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PubMed1996

Non-linear algorithms for processing biological signals.

This paper illustrates different approaches to the analysis of biological signals based on non-linear methods. The performance of such approaches, despite the greater methodological and computational complexity is, in many instances, more successful compared to linear approaches, in enhancing important parameters for both physiological studies and clinical protocols. The methods introduced employ median filters for pattern recognition, adaptive segmentation, data compression, prediction and data modelling as well as multivariate estimators in data clustering through median learning vector quantizers. Another approach described uses Wiener-Volterra kernel technique to obtain a satisfactory estimation and causality test among EEG recordings. Finally, methods for the assessment of non-linear dynamic behaviour are discussed and applied to the analysis of heart rate variability signal. In this way invariant parameters are studied which describe non-linear phenomena in the modelling of the physiological systems under investigation.

Algorithms↗
PubMed2004

[Illusions: a window into perception].

Perception is the active construction of a neural state that correlates with biologically relevant elements present in the environment. This correlation, far from affording a one-to-one mapping, nonetheless guides our actions towards adaptive behaviors, thus being forged under evolutionary constraints. Since the construction of a percept is an intrinsically ambiguous process, perceptual discrepancies can arise from identical stimulation patterns. The recognition of these discrepancies is termed illusion, which originates, however, from the same physiological mechanisms that ordinarily lead to standard perception. Emanating from different sources, such as optical, sensory and cognitive factors, visual illusions are useful tools in accessing the physiological basis of perceptual processes and their interaction with motor planning and execution. Here we examine the biological roots of visual illusions and their interplay with some neurobiological, philosophical and esthetical issues.

Form Perception↗
PubMed1996

Use of adaptive Hilbert transformation for EEG segmentation and calculation of instantaneous respiration rate in neonates.

Broad, as well as narrow, band Hilbert transform filters (HTFs) were used as preprocessing units in the analysis of electroencephalogram (EEG) and respiratory movements in neonates. For these applications, new algorithms for the adaptation of the resonance frequency of a narrow-band-pass filter to the actual signal properties on the basis of an analytic filter design were developed. For the segmentation of the discontinuous EEG, the location of the resonance frequency was imbedded into the learning algorithm of a neural network (NN). In such automatic EEG pattern recognition, the detection of spike activity was taken into consideration. The spike detection scheme introduced uses broad-band HTFs as basis units. Additionally, the algorithm for the continuous control of the resonance frequency was applied to achieve the adaptation of the processing unit that performed the calculation of the instantaneous respiration rate, in this framework, a new on-line method for adaptive frequency estimation that is less sensitive to low signal-to-noise ratios (SNRs) was obtained. The new approaches introduced were tested in comparison with processing methods that have been established for the analysis of experimental and clinical data.

Algorithms↗
PubMed1995

Volatile organic compounds in the breath of patients with schizophrenia.

AIMS: To analyse the breath of patients with schizophrenia for the presence of abnormal volatile organic compounds. METHODS: A case comparison study was performed in two community hospitals in Staten Island, New York. Twenty five patients with schizophrenia, 26 patients with other psychiatric disorders, and 38 normal controls were studied. Alveolar breath samples were collected from all participants, and volatile organic compounds in the breath were assayed by gas chromatography with mass spectroscopy. Differences in the distribution of volatile organic compounds between the three groups were compared by computerised pattern recognition analysis. RESULTS: Forty eight different volatile organic compounds were observed in the breath samples. Three separate pattern recognition methods indicated an increased differentiation capability between the patients with schizophrenia and the other subjects. Pattern recognition category classification models using 11 of these volatile organic compounds identified the patients with schizophrenia with a sensitivity of 80.0% and a specificity of 61.9%. Volatile organic compounds in breath were not significantly affected by drug therapy, age, sex, smoking, diet, or race. CONCLUSIONS: Microanalysis of volatile organic compounds in breath combined with pattern recognition analysis of data may provide a new approach to the diagnosis and understanding of schizophrenia. The physiological basis of these findings is still speculative.

