Near-Infrared Spectroscopy in Bio-Applications

Molecules, Journal Year: 2020, Volume and Issue: 25(12), P. 2948 - 2948

Published: June 26, 2020

Near-infrared (NIR) spectroscopy occupies a specific spot across the field of bioscience and related disciplines. Its characteristics application potential differs from infrared (IR) or Raman spectroscopy. This vibrational technique elucidates molecular information examined sample by measuring absorption bands resulting overtones combination excitations. Recent decades brought significant progress in instrumentation (e.g., miniaturized spectrometers) spectral analysis methods image processing analysis, quantum chemical calculation NIR spectra), which made notable impact on its applicability. review aims to present as matured technique, yet with great for further advances several directions throughout broadly understood bio-applications. practical value is critically assessed compared competing techniques. Attention given link bio-application fundamental principal features spectra.

Language: Английский

---

NIRS-KIT: a MATLAB toolbox for both resting-state and task fNIRS data analysis

Neurophotonics, Journal Year: 2021, Volume and Issue: 8(01)

Published: Jan. 25, 2021

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

Language: Английский

---

Decoding chemical information from vibrational spectroscopy data: Local vibrational mode theory

Wiley Interdisciplinary Reviews Computational Molecular Science, Journal Year: 2020, Volume and Issue: 10(5)

Published: May 11, 2020

Abstract Modern vibrational spectroscopy is more than just an analytical tool. Information about the electronic structure of a molecule, strength its bonds, and conformational flexibility encoded in normal modes. On other hand, modes are generally delocalized, which hinders direct access to this information, attainable only via local vibration associated properties. Konkoli Cremer provided ingenious solution problem by deriving from fundamental modes, obtained harmonic approximation potential, mass‐decoupled Euler–Lagrange equations. This review gives general introduction into mode theory Cremer, elucidating how unifies earlier attempts obtain easy interpret chemical information spectroscopy: (a) furnishes bond descriptors derived force constant matrices with physical basis, (b) provides highly sought after extension Badger rule polyatomic molecules, (c) offers simpler way derive localized vibrations compared complex route overtone spectroscopy. Successful applications presented, including new measure strength, detailed analysis infrared/Raman spectra, recent periodic systems, opening avenue for characterization bonding crystals. At end LMODEA software introduced, performs (with minimal computational costs) frequency calculation optionally using measured frequencies as additional input. article categorized under: Structure Mechanism > Molecular Structures Theoretical Physical Chemistry Spectroscopy Software Quantum Electronic Theory Ab Initio Methods

Language: Английский

---

The Potential of Functional Near-Infrared Spectroscopy-Based Neurofeedback—A Systematic Review and Recommendations for Best Practice

Frontiers in Neuroscience, Journal Year: 2020, Volume and Issue: 14

Published: July 21, 2020

Background: The effects of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI)-neurofeedback on brain activation behaviors have been studied extensively in the past. More recently, researchers begun to investigate near-infrared spectroscopy-based neurofeedback (fNIRS-neurofeedback). FNIRS is a neuroimaging technique based hemodynamics, which easy use, portable, inexpensive, has reduced sensitivity movement artifacts. Method: We provide first systematic review database fNIRS-neurofeedback studies, synthesizing findings from 22 peer-reviewed studies (including total N = 441 participants; 337 healthy, 104 patients). (1) give comprehensive overview how training protocols were implemented, (2) online signal-processing methods used, (3) evaluate quality using pre-set methodological reporting criteria also present statistical sensitivity/power analyses, (4) effectiveness modulating activation, (5) its changing behavior healthy pathological populations. Results discussion: (1-2) Published are heterogeneous (e.g., targets, investigated populations, applied protocols, methods). Large randomized controlled trials still lacking. In view novelty field, published moderate. identified room for improvement important information power detect realistic effects. Several show that people can regulate hemodynamic signals cortical regions with these indicate feasibility motor control prefrontal functioning participants ameliorating symptoms clinical populations (stroke, ADHD, autism, social anxiety). However, valid conclusions about specificity or potential utility premature. Conclusion: Due advantages practicability relatively low cost, might suitable powerful alternative EEG fMRI great translation neurofeedback. Together more rigorous research practices, further improvements may lead solid understanding fNIRS-neurofeedback. Future will benefit exploiting fNIRS, offers unique opportunities research.

