C/C++ Coding for Matrix Pseudo Inverses in Clinical Near Infrared Spectroscopy

Near infrared spectroscopy is used clinically to investigate patterns of change in cerebral oxygenation. We have shown that differences reported between authors are likely the result of computer encoding errors in the manipulation of matrices. Current methods compute the inverse of a non-square matrix to derive chromophore concentration values, and solution of another non-square matrix to derive polynomial coefficients of a least squares best fit curve from which the first derivative can be used to estimate blood flow values. Encoding of these pseudo inverses involves too many nested looping steps to easily identify encoding errors. We have given C/C++ source code along with sample numerical values at the termination of each loop within the algorithm. This provides counter checking for future software development by other programmers, and also permits other investigators to report whether the software used for their experiments agrees with previously published material.     

Speeded Near Infrared Spectroscopy (NIRS) Response Detection

The hemodynamic response measured by Near Infrared Spectroscopy (NIRS) is temporally delayed from the onset of the underlying neural activity. As a consequence, NIRS based brain-computer-interfaces (BCIs) and neurofeedback learning systems, may have a latency of several seconds in responding to a change in participants'' behavioral or mental states, severely limiting the practical use of such systems. To explore the possibility of reducing this delay, we used a multivariate pattern classification technique (linear support vector machine, SVM) to decode the true behavioral state from the measured neural signal and systematically evaluated the performance of different feature spaces (signal history, history gradient, oxygenated or deoxygenated hemoglobin signal and spatial pattern). We found that the latency to decode a change in behavioral state can be reduced by 50% (from 4.8 s to 2.4 s), which will enhance the feasibility of NIRS for real-time applications.     

近红外光谱技术在运动脑功能研究中的应用

近红外光谱是一种评估生物组织氧合水平的无创性光学技术,这一技术以血液动力学原理为基础,能实时监测局部脑区的动态变化。近红外光谱作为一种客观的测量工具,在人体运动科学领域广泛运用。近红外光谱技术可用于区别体能水平、监控耐力训练和抗阻训练过程特征以及考察运动中的认知活动变化。本文综述了近红外光谱技术原理及其在抗阻运动、运动中枢疲劳和运动认知领域的运用,并对近红外光谱在运动科学领域的未来研究趋向作了分析。     

Spectral Analysis of Event-Related Hemodynamic Responses in Functional Near Infrared Spectroscopy

The goal of this paper is to design experiments that confirm the evidence of cognitive responses in functional near infrared spectroscopy and to establish relevant spectral subbands. Hemodynamic responses of brain during single-event trials in an odd-ball experiment are measured by functional near infrared spectroscopy method. The frequency axis is partitioned into subbands by clustering the time-frequency power spectrum profiles of the brain responses. The predominant subbands are observed to confine the 0–30 mHz, 30–60 mHz, and 60–330 mHz ranges. We identify the group of subbands that shows strong evidence of protocol-induced periodicity as well as the bands where good correlation with an assumed hemodynamic response models is found.     

近红外光谱技术在稻米特性检测中的应用(综述)

近红外光谱技术是一种新型的检测分析技术,广泛应用于农业、林业、工业、医药以及食品等多个行业领域。文章综述近红外光谱技术在稻米特性检测中的应用概况,包括对大米淀粉、蛋白质和脂肪酸等营养物质的测定,大米糊化特性、粘稠度和食味特性的分析,水稻生长过程中氮、磷、钾和其他营养元素含量的分析,育种研究与品种鉴别,病害、重金属等有害物质以及其他方面。同时,指出该技术在当前检测应用中存在的一些问题,并针对目前发展趋势展望该技术的前景。     

Decomposition and Mineralization of Organic Residues Predicted Using Near Infrared Spectroscopy

