Color perception and the limits of color constancy

Summary A summary of colorimetry is given and the limits of color constancy mechanism under changing illuminations are discussed.     

On the analysis of the cat's pattern recognition system

The objective of the paper is to determine in abstract terms the algorithms used by the cat detecting simple patterns and to quantify the contributions of the visual areas 17, 18, 19 for this task. The data incorporated in the algorithm are collected from behavioral experiments where the animals had to distinguish between two patterns. The patterns were superimposed with gaussian noise and the detection probability was measured. The resulting model describes pattern recognition in two steps: first extraction of features and second classification. The test of the validity of the model system was to predict the outcome of similar experiments but with different patterns. With the help of the model it is possible to describe the effect of a lesion in parametric form. This in turn gives some hints about the functions of the visual areas 17, 18, 19 for the specific fask, tested in the experiments.     

On environmental variability and limits to similarity

Different model approaches to the problem of environmental variability and limits to similarity are reviewed. It is shown that the assumption of a strictly flat resource spectrum leads to singular results. Hence, the result of May & MacArthur that a qualitative difference exists between a constant and a weakly varying environment is not generally valid. For small variations in the environment, several of the models reduce to a common form and the limits to similarity depend only weakly upon the magnitude of the environmental fluctuations.     

Training improves acoustic pattern perception

Pitch changes that occur in speech and melodies can be described in terms of contour patterns of rises and falls in pitch and the actual pitches at each point in time. This study investigates whether training can improve the perception of these different features. One group of ten adults trained on a pitch-contour discrimination task, a second group trained on an actual-pitch discrimination task, and a third group trained on a contour comparison task between pitch sequences and their visual analogs. A fourth group did not undergo training. It was found that training on pitch sequence comparison tasks gave rise to improvements in pitch-contour perception. This occurred irrespective of whether the training task required the discrimination of contour patterns or the actual pitch details. In contrast, none of the training tasks were found to improve the perception of the actual pitches in a sequence. The results support psychological models of pitch processing where contour processing is an initial step before actual pitch details are analyzed. Further studies are required to determine whether pitch-contour training is effective in improving speech and melody perception.     

Stiff polymer adsorption. Onset to pattern recognition

We present the results of extensive off-lattice Monte-Carlo simulations of a stiff polymer chain adsorbing onto a sticky periodic stripe-like pattern of variable width. We have analyzed, in terms of the chain length and rigidity, the adsorption and the pattern recognition process as a function of the stripe width. We have seen that this process is twofold: (i) the chain adsorbs rather isotropically onto the surface at a characteristic temperature T(c) and (ii) a further reduction in the temperature is needed for the chain to reorganize and adjust to the specific pattern. Such polymer reorganization has been studied through the evaluation of the chain degree of stretching and asphericity. We have found an optimal stripe width that maximizes the stretching. We have introduced a criteria to estimate the characteristic temperature at which the pattern recognition takes place T(r)相似文献   

A pattern recognition machine

Summary A new probabilistic learning machine for pattern recognition is described. The machine operates on the basis of random criteria obtained from special pseudorandom generators. The input, particularly versatile due to the use of an image dissector, allows a random scan for which normal television storage pick-up tubes are not suitable. The computation data section, completely automatic, uses two ferrite core memories with a capacity of 64,000 bits. Consequently it is possible to obtain very quick recognizing cycles for a maximum of 16 classes of 256 learning examples each. Preliminary experiments are reported, some of which, like the recognition of meteorological events by the analysis of absolute baric topography maps, could already be suitable for practical application of the machine.This work was supported by Consiglio Nazionale delle Ricerche (C.N.R.) through the Gruppo Nazionale Cibernetica (G.N.C.).     

A theory of ambiguous pattern perception

A theory of ambiguous pattern perception is formulated. This theory proposes a feature selector (field of attention) based on the time-sequential discrete property of the attention, a short-term memory for storage of the selected features, and a displayer (perception) to display the consecutively stored features. Since the selected features continuously enter, and since the features can only be stored in the short-term memory for a short period, the features which can be displayed in the displayer vary with time. When all the essential features belonging to one pattern happen to be in the displayer, the picture is perceived to be that pattern; when all the essential features belonging to another pattern happen to be in the displayer, then the picture is perceived to be the other pattern. Thus the picture appears to vary with time and alternate between two patterns. A numerical calculation is presented.     

