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PubMed1990

[A dynamic study of the impulse processes in human cerebral neurons by using the principal-component method].

Evoked activity (EA) of single neurons to verbal (or sensory) stimuli was recorded by microelectrodes in the nucleus reticularis and some other thalamic nuclei of the human brain during stereotaxic operations. An approach is considered which results from the assumptions of the cumulativeness and variability of the EA pattern and is based on the principal component analysis and peristimulus covariation matrices. Application of these methods for estimating unitary responses showed their efficiency for the quantitative analysis of the dynamic structure and interneuronal relations within the EA patterns during the performance of voluntary motor acts.

Brain↗
PubMed2001

Principal component analysis and cluster analysis for measuring the local organisation of human atrial fibrillation.

The distribution of atrial electrogram types has been proposed to characterise human atrial fibrillation. The aim of this study was to provide computer procedures for evaluating the local organisation of intracardiac recordings during AF as an alternative to off-line manual classification. Principal component analysis (PCA) reduced the data set to a few representative activations, and cluster analysis (CA) measured the average dissimilarity between consecutive activations of an intracardiac signal. The data set consisted of 106 bipolar signals recorded on 11 patients during electrophysiological studies for catheter ablation. Performances of PCA and CA in distinguishing between organised (type I) and disorganised (type II/III, Wells criteria) were assessed, in comparison with manual reading, by evaluating the predictive parameters of the classification analysis. Both methods gave high accuracy (92% for PCA and 89% for CA), confirming the feasibility of on-line characterisation of AF. Sensitivity was lower than specificity (81% against 98% for PCA, and 77% against 97% for CA), with seven out of eight misclassifications of PCA in common with CA. Differences between manual and computer analysis may be related to the higher resolution of PCA and CA in the measurement of the organisation of atrial activations. These procedures are suitable for providing automatic (by CA) or semi-automatic (by PCA) measures of the extent of local organisation of AF in the pre-ablation treatment phase.

Atrial Fibrillation↗
PubMed2003

Dual relationship activities: principal component analysis of counselors' attitudes.

The British Columbian Members of the Canadian Guidance and Counselling Association were surveyed to explore their attitudes regarding dual relationships. Of 529 deliverable surveys, 206 usable returns yielded a response rate of 39%. The survey instrument collected data regarding respondents' characteristics and ethicality ratings of 39 dual relationship activity items. An exploratory principal components analysis was performed on responses, resulting in a 4-factor equation, which accounted for 44% of the total variance. The results suggest that, although conceptual considerations of dual relationship typology do underlay the resultant factors, the relative ethicality of each item is also influential.

Adult↗
PubMed2000

Principal components analysis of distal humeral shape in Pliocene to recent African hominids: the contribution of geometric morphometrics.

The shape of the distal humerus in Homo, Pan (P. paniscus and P. troglodytes), Gorilla, and six australopithecines is compared using a geometric approach (Procrustes superimposition of landmarks). Fourteen landmarks are defined on the humerus in a two-dimensional space. Principal components analysis (PCA) is performed on all superimposed coordinates. I have chosen to discuss the precise place of KNM-KP 271 variously assigned to Australopithecus anamensis, Homo sp., or Praeanthropus africanus, in comparison with a sample of australopithecines. AL 288-1, AL 137-48 (Hadar), STW 431 (Sterkfontein), and TM 1517 (Kromdraai) are commonly attributed to Australopithecus afarensis (the two former), Australopithecus africanus, and Paranthropus robustus, respectively, while the taxonomic place of KNM-ER 739 (Homo or Paranthropus?) is not yet clearly defined. The analysis does not emphasize a particular affinity between KNM-KP 271 and modern Homo, nor with A. afarensis, as previously demonstrated (Lague and Jungers [1996]

Animals↗
PubMed1997

Nonlinear principal components analysis of neuronal spike train data.

Many recent approaches to decoding neural spike trains depend critically on the assumption that for low-pass filtered spike trains, the temporal structure is optimally represented by a small number of linear projections onto the data. We therefore tested this assumption of linearity by comparing a linear factor analysis technique (principal components analysis) with a nonlinear neural network based method. It is first shown that the nonlinear technique can reliably identify a neuronally plausible nonlinearity in synthetic spike trains. However, when applied to the outputs from primary visual cortical neurons, this method shows no evidence for significant temporal nonlinearities. The implications of this are discussed.

Action Potentials↗
PubMed2000

Mapping quantitative trait loci for principal components of bone measurements and osteochondrosis scores in a wild boar x large white intercross.