Characterization of decomposition characteristics is important for sound management of organic residues for both soils and livestock, but routine residue quality analysis is hindered by slow and costly laboratory methods. This study tested the accuracy and repeatability of near-infrared spectroscopy (NIR) for direct prediction of in vitro dry matter digestibility (IVDMD) and C and N mineralization for a diverse range of organic materials (mostly crop and tree residues) of varying quality (n = 32). The residue samples were aerobically incubated in a sandy soil and amounts of C and N mineralized determined after 28 days. IVDMD and quality attributes were determined using wet chemistry methods. Repeatability was higher with NIR than the original wet chemistry methods: on average NIR halved the measurement standard deviation. NIR predicted IVDMD and C and N mineralization more accurately than models based on wet chemical analysis of residue quality attributes: reduction in root mean square error of prediction with NIR, compared with using quality attributes, was IVDMD, 6%; C mineralization after 28 days, 8%; and N mineralization after 28 days, 8%. Cross-validated r ² values for measured wet chemistry vs. NIR-predicted values were: IVDMD, 0.88; C mineralization, 0.82; and N mineralization, 0.87. Direct prediction of decomposition and mineralization from NIR is faster, more accurate and more repeatable than prediction from residue quality attributes determined using wet chemistry. Further research should be directed towards establishment of diverse NIR calibration libraries under controlled conditions and direct calibration of soil quality, crop and livestock responses in the field to NIR characteristics of residues.     

近红外光谱技术（NIRS）在人体的应用与展望

近红外光谱技术(NIRS)在人体的应用与研究是近年来在国内外新兴的研究领域,因为其方便无创,成本低等优点,近20年来在不断发展和完善,引起大家的广泛关注。近红外光谱在700-900 mm范围内可以穿透一定深度的组织,组织内含氧血红蛋白、去氧血红蛋白对近红外光的吸收系数存在差异,经过传感器和计算机技术分析,得到组织的血氧参数。其测量参数为微动脉、微静脉和毛细血管中血液的血氧参数之加权平均,反应组织中的血氧参数,其中静脉血占主要地位,不同于普通脉搏式血氧监测仪的指端动脉血的血氧饱和度。基于近红外光谱技术的近红外组织血氧无创监测仪、功能性近红外光谱技术(f NIRS)、近红外光谱荧光技术等在临床医学,运动医学,神经生物学,认知科学,脑力疲劳,人机交互等新兴领域正发挥越来越重要作用。     

Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation

MazeSuite is a complete toolset to prepare, present and analyze navigational and spatial experiments¹. MazeSuite can be used to design and edit adapted virtual 3D environments, track a participants'' behavioral performance within the virtual environment and synchronize with external devices for physiological and neuroimaging measures, including electroencephalogram and eye tracking.Functional near-infrared spectroscopy (fNIR) is an optical brain imaging technique that enables continuous, noninvasive, and portable monitoring of changes in cerebral blood oxygenation related to human brain functions^2-7. Over the last decade fNIR is used to effectively monitor cognitive tasks such as attention, working memory and problem solving^7-11. fNIR can be implemented in the form of a wearable and minimally intrusive device; it has the capacity to monitor brain activity in ecologically valid environments. Cognitive functions assessed through task performance involve patterns of brain activation of the prefrontal cortex (PFC) that vary from the initial novel task performance, after practice and during retention¹². Using positron emission tomography (PET), Van Horn and colleagues found that regional cerebral blood flow was activated in the right frontal lobe during the encoding (i.e., initial naïve performance) of spatial navigation of virtual mazes while there was little to no activation of the frontal regions after practice and during retention tests. Furthermore, the effects of contextual interference, a learning phenomenon related to organization of practice, are evident when individuals acquire multiple tasks under different practice schedules^13,14. High contextual interference (random practice schedule) is created when the tasks to be learned are presented in a non-sequential, unpredictable order. Low contextual interference (blocked practice schedule) is created when the tasks to be learned are presented in a predictable order.Our goal here is twofold: first to illustrate the experimental protocol design process and the use of MazeSuite, and second, to demonstrate the setup and deployment of the fNIR brain activity monitoring system using Cognitive Optical Brain Imaging (COBI) Studio software¹⁵. To illustrate our goals, a subsample from a study is reported to show the use of both MazeSuite and COBI Studio in a single experiment. The study involves the assessment of cognitive activity of the PFC during the acquisition and learning of computer maze tasks for blocked and random orders. Two right-handed adults (one male, one female) performed 315 acquisition, 30 retention and 20 transfer trials across four days. Design, implementation, data acquisition and analysis phases of the study were explained with the intention to provide a guideline for future studies.     