Application of pattern recognition to monitoring fermentations ofBacillus amyloliquefaciens

Summary Pattern recognition techniques were applied to analytical data to distinguish abnormal from normal microbial fermentations usingBacillus amyloliquefaciens as a model system. Patterns of fermentation end products during growth ofB. amyloliquefaciens were obtained from HPLC analysis of broth samples. Data were also obtained from fermentations using other bacterial species, strains, and environmental conditions, and were compared with the model data set. The bacterial species cultured includedB. subtilus, B. licheniformis, andEscherichia coli. Environmental variables included acration and temperature. The chromatographic patterns were compared by using hierarchical cluster and principal component analysis to obtain a quantitative measure of their similarity and to establish the normal variability within a model data set. Statistical analysis of the data indicated that individual fermentations can be assigned to distinct clusters on the basis of their divergence from the model system. Altered environments and other species can be identified as outliers from the model set. These results show that pattern recognition analysis has direct applicability to monitoring fermentation processes.     

Visual pattern recognition in humans

We have investigated how observers learn to classify compound Gabor signals as a function of their differentiating frequency components. Performance appears to be consistent with decision processes based upon the least squares minimum distance classifier (LSMDC) operating over a cartesian feature space consisting of the real (even) and imaginary (odd) components of the signals. The LSMDC model assumes observers form prototype signals, or adaptive filters, for each signal class in the learing phase, and classify as a function of their degree of match to each prototype. The underlying matching process can be modelled in terms of cross-correlation between prototype images and the input sample.Study supported by Deutsche Forschungsgemeinschaft grants Re 337/3-3 and Po 121/13-1Deutsche Forschungsgemeinschaft Guest-Professor (Mu 93/103-1)     

Continuum limits of pattern formation in hexagonal-cell monolayers

Intercellular signalling is key in determining cell fate. In closely packed tissues such as epithelia, juxtacrine signalling is thought to be a mechanism for the generation of fine-grained spatial patterns in cell differentiation commonly observed in early development. Theoretical studies of such signalling processes have shown that negative feedback between receptor activation and ligand production is a robust mechanism for fine-grained pattern generation and that cell shape is an important factor in the resulting pattern type. It has previously been assumed that such patterns can be analysed only with discrete models since significant variation occurs over a lengthscale concomitant with an individual cell; however, considering a generic juxtacrine signalling model in square cells, in O’Dea and King (Math Biosci 231(2):172–185 2011), a systematic method for the derivation of a continuum model capturing such phenomena due to variations in a model parameter associated with signalling feedback strength was presented. Here, we extend this work to derive continuum models of the more complex fine-grained patterning in hexagonal cells, constructing individual models for the generation of patterns from the homogeneous state and for the transition between patterning modes. In addition, by considering patterning behaviour under the influence of simultaneous variation of feedback parameters, we construct a more general continuum representation, capturing the emergence of the patterning bifurcation structure. Comparison with the steady-state and dynamic behaviour of the underlying discrete system is made; in particular, we consider pattern-generating travelling waves and the competition between various stable patterning modes, through which we highlight an important deficiency in the ability of continuum representations to accommodate certain dynamics associated with discrete systems.     

Trim5 TAKes on pattern recognition

Retroviral capsids can be recognized and degraded by a host protein, Trim5α. A recent study in Nature (Pertel et al., 2011) shows that, upon sensing of the retrovirus capsid lattice, Trim5α generates free ubiquitin chains that activate the TAK1 kinase and downstream innate immune response genes.     

Fermentation database mining by pattern recognition

A large volume of data is routinely collected during the course of typical fermentation and other processes. Such data provide the required basis for process documentation and occasionally are also used for process analysis and improvement. The information density of these data is often low, and automatic condensing, analysis, and interpretation ("database mining") are highly desirable. In this article we present a methodology whereby process variables are processed to create a database of derivative process quantities representative of the global patterns, intermediate trends, and local characteristics of the process. A powerful search algorithm subsequently attempts to extract the specific process variables and their particular attributes that uniquely characterize a class of process outcomes such as high- or low-yield fermentations.The basic components of our pattern recognition methodology are described along with applications to the analysis of two sets of data from industrial fermentations. Results indicate that truly discriminating variables do exist in typical fermentation data and they can be useful in identifying the causes or symptoms of different process outcomes. The methodology has been implemented in a user-friendly software, named db-miner, which facilitates the application of the methodology for efficient and speedy analysis of fermentation process data. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 53: 443-452, 1997.     

