating scales which are highly subjective.The aim of this study was to develop a functional near infrared spectroscopy (fNIRS) based classification approach for correct identification of impulsive adolescents. Taking into account the multifaceted nature of impulsivity, we propose that combining informative features from clinical, behavioral and neurophysiological domains might better elucidate the neurobiological distinction underlying symptoms of impulsivity.

Classification of motor imagery and execution signals with population-level feature sets: implications for probe design in fNIRS based BCI.

Objective: The aim of this study was to introduce a novel methodology for classification of brain hemodynamic responses collected via functional near infrared spectroscopy (fNIRS) during rest, motor imagery (MI) and motor execution (ME) tasks which involves generating population-level training sets.

Approach: A 48-channel fNIRS system was utilized to obtain hemodynamic signals from the frontal (FC), primary motor (PMC) and somatosensory cortex (SMC) of ten subjects during an experimental paradigm consisting of MI and ME of various right hand movements. Classification accuracies of random forest (RF), support vector machines (SVM), and artificial neural networks (ANN) were computed at the single subject level by training each classifier with subject specific features, and at the group level by training with features from all subjects for ME versus Rest, MI versus Rest and MI versus ME conditions.

The hemodynamic effects of occlusal splint therapy on the masseter muscle of patients with myofascial pain accompanied by bruxism.

: The aim of this study was to investigate the hemodynamic effects of occlusal splint therapy on masseter muscles of patients with myofascial pain accompanied by bruxism with near-infrared spectroscopy (NIRS). : Twenty-four patients were randomly divided into two groups, where the study group ( = 12) received occlusal splint therapy and the control group ( = 12) underwent no therapy. Measurements were categorized into four subgroups: painful or painless control and painful or painless splint.

Partial correlation-based functional connectivity analysis for functional near-infrared spectroscopy signals.

A theoretical framework, a partial correlation-based functional connectivity (PC-FC) analysis to functional near-infrared spectroscopy (fNIRS) data, is proposed. This is based on generating a common background signal from a high passed version of fNIRS data averaged over all channels as the regressor in computing the PC between pairs of channels. This approach has been employed to real data collected during a Stroop task.

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.

Joint state and parameter estimation of the hemodynamic model by particle smoother expectation maximization method.

Objective: In this paper, we aimed for the robust estimation of the parameters and states of the hemodynamic model by using blood oxygen level dependent signal.

Approach: In the fMRI literature, there are only a few successful methods that are able to make a joint estimation of the states and parameters of the hemodynamic model. In this paper, we implemented a maximum likelihood based method called the particle smoother expectation maximization (PSEM) algorithm for the joint state and parameter estimation.

Mutant SOD1 protein increases Nav1.3 channel excitability.

Amyotrophic lateral sclerosis (ALS) is a lethal paralytic disease caused by the degeneration of motor neurons in the spinal cord, brain stem, and motor cortex. Mutations in the gene encoding copper/zinc superoxide dismutase (SOD1) are present in ~20% of familial ALS and ~2% of all ALS cases. The most common SOD1 gene mutation in North America is a missense mutation substituting valine for alanine (A4V).

Similarity analysis of functional connectivity with functional near-infrared spectroscopy.

One of the remaining challenges in functional connectivity (FC) studies is investigation of the temporal variability of FC networks. Recent studies focusing on the dynamic FC mostly use functional magnetic resonance imaging as an imaging tool to investigate the temporal variability of FC. We attempted to quantify this variability via analyzing the functional near-infrared spectroscopy (fNIRS) signals, which were recorded from the prefrontal cortex (PFC) of 12 healthy subjects during a Stroop test.

Analysis of task-evoked systemic interference in fNIRS measurements: insights from fMRI.

Functional near infrared spectroscopy (fNIRS) is a promising method for monitoring cerebral hemodynamics with a wide range of clinical applications. fNIRS signals are contaminated with systemic physiological interferences from both the brain and superficial tissues, resulting in a poor estimation of the task related neuronal activation. In this study, we use the anatomical resolution of functional magnetic resonance imaging (fMRI) to extract scalp and brain vascular signals separately and construct an optically weighted spatial average of the fMRI blood oxygen level-dependent (BOLD) signal for characterizing the scalp signal contribution to fNIRS measurements.

Localization of an absorber in a turbid semi-infinite medium by spatially resolved continuous-wave diffuse reflectance measurements.

A method to locate an absorber embedded in a semi-infinite turbid medium by spatially-resolved continuous-wave (SRCW) diffuse reflectance measurements is introduced. The depth of the absorber is assessed by single wavelength SRCW diffuse reflectance measurements by two detectors in a radial row. The ratio of perturbations introduced by the defect at two detectors is used to be matched with the ratio-versus-depth curve, which are generated by approximate formulas of continuous wave diffuse reflectance.

Association among SNAP-25 gene DdeI and MnlI polymorphisms and hemodynamic changes during methylphenidate use: a functional near-infrared spectroscopy study.