油菜籽含油量傅里叶变换近红外模型的修正

为了提高近红外模型的精确度与准确度,需要定期地对原模型进行修正。常用的方法是在原模型中添加一些包含新信息的新样品,因此,样品的选择成为模型维护过程中的关键因素之一。以利用近红外光谱分析法测定油菜籽含油量为例,向原模型中添加不同偏差的样品建立独立的近红外模型,并设计相应的验证集对各模型的预测性能进行全面评价。结果表明:不同偏差的样品对模型预测性能的改善效果有差异,只有当新样品的偏差与原模型的预测偏差相匹配时,添加的新样品才能更有效地对原模型进行修正。依据偏差选择样品的新思路为近红外模型的维护提供了一条有效地途径。     

精神疲劳状态下脑组织血氧饱和度的近红外光谱分析

目的:研究精神疲劳状态下脑组织血氧饱和度的变化规律。方法:从某军校随机抽取25名被试,采用模拟飞行任务负荷构建精神疲劳模型,采用NASA-TLX量表评价模型。实验全程使用近红外光谱技术对被试脑组织血氧饱和度进行实时监测;实验前后分别对被试的作业绩效水平进行评估。结果:任务后NASA-TLX量表评分明显高于任务前(P0.01);任务前后作业绩效发生变化,反应能力测试的正确率下降(P0.01),错误率上升(P0.01);任务负荷后脑组织血氧饱和度相对于静息状态升高(P0.05)。结论:精神疲劳状态会影响被试的作业绩效。疲劳后脑组织血氧饱和度水平受被试动机以及代偿机制的影响高于静息水平。     

Changes in Self-Regulation-Related Prefrontal Activities in Eating Disorders: A Near Infrared Spectroscopy Study

Objective

The aim of this study is to clarify the symptomatology of the eating disorders examining the prefrontal function and activity associated with self-regulation among participants with or without eating disorders.

Methods

Ten patients with anorexia nervosa, fourteen with bulimia nervosa, and fourteen healthy control participants performed two cognitive tasks assessing self-regulatory functions, an auditorily distracted word fluency task and a rock-paper-scissors task under the measurements on prefrontal oxyhemoglobin concentration with near infrared spectroscopy. The psychiatric symptoms of patient groups were assessed with several questionnaires.

Results

Patients with bulimia nervosa showed decreased performances and prefrontal hyper activation patterns. Prefrontal activities showed a moderate negative correlation with task performances not in the patient groups but only in the healthy participants. The prefrontal activities of the patient groups showed positive correlations with some symptom scale aspects.

Conclusions

The decreased cognitive abilities and characteristic prefrontal activation patterns associated with self-regulatory functions were shown in patients with bulimia nervosa, which correlated with their symptoms. These findings suggest inefficient prefrontal self-regulatory function of bulimia nervosa that associate with its symptoms.     

近红外光谱法无创测量人体血红蛋白浓度

在选定的波长处(760 nm,850 nm)无创测量人体手指的漫反射光谱,利用修正的Lambert-Beer定律,实现了HbO2、Hb的绝对量估算,并由此求得血红蛋白浓度的结果。对16例志愿者进行了测量,全部男性受试者的相对误差在7.39%以下,相关系数为0.954;全部女性受试者的相对误差在7.26%以下,相关系数为0.969。     

Depth Sensitivity and Source-Detector Separations for Near Infrared Spectroscopy Based on the Colin27 Brain Template