Data on osteochondrosis and femur dimensions from 195 F2 pigs from a wild boar x Large White intercross were analysed with the aim of detecting quantitative trait loci (QTLs) for normal and disturbed bone formation. The information from numerous recorded traits was summarized by principal component analysis and analysed by least-squares interval mapping. An increase in the proportion of wild boar alleles across the genome increased length versus width of femur and reduced the prevalence of osteochondrosis. The presence of QTLs with an impact on femur dimensions was indicated on chromosomes 2, 4, 16 and 17 and on osteochondrosis on chromosomes 5, 13 and 15. A substantial effect of the chromosome 5 QTL calls for further studies within commercial populations to evaluate whether marker-assisted selection could be used to reduce the prevalence of osteochondrosis.

Alleles↗
PubMed1996

Quantification of intensity variations in functional MR images using rotated principal components.

In functional MRI (fMRI), the changes in cerebral haemodynamics related to stimulated neural brain activity are measured using standard clinical MR equipment. Small intensity variations in fMRI data have to be detected and distinguished from non-neural effects by careful image analysis. Based on multivariate statistics we describe an algorithm involving oblique rotation of the most significant principal components for an estimation of the temporal and spatial distribution of the stimulated neural activity over the whole image matrix. This algorithm takes advantage of strong local signal variations. A mathematical phantom was designed to generate simulated data for the evaluation of the method. In simulation experiments, the potential of the method to quantify small intensity changes, especially when processing data sets containing multiple sources of signal variations, was demonstrated. In vivo fMRI data collected in both visual and motor stimulation experiments were analysed, showing a proper location of the activated cortical regions within well known neural centres and an accurate extraction of the activation time profile. The suggested method yields accurate absolute quantification of in vivo brain activity without the need of extensive prior knowledge and user interaction.

Algorithms↗
PubMed1998

Action potential classifiers: a functional comparison of template matching, principal components analysis and an artificial neural network.

Multiunit neural activity occurs often in electrophysiological studies when utilizing extracellular electrodes. In order to estimate the activity of the individual neurons each action potential in the recording must be classified to its neuron of origin. This paper compares the accuracy of two traditional methods of action potential classification--template matching and principal components--against the performance of an artificial neural network (ANN). Both traditional methods use averages of action potential shapes to form their corresponding classifiers while the artificial neural network 'learns' a nonlinear relationship between a set of prototype action potentials and assigned classes. The set of prototypic action potentials and the assigned classes is termed the training set. The training set contained action potentials from each class which exhibited the full range of amplitude variability. The ANN provided better classification results and was more robust in analysis of across-animal data sets than either of the traditional action potential classification methods.

Action Potentials↗
PubMed1993

Hydroxy-fatty acid profiles of Legionella species: diagnostic usefulness assessed by principal component analysis.

Twenty-nine species (76 strains) of members of the genus Legionella were analyzed for their cellular hydroxylated fatty acids (OH-FAs). The individual patterns were unusually complex and included both monohydroxylated and dihydroxylated chains of unbranched or branched (iso and anteiso) types. Comparison of the strain profiles by SIMCA (Soft Independent Modelling of Class Analogy) principal component analysis revealed four main groups. Group 1 included Legionella pneumophila plus L. israelensis strains, and group 2 included L. micdadei and L. maceacherneii strains. These two closely related groups were characterized by the occurrence of di-OH-FAs and differed mainly in the amounts of 3-OH-a21:0, 3-OH-n21:0, 3-OH-n22:0, and 3-OH-a23:0. Group 3 (13 species) was distinguished by i14:0 at less than 3%, 3-OH-3-OH-n14:0 at greater than 5%, 3-OH-n15:0 at greater than 2%, and minute amounts of OH-FAs with chains longer than 21:0. Group 4 (12 species) was heterogeneous. Its main characteristics were the presence of 3-OH-n12:0 and 3-OH-n13:0, 3-OH-i14:0 at greater than 5%, as well as significant amounts of 3-OH-a21:0 and 3-OH-n21:0. The groupings obtained by OH-FA profiles were found to reflect DNA-DNA homology groupings reasonably well, and the profiles appear to be useful for differentiation of Legionella species.

DNA, Bacterial↗
PubMedDate not supplied

Principal component analysis. A factor analytical technique for the determination of interobserver variation in histomorphologic tumor grading.

The insufficient interobserver reproducibility limits the practical use of histomorphological tumor grading in daily routine pathology. In this study, the reasons for the quite low rates of agreement between different observers have been investigated by the application of a factor analytical technique, i.e. principal component analysis with varimax rotation, on a tumor grading system. Grading results from 44 cases of G1 and G2 giant cell tumors of the bone (GCT), graded by three different observers according to the five criteria of Jaffe, were taken as an example. It could be proven that the single criteria were used in an observer-specific way. Two criteria, for example, which are scored highly correlated by one observer, may be used independently by another. The resulting observer-specific different recognition patterns may provide an explanation for their quite different grading results, which were identical in only 48.6% to 54.1% (mean: 50.9%) of the cases. No correlation of GCT grading with recurrence was found in 31 cases which had been treated by intralesional surgery.

