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PubMed1993

Information encoding and the responses of single neurons in the primate temporal visual cortex.

1. The possibility of temporal encoding in the spike trains of single neurons recorded in the temporal lobe visual cortical areas of rhesus macaques was analyzed with the use of principal component and information theory analyses of smoothed spike trains. The neurons analyzed had responses selective for faces. 2. Provided that a correction was applied to earlier methods of principal component analysis used for neuronal spike trains, it was shown that the first principal component provides by a great extent the most information, with the second and third adding only small proportions (on average 18.8 and 8.4%, respectively). 3. It was shown that the magnitude of the second and higher principal components is even smaller if the spike train analysis is started after the onset of the neuronal response, instead of before the neuronal response has started. This suggests that variations in response latency are at least a part of what is reflected by the second and higher principal components. 4. The first principal component was correlated with the mean firing rate of the neurons. The second and higher principal components reflected at least partly the onset properties of the neuronal responses, such as response latency differences between the stimuli. 5. A considerable proportion of the information available from principal components 1-3 is available in the firing rate of the neuron. 6. Periods of the firing rate of as little as 50 or even 20 ms are sufficient to give a reasonable estimate of the firing rate of the neuron. 7. Information theory analysis showed that in short epochs (e.g., 50 ms) the information available from the firing rate can be as high, on average, as 84.4% of that available from the firing rate calculated over 400 ms, and 52.0% of that available from principal components 1-3 in the 400-ms period. It was also found that 44.0% of the information calculated from the first three principal components is available in the firing rates calculated over epochs as short as 20 ms. 8. More information was available near the start of the neuronal response, and the information available from short epochs became less later in the neuronal response. 9. Taken together, these analyses provide evidence that a short period of firing taken close to the start of the neuronal response provides a reasonable proportion of the total information that would be available if a long period of neuronal firing (e.g., 400 ms) were utilized to extract it, even if temporal encoding were used.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗
PubMed1994

Translation invariance in the responses to faces of single neurons in the temporal visual cortical areas of the alert macaque.

1. The responses of single neurons in the inferior temporal cortex and the cortex in the banks of the anterior part of the superior temporal sulcus of three awake, behaving macaques were recorded during a visual fixation task. Stimulus images subtending 17 or 8.5 degrees were presented in the center of the display area, and fixation was either at the center of the display area, or at one of four positions that were on the stimulus, or several degrees off the edge of the test stimulus. The experiments were performed with face-selective cells, and the responses were compared for fixation at each position for both effective and noneffective face stimuli for each cell. 2. The firing rates of most neurons to an effective image did not significantly alter when visual fixation was as far eccentric as the edge of the face, and they showed only a small reduction when the fixation point was up to 4 degrees from the edge of the face. Moreover, stimulus selectivity across faces was maintained throughout this region of the visual field. 3. The centers of the receptive fields of the cells, as shown by the calculated "centers of gravity," were close to the fovea, with almost all being within 3 degrees of the fovea. 4. The receptive fields of the cells typically crossed the vertical midline for at least 5 degrees. 5. Information theory procedures were used to analyze the spike trains of the visual neurons. Nearly six times more information was carried by these neurons' firing rate about the identity of an image than about its position in the visual field. Thus the information theory analysis showed that the responses of these neurons reflected information about which stimulus had been seen in a relatively translation invariant way. 6. Principal component analysis showed that principal component 1 (PC1) is related primarily to firing rate and reflected information primarily about stimulus identity. (For identity PC2 added only 14% more information to that contained in PC1.) Principal component 2 (PC2) was more closely related to neuronal response latencies, which increased with increasing eccentricity of the image in the visual field. PC2 reflected information about the position of the stimulus in the visual field, in that PC2 added 109% more information to that contained in PC1 about the position of the stimulus in the visual field.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗
PubMed1996

Patterns of positive and negative symptoms in first episode schizophrenia.

