Measurement of Neocortical Responses to Odors using Optical Imaging

2012 ◽  
pp. 370-383
Author(s):  
Akio Nakamura
Keyword(s):  
Near Infrared ◽  
Temporal Cortex ◽  
Test Solution ◽  
Artificial Sweetener ◽  
Sugar Solution ◽  
Important Indicator ◽  
Evaluation Period ◽  
Cortical Responses ◽  
Cross Adaptation ◽  
Self Adaptation

Using multi-channel near-infrared spectroscopy, the authors sought to monitor cortical activity during the sensory evaluation period to evaluate the effect of flavorings on taste caused by central integration of olfactory and gustatory modalities. They noted that the neocortical response to a test solution showed adaptation by the conditional sugar solution, which was administered 60 seconds before the test solution. Sugar-sugar self adaptation was greater than sugar-artificial sweetener cross adaptation recorded at specific regions of the frontal and temporal cortex. The magnitude of sugar-flavored artificial sweetener cross adaptation tended to approach that of sugar-sugar self adaptation. Therefore, the similarity of the adaptation of cortical responses might be an important indicator in the screening of effective flavorings in order to improve taste.

scholarly journals Near-Infrared Spectroscopy Coupled Chemometric Algorithms for Rapid Origin Identification and Lipid Content Detection of Pinus Koraiensis Seeds

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4905
Author(s):  
Hongbo Li ◽  
Dapeng Jiang ◽  
Jun Cao ◽  
Dongyan Zhang
Keyword(s):  
Lipid Content ◽  
Near Infrared ◽  
Prediction Models ◽  
Principal Component ◽  
Two Dimensions ◽  
Breeding Value ◽  
Pinus Koraiensis ◽  
Small Scale ◽  
Important Indicator ◽  
Chemometric Algorithms

Lipid content is an important indicator of the edible and breeding value of Pinus koraiensis seeds. Difference in origin will affect the lipid content of the inner kernel, and neither can be judged by appearance or morphology. Traditional chemical methods are small-scale, time-consuming, labor-intensive, costly, and laboratory-dependent. In this study, near-infrared (NIR) spectroscopy combined with chemometrics was used to identify the origin and lipid content of P. koraiensis seeds. Principal component analysis (PCA), wavelet transformation (WT), Monte Carlo (MC), and uninformative variable elimination (UVE) methods were used to process spectral data and the prediction models were established with partial least-squares (PLS). Models were evaluated by R2 for calibration and prediction sets, root mean standard error of cross-validation (RMSECV), and root mean square error of prediction (RMSEP). Two dimensions of input data produced a faster and more accurate PLS model. The accuracy of the calibration and prediction sets was 98.75% and 97.50%, respectively. When the Donoho Thresholding wavelet filter ‘bior4.4’ was selected, the WT–MC–UVE–PLS regression model had the best predictions. The R2 for the calibration and prediction sets was 0.9485 and 0.9369, and the RMSECV and RMSEP were 0.0098 and 0.0390, respectively. NIR technology combined with chemometric algorithms can be used to characterize P. koraiensis seeds.

SPXY Sample Classification Method and Successive Projections Algorithm Combined with Near-Infrared Spectroscopy for the Determination of Total Sugar Content of Southern Xinjiang Jujube

2014 ◽  
Vol 1030-1032 ◽  
pp. 352-356 ◽  
Author(s):  
Yun Fa Peng ◽  
Hua Ping Luo ◽  
Xue Ning Luo ◽  
Ying Zhan
Keyword(s):  
Near Infrared ◽  
Sugar Content ◽  
Total Sugar ◽  
Internal Quality ◽  
Successive Projections Algorithm ◽  
Full Spectrum ◽  
Important Indicator ◽  
Characteristic Wavelength ◽  
Successive Projections ◽  
Southern Xinjiang

Sugar degree is an important indicator of red jujube internal quality. The main objectives of this paper are to minimize the collinearity between spectral variables, to find the variable groups which containing the lowest redundant information,and establish the model with better robustness by means of fewer variables. This paper uses SPXY (sample set partitioning based on joint x-y distances) to divide calibrating samples,and applies successive projections algorithm (SPA) to select the near-infrared spectral characteristic variable of southern Xinjiang jujube total sugar. To further establish the partial least squares (PLS) model with selected variables. The root mean square error of prediction (RMSEP) of the model is 2.8804. The correlation coefficient of prediction r is 0.9005.To compare the established PLS model results between SPA selecting variables and full spectrum. The results showed that: Firstly, the divided calibrating samples is reasonable in SPXY way.Secondly, SPA optimizes 9 variables of the full spectrum 1557 variables,and prediction effect of the established PLS model is better than the full spectrum PLS model.Finally,SPA can effectively select characteristic wavelength of component under test.

scholarly journals Mapping Cortical Responses to Somatosensory Stimuli in Human Infants with Simultaneous Near-Infrared Spectroscopy and Event-Related Potential Recording

eNeuro ◽  
2016 ◽  
Vol 3 (2) ◽  
pp. ENEURO.0026-16.2016 ◽  
Author(s):  
Madeleine Verriotis ◽  
Lorenzo Fabrizi ◽  
Amy Lee ◽  
Robert J. Cooper ◽  
Maria Fitzgerald ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Event Related Potential ◽  
Human Infants ◽  
Cortical Responses ◽  
Potential Recording ◽  
Somatosensory Stimuli

