scholarly journals Consciousness & Brain Functional Complexity in Propofol Anaesthesia

2019 ◽  
Author(s):  
TF Varley ◽  
A Luppi ◽  
I Pappas ◽  
L Naci ◽  
R Adapa ◽  
...  
Keyword(s):  
Complex System ◽  
Principal Component Analysis ◽  
Anaesthetic Agent ◽  
Principal Component ◽  
Topological Dimension ◽  
Functional Complexity ◽  
Temporal Measures ◽  
Process Complexity ◽  
The Brain ◽  
Higher Sensitivity

AbstractThe brain is possibly the most complex system known to mankind, and its complexity has been called upon to explain the emergence of consciousness. However, complexity can take many forms: here, we investigate measures of algorithmic and process complexity in both the temporal and topological dimension, testing them on functional MRI data obtained from individuals undergoing various levels of sedation with the anaesthetic agent propofol, in two separate datasets. We demonstrate that the various measures are differently able to discriminate between levels of sedation, with temporal measures showing higher sensitivity. Further, we show that all measures are strongly related to a single underlying construct explaining most of the variance, as assessed by Principal Component Analysis, which we interpret as a measure of overall complexity of our data. This overall complexity was also able to discriminate between levels of sedation, supporting the hypothesis that consciousness is related to complexity - independent of how the latter is measured.

scholarly journals To Weight or Not to Weight, That Is the Question: The Design of a Composite Indicator of Landscape Fragmentation

2021 ◽  
Vol 11 (7) ◽  
pp. 3208
Author(s):  
Andrea De Montis ◽  
Vittorio Serra ◽  
Giovanna Calia ◽  
Daniele Trogu ◽  
Antonio Ledda
Keyword(s):  
Principal Component Analysis ◽  
Geometric Mean ◽  
Composite Index ◽  
Weighted Average ◽  
Principal Component ◽  
Expert Judgment ◽  
Landscape Fragmentation ◽  
Composite Indicator ◽  
Per Se ◽  
Higher Sensitivity

Composite indicators (CIs), i.e., combinations of many indicators in a unique synthetizing measure, are useful for disentangling multisector phenomena. Prominent questions concern indicators’ weighting, which implies time-consuming activities and should be properly justified. Landscape fragmentation (LF), the subdivision of habitats in smaller and more isolated patches, has been studied through the composite index of landscape fragmentation (CILF). It was originally proposed by us as an unweighted combination of three LF indicators for the study of the phenomenon in Sardinia, Italy. In this paper, we aim at presenting a weighted release of the CILF and at developing the Hamletian question of whether weighting is worthwhile or not. We focus on the sensitivity of the composite to different algorithms combining three weighting patterns (equalization, extraction by principal component analysis, and expert judgment) and three indicators aggregation rules (weighted average mean, weighted geometric mean, and weighted generalized geometric mean). The exercise provides the reader with meaningful results. Higher sensitivity values signal that the effort of weighting leads to more informative composites. Otherwise, high robustness does not mean that weighting was not worthwhile. Weighting per se can be beneficial for more acceptable and viable decisional processes.

scholarly journals On the brain structure heterogeneity of autism: Parsing out acquisition site effects with significance-weighted principal component analysis

2016 ◽  
Vol 38 (3) ◽  
pp. 1208-1223 ◽  
Author(s):  
Francisco Jesús Martinez-Murcia ◽  
Meng-Chuan Lai ◽  
Juan Manuel Górriz ◽  
Javier Ramírez ◽  
Adam M. H. Young ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Brain Structure ◽  
Site Effects ◽  
Principal Component ◽  
Component Analysis ◽  
Weighted Principal Component ◽  
Structure Heterogeneity ◽  
The Brain

scholarly journals Categorization of Chinese Dry-Cured Ham Based on Three Sticks’ Method by Multiple Sensory Technologies

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Dong Xia ◽  
Dan Ni Zhang ◽  
Shao Ting Gao ◽  
Le Chen ◽  
Nan Li ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Sensory Evaluation ◽  
Electronic Nose ◽  
Function Analysis ◽  
Principal Component ◽  
Absorption Method ◽  
Dry Cured Ham ◽  
And Cluster Analysis ◽  
Higher Sensitivity

Odor profiles of three grades of Jinhua, Xuanwei, and Rugao dry-cured hams were analyzed and distinguished by both the electronic nose and the sensory evaluation. The odor was absorbed by bamboo sticks, which is the most traditional absorption method to classify different ham grades. Then data from electronic nose was analyzed by discriminant function analysis (DFA) and cluster analysis (CA), compared with that from sensory evaluation by principal component analysis (PCA). Results showed that different grades of Jinhua, Xuanwei, and Rugao dry-cured hams could be distinguished effectively by the DFA results of electronic nose. However, sensory evaluation could not perform as well as electronic nose. It was demonstrated that intelligent sensory technology has higher sensitivity and reliability in classifying producing regions and grades of dry-cured ham.

scholarly journals A Novel Method of Early Diagnosis of Alzheimer’s Disease Based on EEG Signals