BACKGROUND: The aim is to examine, in first episodes of schizophrenia, the appropriateness of the simple two-dimensional model of schizophrenia ('negative' and 'positive' dimensions) and more complex variants. METHOD: All patients with a first episode of schizophrenia who, over a two-year period, made contact with any of the public mental health services of the autonomous region of Cantabria in northern Spain were investigated. The psychiatric evaluation included, among other instruments, the Present State Examination (PSE-9), and the scales for the assessment of the 'positive' and 'negative' symptoms of schizophrenia (SAPS and SANS respectively). The dimensionality of the SAPS/SANS item scores and sub-scales was examined throughout the use of principal component analysis. RESULTS: The principal component solution that best fits the data obtained with the initial SANS/SAPS sub-scales reflects the existence of three different ('negative', 'positive', 'disorganisation') factors. The strategy adopted of repeating the analysis after extracting the principal components of the original sub-scales, revealed that although the nature and item composition of the initial 'negative' and 'disorganisation' factors were in general confirmed, the 'positive' dimension presented a more complex structure with at least two 'positive' ('Non-Paranoid' and 'Paranoid') independent factors. CONCLUSION: The psychopathological structure of the early stages of schizophrenia, as evaluated by the SANS/SAPS, is characterised by the presence of four dimensions: two 'positive', one 'negative' and one 'disorganisation'.

Adolescent↗
PubMed2003

Relationships among rheological and sensorial properties of young cheeses.

This study investigated the sensory and rheological properties of young cheeses in order to better understand perceived cheese texture. Mozzarella and Monterey Jacks were tested at 4, 10, 17, and 38 d of age; process cheese was tested at 4 d. Rheological methods were used to determine the linear and nonlinear viscoelastic and fracture properties. A trained sensory panel developed a descriptive language and reference scales to evaluate cheese texture. All methods differentiated the cheeses by variety. Principal component analysis of sensory texture revealed that three principal components explained 96.1% of the total variation in the cheeses. The perception of firmness decreased as the cheeses aged, whereas the perception of springiness increased. Principal component analysis of the rheological parameters (three principal components: 87.9% of the variance) showed that the cheeses' solid-like response (storage modulus and fracture modulus) decreased during aging, while phase angle, maximum compliance, and retardation time increased. Analysis of the instrumental and sensory parameters (three principal components: 82.1% of the variance) revealed groupings of parameters according to cheese rigidity, resiliency, and chewdown texture. Rheological properties were highly associated with rigidity and resiliency, but less so with chewdown texture.

Cheese↗
PubMed2005

Protection of originality of Tokaji Aszú: amines and organic acids in botrytized wines by high-performance liquid chromatography.

Amine and organic acid composition of Aszú wines from the Tokaj region of Hungary, nonbotrytized Hungarian wines from different regions, and foreign botrytized wines were analyzed by high-performance liquid chromatography. Hungarian and foreign wines (36 Hungarian and seven foreign botrytized wines) were compared in different ways by calculation of ratios of given amine compounds, analyses of variance, principal component, and discriminant analysis. In wines, putrescine and in some samples 3-methyl-butylamine and/or phenyl ethylamine were found in remarkable concentrations, while in botrytized wines four other amines were verified in high concentration. Good separation between Aszú and foreign botrytized wines was found by calculation of the amine component's ratio. The first two principal components of the principal component analysis accounted for 77 and 84% of the total variance in the data of amines and acids, respectively. The component scores of samples grouped according to Aszú, foreign botrytized, and nonbotrytized wines. Linear discriminant analysis was used for differentiation of Aszú, foreign botrytized, and normal wines. Using nine amines and two acids as variables, the correct classification was 97.6%. On the basis of results, an objective evaluation method can be elaborated for quality control in order to protect the authenticity and origin of wine specialties made from botrytized grapes.

Acids↗
PubMed2006

Correlation and prediction of trunk fat mass with four anthropometric indices in Chinese males.