Breath Tests↗
PubMed1976

[The significance of the CNS for the physiology of hearing (author's transl)].

Some general aspects of auditory perception (funnelling, contrast, pattern recognition, form perception, methodological limitations) are discussed in the first part of this presentation. The modern concept of the hydrodynamics of the inner ear, including electronic modelling of the function of the basilar membrane is their dealth with. For the encoding and decoding processes of the auditory system the different grades of intensity function at the different neuronal levels is compared with that of the envelope of the basilar membranes deflection. The influence of the efferent system is discussed. In a third section of the paper some new results from our department are reported concerning the single unit activity at geniculate level recorded from the awake cat by means of a telemetric system. Neurophysiological correlates to vowel- and consonant detectors and their relations to be the phonem recognition of speech could be demonstrated. Finally, the most recent state of objective audiometry is discussed (DC-potentials, simultaneous records of electrocochleogram and cortically evoked activity, relations to EEG's power spectrum, and brains changes in vigilance) with a view of future approaches to ERA.

Animals↗
PubMed1995

Interventional physiology. Part XVI: normal coronary flow velocity patterns: considerations of artifacts, arrhythmias, and anomalies.

During normal flow velocity recording, various physiologic or technical problems may appear which can produce confusing flow signals. This section of Interventional Physiology reviews the patterns of normal coronary flow velocity and examines several artifacts and other features encountered in clinical practice. Recognition of these variations will help the interventional cardiologist to differentiate between physiologic and pathologic events.

Arrhythmias, Cardiac↗
PubMed1980

A template matching model for pattern recognition: self-organization of templates and template matching by a disinhibitory neural network.

A template matching model for pattern recognition is proposed. By following a previously-proposed algorithm for synpatic modification (Hirai, 1980), the template of a stimulus pattern is self-organized as a spatial distribution pattern of matured synapses on the cells receiving modifiable synapses. Template matching is perfomed by the disinhibitory neural network cascaded beyond the neural layer composed of the cells receiving the modifiable synapses. The performance of the model has been simulated on a digital computer. After repetitive presentations of a stimulus pattern, a cell receiving the modifiable synapses comes to have the template of that pattern. And the cell in the latter layer of the disinhibitory neural network that receives the disinhibitory input from that cell becomes selectively sensitive to that pattern. Learning patterns are not restricted by previously learned ones. They can be subset or superset patterns of the ones previously learned. If an unknown pattern is presented to the model, no cell beyond the disinhibitory neural network will respond. However, if previously learned patterns are embedded in that pattern, the cells which have the templates of those patterns respond and are assumed to transmit the information to higher center. The computer simulation also show that the model can organize a clean template under a noisy environment.

Animals↗
PubMed1989

An investigation of trained neural networks from a neurophysiological perspective.

The application of theoretical neural networks to preprocessed images was investigated with the aim of developing a computational recognition system. The neural networks were trained by means of a back-propagation algorithm, to respond selectively to computer-generated bars and edges. The receptive fields of the trained networks were then mapped, in terms of both their synaptic weights and their responses to spot stimuli. There was a direct relationship between the pattern of weights on the inputs to the hidden units (the units in the intermediate layer between the input and the output units), and their receptive field as mapped by spot stimuli. This relationship was not sustained at the level of the output units in that their spot-mapped responses failed to correspond either with the weights of the connections from the hidden units to the output units, or with a qualitative analysis of the networks. Part of this discrepancy may be ascribed to the output function used in the back-propagation algorithm.

Algorithms↗
PubMed2006

Hierarchy and adaptivity in segmenting visual scenes.