Face Pareidolia Recruits Mechanisms for Detecting Human Social Attention

2020 ◽  
Vol 31 (8) ◽  
pp. 1001-1012 ◽  
Author(s):  
Colin J. Palmer ◽  
Colin W. G. Clifford
Keyword(s):  
Sensory Input ◽  
Temporal Cortex ◽  
Social Attention ◽  
Systematic Bias ◽  
Sensory Cues ◽  
Everyday Objects ◽  
Specific Direction ◽  
Cross Adaptation ◽  
Human Faces ◽  
Perceptual Phenomenon

Face pareidolia is the phenomenon of seeing facelike structures in everyday objects. Here, we tested the hypothesis that face pareidolia, rather than being limited to a cognitive or mnemonic association, reflects the activation of visual mechanisms that typically process human faces. We focused on sensory cues to social attention, which engage cell populations in temporal cortex that are susceptible to habituation effects. Repeated exposure to “pareidolia faces” that appear to have a specific direction of attention causes a systematic bias in the perception of where human faces are looking, indicating that overlapping sensory mechanisms are recruited when we view human faces and when we experience face pareidolia. These cross-adaptation effects are significantly reduced when pareidolia is abolished by removing facelike features from the objects. These results indicate that face pareidolia is essentially a perceptual phenomenon, occurring when sensory input is processed by visual mechanisms that have evolved to extract specific social content from human faces.

scholarly journals Identification of Coal Geographical Origin Using Near Infrared Sensor Based on Broad Learning

2019 ◽  
Vol 9 (6) ◽  
pp. 1111 ◽  
Author(s):  
Meng Lei ◽  
Zhongyu Rao ◽  
Ming Li ◽  
Xinhui Yu ◽  
Liang Zou
Keyword(s):  
Near Infrared ◽  
Geographical Origin ◽  
Learning Algorithm ◽  
Nir Spectroscopy ◽  
Chemical Compositions ◽  
Important Indicator ◽  
Quantitative And Qualitative Research ◽  
Quality Grading ◽  
Improved Model ◽  
Origin Identification

Geographical origin, an important indicator of the chemical composition and quality grading, is one essential factor that should be taken into account in evaluating coal quality. However, traditional coal origin identification methods based on chemistry experiments are not only time consuming and labour intensive, but also costly. Near-Infrared (NIR) spectroscopy is an effective and efficient way to measure the chemical compositions of samples and has demonstrated excellent performance in various fields of quantitative and qualitative research. In this study, we employ NIR spectroscopy to identify coal origin. Considering the fact that the NIR spectra of coal samples always contain a large amount of redundant information and the number of samples is small, the broad learning algorithm is utilized here as the modelling system to classify the coal geographical origin. In addition, the particle swarm optimization algorithm is introduced to improve the structure of the Broad Learning (BL) model. We compare the improved model with the other five multivariate classification methods on a dataset with 243 coal samples collected from five countries. The experimental results indicate that the improved BL model can achieve the highest overall accuracy of 97.05%. The results obtained in this study suggest that the NIR technique combined with machine learning methods has significant potential for further development of coal geographical origin identification systems.

scholarly journals Cross-Correlation of Motor Activity Signals from dc-Magnetoencephalography, Near-Infrared Spectroscopy, and Electromyography

2010 ◽  
Vol 2010 ◽  
pp. 1-8 ◽  
Author(s):  
Tilmann H. Sander ◽  
Stefanie Leistner ◽  
Heidrun Wabnitz ◽  
Bruno-Marcel Mackert ◽  
Rainer Macdonald ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Cross Correlation ◽  
Near Infrared ◽  
Vascular Response ◽  
Neuronal Responses ◽  
Finger Movements ◽  
Time Resolved ◽  
Cortical Responses ◽  
Movement Sequence

Neuronal and vascular responses due to finger movements were synchronously measured using dc-magnetoencephalography (dcMEG) and time-resolved near-infrared spectroscopy (trNIRS). The finger movements were monitored with electromyography (EMG). Cortical responses related to the finger movement sequence were extracted by independent component analysis from both the dcMEG and the trNIRS data. The temporal relations between EMG rate, dcMEG, and trNIRS responses were assessed pairwise using the cross-correlation function (CCF), which does not require epoch averaging. A positive lag on a scale of seconds was found for the maximum of the CCF between dcMEG and trNIRS. A zero lag is observed for the CCF between dcMEG and EMG. Additionally this CCF exhibits oscillations at the frequency of individual finger movements. These findings show that the dcMEG with a bandwidth up to 8 Hz records both slow and faster neuronal responses, whereas the vascular response is confirmed to change on a scale of seconds.

A Comparison of Self-Adaptation and Cross-Adaptation to Odorants Presented Singly and in Mixtures

Perception ◽  
1993 ◽  
Vol 22 (1) ◽  
pp. 103-111 ◽  
Author(s):  
Birgitta Berglund ◽  
Trygg Engen
Keyword(s):  
Hydrogen Sulfide ◽  
Magnitude Estimation ◽  
Dimethyl Disulfide ◽  
The Other ◽  
Prior Exposure ◽  
Perceived Intensity ◽  
Cross Adaptation ◽  
Contrast Exposure ◽  
Self Adaptation ◽  
Olfactory Adaptation

Fifteen subjects made 450 judgments each by the method of magnitude estimation of dimethyl disulfide and hydrogen sulfide after prior exposure to various mixtures of them. Exposure to the same odorant clearly affected the perceived intensity of it (self-adaptation). By contrast, exposure to the other odorant showed at best a small effect (cross-adaptation). Consistent with this, adaptation to a mixture of the test odorant and another odorant is proportional to the amount of the test odorant in the mixture, and does not exceed that of self-adaptation. These results indicate that olfactory adaptation is specific and that the sense of smell is more robust than generally assumed.

Sign in / Sign up

Export Citation Format

Share Document