To increase our understanding of the relationships of trunk fat mass (FMtrunk) and four anthropometric indices in Chinese males, 1090 males aged 20-40 years were randomly recruited from the city of Changsha, China. Waist circumference (WC) and hip circumference (HC) were measured using standardized equipment, and three other anthropometric indices of BMI, waist:hip ratio (WHR) and conicity index (CoI) were calculated using weight, height, HC and WC. FMtrunk (in kg) was measured using a Hologic QDR 4500 W dual-energy X-ray absorptiometry scanner. There was an increasing trend of FMtrunk, %FMtrunk (percentage of FMtrunk) and BMI, WC, WHR, CoI in successively older age groups (e.g. the mean FMtrunk values were 4.63 (SD 2.58), 5.39 (SD 2.74), 5.93 (SD 2.82), 6.57 (SD 2.94) in four 5-year age groups, respectively). FMtrunk and %FMtrunk were significantly correlated with four anthropometric indices with the Pearson's correlation coefficients ranging from 0.25 to 0.86. Principal component analysis was performed to form three principal components that interpreted over 99.5% of the total variation of four related anthropometric indices in all age groups, with over 65% of the total variation accounted by principal component 1. Multiple regression analyses showed that three principal components explained a greater variance (R(2) 70.0-80.1%) in FMtrunk than did BMI or WC alone (R(2) 57.8-74.1%). The present results suggest that there is an increasing trend of FMtrunk and four anthropometric indices in successively older age groups; that age has important effects on the relationships of FMtrunk and studied anthropometric indices; and that the accuracy of predicting FMtrunk using four anthropometric indices is higher than using BMI or WC alone.

Adipose Tissue↗
PubMed2001

Unified stabilization approach to principal and minor components extraction algorithms.

Principal component and minor component extractions provide powerful techniques in many information processing fields. There have been proposed a number of algorithms for principal and minor component (or subspace) extraction, which have different dynamical behaviors. In this paper, we give rigorous stability analysis of these algorithms, obtaining a unified insight view on the dynamical behaviors of various algorithms.

Algorithms↗
PubMed1999

Statistical analysis of array expression data as applied to the problem of tamoxifen resistance.

BACKGROUND: Although the emerging complementary DNA (cDNA) array technology holds great promise to discern complex patterns of gene expression, its novelty means that there are no well-established standards to guide analysis and interpretation of the data that it produces. We have used preliminary data generated with the CLONTECH Atlas human cDNA array to develop a practical approach to the statistical analysis of these data by studying changes in gene expression during the development of acquired tamoxifen resistance in breast cancer. METHODS: For hybridization to the array, we prepared RNA from MCF-7 human breast cell tumors, isolated from our athymic nude mouse xenograft model of acquired tamoxifen resistance during estrogen-stimulated, tamoxifen-sensitive, and tamoxifen-resistant growth. Principal components analysis was used to identify genes with altered expression. RESULTS AND CONCLUSIONS: Principal components analysis yielded three principal components that are interpreted as 1) the average level of gene expression, 2) the difference between estrogen-stimulated gene expression and the average of tamoxifen-sensitive and tamoxifen-resistant gene expression, and 3) the difference between tamoxifen-sensitive and tamoxifen-resistant gene expression. A bivariate (second and third principal components) 99% prediction region was used to identify outlier genes that exhibit altered expression. Two representative outlier genes, erk-2 and HSF-1 (heat shock transcription factor-1), were chosen for confirmatory study, and their predicted relative expression levels were confirmed in western blot analysis, suggesting that semiquantitative estimates are possible with array technology. IMPLICATIONS: Principal components analysis provides a useful and practical method to analyze gene expression data from a cDNA array. The method can identify broad patterns of expression alteration and, based on a small simulation study, will likely provide reasonable power to detect moderate-sized alterations in clinically relevant genes.

Animals↗
PubMed1990

Puff-by-puff sensory evaluation of a low to middle tar medium nicotine cigarette designed to maintain nicotine delivery to the smoker.