Adult↗
PubMed1987

Principal components analysis of physical growth in savannah baboons.

Morphometric data collected from 118 male and 169 female savannah baboons (Papio cynocephalus anubis) aged between birth and 5.5 years were analyzed to describe the morphology and physical growth of this species. Measurements included weight, crown-rump length, triceps circumference, and skinfolds at the neck, subscapular, suprailiac, and triceps anatomical sites. Principal components analyses were applied to the data to provide multivariate assessments of morphological patterning among the variables. These analyses resulted in the extraction of two unrotated orthogonal components that accounted for 88% of the overall sample variation. The first component accounted for 77% of the variation and represents an axis of overall body size. The second component represents an axis of shape variation that contrasts body size with fat patterning, and was interpreted as a measure of body leanness. Individual component scores were computed for determining age, gender, and age-by-gender interaction effects. Both components were found to be age dependent for both genders. Males and females shared similar age patterning along the two components; however, gender differences did occur in patterning along the two components; however, gender differences did occur in respect to leanness. The multivariate measure of overall body size increased for both genders similarly with advancing age. Age patterning along the leanness component was described as a decrease from birth to 1 year, followed by an increase in leanness in older ages. Females had a delayed and significantly less intense increase in leanness relative to males.

Aging↗
PubMed1994

Automatic analysis of sleep using two parameters based on principal component analysis of electroencephalography spectral data.

A computer program for the analysis of a sleep electroencephalogram (EEG) is presented. The method relies on two steps. First, a spectral analysis is performed for signals recorded from one or more electrode locations. Then, two EEG parameters are obtained by storing the spectral activity in a multidimensional space, whose dimension is reduced using principal component analysis (PCA) techniques. The main advantage of these parameters is in describing the process of sleep on a continuous scale as a function of time. Validation of the method was performed with the data collected from 16 subjects (8 young volunteers and 8 elderly insomniacs). Results showed that the parameters correlate highly with the hypnograms established by conventional visual scoring. This signal parametrisation, however, offers more information regarding the time course of sleep, since small variations within individual sleep stages as well as smooth transitions between stages are assessed. Finally, the concurrent use of both parameters provides an original way of considering sleep as a dynamic process evolving cyclically in a single plane.

Adult↗
PubMed1996

Effects of habitual physical exercise on physiological age in men aged 20-85 years as estimated using principal component analysis.

A population of 221 healthy adult men (aged 20-85 years) was studied to determine whether those who exercised regularly were in good biological condition, and also whether those who were in a state of high physical fitness were in a good state biologically, in terms of physiological age (PA) and physical fitness age (FA) as estimated by principal component analysis. A group of 17 physiological function tests and 5 physical fitness tests were employed to estimate PA and FA, respectively. The results of this study indicated that those who maintained high physical fitness at all age decade groups from 20 to 79 years had a trend towards maintaining a relatively lower PA (physiologically younger). Mean PA and FA of the trained group were younger by 4.7 and 7.3 years, respectively than those of the untrained group. In addition, the slope of regression line of PA on chronological age was more gentle in the trained group than that in the untrained group. These results would suggest that those who are in a state of high physical fitness maintain a relatively good physiological condition, and that regular physical exercise may delay physiological changes normally seen with aging, and consequently may increase the life span.

Adult↗
PubMed1997

Infrared spectroscopy of normal and abnormal cervical smears: evaluation by principal component analysis.

Fourier-transform infrared (FT-IR) spectra of malignant and dysplastic cervical scrapings were abnormal, as first described in our study of a limited number of samples, where the spectra were evaluated by visual inspection and peak intensity ratios. We have expanded our study to evaluate more cervical conditions, and to analyze the spectra by a chemometric approach (principal component analysis [PCA]). Cervical samples from 436 females were evaluated by FT-IR and Papanicolaou testing; 40/436 spectra were nonanalyzable. The remaining were as follows: normal, 174; malignant, 19; dysplasia, 8; atypia, 113; atrophy, 19; inflammatory, 47; bloody smear, 12; hypocellular, 4. PCA analysis followed by chi2 test revealed that statistically significant frequencies of being predicted malignant by FT-IR were associated with samples diagnosed as malignant (P < 0.0001), and also those diagnosed as "atrophy" (P < 0.001), "atypical with bloody smear" (P < 0.05), "atypical with atrophic pattern" (P < 0.05), and "dysplasia" (P < 0.05). Based on these findings, for the diagnosis of cervical cancer by FT-IR, as defined here, the sensitivity is 79%, the specificity is 77%, the positive predictive value is 15%, and the negative predictive value is 98.6%. Our findings (a) demonstrate the application of a chemometric approach to the study of cervical FT-IR spectra; (b) assess its potential diagnostic role; (c) suggest that atrophic and neoplastic samples share structural features; and (d) suggest that blood may interfere with such spectroscopic evaluation. These findings warrant further evaluation of FT- IR spectroscopy in cervical and other malignancies.