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Dhiya Al-Jumeily ◽  
Shamaila Iram ◽  
Francois-Benois Vialatte ◽  
Paul Fergus ◽  
Abir Hussain
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Principal Component Analysis ◽  
Healthy Subjects ◽  
Early Stage ◽  
Measurement Techniques ◽  
Principal Component ◽  
Component Analysis ◽  
Neural Synchrony ◽  
The Brain

Studies have reported that electroencephalogram signals in Alzheimer’s disease patients usually have less synchronization than those of healthy subjects. Changes in electroencephalogram signals start at early stage but, clinically, these changes are not easily detected. To detect this perturbation, three neural synchrony measurement techniques: phase synchrony, magnitude squared coherence, and cross correlation are applied to three different databases of mild Alzheimer’s disease patients and healthy subjects. We have compared the right and left temporal lobes of the brain with the rest of the brain areas (frontal, central, and occipital) as temporal regions are relatively the first ones to be affected by Alzheimer’s disease. Moreover, electroencephalogram signals are further classified into five different frequency bands (delta, theta, alpha beta, and gamma) because each frequency band has its own physiological significance in terms of signal evaluation. A new approach using principal component analysis before applying neural synchrony measurement techniques has been presented and compared with Average technique. The simulation results indicated that applying principal component analysis before synchrony measurement techniques shows significantly better results as compared to the lateral one. At the end, all the aforementioned techniques are assessed by a statistical test (Mann-WhitneyUtest) to compare the results.

Analog Circuits Test by Using Principal Component Analysis

2013 ◽  
Vol 278-280 ◽  
pp. 709-713
Author(s):  
Chao Jie Zhang ◽  
Guang Hui Chang
Keyword(s):  
Principal Component Analysis ◽  
Analog Circuits ◽  
Principal Component ◽  
Component Analysis ◽  
Test Methods ◽  
Component Model ◽  
Suitable Candidate ◽  
Principal Component Model ◽  
Other Test Methods ◽  
Higher Sensitivity

In view of the difficulties caused by determining threshold for analog circuits test, a method based on principal component analysis (PCA) of node voltages was proposed to overcome these difficulties. At first, the principal component model of fault-free circuits was constructed. Then the circuits-under-test was compared with the principal component model to calculate the statistic for fault detection. The proposed method was used to test the output signal amplifying circuit, which is used in the ultrasonic liquid sensor. The testing results show that the PCA based method has a higher sensitivity than other test methods. And the proposed method can overcome the difficulties in determining threshold by the expert’s empirical knowledge. These make it a suitable candidate for analog circuits test.

scholarly journals Characterization of Postprandial Effects on CSF Metabolomics: A Pilot Study with Parallel Comparison to Plasma

Metabolites ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 185 ◽  
Author(s):  
Kosuke Saito ◽  
Kotaro Hattori ◽  
Tomohiro Andou ◽  
Yoshinori Satomi ◽  
Masamitsu Gotou ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Principal Component Analysis ◽  
Cerebrospinal Fluid ◽  
Healthy Subjects ◽  
Principal Component ◽  
Blood Metabolites ◽  
Interindividual Variations ◽  
The Brain ◽  
Time Point

Cerebrospinal fluid (CSF) metabolites reflect biochemical diffusion/export from the brain and possibly serve as biomarkers related to brain disease severity, pathophysiology, and therapeutic efficacy/toxicity. Metabolomic studies using blood matrices have demonstrated interindividual and preanalytical variation of blood metabolites, whereas those of CSF metabolites remain unclear. In this study, we aimed to delineate the postprandial effects on CSF metabolites because fasting of patients with brain-related disorders is challenging. We collected pre- and postprandial (1.5, 3, and 6 h) plasma and CSF from nine healthy subjects. Using a mass-spectrometry-based global metabolomics approach, 150 and 130 hydrophilic metabolites and 263 and 340 lipids were detected in CSF and plasma, respectively. Principal component analysis of CSF hydrophilic metabolites and lipids primarily classified individual subjects at any time point, suggesting that the postprandial effects had a lower impact than interindividual variations on CSF metabolites. Individually, less than 10% of the CSF metabolites were putatively altered by postprandial effects (with either significant differences or over 2-fold changes, but not both) at any time point. Thus, global CSF metabolite levels are not directly associated with food intake, and except for several putatively altered CSF metabolites, postprandial effects are not a major concern when applying CSF metabolomics to screen biomarkers.

Topographic Structure of Alpha Wave Activity by Means of Principal Component Analysis

1993 ◽  
Vol 5 (3) ◽  
pp. 209-213
Author(s):  
Yoichi Tsuji ◽  
◽  
Hidekazu Takase ◽  
Kazuyuki Nagasawa ◽  
Misao Itoi
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Principal Component ◽  
Component Analysis ◽  
Wave Activity ◽  
Alpha Activity ◽  
Analysis Method ◽  
Alpha Wave ◽  
The Brain ◽  
Topographic Structure

In order to find out the topographic structure in alpha wave activity, the principal component analysis method was applied to 17 channel scalp EEGs. Three kind of topographic structures were obtained from the factor loadings of principal components as follows: frontal-occipital, centoral or lateral activity. These structures may be related to the mechanism of alpha activity on the brain.

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