Puff-by-puff assessments of a range of sensory and subjective attributes were made for three cigarettes, with tar and nicotine yields of: 10.0 and 1.4; 17.0 and 1.7; and 8.8 and 0.8 mg/cigarette, respectively. Seven attributes were assessed: mouth impact, throat impact, chest effect, roughness, intensity of flavour, satisfaction and quality of flavour. Significant differences between the three cigarettes were obtained for most of these attributes. Principal component analysis of the data revealed three principal components related to the cigarettes under investigation. Components 1 and 2 accounted for approximately 47 and 28% of the total variance and component 3 only added a further 7%. Principal component 1 was a complex combination of intensity-related characteristics, i.e. mouth and throat impact, chest effect, intensity of flavour, roughness, while quality of flavour and satisfaction contributed to the separation of samples on principal component 2. However, the two major components could not be defined simply in terms of the yields of tar and nicotine for the products determined on a smoking machine.

Adult↗
PubMed2005

Differentiating lifting technique between those who develop low back pain and those who do not.

BACKGROUND: No research to date has been able to discriminate differences in lifting technique for healthy individuals who eventually develop low back pain compared to those that do not while employed in a manual materials handling industry. The purpose of this study was to demonstrate the ability of principal component analysis to identify differences in lifting technique. METHODS: Principal component analysis was applied to sixteen kinematic and kinetic waveforms describing the two-dimensional motion of the trunk and load. The principal component scores for each variable were used as the dependent measures in a one-way ANOVA to determine group differences. FINDINGS: Significant group differences (P<0.05) were found for five of the principal component scores capturing associated kinematic waveform patterns related to the control and placement of the box on the shelf, and associated kinetic waveform patterns related to the relative timing of extension moment generation in the sacral and thoracic regions. A related waveform pattern for trunk compression was also found. INTERPRETATION: Due to the coordinated movements involved in tasks such as lifting, differences among clinical populations have been difficult to demonstrate empirically. We were able to identify different characteristics in lifting kinematics and kinetics prior to the development of low back pain. Principal component analysis was able to identify important biomechanical differences where traditional analyses failed. This is the first study to identify such lifting differences prior to the development of low back pain.

Diagnosis, Computer-Assisted↗
PubMed1989

ERP study of the development of the holistic and analytic modes of processing between 6 and 8 years.

Event-related potentials (ERPs) were recorded (01, 02, Fcz, Cpz leads) from 32 normal children aged from 6 to 8 years during a categorisation task performed with 4 types of stimuli that allowed for a holistic and/or an analytic development to modify information processing according to the child's age. Whatever age, derivation or stimulus, the individual ERPs showed a large negative N2 wave (mean latency: 230 ms) made up of two widely overlapping components. In order to separate these components, an initial principal component analysis (PCA) was performed on the waveforms; this PCA provided a principal component that accounted for the amplitude difference between the first negative peak of the N2 wave (180 ms after stimulus onset) and the subsequent slope change. A second PCA was then carried out on the corresponding individual component scores; this second PCA provided two factors according to whether the stimuli were holistically or analytically processed. Regarding the pre- and post-vertex data (Fcz and Cpz), these two factors accounted for the same ERP effect for the 6-year-old children but opposite effects after the age of seven. We interpreted this change as reflecting the differentiation of specific - holistic and analytic - modes of processing from a non-specific mode after the establishment of the concrete operation period.

Brain↗
PubMed2000

Physiological and anthropometric determinants of sport climbing performance.