Language: Английский

---

A consensus guide to using functional near-infrared spectroscopy in posture and gait research

Gait & Posture, Journal Year: 2020, Volume and Issue: 82, P. 254 - 265

Published: Sept. 18, 2020

Language: Английский

---

Frequency-Domain Techniques for Cerebral and Functional Near-Infrared Spectroscopy

Frontiers in Neuroscience, Journal Year: 2020, Volume and Issue: 14

Published: April 7, 2020

This article reviews the basic principles of frequency-domain near-infrared spectroscopy (FD-NIRS), which relies on intensity-modulated light sources and phase-sensitive optical detection, its non-invasive applications to brain. The simpler instrumentation more straightforward data analysis continuous-wave NIRS (CW-NIRS) accounts for fact that almost all current commercial instruments cerebral have embraced CW technique. However, FD-NIRS provides with richer information content, complements or exceeds capabilities CW-NIRS. One example is ability measure absolute properties (absorption reduced scattering coefficients) tissue, thus concentrations oxyhemoglobin deoxyhemoglobin in brain tissue. measured values such hemoglobin reported literature animal models human newborns, infants, children, adults. We also review application functional studies focused slower hemodynamic responses activity (time scale seconds) faster signals been linked neuronal activation 100 ms). Another power related different regions sensitivity featured by intensity phase data. report recent developments take advantage this feature maximize tissue relative superficial extracerebral (scalp, skull, etc.). contend latter capability a highly appealing quality FD-NIRS, measurements may result significant advances field sensing

Language: Английский

---

Short-channel regression in functional near-infrared spectroscopy is more effective when considering heterogeneous scalp hemodynamics

Neurophotonics, Journal Year: 2020, Volume and Issue: 7(03)

Published: Sept. 29, 2020

Significance: The reliability of functional near-infrared spectroscopy (fNIRS) measurements is reduced by systemic physiology. Short-channel regression algorithms aim at removing “noise” subtracting the signal measured a short source–detector separation (mainly scalp hemodynamics) from one long (brain and hemodynamics). In literature, incongruent approaches on selection optimal regressor are reported based different assumptions hemodynamics properties. Aim: We investigated spatial temporal distribution over sensorimotor cortex evaluated its influence effectiveness short-channel regressions. Approach: performed hand-grasping resting-state experiments with five subjects, measuring 16 optodes areas, including eight 8-mm channels. detailed correlation analyses 180 270 simulated (overlaid measurements) trials. Five combinations were implemented general linear models. Three chosen according to two proposed additional physiological [considering multiple channels their Mayer wave (MW) oscillations]. Results: found heterogeneous in scalp, coming top global close-to-homogeneous behavior (correlation 0.69 0.92). results further demonstrate that always improves brain activity estimates but better obtained when heterogeneity assumed. particular, we highlight more effective combining regressors MWs additionally included. Conclusion: shed light signals for improving removal artifacts fNIRS. conclude most assuming hemodynamics, particular spatial- frequency-specific information. A understanding will promote accurate assessments clinical research settings.

Language: Английский

---

Deep learning in fNIRS: a review

Neurophotonics, Journal Year: 2022, Volume and Issue: 9(04)

Published: July 20, 2022

Significance: Optical neuroimaging has become a well-established clinical and research tool to monitor cortical activations in the human brain. It is notable that outcomes of functional near-infrared spectroscopy (fNIRS) studies depend heavily on data processing pipeline classification model employed. Recently, deep learning (DL) methodologies have demonstrated fast accurate performances tasks across many biomedical fields. Aim: We aim review emerging DL applications fNIRS studies. Approach: first introduce some commonly used techniques. Then, summarizes current work most active areas this field, including brain-computer interface, neuro-impairment diagnosis, neuroscience discovery. Results: Of 63 papers considered review, 32 report comparative study techniques traditional machine where 26 been shown outperforming latter terms accuracy. In addition, eight also utilize reduce amount preprocessing typically done with or increase via augmentation. Conclusions: The application mitigate hurdles present such as lengthy small sample sizes while achieving comparable improved

Language: Английский

---

Opportunities and Limitations of Mobile Neuroimaging Technologies in Educational Neuroscience

Mind Brain and Education, Journal Year: 2021, Volume and Issue: 15(4), P. 354 - 370

Published: Oct. 5, 2021

As the field of educational neuroscience continues to grow, questions have emerged regarding ecological validity and applicability this research practice. Recent advances in mobile neuroimaging technologies made it possible conduct neuroscientific studies directly naturalistic learning environments. We propose that embedding a cycle (Matusz, Dikker, Huth, & Perrodin, 2019), involving lab-based, seminaturalistic, fully experiments, is well suited for addressing questions. With review, we take cautious approach, by discussing valuable insights can be gained from technology, including electroencephalography functional near-infrared spectroscopy, as challenges posed bringing methods into classroom. Research paradigms used alongside technology vary considerably. To illustrate point, are discussed with increasingly designs. conclude several ethical considerations should taken account unique area research.

Language: Английский

---

Wearable, high-density fNIRS and diffuse optical tomography technologies: a perspective

Neurophotonics, Journal Year: 2023, Volume and Issue: 10(02)

Published: May 17, 2023

Recent progress in optoelectronics has made wearable and high-density functional near-infrared spectroscopy (fNIRS) diffuse optical tomography (DOT) technologies possible for the first time. These have potential to open new fields of real-world neuroscience by enabling neuroimaging human cortex at a resolution comparable fMRI almost any environment population. In this perspective article, we provide brief overview history current status fNIRS DOT approaches, discuss greatest ongoing challenges, our thoughts on future remarkable technology.

Language: Английский

---