Finding salient, coherent regions in images is the basis for many visual tasks, and is especially important for object recognition. Human observers perform this task with ease, relying on a system in which hierarchical processing seems to have a critical role. Despite many attempts, computerized algorithms have so far not demonstrated robust segmentation capabilities under general viewing conditions. Here we describe a new, highly efficient approach that determines all salient regions of an image and builds them into a hierarchical structure. Our algorithm, segmentation by weighted aggregation, is derived from algebraic multigrid solvers for physical systems, and consists of fine-to-coarse pixel aggregation. Aggregates of various sizes, which may or may not overlap, are revealed as salient, without predetermining their number or scale. Results using this algorithm are markedly more accurate and significantly faster (linear in data size) than previous approaches.

Adaptation, Physiological↗
PubMed1987

Recognition of hierarchically encoded images by technical and biological systems.

All the contours and regions of objects can be mapped to code-trees of the Hierarchical Structure Code (HSC). Invariant features like structure classes, shape descriptions, or relations between structures and components may be easily extracted from the HSC. HSC-based pattern recognition provides a straightforward transition between the signal-space of the image and the space of its symbolic representation. Physiological data are well predicted and do not exclude an implementation of an HSC-based system within the visual cortex.

Cybernetics↗
PubMed1988

Neurophysiological properties of the retinal ganglion cell classes of the Cuban treefrog, Hyla septentrionalis.

The properties of the retinal ganglion cell classes in the cuban treefrog Hyla septentrionalis were studied qualitatively and quantitatively. In the superficial layers of the optic tectum three main classes of afferent optic nerve fibers could be distinguished, class-1*, class-3 and class-4 neurons. Hyla displays a more "classical" organization of the receptive fields in class-1* neurons and a weaker inhibitory surround and lower thresholds with respect to velocity, size and contrast than in Bufo or ranid frogs. The functions for velocity, contrast, size of stimulus, neuronal adaptation and adaptation to background luminance level were evaluated. Experiments with monochromatic light spots are mentioned. The results are compared to those of other amphibia and the diversity of the retinal ganglion cell properties in the different species is stressed as an important factor in the processing of the various ganglion cell types at the tectal level.

Action Potentials↗
PubMed1999

Otto Lowenstein: neurologic and ophthalmologic testing methods during his lifetime.

Lowenstein's work on the pupil is well known in this country and in Europe. It constituted, however, only one of many of his fields of interest. In all of them his contributions were based on experiments in which accurate, objective recording replaced mere observation with the unaided eye. The resulting traces, obtained under stable conditions and with well-defined stimuli, revealed specific normal or pathologic reaction patterns, and these, in turn, allowed recognition, quantification and localization of the underlying physiologic mechanisms or pathologic defects. During the early decades of this century Lowenstein invented and built his own instruments. And as more advanced technical means became available, he adopted these, so that his methods became more elegant and less time-consuming. This history forms an interesting parallel to the development of work done by others throughout the twentieth century.

Diagnostic Techniques, Neurological↗
PubMed2006

Neighborhood detection using mutual information for the identification of cellular automata.

Extracting the rules from spatio-temporal patterns generated by the evolution of cellular automata (CA) usually requires a priori information about the observed system, but in many applications little information will be known about the pattern. This paper introduces a new neighborhood detection algorithm which can determine the range of the neighborhood without any knowledge of the system by introducing a criterion based on mutual information (and an indication of over-estimation). A coarse-to-fine identification routine is then proposed to determine the CA rule from the observed pattern. Examples, including data from a real experiment, are employed to evaluate the new algorithm.

Algorithms↗
PubMed1985

Visual grating induction.

If a homogeneous illuminated test field is inserted within a sine-wave grating, an opposite phase grating will be perceived in the test field under a wide range of conditions. A cancellation technique was used to measure the magnitude of grating induction. The manner in which the effect depends on eye movements, inducing frequency, test-field height, inducing-field height, inducing amplitude, test-field luminance, and test-field width was determined in four experiments. Mathematical equations that describe these results are presented. It is shown that linear filters whose spatial weighting functions resemble receptive fields of the most common types of visual cell do not produce outputs with the properties of induced gratings. However, linear filters with highly elongated negative end zones and a small positive center produce opposite phase gratings in the test field, and an array of such filters of different sizes can account for several properties of induced gratings. There are other properties of the effect that are highly nonlinear. A second model, which is nonlinear and based on the properties of hypercomplex cells, is suggested that may encompass both the linear and the nonlinear properties of the effect.