OBJECTIVE: To identify the physiological and anthropometric determinants of sport climbing performance. METHODS: Forty four climbers (24 men, 20 women) of various skill levels (self reported rating 5.6-5.13c on the Yosemite decimal scale) and years of experience (0.10-44 years) served as subjects. They climbed two routes on separate days to assess climbing performance. The routes (11 and 30 m in distance) were set on two artificial climbing walls and were designed to become progressively more difficult from start to finish. Performance was scored according to the system used in sport climbing competitions where each successive handhold increases by one in point value. Results from each route were combined for a total climbing performance score. Measured variables for each subject included anthropometric (height, weight, leg length, arm span, % body fat), demographic (self reported climbing rating, years of climbing experience, weekly hours of training), and physiological (knee and shoulder extension, knee flexion, grip, and finger pincer strength, bent arm hang, grip endurance, hip and shoulder flexibility, and upper and lower body anaerobic power). These variables were combined into components using a principal components analysis procedure. These components were then used in a simultaneous multiple regression procedure to determine which components best explain the variance in sport rock climbing performance. RESULTS: The principal components analysis procedure extracted three components. These were labelled training, anthropometric, and flexibility on the basis of the measured variables that were the most influential in forming each component. The results of the multiple regression procedure indicated that the training component uniquely explained 58.9% of the total variance in climbing performance. The anthropometric and flexibility components explained 0.3% and 1.8% of the total variance in climbing performance respectively. CONCLUSIONS: The variance in climbing performance can be explained by a component consisting of trainable variables. More importantly, the findings do not support the belief that a climber must necessarily possess specific anthropometric characteristics to excel in sport rock climbing.

Adult↗
PubMed2003

Statistics of trinucleotides in coding sequences and evolution.

The aim of this paper is to give measurements indicative of evolutional stages of the species. Two types of statistics of trinucleotides in coding regions are analysed for 27 species. The first one is the codon space, the nucleotide ratio for each of the three codon positions. We apply principal component analysis on this space and extract two principal components faithfully describing the original distribution of the codon space. The first principal component corresponds to the GC content. The second principal component classifies the species into three evolutional groups, Archaea, Bacteria and Eukaryota. The second statistics is the real and theoretical frequency of amino acids. The real frequency of an amino acid in a coding sequence is its frequency in the translated protein. The theoretical frequency is the expected frequency calculated from the ratio of nucleotides. We introduce the discrepancy between these two frequencies as an index of non-randomness of nucleotides in the sequence. This index of non-randomness divides the species into two groups: eukaryotes having smaller non-randomness (i.e. being more random) and prokaryotes having higher non-randomness.

Animals↗
PubMed2004

Morphometrics for cephalometric diagnosis.

This article demonstrates morphometric methods by applying them to an orthodontic sample. A total of 150 pretreatment cephalograms of consecutive patients (84 female, 66 male) were traced and digitized. Fifteen points were used for the analysis. The tracings were superimposed by the Procrustes method, and shape variability was assessed by principal component analysis. Approximately 70% of the total sample variability was incorporated in the first 5 principal components. The most significant principal component, accounting for 29% of shape variability, was the divergence of skeletal pattern; the second principal component, accounting for 20% of shape variability, was the anteroposterior maxillary relationship. It is recommended that Procrustes superimposition and principal component analysis be incorporated into routine cephalometric analysis for more valid and comprehensive shape assessment.

Cephalometry↗
PubMed2004

Machine learning based pattern recognition applied to microarray data.

MOTIVATION: Microarrays have allowed the expression level of thousands of genes or proteins to be measured simultaneously. Data sets generated by these arrays consist of a small number of observations (e.g., 20-100 samples) on a very large number of variables (e.g., 10,000 genes or proteins). The observations in these data sets often have other attributes associated with them such as a class label denoting the pathology of the subject. Finding the genes or proteins that are correlated to these attributes is often a difficult task since most of the variables do not contain information about the pathology and as such can mask the identity of the relevant features. We describe a genetic algorithm (GA) that employs both supervised and unsupervised learning to mine gene expression and proteomic data. The pattern recognition GA selects features that increase clustering, while simultaneously searching for features that optimize the separation of the classes in a plot of the two or three largest principal components of the data. Because the largest principal components capture the bulk of the variance in the data, the features chosen by the GA contain information primarily about differences between classes in the data set. The principal component analysis routine embedded in the fitness function of the GA acts as an information filter, significantly reducing the size of the search space since it restricts the search to feature sets whose principal component plots show clustering on the basis of class. The algorithm integrates aspects of artificial intelligence and evolutionary computations to yield a smart one pass procedure for feature selection, clustering, classification, and prediction.