Cervix Uteri↗
PubMed1997

Obstructive sleep apnoea syndrome: results and conclusions of a principal component analysis.

A cephalometric analysis according to Hasund, supplemented by special obstructive sleep apnoea syndrome (OSAS) parameters, was performed on 169 patients who had been referred from the sleep laboratory. Statistical analysis showed a correlation between specific cephalometric landmarks including posterior airway space (PAS), a soft palate length, hyoid position and posterior growth development of the mandible and OSAS severity. A principal component analysis differentiated between four subgroups of OSAS patients: (1) orthognathic obese subjects; (2) patients with a long soft palate and low-positioned hyoid; (3) retrognathic patients with narrow PAS; and (4) prognathic ones. Lateral cephalometry is an important contribution to OSAS diagnostics and oral and maxillofacial therapy procedures.

Adult↗
PubMed1990

Update on the parallel analysis criterion for determining the number of principal components.

Recent developments in parallel analysis with unities in the diagonal are reviewed, and the application of the parallel analysis criterion is illustrated with three examples. It is shown that the results of various approaches do not always agree. Investigators are encouraged to employ the parallel analysis criterion, along with one or more other criteria, in deciding on the number of principal components.

Analysis of Variance↗
PubMed2000

Phenotypic covariance structure in tamarins (genus Saguinus): a comparison of variation patterns using matrix correlation and common principal component analysis.

Constancy of variation/covariation structure among populations is frequently assumed in order to measure the differential selective forces which have caused population differentiation through evolutionary time. Following Steppan ([1997] Evolution 51:571-594), this assumption is examined among closely related tamarin species (genus Saguinus), using two distinct approaches applied to the task of evaluating similarity in patterns of morphological variation: common principal component analysis and matrix correlations. While the results of these analyses may appear contradictory, closer examination reveals them as complementary, highlighting the wisdom of combined methodologies. Overall, the results reveal a close relationship among the morphologically based variance structures of the tamarin species a relationship whose pattern is consistent with the pattern of phylogenetic relatedness as found via a molecular genetic study. More specifically, both methodological approaches provide some support for divergence of S. geoffroyi and S. oedipus (with regards to their patterns of morphological variation) from other tamarin species. This suggests that variance/covariance structure may have diverged through evolutionary time in the tamarin lineage, placing assumptions of constancy in doubt.

Analysis of Variance↗
PubMed1984

Echocardiographic evaluation of responses to left ventricular volume loading by principal components and nomographic analysis.

Changes in performance of left ventricles (LV) with volume overloads are difficult to determine by conventional clinical methods. This information, however, is important for the proper timing of therapeutic interventions to preserve LV function. Seven size-adjusted (by regression with end-diastolic diameter, EDD) LV performance parameters from 100 normal echocardiograms (echos) were entered into a principal component analysis (PCA). Two factors (linear combination of the 7 parameters) were obtained from the analysis. Prediction limits (95%) about these two factors used in combination, correctly classified 92% of the normal echos. More detailed analysis of the two PCA factors revealed that the majority of the variability within the factors was explained by size-adjusted parameters resultant from the EDD posterior wall (factor 1) and EDD septal excursion (factor 2) regressions, respectively. Plots of the 95% prediction limits about these two regression lines provided nomograms. These nomograms used in combination, correctly classified 95% of the normal echos. When the performance parameters of 64 volume loaded ventricles were evaluated by PCA, four groups were identified. Ten ventricles (16%) were hypokinetic, 29 (45%) were hyperkinetic, 23 (36%) were nomokinetic, and 2 (3%) could not be classified. These classifications were supported by significant between group differences of shortening fraction, velocity of circumferential shortening, and velocity of circumferential expansion. Nomographic classification of the same volume loaded hearts was in excellent (94%) agreement with PCA classification. Nomographic analysis (derived from the PCA) is offered as a less complex, more clinically applicable echo method for evaluating LV performance of volume loaded hearts.

Adolescent↗