Adaptation, Physiological↗
PubMed2003

The vigilance decrement reflects limitations in effortful attention, not mindlessness.

Robertson, Manly, Andrade, Baddeley, and Yiend (1997) proposed that the decline in performance efficiency over time in vigilance tasks (the vigilance decrement) is characterized by "mindlessness" or a withdrawal of attentional effort from the monitoring assignment. We assessed that proposal using measures of perceived mental workload (NASA-TLX) and stress (Dundee Stress State Questionnaire). Two types of vigilance task were employed: a traditional version, wherein observers made button-press responses to signify detection of rarely occurring critical signals, and a modified version, developed by Robertson et al. to promote mindlessness via routinization, wherein button-press responses acknowledged frequently occurring neutral stimulus events and response withholding signified critical signal detection. The vigilance decrement was observed in both tasks, and both tasks generated equally elevated levels of workload and stress, the latter including cognitions relating to performance adequacy. Vigilance performance seems better characterized by effortful attention (mindfulness) than by mindlessness. Actual or potential applications of this research include procedures to reduce the information-processing demand imposed by vigilance tasks and the stress associated with such tasks.

Adult↗
PubMed1996

Contrast-dependent dissociation of visual recognition and detection fields.

Seeing an object 'as something' is different from simply seeing it (see Watanabe, S., 1985, Pattern Recognition: Human and Mechanical, John Wiley). This distinction between recognition and detection often goes unnoticed in physiology and clinical practice, where visual performance is characterized in terms of acuity, visual field and contrast sensitivity. The corresponding functions of stimulus detection are consistent with the neural projection properties from the retina to the striate cortex, i.e. the 'cortical magnification theory'. Yet recognition performance for characters (Strasburger, H. et al., 1994, Eur. J. Neurosci., 6, 1583-1588) and grey-level patterns (Jüttner, M. and Reutschler, I., 1996, Vision Res., 36, 1007-1022) does not fit into this scheme. Here we show that this discrepancy results in the dissociation of visual recognition and detection fields, which is dramatic at low pattern contrast. Form proper can be appreciated exclusively within the much narrower field of recognition, the window of visual intelligence. Its function is, at low contrast, probably mediated by the magnocellular pathway and at all contrasts is determined by the processing characteristics of higher stages of the ventral visual pathway.

Adult↗
PubMed1987

A model of neural network for spatiotemporal pattern recognition.

A model of neural network to recognize spatiotemporal patterns is presented. The network consists of two kinds of neural cells: P-cells and B-cells. A P-cell generates an impulse responding to more than one impulse and embodies two special functions: short term storage (STS) and heterosynaptic facilitation (HSF). A B-cell generates several impulses with high frequency as soon as it receives an impulse. In recognizing process, an impulse generated by a P-cell represents a recognition of stimulus pattern, and triggers the generation of impulses of a B-cell. Inhibitory impulses with high frequency generated by a B-cell reset the activities of all P-cells in the network. Two examples of spatiotemporal pattern recognition are presented. They are achieved by giving different values to the parameters of the network. In one example, the network recognizes both directional and non-directional patterns. The selectivities to directional and non-directional patterns are realized by only adjusting excitatory synaptic weights of P-cells. In the other example, the network recognizes time series of spatial patterns, where the lengths of the series are not necessarily the same and the transitional speeds of spatial patterns are not always the same. In both examples, the HSF signal controls the total activity of the network, which contributes to exact recognition and error recovery. In the latter example, it plays a role to trigger and execute the recognizing process. Finally, we discuss the correspondence between the model and physiological findings.

Brain↗