Algorithms↗
PubMed2002

Do schizophrenic patients who managed to get to university have a non-developmental form of illness?

BACKGROUND: Many people who develop schizophrenia have impairments in intellectual and social functioning that are detectable from early childhood. However, some patients do not exhibit such deficits, and this suggests that they may have suffered less neurodevelopmental damage. We hypothesized that the aetiology and form of schizophrenia may differ in such patients. We therefore studied a group of schizophrenic patients who were functioning well enough to enter university prior to illness onset. METHODS: The casenotes of 46 university-educated patients and 48 non-university-educated patients were rated on several schedules including the OPCRIT checklist, and the two groups were compared using univariate statistical techniques. Principal components analysis was then performed using data from all patients, and the factor scores for each principal component were compared between groups. RESULTS: Univariate analyses showed the university-educated patients had an excess of depressive symptoms, and a paucity of core schizophrenic symptoms. Four principal components emerged in the principal components analysis: mania, biological depression, schizophrenic symptoms, and a reactive depression. University-educated patients scored significantly higher on the reactive depression principal component, and lower on the schizophrenic symptoms principal component, than the non-university-educated patients.

Adjustment Disorders↗
PubMed1996

Linear dimension reduction of sequences of medical images: III. Factor analysis in signal space.

A method is presented for improving the precision of factor analysis by utilizing physiological information. The first step is an optimal linear dimension reduction, whereby the data are projected onto a low-dimensional signal space. Then principal component analysis is performed in the signal space rather than in the entire data space. This improves the precision of the principal components. Unlike ordinary principal component analysis, the present method is not degraded when the time intervals are subdivided, provided that the signal space is correct. Alternatively, but with identical results, the covariance matrix can be calculated from the whole data space. The covariance matrix is then transformed and principal component analysis is performed in either a low-rank matrix or a low-dimensional submatrix instead of in the whole covariance matrix. Factor analysis using the intersection method with a theory space may be improved by employing the present method. In simulations based on a [11C]flumazenil study with 27 frames, the proposed method required only 58 per cent of the radioactivity to produce the same precision as the intersection method and only 27 per cent when compared to ordinary principal component analysis.

Biophysical Phenomena↗
PubMed2005

Identification of Africanized honeybees.

Gas chromatography and pattern recognition methods were used to develop a potential method for differentiating European honeybees from Africanized honeybees. The test data consisted of 237 gas chromatograms of hydrocarbon extracts obtained from the wax glands, cuticle, and exocrine glands of European and Africanized honeybees. Each gas chromatogram contained 65 peaks corresponding to a set of standardized retention time windows. A genetic algorithm (GA) for pattern recognition was used to identify features in the gas chromatograms characteristic of the genotype. The pattern recognition GA searched for features in the chromatograms that optimized the separation of the European and Africanized honeybees in a plot of the two or three largest principal components of the data. Because the largest principal components capture the bulk of the variance in the data, the peaks identified by the pattern recognition GA primarily contained information about differences between gas chromatograms of European and Africanized honeybees. The principal component analysis routine embedded in the fitness function of the pattern recognition GA acted as an information filter, significantly reducing the size of the search space since it restricted the search to feature sets whose principal component plots showed clustering on the basis of the bees' genotype. In addition, the algorithm focused on those classes and/or samples that were difficult to classify as it trained using a form of boosting. Samples that consistently classify correctly are not as heavily weighted as samples that are difficult to classify. Over time, the algorithm learns its optimal parameters in a manner similar to a neural network. The pattern recognition GA integrates aspects of artificial intelligence and evolutionary computations to yield a "smart" one-pass procedure for feature selection and classification.

Animals↗