Antiviral signaling through pattern recognition receptors

Viral infection is detected by the host innate immune system. Innate immune cells such as dendritic cells and macrophages detect nucleic acids derived from viruses through pattern recognition receptors (PRRs). Viral recognition by PRRs initiates the activation of signaling pathways that lead to production of type I interferon and inflammatory cytokines, which are important for the elimination of viruses. Two types of PRRs that recognize viral nucleic acids, Toll-like receptors (TLR) and RIG-I-like RNA helicases (RLH), have been identified. Of the TLRs, TLR3 recognizes viral double-stranded (ds) RNA, TLR7 and human TLR8 identify viral single-stranded (ss) RNA and TLR9 detects viral DNA. TLRs are located in endosomal compartments, whereas RLH are present in the cytoplasm where they detect viral dsRNA or ssRNA. Here we review the role of TLRs and RLHs in the antiviral innate immune response.     

Cerebellar LTD and pattern recognition by Purkinje cells

Many theories of cerebellar function assume that long-term depression (LTD) of parallel fiber (PF) synapses enables Purkinje cells to learn to recognize PF activity patterns. We have studied the LTD-based recognition of PF patterns in a biophysically realistic Purkinje-cell model. With simple-spike firing as observed in vivo, the presentation of a pattern resulted in a burst of spikes followed by a pause. Surprisingly, the best criterion to distinguish learned patterns was the duration of this pause. Moreover, our simulations predicted that learned patterns elicited shorter pauses, thus increasing Purkinje-cell output. We tested this prediction in Purkinje-cell recordings both in vitro and in vivo. In vitro, we found a shortening of pauses when decreasing the number of active PFs or after inducing LTD. In vivo, we observed longer pauses in LTD-deficient mice. Our results suggest a novel form of neural coding in the cerebellar cortex.     

Transformation and relational-structure schemes for visual pattern recognition

Two models for visual pattern recognition are described; the one based on application of internal compensatory transformations to pattern representations, the other based on encoding of patterns in terms of local features and spatial relations between these local features. These transformation and relational-structure models are each endowed with the same experimentally observed invariance properties, which include independence to pattern translation and pattern jitter, and, depending on the particular versions of the models, independence to pattern reflection and inversion (180° rotation). Each model is tested by comparing the predicted recognition performance with experimentally determined recognition performance using as stimuli random-dot patterns that were variously rotated in the plane. The level of visual recognition of such patterns is known to depend strongly on rotation angle. It is shown that the relational-structure model equipped with an invariance to pattern inversion gives responses which are in close agreement with the experimental data over all pattern rotation angles. In contrast, the transformation model equipped with the same invariances gives poor agreement to the experimental data. Some implications of these results are considered.     

C- and Adelta-fibre mediated thermal perception: response to rate of temperature change using method of limits

Studies investigating the effect of rate of temperature change on thermal thresholds have used a variety of different methods and threshold combinations, and many display incomplete reporting of statistical analyses. It has been suggested that C- and Adelta-fibre mediated thresholds differ in their reaction to different rates of temperature change. Ten healthy female volunteers (aged 18-26 years; mean 21 +/- S.D. 2.53) undertook cold sensation (CS), warm sensation (WS), cold pain (CP) and heat pain (HP) threshold determinations on the thenar eminence of the dominant hand. Rates of temperature change of 0.5, 1, 2.5 and 4 degrees C/s were used, with a modified method of limits. Adaptation temperature was 32 degrees C and thermode size 3 cm x 3 cm. Results showed a significant increase in WS, HP and CP thresholds with increased rates of temperature change (all p < 0.001), but no significant change for CS (p = 0.653). These results suggest that thresholds with a C-fibre component (WS, HP and CP) and those that are Adelta-fibre mediated (CS) behave differently. A traditional explanation of measurement artefact alone is insufficient in rationalizing these results, with additional factors potentially involved. Slow rates of temperature change were shown to reduce mean intra-individual differences in recorded threshold values, and also to abolish ceiling effects with HP threshold determinations. Clinically, therefore, using slow rates of temperature change with method of limits has a range of benefits over and above simply minimizing measurement artefact.