Understanding the spatial and depth sensitivity of non-invasive near-infrared spectroscopy (NIRS) measurements to brain tissue–i.e., near-infrared neuromonitoring (NIN) – is essential for designing experiments as well as interpreting research findings. However, a thorough characterization of such sensitivity in realistic head models has remained unavailable. In this study, we conducted 3,555 Monte Carlo (MC) simulations to densely cover the scalp of a well-characterized, adult male template brain (Colin27). We sought to evaluate: (i) the spatial sensitivity profile of NIRS to brain tissue as a function of source-detector separation, (ii) the NIRS sensitivity to brain tissue as a function of depth in this realistic and complex head model, and (iii) the effect of NIRS instrument sensitivity on detecting brain activation. We found that increasing the source-detector (SD) separation from 20 to 65 mm provides monotonic increases in sensitivity to brain tissue. For every 10 mm increase in SD separation (up to ∼45 mm), sensitivity to gray matter increased an additional 4%. Our analyses also demonstrate that sensitivity in depth (S) decreases exponentially, with a “rule-of-thumb” formula S = 0.75*0.85^depth. Thus, while the depth sensitivity of NIRS is not strictly limited, NIN signals in adult humans are strongly biased towards the outermost 10–15 mm of intracranial space. These general results, along with the detailed quantitation of sensitivity estimates around the head, can provide detailed guidance for interpreting the likely sources of NIRS signals, as well as help NIRS investigators design and plan better NIRS experiments, head probes and instruments.     

人血清中胆固醇近红外光谱快速检测初步研究

以全自动生化分析仪测定结果为参考值,采用傅利叶变换近红外透射光谱技术,结合偏最小二乘法,建立人血清中胆固醇和甘油三酯的定标模型。利用内部交叉验证和自动优化功能对预测模型进行了优化,确定了最优建模参数。模型对人血清中胆固醇和甘油三酯定标样品集的预测值与参考值的相关系数r分别为0．9011、0．9593,预测校正标准误RMSECV分别为15．0mg／dL,21．6mg／dL。表明利用近红外光谱分析技术实现血清中胆固醇和甘油三酯快速检测是可行的。     

食用调和油中花生油含量的近红外光谱分析

采用偏最小二乘法(PLS)等方法建立了食用调和油中花生油含量定量分析的近红外光谱定标模型。采集食用调和油样品在4 000 cm-1~10 000 cm-1范围内的近红外漫反射光谱,光谱经一阶导数处理后,采用偏最小二乘法建立样品中花生油含量的定标模型,并用Leave-one-out内部交叉验证法对模型进行验证。模型相关系数为0.99961,校正均方根RMSEC为0.830%。比较不同光谱预处理方法对定标模型的影响,结果表明一阶导数Corr.coeff最好。采用不同的化学计量学方法建立的定标模型中以偏最小二乘回归法最理想。     

Near Infrared Spectroscopy Facilitates Rapid Identification of Both Young and Mature Amazonian Tree Species

Precise identification of plant species requires a high level of knowledge by taxonomists and presence of reproductive material. This represents a major limitation for those working with seedlings and juveniles, which differ morphologically from adults and do not bear reproductive structures. Near-infrared spectroscopy (FT-NIR) has previously been shown to be effective in species discrimination of adult plants, so if young and adults have a similar spectral signature, discriminant functions based on FT-NIR spectra of adults can be used to identify leaves from young plants. We tested this with a sample of 419 plants in 13 Amazonian species from the genera Protium and Crepidospermum (Burseraceae). We obtained 12 spectral readings per plant, from adaxial and abaxial surfaces of dried leaves, and compared the rate of correct predictions of species with discriminant functions for different combinations of readings. We showed that the best models for predicting species in early developmental stages are those containing spectral data from both young and adult plants (98% correct predictions of external samples), but even using only adult spectra it is still possible to attain good levels of identification of young. We obtained an average of 75% correct identifications of young plants by discriminant equations based only on adults, when the most informative wavelengths were selected. Most species were accurately predicted (75–100% correct identifications), and only three had poor predictions (27–60%). These results were obtained despite the fact that spectra of young individuals were distinct from those of adults when species were analyzed individually. We concluded that FT-NIR has a high potential in the identification of species even at different ontogenetic stages, and that young plants can be identified based on spectra of adults with reasonable confidence.     