Objective: To investigate the interaction of treatment-related hemodynamic changes with genotype status for Synaptosomal associated protein 25 (SNAP-25) gene in participants with attention deficit hyperactivity disorder (ADHD) on and off single dose short-acting methylphenidate treatment with functional near-infrared spectroscopy (fNIRS).

Method: A total of 15 right-handed adults and 16 right-handed children with DSM-IV diagnosis of ADHD were evaluated. Ten milligrams of short-acting methylphenidate was administered in a crossover design.

The Possible Role of CO(2) in Producing A Post-Stimulus CBF and BOLD Undershoot.

Comprehending the underlying mechanisms of neurovascular coupling is important for understanding the pathogenesis of neurodegenerative diseases related to uncoupling. Moreover, it elucidates the casual relation between the neural signaling and the hemodynamic responses measured with various imaging modalities such as functional magnetic resonance imaging (fMRI). There are mainly two hypotheses concerning this mechanism: a metabolic hypothesis and a neurogenic hypothesis.

Investigating brain hemodynamics of ADHD patients by functional near infrared spectroscopy.

Inhibition of prepotent response is an executive function and is subserved by prefrontal cortex of the brain in healthy subjects. Damage to these regions results in response inhibition deficits. Response inhibition deficits have been linked to several neurological disorders.

Effect of aerobic exercise training on oxygen uptake and kinetics in patients with fibromyalgia.

The aim of this study is to investigate relation between cardiopulmonary performance and muscular microcirculation in patients with fibromyalgia syndrome (FMS). Twenty-one female sedentary patients who were diagnosed as FMS, and 15 sedentary females were enrolled in to the study. All participants underwent a modified Bruce multistage maximal treadmill protocol with metabolic measurements and Near-Infrared Spectroscopy measurements.

On temporal connectivity of PFC via Gauss-Markov modeling of fNIRS signals.

Functional near-infrared spectroscopy (fNIRS) is an optical imaging method, which monitors the brain activation by measuring the successive changes in the concentration of oxy- and deoxyhemoglobin in real time. In this study, we present a method to investigate the functional connectivity of prefrontal cortex (PFC) Sby applying a Gauss-Markov model to fNIRS signals. The hemodynamic changes on PFC during the performance of cognitive paradigm are measured by fNIRS for 17 healthy adults.

Use of N-terminal pro-brain natriuretic peptide to assess left ventricular function after adjuvant doxorubicin therapy in early breast cancer patients: a prospective series.

Background And Objective: Anthracyclines are well established and highly efficacious antineoplastic agents for various haematopoietic and solid tumours, such as breast cancer. The main adverse effect of anthracycline therapy is cardiotoxicity. The aim of this prospective study was to determine the role of plasma levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) in assessing left ventricular function in early breast cancer patients receiving adjuvant anthracycline treatment.

Crosstalk and error analysis of fat layer on continuous wave near-infrared spectroscopy measurements.

Accurate estimation of concentration changes in muscles by continuous wave near-IR spectroscopy for muscle measurements suffers from underestimation and crosstalk problems due to the presence of superficial skin and fat layers. Underestimation error is basically caused by a homogeneous medium assumption in the calculations leading to the partial volume effect. The homogeneous medium assumption and wavelength dependence of mean partial path length in the muscle layer cause the crosstalk.

Multilevel statistical inference from functional near-infrared spectroscopy data during stroop interference.

Functional near-infrared spectroscopy (fNIRS) is an emerging technique for monitoring the concentration changes of oxy- and deoxy-hemoglobin (oxy-Hb and deoxy-Hb) in the brain. An important consideration in fNIRS-based neuroimaging modality is to conduct group-level analysis from a set of time series measured from a group of subjects. We investigate the feasibility of multilevel statistical inference for fNIRS.

Constraining the general linear model for sensible hemodynamic response function waveforms.

We propose a method to do constrained parameter estimation and inference from neuroimaging data using general linear model (GLM). Constrained approach precludes unrealistic hemodynamic response function (HRF) estimates to appear at the outcome of the GLM analysis. The permissible ranges of waveform parameters were determined from the study of a repertoire of plausible waveforms.

Reconstruction and flux analysis of coupling between metabolic pathways of astrocytes and neurons: application to cerebral hypoxia.

Background: It is a daunting task to identify all the metabolic pathways of brain energy metabolism and develop a dynamic simulation environment that will cover a time scale ranging from seconds to hours. To simplify this task and make it more practicable, we undertook stoichiometric modeling of brain energy metabolism with the major aim of including the main interacting pathways in and between astrocytes and neurons.

Model: The constructed model includes central metabolism (glycolysis, pentose phosphate pathway, TCA cycle), lipid metabolism, reactive oxygen species (ROS) detoxification, amino acid metabolism (synthesis and catabolism), the well-known glutamate-glutamine cycle, other coupling reactions between astrocytes and neurons, and neurotransmitter metabolism.