Online monitoring of horseradish peroxidase structural changes by Near Infrared (NIR) Spectroscopy

The development of online monitoring techniques is of great relevance for understanding the structural changes of proteins under different conditions in order to maximize their catalytic activity. This study aimed to evaluate the potential of the NIR (near-infrared spectroscopy) technique for the monitoring of alterations of secondary and tertiary structures of Horseradish peroxidase (HRP), an oxidoreductase that has several applications in the industrial environment, food industry and bioremediation. The NIR associated to the multivariate calibration, through the PLS (partial least square) method allowed the construction of a robust model for the prediction of the analysis. The values of the correlation coefficient (R²), root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP) and root mean square error of cross validation (RMSECV) for secondary structure analysis using circular dichroism (CD) data as reference (actual values) were 0.9681, 0.647 (mdeg), 0.945 (mdeg), and 1.12 (mdeg), respectively. For tertiary structure analysis, fluorescence spectroscopy (FL) data were used as reference. R², RMSEC, RMSEP and RMSECV were, respectively 0.9999, 1.95 (a.u.), 2.09 (a.u.); and 2.19 (a.u.). NIR combined multivariate calibration showed promising results for sctructural changes monitoring of HRP.     

Prefrontal Cortex Haemodynamics and Affective Responses during Exercise: A Multi-Channel Near Infrared Spectroscopy Study

The dose-response effects of the intensity of exercise upon the potential regulation (through top-down processes) of affective (pleasure-displeasure) responses in the prefrontal cortex during an incremental exercise protocol have not been explored. This study examined the functional capacity of the prefrontal cortex (reflected by haemodynamics using near infrared spectroscopy) and affective responses during exercise at different intensities. Participants completed an incremental cycling exercise test to exhaustion. Changes (Δ) in oxygenation (O₂Hb), deoxygenation (HHb), blood volume (tHb) and haemoglobin difference (HbDiff) were measured from bilateral dorsal and ventral prefrontal areas. Affective responses were measured every minute during exercise. Data were extracted at intensities standardised to: below ventilatory threshold, at ventilatory threshold, respiratory compensation point and the end of exercise. During exercise at intensities from ventilatory threshold to respiratory compensation point, ΔO₂Hb, ΔHbDiff and ΔtHb were greater in mostly ventral than dorsal regions. From the respiratory compensation point to the end of exercise, ΔO₂Hb remained stable and ΔHbDiff declined in dorsal regions. As the intensity increased above the ventilatory threshold, inverse associations between affective responses and oxygenation in (a) all regions of the left hemisphere and (b) lateral (dorsal and ventral) regions followed by the midline (ventral) region in the right hemisphere were observed. Differential activation patterns occur within the prefrontal cortex and are associated with affective responses during cycling exercise.     

Gold Nanoring Arrays for Near Infrared Plasmonic Biosensing

Gold nanoring array surfaces that exhibit strong localized surface plasmon resonances (LSPR) at near infrared (NIR) wavelengths from 1.1 to 1.6 μm were used as highly sensitive real-time refractive index biosensors. Arrays of gold nanorings with tunable diameter, width, and spacing were created by the nanoscale electrodeposition of gold nanorings onto lithographically patterned nanohole array conductive surfaces over large areas (square centimeters). The bulk refractive index sensitivity of the gold nanoring arrays was determined to be up to 3,780 cm⁻¹/refractive index unit by monitoring shifts in the LSPR peak by FT-NIR transmittance spectroscopy measurements. As a first application, the surface polymerization reaction of dopamine to form polydopamine thin films on the nanoring sensor surface from aqueous solution was monitored with the real-time LSPR peak shift measurements. To demonstrate the utility of the gold nanoring arrays for LSPR biosensing, the hybridization adsorption of DNA-functionalized gold nanoparticles onto complementary DNA-functionalized gold nanoring arrays was monitored. The adsorption of DNA-modified gold nanoparticles onto nanoring arrays modified with mixed DNA monolayers that contained only 0.5 % complementary DNA was also detected; this relative surface coverage corresponds to the detection of DNA by hybridization adsorption from a 50 pM solution.